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MIGRANT FARM LABOR IN MICHIGAN: AN ANALYSIS OF
RECENT TRENDS IN SUPPLY AND DEMAND, AND POLICY
IMPLICATIONS

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MIGRANT FARM LABOR IN MICHIGAN: AN ANALYSIS OF RECENT TRENDS
IN SUPPLY AND DEMAND, AND POLICY IMPLICATIONS

By

Pamela Riley Miklavcic

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Doctor of Philosophy
Department of Agricultural Economics

2004

ABSTRACT

MIGRANT FARM LABOR IN MICHIGAN: AN ANALYSIS OF RECENT TRENDS
IN SUPPLY AND DEMAND, AND POLICY IMPLICATIONS

By

Pamela Riley Miklavcic

A perception exists in Michigan that the supply of migrant farm labor no longer
meets grower demand (Schmucker, 1998; Roccisano, 1998). An increasing shortage of
workers implies an inability to harvest crops on time, incurring potentially heavy
financial and quality losses for unharvested fruits and vegetables.

To understand the magnitude of the perceived problem, this study analyzes
Michigan’s migrant farm labor situation through a grower mail survey, a migrant pilot
survey, and a migrant focus group. It explores the current and perceived future supply of
(and demand for) migrant farm labor in the apple, asparagus, blueberry, and pickling
cucumber subsectors.

The primary ﬁnding is that only 25% of the grower respondents experienced a
labor shortage in 2000. Of these, only a small percentage had unharvested or late
harvested acres, indicating that the present ﬁnancial losses associated with the shortage
are still quite small. The migrant respondents stated that non-economic, management-
related changes are as likely as a rise in wages to attract additional labor to where it is
needed. The overall survey responses indicate that both types of changes may be

necessary throughout Michigan agriculture to prevent a future widespread labor shortage.

The ﬁrst recommendation of this research is an extensive survey of migrant farm
workers who seek employment in Michigan, to expand the knowledge obtained from the
migrant pilot survey and focus group and to better balance the data made available by
Michigan growers. The second recommendation is for the Michigan Agricultural
Statistics Service to implement periodic and regular surveys (every two to three years) of
growers in Michigan, with an eye to better understanding the long-term trends in grower-
migrant relationships and employment opportunities. The third recommendation is for a
pilot study to take place, to explore the possible establishment of fair wage niche markets
for one or more Michigan agricultural commodities, similar to fair trade coffee presently
sold in the United States. The fourth recommendation is the establishment of a state-
wide task force whose role would be to improve communication between growers,
migrants, and consumers--through survey work, training sessions, and newsletters made

available in both English and Spanish.

To my husband, Milan,
and
in loving memory of my father, Elmer Newell Riley,

who died during the ﬁnal editing of this dissertation

iv

ACKNOWLEDGMENTS

Many friends, family members, and colleagues have made completion of this
dissertation possible. It was a struggle in more ways than one, and their support
throughout this long process has been more valuable than they will ever know. Their
kind encouragement has made all the difference during this unintentionally long journey.

In particular, thank you to Dr. Richard Bemsten for his patience and unfailing
conﬁdence in me.

Thank you, too, to Dr. Lindon Robison, for his inspiration in tackling so many of
life’s hurdles. I truly could not have done this without his support early in the
dissertation process.

In addition, thank you to Dr. Vera Bitsch for her timely and constructive feedback
throughout the numerous drafts of this project. I have enjoyed our interactions
throughout the last few years and hope to have many collaborative opportunities in the
future.

I also could not have completed this project without the kind understanding of Dr.
Eric Crawford. He has shown much faith in me for which I am grateful.

Thank you, too, to Dr. David Schweikhardt and Dr. Steven Gold for agreeing to

serve on my committee.

Willie Wibert, Amparo Alvarado, and Juan Cruz, deserve a thousand thank yous.
Their willingness to introduce me to migrant students at Michigan State University, to
survey migrants in the ﬁeld, and to answer numerous questions about migrant life in
Michigan contributed greatly to the second half of this study. When I was despairing of
gaining access to Michigan migrants, Willie made everything right.

Thank you to Dr. Jim Oehmke for advising me on the econometric portion of this
study. His comments were helpful, forcing me to think more critically about the
modeling portion of this dissertation than I might have otherwise. What a relief to learn
that an econometrician can be so plain spoken.

Thanks, too, to Dr. Cynthia Donovan for being such a good friend throughout the
many years of this project. Balancing three small children, a husband, and a dissertation
has not always been easy. Cynthia has been the worthiest of listeners.

Other friends who have helped are Alecia McClure, Susan Baker, Julie
Kelterbom, Terry Lingo, sisters Cindy Lamed and Becky VerPlanck, Claire Capra,
Vickie and Scott Zittel, and Janet and Sam Batzli. They have been so encouraging and I
am fortunate to have them as my friends.

Additional professors and colleagues who contributed to the success of this
dissertation are Professors Don Ricks and Marcelo Siles, former graduate student Amy
Damon, Linda Beck, Marv Johansen (MDA), Joel Gorch (MDA), Craig Anderson
(MFB), Jim Breinling (MSUE), Amy Brown (MSUE), Mark Longstroth (MSUE), Larry
Borton (MSUE), Phil Schwallier (MSUE), Norm Myers (MSUE), Jerry Deer (ESA),

Beverly DeJonge (UPM), Mark Depta (MBGA), and the late Manny Gonzales (former

vi

Director, Migrant Counsel). Likewise, Dr. Jim Stapleton and Dr. Dennis Gilliland were
crucial to reviewing the statistical portion of this dissertation.

Last, thank you to my wonderful family. My parents have always cheered me on,
while my husband Milan’s quiet encouragement has taken me farther than I ever dreamed
I could go. My two middle children, Will and Marija, have ﬁlled my life with smiles,
even during the most difficult times. Claudia’s impending arrival provided the impetus to
get things wrapped up. Last but not least, my oldest child, Peter, has shown by example
how to ﬁght the good ﬁght. He has taught me that goals are best achieved by living one

day at a time-mo matter how long it takes. I am the luckiest wife and mom in the world.

vii

TABLE OF CONTENTS

PAGE

LIST OF TABLES .......................................................................................................... xvii

LIST OF FIGURES ....................................................................................................... xviii

KEY TO ABBREVIATIONS ........................................................................................ xxiii

CHAPTER 1 — INTRODUCTION ...................................................................................... l

1.1 PROBLEM STATEMENT ............................................................................................ 1

1.2 PURPOSE OF THE STUDY ......................................................................................... 2
1.3 RATIONALE FOR ASPARAGUS, BLUEBERRIES

AND PICKLING C UCUMBERS .7 ................................................................................ 4

1.3.1 Apples ............................................................................................................ 6

1.3.2 Asparagus ....................................................................................................... 6

1.3.3 Blueberries ..................................................................................................... 7

1.3.4 Pickling Cucumbers ....................................................................................... 8

1.4 RESEARCH QUESTIONS ............................................................................................ 8

1.5 H YPOTHESES AND JUSTIFICATION ...................................................................... 10

1.6 ORGANIZATION OF THE STUDY ............................................................................ l7

viii

PAGE

CHAPTER 2 - MICHIGAN’S AGRICULTURAL HERITAGE, A HISTORY OF
MIGRANT FARM LABOR IN THE UNITED STATES AND

MICHIGAN, AND A REVIEW OF SOCIAL CAPITAL THEORY ....... 18

2.1 A BRIEF HISTORY OF AGRICULTURE IN MICHIGAN ......................................... 18
2.1.1 The Early Days ............................................................................................ 18

2.1.2 Michigan Agriculture After 1940 ................................................................ 20

2.2 A HISTORY OF MIGRANT FARM LABOR IN THE UNITED STATES .................... 22
2.2.1 The Role of Hispanics in U. S. Agriculture ................................................. 25

2.2.2 A Growing Concern Over Too Many Immigrants ....................................... 26

2.2.3 Changing Migrant Opportunities ................................................................. 27

2.2.4 A Complex Problem .................................................................................... 28

2.3 A REVIEW OF SOCIAL CAPITAL THEORY ............................................................. 29
2.3.1 Introduction to Social Capital Theory .................... I ...................................... 3 1

2.3. The Promise and Limitations of Social Capital Theory ................................. 37

2.3.3 Relevant Studies Using Social Capital Theory ............................................ 38

2.3.3.1 Importance of Social Ties to the Success Rate
of Agricultural Micro-Enterprises in Ghana ................................. 38

2.3.3.2 The Role of Soccer Clubs in the Development of
Migrant Networks from Mexico ................................................... 40

2.3.3.3 Social Capital’s Minimization of Adverse
Poverty Effects in Latino Communities ......................................... 41

2.3.3.4 Human Capital Resources as a Tool for
Finding Work in the United States ................................................ 42

2.3.3.5 The Importance of Social Capital in Making
the Right First Impression ............................................................. 42

ix

PA GE

2.3.4 How Social Capital Theory Will Enhance the Relevance of

Traditional Economic Theory ...................................................................... 43
CHAPTER 3 — THEORETICAL FRAMEWORK AND METHODOLOGY .................. 47
3.1 THEORETICAL FRAMEWORK ................................................................................. 47
3.1.1 An Integrated Interpretation of the Problem ................................................ 47
3.1.2 Proposed Determinants of Migrant Farm Labor

Supply and Demand ................................................................................... 51
3.2 METHODOLOGY ....................................................................................................... 55
3.2.1 Modiﬁed Rapid Appraisal ............................................................................ 56
3.2.2 The Survey and Case Study Populations ..................................................... 57
3.2.2.1 Targeted Growers .......................................................................... 57

3.2.2.2 Targeted Migrant Farmworkers (Pilot Survey
and Focus Group) ........................................................................... 60
3.2.3 Survey Instruments ...................................................................................... 60
3.2.3.1 Grower Mail Survey ..................................................................... 61
3.2.3.2 Migrant Farmworker Case Study .................................................. 62
3.2.4 Data Analysis ............................................................................................... 63
3.2.4.1 Valuation of Perquisites ................................................................ 64
3.2.4.2 Standardized Wage Calculation .................................................... 64
3.2.4.3 Real Wage Calculation ................................................................. 65

3.2.4.4 Calculation of Earnings Percentages Returned to
the State of Michigan by Migrant Workers .................................. 65

3.2.5 A Logit Regression Model that Explores the Determinants
of Having Sufﬁcient Migrant Farm Labor ................................................. 66

PA GE

3.3 CONCLUSION ............................................................................................................ 69
CHAPTER 4 - GROWER SURVEY RESULTS.......... .................................................... 70
4.1 CHARACTERISTICS OF THE SURVEY RESPONDENT S ........................................ 70
4.1.] Response Rate .............................................................................................. 70
4.1.2 Characteristics of the Survey Participants ................................................... 73
4.1.2.1 Grower Distribution by County .................................................... 73
4.1.2.2 Grower Experience Working on a Farm

and Hiring Migrant Farmworkers .................................................. 75
4.1.2.3 Crop Acreage ................................................................................ 76
4.1.2.4 Off-Farm Work ............................................................................. 78
4.1.2.5 Attendance at Extension Meetings ................................................ 79
4.1.2.6 Spanish-Speaking Ability ....................... I ...................................... 79

4.1.3 Characteristics of Those Surveyed Who Did Not Hire
Migrants in 2000 ........................................................................................ 80
4.2 RESULTS OF THE GROWER SURVEY ..................................................................... 82
4.2.1 Statistics About Growers ............................................................................. 82
4.2.1.1 Gross Crop Income Versus Net Crop Income .............................. 82

4.2.1.2 Migrant Payroll as a Percentage of Total Farm

Operating Expenses ....................................................................... 84

4.2.1.3 Crop Sales as a Percentage of Total Farm
Earnings ......................................................................................... 85
4.2.2 Migrant Worker Statistics ............................................................................ 86

xi

PAGE

4.2.2.1 Migrant Origins ............................................................................. 86
4.2.2.2 How and When Growers Recruited

Migrant Workers ............................................................................ 88
4.2.2.3 Number of Migrants Returning to Previous

Employers ...................................................................................... 92
4.2.2.4 Migrant Hires Per Day During the

Harvest Season ............................................................................... 93
4.2.2.5 Migrant Worker Harvest Days by Subsector ................................ 94
4.2.2.6 Wage Arrangements ...................................................................... 96

4.2.2.6.] How Migrant Workers Are Paid .................................... 96

4.2.2.6.2 Standardized Wage Calculation ..................................... 97

4.2.2.6.3 Expected Wage Rates in the Absence

of Migrant Workers ..................................................... 98

4.2.2.7 Primary Migrant Worker Perquisites:

Housing and Utilities ..................................................................... 99

4.2.2.7.] On-Farm Migrant Housing .......................................... 100

4.2.2.7.2 Rent and Utility Issues ................................................. 103

4.2.2.7.3 Off-Farm Migrant Housing .......................................... 106

4.2.2.8 Secondary Migrant Worker Perquisites
and Services ................................................................................. 107

4.2.2.8.] Secondary Perquisites Provided to

Migrant Workers .......................................................... 107
4.2.2.8.2 Secondary Services Available
for Migrant Use ............................................................ 111
4.2.2.9 An Estimation of Real Wages Paid to
Migrant Workers in Michigan .................................................... 113
4.2.2.10 Mean Crop Percentages Harvested by Migrants ....................... 115

xii

PA GE

4.2.3 Has There Been a Migrant Labor Shortage in Michigan? ......................... 115
4.2.3.1 Labor Shortage in Relation to Unharvested Acres ..................... 117
4.2.3.2 Labor Shortage in Relation to Late-Harvested Acres ................. 119
4.2.3.3 Labor Shortage in Relation to Farm Size .................................... 121
4.2.3.4 Labor Shortage in Relation to Real Wages ................................. 121
4.2.3.5 Labor Shortage in Relation to the Provision of Housing ............ 122

4.2.3.6 Labor Shortage in Relation to Growers’ Ability to
Communicate in Spanish ............................................................. 122

4.2.3.7 Labor Shortage in Relation to Migrants that Return to

Same Farms Year-After-Year ...................................................... 122
4.2.3.8 Potential Explanations for the Perceived Labor Shortage .......... 123
4. 2. 3. 9 Changes Made By Growers to Accommodate
Labor Shift .................................................................................. 125
4.2.4 Anticipated Future Migrant Labor Needs .................................................. 126
4.2.5 Anticipated Future Migrant Labor Availability ......................................... 131
4.2.6 Non-Mi grant and Year—Round Labor Statistics ......................................... 134
4.3 REGRESSION ANALYSIS ......................................................................................... 138
4.4 SUMMARYAND CONCLUSION ............................................................................. 139

CHAPTER 5 — MIGRANT FARMWORKER PILOT SURVEY AND
FOCUS GROUP RESULTS, AND A COMPARISON

OF GROWER AND MIGRANT DATA ................................................. 142
5.1 INTRODUCTION ..................................................................................................... 142
5.2 MIGRANT STUDY FINDINGS ................................................................................. 143

xiii

PAGE

5.2.1 Basic Demographics .................................................................................. 143
5.2.1.1 Pilot Survey Participants ............................................................. 143
5.2.1.2 Focus Group Participants ............................................................ 146

5.2.2 Ease of Finding Employment ..................................................................... 146
5.2.2.1 Pilot Survey Participants ............................................................. 146
5.2.2.2 Focus Group Participants ............................................................ 147

5.2.3 Crop Preferences ........................................................................................ 147
5.2.3.1 Pilot Survey Participants ............................................................. 147
5.2.3.2 Focus Group Participants ............................................................ 149

5.2.4 Wage Preferences ....................................................................................... 150

5.2.5 Individual and Family Income Levels ....................................................... 151

5.3 ADDITIONAL MIGRANT FINDINGS ...................................................................... 153

5.3.1 A Potential Explanation for the Shortage of Labor

on Blueberry Farms .................................................................................... 153
5.3.2 Migrant Incomes and the Poverty Line ...................................................... 154
5.3.3 Estimated Percentage of Migrant Farm Earnings Returned

to the State of Michigan as Expenditures .................................................. 154

5.3.4 Likes and Dislikes About Migrant Farm Work in Michigan ..................... 156

5.3.5 What Migrants Look For When Seeking Employment ............................. 159

5.3.6 Perceived ‘Good’ and ‘Bad’ Farm Characteristics .................................... 160

5.3.7 Migrants’ Perceptions of the Farm Labor Situation

and Plans for the Future (Michigan, 2002) ................................................ 162
5.4 TWO MIGRANT PERSPECTIVES ........................................................................... 164

xiv

PA GE

5.5 A COMPARISON OF GROWER AND MIGRANT DATA,

AND SOCIAL CAPITAL FINDINGS ......................................................................... 166
5.5.1 A Comparison of Divergent Opinions Reported by
Growers and Migrant Farmworkers in Michigan ...................................... 166
5.5.1.1 Job Search and Recruitment ........................................................ 167
5.5.1.2 Migrant Housing and Perquisites ................................................ 168
5.5.1.3 Wages .......................................................................................... 168
5.5.1.4 Reasons For (and Solutions To) the Decline
in Migrant Farm Labor ................................................................ 169
5.5.1.5 Characteristics of a Satisfactory Work
Environment ................................................................................ 170
5.5.2 Social Capital Implications of this Research ............................................. 171
5.6 CONCLUSION ..................................................... * ..................................................... 172

CHAPTER 6 — SUMMARY, CONCLUSIONS AND

POLICY RECOMMENDATIONS ................................................................................. 173
6.1 INTRODUCTION ..................................................................................................... 173
6.2 SUMMARY OF THE MAIN RESEARCH FINDINGS .............................................. 173
6.3 RECOMMENDATIONS ............................................................................................ 179

6.3.1 Additional Research into Migrant Farm Labor Issues in Michigan .......... 181

6.3.1.1 Extension of the Migrant Pilot Survey to a Statistically
Comparable Number of Migrants ............................................... 182

6.3.1.2 Periodic Collection of Mi grant-Related
Data from Michigan Growers ..................................................... 182

6.3.1.3 Research into the Possibility of Offering
Fair Wage Cr0ps in Michigan ........................................ 183

XV

PA GE

6.3.2 Steps to Improve Communication Between

Michigan Growers and Migrant Farmworkers .......................................... 185

6.4 CONCLUSIONS AND RECOMMENDATIONS

FOR FUTURE RESEARCH ...................................................................................... 187
APPENDICES ................................................................................................................. 189
APPENDD( A .................................................................................................................. 190
ORIGINAL SURVEY INSTRUMENT .......................................................................... 190
APPENDIX B .................................................................................................................. 211
SUPPLEMENTAL SURVEY INSTRUMENT
FOR BLUEBERRY GROWERS .................................................................................... 211
APPENDIX C .................................................................................................................. 214
MIGRANT FARMWORKER SURVEY ........................................................................ 214
APPENDIX D .................................................................................................................. 220
CORRELATIONS OF CONTINUOUS VARIABLES
USED IN CHAPTER 4 REGRESSIONS ........................................................................ 220
BIBLIOGRAPHY ............................................................................................................ 221

xvi

Figure 3.1

Figure 3.2

Figure 3.3

Figure 4.1

LIST OF FIGURES

PAGE
A neo-classical supply and demand diagram in
response to a decline in labor supply ......................................................... 48
Schematic diagram of the factors that influence migrant
farm labor supply and demand in Michigan .............................................. 53
A map showing the counties targeted by the
grower survey (Michigan, 2000) ................................................................ 59
Cumulative percent of growers according to when they initiated
their search for the 2000 harvest, by subsector (Michigan, 2000) ............. 91

xvii

LIST OF TABLES

PAGE

Table 3.1 Labor supply and demand shifters, and their potential impact

on supply and demand for migrant farm labor in Michigan ............................ 52
Table 4.1 Response rate, by subsector (Michigan, 2000) ................................................. 71
Table 4.2 Distribution of respondents, by county and subsector

(Michigan, 2000) .............................................................................................. 74
Table 4.3 Grower experience working on a farm and hiring migrant

farmworkers, by subsector (Michigan, 2000) ................................................. 76
Table 4.4 Mean farm size and acreage planted to annual and

target crops, by subsector (Michigan, 2000) .................................................... 77
Table 4.5 Percentage of growers who work off-farm, number of

hours/week they spent working elsewhere, and the number

of extension meetings attended annually, by subsector

(Michigan, 2000) .............................................................................................. 78
Table 4.6 Percentage of growers claiming ability to communicate in

Spanish and mean ﬂuency level, by subsector (Michigan, 2000) .................... 80
Table 4.7 Gross crop income distribution (sales) of apple, asparagus,

and pickle producers (Michigan, 2000) ........................................................... 83
Table 4.8 Net crop income distribution (sales - expenses) of

blueberry producers (Michigan, 1998-2000) .................................................. 83
Table 4.9 Migrant payroll as a percentage of total farm operating

expenses, by subsector (Michigan, 1998-2000) ............................................... 84
Table 4.10 Speciﬁed crop sales as a % of total farm earnings,

by subsector (Michigan, 1998-2000) .............................................................. 86
Table 4.11 Migrant worker origins, by subsector (Michigan, 2000) ................................ 87

xviii

Table 4.12

Table 4.13

Table 4.14

Table 4.15

Table 4.16

Table 4.17

Table 4.18

Table 4.19

Table 4.20

Table 4.21

Table 4.22

Table 4.23

Table 4.24

Table 4.25

PAGE

Growers’ methods for recruiting migrant workers,

by subsector, (Michigan, 2000) ...................................................................... 89
Percentage of workers hired by different methods,

by subsector (Michigan, 2000) ....................................................................... 90
Mean percentages of migrant laborers that worked previously

for the same grower, by subsector (Michigan, 2000) ..................................... 92
Mean number of migrants needed per day for subsector

harvests (Michigan, 1998-2000) ..................................................................... 94

Mean number of migrant worker harvest days (MWI-IDs),
by subsector (Michigan, 1998-2000) .............................................................. 95

Percentage of growers using different wage types for
migrant workers and mean dollars paid per unit, by

subsector (Michigan, 2000) ............................................................................ 97
Percent distribution of standardized wages paid by growers in the

target subsectors (Michigan, 2000) ................................................................. 98
Mean expected daily wage in absence of migrant workers,

by subsector (Michigan, 2000) ....................................................................... 99
Percentage of growers that provide migrant housing,

by subsector (Michigan, 2000) ..................................................................... 100
Mean housing capacity, by subsector (Michigan, 2000) ............................. 101

Mean number of workers/farm that could be housed in
2000 versus the mean number employed and mean

additional number needed, by subsector (Michigan, 2000) .......................... 102
Migrant housing rental payments by subsector

(Michigan, 2000) ........................................................................................... 103
Migrant utility payments by subsector (Michigan, 2000) ............................. 105

Mean number of growers with migrants who lived off-farm,
where they lived, and distance traveled to work, by subsector
(Michigan, 2000) ............................................... _ ............................................. 106

xix

Table 4.26

Table 4.27

Table 4.28

Table 4.29

Table 4.30

Table 4.31

Table 4.32

Table 4.33

Table 4.34

Table 4.35

Table 4.36

Table 4.37

Table 4.38

PA GE

Number and percentage of growers providing secondary

perquisites to migrant workers, and mean harvest season

value, by subsector (Michigan, 2000) ........................................................... 108
Mean distance from farms to services, as reported by

growers, by subsector (2000) ........................................................................ 112
Estimated real wage rates, by subsector (Michigan, 2000) .......................... 114
A comparison of real and standardized wages,

by subsector (Michigan, 2000) ..................................................................... 115
Mean crop percentages harvested by migrants,

by subsector (Michigan, 2000) ..................................................................... 116

Percentages of growers reporting a shortage of migrant labor
and the mean number of additional workers needed, by
subsector (Michigan, 1998-2000) ................................................................. 116

Mean unharvested acres and ﬁnancial loss per acre, among those
growers citing an inability to hire sufﬁcient migrants -
by subsector (1998-2000) ............................................................................. 118

Mean acres harvested beyond the optimal time and ﬁnancial
loss per acre, among growers reporting a shortage of

migrant labor, by subsector (Michigan, 1998-2000) .................................... 120
First or second place grower ranking (%) of reasons for why

there is a migrant labor shortage, by subsector ............................................. 124
Percentage of respondents citing labor shortage who made changes

in their farm operating procedures to reduce labor need or attract

more labor to their farms, by subsector (Michigan, 2000) ........................... 126
Growers’ anticipated need for migrant workers in 2001 and 2005,

by subsector (Michigan, 2000) ..................................................................... 127
Factors that growers believe will increase their future labor

need, by subsector (Michigan, 2000) ............................................................ 129
Factors that growers believe will decrease their future labor

need, by subsector (Michigan, 2000) ............................................................ 130

XX

PAGE

Table 4.39 Growers’ expectations regarding the availability of migrant
workers in ﬁve years, by subsector (Michigan, 2000) .................................. 132

Table 4.40 Growers’ suggestions for increasing the future supply of
migrant workers, by subsector (2000) ......................................................... 133

Table 4.41 Mean number of non-mi grants growers hired per day
per farm, by subsector (Michigan, 1998-2000) ............................................ 135

Table 4.42 Percentage of growers citing they had trouble hiring
year-round workers, by subsector (Michigan, 1998-2000) ........................... 136

Table 4.43 Grower reasons concerning why they had difﬁculty hiring
year-round labor, by subsector (Michigan, 1998-2000) ............................... 137

Table 4.44 Percentage of growers citing they had trouble hiring other
peak time laborers in 1998-2000 -- by subsector .......................................... 137

Table 4.45 Growers’ reasons for having difﬁculty hiring laborers
during non-harvest peak labor periods, by subsector
(Michigan, 2000) ........................................................................................... 138

Table 5.1 General information about the pilot survey participants
(Michigan, 2002) ............................................................................................ 144

Table 5.2 Migrant permanent residence, crop and state preferences,
how jobs are found, and opinions about difficulties in
ﬁnding Michigan work, by pilot survey participants
(Michigan, 2002) ............................................................................................ 145

Table 5.3 Percentage of the pilot survey participants who harvested the
crops relevant to this study (Michigan, 2000-02) .......................................... 148

Table 5.4 Mean individual and family income statistics among
pilot survey participants (Michigan, 2000-02) ............................................... 152

Table 5.5 Individual income from MI farm work as a % of overall
individual income and overall individual income as a percentage
of overall migrant family income (Michigan, 2000-02) ................................ 152

Table 5.6 Pilot survey participants’ weekly expenditures, and the estimated

mean weekly cost of these expenditures while living in Michigan
(Michigan, 2002) ............................................................................................ 156

xxi

PAGE

Table 5.7 Percentage of pilot survey respondents ranking following factors
among their top three positive reasons for working as migrants
in Michigan (Michigan, 2002) . ...................................................................... 157

Table 5.8 Percentage of pilot survey respondents ranking following factors

among their top three negative reasons for working as migrants
in Michigan (Michigan, 2002) ....................................................................... 158

Table 5.9 Percentage of pilot survey respondents ranking following factors
among their top three considerations when seeking farm work

in Michigan (Michigan, 2002) ....................................................................... 159

Table 5.10 Characteristics that migrant workers felt contribute to a ‘good’
and ‘bad’ work environment (Michigan, 2002) ............................................ 161

Table 5.11 Migrant opinions about the number of workers coming to Michigan,
and future plans (Michigan, 2002) ................................................................ 162

xxii

ANOVA

CAMP

ESA

GAO

GCI

JSRI

MASS

MBGA

MDA

MDCD

MSU

MSUE

MWHD

NC]

US.

KEY TO ABBREVIATIONS

Analysis of variance

College Assistance Migrant Program
Employment Services Agency

General Accounting Ofﬁce

Gross crop income

Julian Samora Research Institute
Michigan Agricultural Statistics Service
Michigan Blueberry Growers Association
Michigan Department of Agriculture
Michigan Department of Career Development
Michigan Farm Bureau

Michigan State University

Michigan State University Extension
Migrant worker harvest day

Net crop income

United Producers of Michigan

United States

xxiii

“F arming looks mighty easy when your plow is a pencil and you ’re a thousand miles

from the cornﬁeld. ” -- Dwight D. Eisenhower, Address at Peoria, IL 25 Sep 56

xxiv

CHAPTER 1

INTRODUCTION

1.1 PROBLEM STATEMENT

In recent years, a perception has emerged among Michigan growers that the
migrant farm labor supply no longer meets grower demand (Schmucker, 1998;
Roccisano, 1998). This perception has been corroborated in places like Florida where
hand picked crops require large quantities of migrant labor, yet the labor has not been
forthcoming (Dunn, 1999). Dunn (1999) called this the result of a strong economy,
implying more alternatives to farm work for both legal and illegal immigrants. Yet the
more recent slump in the national economy does not support this reasoning.

Despite complaints of farm labor scarcity across the nation, the US. General
Accounting Ofﬁce (GAO) reported (1997) that no such deﬁciency exists and one is not
likely to occur in the near future (Kelly, 1998). More recently, in support of GAO’s
stance, Verhovek (2002) writes that migrant farm workers in Washington State and
Oregon are having a hard time ﬁnding jobs.

Statistics from the Michigan Agricultural Statistics Service (MASS) point to more
conflicting ﬁndings. For example, contrary to the grower statement that workers are

increasingly difﬁcult to recruit, the number of migrant laborers hired for farm work in

Michigan actually increased from 1998 to 1999 (MASS, 2000). Furthermore, while the
average U. S. real wage increased by only 2.68% in 1999 (Labor Research Association,
2003), the average wage of Michigan farm workers rose by 4%, to a recorded mean of
$8.21 per hour (MASS, 2000).

Thus, the perceived farm labor shortfall in Michigan may be a true reﬂection of a
decreasing number of migrant farm laborers seeking work in Michigan. It may also be
the result of numerous underlying factors, including: 1) wages that are simply too low to
attract workers, especially when compared to those offered by today’s service-oriented
economy, 2) inadequate farm labor recruiting practices, 3) housing inadequacies, or 4)

substandard farm labor management practices by growers.

1.2 PURPOSE OF THE STUDY

The purpose of this study is to analyze the migrant farm labor market in Michigan,
focusing on the current and future supply of and demand for migrant farm labor in the
apple, asparagus, blueberry, and pickling cucumber subsectors. This study is important to
the Michigan plant industries for two reasons. First, the state extensively relies on
migrant workers to harvest its numerous labor-intensive crops (Michigan Department of
Agriculture (MDA), 1997). An increasing failure to hire enough workers, for whatever
reason, reduces growers’ ability to harvest crops on time, resulting in potentially heavy
financial and quality losses for un-harvested (or late-harvested) fruits and vegetables.

Second, Congress intermittently considers legislative changes that could
signiﬁcantly influence the farm labor supply. While a proposal, attached to a bill that

failed in Fall 1998, would have ensured a steadier flow of legal migrant farrnworkers

nation-wide, it would have simultaneously increased growers’ labor costs, through higher
wages and mandatory housing improvements (Anderson, 1998). Such legislation likely
would have led to higher agricultural prices, thus potentially reducing the competitiveness
of US. produce.

If the absence of an actual labor shortfall could be documented, then it is possible
that simpler, more cost-effective measures could be proposed for better aligning
Michigan’s labor supply and demand needs. For example, a more effective system than
the one currently in place for directing migrant workers to growers who need laborers
may be one solution. Another solution may be to establish a statewide committee,
composed of growers and migrant farm workers, to identify and resolve communication
problems and cultural difﬁculties between the two groups.

The goal of this dissertation is to answer a series of research questions as they
pertain to migrant farm labor in Michigan’s apple, asparagus, blueberry, and pickling
cucumber industries. In addition to serving as a baseline study of the target crops, against
which future data can be compared, this study can also serve as a model for studying

migrant farm labor issues among other commodity subsectors in Michigan and elsewhere

around the country.
This study will benefit:
1) apple, asparagus, blueberry, pickling cucumber, and other kinds of

growers - by identifying the most effective ways for attracting and retaining

migrant labor,

2) extension agents - by generating information that they can share with

growers to improve their ability to recruit and retain migrant labor,

3) researchers - by establishing a line of research that can be expanded to other
crops and elsewhere in the country, and

4) Michigan (and other state) legislators - by providing them with information
they need to take into account when considering legislative changes that

apply to migrant labor in Michigan and elsewhere.

1.3 RATIONALE FOR APPLES, ASPARAGUS, BLUEBERRIES, AND

PICKLING CUCUMBERS

As of 1999, Michigan continued to be the nation’s leading state in blueberry and
pickling cucumber production, and third in apple and asparagus production (MASS,
2000). Bluebenies and pickling cucumbers, respectively, accounted for 40% and 26% of
national production, up from 32% and 23% in 1998 (Michigan Department of Agriculture
(MDA), 1999). In 1999, apples accounted for 12% of national production, up from 9%
the previous year (MDA, 1999). Finally, asparagus accounted for 14% of national
production in 1999 (MASS, 2000).

In terms of Michigan’s agricultural output, during 1994-1998, apples accounted
for nearly one-half of Michigan’s fruit production value. Blueberries accounted for
nearly one-quarter of the state’s fruit production value (23%), and pickling cucumbers
accounted for approximately 12% of Michigan’s vegetable production value (MASS,
1999). Furthermore, asparagus is a $20 million industry, with 80—90% of the crop
processed and 10-20% marketed fresh (MASS, 2000; Hemer and Kelly, 1992).

The most recent available data indicate that 57,000 acres of apples and 17,000

acres of blueberries (1997), and 17,500 acres of asparagus and 27,000 acres of pickling

cucumbers (1998) were grown (MDA, 1998; MDA, 1999).1 In terms of acreage shares,
41.1% and 12.3% of Michigan’s fruit acreage was planted to apples and blueberries,
respectively. In 1998, pickling cucumbers2 accounted for 15.4% of Michigan’s vegetable
acreage while asparagus accounted for 10% (MASS, 1999).

While a substantial amount of land is planted to these crops, in 1998 fruit
accounted for slightly less than 6% of cash receipts from Michigan agriculture and
vegetables accounted for a little less than 9%3 (MASS, 1999). However, of the 38
Michigan crops that require migrant farm labor, the fruit and vegetable subsectors
account for a signiﬁcant proportion of this labor usage (MASS, 2000). Since migrant
farm labor issues form the core of this study, and since it is the consensus of MDA,
MASS, and commodity specialists throughout the state that the apple, asparagus,
blueberry, and pickling cucumber subsectors are among the principal users of migrant
farm labor in Michigan, this study targets these four crops.

Currently, disaggregated data are not available to estimate the distribution of

migrant labor across the fruit and vegetable subsectors“. This speciﬁc lack of

 

'A comparison across years indicates that these numbers do not shift signiﬁcantly from
year- to-year.

2Pickling cucumbers are differentiated from the 7,000 acres of cucumbers that were

planted for the fresh market in Michigan in 1997 (MDA, 1998). Pickling cucumbers are
grown for processing.

3 Livestock, livestock products, and ﬁeld crops together account for the vast majority of
cash receipts from Michigan agriculture.

‘Most data report hired farm labor as a whole, without distinguishing between migrant
farm labor and resident labor.

information, as well as the ongoing claims by Michigan growers that migrant farm
workers are becoming harder to ﬁnd, makes this study particularly relevant.

In addition to their labor contribution to the target fruit and vegetable subsectors,
these workers contribute considerably to small rural economies throughout Michigan
during their tenure on Michigan farms. As pointed out by several growers in southwest
Michigan, many of Michigan’s small rural communities would suffer signiﬁcant ﬁnancial

losses if migrant farm labor fell below current levels.

1.3.1 Apples

During 1986-1997, the number of apple farms declined by nearly 27% (from
1,516 in 1986 to 1,100 in 1997) and apple crop acreage declined by 8% (61,000 acres
were planted in 1986, 57,000 in 1998). However, the number of apple trees in Michigan
grew by 52.6% (8,850,000 trees in 1997 compared to 5,800,000 in 1986). This growth
in the number of trees is a convincing indicator of the anticipated strength of the apple
industry and its importance to Michigan’s fruit sector. In fact, apple production reached

a record high in 1999, producing 1.21 billion pounds--up 23% from 19985 (MASS,

2000).

1.3.2 Asparagus

Michigan is the only regional source of good quality “fresh” asparagus6. As such,

the demand for fresh Michigan asparagus is high, as is the demand for processed

 

5 In part, this was due to favorable climatic conditions.

° California is the country’s top asparagus producer.

asparagus. Described by Hemer and Kelly (1992) as environmentally friendly7,
nutritious, and high in dietary ﬁber, it is likely that an increasingly health-conscious
public’s demand for Michigan asparagus will continue to grow. Asparagus is a good crop

for migrant workers, as it provides work during the spring when other crops do not offer

job possibilities.

1.3.3 Blueberries

During 1986-1997, blueberry acreage grew from 14,100 acres to 17,000 acres, an
increase of nearly 21% (MDA, 1998), despite a decline in the number of blueberry farms
from 624 to 562 in the same time period. According to Hanson (1992), Michigan will
likely remain the leader in blueberry productions, in part because the area planted to
blueberries can be expanded more easily in Michigan than in other states where high land
values and wetland restrictions prevent such expansion.

While Michigan blueberry growers have been among those voicing public concern
about a growing labor shortage, according to Hanson (1992) more acres of blueberries are
mechanically harvested than hand-harvested in Michigan--while in other states, the
reverse is true. Thus, it seems likely that smaller blueberry growers, without the capacity
for mechanical harvesting, are most at risk from a labor shortage. Larger growers, who

have been able to invest in mechanical harvesting equipment, will likely not feel the

 

7Asparagus requirements are small in terms of fertility and pesticide applications (Hemer
and Kelly, 1992).

3 Hanson (1992) estimates Michigan’s annual production of blueberries ranges from 60 to
80 million pounds, or roughly 20% of world production.

pinch of a labor shortage at harvest time, although they may when it comes to pruning and

sorting activities which are labor-intensive (Hanson, 1992).

1.3.4 Pickling Cucumbers

The number of harvested acres of pickling cucumbers has remained virtually
unchanged since 1995 (26,000 acres in both 1995 and 1998) (MDA, 1999). However,
total salt stock, fresh pack, and refrigerated pickle production increased signiﬁcantly from
1998 to 1999, from 324,525 tons to 425,288 tons (MASS, 2000). While Michigan is the
nation’s number one producer of pickling cucumbers, it is projected that “the market
demand for pickling cucumbers is not likely to increase much in the future” (Hemer and
Kelly, 1992, p. 21). According to Hemer and Kelly (1992), because of the crop’s labor-

intensity at harvest time, the pickling cucumber industry is vulnerable to labor shortages.

1.4 RESEARCH QUESTIONS
Seven research questions are addressed in this study:

1) How do the apple, asparagus, blueberry, and pickling cucumber
subsectors in Michigan differ in terms of their recruitment and
retention of migrant farmworkers? (See Hypotheses 1 and 2 in the
following section.)

2) How do large, more ﬁnancially secure (and productive) farms in
Michigan differ from smaller, less financially secure farms in their
ability to recruit and retain migrant farmworkers? Does the same

pattern hold across subsectors? (See Hypothesis 3.)

3)

4)

5)

6)

7)

How do wage scales, housing opportunities, and other perquisites
for migrant farmworkers contribute to real wages received and how
do these real wages vary by subsector? Also, how do these real
farm wages compare to non-farm wage opportunities? (See
Hypotheses 4 and 5.)

What role does social capital play in migrant farm labor
recruitment and retention? For example, how do repeat positive
(or negative) interactions between growers and migrant
farmworkers influence the ability of growers to attract sufﬁcient
labor to their farms? (See Hypotheses 6 and 7.)

To what extent do repeated interactions between growers and
migrant farmworkers lower the transaction costs associated with
locating and retaining migrant labor? (See Hypothesis 8.)

How do the perceptions of growers and migrant farmworkers differ
with respect to the recruitment and retention practices of apple,
asparagus, blueberry, and pickling cucumber growers? (See
Hypothesis 9.)

How much of a migrant farmworker’s Michigan earnings are
returned to Michigan through local purchases? (See Hypothesis

10.)

1.5 H YPOTHESES AND J US TIF ICA TI ON

This dissertation tests ten hypotheses. A brief statement justifying its inclusion

follows each hypothesis. Theoretical, factual, and intuitive reasoning are used to justify

each hypothesis.

HYPOTHESIS 1:

JUSTIFICATION l:

Growers that supply approved migrant housing have an easier time
attracting and retaining migrant farm labor than growers who do

not, regardless of the subsector(s) in which they are involved.

The provision of migrant housing on the farm, at zero or reduced
cost to the worker, raises a migrant worker’s real wages and
eliminates the cost of travel. Thus, assuming that: 1) farm wages
are equivalent on farms that do and do not provide migrant
housing, and 2) migrant farmworkers are rational decision-makers
(in accordance with neoclassical theory), it can be argued that
growers who provide migrant housing will have an easier time
recruiting and retaining migrant labor than those who do not.
Likewise, growers who supply approved migrant housing are
eligible to be listed with the Michigan Department of Career
Development (MDCD) (interview with Jane Anderson, agricultural
employment specialist, MDCD, October 2003). MDCD then
shares this list of potential employers with approved housing with

migrants seeking work in Michigan.

IO

HYPOTHESIS 2:

JUSTIFICATION 2:

HYPOTHESIS 3:

JUSTIFICATION 3:

The apple, asparagus, and pickling cucumber industries have an
easier time recruiting and retaining migrant farm labor than does

the blueberry industry.

Discussions with MDA, MASS, and commodity specialists
indicate that Michigan apple, asparagus, and pickling cucumber
growers are more inclined to provide migrant housing than are
blueberry growers. Thus, in accordance with Justiﬁcation #1 ,
apple, asparagus and pickling cucumber growers will be more
successful recruiting and retaining migrant farm labor than will

blueberry growers.

Large farms (wherein farm size is defined in terms of total farm
acreage, crop earnings, and estimated total farm earnings) have an

easier time recruiting and retaining migrant farm labor than small

farms.

As large farms generally have a stronger financial base, they are in
a better position to invest in recruiting migrant farm labor. This is
in accordance with economies of scale. In several instances, key
informants noted that growers with large farms actually travel to

Texas during the winter months to sign on workers. However,

11

more often, they hire crewleaders to do this for them. In terms of
farmworker retention, growers with large farms can provide more
and often better housing to workers. They also provide a larger
variety of job opportunities, as well as more jobs, due to greater

crop diversiﬁcation and bigger areas planted per crop.

HYPOTHESIS 4: Farms that provide higher real wages have an easier time recruiting
and retaining migrant labor than farms that provide lower real
wages. In this case, real wages include actual wages plus the value
associated with housing, utilities, and other grower-provided

perquisites.

JUSTIFICATION 4: Based on the economic assumptions that: 1) all individuals are
rational decision-makers, and 2) perfect information exists,
farmworkers will likely migrate to where they can earn the highest
wages. Frequently, wages are bolstered through the provision of
special perquisites. Perquisites are arrangements like free or lower-
cost housing, utilities, transportation, the provision of free
childcare, or ﬁestas at harvest time9. When taken into account,
these perquisites raise the real wages of workers, thus freeing up

actual earnings for transactions elsewhere in the economy. Thus,

 

Wage and perquisite information is communicated by word-of-mouth among migrant
farmworkers.

12

HYPOTHESIS 5:

JUSTIFICATION 5:

migrant farmworkers will choose those opportunities that

ultimately provide the greatest real income.

Among the growers of the target crops who provide migrant
housing and other in-kind perquisites to migrant farmworkers, the
real farm wages received by migrant laborers are higher than the
non-farm wages they could receive elsewhere. Likewise, real farm
wages are lower than non-farm wages when offered by target crop

growers who provide fewer or no in—kind perquisites.

Anecdotal evidence reveals that some growers are having difﬁculty
recruiting and retaining migrant farm labor while others are not.
Since the same non-farm opportunities are available to workers
employed by both kinds of growers, it can be assumed that the
growers in each case are somehow managing their operations
differently. Although minimum wage is the same throughout the
economy, non-farm wages have risen in recent years, while
increasing numbers of minimum wage job opportunities are
available to all kinds of workers in today’s service-oriented
economy. Thus, non-farm opportunities are competing with
agricultural opportunities, drawing workers away from the
traditional migrant farm labor market. Growers who are able to

compete with today’s non—farm opportunities are those who

13

HYPOTHESIS 6:

provide perquisites regarded by migrant farmworkers as sufﬁcient

to compensate for the potentially lower farm wages.

Growers who speak Spanish have an easier time recruiting and

retaining labor than growers who do not.

JUSTIFICATION 6: This hypothesis draws on social capital theory, which focuses on

HYPOTHESIS 7:

“the sympathy of one person towards another person”10 (Robison
and Siles, 1997) and the impact of this relationship on the
economic transactions that take place between the two parties.
Using Spanish fluency as a proxy for the ability and desire of a
grower to communicate with Hispanic workers, migrants (the
objects of social capital in this case) can expect to be better
understood and, in turn, better treated by such growers (the
providers of social capital) (Robison and Siles, 1997). Thus, it is
hypothesized that growers who speak Spanish are better able to
provide the kinds of social capital that attracts, and then retains,

migrant farmworkers.

Growers with migrant farmworkers who return year-after-year are

better able to recruit and retain new migrant labor.

 

‘° This sympathy can also be “extended towards an idealized self or object” (Robison and

Siles, 1997).

I4

JUSTIFICATION 7:

HYPOTHESIS 8:

JUSTIFICATION 8:

It is assumed that migrant farmworkers who return to the same
farm year-after-year ﬁnd the working and living conditions on that
farm sufficient to meet their economic and lifestyle needs. Positive

word-of-mouth attracts additional workers to the same farms.

Growers whose migrant farmworkers return year-after-year have
lower transaction costs associated with locating and retaining labor

than growers whose migrant workers do not.

Social capital theory suggests that transaction costs are reduced
when workers return annually. According to Robison and Siles
(1997), social capital lowers transaction costs because each party’s
well being is linked to the well being of the other party. Growers
need mi grant workers they can trust and rely on; migrant workers
need fair, just employers who offer regular employment. Where
trusting relationships develop between growers and migrant
workers, verbal agreements are used to arrange labor for the
following year. As a result, growers do not have to spend money
on advertising or crew-leaders, and migrant workers are saved the

cost of searching for a place to work.

15

HYPOTHESIS 9:

JUSTIFICATION 9:

Discrepancies exist between the perceptions of growers and
migrant farm laborers about what inﬂuences the recruitment and
retention of apple, asparagus, blueberry, and pickling cucumber
farm workers. These discrepancies are expected to be smaller
between growers and migrant farm workers who interact with one
another in the sharing and exchange of signiﬁcant amounts of
social capital. Nevertheless, because it is impossible to interview
growers and migrants from the same farms, this hypothesis is
difficult to assess directly. Rather, it will be explored broadly,

through the responses of two unrelated samples of growers and

mi grant workers.

In general, growers and migrant farmworkers share little in
common, culturally or economically. Thus, their perceptions of the
world are different, compounded by the fact that each group plays a
different role in the world of agriculture. Expectations differ, as do
education levels. Perhaps most important is the language barrier
that frequently stiﬂes communication between growers and migrant
farmworkers. Therefore, it can be hypothesized that growers and
workers who invest in gaining greater knowledge of each other (a
social capital investment) will have a better grasp of each other’s

modes of thinking.

16

HY POTHESIS 10: Much of a migrant farmworker’s earnings are returned to Michigan

through local purchases that support Michigan’s local, rural

economies.

JUSTIFICATION 10: While living in Michigan, migrant farmworkers must purchase
food, clothing, services and other items. Although all migrant farm
workers may not live in rural communities while in Michigan, it
can be hypothesized that those who do, contribute to the economic

well being of local, agricultural communities throughout the state.

1.6 ORGANIZATION OF THE STUDY

This study is organized as follows. Chapter 2 presents a literature review,
beginning with a discussion of Michigan’s agricultural heritage and a concise history of
migrant farm labor in the United States. It ends with an examination of social capital
theory and its application to this research. Chapter 3 describes the study’s theoretical
framework and methodology. Chapter 4 reviews the ﬁndings from the Fall 2000 grower
survey, as well as the logit regression results. Chapter 5 presents the results of the Fall
2002 migrant pilot survey and February 2003 migrant focus group. It also offers a
comparison of grower and migrant ﬁndings, and the social capital implications of the
research. Finally, Chapter 6 presents a summary of the research results, reviews the
social capital ﬁndings of this research, and presents a series of conclusions, limitations,

and policy recommendations.

17

CHAPTER 2

MICHIGAN’S AGRICULTURAL HERITAGE, A HISTORY OF MIGRANT
FARM LABOR IN THE UNITED STATES AND MICHIGAN, AND A REVIEW

OF SOCIAL CAPITAL THEORY

2.1 A BRIEF HISTORY OF AGRICULTURE IN MICHIGAN

Agriculture has played an important role throughout Michigan’s history.

2.1.1 The Early Days

Native Americans, who first came to Michigan 10,000 years ago, used simple
agricultural techniques to produce corn, beans, peas, squash, and pumpkins (Schaetzl,
2002). In the 17‘h century, fruit trees, primarily apples and pears, were introduced to
Michigan by French explorers. As French-initiated fur trading declined in the early
18005, Schaetzl (2002) asserts that farming took on an added role. The opening of the
Erie Canal in 1825 and the removal of Native Americans from the region through federal
Indian policies in 1833 laid the foundations required to develop an agricultural society.

Both events encouraged the arrival of pioneers into the region, who developed Michigan

agriculture.

18

New Englanders, who arrived ﬁrst, established the state’s wheat and wool
industries, the ﬁrst two legitimate cash crops in Michigan'. In the late-1800s, the
EurOpeans began to arrive. Typically, the Europeans settled in areas where others of the
same nationality had settled before themz. Once established, the pioneers developed
agriculture to the point where it became the main economic activity throughout the rest of
the 18008 (Schaetzl, 2002).

By the turn of the century, however, the Industrial Revolution was in full swing.

“The tractor, the telephone, and the automobile revolutionized

cultivation, communication, and transportation, and rural isolation

was broken. Although farm conditions improved, people left the

farms in droves and resettled in the cities. Rural depopulation

became so severe during the 19205 that many farmers and growers

had to import migrant labor” (Schaetzl, 2002).

Likewise, increasing competition from agricultural products in other states forced
Michigan farmers to diversify their agricultural commodity base. Much of this
diversiﬁcation came about as knowledge was acquired concerning which
ecosystems were best suited to which kinds of crops. According to Hill (1939),
writing in the early part of the 20th century, differences in soil type, typography,

climate and economic conditions played a major role in achieving this advanced

level of diversiﬁcation.

 

‘ Schaetzl (2002) points out that so many people arrived at this time that Michigan’s
population was ten times greater in 1834 than it was in 1820.

2 This pattern illustrates the role social capital played to reduce the transaction costs
associated with settling in a new land. For example, the Germans settled near Saginaw,

the Dutch in the Grand Rapids region, and the Firms in the Upper Peninsula (Schaetzl,
2002).

19

2.1.2 Michigan Agriculture After 1940

According to Bemsten (1998), non-farm factors, technology shifts, and the
state of the economy began to exert stronger inﬂuences over the structure of
Michigan agriculture in the 1940s. As suburban areas expanded out from the
urban areas, land use patterns shifted as land values changed. This resulted in
farms becoming much more specialized, breaking away from our traditional
image of what a farm is. For example, in 1950 almost all farms kept animals. By
1987, farms had become so specialized that animals were kept on only some
farms and, where animals were kept, the herds (or ﬂocks) were very large
(Bemsten, 1998). Likewise, farm inputs shifted. For example, tractor and
fertilizer use increased, while overall labor hires declined3.

From 1950 to 1987, Michigan experienced a 20% decline in harvested
acres". However, the acreage planted to some crops increased while that of other
crops decreaseds, and the agricultural sector became more and more diversified.
While the overall number of farms declined by 67%6, average farm size nearly

doubled, from 111 acres in 1950 to 202 acres in 1987. Whereas only 6% of

 

3 In 1950, 49% of Michigan farms hired labor of any kind. This number had dropped to
35% by 1987 (Bemsten, 1998).

‘ According to Bemsten (1998), whereas 47% of Michigan’s land was used for farmland
in 1950, only 28% was used for the same purpose in 1987.

5 The ﬁve major crops throughout this period were hay, corn, oats, wheat, and dry beans.
Bemsten (1998) states that they accounted for 90% of harvested acres in 1950; 82% in
1987.

6 There were 155,589 farms in 1950, but only 51,172 in 1987 (Bemsten, 1998,
p. 2).

20

farms in 1950 consisted of more than 500 acres, by 1987 45% of farms were this
large.

Non-farm income also became an increasingly important source of
revenue on Michigan farms between 1950 and 1987.

“In 1950, only 33% of the farm households earned more income

from nonfarm sources than farm sales. By 1987 almost one-half

(49%) of farm households reported that farming was not their main

occupation. Similarly, while only 31% of the households reported

working 100 or more days off-farm in 1950, by 1987 this share

rose to 49%--with 43% reporting working 200 or more days off-

farrn” (Bemsten, 1998, p. 4).

Despite these agricultural shifts, the continuing importance of agriculture
to the stability of Michigan’s economy must not be underestimated. In 1990,
agriculture, food and forestry products contributed more than $53 billion to the
state’s economy. Of this total, food processing accounted for 51%, followed by
forest product sales (29%), and input sales (3%) (Bemsten, 1998).

Agriculture and food processing serve to stabilize the state’s economy
when business cycles inevitably disrupt Michigan’s manufacturing enterprises
(Ferris, 2000). “Food processing tends to be located near metropolitan areas,
facilitating employment shifts. Similarly, the proximity of alternative
employment opportunities provides stability for households involved in
agriculture and food processing” (Ferris, 2000, p. 3).

Likewise, Michigan agriculture contributes to the well being of the whole
nation. Given that one-half of all Americans and Canadians live within 500 miles

of Michigan (Ferris, 2000), most North Americans consume agricultural produce

from Michigan farms.

21

2.2 A HISTORY OF MIGRANT FARM LABOR IN THE UNITED STATES

Many ethnic groups have worked in the US. as migrant farmworkers. In
addition to Mexicans and African-Americans, numerous other immigrant nationalities,
including Chinese, Japanese, Filipinos, and various European ethnicities, have ﬁlled this
role in the past (Guerin-Gonzales, 1994). However, in many parts of the country,
Hispanics have filled this role the longest number of years.

California growers set the pattern for migrant farm labor hiring practices that were
eventually adopted throughout the country. Starting in the mid-to-late 1800s, when it
became apparent that the supply of part-time farmworkers and domestic migrant workers
was insufficient, growers in California were the first to “turn to foreign labor and
recruited large numbers of workers from economically distressed countries” (Guerin-
Gonzales, 1994, p. 15). According to Guerin-Gonzales, the Chinese were the first in a
long line of migrant recruits, arriving in the late 1800s. But because they came in such
large numbers and were willing to work for very low wages, worker riots eventually
broke out. This, in turn, created pressure to stop Chinese immigration.

Consequently, at the turn of the 20‘h century, California growers turned to
recruiting Japanese workers. From the start, the Japanese formed associations that
enabled workers to look out for each other. Guerin-Gonzales (1994) reports that the
Japanese were eventually able to organize themselves and thereby increase their wages as
migrant farmworkers, as well as to buy their own land. In response, California growers

began hiring Italian, Portuguese, Armenian, Asian Indian, Korean, Filipino, and

22

eventually Mexican workers, all of whom worked for signiﬁcantly lower wages than the
Japanese (Guerin-Gonzales, 1994).

Eventually, immigrants of white ancestry (the Armenians, for example) were
allowed by law to purchase land. Others, like the Mexicans, were excluded from land
ownership, primarily because of a California law (the Alien Land Law, passed in 1913)
that made it illegal for non-whites to own land. Consequently, it was no longer possible
for Mexicans and Asians to move up the ladder in the world of agriculture.

During World War I, when many white workers were drafted and the economy
was booming with numerous non-farm opportunities, it became necessary for growers to
provide additional perquisites to attract a sufficient supply of migrant farmworkers. It
was during this time that growers ﬁrst provided permanent shelter as housing to migrants.
Nevertheless, as the war drew to a close and the shortage of low-wage farm labor began
to subside, these early housing experiments ended (Guerin-Gonzales, 1994),.

The Great Depression of the 19305 dealt a severe blow to Mexicans throughout
the US, as well as to Americans of Mexican ancestry. In an effort to restore jobs to
unemployed Americans, the US. government deported half a million Mexican
immi grants and Mexican Americans from throughout the country8 (Guerin-Gonzales,
1994; Valdes, 1992). Naively expecting a reprieve from discrimination upon returning
home, repatriated Mexicans found themselves the target of discriminatory practices in

Mexico. First rejected by Americans as Mexicans, they were now rejected by Mexicans

 

7 At the time, Mexican workers were segregated from white workers, and white workers’
houses were of a signiﬁcantly better quality.

8Mexicans families living in the US. were earning roughly one-sixth of the 1935 national
average at (Guerin-Gonzales, 1994).

23

as Americans. According to Balderrama (1995), “Adults found that the family and
friends they had left behind were now total strangers. The Mexico they remembered no
longer existed” (p. 3). As soon as it was possible for these workers to return to the US,
they did so.

In other parts of the country, the transition of agriculture from a subsistence
activity to a labor-intensive, market-oriented industry proceeded at a somewhat slower
pace. Vargas (1997) cites Dennis Valdes’ ﬁnding that during the late-19th century, sugar
beet production in the Great Lakes region “triggered the emergence and eventual
transformation of agriculture from subsistence farming to a labor-intensive corporate
industry” (p. 4). Not until this time did migrant labor become a component of agriculture
in the Midwest.

The ﬁrst migrants to work in the Midwest were European immigrants. As the
Europeans moved towards owning their own farms or becoming factory workers,
African-Americans and Puerto Rican-Americans stepped in to ﬁll the void (Vargas,
1997). Mexicans and Mexican-Americans followed them, mostly by way of Texas, in the
19105 and 19205 (Valdes, 1992). Referred to as Tejanos, these Mexicans and Mexican-
Americans comprised the largest work force in the Midwestern states. “By 1938, 10,000
Tejanos migrated to the northern beet ﬁelds of the Midwest. By 1940, more than 60,000
Tejano workers annually entered the Great Lakes region for employment in agriculture,
the majority migrating to Michigan” (Vargas, 1997, p. 4).

Since the 19705, the number of migrant workers coming to Michigan has tapered
(Aponte, 1995). Many have chosen to live here permanently, and now do other than

migrant work. In 1970, 65,000 people of Mexican origin lived in Michigan. This

24

number grew to 112,000 in 1980 and to 138,000 in 1990 (Aponte, 1995). Presently,
Michigan’s migrant workers tend to come from Texas or Florida, rather than from

Mexicog.

2.2.1 The Role of Hispanics in US. Agriculture

Over time, Mexicans became the preferred group for migrant labor hires, due to
the widespread belief that “Mexicans who returned to their home country each year...
would not change the racial, cultural, or social character” of the communities in which
they lived (Guerin—Gonzales, 1994, p. 24). Thus, considered a non-threat to local
customs, as compared to the perceived threat of foreigners who settle permanently in a
place, growers faced no opposition when inviting Mexicans to work in their fields.

Across the country, World War II cemented the role of Mexicans in American
agriculture. Again, as soldiers marched off to war, white agricultural workers had to be
replaced, this time via Mexicans recruited by the US. Government through the Bracero
Program. According to Massey (1986), for a decade this program provided agricultural
areas throughout the US. with a pool of authorized workers from Mexico and
strengthened social ties between Mexicans living in Mexico and Mexicans living in the
US. The Bracero Program continued long after the end of World War II, enduring for
more than twenty years.

Massey (1986) reports that several migrant networks were in place by the time the
Bracero Program ended in 1964, implying that communication between present and

potential migrant workers was increasing. “The maturation of the networks after 1964

 

9 Most Mexicans come to work in what are called the ‘big 5’--California, Texas, New
Mexico, Arizona, and Colorado (Aponte, 1995).

25

coincided with a wave of capital-intensive agricultural modernization in rural Mexico,
giving rise to a massive upsurge in out-rnigration, most of it undocumented.
Consequently, townspeople turned to international rather than internal migration because
the networks put a US. job within easy reach” (Massey, 1986, p. 107).

During the twenty years of the Bracero Program, growers and Mexican migrants
established personal ties which insured a stable and reliable labor force, without incurring
any legal obligations to the workers and, above all, without having to pay the
transportation costs that were stipulated in the Bracero Treaty” (Massey, 1986, p. 107).
Over time, Mexican labor contractors jumped into the fray, as middlemen involved in
establishing connections between migrants and growers. As long as immigration ofﬁcials
overlooked the 2,000-mile border between Mexico and the US, growers, migrants, and

labor contractors all benefited from this arrangement.

2.2.2 A Growing Concern Over Too Many Immigrants

In recent years, amidst public opposition to too many immigrants (legal and
illegal), the US. government has mandated that border patrols step up their efforts to turn
back would-be immigrants at the U.S.-Mexican border”). Millions of dollars have been
pumped into this renewed effort. Nevertheless, undocumented workers continue to
stream into the US. with relative ease, oftentimes adding to the Mexican-American
populations that have already settled in border areas like southern Texas and southern

California. From these new points of origin, it is signiﬁcantly easier to pursue migrant

 

'° According to Baker and Espitia (2000), US. citizenship applications alone increased
eight-fold between 1991 and 1996, from 200,000 to 1.6 million. Much of this growth is

due to Latin American immigration, accounting for the growing antagonism at the US.-
Mexican border.

26

activities in highly agricultural states. Michigan is a favored destination among migrant
workers from Texas1 1. In fact, many of these individuals have already obtained US.

citizenship.

2.2.3 Changing Migrant Opportunities

The country’s estimated 1.5 million farmworkers are considered by many to be
the most vulnerable workers in the US. economy. After decades of ﬁlling backbreaking
jobs unwanted by most Americans, migrant farmworkers have won little attention from
the US. government despite accepting living and working conditions that most
Americans simply would not tolerate (Howell, 2001). During the decades, when small
and mid-sized farms predominated, this treatment was rationalized through the argument
that migrant farmworkers make more money here than they would have made back home
(Li ghtsey, 1999). Furthermore, the rationalization continues, many of these workers are
here illegally.

Yet, as prior migrant populations have demonstrated, migrant farmworkers are
finding alternative opportunities in an increasingly service-oriented economy. “Some...
grueling jobs are. .. being abandoned in favor of hi gher-paying, easier work. It’s another
chapter in the age-old immigrant story: come to America, work hard and move up”
(Lightsey, 1999, p. 28).

With major structural changes taking place in American agriculture over the past
forty years, a new chapter in American history is slowly emerging. Firstly, large

industrial-sized farms (i.e., in the form of agribusinesses) are replacing small- and

 

” Known as Tejanos.

27

medium-sized farms. In 1960, 15.6 million people (8.9 % of the nation’s population)
lived and worked on farms (Rochin, 1989). By 1985, this number had dropped to 5.3
million people, less than 2% of the nation’s population. Secondly, as stated by
Bustamante (1992), fewer local workers are available or willing to ﬁll our nation’s low-
wage jobs, especially doing farm work. Thirdly, the population of the US. is rapidly

aging (Bustamante, 1992), implying a further dearth of workers at all levels.

2.2.4 A Complex Problem

It can be argued that the solution to any labor shortage lies in the readjustment of
farm wages. Although agreeing that higher wages will attract workers towards any
sector, small and mid-sized farmers argue that they cannot afford to pay higher wages
and remain competitive with imported farm produce. In addition, even at current wage
levels, farm operations are frequently not self-supporting without government assistance
via farm programs. Schweikhardt (2000) notes that “the share of US. net farm income
derived as government payments has risen from 13 percent in 1996 to 47 percent in 1999
(p. 5).”

Clearly, a number of complex issues complicate this analysis of Michigan
agriculture’s perceived labor problem, including a historical dependence on low migrant
wages, a growing number of illegal workers who utilize their social ties (social capital) to
migrate to the US, an increasing set of alternative job opportunities within the economy,
a history of discrimination against migrants, a growing number of large farms, and a

forecasted decline in the overall number of workers in America.

28

However, since growers (and agribusinesses) of all sizes depend on migrant
workers, it is crucial to develop affordable, rewarding incentives to attract migrants (from

whatever origin) to these essential jobs within our state’s economy.

2.3 A REVIEW OF SOCIAL CAPITAL THEORY

A common question these days concerns why it has become increasingly easy for
workers to enter the US. from Mexico, despite stepped-up border efforts. The answer
can be found in social capital theory”, which can be used to examine the accumulation of
relationships between Mexican populations north and south of the border. Social capital
provides the network, knowledge, and ﬁnancial means to bring friends and relatives from
home regions and villages in Mexico to the US.

As such, the number of Mexicans with US. experience has risen greatly since the
days of the Bracero Program. Phillips and Massey (2000) estimate that nearly one-half of
all Mexican men, from western Mexico, between the ages of 30 and 34 have been to the
US.13 In fact, in contemporary Mexican society it is common for one or more men from
a family to migrate to the US. at some point in their working lives. Through their
research, Phillips and Massey (2000) show that 64% of those of working age in their
sample report one or two prior U.S. trips and many reported making multiple trips,

“indicating a pattern of recurrent seasonal migration” (Phillips and Massey, 2000, p. 40).

 

l2Social capital is deﬁned by Robison, Siles, and Schmid (2001) as “. . .a person or
group’s sympathetic feelings of admiration, caring, concern, empathy, regard, respect,
sense of obligation, or trust toward another person or group” (p. 4).

‘3 Phillips and Massey’s 2000 study included a sample of 200 households in 38
communities in western Mexico.

29

For example, about 21% of working-age migrants reported ﬁve or more trips, 9%
reported 6-10 trips, 6% reported 11-20 trips, and 2% reported 20 or more trips to the US.
The number of Mexicans with US. connections is large. According to Phillips
and Massey (2000), “household heads reported having 3.4 immediate family members,
13.8 extended family members, and 11.6 friends with US. experience, yielding a total of
about 29 potential contacts for advice on crossing the border, getting a job, or making
one’s way in the US.” (p. 42). Respondents to Phillips and Massey’s survey had a mean
of 19.2 American contacts.
Thus, regardless of US. immigration policy, new migrants from Mexico
will ﬁnd a way to cross the border through their northern connections”.
Likewise, as populations grow and connections multiply, social capital will
continue to grow. Phillips and Massey (2000) conclude that
“stocks of mi gration-related human and social capital that have already
accumulated in Mexico will continue to serve as powerful engines of
emigration for years to come. Unless there are dramatic changes in the
binational political economy or shifts in the rules of the game along the

border, the United States can expect the continuation of large-scale
Mexican immigration well into the next century” (p. 46).

 

'4 According to Bustamante, Reynolds, and Hinojosa Ojeda (1992),

“At least ten percent of the growth of the US. labor supply in recent years
has been composed of Mexican migrants, with Mexican workers playing a
far greater role in the US. economy than do U.S.-Mexico trade, direct
foreign investment, or financial transactions. Native Mexicans working in
the United States... represent fully a ﬁfth of the Mexican-bom workforce,
and immigrant remittances to Mexico are just as important as oil exports
and net earnings from maquiladoras” (p. 1).

3O

2.3.1 Introduction to Social Capital Theory

An important component of this dissertation is the integration of social capital
theory with the traditional economic theory of supply and demand. According to
Bourdieu (1986), “it is impossible to account for the structure and functioning of the
social world unless one reintroduces capital in all its forms and not solely in the one form
recognized by economic theory” (p. 242). Robison, Siles, and Schmid (2001) deﬁne
social capital as “the feelings of goodwill, caring, and respect people have for each other”
(p. 2)15 . They also define it as “...a person or group’s sympathetic feelings of admiration,
caring, concern, empathy, regard, respect, sense of obligation, or trust toward another
person or group” (p. 4).

Lin (2001) describes social capital as “investment in social relations with
expected returns” (p. 6). According to Lin’s theory, four elements, including
information, inﬂuence, social credentials, and reinforcement, explain why social capital
works in “instrumental and expressive actions not accounted for by forms of personal
capital such as economic capital or human capital” (p. 7). First, social ties allow an
individual access to information about job opportunities and other life options that he or
she may not have had without such ties. Second, members of the same social set can
exert inﬂuence on behalf of one another in securing specific jobs. Third and fourth,
social tie resources and relations reinforce one’s membership within a group.

As two people (or groups of people) interact with one another, a rapport develops,

as do feelings of sympathy and caring for one another (Robison, 1999). Social capital

 

'5 This, and the following, definition actually describes positive social capital. Since we
are generally concerned with the positive connotations of social capital, we will continue
to call it simply ‘social capital’. Later in this chapter, negative social capital is deﬁned.

31

theory identiﬁes the recipient of this sympathy as the owner of social capital. “A person
or group having social capital has an important resource that may provide them
preferential treatment, access to information, and support from the social capital provider.
Social capital providers often alter the ﬂows of goods and services to benefit owners of
social capital because relationships of sympathy internalize the consequences of their
choices” (Robison, 1999, p. 4).

Social capital can also be described in terms of socio-emotional needs that must
be met. According to Robison and Siles (2000),

“It is well-established that individuals have social and emotional as well as

physical needs. Socio-emotional needs include the need for validation

(meaningful assignments), experiences of caring (friends), and

information ﬂows that communicate encouragement, support, and

acceptance. Just as physical needs are satisﬁed by physical goods, socio-

emotional needs are satisfied by socio-emotional goods. One important

characteristic of socio-emotional goods is that they must be obtained

directly or indirectly from others, including one’s ideal self. Our need for

socio-emotional goods provides an important incentive for investing in

and maintaining one’s social capital” (p. 4-5).

This being the case, it is worth considering the relationship between grower and migrant
in socio-emotional, as well as economic, terms. This is especially true for migrants who
may be lookin g towards growers for some degree of validation.

Robison, Siles, and Schmid (2001) describe the shared traits that originally entice
people to interact with one another as ‘kernels of commonality’. Such kernels, which can
be either inherited or earned, must be in place for a relationship to begin and social
capital to emerge. ‘Inherited kernels’ are traits about which we can do nothing, but
which offer us something in common with other people. Some examples include

nationality, gender, age, and the language in which we were raised. ‘Earned kernels’ are

those we attain through interest or experience (for example, where we go to school, club

32

memberships, illnesses overcome, or even hobbies). Robison (1999) argues that
relationships built on inherited kernels create stronger, longer-lasting bonds than do those
built on earned kernels. This is because “inherited kernels cannot be destroyed or easily
changed” (Robison, 1999, p. 5). Nevertheless, both inherited and earned kernels give us
something in common with others, which is key to starting new relationships.

Some kernels are more important than others (Robison, Siles, and Schmid, 2001).
Likewise, a kernel that is shared by only a few, and lasts over a period of time, tends to
be stronger. For example, during my son’s long battle with leukemia, we have met
numerous families whose children are battling the same disease. As relatively rare as
childhood leukemia is, this one earned kernel of commonality is equivalent to numerous
other inherited or earned kernels that we may have in common, yet is so overshadowing
that other kernels have only recently begun to surface. Acting alone, this one kernel has
been sufficient to foster much social capital development between our families.

In economic terms, the same can be said of grower families and migrant families
who have worked together for a number of years. Motivated by (and striving towards)
the same harvesting goal year-after-year, families get to know one another, moving past
cultural differences towards a sense of caring for one another. For migrants and growers
willing to bridge the cultural and economic gaps that divide them, the overall work
environment is improved. As described by several growers, trust and respect ensue.
Thus, this earned kernel of commonality works to reduce transaction costs for both sides.

Most relationships rely on multiple kernels. “As the number of shared kernels
increases, the strength of the relationship increases as well... When persons of different

cultures first meet, the search for kernels may require more effort than when persons

33

share a culture, particularly if they do not share a language” (Robison, 1999, p. 13).
Perhaps this explains why, to date, there are not more instances of strong social capital
development between growers and migrant farmworkers. While the effort required of the
two parties to acquire social capital is great, the value of the subsequent trust, respect, and
reduced transaction costs associated with social capital accumulation may not be
apparent.

Just as there are two ‘kernel of commonality’ types, there are also two kinds of
social capital. ‘Linking social capital’ emerges from earned kernels when two parties are
‘semi-socially close’. Robison, Siles, and Schmid (2001) assert that linking social capital
can be “characterized by moderately intense feelings of connectedness such as respect,
trust, and collegiality as might exist among colleagues, co-workers, and members of the
same club, community, or athletic team” (p. 6). ‘Bridging social capital’ develops in
more asymmetric situations, where contact between the individuals is limited, there are
fewer shared kernels, and resources vary greatly between the two parties. Robison, Siles,
and Schmid (2001) argue that bridging social capital develops between bosses and
employees, teachers and students, and others whose ‘ranks’ are not the same. Bridging
social capital plays a role in the relationship that develops between growers and migrant
farmworkers.

Another assertion of social capital theory is that, in certain situations, weak ties
are stronger than so-called strong ties. Referring to work by Granovetter, Robison (1999)
notes that social capital derived from earned kernels of commonality is oftentimes more
valuable in securing employment than is social capital derived from inherited kernels.

This is because people who share inherited kernels often share a wide pool of similar

34

traits. Likewise, their access to job information is similarly limited. But because
individuals with ties beyond their peer group are not so limited, they can use their earned
kernels to network far beyond their original peer group. To date, the demand for migrant
farm labor in the US. has been so great that inherited and earned kernels of commonality
have both played a role in supplying jobs to workers.

Schmid (2000) describes yet another situation, common throughout the
developing world, in which earned kernels have the potential to be enabling for an
individual whereas inherited kernels can be quite crippling. The situation described by
Schmid involves the gold craftsmen of Mali, all of who come from neighboring countries
to work in Mali. They have chosen not to set up businesses in their homelands since
relatives there would expect a share of the proﬁts. Such close kinship ties (via inherited
social capital) would obligate the artisans out of their savings, making it impossible to
reinvest and grow their businesses. In this case, inherited kernels of commonality are
actually harmful, particularly in today’s competitive economic setting. Earned kernels,
however, enhance the craftsman’s ability to get ahead financially. Since migrant workers
are known for sending much of their earnings back to their points of origin (an inherited
kernel obligation), the advantage associated with earned kernels of commonality is
probably most relevant when migrants choose to settle permanently in a community
where they have found work.

A last quality of social capital is that it can take on positive and negative
characteristics. Whereas the deﬁnitions cited at the beginning of this chapter pertain to
positive social capital, negative social capital has been deﬁned by Robison, Siles, and

Schmid (2001) as “a person or group’s hostile feelings of disgust, lack of concern,

35

antipathy, disregard, disrespect, lack of responsibility, or mistrust toward another person
or group” (p. 6). Where negative social capital reigns, repeat interactions between
individuals simply serve to reinforce negative stereotypes, fostering a mutual sense of ill
will. On occasion, negative social capital develops between growers and migrant
workers. Perhaps this explains why some growers are unable to ﬁnd sufﬁcient workers in
what is otherwise described by experts as a labor-rich environment.

In closing, an effective way to highlight the importance of social capital is to
envision a situation in which it does not exist. For example, foreign aid has failed time
and again because foreign aid recipients have not been included in the development
process (Schmid, 2000). As a result, no build-up of social capital ensued. Since the
intended recipients were not consulted to learn if the “aid” would help to ease their
burden, the good intentions of the so-called benefactors were received with malice
because of the way in which the gifts were delivered. A lesson from this ﬁnding is that
all parties involved in any difficult situation must be consulted for a truly workable
solution to be identiﬁed.

Thus, social capital theory helps to explain why it is important to obtain the views
of both growers and migrant workers when evaluating labor shortages. Taking into
account both points of view offers the best hope of delivering solutions that are amenable
to both parties. Areas of commonality and dissonance will be identiﬁed, serving as a ﬁrst
step towards developing the kind of improved communication necessary for additional
social capital accumulation. In turn, it is expected that this social capital accumulation

will lead to a better working environment for both parties.

36

2.3.2 The Promise and Limitations of Social Capital Theory

A major drawback to social capital theory is that it is still in an early stage of
development. Researchers from many different ﬁelds are working to incorporate it into
their paradigms, and academics and politicians are paying attention to it as well (Field,
2001). Nevertheless, measurement issues are a constant worry, and deﬁnitions seem to
vary from ﬁeld—to-ﬁcld. Yet Field (2001) states, “As the research ﬁeld matures, some of
the fog should lift, and it will become easier to see where the greatest policy returns can
be realized from investment in research on social capital and its measurement” (p. 55).

Nobody has yet proven that social capital can increase economic output (Field,
2001). According to Robison and Siles (1997), plenty of evidence points to the fact that
higher incomes are strongly correlated with higher levels of social capital. Ironically, it is
in well-developed economies where one ﬁnds the most impersonal transactions taking
place. Over time, these transactions have become plausible through the well-thought-out
placement of organizations and institutions for that purpose. Transaction costs are
greatly reduced or eliminated, in turn reducing the need for social capital.

This implies that if one can enhance a community’s sense of caring, an enhanced
level of trust will ensue, thereby reducing transaction costs (in part, at least, through
institutions) and enhancing a willingness to do business at a fair price. As observed by
Schmid (1999), “you don’t take advantage of a friend” (p. 164). All members of the
community beneﬁt and incomes rise, as long as they are the ones for whom the rules
were written. As Robison (1999) points out, “Institutions are rules, regulations, norms,

and values useful in regulating and ordering relationships. Organizations are groups of

37

persons with well-deﬁned membership requirements governed by institutions.
Organizations and institutions reﬂect the social capital ” (p. 5).

This dissertation examines what happens when a second party, like migrant
farmworkers, works its way into a system that was originally devised to look after the
rights of a ﬁrst party (i.e., growers). More speciﬁcally, how can social capital
accumulation be used to expand the base of beneﬁciaries that certain institutions
represent (Robison, 1999)? The assumption is that increased knowledge of one another,
and increased caring in the social capital context, will lead to a willingness among groups

to devise organizations and institutions that better serve both parties.

2.3.3 Relevant Studies Using Social Capital Theory

In recent years, numerous studies have used social capital theory as a tool for
exploring issues as diverse as small business development, minority characteristics in a
majority setting, migrant travel patterns, and entrepreneurial affairs. This section reviews

a series of studies that demonstrate the ﬂexibility of social capital theory and its relevance

to the study at hand.

2.3.3.1 Importance of Social Ties To the Success Rate of Agricultural Micro-
Enterprises in Ghana
The ﬁrst study explores the impact of relationships on how pairs of individuals
choose to do business with one another. Since some growers and migrants have arms-

length relationships while other relationships are like family, this study by Fergus Lyon

38

(2000) is of interest because it highlights the impact that even small actions can have on
building trust and, hence, the desire to work together year-after-year.

Noting “a lack of empirical work on the social relations of markets and how
actors build up trust that enables more complex exchange than spot transactions to take
place” (Lyon, 2000, p. 663), Lyon conducted a study of agricultural markets in Ghana,
focusing on the importance of social ties to the success rate of micro-enterprises. In the
rural parts of Ghana where the study was conducted, no formal legal institutions exist to
enforce business agreements. Rather, the two transacting parties totally rely on social
capital accumulation. Through his research, Lyon used social capital theory to identify
numerous social capital qualities that tie directly into the economic stability of Ghana’s
tomato subsector at the micro-enterprise level.

For example, Lyon learned that a tomato trader always knows where a tomato
grower lives and works. This knowledge is equivalent to a lien on a house in another
culture, in that it serves as a way to disgrace the grower into repaying money should an
unpaid loan be at stake. All the creditor needs to do is visit the ‘customer’ at home or
work, criticizing him or her publicly, thereby shaming and disgracing the person into
making a rapid repayment.

Likewise, as a type of business insurance, a trader always attends the funerals of a
customer’s family members. The trader’s attendance at (and contribution towards) a
funeral creates a moral obligation on the part of the grower towards the trader. As a
result, the grower will feel obligated to continue business dealings with the trader and
will feel compelled to repay all loans. Since moral obligations are taken very seriously

in this society, a social capital phenomenon like funeral attendance replaces the need for

39

legal institutions. Nevertheless, as Lyon learned, it also severely restricts the number of

people one feels comfortable doing business with, resulting in very high transaction costs.

2.3.3.2 The Role of Soccer Clubs in the Development of Migrant Networks from

Mexico

The second study examines community ties among migrant farmworkers in the
US, how much those ties are strengthened through regular, informal social gatherings,
and how important these gatherings are for job networking purposes. Had this study
omitted its social component, many determinants of economic decision-making by
migrant farmworkers in California would have been missed.

Douglas Massey (1986) applied social capital theory to his study of the role of
soccer clubs in the development of migrant networks from Mexico. Massey learned that
nearly one-half of all migrants from urban areas in Mexico join soccer clubs while living
in the Los Angeles, California area. “Sunday after Sunday, townspeople meet to watch
soccer and to socialize. This weekly reunion not only breaks up the routine of work, but
it also provides a regular forum for communication and exchange. By sponsoring the
regular interaction of townspeople, the soccer club serves as a clearinghouse for jobs,
housing, and other information” (Massey, 1986, p. 106).

Thus, this unusual source of social capital is responsible for informally matching
up employers with employees. It works in addition to family and paisanajem networks,

likewise channeling migrants towards job (and housing) opportunities throughout the

 

‘6 Paisanaje networks are those based on same communities of origin in Mexico. People
from the same community are obligated to help one another as they navigate their way
towards agricultural and other job opportunities throughout the US.

40

U.S. According to Massey (1986), such social networks offer jobs, housing, food,
transportation, and a social life to new migrants. “Their existence greatly reduces the

cost of US. migration permitting its regular and repeated use by Mexican families in a

conscious economic strategy” (Massey, 1986, p. 111).

2.3.3.3 Social Capital’s Minimization of Adverse Poverty Effects in Latino

Communities

The following study demonstrates that lifestyle decisions within the Latino
community are inﬂuenced by social capital, rather than only economic considerations.
Similarly, it is justifiable to assume that migrant workers use more than wage level, and
other economic criteria, when choosing a farm on which to work.

Denner, Kirby, Coyle, and Brindis (2001) use social capital theory to explain why
numerous Latino communities do well in all but economic terms. Success can be
measured other than economically. In particular, this group of researchers studied how
“four communities limit rates of teenage childbearing among Latinas, despite high rates
of poverty” (Denner, Kirby, Coyle, and Brindis, 2001, p. 4). The authors conclude that
communities with high social capital, or high levels of positive interaction with one
another, are better able to maintain cultural norms than are less uniﬁed communities. The

poverty in which they live is overshadowed by the social cohesion and resultant norms

that surround them.

41

2.3.3.4 Human Capital Resources as a Tool for Finding Work in the United States

Phillips and Massey (2000) use social capital theory to better understand migrant
farmworker travel patterns. By exploring the impact of social capital on the migration
patterns of migrant farmworkers from Mexico, Phillips and Massey learned that repeat
trips to the US, for the purpose of farm work, creates a wealth of human capital
resources on which numerous other individuals can draw. “People who have already
been to the US. are in a position to help friends and relatives travel northward, cross the
border, and obtain work by providing information, contacts, and material assistance”
(Phillips and Massey, 2000, p. 34).

This social capital phenomenon enables workers from the same location to travel
to the same destinations for farm work and establish ti ght-knit communities away from
home. After more than 50 years of building up social capital in this way, “this process of
social capital formation is well-advanced and largely self-sustaining. .. so that social

capital... is very widely diffused throughout the Mexican population” (Massey and

Espinosa, 1997, p. 989).

2.3.3.5 The Importance of Social Capital in Making the Right First Impression

In their study of what makes an entrepreneur successful, Baron and Markman
(2000) point to the initial importance of social capital. “Only candidates possessing high
levels of social capital are initially considered (for a kind of work)--persons with
favorable reputations, an established record in the ﬁeld, a degree from one of the right
schools, work experience with good employers, and so on” (Baron and Markman, 2000,

p. 108). However, they conclude that social capital only gets one in the door. At this

42

point, Baron and Markman conjecture that social skills” take over in establishing an
individual’s potential worth to an enterprise.

Different cultural viewpoints are expected to inﬂuence how one person perceives
another person’s social capital worth. If both parties are from the same background, the
social capital “ranking” is expected to be higher than if the two parties are from different
backgrounds, as in the case of the grower who must hire an unknown migrant worker.
Yet by hiring the friend of a trusted worker, it is expected that the social capital ranking
of that friend will be higher by association.

Thus, social capital encourages workers from the same origin to seek work at the
same farm and suggests that wages and perquisites alone do not explain worker

destinations and grower hiring practices.

2.3.4 How Social Capital Theory Will Enhance the Relevance of Traditional
Economic Theory
The social capital model recognizes that many (if not most) transactions take
place on a quasi-emotional level (Robison, Siles, and Schmid, 2001). In other words, our
feelings about (or toward) the person with whom we are doing business guide the path of
that business, particularly when the business takes place in a less formal setting”.
Business arrangements between growers and migrant workers are usually of this type,

taking place at the farm gate and involving somewhat arbitrary payment methods,

 

‘7 Social skills are defined as ‘speciﬁc competencies that help one interact effectively
with others’ (Baron and Markman (2000, p. 106).

‘3 In this instance, “informal” is defined as outside the modern market setting, where
buyers and sellers are frequently strangers and prices are set ahead of time.

43

especially when taking into account perquisites such as housing, transportation, or the
provision of childcare.

A corollary is that we rarely make decisions on our own, as isolated individuals.
Rather, we are constantly receiving information from the media, as well as from family,
friends, colleagues and acquaintances. Some of that input is actively sought. Other
times, it is absorbed subliminally, as a general feeling from our environment”. Since we
are unique, each of us is surrounded by a completely different set of contacts. Thus,
while we may feel as though we make our own decisions, we never really act ‘alone’.
One motivation for this is that we try to please others with our actions, acting in ways that
directly seek validation from those we care about (Robison, 1999). Field (2001) says we
are so engrossed in our surroundings that we generally overlook the fact that our
decisions are never truly made alone (Field, 2001).

The point of the above is that no action, not even a business transaction, takes
place in a vacuum. Likewise, the more informal the business environment (i.e., taking
place outside the conﬁnes of an institutional setting), the greater will be the social capital
inﬂuence between the two individuals conducting the transaction. Robison (1999) argues
that “...only when an economic good is exchanged without ﬂows of validation signals,
expressions of caring, and privileged information is the terms of trade likely to reﬂect the
good’s economic exchange value” (p. 16).

A study conducted by Robison and Schmid (1991) found that in a structured,

impersonal market, people generally compete with one another to amass wealth, along

 

‘9 Amin (1996) asserts that we live in a world of social contestation, where power
struggles affect all levels of society by determining who controls what resources. More
speciﬁcally, this social contestation inﬂuences what group is chosen to draw up
institutional rules and how these rules inﬂuence economic transactions.

44

the lines of the quote: “He who dies with the most toys, wins”. Yet in simple, two-way
transactions, Robi son and Schmid found that “sellers gave breaks to relatives and friends
while selling at the equilibrium market price to strangers and refusing to sell to those they
disliked” (Schmid, 2000, p. 163). Relationships distinctly inﬂuence how business is
transacted.

According to Glaeser er al. (2000), incorporating a social capital variable into the
neoclassical model should not be difﬁcult. They argue that “. . .social capital is a
meaningful, individual-level variable that can be studied with the tools of price theory...
Human capital includes not only cognitive and physical abilities but also social capital,
e. g. , interpersonal skills, status, and access to social networks” (Glaeser et al., 2000,

p. 841). This suggestion will be taken into account in Chapter 3.

In discussing how the social capital paradigm enhances the neoclassical model,
Robison, Siles, and Schmid (2001) argue that “ an absence of social capital in resource-
rich networks may create for the poor unfavorable terms and levels of trade and limit the
ability to take advantage of new economic opportunities... Absent linking social capital,
communities are likely to under—invest in public goods, an outcome whose negative
consequences fall disproportionately on the poor” (p. 21). Since social capital can alter
the ﬂow of goods and services (Robison, 1999), a goal of this dissertation is the
integration of social capital theory on behalf of both growers and migrant workers.

In closing, the inclusion of social capital theory in this dissertation is a strong
addition because of the simpler policy solutions it can point towards Giield, 2001).
Rather than expensive and incapacitating politically motivated policy solutions, such as

the recommendation for additional regulations concerning the hiring practices of growers,

45

this research seeks to identify simpler, more useful, cost-effective means for improving
relations between growers and migrant workers. This may result in a better supply of
migrant workers for growers and enable growers to keep good workers once they ﬁnd
them. After all, “many ﬁrms lose new employees due to poor management and poor
environments” (Baker, 2001, p. 9). If possible to raise social capital between growers

and migrant farmworkers, market efﬁciency should increase, leading to higher output

(Field, 2001, p. 56).

46

CHAPTER 3
THEORETICAL FRAMEWORK AND

METHODOLOGY

3.1 THEORETICAL FRAMEWORK

Since personal and social capital factors also inﬂuence the hiring decisions of
growers and work destinations of migrants, both social and economic variables must be
included in the modeling. This chapter presents the rationale for including social capital
variables and describes the migrant farm labor supply and demand shifters that must be

included in a conceptualization of this model.

3.1.1 An Integrated Interpretation of the Problem

A perceived undersupply of migrant farm labor in Michigan is the central problem
of this dissertation. In conjunction with a series of simplifying assumptions and the
maintenance of ceteris paribus conditions, neo—classical economic theory argues that the
wage rate (w) is established at the point where the supply (S) and demand (D) curves
intersect (Figure 3.1). A decrease in labor supply causes the supply curve to shift left (S ')
in response to fewer workers, while, in the short run at least, the demand curve (D ’)
remains unchanged. A new equilibrium wage rate (w’) is established at the intersection

of the D and 5’ curves. To maintain this new equilibrium level, wages must rise from w

47

in the original conﬁguration to w’ in the new conﬁguration. Thus, the observance of a

rise in wages would support the argument that migrant farm labor has declined in recent

years.

 

 

Wage
s 9
S
w,
W /
/ , D

 

 

 

 

L’ L Labor Quantity

Figure 3.1: A neo-classical supply and demand diagram in
response to a decline in labor supply

However, a preliminary analysis of available wage data provides inconclusive
evidence as to whether or not wages have risen in recent years. The grower survey
only requested wage data for the 2000 harvest season. This was because wages are
difﬁcult to estimate: 1) they can take many forms (hourly, piece rate, by the box, by
the bucket etc.), 2) frequently depend on the type of growing season (conditions
suited to a good crop or bad crop, for instance), and 3) may not be recalled with a

great degree of accuracy over time.

48

While lacking multi-year wage data from growers, it is possible to use data
obtained from migrant workers to identify trends in hourly wage rates. According to the
focus group migrant workers interviewed (N = 8), mean migrant incomes (attributable to
only Michigan farm work) rose by 9% between 2000 and 2001 and by 2% between 2001
and 2002 (Table 5.5). While this anecdotal evidence supports the labor decline argument,
it is not statistically signiﬁcant due to the small sample size. Further complicating the
issue, the respondents to the grower survey typically reported paying workers more than
minimum wage in 2000. Paradoxically, the migrant workers insisted that they rarely, if
ever, receive the minimum wage for their harvesting activities'.

The perceived decrease in migrant farm labor availability may be the result of
migrants seeking work in guaranteed, minimum wage jobs elsewhere in the economy.
While this would indicate that migrants are responding as rational decision-makers
(seeking employment where the money is higher, with full information available to
them), key informant interview indicated that migrants take many non-economic factors
into account when seeking work.

Assuming the growers typically pay higher than minimum wage, economic theory
suggests that rational—minded workers in the minimum wage service sector should seek
farm jobs where standardized and real migrant farm wages exceed service sector wages,

and where housing (a costly monthly expense in Michigan) is frequently provided.

 

' The mean standardized wage rates calculated for the four grower groups ranged from
$6.13/hour to $6.75/hour. This is 19% to 31% higher than the minimum wage rate of
$5.15/hour paid elsewhere in the economy. A mean standardized real wage rate was also
calculated, taking into account the perquisites such as housing that are frequently
supplied by growers as in-kind supplements to their earnings. Generally speaking, these
real wage rates were 4% to 44% higher than the standardized wage rates.

49

However, growers reported that fewer migrants are coming to their farms, which also
implies that non-economic factors may contribute to inﬂuence migrant employment
decisions.

As described in Chapter 2, social capital factors (e. g., the opportunity to work
with family members, to identify a ‘good’ farm through one’s home of origin
connections, or to maintain a friendly, comfortable relationship with a speciﬁc grower)
are likely to inﬂuence a mi grant’s target destination. Likewise, worker status inﬂuences
the employment options of a migrant worker. For example, an illegal immigrant, who is
afraid of deportation, will look for employment at an anonymous, out of the way farm,
rather than in a hi gh-profile factory or restaurant where he or she is more likely to be
noticed. On the other hand, a legal immi grant is free to seek opportunities where wage
rates are more central to the employment decision. Likewise, a lack of education (i.e., an
inability to speak, read or write English) is a barrier to many job possibilities, which may
explain why older migrant farmworkers tend to return to Michigan farms year-after-year
while their more educated children have an easier time securing non-farm jobs. Finally,
the focus group participants (all migrant students at MSU) consistently cited respect and
fair treatment by growers as important factors guiding their decisions about where to
work.

Interestingly, economists use the term ‘labor shortage’ differently from growers.
An economist considers labor to be an input that increases or decreases as the wage level
increases or decreases. Thus, a labor shortage can be corrected by simply offering
higher wages. On the other hand, growers feel that a labor shortage exists if the number

of migrant workers willing to work for a predetermined wage is insufﬁcient to harvest

50

their crop on time. Because growers have a ﬁxed wage rate in mind, they are unwilling
or unable to offer higher wages to attract additional workers. Thus, whereas the
economist sees a labor shortage as a problem that can be solved by increasing wages, the
grower sees it as a chronic problem with no solution.

The growers’ interpretation of a labor shortage is conﬁrmed by the responses of
roughly one-quarter of the grower respondents (across the four subsectors) who said they
had an insufﬁcient number of migrant workers to harvest their crops during the 1998-
2000 harvest seasons. This percentage, which ranged from 27% in 1999 to 22% and 23%
for 1998 and 2000, respectively), was highest among blueberry growers (Table 4.33).
Paradoxically, less than one-half of the growers who said they had insufﬁcient labor
reported leaving any acres unharvested in 1998 through 2000 (Table 4.34). These results
support that for a majority of the growers, a sufﬁcient (if not optimal) number of workers

were available to harvest their crop, raising doubt that they actually faced a labor crisis.

3.1.2 Proposed Determinants of Migrant Farm Labor Supply and Demand

Labor demand is impacted by external factors, including crop prices, government
regulations, and weather conditions (Table 3.1). Crop prices are primarily determined by
weather conditions, the state of the global economy and worldwide agricultural
competition, whereas government regulations (e.g., minimum wage, worker living
conditions, and the stringency with which workers’ immigration status is monitored) are
determined by the state and federal political climate. In turn, these factors (over time)
inﬂuence the demand for labor through their impact on growers’ decisions regarding crop

acreage, crop composition, and harvest mechanization investment decisions. These

51

shifters inﬂuence how many migrant workers a grower will employ in any given year, as

illustrated in Figure 3.2.

Table 3.1: Labor supply and demand shifters, and their potential impact
on supply and demand for migrant farm labor in Michigan

 

Labor Demand Shifters Impact on Labor Supply Shifters Impact on

 

 

 

 

Demand 5 Supply

Crop prices 5 I or T Higher wages elsewhere in E l

the economy
Crop acreage 1 or T Different types of job I

5 opportunities in MI (e.g.,

. service sector, landscaping)
Crop composition 1 or T More job opportunities I

' closer to permanent '

. residence 1
Mechanization of 1 Social capital networks I or T
harvesting equipment 5 leading workers to other

destinations - or more to
particular destinations in
l

 

 

 

 

 

 

MI

Stringency of govemment I or T Better information through I or T,
regulations concerning 5 Internet resources, leading 5 depending
worker status, living workers to better-payin g on farm
conditions, and wages 5 jobs or jobs with better

working conditions :
Number of family J, or T Availability of perquisites, T
members available to work 5 such as housing I
on farm 1
Weather conditions I or T Ability of family to stay T

together and work together 2

 

In contrast, the supply of labor offered by migrant workers is impacted by a
number of additional factors, especially (in recent years) growth in the number of
employment options, including different and higher wage job opportunities throughout
the economy (Table 3.1). Assuming their status in this country is legal, making such

positions easier to acquire, these opportunities offer more security and stability to

52

Global Economy Political Climate

I

 

Government Regulations
Crop Prices _ .
Weather Conditions
II
Wages
Crop Acreage
Crop Composition

it Family Workers

 

 

 

Available \ Mechanization
DEMAND FOR FARM LABOR
SUPPLY OF FARM LABOR
Higher Wage Opportunities \
Social Capital
Different Job Opportunities Ne‘wmkmg
Wages & Perqs
_ . Internet
Job Opporwmuw Closer Ability ofFamin Access
to Permanent Residence to Stay Together

 

 

 

 

 

Non-Farm Factors Farm Factors

\ /

Government Regulations

Figure 3.2: Schematic diagram of the factors that inﬂuence migrant
farm labor supply and demand in Michigan

53

families than traditional migrant farm labor work. Opportunities in the service sector

(e. g., fast food employment) or in agricultural, related enterprises (such as landscaping,
which has grown tremendously in recent years) are available in Michigan as well as other
parts of the country. These opportunities also offer migrant workers the option of staying
closer to their permanent residence (for example, in Texas or Florida) or resettling in
Michigan, where they may already have many contactsz.

In recent years, the Internet has likewise become a supply shifter within the farm
sector, inﬂuencing the work destinations of potential migrant workers. According to
several key informants, migrant workers in Texas can use the computer literacy and
language skills of their children to access migrant farm work information in Michigan. A
web site established by the Employment Services Agency in Michigan allows migrants to
compare the wages and living conditions of one farm against another, which better
enables them to target the farms on which to seek work. This information supplements
that of the already strong social capital networks, which use word-of-mouth
communication to draw members of the same home communities to farms with more
desirable working climates. Thus, Internet resources and social capital networks both
serve to attract workers to farms with higher wages and/or improved working and living
conditions.

In summary, growers face an increasing number of constraints that inﬂuence how
they do business. Associated with these constraints are a growing number of costs that

negatively impact an already financially compromised segment of our national economy.

 

2 This increased set of options implies that higher wages and improved perks are likely
necessary to draw traditional migrant workers back to the ﬁeld since growers must now
contend with their competitors, adding to their cost of doing business.

54

In contrast, an increasing number of options are becoming available to migrant workers.
More options imply more possibilities for moving away from migrant farm labor, an
obvious choice in light of the hard labor and low wages associated with migrant farm
work. Historically, Asian and European immigrants participated in the U.S.’s migrant
farm labor work force but used their experience as a means towards eventually obtaining
more rewarding work. Today, it appears that the predominantly Hispanic farmworkers

are following a similar path, given that better-paying, more rewarding jobs are now in

their grasp.

3.2 METHODOLOGY

In this study, a modiﬁed rapid appraisal, a grower survey, a migrant worker pilot
survey, and a migrant worker focus group were used to collect data required to analyze
factors that explain the perceived shortage of migrant farm labor in Michigan.

A modiﬁed rapid appraisal was used to collect quickly much disparate
information about Michigan crops that require the employment of migrant farm labor. A
rapid appraisal is described by McCracken, Pretty, and Conway (1988) as a timely,
iterative, interactive way to assemble information from a variety of sources about a
specific topic. The rapid appraisal was ‘modiﬁed’ in the sense that a single individual,
rather than a multidisciplinary team, compiled the requisite information with experts in
the ﬁeld. Throughout the rapid appraisal, the assembled data were continually shared
with the key informants in order to resolve inconsistencies and solicit their insights
regarding the observed trends. This information served as the core source of information

used to generate the study’s hypotheses and design the research study.

55

The original intent of this study was to survey a sample of both growers and
migrants in Michigan. Staff of the Julian Samora Research Institute (J SR1), at Michigan
State University (MSU), agreed to interview the migrants, this researcher would survey
the growers, and the information obtained from each group was to be shared equally by
the two sets of researchers.

Disappointingly, a number obstacles and rniscommunications led to the
dissolution of this collaborative effort. The grower survey continued as planned, but a
new approach was needed to collect similar data from migrant workers, hence reverting
this round of data collection to a pilot survey and focus group. With assistance from the
College Assistance Migrant Program (CAMP) at MSU, the on—campus ofﬁce that recruits
migrant students as undergraduates, a small sample (n = 10) of migrant workers were
recruited to participate in a pilot survey3. Likewise, migrant students attending MSU (n =
8) were invited to participate in a focus group in order to validate and supplement the
data obtained from Michigan migrant farmworkers.

The rest of this section elaborates on the four research components to this study.

3.2.1 Modiﬁed Rapid Appraisal

In Fall 1999, a modified rapid appraisal was carried out to collect background
information on factors that affect the supply of and demand for migrant farm labor in
Michigan. After reviewing the literature, key individuals were contacted to gain insights

on issues related to migrant farm labor, including farm leaders, extension staff,

 

3 Henceforth, this portion of the study is henceforth referred to as a pilot survey, rather
than a survey, because of the small number of respondents and the potential bias
associated with how the sample was obtained.

56

commodity groups, Michigan Department of Agriculture staff (including those on the
recently-formed Jobs Commission Task Force which has a mandate to analyze farm labor
issues), state legislators/staff with expertise in migrant labor issues, Michigan Farm
Bureau members, and Michigan’s several migrant service agencies.

Information collected at these meetings served to inform the types of questions
that were included in the grower and migrant surveys. Likewise, as information was
gathered and more questions arose, these key informants were contacted to clarify details
about the key issues and problems associated with migrant farm labor in Michigan. The
modiﬁed rapid appraisal provided the opportunity to quickly gain a thorough

understanding of the problems faced by both growers and migrant farmworkers.

3.2.2 The Survey and Pilot Survey Populations

The sample of Michigan growers and migrant farmworkers were selected as

described below.

3.2.2.1 Targeted Growers

MSU’s county extension agents (MSUE), who worked in areas of the state where
apple, asparagus, and pickling cucumber growers are widely grown, were contacted and
asked to assist in identifying growers of these crops and to mail out surveys to ensure the
anonymity of the growers. Blueberry growers were identiﬁed through two commodity
groups, the Michigan Blueberry Growers Association (MBGA) and the United Producers

of Michigan (UPM). Representatives of these groups mailed out the blueberry surveys.

57

In 2000, there were approximately 1,100 apple growers in Michigan (MASS,
2000). Of this total, 37% (representing 56% of Michigan’s apple acreage) lived in eight
counties—Berrien, Ionia, Kent, Manistee, Montcalm, Muskegon, Newaygo, and Ottawa
county (Figure 3.3). The survey was mailed to 270 growers (25% of the state’s apple
growers) in these target counties. 3

In 2000, there were approximately 410 asparagus growers in Michigan (MASS,
2000). Of this total, 70% (representing 89% of the state’s asparagus acres) lived in eight
counties—Berrien, Manistee, Mason, Mecosta, Oceana, Ottawa, St. Joseph, and Van
Buren counties. The survey was mailed to two-thirds of the growers (46% of the state’s
asparagus growers) in the target counties.

In 2000, there were approximately 575 blueberry growers in Michigan (MASS,
2000). Of this total, 81% (representing 95% of the state’s blueberry acreage) lived in ﬁve
counties—Allegan, Berrien, Muskegon, Ottawa, and Van Buren county. The survey was
mailed to 240 growers (42% of the state’s blueberry growers) in the target counties.

In 2000, there were approximately 160 pickling cucumber growers in the state
(MASS, 2000). Of this total, 20% of the state’s growers (representing 15% of
Michigan’s cucumber acreage) lived in four counties—Manistee, Montcalm, Newaygo,
and Oceana county. However, it was only possible to obtain a list of twenty pickling
cucumber growers, due to the large size of these enterprises and the reluctance of the
hi gh-proﬁle ﬁrms associated with this industry (e.g., Vlasic and Heinz) to identify their
contract growers. The survey was mailed to the 20 pickling cucumber growers in the
target counties. Despite the difficulty in selecting a representative sample of pickling

cucumber growers, pickling cucumbers were included in this study for the insight they

58

 

_ . Mum: m 5““.
more . . '
claim .
SW . van '

4'5

 

1M $91”er m

. mu:

 

 

 

124 _
Surveyed Counties: %

1- apple m 14, 2
2- asparagus 24%;.QP We

3 - blueberry 13' 3?. 1 .444 “W"? W um
4 ' pICRlc 16"”! m mm mm. 911‘- f 4 4,

 

 

 

 

' w

s" 51%.“

 

 

 

 

 

123—5., 4 4 4 5
[3111mm we atrium m mo

 

 

 

st.~ .

 

~ WH-

 

 

 

. rost'm 1&5 taunt!

Figure 3.3 A map showing the counties targeted by the grower survey

(Michigan, 2000)

59

have to offer regarding a different type of migrant labor usage. Nevertheless, given their

small number, pickling cucumber data can only be reported as anecdotal ﬁndings.

3.2.2.2 Targeted Migrant Farmworkers (Pilot Survey and Focus Group)

The College Assistance Migrant Program identiﬁed 30 migrant farmworker
families, ten of whom agreed to respond to the written migrant survey during Fall 2002.
Since each family was an acquaintance of a student studying at MSU", the respondents do
not represent a random sample of Michigan migrant workers. Thus, due to the small size
and nature of the sample, data are reported as a pilot survey.

In addition, to supplement the pilot survey ﬁndings, a focus group involving MSU
migrant students (n = 8) was conducted. Held in February 2003, the focus group served
as a source of additional feedback from students who have spent their lives in migrant

farm working families.

3.2.3 Survey Instruments
Three surveys were designed to collect data for this study--a grower mail survey,

a supplemental grower mail survey, and a migrant pilot survey. Each survey was written

in collaboration with Dr. Richard Bemsten, a data collection and survey specialist.

 

‘ These same MSU students were asked to administer the survey to respondent families,
since the families were described as wary of outsiders. Although a degree of bias may
have been introduced by having the students administer the survey, this bias was less

signiﬁcant than the likely bias that would have resulted from having the researchers ask
the questions.

60

Likewise, each survey was written with the assistance of crop specialists and extension
agents from around the states.

In Fall 2000, the mail survey was sent to apple, asparagus, blueberry, and pickling
cucumber growers. In addition, a supplemental survey was sent to blueberry growers"
(Appendices A and B, respectively). The survey of migrant farmworkers was conducted
in Fall 2002 (Appendix c7).

Since available Michigan farm labor and wage rate data do not classify hired
farmworkers by migrant or local hire status, the grower survey was constructed to collect
information needed to calculate migrant worker supply, demand, and wage rate statistics.
In addition, the surveys were designed to generate data required to carry out a regression

analysis to identify the supply of and demand for migrant farm labor.

3.2.3.1 Grower Mail Survey
To document recent trends in wage rates and labor supply, as well as the growers’
perceptions regarding the magnitude of migrant farm labor supply problems, the mail

survey solicited data from growers to determine, among other things: 1) the number of

 

5 For example, Professor Don Ricks was a crucial contact for identifying questions to ask
apple growers, and the three other growers. In particular, he offered advice about how to
phrase questions so the responses could be interpreted with the least degree of ambiguity.

6 The survey was ﬁrst mailed to blueberry growers. Given the unexpectedly high number
of blueberry growers who did not hire migrant labor in 2000, the survey for apple,
asparagus, and pickle growers was modified to obtain additional information about
growers who do not use migrant labor. This supplemental survey was also sent to all

blueberry growers targeted by the ﬁrst survey, in order to gather the same kind of
information.

7 The migrant pilot survey was mailed nearly two years after the grower survey, partly
because of the difﬁculty of ﬁnding a reliable migrant farmworker connection and partly
because the results of the grower survey were needed to determine the line of questioning
for the migrant farmworkers.

61

migrant farmworkers hired in each of the previous three years and the period during
which they were employed, 2) the number of migrant farmworkers actually needed
during each of the previous three years to harvest crops, 3) the percentage of all hired
laborers which migrant farmworkers represented, 4) the wage rates paid to migrant
workers, 5) the types and value of perquisites (particularly housing) offered to attract
migrant workers, 6) methods used to recruit migrant labor, 7) farmers’ assessment of
whether the supply of labor has been sufﬁcient to meet his/her labor demand and, if not,
what factors contributed to the shortage, 8) costs, other than wages and perquisites,
associated with hiring migrant labor, 9) the cost of the next best alternative (non-migrant)
source of farm labor, and 10) crop land area and value (if any) lost because of a shortage
of harvest workers.

To assess future trends in the supply of and demand for migrant labor, the grower
survey solicited information regarding both: 1) the growers’ assessment of the factors that
are likely to increase/decrease their demand, and 2) the growers’ assessment of the future
supply of migrant labor and factors that are likely to increase/decrease the supply.

To facilitate analysis of these data by type of enterprise/crop, additional data were
collected including farm size, crops grown, area planted to each crop, gross farm
revenues, percentage of production value attributable to apples, asparagus, blueberries or

pickling cucumbers, and agricultural production value harvested by migrant workers.
3.2.3.2 Migrant F armworker Survey

The survey of migrant farmworker families solicited information on the

following: 1) wages received during each of the past three years, 2) location of permanent

62

residence, 3) migratory work pattern during atypical year and number of years seeking
work in Michigan, 4) months spent in the state during the past three years, 5) reasons for
seeking work in Michigan, 6) how they identify farm labor opportunities, including work
in Michigan, 7) positive/negative aspects of working as a farm laborer in Michigan, as
compared to other states, 8) impressions regarding the apparent labor shortage (i.e.,
increased/decreased difﬁculty of ﬁnding work), 9) the amount of their earnings spent on
food, clothing, rent, services, entertainment, and other expenses while in the state of

Michigan, and 10) the ages of family members traveling and/or working with the laborer.

3.2.4 Data Analysis

Logit regressions are estimated to identify the variables that influence the labor
decisions made by growers and migrant farmworkers. To transform the survey data into
variables to be used in the analysis, a few preliminary steps are necessary. The ﬁrst step
is to construct several new variables. For example, perquisites must be assigned
estimated values and real wages must be calculated for workers, based on the perquisites
received at their places of employment. Second, information obtained from migrant
workers about how they allocate their earnings is used to generate an estimate of the
percentage of migrant farm earnings returned to the state of Michigan.

For statistical comparisons, two-sample t-tests and chi-square tests are performed.
Given the levels of non-response, these tests do not provide quantiﬁable inferences for
the populations but rather serve as descriptors of the sizes of the sample differences. If

outliers are removed for the analyses, this will be noted.

63

3.2.4.1 Valuation of Perquisites

Perquisites received by farmworkers were assigned estimated weekly values in
the following manner. First, the cases were divided according to which perquisites the
respondents provided. For example, growers who supplied an end-of-season bonus were
separated out from growers who did not. Within this sub-group of bonus providers, a
mean perquisite value was calculated based on the responses of growers who assigned a
value to the respective perquisites. In some instances, this mean value was based on
numerous responses; in other cases, it was based on only a small number of responses.
This estimated value was then assigned to all respondents who reported offering the
perquisite but did not estimate its value. For all other respondents who reported the value
of this perquisite, the actual value they assigned was retained. This process was repeated
for all perquisites, and then these values were summed case-wise to estimate the weekly

value of perquisites offered by each grower.

3.2.4.2 Standardized Wage Calculation

The wages reported by each grower were standardized by ﬁrst normalizing the
data across the different units of pay. For example, some growers paid by the hour,
others by the bushel, bin, pound, bucket or piece in 2000, depending on the crop and type
of farm operation. Thus, it was ﬁrst necessary to estimate the mean number of bushels,
bins, buckets or pounds harvested per hour, in order to compute a standardized hourly
wage for each case. For example, since $/lb/$/hr = hr/lb, the known values for $llb and
Mn make it possible to calculate how long it took (in hours) to harvest each unit type.

Then, this number was substituted for the non-hourly payment unit for each unit type and

64

multiplied by the cost per harvest unit to calculate a standardized hourly wage for each

C386.

3.2.4.3 Real Wage Calculation
The real wage paid by growers is deﬁned as:
migrant real wage = standardized wage + housing value + total perquisite value.
For each case, a “real hourly wage” was calculated by first converting the housing value
(i.e., rent and utilities) and total perquisite value (i.e., transportation, daycare, or bonus)

to an hourly rate; and then adding these values to the standardized wage rate.

3.2.4.4 Calculation of Earnings Percentages Returned to the State of Michigan By
Migrant Workers
The migrant farmworker survey asked the ten respondents to estimate their
weekly expenditures on typical purchases such as food, clothing, and medicine. These
figures were then summed and multiplied by the number of weeks the family did migrant
farm work in Michigan. A ﬁnal calculation involved estimating the percentage of each

migrant family’s annual farm work earnings spent in the states.

 

8 Given the small sample size on which these calculations were based, and the degree of
data processing involved, the results may not be considered reliable. They are provided
solely as an indicator about what a future, more extensive study may reveal.

65

3.2.5 A Logit Regression Model that Explores the Determinants of Having

Sufﬁcient Migrant Farm Labor

This section presents a logit regression model that was estimated to identify
factors associated with the growers’ assessment that they did/did not have sufﬁcient
migrant farm labor during the 2000 harvest season, including both economic and non-
economic factors, as discussed in the theoretical framework.

A logit model is selected for this analysis because of the dichotomous nature of
the dependent variable (e. g., did/did not have sufﬁcient harvest labor). Although probit
or logit models give equivalent results when the sample size is small (it = 79)9, the logit
model is easier to estimate using SPSS, the statistical package used in the analytical
component of this study. Generally speaking, the cumulative normal distribution is taken
into consideration when working with the probit model, while the logistic distribution is
associated with the logit model. i

The regression relationship is described as follows:

y3=ﬂm+ui
where y‘; is unobservable yet influenced by a number of factors x; . y'i can be replaced
by a dummy variable y such that
y=1 if y‘i>0,or
y = 0 otherwise.
In this model, Maddala (1990) defines B'xi as E (y‘i | xi), with

Prob (y; = l) = Prob(ui > -B'xi) = 1 — F(-B'xi) (p.22).

 

9 According to Maddala, “Because the cumulative normal distribution and logistic
distribution are very close to each other, except at the tails, we are not likely to get very
different results using... the logit or the probit method, unless the samples are large (so
that we have enough observations at the tails” (Maddala, 1990, p. 23).

66

In the logit model, the functional form for F depends on the logistic distribution and can
be written as:
F(-B'xi) = [exp(-B'xi)]/[l + exp(-B'xi)] = 1/[1 + exp(B'xi)].
Subtracting F(-B'xi) from both sides of the equation gives:
1 - F(-B'xi) = [CXp(B'xi)]/[ 1 + CXP(B'xi)]-

Returning to the regression relationship cited at the top of this page and

displaying the vector components of xi gives:
ENOUGHOOij = anEii + Bierii + Bisjwii + Bi4j51i+B155Rri + Ulij
where Y. = 0 if ENOUGHOOij _<_ O
1 if ENOUGHOOij > O
and ENOUGHOO = sufﬁcient workers in 2000.

In the above equation, E represents the economic vector. It consists of the
standardized hourly wage and the real hourly wage paid to migrant workers.

Vector F represents farm characteristics, including the grower’s main crop, farm
earnings per acre, farm earnings per acre on a large versus small farm, migrant days per
acre of crop of interest, migrant payroll as a percentage of farm operating expenses,
number of years spent hiring migrant farmworkers, and mean hours per week spent off-
farrn at another job. As reported in Chapter 4, these vector components are used in
different combinations in the regression presentation. Some of these independent
variables could be included in the economic vector, but are included here instead since
they ﬁt in better as statistics that describe the ﬁnancial size of the farm than as factors

that might encourage migrants towards or away from a particular harvesting job.

67

Vector W represents the work environment, including the percentage of migrants
living off-farm, as well as the number of perks provided to the migrant workers"). These
independent variables are similar to social capital variables in that they are non-economic
indicators that work separately from economic incentives, such as wages, to attract or
deter migrant workers towards or away from a particular farm. Like wages, they are
expected to inﬂuence where a migrant seeks employment.

Vector S represents social capital variables, including non—economic variables
such as Spanish fluency level, the percentage of migrants that have worked on the farm in
the past, the percentage of migrants that have worked on the farm for ﬁve or more years,
and the point of origin (home location) of the workers on each farm.

Vector R represents recruitment methods that growers use to attract migrant labor
to their farms. Vector U represents the error term.

The above vector series closely follows the vector components of Strauss’s
marketed surplus model (1984) and is similar to one used by Miklavcic (1995) to
examine the determinants of farm household participation in an income-generating
activity. In addition, it takes into account Glaeser’s et al. (2000) observation that
incorporating a social capital variable into the traditional economic model is not difﬁcult.
“Social capital is a meaningful, individual-level variable that can be studied with the tools
of price theory. Human capital includes not only cognitive and physical abilities but also

social capital, e. g., interpersonal skills, status, and access to social networks” (Glaeser er

al., 2000, p. 841).

 

'° Note that real hourly wage and number of perks are never contained in the same

regression trial since the latter variable is endogenously accounted for in the real hourly
wage variable.

68

3.3 CONCLUSION

This chapter provides the rationale for utilizing a modeling framework that
incorporates both economic and non-economic variables to identify factors associated
with the decision-makin g paths followed by both growers and migrant workers in
Michigan. It also describes independent variables that are included in the logit regression
for analyzing the determinants of sufﬁcient migrant farm labor supply on Michigan

farms. This regression includes economic, farm characteristic, work environment, social

capital, and recruitment method vectors.

69

CHAPTER 4

GROWER SURVEY RESULTS

4.1 CHARACTERISTICS OF THE SURVEY POPULATION

This chapter characterizes the sample of growers surveyed, reports the results of

the grower survey, and presents the findings of the regression analysis.

4.1.1 Response Rate

According to MASS, Michigan had 52,000 growers across all commodities in
2000. Apple, asparagus, blueberry, and pickle growers comprised 4% of this total. Of
the 2,205 apple, asparagus, blueberry, and pickle growers in-state, this survey was sent to
33% (n = 720), with 310 ﬁlled out and returned (43% of the surveyed growers). When
broken down by subsector (Table 4.1), the data show that 32% of targeted apple, 29% of
targeted asparagus, 59% of targeted blueberry, and 50% of targeted pickle growers
responded to the survey. Although lower than the barer feasible 60% response rate

desirable for a mail survey (Salant and Dillman, 1994), D88 Researchl claims that a 10%

 

‘ DSS Research, a ﬁrm based in Arlington, TX, conducts mail surveys for research
purposes.

70

to 15% response rate is common for a mail surveyz, although high involvement issues, as
in this case, typically command a 30% to 50% response rate (DSS Research, 2001). In

this context, the response rates for apple, asparagus, and blueberry growers are

 

 

 

 

 

 

acceptable.
Table 4.1: Response rate, by subsector (Michigan, 2000)
Crop Surveys sent Responses Grew crop and hired
receiveda migrants"
Apple 270 85 53
(32%) (61%)
Asparagus 190 73 31
(38%) (42%)
Blueberry 240 142 32
(59%) (23%)
Pickle 20 10 10
(50%) (100%)
Total 720 310 126
(43 %) ' (41%)

 

 

 

 

 

 

a - The first number per cell is the number of respondents; the number in
parentheses is the response rate per surveys sent.

b - The ﬁrst number per cell is the number of respondents; the number in
parentheses is the percentage of respondents per responses received.

On the other hand, although 50% of the pickle growers returned their survey, the
sample size (n = 10) was small and only a small percentage of the population was
sampled. Therefore, the pickle data are included in the statistical means, but not
compared statistically against any of the other target groups.

The varying response rate among subsectors may be due to the degree to which

growers are concerned with the problem of farm labor. Prior to conducting the survey,

 

2 Such a response rate, however, is unavoidably biased since 85-90% of the targeted
population is not represented in the data.

71

numerous blueberry growers contacted by the researcher complained about a labor
shortage. Thus, because of their concern about the problem, it is likely that they were
more inclined to return (59%) the survey. Another possible explanation may be how the
grower lists were obtained. Whereas regional extension ofﬁces3 provided the lists for
apple, asparagus, and pickle growers, blueberry growers were surveyed through two
grower associations-- the Michigan Blueberry Growers Association and the United
Producers of Michigan. Perhaps association afﬁliation prompted a stronger response than
extension afﬁliation. A third explanation may be that the survey was long. Potentially
less-concemed apple and asparagus growers (with respective response rates of 32% and
38%) may have thought that answering the questionnaire was too taxing.

Of the growers who responded to the survey, 59% of the respondents (n = 184)
either did not grow the crop in question or did not hire migrant labor in 2000. These
numbers were unexpectedly high. The ﬁnding that a large number of growers no longer
grew the crop in question is likely due to the dynamic nature of farming in Michigan.
Even though the target lists were relatively current, some growers had changed their
crops. For example, some growers reported that they had cut down their apple trees to
make room for other, more proﬁtable crops. A number of respondents also reported
selling much of their cropland.

While it would have been desirable to target growers who had hired migrant
workers in the past, no such sampling frame was available. In addition, some farmers

who previously hired migrant labor may not have hired migrants in 2000 because they no

longer planted the target crops.

 

3 These extension ofﬁces were primarily situated in southwest Michigan, where most of
these four crops are grown.

72

Respondents who did not grow the crop in question or who did not hire migrant
labor in 2000 were excluded from the statistical analyses that follow. This study is based
on the responses of 126 growers--53 apple growers, 31 asparagus growers, 32 blueberry

growers, and 10 pickle growers--all of who hired migrant labor for apples, asparagus, or

blueberries in 2000.

4.1.2 Characteristics of the Survey Participants

The characteristics of the survey respondents are presented in the following sub-
sections. However, these respondents may differ from the growers who chose not to
respond. It is likely that the sample of growers who returned the questionnaire were more

concerned about a labor shortage than the non—respondents.

4.1.2.1 Grower Distribution by County

The apple data (n = 53) were provided by growers from eight counties. Kent and
Ottawa counties accounted for 65% of the total sample (Table 4.2). As these two
counties are among Michigan’s largest apple-producing regions (Section 3.2.2.1), this
indicates that the respondents constitute a fairly representative sample of Michigan’s
apple growers. In addition, apple growers in Berrien, Ionia, Manistee, Montcalm,
Muskegon, and Newaygo counties also responded to the survey. In total, 8% of
Michigan’s apple grower population responded to the survey.

The asparagus data (n = 31) were provided primarily by growers from Oceana and
Mason counties (68% of the 31 responses), although Allegan, Benzie, Manistee, and

Ottawa counties were also represented. These counties account for nearly 90% of

73

Michigan’s asparagus acreage. In total, responses were obtained from 18% of
Michigan’s population of asparagus growers.

The blueberry data (n = 31) were provided mainly by growers from Ottawa and
Van Buren counties (81%), while Allegan and Muskegon counties were also represented.
These four counties account for 95% of blueberry acreage in Michigan. Twenty—ﬁve

percent of Michigan’s blueberry grower population responded to the survey.

Table 4.2: Distribution of respondents, by county and subsector (Michigan, 2000)4

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Countya Apple Asparagus Blueberry Pickle Total
Kent 24 0 0 0 24
(45%) (19%)
Manistee 0 0 0 6 6
(60%) (5%)
Mason 0 9 O 0 9
(29%) (7%)
Oceana 0 12 0 2 14
(39%) (20%) (1 1%)
Ottawa 1 I 2 12 0 25
(20%) (7%) (39%) (20%)
Van Buren 0 0 I3 0 13
(42%) (10%)
Other 18 8 7 2 35
(35%) (25%) (19%) (20%) (28%)
Total 53 31 32 10 126
(100%) (100%) (100%) (100%) (100%)

 

 

a - The ﬁrst number per cell is the number of respondents; the number in
parentheses is the percentage of respondents by county.

The pickling cucumber data (n = 10) were mainly provided by growers from

Manistee County (60%). Responses were also obtained from Oceana, Montcalm and

 

" These data represent the respondents who grew the target crop and hired migrant farm
labor in 2000. Listed separately are the counties with the highest number of respondents.
Other counties are combined under ‘Other’.

74

Muskegon counties. This total represented eight percent of the pickling cucumber

population in Michigan.

4.1.2.2 Grower Experience Working on a Farm and Hiring Migrant Farmworkers

Across the four target subsectors, growers had worked on a farm for a mean of 30
years. This high level of experience indicates that the growers are well versed in the issues
addressed by this survey. As of 2000, apple growers had worked on farms for the longest
time (31 years), followed by asparagus (29 years) and blueberry growers (28 years). Among
growers in the three primary subsectors (i.e., subsectors with a large enough sample size for
statistical comparisons), farm experience varied very little (Table 4.3) and differences were
not statistically significant (2-tailed t-test, 5% level). The ten pickle growers had worked on
a farm a mean of 33 years.

Growers in the four subsectors had raised their target crop for a mean of 27 years.
Apple growers had grown apples for the longest amount of time (30 years), followed by
asparagus (24 years) and blueberry growers (27 years). However, the difference between
grower’s mean years of target crop experience was only signiﬁcantly different for apple
and asparagus growers. This is likely because asparagus did not become a prominent
Michigan crop until the 197055. The ten pickling cucumber growers had only grown this
crop for a mean of 16 years.

Growers from the four target subsectors had managed a farm for a mean of 24

years. However, there were no signiﬁcant differences by grower type. Pickle growers

had run a farm for a mean of nearly 27 years.

 

5 The Michigan Asparagus Advisory Board was established in 1978.

75

Growers from the four target subsectors had hired migrants for farm labor for a
mean of 21 years. Apple growers had the most experience (23 years), followed by
blueberry (21 years), and asparagus growers (16 years). The difference in these means
was statistically signiﬁcant between apple and asparagus growers. The ten pickle
growers had hired migrant farmworkers a mean of 21 years.

Table 4.3: Grower experience working on a farm and hiring mi grant farmworkers,
by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

 

 

 

Mean years“ Apple Asparagus Blueberry Pickle
(n = 52) (n = 31) (n = 32) (n =10)

Worked on a 31 29 29 33

farm" (13) (12) (12) (12)

Grew target 30 24 27 16

cr0pc (14) (8) (11) (8)

Managed 24 23 23 27

farm" (13) (13) (12) (11)

Hired 23 16 21 21

migrantc (12) (9) (12) (7)

a - Standard deviations are given in parentheses.

b - Two-tailed t-test shows non-signiﬁcant difference across the primary crop
pairs.

c - Two—tailed t-test shows significant difference for apple-asparagus pairing
(si g = .009).

e - Two-tailed t-test shows significant difference for apple-asparagus pairing
(si g = .007).

4.1.2.3 Crop Acreage

Asparagus growers had the largest farms (545 acres), followed by apple (439
acres) and blueberry growers (435 acres) (Table 4.4). However, the differences in the

primary subsectors were not statistically signiﬁcant. Pickling cucumber growers’ farms

averaged 323 acres.

76

Asparagus growers planted the largest acres to annual crops, followed by
blueberry (149 acres) and apple growers (63 acres). However, the difference in mean
acreage planted to annual crops was only signiﬁcant between apple and asparagus

growers. Pickle growers planted an average of 197 acres to annual crops.

Table 4.4: Mean farm size and acreage planted to annual and target crops, by

 

 

 

 

subsector (Michigan, 2000)
Mean acreageal Apple Asparagus Blueberry Pickle

(n = 52) (n = 31) (n = 32) (n =10)
or overall farmb 439 546 345 323

(481) (606) (793) (276)

Planted to annual 63 188 149 197
crops“ ( 109) (286) (549) (251)
Planted to target 246 97 I6] 60
cropc (318) (90) (221) (55)

 

 

 

 

 

 

 

a - Standard deviations are given in parentheses.

b — Two-tailed t-test shows non-signiﬁcant difference across the primary crop

c - gtfitailed t-test shows signiﬁcant difference between apple and asparagus
growers (si g = .002).

Apple growers planted the largest area to their target crop (246 acres), followed
by blueberry (161 acres) and asparagus growers (97 acres). The difference in mean
acreage planted to target crops was only significantly different between apple and
asparagus growers. Pickle growers averaged 60 acres of pickles.

Apple growers allocated the highest share of their land to the target crop (56%),
followed by blueberry (47%) and asparagus growers (18%). These data indicate greater

diversification among asparagus growers than apple growers. Pickle growers planted

19% of their land to pickling cucumbers.

77

4.1.2.4 Off-Farm Work

Asparagus growers were most likely to work part-time off-farm (32%), followed
by apple (23%) and blueberry growers (22%) (Table 4.5). However, these differences
were not statistically signiﬁcant (chi-square test6, 5% level). These results likely indicate
that, due to low crop proﬁtability, many growers in each subsector ﬁnd it necessary to

seek off-farm employment part-time. Among pickle growers, 20% sought off-farm work.

Table 4.5: Percentage of growers who work off-farm, number of hours/week they
spent working elsewhere, and the number of extension meetings
attended annually, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

 

Meana Apple Asparagus Blueberry Pickle
(n=53) (n=31) (n=32) (n=10)

Growers who work 22.6% 32.3% 21.9% 20.0%

off-farm (%)b (12) (10) (7) (2)

Hours/wk at 31.7 36.4 39.4 30.50

off-farm job“ (14.2, 11) (17.7, 9) (14.8, 6) (21.0, 2)

Annual extension 5.6 3.9 2.2 4.5

meetings attendedc (4.1, 52) (5.3, 3]) (2.2, 31) (2.7, 8)

a - Numbers in parentheses indicate it if presented alone, or standard deviation

followed by n if more than one number.

b - Chi-square test shows non-signiﬁcant difference across all grower pairs.

c - Two-tailed t-test shows non-signiﬁcant difference across all grower pairs.

(1 - These data are based only on those growers who work off-farm.

e - Two-tailed t-test shows signiﬁcant difference between number of meetings

attended by apple and blueberry growers (si g = .000).

 

Among the growers who work off-farm, the number of hours spent working off-

farm was highest for blueberry growers (39 hours), followed by asparagus (37 hours) and

 

° A Pearson chi-square test was used. This non-parametric test requires no assumptions
about the shape of the underlying distribution yet assumes a random sample. Expected
frequencies for each category must be at least one with fewer than 20% of the cells
showing an expected frequency less than ﬁve.

78

apple growers (32 hours). However, these differences were not statistically signiﬁcant
(2-tailed t-test, 5% level) across the three primary crop pairings. Pickle growers who

work off-farm spend 31 hours per week at other jobs.

4.1.2.5 Attendance at Extension Meetings

Apple growers attend the most extension meetings annually (5.6/year), followed
by asparagus (3.9/year) and blueberry growers (2.2/year) (Table 4.5). However, the
means were only significantly different (2-tailed t-test, 5% level) between apple and

blueberry growers. The eight pickle growers who responded to this question attended 4.5

meetings annually.

4.1.2.6 Spanish-Speaking Ability

Apple growers were most likely to speak some Spanish "(54%), followed by
asparagus (45%) and blueberry growers (44%) (Table 4.6). These numbers were not
signiﬁcantly different (chi-square test, 5% level) in any of the primary subsector pairs.
Fifty percent of the pickle respondents claimed some ability to communicate in Spanish.

Growers who claimed some Spanish-speakin g ability (49%) were asked to rate
their level of Spanish fluency on a scale of 1 to 5, where 1 represented ‘basic vocabulary’
and 5 represented ‘fluent’. The growers’ mean ﬂuency level ranged from 1.3 for
asparagus to 1.8 for blueberry growers—which indicated slightly more than rudimentary
ability to communicate in Spanish. Pickle growers had a slightly better Spanish ability,
with a mean fluency level of 2.

These results indicate that since growers and migrant workers are typically unable

to communicate well with one another, an interpreter is likely needed to communicate all

79

but the simplest information messages between the two parties—which likely widens the

social and emotional gap between growers and migrant workers.

Table 4.6: Percentage of growers claiming ability to communicate in Spanish and
mean fluency level, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

 

Spanish-speaking Apple Asparagus Blueberry Pickle
ability“ (n = 52) (n = 31) (n = 32) (n = 8)
% claiming 53.8% 45.2% 43.8% 50.0%
Spanish ability” (28) (14) (14) (4)
Mean ﬂuency 1.4 1.3 1.7 2.0
level“ (0.7, 28) (0.6, 14) (1.1, 14) (0.8, 4)
a - Numbers in parentheses indicate n if presented alone, or standard deviation
followed by n if more than one number.
b - Chi—square test shows non-signiﬁcance across all primary grower pairs.
c - Two-tailed t-test shows non-signiﬁcance across all primary grower pairs.
d - Mean ﬂuency level, where 1 indicates basic Spanish vocabulary and 5

indicates ﬂuency.

4.1.3 Characteristics of Those Surveyed Who Did Not Hire Migrants in 2000

Several questions were directed at the 83 growers who did not hire migrants in 2000.
Of this group, only 27 (33%) had hired migrants sometime in the past. Twenty-six of
these growers (96%) were blueberry growers. Ironically, blueberry growers are the group
that now claims to have difﬁculty ﬁnding migrant labor. These same 26 blueberry
growers reported having hired migrant labor for a mean of 8.5 years (ranging from 1 to
22 years), indicating that they were seasoned employers of migrant labor. The sole
asparagus grower with a history of migrant hires had done so for only one year.

In most cases, these blueberry growers stopped hiring migrants in 1989. However,
36% stopped between 1988 and 1994 and 23% terminated their use of migrant labor

between 1998 and 1999. These growers most frequently reported that they no longer

80

hired migrant labor because they had recently bought harvesters and no longer needed the
workers (38%) or claimed that the government worker records had become too difﬁcult
and expensive to keep (15%). A variety of other reasons were also cited, including that
migrants were not reliable, their housing did not meet new standards, they now managed
u-pick operations or hired labor contractors, the farm was too small to attract help, or that
local workers were used instead of migrant laborers. Most of the answers accounted for
only one grower apiece.

Since no longer hiring migrant labor, 63% reported that their income had increased,
while 25% reported no change, and 12% reported a decrease.

When asked why net income had changed, over 52% attribute the change to their
switch to mechanical harvesting, a less costly alternative to hiring migrant workers.
Other answers included weather, prices, contract labor, and the use of non-migrant
harvesters as inﬂuencing net earnings. 2

When asked how many days of non-mi grant labor they hired for the 2000 harvest,
the growers across the four target subsectors reported employing an average of three non-
mi grants/day, with a range of zero to 30. Apple and asparagus growers hired a mean of
3.8 non-mi grant workers/day, while blueberry growers hired 2.9 non-migrants/day.

Finally, a mean of 0.5 year-round workers were hired across the four subsectors.
Although no apple and asparagus growers hired year-round employees, blueberry

growers hired a mean of 0.59 year-round workers, with a range of zero to 30.

81

4.2 RESULTS OF THE GROWER SURVEY

This section analyzes information that growers provided about themselves and

their migrant workers.

4.2.1 Statistics About Growers

This section reports statistical analysis of growers’ income, migrant payroll, and

crop sales.

4.2.1.1 Gross Crop Income Versus Net Crop Income

Due to an oversight in questionnaire design, blueberry growers were asked
different income questions than the three other types of growers. Whereas blueberry
growers were asked about their net crop income (NCI) from blueberries during a three-
year interval (1998-2000), apple, asparagus, and pickle growers were asked only about
their gross crop income (GCI) for the year 2000.

GCI is deﬁned as total crop sales (from the target crop). NC] is deﬁned as total
crop sales minus all expenses related to the target crop. For each question, growers were
provided a list of income intervals and asked to estimate into which interval their target
crop income fell.

As Table 4.7 shows, more apple growers in 2000 earned a GCI > $30,000
(73.8%) than asparagus (33.8%) or pickle growers (33.4%). In contrast, more asparagus
(64.2%) and pickle growers (67.0%) earned a GCI < $30,000. These ﬁgures do not take

into account the expenses associated with producing the respective crops.

82

In contrast, in 2000, 68.2% of the blueberry growers reported an NCI > $30,000
(Table 4.8). Accounting for the numerous expenses included in the NCI, the blueberry

grower GCI must be greater than the cited apple, asparagus, or pickle grower GCI.

Table 4.7: Gross crop income distribution (sales) of apple, asparagus,
and pickle producers, (Michigan, 2000)

 

 

 

 

 

 

 

GCI distribution (by intervals)al Apple Asparagus Pickle
(n = 38) (n = 28) (n = 9)

< $9,999 18.4% 21.4% 33.3%
$10,000-29,999 7.8% 42.8% 33.3%
$30,000-39,999 26.3% 21.4% 11.1%

> $40,000 47.5% 14.4% 22.3%

Total 100.0% 100.0% 100.0%

 

 

 

 

 

a - The number of growers reporting GCI is smaller than the respective sample
sizes, as some growers did not report their gross earnings.

Table 4.8: Net crop income distribution (sales minus expenses) of blueberry
producers (Michigan, 1998-2000)

 

 

 

 

 

 

 

 

 

 

NCI distribution 2000 1999 1998
(by intervals)3 (11 = 22) (n = 23) (n = 22)
< $9,999 18.2% 21.7% 40.9%
310,000-129,999 13.6% 21.8% 9.1%
>$30,000 68.2% 56.5% 50.0%
Total 100.0% 100.0% 100.0%

 

a - The number of growers reporting NCI is smaller than the sample size, as some
growers did not report their net earnings.
Although income data were not collected from apple, asparagus, or pickle
growers for 1998 or 1999, it was gathered from blueberry growers. The percentage of
blueberry respondents with NCI > $30,000 rose by 7% from 1998 to 1999 and by 11%

from 1999 to 2000. Simultaneously, the percentage of blueberry respondents with NCI <

83

$9,000 declined by 19% from 1998 to 1999, and by another 4% from 1999 to 2000.

These numbers indicate an increasing NCI in the blueberry subsector from 1998 to 2000.

4.2.1.2 Migrant Payroll as a Percentage of Total Farm Operating Expenses
Blueberry growers reported the largest percentage of expenses going towards
migrant payroll (34%), followed by apple (30%) and asparagus growers (23%)7 (Table
4.9). In each of the three years, these mean percentages were signiﬁcantly different
between apple and asparagus growers, and between asparagus and blueberry growers (2-

tailed t—test, 5% level). Pickle growers reported 36% of expenses going towards migrant

 

 

 

 

 

 

 

 

 

 

 

payroll.
Table 4.9: Migrant payroll as a percentage of total farm operating
expenses, by subsector (Michigan, 1998-2000)
Grower typea Year
2000 1999 1998

Apple 30 130.04 31 d0.05 30 r0.04

(n = 36-39) (12) (l4) (l3)

Asparagus 24 b0.04 C0.01 23 d0.05 €0.07“ 23 r0.04 g0.02

(n=29) (13) (13) (13)

Blueberry 35 Com 33 C007 35 80,02

(11 = 26-27) (20) (22) (21)

Pickle 31 38 39

(n=8) (19) (19) (17)

a - Standard deviations are given in parentheses.

b-g - Means followed by the same letter (one above the other within a
column) are signiﬁcantly different according to a 2-tailed t-test, at
signiﬁcance level that appears beside letter.

h- Although above the 5% cut-off point, this signiﬁcance level marked by

the letter e was considered sufﬁciently close to report.

 

7 These percentages are averaged across three years.

84

 

During 1998 through 2000, migrant payroll increased as a percentage of farm
operating expenses for asparagus growers. Although blueberry and apple grower payrolls
showed no consistent trends, their migrant payroll expenses (as a percentage of total farrn
operating expenses) were slightly higher in 2000 than 1998. Pickle growers showed a
decrease in migrant payroll as a percentage of farm operating expenses (1998-2000).

If migrant expenses that are not part of the actual payroll (i.e., medical care,
transportation, daycare provision, and housing) were added to payroll expenses, the costs
associated with migrant farm labor would increase as a percentage of a grower’s

expenses, to more than 30%.

4.2.1.3 Crop Sales as a Percentage of Total Farm Earnings (2000)

Although the majority of farm income in all four subsectors comes directly from
the target crops, the level of diversification varied considerably (Table 4.10). Blueberry
growers were the least diversiﬁed, with 96% of total farm earnings coming from
blueberry sales, followed by apple (79%) and asparagus sales (47%). These differences
were statistically signiﬁcant between apple and asparagus growers, and between
asparagus and blueberry growers, across all three years (2-tailed t-test, 5% level). They
were also statistically signiﬁcant between apple and blueberry growers in 1999 and 1998.
During 1998-2000, pickle growers reported that 42% of their farm earnings were from
pickle sales.

Given that blueberry growers are the least diversified, they are at the most risk

should a labor shortage arise.

85

4.2-2 Migrant Worker Statistics

The grower survey solicited information from growers in each subsector regarding
the characteristics of their migrant farm workers: state or foreign country where the
migrants reside during most of the year, recruitment methods, when recruitment began
for the 2000 harvest season, number of migrants who worked previously on the farm,
"1581‘ ant hires per day during the harvest season, wage arrangements, migrant housing

arrangements, perquisites and services provided to migrant workers, and mean crop

Percentages harvested by migrants.

Table 4.10: Specified crop sales as a % of total farm earnings, by subsector

(Michigan, 1998-2000)

 

Grower typea

 

 

 

 

 

 

 

  

 

 

 

 

Year
2000 1999 1998
Apple 78 730.00 C000 79 60.00 f0.00 80 1‘000
(n = 39-40) (26) (23) (22)
Asparagus 48 130.00 d0.00 47 e000 g0.00 47 h0.00 10.03
= 28) (32) (33) (33
Blueberry 96 c0.00 d0.00 96 10.00 g0.00 96 I0.03
= 25-26) (10) (10) (10)
Pickle 38 43 ‘ 45
(n = 7-8) (36) (36) (34)
a - Standard deviations are given in parentheses.

b - 1 Means followed by the same letter (one above the other within a column)
are signiﬁcantly different according to a 2-tailed t-test, at signiﬁcance level

that appears beside letter.

4.2.2.1 Migrant Origins

Across the four subsectors, growers reported that in 2000, an equal percentage

(29%) of the migrants traveled to Michigan from two states - Florida and Texas (Table

86

 

4.11). In contrast, a much smaller percentage of the migrants came from Mexico (10%)8,
Guatemala, and mixed origins (Texas and Mexico, 8.9%; Texas and Florida, 10.5%;
Mexico and Florida, 7.3%; and Texas, Mexico, and Florida, 3.2%). Clearly, the data
indicate that Florida and Texas are most crucial to the survival of Michigan’s migrant-

based agricultural economy.

Table 4.11: Migrant worker origins, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

 

 

Migrant ori gin“ Grower type (%) Total
Apple Asparagus Blueberry Pickle (n = 114)
(n=51) (n=31) (n=32) (n=10)
Texas 10 65 28 20 29
Florida 45 6 25 30 29
Mexico 10 7 19 0 I 1
Guatemala 0 3 3 0 2
TX & MX 8 6 I6 0 9
TX & FL 10 7 9 30 10
MX & FL 12 6 0 10 7
TX, MX & FL 5 0 0 10 3

 

 

 

 

 

 

 

a - A 2x2 chi-square test9 for goodness of fit indicated a signiﬁcant difference
in the distribution of grower-observed Florida versus Texas migrant origins
for all primary crop pairings (apple-blueberry signiﬁcance = .01, apple-
asparagus signiﬁcance = .00, asparagus-blueberry signiﬁcance = .01
(FET)). Likewise, two of the three primary crop pairings showed a
significant difference in the distribution of Texas versus Mexico origins
(apple-asparagus signiﬁcance = .02 (FET), asparagus-blueberry signiﬁcance
= .04 (FET)).

However, the source of mi grant labor varied considerably by primary subsector.

Apple growers were more likely to hire workers from Florida (45%), while asparagus

 

8 This ﬁgure, however, must be treated with caution since illegal immigration fears may
inﬂuence the answers given by respondents.

9 In instances where the expected value of more than 20% of the cells was less than ﬁve, a

two-sided Fisher’s Exact Test was conducted. These results are identiﬁed by placing
(FET) after the signiﬁcance value.

87

growers were more likely to hire from Texas (nearly 65%). In contrast, blueberry
growers hired workers from more diverse origins—almost equally from Texas (28%) and
Florida (25%).

Some statistically significant differences were noted in the distribution of Texas
versus Florida and Texas versus Mexico migrant origins by primary subsector pairing
(Pearson chi-square test, 1% and 5% levels respectively), suggesting that growers from
different subsectors follow different hiring patterns. The ten pickle growers hired 80% of

their migrant farm workers from Texas and Florida.

4.2.2.2 How and When Growers Recruited Migrant Workers

Growers recruit their workers in several different ways, and some use more than
one method to recruit workers in a given season (Table 4.12). Across all four subsectors,
73% of growers recruited at least some of their workers in 2000 through a verbal
agreement (i.e., these growers asked their 1999 workers to return in 2000). In addition,
61% of the growers reported hiring at least some of their workers from among those who
sought work at the farm gate. Growers tend to use the ﬁrst method to insure the
availability of a minimum number of workers while they use the second method to hire
additional migrants, if the number of returnees is insufﬁcient to meet their labor needs.

Michigan has two state programs10 whose funding is provided speciﬁcally to
assist growers in recruiting farmworkers. First, a state matching service is available to
help growers locate and hire migrant farmworkers (of domestic origin) who are actively

seeking work in Michigan. In addition, the H2A program arranges for foreign workers

 

'° Both the traditional matching service and H2A matching service are offered by
Michigan’s Employment Services Agency.

88

(often from the Caribbean) to work for growers who provide thorough documentation
that he or she has tried, but is unable, to locate sufﬁcient workers. Despite the
availability of these services, they were either unused or underused by the survey group
in 2000. Only 9% of the survey participants used state matching services in 2000 and
none of the growers employed any H2A hires.

Growers’ recruiting practices were similar across the target subsectors in 2000
(Table 4.12). A ‘verbal agreement with past workers’ was used most by apple (75%) and
asparagus growers (74%), followed by blueberry growers (59%). Migrants were ‘hired at
the farm gate’ by more apple (75%) than blueberry (56%) or asparagus growers (42%).
Furthermore, only a few growers in each category used state matching services to recruit
workers (less than 10% in any group) in 2000. Ninety percent of the pickle growers used

verbal agreements while 60% used farm gate hires.

Table 4.12: Growers’ methods for recruiting migrant workers, by subsector

 

 

 

 

 

 

 

 

 

 

 

 

 

 

(Michigan, 2000)
Hiring methoda Grower type (%)
Apple Asparagus Blueberry Pickle
(n=53) (n=31) (n=32) (n=10)
Verbal agreement with 75 74 59 90
past workers
Farm gate hires 75 42 56 60
Crewleader hires 21 19 28 20
Other 25 23 22 10
State matching services 9 10 9 0
a - A grower may use more than one hiring method.

Growers were asked what percentage of their hires they recruited using each

method. Table 4.13 shows that verbal agreements accounted for the largest share of

89

growers’ recruits among asparagus (49%), apple (47%), and blueberry growers (37%).
Farm gate hiring was the second most used method (apple, 28%; blueberry, 25%; and
asparagus growers, 22%). Growers reported hiring only a small share of their migrants
via other methods. State matching services accounted for no more than 2% of hires for
any subsector. Crewleader hires accounted for 20% among blueberry growers, 11%
among apple growers, and 10% among asparagus growers. In addition, a few growers
reported hiring migrants by: 1) word-of-mouth, 2) recruiting individuals employed by
another grower, 3) referrals from local families of Mexican origin, and 4) advertising
Openings in local businesses. A series of two-tailed t-tests shows no signiﬁcant
difference in how growers in the three primary subsectors recruited migrant labor in
2000. Among pickle growers, 62% of the workers were hired by verbal agreement, 18%

by farm gate hires, and 14% through crewleaders.

Table 4.13: Percentage of workers hired by different methods,
by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Hiring method“ Grower type (mean %)
Apple Asparagus Blueberry Pickle
(n=53) (n=31) (n=32) (n=10)
Verbal agreement 47.3 48.9 36.6 62.2
State matching 2.2 1.5 1.0 0.0
services
Crewleader 1 1.1 9.5 20.8 16.0
At the farm gate 28.1 21.7 25.0 17.8
Other 6.9 14.7 12.7 2.0
a - Since these are mean percentages across all growers in a subsector, they do

not necessarily sum to one hundred.

Some growers began to recruit migrant farm labor as long as a year ahead of the

harvest (Figure 4.1). This ﬁnding is consistent with growers’ widespread use of verbal

9O

agreements with past workers. As one harvest year ends, the growers typically recruit as
much labor as possible for the following year. Roughly a quarter of the apple growers
made arrangements in this way (12 of 46 apple growers) for the 2000 harvest season, as
did 25% of the asparagus growers and 20% of the blueberry growers. Only one of the

nine pickling cucumber respondents made such early arrangements.

120

 

100~

 

 

 

 

 

80 -
Grower type
E 60 " —
g Apples
(L 40 . _—
g) Asparagus
5% 2° ‘ Blueberries
E _—
3 .
0 O Pickles
0
o
0
02,394?»
6o.

 

When did migrant search begin for 2000 harvest?

Figure 4.]: Cumulative percent of growers according to when they initiated
their search for the 2000 harvest, by subsector (Michigan, 2000)
However, many growers hired their workers closer to harvest time. More than
one-half of the apple growers initiated their recruitment efforts after June 2000 (for work
that was to begin in August); just under one-half of the asparagus growers began to hire

migrants in the ﬁrst three months of 2000 (just ahead of the April harvest), and the same

91

was also true of blueberry growers, nearly half of who began their hires in June, July, or

August of 2000.

4.2.2.3 Number of Migrants Returning to Previous Employers

The mean percentages of migrant laborers who worked previously for the same
grower ranged from 0% to 100%. However, across the four target subsectors, about 60%
had previously worked for the same grower, and nearly 45% had returned to the same

farm for ﬁve or more years (Table 4.14).

Table 4.14: Mean percentages of migrant laborers that worked previously
for the same grower, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

Grower type“b Worked previously on grower’s Worked 5 or more years
farm for grower

Apple 57.2% 32.9%
(n = 53) (29.6) (32.6)
Asparagus 64.6% 41.7%
(n = 31) (35.5) (37.3)
Blueberry 55.8% 32.3%
(n = 32) (36.4) (33.7)
Pickle 73.5 55.0%
(n = 10) (17.5) (27.0)
Total 60.0 36.7%

(n = 126) (32.3) (34.0)

 

a — Standard deviations are given in parentheses.
b- Two-tailed t-test shows non—signiﬁcance across all primary crop pairs.

 

Across the four target subsectors, asparagus growers (65%) were most likely to
hire former employees, followed by apple (57%) and blueberry growers (56%).
Asparagus growers (42%) were also most likely to have migrants that had worked for

them for ﬁve or more years, followed by apple (33%) and blueberry growers (32%).

92

Thus, despite the existence of other job opportunities throughout Michigan, a fairly
steady number of workers return to the farms on which they previously worked.
However, the differences in these mean retention rates were not statistically different
across the three primary subsectors (two-tailed t-test, 5% level). Pickle growers showed
the highest retention rate—74% of the migrants had worked previously on the farm,

while 55% had worked for the grower for ﬁve or more years.

4.2.2.4 Migrant Hires Per Day During the Harvest Season

Apple and blueberry growers reported hiring the largest number of migrant
workers per day during the harvest season.” (See Table 4.15.) However, apples are
harvested once a year per type of apple, whereas blueberries are harvested twice a year—
early in the summer, and again late in the summer. In 2000, apple growers hired a mean
of 40.3 migrant workers per day, compared to 44.9 among blueberry growers, and 13.3
among asparagus workers. This mean number of migrants was signiﬁcantly different
between apple and asparagus growers, and asparagus and blueberry growers, in 2000 (2-
tailed t-test, 5% level). Pickle growers hired a mean of 37.3 workers per day.

These differences in mean migrant hire numbers were statistically significant
between apple and asparagus growers, and between asparagus and blueberry growers, in
all three years (2-tailed t-test, 5% level). However, no statistically signiﬁcant difference

was found between apple and blueberry labor hires in any of the three years.

 

” This survey is exclusively concerned with labor needs during the harvest season.
Although a few questions are asked regarding labor needs during other times in the crop

season, growers’ answers will indicate whether a future survey should focus on other
labor-intensive periods.

93

From 1998 to 2000, the mean number of workers hired per day increased more
among blueberry growers (+6.2) than among apple (+1.9) or asparagus growers (+0.7).
This is consistent with the impression that blueberry growers are more concerned about a
lack of migrant labor than are other types of growers. 1 However, it is inconsistent with the

ﬁnding that fewer blueberry growers actually hire migrant labor than do growers in the

other primary subsectors.

Table 4.15: Mean number of migrants needed per day for subsector
harvests (Michigan, 1998-2000)

 

 

 

 

 

 

 

 

 

 

 

Grower type“ ............................... XE?! ...............................
2000 l 1999 1998
Apple 40.3 2‘0.05 41.3 c(105 38.4 e005
(n = 51) (68.4) (61.8) (54.8)
Asparagus 13-3 a0.05 b0.05 12.8 c0.05 60.05 12-6 e0.05 f0.05
(n = 31) (9.3) (7.7) (7.3)
Blueberry 44.9 “0.05 34.5 “(105 38.7 f(ms
(n = 31-32) (52.6) (41.7) (43.5)
Pickle 37.2 38.9 39.4
(n = 9-10) (24.6) (23.7) (23.0)
a - Standard deviations are given in parentheses.

b - f Means followed by the same letter (one above the other within a
column) are signiﬁcantly different according to 2-tailed t-test, at
signiﬁcance level that appears beside letter.

4.2.2.5 Migrant Worker Harvest Days By Subsector

The information from the preceding section is combined with the harvest length
data to calculate the mean number of migrant worker harvest days per farm, per subsector
(Table 4.16). Migrant worker harvest days (MWHDs) are deﬁned as the number of

migrant workers per day during the harvest season multiplied by the harvest season

94

length in days”. MWIDDS were calculated by farm, based on individual grower

statements about harvest length.

Table 4.16: Mean number of migrant worker harvest days (MWHDs), by
subsector (Michigan, 1998-2000)

 

 

 

 

 

 

 

 

 

 

 

Grower type“ Year Three-year
2000 1999 1998 mean

Apple 2,500 10,0. 2,500 “0.02 2,400 30,02 2,500 ‘01,,

(n = 51) (5,100) (4,600) (4,000) (4,500)

Asparagus 600 b0.04 600 “0.02 600 60.02 600 e0.03

(n = 30) (400) (400) (400) (400)

Blueberry 2,100 900 1,000 1,500

(n = 5) (1,600) (1,300) (1,100) (1,300)

Pickle 1,800 1,900 2,000 1,900

(n = 10) ( 1,300) (1,400) (1,300) (1,400)

 

a - Standard deviations are given in parentheses.
b - Means followed by the same letter (one above the other within a column)
e are signiﬁcantly different according to analysis of variance test (ANOVA),

at significance level that appears beside letter.

The apple, blueberry, and pickling cucumber growers used much more total labor
in each of the three years than did the asparagus growers. Over the course of the three
years, apple growers hired an average of more than 2,500 MWHDs per farm, blueberry
growers hired less than 2,000 MWI-IDs, and asparagus growers hired not quite 600. On
average, between 1998 and 2000, apple growers used about four times as much labor as

did asparagus growers, while blueberry and pickling cucumber growers used about three

times as much labor.

 

EData from this study indicate that the typical apple and blueberry harvests last 56 days

(apple harvest range = 28 to 90 days; blueberry harvest range = 30 to 80 davs); The
typical maragus harvest lasts 44 davs (range = 20 to 60 days). The typical pickle
harvest lasts 47 days (range = 35 to 65 days),

95

 

An analysis of variance test shows that apple and asparagus growers required
signiﬁcantly different amounts of migrant worker days in the three years covered by this
study. As indicated by the large standard deviation (Table 4.16), the range in worker
days used by growers was enormous across all three years. Since farm size varies, labor

use patterns differ greatly.

4.2.2.6 Wage Arrangements

This section reports the units used by growers to pay migrant workers, estimates
the standardized wages that migrant workers receive, estimates their real wages (taking
into account rent, utilities, perquisites, and services), and looks at the expected cost of

alternative forms of labor.

4.2.2.6.1 How Migrant Workers Are Paid

A total of 116 growers provided information on how they paid their workers.
Apple growers generally (84%) pay their workers by the box or bin in 2000 (Table 4.17).
While blueberry (66%) and asparagus growers (52%) are more inclined to pay by the
hour, some also pay by the pound (asparagus, 42%; blueberry, 24%). Pickle growers
pay by the hour or offer harvest splits to the migrants, in which the migrants receive 45-

50% of the gross harvest proceeds'“.

 

'3 The five other pickle growers offered 50/50 or 55/45 splits to their migrants, in which
50% or 45% of the gross pickling cucumber sales were given to the migrants instead of
regular pay.

96

4.2.2.6.2 Standardized Hourly Wages

Since growers paid migrants in a variety of ways, it was necessary to standardize
wages to an hourly rate, which could be compared across the subsectors and used in the
real wage estimate. The mean hourly wage estimated for each subsector in Table 4.17
was used as the estimate in cases where hourly wages were not paid. In all other
instances, the hourly wages supplied by each grower were used. A distribution of the

estimated standardized wages is shown in Table 4.18.

Table 4.17: Percentage of growers using different wage types for migrant workers and
mean dollars paid per unit, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

 

 

 

Grower ........................................ Wages/128 ........................................
typea Hour Box/bin i Bushel i Bucket Pound
Apple 12% 84% 4% 0% 0%

(n = 51) (7.3, 2.6) (12.4, 1.4) (0.9, 0.2)

Asparagus 52% 0% 6% 0% 42%

(n = 31) (6.2, 0.6) (0.1, 0.0) (0.1, 0.0)
Blueberry 66% 0% 0% 10% 24%

(n = 29) (7.1, 1.2) (1.8, 0.2) (0.3, 0.1)
Pickle 80% 0% 0% 20% 0%

(n = 5) (5.9, 0.3) (30.0, 0.0)

a - Mean $lunit and standard deviations are given in parentheses, respectively.

Apple growers paid the highest mean standardized wages ($7.28/hour), followed
by blueberry ($7.14/hour) and asparagus growers ($6.18/hour). Eighty-eight percent of
the apple growers paid two to three dollars above Michigan’s minimum wage of $5.15
per hour while two thirds of the asparagus and blueberry growers paid from one to two
dollars above minimum wage. A two-tailed t-test shows that the differences in mean

standardized hourly wages were statistically significant (5% level) between apple and

97

 

asparagus growers, and between asparagus and blueberry growers. The mean

standardized hourly wage paid by pickle growers was $5.94/hour, with four of the ﬁve

pickle growers paying less than a dollar above minimum wage.

Table 4.18: Percent distribution of standardized wages paid by growers in the
target subsectors (Michigan, 2000)

 

 

 

 

 

 

 

 

 

 

 

 

standardized ............................. (.3. {strait/129.172). .............................
wage rate Apple Asparagus Blueberry Pickle
($lhour)““ (n = 51) (n = 31) (n = 29) (n = 5)
(7.28, 0.81) (6.18, 0.39) (7.14, 0.95) (5.94, 0.27)
< 5.15c 0.0 3.2 0.0 0.0
5.16 - 6.15 7.9 29.1 10.3 80.0
6.16 - 7.15 0.0 67.7 65.6 20.0
7.16 - 8.15 88.2 0.0 17.2 0.0
> 8.15 3.9 0.0 6.9 0.0
a - Mean and standard deviation given in second set of parentheses,
respectively. .
b- Two-tailed t-test shows signiﬁcant difference between apple and asparagus
means (level = .01), and asparagus and blueberry means (level = .01).
c- This is the minimum wage rate paid in Michigan.

4.2.2.6.3 Expected Wage Rates in the Absence of Migrant Workers

A total of 59 growers estimated the daily wages that they would have to pay to

 

other workers, if migrants were not available. Apple growers estimated the highest rate
($83/day), followed by asparagus ($73) and blueberry growers ($72) (Table 4.19). Pickle
growers estimated that they would have to offer $63/day. Assuming a ten to twelve hour
work day, these ﬁgures translate to $6.90-8.30 per hour paid by apple growers, $6.10-

7.30 per hour paid by asparagus growers, $6.00-7.20 per hour paid by blueberry growers,

98

and $5.25-6.30 per hour paid by pickle growers. Each estimate is above the $5.15 per

hour minimum wage offered in Michigan.

Table 4.19: Mean expected daily wage in absence of migrant
workers, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

Grower type“ Mean wage ($)b

Apple (n = 27) 83 (41)

Asparagus (n = 15) 73 (24)

Blueberry (n = 14) 72 (18)

Pickle (n = 2) 63 (18)

a - The number of responses was too small to conduct a
reliable t-test.

b - Standard deviation given in parentheses.

Many of the respondents said that this question was irrelevant, since it would be
impossible to ﬁnd workers to do the kind of work that they would be asked to do—
regardless of the wage offered. Some growers even said they would sell their farms if

they had to look for other workers.

4.2.2.7 Primary Migrant Worker Perquisites: Housing and Utilities

The following sub—sections explore the availability of housing to migrants across
the four subsectors. Housing and utilities are considered primary migrant worker
perquisites because they comprise the largest non-pecuniary compensation received by

migrant workers.

99

4.2.2.7.1 On-Farm Migrant Housing

Eighty-one percent of the growers who responded to this question (n = 125)
supplied housing for at least some of their migrant workers in 2000 (Table 4.20). More
apple growers supplied housing (93%) than did asparagus (75%) or blueberry growers
(58%). As expected, based on the key informant interviews, the blueberry growers were
least inclined to supply migrant housing, although more than one-half did. A 2x2 chi-

square test indicated a signiﬁcant difference between apple and blueberry growers (level

= .001).

Table 4.20: Percentage of growers that provide migrant housing, by subsector

 

 

 

 

 

 

 

 

 

(Michigan, 2000)
Providedmigrant -----_------------,------------9193’5’9133119 ________________________________
housing“ Apple Asparagus Blueberry Pickle
(n=53) (n=31) (n=31) (n=10)
Yes 93% 75% 58% 100%
a - Chi-square test showed signiﬁcant difference in percentages between

apple and blueberry growers (level = .001).

Growers in Michigan provide housing for single workers that is separate from
housing provided for families traveling together. Apple growers reported having a
capacity to house the most single migrants (44) in 2000, followed by blueberry (25 single
migrants) and asparagus growers (16) (Table 4.21.) A 2-tailed, t—test indicated that this
number was signiﬁcantly different (1% level) between apple and asparagus growers.
However, upon standardizing the data to account for differences in migrants/acre (i.e.,
dividing the number of migrants per farm by the farm’s total acreage), this difference

disappeared. Pickle growers were able to house a mean of 43 single workers.

100

Table 4.21: Mean housing capacity, by subsector (Michigan, 2000)

 

 

 

 

 

 

Housing capacity Grower type“
Apple “ Asparagus 1 Blueberry Pickle
(n = 48) (n = 24) (n = 18) (n = 10)
Single migrants“ 43.8 15.7 25.4 43.3
(54.7) (19.9) (25.1) (43.3)
Migrant familiesc 7.9 5.4 9.1 15.3
(8.3) (4.6) (12.3) (16.5)

 

 

 

 

a - Standard deviations are given in parentheses.

b - Two-tailed t-test shows signiﬁcant difference between apple and
asparagus growers (level = .02).

c - Two-tailed t-test shows no statistically signiﬁcant differences between
primary crop pairs.

In terms of being able to house migrant families, blueberry growers had the
capacity to house the most (nine families), followed by apple (eight) and asparagus
growers (ﬁve). However, these differences were not statistically significant across the
primary subsectors (2-tailed t-test, 5% level). Pickle growers had the capacity to house a
mean of 15 families in 2000.

The asparagus subsector supplied the greatest number of workers per migrant
family (4.4, standard deviation = 1.4), followed by the blueberry (3.9 workers, standard
deviation = 1.6) and apple subsectors ( 3.3, standard deviation = 1.5). While a 2-tailed,
t-test indicated that this number was signiﬁcantly different between the apple and
asparagus subsectors (level = .006), this difference was not signiﬁcant after standardizing
the data to account for differences in mi grants/acre.

Interestingly, there was a large disparity between the number of workers that

growers could house in 2000 and the number of workers they actually employed (Table

4.22). The fact that growers housed fewer migrants per farm than their capacity allowed

101

for may indicate the existence of a labor shortage. On the other hand, it may indicate that
not all housing on a farm has met state approval for migrant usage. In this case, growers
may report it as available housing when, in fact, it may not be approved. In this instance,
some workers may be forced to live elsewhere during their tenure on a particular farm,

even though it appears that housing is available.

Table 4.22: Mean number of workers housed in 2000,
number that were employed, and additional workers needed,
by subsector (Michigan, 2000)

 

 

 

 

 

 

Type“b Migrants : Add’l workers : Totale Housing Housing
hiredc : needed“ 5 capacityf surplus/deﬁcitg

Apple 40.3 ; 6.4 g 46.7 69.9 g 23.2
(51) g (8) g (48) g

Asparagus 13.3 i 3.6 5 16.9 39.5 5 23.4
(31) ' (8) 5 (23) i

Blueberry 44.9 . 22.5 i 67.4 60.9 E -6.5
(32) E (10) i (18) i

Pickle ~ 37.2 E 15.0 5 52.2 109.1 56.9
(10) I (1) i (10)

 

 

 

 

a - Number of respondents given in parentheses.

b - Standard deviations cited elsewhere in text.

c- Mean worker days/farm based on responses of those with and without
sufﬁcient workers in 2000. If calculated to include only those without
sufﬁcient workers, these numbers are even lower, resulting in an even greater

(1 - housing surplus.

Based on responses of those without sufﬁcient workers in 2000.

e - Sum of hired and needed migrants/day.

f - Based on those with and without sufficient workers in 2000.

g - Housing capacity minus sum of hired and needed mi grants/day.

These data indicate that, on average, only the blueberry growers would have had
insufﬁcient housing in 2000, had they been able to employ as many migrant workers as

they felt they needed. While the means show that, on average, even blueberry growers

102

had sufﬁcient capacity to house the mean number of workers hired in 2000, it is likely
that certain blueberry farms had excess capacity for housing migrants, while others had a

housing shortage.

4.2.2.7.2 Rent and Utility Issues

Seventeen percent of asparagus growers charged migrant workers rent while they
lived on their farm, as did 11% of blueberry growers, and 2% of apple growers. Given the
blueberry growers’ apparent difﬁculty in attracting labor, relative to other growers, it is
surprising that blueberry growers, who are less likely to charge rent than those growing

asparagus, noted having a harder time attracting workers than the asparagus subsector

(Table 4.23).

Table 4.23: Migrant housing rental payments, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

 

Housing rental payments _______________________ Growertype ______________________
Apple Asparagus Blueberry “ Pickle
Charged rent?ab 2% 17% 11% 30%
(49) (24) (18) (10)
If yes, when? -- Always 0% 0% 50% 0%
-- While working elsewhere 100% 75% 50% 100%
--Other 0% 25% 0% 0%
(1) (4) (2) (3)
Weekly rental Single workers: $25.00 $7.50 $30.00 $12.70
charge?° ............................ (NA:-192--.--.(.1.Q.65.2.) ...... (2.8.3-2.) ..... < .883).
' Families $100.00 $92.80 $75.90 $19.30
(NA, 1) (77.45, 4) (65.5, 2) (5.1, 3)
a - Chi—square test of primary crop pairs indicates a signiﬁcant difference
between apple and asparagus growers (level = .02).
b - Number in parentheses refers to the number of respondents to that question.
c — Numbers in parentheses refer to standard deviation and number of

respondents to that question,

respectively.

103

 

When asked under what conditions migrants were obliged to pay rent, 80% of
those charging rent (11 = 10) said that they only charged rent while the migrants were
working on another farm. In only one instance (a blueberry grower) was rent paid in all
cases.

Rents varied according to whether the worker was living alone or with a family.
Across all subsectors, a mean of $17.30/week was paid by single workers, while
$59/week was paid by families.

Given the small number of responses, statistical analyses of these data by
subsector were carried out only for whether or not growers charged rent. A statistically
significant difference was only observed between apple and asparagus growers.

Fifty percent of asparagus growers charged for utilities, as did 33% of apple and
22% of blueberry growers (Table 4.24). Forty percent of pickle growers charged for
utilities.

Of the growers who charged for utilities, 93% of the apple growers (n = 15)
charged utilities in all situations, as did 83% of the asparagus growers (n = 12) and 50%
of the blueberry growers (n = 4). Less than 10% of the growers only charged utilities
while migrants were working on another farm. All of the pickle growers charged utilities
in all situations.

Among those growers who charged for utilities, the utility rate for single migrant
workers ranged from a low of $2.50/week by blueberry growers (n = 2), to $9.50/week
by apple growers (n =14), to $21 .50/week by asparagus growers (n = 5). Pickle growers

charged a mean of $10.00/week (n = 3).

104

Table 4.24: Migrant utility payments by subsector (Michigan, 2000)

 

 

 

 

 

 

Housing utility payments: ________________________ Grower type _________________________
Apple 1 Asparagus Blueberry Pickle
Charged utilities?ab 33% 50% 22% 40%
(49) (24) (18) (10)
If yes, when? -- Always 93% 83% 50% 100%
-- While working elsewhere 7% 17% 0% 0%
-- Propane only 0% 0% 25% 0%
-- Only when working 0% 0% 25% 0%
. (15) (12) (4) (4)
Weekly utility 5 Single workers: $9.30 $21.50 $2.60 $10.20
rate charged“ (7.9, 14) (41.3, 5) (1.9, 2) (12.9, 3)
é'iia'nii'r'i'es: """" 824.10 """" a 24:40 """" $28.10 """"" 7379290 """
E (26.3, 14) (29.5, 9) (30.9, 2) (10.9, 4)

 

 

 

 

 

a - Chi-square test shows no significant differences by subsector.
b - Number in parentheses refers to the number of respondents to that question.

c - Numbers in parentheses refer to standard deviation and number of respondents to
that question, respectively.

Blueberry growers ( n = 2) charged families the highest utility rates
($28.00/week), followed by apple (11 = 14) and asparagus growers (n = 9) that charged a
mean of $24.00/week”. Pickle growers charged $10.00/week. Given the small number
of responses, statistical analysis of these data by subsector was only possible concerning
whether or not growers charged for utilities15 . No statistically signiﬁcant difference was
observed between any of the primary crop pairings.

The mean rent and utility rates shown in Tables 4.23 and 4.24 will be used to

estimate a monetary value for migrant worker beneﬁts.

 

'4 It is assumed that families are charged a higher utility rate because of their overall

higher utility usage, caused by several family members living together under the same
roof.

‘5 The other utilities data did not have sufﬁcient numbers per category for statistical
analysis.

105

4.2.2.7.3 Off-Farm Migrant Housing

More blueberry growers had workers that lived-off farm in 2000 (75%) than did

apple or asparagus growers (42% each) (Table 4.25). This appears contrary to the

ﬁndings in Section 4.2.2.7.1, which reported that, on average, housing availability

exceeded the number of workers who actually lived on these farms. A chi-square test

indicated that the differences in the percentages of migrants who live off-farm were

statistically significant between apple and blueberry growers, and between asparagus and

blueberry growers.

Table 4.25: Mean number of growers with migrants who lived off-farm,
where they lived, and distance traveled to work, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

Migrants that live off-farm _______________________ Growertype _______________________
Apple Agaragus Blueberry Pickle
Growers with migrants living off— 42% 42% 75% 30%
farrnab (53) (31) (32) (10)
If yes, mean number“ 14.6 10.1 35.2 23.7
(17.2, 22) (8.3,13) (36.5, 23) (27.2, 3)
Where they lived:b
-- Other farm 24% 59% 32% 100%
—— Quarters self-secured 71% 33% 58% 0%
--With a local, permanent resident 0% 0% 5% 0%
—- Other
5% 8% 5% 0%
(17) (12) (22) (3)
Mean travel distance (miles)“ 14.8 8.5 14.1 8.3
(19.5, 22) (6.3, 13) (9.4, 23) (5.8, 3)

 

 

Chi-square test shows signiﬁcant difference between apple and blueberry

growers (level = .00) and between asparagus and blueberry growers (level =

.01).

to that question, respectively.

106

Number in parentheses refers to the number of respondents to that question.
Numbers in parentheses refer to standard deviation and number of respondents

 

When taking into account only those farms where some migrants lived off-farm in
2000 (n = 62), this number was highest among blueberry growers (3S migrants), followed
by apple (15) and asparagus growers (10). Pickle growers had a mean of 24 migrants live
off-farm.

More than 50% of the growers with some migrants living off-farm stated that
these migrants lived in quarters that the migrants secured themselves and close to 40% of
the growers said that their workers lived in migrant housing on a neighboring farm.

On average, migrants who lived off-farm commuted nearly 13 miles to work in
2000, ranging from 15 miles for apple workers (one way), 14 miles for blueberry workers
and nine miles for asparagus workers. Pickle migrants who lived off-farm traveled a

mean of eight miles to work.

4.2.2.8 Secondary Migrant Worker Perquisites and Services

This sub-section reviews secondary perquisites provided by growers to their
migrant workers. Secondary perquisites extend beyond rent and utilities to include such
things as laundry facilities, telephone access, and end-of season bonuses. Secondary

services provided to migrant workers by outside sources (i.e., churches, stores, daycare)

are reported in Section 4.2.2.8.2.

4.2.2.8.1 Secondary Perquisites Provided to Migrant Workers
As shown in Table 4.26, the percentage of growers who provided any secondary
perquisites was higher for apple growers (58%) than for asparagus and blueberry growers

(35% each). Secondary perquisites are defined as non-wage benefits (in addition to

107

housing and utilities) that growers provided to migrant workers in 2000. These

differences were statistically signiﬁcant between apple growers and both asparagus and

blueberry growers (chi-square test, 5% level). Fifty-eight percent of the pickle growers

provided secondary perquisites.

Table 4.26: Number and percentage of growers providing secondary perquisites to
migrant workers, and mean harvest season value, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

Growers providing -...-----§IQW§T.3XPE ____________________________
perquisites Apple “ Asparagus Blueberry Pickle
Provided migrant 58% 35% 35% 60%
perquisites“b (52) (31) (31) (10)
Number of 30 ll 11 6
5.1%1291199913 ..............................................................................
Type of End-of—season 63% 45% 45% 33%
Perquis- 5.13.999? .................. ($19,122.) ...... ($297.99)--- -.-.(§§.32-.9.6.2.-...-..--_:: .......
itec 5 Improved lunch 17% 9% 0% 33%
Lariat). ................. 4.4.1.67) ....... ($19.99)? ....................... < 3,199.99)?
3 Telephone 43% 27% 55% 50%
1.699.??? .................. ($59.21.?) ....... ($199911. ........ ($1.29.)---_..-.(.$;.29;992‘.’--
Transportation 23 % 18% 18% 33%
. .......................... (11.1.81?) ...... (55.1.5999)--- --..($.l-1.:‘}.2.2 ...... 1§1§9;99).-
Laundry 40% 1 8% 27% 50%
..f.t.c.il.iti.e_s ................ ($§§.-§8) ....... ($99.99)". ........ < .$.6.-99)."...---..<§.29.99)t‘--
5 End-of-season 30% 55% 27% 67%
2.13.991? .................... ($14.99.) ........ < 32.7.59)---.__-.<§59..9.1.) ...... ($8,999.).
Other“ 17% 0% 36% ’ 50%
a - Chi-square test shows signiﬁcant difference between apple and asparagus

growers (level :05), and apple and blueberry growers (level = .05).

b-
c-
(1.

Number in parentheses refers to the number of respondents to that question.
Number in parentheses refers to subsectoral mean for perquisite.
Indicates that mean is based on only one observed value for that subsector.

Other perks included paid rain days, overtime, meals or food, new housing, an

interpreter, jail bond money, daycare, and loans. Each of these was cited no
more than twice by growers.

108

 

The kinds of perquisites offered to the migrant workers varied from farm-to—farm.
The most common perquisites given by growers were an end-of-season bonus, telephone
access, laundry facilities, and an end-of-season ﬁesta.”

An end-of-season bonus was given by 63% of apple growers and 45% each of
asparagus and blueberry growers. Asparagus growers gave the largest mean bonus
($208.00/season), followed by apple ($192.00) and blueberry growers ($63.00). Only
two of the six pickle respondents to this question provided an end-of-season bonus.

Asparagus growers reported the highest mean bonus value in 2000
($208/season/worker), followed by apple ($192) and blueberry growers ($63). These
values indicate that growers perceive end-of—season bonuses as important incentives to
attract and keep migrants on their farms. Since bonuses are distributed when the harvest
is complete, they encourage migrants to stay until the end of the harvest season.

Fifty-ﬁve percent of blueberry growers supplied telephone access as a perquisite,
followed by 43% of the apple growers and 27 % of the asparagus growers. Apple growers
reported a mean value of $49/season/worker, followed by asparagus ($10) and blueberry
growers ($7). Three of the six pickle respondents to this question provided telephone
access.

Laundry facilities were supplied by 40% of the apple growers, 27% of the

blueberry growers, and 18% of the asparagus growers. Apple growers valued laundry

 

1“ Growers were asked to list the perquisites that they provided in 2000. Since a list of
secondary perks was not provided to growers, this question was left to interpretation by
the survey respondents. To answer this question, the grower had to think about what they
considered a perquisite in excess of cash payment. Thus, a provision recognized as a
perquisite by one grower may not have been thought of as a perquisite by another grower.
Likewise, since this question took more effort to answer, several respondents simply
skipped it.

109

facilities at $57/season/worker, followed by asparagus ($30) and blueberry growers ($6).
Fifty percent of the pickle growers supplied laundry facilities.

An end-of-season ﬁesta was provided by 55% of the asparagus growers, 30% of
the apple growers and 27% of the blueberry growers. Blueberry growers valued the end-
of-season ﬁesta at $50/season/worker, followed by asparagus ($28) and apple growers
($14). Sixty-six percent of the pickle growers provided workers with an end-of-season
ﬁesta.

Other perquisites cited by growers as part of their incentive structure (it = 124)
included transportation (22%), improved lunch facilities (16%), paid rain days (2%), paid
overtime (2%), meals or food (3%), new housing (2%), interpreter costs (2%), jail bond
provisions (4%), daycare facilities (4%), and ﬁnancial loans (4%).

Interestingly, only 2% of the growers used new housing as a perquisite.
Considering the importance placed on housing by both growers and migrant workers, this
is surprising. However, this may be due to the high cost of constructing new housing. In
a cost-beneﬁt scenario, it is likely that the cost of building new migrant housing
outweighs its beneﬁt as an incentive for attracting more migrant labor.

This analysis suggests that growers frequently provide perquisites as a way to
supplement migrant monetary wages. These estimated perquisite values will be used to
construct an overall real wage rate across the four subsectors, which will then be
compared with wages paid elsewhere in the economy, against which growers are

competing for labor.

IIO

4.2.2.8.2 Secondary Services Available for Migrant Use

In addition to wages and perquisites, the availability of services to migrant
workers may attract them to a particular farm. This section analyzes whether or not
access to services is associated with a grower’s ability or inability to attract migrants to
work on his/her farm. Six services were selected for inclusion in this analysis. They
include availability of religious services, schooling for migrant children, medical
services, a grocery store, a clothing/all-purpose store, and migrant job location services.
More than 90% of the growers reported access to each of these services from their farms.

As shown in Table 4.27, the mean distance between farms and religious services
was only 5.85 miles across the four target subsectors. Asparagus migrants traveled
nearly eight miles to religious services, while apple and blueberry migrants traveled less
than ﬁve miles. Pickle migrants traveled seven miles to religious services.

The mean distance between farms and schools was highest for asparagus migrants
(six miles), followed by apple and blueberry migrants (five miles each). Pickle migrants
traveled less than four and one-half miles to school.

On average, asparagus migrants traveled more than 11 miles to medical services,
while apple migrants traveled seven miles and blueberry migrants traveled slightly more
than ﬁve miles. Pickle migrants traveled ten and one half miles to medical services.

Apple migrants traveled more than four and one-half miles to a grocery store
while asparagus migrants traveled just under four and one-half miles and blueberry

migrants traveled four miles. Pickle migrants also traveled approximately four miles to a

grocery store.

111

Table 4.27

: Mean distance from farms to services, as reported by
growers, by subsector (2000)

 

 

 

 

 

 

 

 

 

 

Distance to services in ___-_-__“__Gr.o}y.er.t_ype _____________________________
miles“ Apple Asparagus Blueberry i Pickle
(44-51) (26-29) (20-26) (8-9)
Religious services“ 4.95 7.73 4.93 7.25
----.(.32;§.2.2 .......... (.7489). ........... (3,-2.1) ............ (. 33:91.) ......
Schooling 5.02 5.75 4.96 4.44
----.(.2.;7.8.) .......... (3,-2.2). ........... (2.69.4) ............ (. 4:72) ......
Medical services 6.93 1 1.33 5.31 10.50
-..-.(.‘l-.l.5.). .......... (2.7.8). ........... (2.9.3.) ............ (. $5.3.) ......
Grocery store 4.65 4.38 3.92 4.17
-.---.(.2.~.3.'.1.). .......... (3,-1.3). ........... (2:7,!) ............ (. 3:14) ......
Clothing/All-Purpose 7.87 10.07 7.28 11.94
Store -.-_-.(.‘!;!.9.)--..- -----(§.-.Q§). ........... (3,-8.1) ............ (. 7:12) ......
Migrant services for 11.34 14.41 9.25 16.33
locating jobs (7.52) (5.90) (5.36) (4.61)

 

 

 

 

a — The number of responses to each question varied slightly, as indicated by the
range in n (as shown in parentheses following the crop name).
b - Numbers in parentheses refer to standard deviation.

Asparagus migrants traveled ten miles to a clothing/all-purpose store while apple

migrants traveled eight miles and blueberry migrants traveled seven miles. Pickle

migrants traveled twelve miles to a clothing/all-purpose store.

Asparagus migrants traveled nearly 14.5 miles to migrant services for locating

jobs while apple migrants traveled approximately 11.5 miles and blueberry migrants

traveled greater than nine miles. Pickle migrants traveled greater than sixteen miles to

migrant services for locating jobs.

Since almost none of these services were available on-farm, they cannot be

considered direct perquisites. Also, no signiﬁcant differences were found in the

availability of perquisites offered across the three primary subsectors (chi-square test, 5%

level). Thus, no attempt will be made to assign values to these services in the shadow
wage estimation. Furthermore, as these services were all widely available across the four
subsectors, it is unlikely that they inﬂuence migrants’ decision as to where to seek a job.
However, the availability of these services may attract workers towards farm employment
in Michigan and, in turn, contribute to the social welfare of migrant workers from

faraway places like Florida and Texas.

4.2.2.9 An Estimation of Real Wages Paid to Migrant Workers in Michigan
As describe in Section 3.3.2, the ‘real wages’ paid to migrant workers are deﬁned
as:
real wages = standardized wages + housing value (rent and utilities)

+ estimated total perquisite value

To estimate the “real wage” for each subsector, the previously estimated
standardized wages (Section 4.2.2.6.2), housing values (Section 4.2.2.7.2) and perquisite
values (Section 4.2.2.8.1) are inserted in the above equation for each case (grower). If a
grower did not provide an estimated value for the rental, utility, or perquisite categories,
but provided the perquisite, the mean value obtained through other growers in the same
subsector was used instead. Sufﬁcient data to make these calculations was available for
66 growers across the four target subsectors.

Table 4.28 reports the estimated mean real wage paid by growers in each
subsector. As in the standardized wage case, 76% of the growers paid a real wage

ranging from $550-$750 per hour. This included 90% of asparagus growers, 70% of

113

apple growers, and 60% of blueberry growers. As expected, real wages are consistently
higher than standardized wages, ranging from a difference (attributable to housing and
other perquisites) of $0.45/hour for asparagus workers to $0.86/hour for apple workers

(Table 4.29))7

Table 4.28 Estimated real wage rates, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

Real wage rate .---..---§.t9>¥.e.r..txrze‘.’-£f’{'q). ...............................
($lhour)“ Apple Asparagus Blueberry Pickle
n = 31 n = 20 n = 5 n = 8
(7.3, 0.8) (6.6, 1.3) (7.3, 1.0) (8.8, 4.3)

< $5.50 0 5 0 0
$5.51-6.50 13 55 40 50
$6.51-7.50 58 35 20 25
$7.51-8.50 19 0 40 0
5851-950 10 0 0 0
> $9.50 0 5 0 25

 

 

 

 

 

 

a - No 2-tailed t-test was conducted given the unreliability of results when n < 30.
b - Numbers in parentheses refer to the mean and the standard deviation.

Although it was expected that real wages would exceed the minimum wage, it
was not clear that the same would be true of standardized wages. However, on average,
both the estimated standardized and real wages are above Michigan’s $5.15/hour state-
mandated minimum wage rate'“. In fact, across the four target subsectors, the average
real wage rate ($7.28/hour) was 46% higher than the minimum wage rate and the

standardized wage rate ($6.39/hour) was 24% higher than the rrrinimum wage.

 

'7 A difference of $2.70 was noted for the pickle subsector. However, due to the small
number of respondents, this estimate is not considered to be reliable.

'8 Michigan’s minimum wage rate is the same as the federal government’s minimum
wage rate (US. Department of Labor, 2003).

114

Table 4.29 A comparison of real and standardized wages, by subsector (MI, 2000)

 

 

 

 

 

 

Wage rate _____________________ Grower type ______________________ Total
($lhour) Apple Asparagus 1 Blueberry Pickle n = 66
n = 31 1) =20 n = 7 n = 8
Real wage rate 7.31 6.43 7.28 8.83 7.28
Standardized wge rate 6.45 6.18 6.75 6.13 6.39
Real wage rate minus .86 .45 .53 2.70 .89
standardized wage rate

 

 

 

 

 

 

4.2.2.10 Mean Crop Percentages Harvested By Migrants

Growers who hired migrants reported that migrants harvested 98% of their apple
and asparagus crops but only 59% of growers’ blueberry crops (Table 4.30). Pickle
growers reported that migrants harvested 100% of their pickling cucumber crops. These
data highlight the key role that migrant labor plays in harvesting these crops and the

severe impact that a disruption in the migrant labor supply would have on these

subsectors.

4.2.3 Has There Been a Migrant Labor Shortage in Michigan?

In 2000, 85% of the apple growers, 74% of the asparagus growers, and 63% of the
blueberry growers reported that they were able to hire enough migrant workers at harvest
time (Table 4.31). In all but the asparagus subsector, these percentages were slightly
lower in the previous two years but did not differ signiﬁcantly from year-to-year (two-
tailed t-test). These percentages were significantly different (Pearson chi-square test)
between apple and blueberry growers in all three years, and between asparagus and
blueberry growers in all years but 2000. Ninety percent of the pickle growers reported

that they were able to hire enough migrant workers for the 2000 harvest.

115

 

Table 4.30 Mean crop percentages harvested by migrants, by subsector

 

 

 

 

 

 

 

 

 

(Michigan, 2000)
Grower type Mean percent“
Apple (n = 50) 97.9 (4.7)“000,
Asparagus (n = 31) 97.6 (9.1) “0,001
Blueberry (n = 31) 59.2 (34.5)”0.001°0.om
Pickle (n = 10) 100.0 (0.0)
a - Numbers in parentheses refer to standard deviation.
b-c - Means followed by the same letter (one above the other within a

column) are signiﬁcantly different according to a 2-tai1ed t-test, at
signiﬁcance level that appears beside letter.

Table 4.31: Percentages of growers reporting a shortage of migrant labor and
the mean number of additional workers needed, by subsector (M1, 1998-2000)

 

 

 

 

 

 

 

 

Year ................................. grgwsrlyps ..................................

Apple “ Asparagus Blueberry Pickle

(53)f (31) (29-32) (9-10)
2000a 15% 26% 38% 10%
Additionaiwo'rit'ers"""""6'I4""""""""'3.'6 """"""""" 2'2'.’5°""'""""""'1'5'30 """""
needed“ (5.7, 8) (2.1, 8) (30.5, 10) (na, 1)
1999b 21% 6% 53% 44%
Additional workers 7635 """"""""" 2 '3'.’6"""""'""1'3I0 """"""
needed (8.1, 10) (2.1, 2) (32.0, 15) (5.72.4)
-19? 8.“ .......................... 2. 1?? .............. 3 2?? ................ ‘1 .1179 ................. 3.3179 .........
Additional workers 11.6 2.0 20.6 8.3
needed (15.1, 10) (na, 1) (27.6, 11) (5.8, 3)

 

a - Pearson chi-square test shows signiﬁcant difference between apple and
blueberry growers in whether or not there were sufﬁcient workers (level = .02).

b - Pearson chi—square test shows significant difference in apple-blueberry (level =
.00) and asparagus-blueberry pairings (level = .00).

c - Pearson chi-square test shows signiﬁcant differences in all three pairings:
apple-asparagus (level = .03), apple-blueberry (level =.05), and asparagus-
blueberry (level = .00).

d - ‘Additional workers needed’ refers to the mean number needed by respondents
reporting a labor shortage within a subsector, per farm per day.

e - Numbers in parentheses refer to standard deviation and number of respondents
to that question, respectively.

f - Refers to the number of respondents reporting whether or not they experienced
a labor shortage.

116

 

In all three years, blueberry growers were most likely to report that they had
insufﬁcient migrant workers (38-53%, depending on the year) to meet their labor
requirements. Blueberry growers who reported a labor shortage estimated that they
needed 21-24 additional workers, depending on the year. In contrast, apple growers who
reported insufﬁcient labor (15-21 %) estimated they needed six to twelve additional
workers, and asparagus growers (6-32%) estimated they needed two to four additional
workers, depending on the year. However, as the number of respondents per subsector in

any given year was quite small, differences in additional workers needed were not

statistically significant.

4.2.3.1 Labor Shortage in Relation to Unharvested Acres

Of the growers who reported a labor shortage, many claimed that, in at least one
of the three years, this shortage resulted in at least some of their crop being unharvested.
This number included 88% of the asparagus growers (n = 8), 33% of the blueberry
growers (n = 18), and 31% of the apple growers (n = 16) (Table 4.32). All of the pickle
growers that reported a labor shortage (n = 4) also reported unharvested acres.

Between 1998 and 2000, affected blueberry growers (n = 3-6, depending on the
year) reported a mean acreage loss of seven to 19 acres, resulting in an estimated
financial loss of $1,800 to $2,200 per acre. Affected apple growers (n = 24) reported an
acreage loss of 8 to ten acres, resulting in an estimated ﬁnancial loss of $1,500 to $3,000
per acre. Asparagus growers (n = 0-7) reported a mean acreage loss of six to 22 acres,

resulting in an estimated financial loss of $0 to $2,800 per acre. Affected pickle growers

117

(n = 14) reported an acreage loss of ﬁve to ten acres, resulting in an estimated ﬁnancial

loss of $1,400 to $1,500 per acre.

Table 4.32: Mean unharvested acres and ﬁnancial loss per acre, among growers
who reported a shortage of migrant labor, by subsector (Michigan, 1998-2000)

 

 

 

 

 

 

Growertype ............ Meatless.lsﬁrvharxsaséiasf‘ .............
2000 1999 1998
Apple 10 8 9
............................................ (1922)--.---. ------.(.‘.1:-?).------. --------(.9.t.f1)..-..-..-
Mean ﬁnancial loss ($lacre) $3000 $1500 $1700
(na, 1) (na, 1) (2100, 3)
Asparagus 22 6 0
(11, 7) (9, 2) (na, 0)
Mean ﬁnancial loss ($lacre) ““““““ $800 “““““““““““““ $2800 ““““““““““““““““ $0 ““““““““““
(900, 7) (4000, 2) (na, 1)
Blueberry 19 17 7
............................................ (2.1.2.4.)----.-.---_--(.1.6.z.§.)------ (33)
Mean financial loss ($/acre) $2100 $2200 $1800
(2000, 4) (1900, 6) (1300, 3)
Pickle 10 7 5
............................................ £0.a-1)---.-- (34)(43)
Mean ﬁnancial loss ($lacre) $1500 $1400 $1400
(na, 1) (600, 4) (700, 3)

 

 

 

 

 

a - Numbers in parentheses refer to standard deviation and number of

respondents to that question, respectively.

Another way to look at this is from an industry-wide perspective, roughly
estimating what each subsector would look like if similar percentages of each subsector
faced similar labor-related losses due to unharvested acres‘“. Using the mean acreage and
financial loss ﬁgures cited for 2000, the blueberry subsector could face annual losses of
more than $2 million, the asparagus subsector more than $1 million, the apple subsector

nearly $1 million, and the pickle subsector $200 thousand.

 

'9 The losses were projected by averaging the growers’ estimated 1998—2000 unharvested
crop loss values and multiplying by the relevant percentage of growers per subsector.

118

4.2.3.2 Labor Shortage in Relation to Late-Harvested Acres

Of the respondents who reported a labor shortage, many claimed that in at least
one of the last three years, this shortage resulted in some of their crop being harvested
later than at the optimal time. This included 88% of the apple growers (n = 16), 78% of
the 18 blueberry growers (n = 18), and 63% of the asparagus growers (n = 8) (Table
4.33). Fifty percent of the pickle growers (n = 4) that reported a labor shortage also
reported late-harvested acres.

For the years 1998 through 2000, affected apple growers (n = 7-9, depending on
the year) reported harvesting 21 to 30 acres later than at the optimal time, resulting in a
mean ﬁnancial loss of $500 to $8,500 per acre“°. Affected blueberry growers reported
harvesting eight to 14 acres later than at the optimal time, resulting in a mean ﬁnancial
loss of $2,700 to $3,600 per acre. Asparagus growers reported harvesting zero to to 31
acres later than at the optimal time, resulting in a financial loss of zero to $4,500 per acre.
Affected pickle growers reported harvesting three to ten acres later than at the optimal
time, resulting in a ﬁnancial loss of $500 to $1,000 per acre.

As before, this can also be looked at from an industry-wide perspective,
estimating what each subsector would look like if a similar percentage of all Michigan
growers in that subsector faced similar labor-related losses due to late harvested acres”.

Using the mean acreage and ﬁnancial loss ﬁgures cited above, Michigan’s apple and

 

2° Since the sample sizes on which these estimates are based are very small, they must be
treated with caution. Nevertheless, the ﬁgures provide a rough estimate regarding the

troubles faced by Michigan growers who reported an inability to hire sufﬁcient migrant
farm workers in recent years.

2' These losses were projected by averaging the growers’ estimated 1998-2000 crop loss
values and multiplying by the relevant number of growers per subsector.

119

asparagus subsectors could face annual losses of more than $5 million apiece, the

blueberry subsector $2.5 million, and the pickle subsector less than $100 thousand.

4.33: Mean acres harvested beyond the optimal time and ﬁnancial loss per
acre, among growers reporting a shortage of migrant labor, by subsector
(Michigan, 1998—2000)

 

 

 

 

 

 

 

 

 

Cror) ........................... X sari ............................
2000 ‘ 1999 1998
Apple 28 21 30
............................................ (34.1)---" (179)<479)
Mean ﬁnancial loss ($lacre) $500 $8,500 $2,000
(500, 5) (18,400, 7) (3,300, 8)
Asparagus 31 24 0
(35, 5) (na, 1) (na, 1)
Mean financial loss ($lacre) $4,500 """""" $4§000'"" ‘ 0 " ‘
(3,100, 5) (na, 1) (na, 1)
Blueberry 14 14 8
........................................... 0.42-19)--- -----.<.12._).i)--.... (910)
Mean ﬁnancial loss ($lacre) $3,600 $2,900 . $2,700
(8,100, 9) (5,700, 12) (5,200, 8)
Pickle 10 9 3
............................................ wail)-.-" -----_.(.1:-2).------.----.-t!ta-!)------.
Mean ﬁnancial loss ($lacre) $1,000 $800 $500
(na, 1) (350, 2) (na, 1)

 

 

a-

respondents to that question, respectively.

Industry-wide, annual losses attributable to both unharvested and late-harvested

Numbers in parentheses refer to standard deviation and number of

acres are potentially as high as $6 million for the apple subsector and asparagus

subsectors, $4.5 million for the blueberry subsector, and $300 thousand for the pickle

subsector.

120

4.2.3.3 Labor Shortage in Relation to Farm Size

Across the four subsectors, farm size was deﬁned in two ways. First, it was
deﬁned by total farm acreage; second, by crop earnings in 2000 and estimated total farm
earnings for 1998 through 2000. To test Hypothesis 3 that large farms have an easier
time recruiting migrant farm labor than do small farms, 3 discriminant analysis was
conducted using ‘farm size’ as the continuous, independent variable and ‘ability to recruit
sufﬁcient migrant labor’ as the categorical, dependent variable (Alreck and Settle, p.
320). Neither farm size by acreage nor farm size by crop earnings (or estimated total
farm earnings) was found to have a statistically significant correlation with the ability of

growers to recruit sufficient migrant labor at harvest time for any of the three years for

which data were collected (1998-2000).

4.2.3.4 Labor Shortage in Relation to Real Wages

To test Hypothesis 4 that higher real wages lead to easier recruitment and
retention of workers, a discriminant analysis was conducted using ‘estimated real wages’
as the continuous, independent variable and ‘ability to recruit sufﬁcient mi grant labor’ as
the categorical, dependent variable (Alreck and Settle, p. 320). Real wage rates were not
found to have a statistically signiﬁcant correlation with the ability of growers to recruit
sufficient migrant labor at harvest time in 2000““. Likewise, a 2-tailed test of
signiﬁcance (Pearson correlation) indicated no statistically signiﬁcant correlation
between the real wage rates calculated in this chapter and: (1) the number of migrants

who had worked previously on the same farm (corr = .067, 81 g = .559), and (2) the

 

“2 This was the only year for which sufficient data was available to make this calculation.

121

number of migrants who had worked on a particular farm for ﬁve or more years (corr =
.060, sig 2 .663). Thus, these results do not support the hypothesis that growers who pay

higher real wages can more easily recruit and retain workers.

4.2.3.5 Labor Shortage in Relation to the Provision of Housing

‘Housing’ and ‘ease of recruiting’ were not signiﬁcantly correlated for any of the

three years.

4.2.3.6 Labor Shortage in Relation to Growers’ Ability to Communicate in Spanish
Although a weakly statistically signiﬁcant relationship was noted between a
grower’s ability to speak or understand some Spanish (regardless of ﬂuency level) and
having a sufﬁcient number of migrants in 2000 (chi-square = 3.1, sig = .078), non-
signiﬁcant results were obtained for 1999 and 1998. Non-signiﬁcant associations were

also obtained between levels of ﬂuency and having a sufﬁcient number of migrants for

1998 through 2000.

4.2.3.7 Labor Shortage in Relation to Migrants that Return to Same Farms Year-
After-Year

The Pearson correlation between sufficient labor and the percent of migrants
returning to the same farm for ﬁve or more years is signiﬁcant (corr = 0.756, indicating
that nearly sixty percent of the variation is shared by the two variables (Alreck and Settle,
p. 315)), although sufficient labor is not signiﬁcantly correlated with the more general

category of percentage of workers who have worked on the farm in previous years. Thus,

122

the analysis generally supports the hypothesis that growers with a high percentage of
long-term return employees are better able to access sufﬁcient quantities of migrant farm

labor.

4.2.3.8 Potential Explanations for the Perceived Labor Shortage

One survey question solicited growers’ opinions about why they have experienced
a labor shortage in recent years by asking them to rank a series of possible reasons (Table
4.34).23 Approximately two-thirds of the apple growers that responded to this question (11
= 16) identiﬁed among their top two rankings ‘hi gher-payin g non-farm-work elsewhere’
(69%) and ‘too few migrants coming to Michigan now’ (63%). Two-thirds of the
asparagus growers who responded to this question (n = 8) also identified ‘higher-paying
non-farm-work elsewhere’ (63%) among their top two reasons. More than one-third of
the blueberry respondents (n = 18) cited ‘too few migrants’ and ‘tighter INS restrictions’
among their top two reasons (39%), while another third cited ‘hi gher-paying non-farm-
work elsewhere’ and ‘an inability to provide enough housing to meet federal standards’
(33 %).

Equally telling is the number of growers who rejected other possible reasons for
the labor shortage. Ninety-six percent of the respondents rejected ‘insufﬁcient matching
services’ as a possible explanation. Seventy-eight percent rejected ‘higher paying fann-
work elsewhere’. Finally, 65% (including nearly 40% of the blueberry growers) rejected
‘an inability to provide enough housing that meets federal standards’ as an explanation

for the labor shortage. This is surprising since a many blueberry growers do not supply

 

2“ This question was asked only of growers who reported a labor shortage during 1998-
2000.

123

housing, which was hypothesized as being a signiﬁcant factor in attracting migrant

workers to a given farm.

Table 4.34: First or second place grower ranking (%) of reasons for why
there is a migrant labor shortage, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

 

 

Possible reason for -.--------.G..r.9.".".eI.t).’P.e. ______________________________

farm labor shortage“b Apple Asparagus Blueberry Pickle
(n= 16) (n=8) (n=18) (n=4)

Hi gher-paying non- 68.8% 62.5% 33.3% 25.0%

farm-work elsewhere

Too few migrants 62.6% 25.0% 38.9% 25.0%

coming to Michigan

now

Tighter INS 37.6% 25.0% 38.9% 25.0%

restrictions

Cannot provide 6.3% 25.0% 33.4% 0.0%

enough housing to

meet federal

standards

Hi gher-payin g farm- 0.0% 0.0% 1 1.1% 25.0%

work elsewhere

Insufﬁcient matching 6.3% 0.0% 0.0% 0.0%

services

 

 

 

a - Growers were asked to rank the top three reasons for the labor shortage,
assigning a 1 to the most likely reason, a 2 to the second most likely reason,
and a 3 to the third most likely reason. Data in this table refer to the top two
rankings per reason only.

b - Due to small sample size, no signiﬁcance testing was performed.

Although the list of possible explanations for a labor shortage was fairly
comprehensive, growers were given the opportunity to select ‘other’ as a reason for the
labor shortage. Eighty-seven percent of the growers did not include this option in their

ranking of the alternatives.

124

4.2.3.9 Changes Made by Growers to Accommodate Labor Shift

To reduce a labor shortage, growers can make changes in their operations to either
reduce their labor needs or to attract more migrant labor. Many of the respondents who
reported a labor shortage claimed to have made such changes in their farming operation
to reduce labor needs during the last few years. This included 72% of the blueberry
growers (n = 18), 63% of the apple growers (n = 16), and 50% of the asparagus growers
(n = 8) (Table 4.35). Fifty percent of the four pickle growers also made changes in their
farming operation.

The means by which growers reduced their labor requirements varied by
subsector and from farm-to—farm“. A majority of blueberry growers (92%) reported
switching to machine-harvestin g to reduce their labor needs. Numerous asparagus (and
pickle) growers reduced their crop acreage. While only two of the ten apple growers
reduced their acreage, two others switched to smaller trees that are easier to harvest and
one apple grower began planting more vegetables to extend the migrant employment
season.

However, rather than attempting to reduce their need for labor, more respondents
reported making changes in their farm operating procedure to attract more migrant labor
to their farm (Table 4.35), including 86% of the asparagus growers, 75% of the apple
growers, and 59% of the blueberry growers. Seventy-ﬁve percent of the pickle growers

also made changes to attract labor.

 

2‘ Growers provided so many different responses to this question that a table was
considered not useful.

125

Table 4.35: Percentage of respondents citing labor shortage who made
changes in their farm operating procedures to reduce labor need or
attract more labor to their farms, by subsector (Michigan, 2000)

 

 

 

 

 

Recent changes in farming ....................... G rowertype“ _______________________
operation to: Apple Asparagus Blueberry 1 Pickle
(16) (7-8) (17-18) (4)
Reduce migrant labor needb 62.5% 50% 72.2% 50%
Attract more labor“ 75% 85.7% 58.8% 75%

 

 

 

 

 

a - Number in parentheses refers to number of respondents.
b - Due to small sample size, no signiﬁcance testing was performed.

To attract more migrants, 71% of the growers reported building or improving
existing migrant housing and nearly 50% increased migrant worker pay levels. In
addition, some growers added a new lunchroom or modern bathroom facilities, or
provided an end-of-season bonus, hired a crewleader to help with migrant hires, planted
smaller trees (apple growers), planted vegetables to provide continuous employment, or

eliminated long-term workers who could not get along with new workers.

4.2.4 Anticipated Future Migrant Labor Needs

When asked if they expected to need more, less, or the same number of migrant
workers in 2001, 66% reported that they anticipated needing the same number in 2001
while 25% anticipated needing more workers, and 9% reported that they would need
fewer workers (Table 4.36.)

Among the subsectors, asparagus growers most frequently anticipated an increased
demand for labor in 2001 (39%), followed by blueberry growers (34%) and apple
growers (17%). Nine percent of pickle growers anticipated an increased demand for

labor. In contrast, only 9% of apple growers anticipated a decreased need for labor,

126

followed by blueberry growers (6%) and asparagus growers (0%). Forty percent of the
pickle growers expected to need fewer workers in 2001. However, these differences

were not statistically signiﬁcant among any of the pairings (Chi-square test).

Table 4.36: Growers’ anticipated need for migrant workers in 2001 and 2005,
by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

Future demand for _______________________ Growertype“ ________________________ Total
migrant labor Apple 1 Asparagus Blueberry 1 Pickle (124-126)
expected to (52-53) (31) (31-32) (10)
Next year T Rise 17.0% 38.7% 34.4% 0.0% 25.4%
(2001)b Drop 9.4% 0.0% 6.3% 40.0% 8.7%
Same 73.6% 61.3% 59.3% 60.0% 65.8%
In 5 years 5T Rise 28.8% 48.4% 41.9% 0.0% 34.7%
(2005)b Drop 25.0% 19.4% 25.8% 50.0% 25.8%
Same 46.2% 32.2% 32.3% 50.0% 39.5%

 

 

a - Number in parentheses refers to number of respondents.

b - Chi-square conducted by combining “rise” and “drop” categories into “change”
category - no statistically signiﬁcant difference noted in any of the primary crop
pairings.

With respect to growers’ anticipated demand for migrant labor in 2005, across the
four subsectors, 35% of growers expected to need more workers, 25% expected to need
fewer, and 40% expected their demand to remain the same.

Growers’ anticipated demand for migrants in 2005 varied by subsector. Fifty
percent of asparagus growers, 40% of blueberry growers, and 30% of apple growers
expected to need more laborers. In contrast, one-quarter or less of each group expected

to need fewer workers. None of the pickle growers expected to need more labor in 2005

while half expected to need fewer workers.

127

An open-ended question in this survey asked growers to identify factors that will
increase their future labor needs. Forty-nine percent of the apple growers, 43% of the
asparagus growers, and 22% of the blueberry growers responding to this question cited
‘an increase in acreage’ (Table 4.37). One-third of the pickle growers gave the same
response.

Citing ‘increased production of other crops’ as a factor that would increase their
demand for labor were 24% of the apple growers, 19% of the asparagus growers, and 6%
of the blueberry growers. None of the pickle growers cited this factor.

Citing ‘increased production of the survey crop’ were 39% of the blueberry
growers and 0% of the apple and asparagus growers. Likewise, none of the pickle
growers cited this factor.

Citing ‘increased crop price/proﬁtability’ were 16% of the apple growers, 5% of
the asparagus growers, and 0% of the blueberry growers. None of the pickle growers
cited this factor.

Citing ‘increased on-farm processing’ were 16% of the apple growers and 5% of
the asparagus growers. None of the blueberry (or pickle) growers cited this factor.

Regarding factors that might decrease their demand for labor, the most important
finding from this question is that 13% of the growers that responded to this question said
that they will have sold their businesses in the next five years -- and thus cannot answer
this question (Table 4.38.) Growers who expected to sell their farms included 18% of the
asparagus growers (n = 17), 15% of the apple growers (n = 33), and 13% of the blueberry
growers (n = 13). Seventeen percent of the pickle growers (n = 6) expected to have sold

his or her farm by 2005.

128

Table 4.37: Factors that growers believe will increase their future labor need, by

 

 

 

 

 

 

 

 

subsector (Michigan, 2000)
Factor” ----------§.r.9wsr..txr>s-(rs§1299§9§t .(‘f/é»-9f..r§§peas,9§).). ..........
Apple Asparagus Blueberry Pickle
(n=37) (n=21) (n=18) (n=3)
-- 1‘ acreage 18 9 4 1
- ................................... (4.8-.972). ......... ( ﬁZ-§79).-..-----.(.22.-.2.‘.79) ......... (3.39.1781---
-- 1 production of other 9 4 1 0
£913.92 ............................ (25-.372) ......... ( -1. 9.9%.). ......... (5.26.79). ......... (9:933) .....
-- T production of 0 0 7 0
smarter. ..................... ( 9:958)--.-.----.(9-9.‘72>_----.----.<.3.§.-.9.‘f/9.> .......... (9:979) .....
-- T crop price/ 6 1 0 0
resistant)? ................. 09.382)----._---_<51.8a) .......... (9.9a). .......... (9,-9.79.) .....
-- T on-farm 1 6 0 0
assessing.“ ...................... ( 2-7.79) .......... ( 2.89%.). ......... (99%.). .......... (9:979) .....
-- Less efficient I 1 1 1
mikes .......................... ( .2.;7.‘i/<2)-----.----.(5‘:.8f72). .......... 1.5.163.) .......... (3.33.79)---
-- Product selling I 0 2 1
-999F29ts ......................... ( .2.;7.‘.7<3)---.-.---_.(Q-.9."/'.8>.----.----.(.1.l.-.1.‘.79.) ......... (339.322----
-- Hand-harvesting for 1 0 1 0
quality fruit (2.7%) L (0.0%) (5 6%) (0.0%)
-- Too stringent INS 0 0 i 2 ’ 0' " '
regulations (0.0%) (0.0%) (l 1.1%) (0.0%)
Total responses 37 21 18 3
(100%) (100%) (100%) (100%)

 

 

a - Respondents could offer multiple factors.

b - As a crop price rises, the return to the grower increases, making it worthwhile
to plant more of the same crop. More acreage planted to a crop requires
additional labor to tend and harvest that crop.

c - On-farm processing requires labor in excess of that needed for harvesting.

Excluding those who planned to sell their farm, more asparagus (47%) than apple
(25%) or blueberry growers (11%) cited ‘less acreage’ as the most compelling factor for
why labor demand may drop among apple and asparagus growers (Table 4.38). Only one

of the six pickle respondents cited this factor.

129

Table 4.38: Factors that growers believe will decrease their future labor needs by year
2005, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

Factor“ Grower Type (responses, (% of responses))
Apple “ Asparagus “ Blueberry “ Pickle
(n = 33) (n = 17) (n = 16) (n = 6)
-- I acreage 10 8 2 l
....................................... ( 25.9%.)---".---.(.‘!.7...1.?ib).---.----.(.1.9.-.5.‘.79).---. --..-(.1.4.-.3.‘.78).--.-.
-- T mechanization 4 2 10 1
...................................... (. 1.1%-9281.-----.---.(.1..1.-§79).-....-.-.(.5.2.-§‘.79).---. -----(.1.4.-3.‘.78.).----
-- l crop price/ 1 6 2 0 3 1
.-1-Rr.9ﬁtahil.i!x .................... (. 15.9%). .......... ( -1..1.-§%.).---.------.(Q?'9) ............ 1:128??? ......
-- Will have sold farm 5 3 2 1
....................................... (. 12.25.79)---".---.<.l7.-§%).---.--.-.(.1.9.-.5.‘.79.).---. _--.-(.1.‘1.-.3.‘.79.)-----.
-- Shift from hourly to 4 1 1 0
939.99-91.13. was ............ . ..... (. 1.99%.)---“.----.(.5.:97.0.).----1 ..... 1.5.47.0). ............ £9.79) ........
-- Direct marketing“ 5 1 0 0
....................................... (. 1.2.-.5.f7.°.).-----.-"1.532791-----------.(9“.7?.).-----.----.--(9‘.7?.)..---.-.
-- Switch to smaller, 4 0 0 0
..§b9nsr.trs.e.§ ...................... (. 19-928)-----.-----.(9f79).----.-_-.---.(9%) .............. £9.79.) ........
-- More restrictive 1 0 2 0
.Jsbsrrssulatieas ......... ..-----.(.2.-§.'i/<2) ............. ( 9%.)..-m-----.(.1.9.-.5_%) ........... £9.79.) ....... r
-- More u-pick 1 0 1 1 1
..a9.t.ixi.t.i.e.§--------------------.-----.(.2.-§.‘7.0.)------.-.---.(9?/2). ........... (5.23.81). .......... (14:279.) .....
-- Cost/availability of 0 0 I 0
labor (0%) (0%) (5.3%) (0%)
Total responses 40 17 19 7
(100%) (100.0%) (100%) (100%)

 

 

 

a-
[3.

Respondents could offer multiple factors.
As a crop price rises, the return to the grower increases, making it worthwhile to

plant more of the same crop. More acreage planted to a crop requires additional
labor to tend and harvest that crop.

No longer necessary to sell to only large buyers.

Citing ‘increased mechanization’ as a factor likely to decrease labor demand were

53% of the responses given by blueberry growers, but only 12% of the asparagus

responses and 10% of the apple responses. Only one of the six pickle respondents cited

‘increased mechanization’ as a factor.

130

Six of the 33 apple respondents (15%), two of the 17 asparagus respondents
(12%), and none of the 16 blueberry respondents pointed to ‘lower crop price and
decreased proﬁtability’ as a factor likely responsible for decreased labor demand by
2005. Three of the six pickle respondents gave this answer.

Among the other reasons cited for an anticipated decrease in labor demand were a
‘conversion from an hourly to a piece rate wage’, ‘direct marketing activities’, ‘a shift to

smaller, shorter trees’ among apple growers, ‘more restrictive labor regulations’, and

‘more u-pick activities.’

4.2.5 Anticipated Future Migrant Labor Availability
When asked about the anticipated future availability of migrants across the four

target subsectors, 68% of the growers expected there to be fewer migrant workers
available in ﬁve years (Table 4.39). However, 30% of the respondents (n = 122) expected
no change in labor and 2% expected that more migrant workers would be available in the
future. These percentages are similar across the subsectors.

A chi-square test (5% level) indicated no statistically signiﬁcant differences
among grower types, regarding their expectations.

Growers offered suggestions for increasing the future supply of migrant labor
(Table 4.40). Multiple suggestions were allowed per grower. The most frequently cited
recommendations were legal in nature (58% of the responses), primarily divided between
the issuance of seasonal migrant permits at the federal or state level and relaxing
government regulations to ensure sufficient farm labor in Michigan (25% of the

responses each). Apple (30%) and asparagus growers (40%) favored seasonal permits.

131

Blueberry growers (60%) favored looser government regulations as they pertain to
immigration and, hence, migrant availability. Four of the eight pickle growers also

favored seasonal permits.

Table 4.39: Growers’ expectations regarding the availability of migrant
workers in ﬁve years, by subsector (Michigan, 2000)

 

 

 

 

Expected Grower type (11, (%)) Total
Avarlabrlrty Apple Asparagus 1 Blueberry 1 Pickle (n - 122)
(n=51) (n=30) (n=32) (n=9)
Hrgher 2 0 1 0 3
---.(.3..?."{'8) ........ (. 1).-9%) ........ (3:179). ......... (9-9%) ............ (. 2.5.82) ......
Lower 34 20 23 6 83
..................... ( 96.27.81)--. ---(§.6.;75'./9)-.-..-.(.7.1.-.9.‘.’/.0)..-, ----($5.6.;7.°{?2)---- ,-.---(.§§-.9.‘7.8)-----
Same 15 10 8 3 36
(29.4%) (33.3%) (25.0%) (33.3%) (29.5%)

 

 

 

 

 

 

a - A chi-square test showed non-signiﬁcant differences among primary crop
pairs.

Some respondents also made economic suggestions (16% of the responses), primarily
related to changing the tax structure for migrant workers (10%) and increasing crop
prices so that wages and beneﬁts could rise (6%). Twenty-three percent of the responses
from asparagus growers were in favor of changing the tax structure, although no clear-cut
economic preferences were noted for the other three subsectors.

Nineteen percent of the responses cited on-site changes, including continued
assistance for building on-farm housing (12% of the responses) and growing crops that
maximize a grower’s ability to retain migrant workers on his or her farm during slow
times (7%). More apple, asparagus, and blueberry growers were in favor of construction

assistance (13—15%) as compared to those in favor of making crop changes (4-10%).

132

Table 4.40: Growers’ suggestions for increasing the future supply of migrant
workers, by subsector (Michigan, 2000)

 

 

 

 

 

 

 

 

 

 

 

 

 

Suggestions Grower Type (responses, Total
.--.(9§.9.f_rs.spo.t)§e.§)) ................... (responses,
Apple Asparagus 1 Blue- Pickle (% Of
(n = 37) (n = 22) berry (n = 8) resronses»
(n = 25)
L888“
-Issue seasonal permits 14 10 2 4 30
at Federal/State level (29.2%) (38.5%) (5.7%) (44.5%) (25.4%)
-Re1ax government 7 2 20 0 29
regulations to ensure (14.6%) (7.7%) (57.0%) (0.0%) (24.6%)
sufﬁcient migrants
-5—year visas for ag. 4 0 4 1 9
workers, followed by (8.2%) (0.0%) (11.4%) (11.1%) (7 .7%)
citizenship option
Economic:
-Rework mi grant- 4 6 0 2 12
related tax structure (8.4%) (23.1%) (0.0%) (22.2%) (10.1%)
-T crop prices so that 6 0 1 0 7
beneﬁts/wages can 1 (12.5%) (0.0%) (2.9%) (0.0%) (5.9%)
On-site:
-Continue assistance in 6 4 5 O 15
building on-farm (12.5%) (15.4%) (14.3%) (0.0%) (12.7%)
housing
-Use crop-growing 5 1 1 0 7
pattern that maximizes (10.4%) (3.8%) (2.9%) (0.0%) (5.9%)
migrants’ ability to
stay on one farm
Other“: 2 3 2 2 9
(4.2%) (11.5%) (5.8%) (22.2%) (7.7%)
Total responses 48 26 35 9 118
(100%) (100%) (100%) (100%) (100%)
a - Due to n < 30 for three of the four crops, no significance testing was performed.
b- Other responses included ‘programs to teach growers about regulations’, ‘the

development of housing projects to supply migrant labor pools’, ‘better
communication between growers and mi grants’, ‘H2A program reforms’, and
‘monetary rewards for families who do good work’.

133

 

4.2.6 Non-Migrant and Year-Round Labor Statistics

To fully meet their labor needs, 61-66% of the growers hired some non-migrant
labor during 1998-2000. The mean number of non-migrant hires per day was relatively
constant over the three years (Table 4.41). Blueberry “growers hired the greatest number--
approximately nine per day, followed by apple growers (5) and asparagus growers
(slightly more than one). On average, pickle growers hired less than one worker per day.
Due to the small number of responses per category in a given year, the differences in the
means were only statistically signiﬁcant between apple and asparagus growers in all three
years.

During the last three years, only about 20% of the growers said that they had any
difﬁculty hiring sufficient year-round labor (Table 4.42). Nevertheless, this percentage
increased from 18% in 1998 to 19% in 1999, and then to 22% in 2000.

Apple growers reported having the most trouble hiring year-round labor during
1998-2000. Depending on the year, 25-27% of apple growers reported this problem,
followed by 14-20% of the blueberry growers and 10% of the asparagus growers.

However, these differences were only statistically signiﬁcant between apple and
asparagus growers in 1999 and 1998. Twenty to thirty percent of the pickle growers
reported difﬁculty hiring year-round labor.

More than two-thirds of the respondents (n = 26) reported higher wages elsewhere
and better non-farm opportunities as the reason they had trouble locating year-round
laborers (Table 4.43)““. Blueberry growers (n = 12) gave numerous reasons not given by

other growers for why they had difﬁculty recruiting year-round workers, including that

 

“5 Since this question was answered by only those respondents who had difﬁculty hiring
year-round labor, the n is quite small.

134

there was so much other work available for pruning and tractor crews, farm work is

backbreakin g and unglamorous, potential workers lack the experience needed for year-

round work, and too many workers are simply undependable. The ﬁrst two of these

explanations are directly related to there being better job opportunities in the local and

national economies. The last two reasons can be argued as indirectly related to other

economic options.

Table 4.41: Mean number of non-mi grants growers hired per day per farm, by
subsector (Michigan, 1998-2000)

 

 

 

 

 

 

 

 

 

 

 

Grower _______________________________ Year _______________________________ 3-year mean
type“ 2000 1999 1998
Apple 4.08 ‘00 552‘?03 5.3833 4.99
(5.98, 52) (13.89, 52) (13.78, 52)
Asparagus 1.15 900 1.17 “.03 1.10603 1.14
(1.86, 30) (1.80, 30) (1.79, 30)
Blueberry“ 9.12 9.33 8.80 9.09
(1714,21) (16.54, 21) (18.38, 20)
Pickle 0.70 0.67 0.78 0.72
(0.95, 10) (0.87, 9) (1.09, 9)
a - Standard deviations and number of respondents are given in parentheses,
respectively.
b - The number of blueberry respondents was too small for inclusion in a
reliable t-test comparison.
c - e Means followed by the same letter (one above the other within a column)

are signiﬁcantly different according to a 2-tailed t-test, at signiﬁcance level

that appears beside letter.

Across the three years, apple growers (21%) reported the greatest difﬁculty hiring

labor during other than the harvest periods, compared to only 12% of the blueberry

135

 

growers (Table 4.44)“. Twenty percent of the pickle growers also reported having

difﬁculty hiring labor during times other than the harvest period.

Table 4.42: Percentage of growers citing they had trouble hiring year-
round workers, by subsector (Michigan, 1998-2000)

 

 

 

 

 

 

 

 

 

Grower type Year
"""" 2000"“1"""'i°9'99"""""""i'9'9'8"""
Apple (n = 51) 27.5% 25.5% “0,0. 27.5% “cm
Asparagus (n = 29-30) 10.3% 6.9% “0.0.. 6.9% “0,03
lueberry (n = 29-30) 20.0% 16.7% 13.8%
Pickle (n = 10) 30.0% 30.0% 20.0%
otal (n = 119—120) 21.7% 19.2% 18.5%

 

 

 

a - b Percentages followed by the same letter (one above the other

within a column) are signiﬁcantly different according to a Pearson
chi-square test, at signiﬁcance level that appears beside letter.

Among growers who reported it difﬁcult to hire labor during non-harvest peak
periods (n = 24), 64% of the apple growers (n = 14) and 43% of the blueberry growers (n
= 7) said that it is ‘difﬁcult to ﬁnd workers with the necessary skills required for pruning
or tractor-based activities’ (Table 4.45). Two of the three pickle respondents also made
this claim. Twenty-nine percent of the blueberry growers and 21 % of the apple growers
cited the ‘existence of higher wages and beneﬁts off—farm’ (one of the three pickle
growers cited this factor), while 29% of the blueberry growers and 14% of the apple
growers said that the work is ‘too monotonous and backbreakin g’ to attract workers in

today’s economy. No pickle growers cited this last factor.

 

2“ Asparagus growers were not asked this question as other peak time labor is not an issue
for them.

136

Table 4.43: Grower reasons concerning why they had difﬁculty hiring

year-round labor, by subsector (Michigan, 1998-2000)

 

if

 

 

 

 

 

 

 

Reasons Grower type (n, (%)) Total
1 """"""""""""""""""""""""""" .' """" (11, (%))
Apple Asparagus 1 Blueberry Pickle
Better non-farm 3 1 6 1 11
opportunities available (25.0%) (50.0%) (50.0%) (50.0%) (39.3%)
Higher wages 6 I 0 l 8
elsewhere (50.0%) (50.0%) (50.0%) (28.6%)
Workers lack 0 0 4 0 4
experience and (33.3%) (14.3%)
dependability
Other 3 0 0 0 3
(25.0%) (10.7%)
Farrnwork is 0 0 2 0 2
backbreaking (16.7%) (7.1%)
Total 12 2 12 2 28
(100%) (100%) (100%) (100%) (100%)

 

 

 

 

 

 

 

a - Only reasons given by more than one respondent are included in this table.
b - Due to the small n per category, no signiﬁcance testing was performed.

Table 4.44: Percentage of growers reporting labor shortages during other peak

times, by subsector (Michigan, 1998-2000)

 

 

 

 

 

 

 

Grower type“b ....................... Y ear. Three-year
2000 1999 ' 1998 mean
Apple (11 = 51) 21.6% 23.6% 17.6% 20.9
Blueberry (n = 28-29) 13.8% 10.3% 10.7% 11.6
Pickle (n = 10) 10.0% 30.0% 20.0% 20.0

 

 

 

a-

b-

Asparagus growers were not asked this question as
other peak time labor is not an issue for them.

A chi-square test (5% level) indicated no statistically
signiﬁcant differences among grower types.

137

 

4.3 REGRESSION ANALYSIS

The aim of this section is to present the results of the logit multinomial
regressions, identifying the factors associated with whether or not growers had sufﬁcient
migrant farm labor for the 2000 harvest season. Five logit models were estimated as part

of this analysis but were found inconclusive and are therefore not presented here.

Table 4.45: Growers’ reasons for having difﬁculty hiring laborers during non-
harvest peak labor periods, by subsector (Michigan, 2000)

 

 

 

 

 

 

Reasons” Grower type (11, (%))
Apple Blueberry Prckle
Difficult ﬁnding workers skilled in 9 3 2
.99919811991919.993111%------------------ -----194.-§%)..-.-.----.(4.2_-§%) ......... (9.89.72)--.
Higher wages/beneﬁts in off-farm 1 3 2 1
Opportunities -----.(.2.!.-ft%.>..-.-.-.-..(.2.8.-.6.‘.79) ......... 1.3.3.379)..-
Work too monotonous to compete 2 2 0
with other jobs (14.3%) (28.6%)
Total 14 7 3
(100%) (100%) (100%)

 

 

 

a- Only reasons given by more than one respondent were included in this table.
b- Asparagus growers were not asked this question as other peak time labor is not
an issue for them.

c - The n was too small per subsector for reliable signiﬁcance testing. Therefore,
none was done.

It is likely that these results are non-significant for several reasons. First, the high
level of data processing required to standardize several of the variables, such as the
standardized and real wage rates, make it likely that some of the information was lost in
the standardization process. Second, the social capital variables used in the regression
series were not adequate proxies for the information sought by this study. Thus, relevant

information that might have been captured by asking particular survey questions in a

138

more appropriate way was not captured. Third, several questions asked on the survey
were open—ended, requiring more time by growers to answer. Hence, fewer responses
were obtained, shrinking the data pool for use in the regression series. Each time data
were missing for one respondent, the sample population automatically diminished,
making it increasingly difﬁcult to obtain conclusive results from the logit analyses”.
Last, given the self-selection of the growers who responded to the grower and mi grant

pilot surveys, bias was introduced to the study, potentially inﬂuencing the nature of the

results obtained in the logit analyses.

4.4 SUMMARY AND CONCLUSION

The data indicate that the respondents had many years of experience, particularly
working with migrants. Across the four subsectors, they had worked on a farm for 30
years, had spent 27 years growing their target crops, and had actually managed a farm for
24 years.28 Most importantly, they had hired migrant workers for 21 years. On average,
growers managed large farms that averaged 430 acres, with a little less than one-third of
their acreage planted to annual acres (127 acres). Asparagus growers had signiﬁcantly
more acres planted to annual crops (188 acres) than the other target growers”. Whereas a
mean of 40% of growers’ farm acreage was planted to the target crop, this ranged from

18% for asparagus growers to 56% for apple growers.

 

2" The data set available for inclusion in the logit analyses was small compared to the

number of growers originally targeted by this study (79 versus 720, slightly more than
10%).

2“ These are all mean values, averaged across the four subsectors.

“9 Apple growers have a mean of only 63 acres planted to annual crops.

139

Although these data imply that asparagus growers are more diversiﬁed, increased
diversiﬁcation does not necessarily imply greater ﬁnancial security from farm earnings.
Nearly one-third of the asparagus growers worked off-farm, compared to only one-
quarter of the growers across the four subsectors. Off-farm earnings are thus used to
enhance overall ﬁnancial security.

Apple growers attended more extension meetings each year than the three other”
target groups. Whereas the mean number of meetings attended each year by all growers
was 4.2, apple growers attended 5.6 and blueberry growers attended only 2.2 meetings
per year. Meeting attendance indicates the degree to which growers seek outside input in
the management of their farms, possibly including information about sources of migrant
farm labor.

Nearly one-half of all growers reported some ability to speak/comprehend
Spanish. Nevertheless, these growers’ mean ability (on a scale of 1 to 5) averaged only a
1.5, indicating a distinct disadvantage across all growers in communicating with their
migrant employees.

Among growers responding to this survey, 83 (27%) did not hire migrant labor in
2000. Of the 33% of this group who hired migrant labor prior to 2000, more than 96%
were blueberry growers. The vast majority of blueberry growers stopped hiring migrant
labor because they switched to mechanical harvesting. Eighty-eight percent of these
growers reported that their farm earnings had stayed the same or risen since they stopped
hiring migrant labor.

While some growers reported that a labor shortage was indeed a problem, these

data show that a majority of the growers in each of the four target subsectors are able to

I40

hire sufﬁcient migrant labor. For example, although roughly one-quarter of the growers
in each subsector cited having insufﬁcient labor during the 1998 through 2000 growing
seasons, very few reported that this resulted in unharvested or late harvested acres. Thus,
few growers have suffered substantial income losses due to a shortage of migrant labor.

Most of the growers avoided a labor shortage by anticipating their needs for
future labor and planning accordingly. While most growers expect the decline in labor to
continue, they are preparing to meet this challenge by changing their farm management
practices (i.e., growing different crops, diversifying, giving up farming altogether, or
increasing mechanization).

An interesting ﬁnding of this chapter is that state-funded services are an untapped
source by growers for migrant recruitment purposes. Thus, one must ask how these
services can be improved to better help growers threatened by a shortage of labor.

This chapter has covered much information pertaining to grower perceptions

about migrant farm labor. The goal of the next chapter is to present a migrant viewpoint.

141

CHAPTER 5

MIGRANT FARM WORKER PILOT SURVEY AND FOCUS GROUP RESULTS,

AND A COMPARISON OF GROWER AND MIGRANT DATA

5.1 INTRODUCTION

This chapter reports information provided by eighteen migrant workers-—ten who
formally responded to the pilot survey in Fall 2002 and eight who participated in a two-
hour-long focus group in February 2003. Whereas Michigan State University student
volunteersl interviewed the ten survey respondents in a farm setting, the focus group
participants were drawn from among the undergraduate population at Michigan State
University. These eight students grew up in migrant families and traveled yearly to work
in Michigan fields. They are a sub-group of students recruited in recent years by
Michigan State University to pursue Bachelor’s degrees. All are in their ﬁrst, second, or
third year at the university and agreed to meet as a focus group for this project in
February 2003. The purpose of the focus group was to supplement the results obtained

from the small number of migrants who responded to the Fall 2002 survey.

 

' These students came from migrant backgrounds but were not the same individuals as
those who participated in the focus group.

142

The information presented in this chapter is not intended to counter the grower
results reported in Chapter 4. Rather, it is a starting point for better understanding
differences in the perceptions of Michigan growers and migrant workers with regard to
migrant farm labor issues. The results reported in thislchapter are intended to aid in the
development of future research objectives related to migrant farm labor issues in

Michigan, and possibly the United States.

5.2 MIGRANT STUDY FINDINGS

This section explores the results of the Fall 2002 migrant pilot survey and

February 2003 focus group.

5.2.1 Basic Demographics
Basic information was collected about both the pilot survey participants and focus

group participants. Some of the types of information vary from group to group since the
direction of conversation taken by the focus group was not always parallel in content to

the survey completed by pilot survey participants.

5.2.1.1 Pilot Survey Participants

The pilot survey respondents worked in Michigan as migrant farm laborers for a
mean of 23.3 years, spending from ﬁve to six months each year harvesting crops (Table
5.1). They reported being paid an hourly wage slightly above the mandated minimum

wage of $5.15/hour or, in some instances, a piece rate wage. They travel north annually

143

with a mean of 3.2 adults and 2.5 children. On average, participants reported that 2.4

workers contribute to the family income through migrant labor activities.

Table 5.1: General information about the pilot survey participants (Michigan, 2002)

 

 

 

 

 

 

 

contributing to

 

 

family income

 

 

 

Migrant Mean value 8‘31.“de n'| Comment
statistic devratron
Years worked 23.3 14.5 9
in MI as
migrant worker
Months spent 2000: 5.7 2.8 10
in MI doing 2001: 5.0 2.1 10
farm work in: 2000: 5.7 1.1 10
Mean hourly Apple 2002 $5.25 0.0 2 Piece rate (11 = 2,
wages received 2001 $5.25 0.0 2 2001-02; 11 = 3,
(2000-02): 2000 $5.25 1 2000)
Aspar— 2002 $5.70 0.6 5 No piece rate
agus 2001 $5.55 0.4 5
2000 $5.38 0.4 5
Blue- 2002 -- -- Piece rate for one
berry 2001 -- -- case each year
2000 $5.25 1
Pickle No data Respondents did
not work crop or
provide info
# of adults that 3.2 2.4 10 Refers to 2002
migrate with growing season
respondent
(including self)
# of children th: 2.5 2.1 10 Refers to 2002
migrate with growing season
respondent
# people 2.4 1.4 9 Refers to 2002

growing season

 

n refers to the number of responses to a particular question.

144

 

All of the respondents were permanent residents of Texas and migrate to

Michigan from Texas (Table 5.2). Nine of the ten preferred migrant work in Michigan to

any other state. One respondent preferred comparable work in Texas, but could not ﬁnd

suitable employment.

Table 5.2: Migrant permanent residence, crop and state preferences, hc
jobs are found, and opinions about difﬁculties in ﬁnding Michigan work,
by pilot survey participants (Michigan, 2002)

 

 

 

 

Characteristic Percent (11 = 10)
Permanent residence Texas — 100%
Preferred state in which to work Michigan - 90%
Texas — 10%
Preferred crop with which to work Apples — 40%

Asparagus — 10%
Blueberries — 20%
Pickles - 0%

 

Other“ - 20%

No Pref - 10%
Considers it easy or hard to ﬁnd work Easy — 90%
Michigan Hard“ - 10%

 

Finds places to work by“:

 

 

Family/friends — 60%

Asking around — 20%

Always returning to same farm - 10%
Driving around looking for farms - 10%
No response — 10%

 

a - The ‘other’ category refers to ‘greens’, including different lettuce types.

b - Multiple responses possible due to open-ended nature of this question.

c - The reason cited for why it is hard to ﬁnd work is that ‘growers already have
workers, making it hard to break in’.

145

 

5.2.1.2Focus Group Participants“

One-half of the focus group participants (11 = 8) were male; the other half were
female. Their mean age was 21 years. Seven of the eight were from Texas, and one was
a resident of Florida. Three of the students were freshmen, four were sophomores, and
one was a junior. The students and their families have been traveling to Michigan as
migrant workers for a mean of more than 10 years, with two students’ families coming to
Michigan for 25 and 30 years. Individually, they have participated in the migrant farm
labor force for a mean of nearly seven years, and almost all of them had worked as
migrant laborers with their families before entering their teenage years. Two of the eight
students have not yet specified a major field of study while the other six have selected
majors that include social work, international relations, landscape architecture, and

agribusiness management. All reported being well-informed about the ﬁnancial activities

of their families.

5.2.2 EASE OF FINDING EMPLOYMENT
5.2.2.1 Pilot Survey Participants

Ninety percent of the pilot survey respondents consider it easy to ﬁnd
employment in Michigan. By way of explanation, one respondent stated that returning to

the same farm(s) year-after—year guarantees job security, as does a long history of

 

2 Although unanimously reporting an aspiration to enter professions far removed from
mi grant farm labor, each focus group participant stated a desire for his or her children
to spend a portion of their lives in the ﬁelds, gaining an appreciation for the hard
work of their forebears and a clearer understanding of their heritage. All were proud
of their families’ role in American agriculture.

146

migrating to Michigan. Long—term familiarity with the state implies knowing where and
when crops are ready for harvesting, and where to go for a good farm experience. In
their own words, other respondents reported that it is generally easy to ﬁnd work in
Michigan because ‘there are many places to go in general’, ‘a good word-of-mouth
network exists’, ‘they come with a contract from Texas’, and ‘there are always
opportunities since Caucasians will not do the work’.

Only one of the ten survey respondents reported returning to the same farm year-
after-year. Sixty percent find new job opportunities through family and friends, in
keeping with the social capital connections discussed in Chapter 2, while another 20%

seek out word-of-mouth tips and 10% drive from farm-to-farm looking for work.

5.2.2.2 Focus Group Participants
The focus group participants were in agreement that it is not difﬁcult to ﬁnd
migrant work in Michigan. Only one focus group participant reported returning to the

same farm year-after-year. In this instance, the family has returned to the same farm for

25 years.

5.2.3 Crop Preferences
5.2.3.1 Pilot Survey Participants

The largest share of the respondents preferred harvesting apples (40%), followed
by blueberries (20%), ‘other’ crops (20%), and asparagus (10%). Reasons stated for crop
preference include ‘more money’ (11 = 4), ‘easier to pick/less tiring’ (n = 3), ‘can earn

money faster’ (n = 2), ‘fair pay’ (11 = 1), and ‘better weather conditions’ (11 = 1). Table

147

5.3 compares the nri grants’ preferences with the actual crops they harvested during the
2000 to 2002 harvest seasons. During this period, 60% to 70% of the respondents
harvested apples, 60% harvested asparagus, 20-40% harvested blueberries, and 10%
harvested pickles. Another 20% harvested ‘other crops’ (e.g., radishes, greens, and
onions). Although not representative of the migrant population at large (because of the
small sample size), these ﬁndings provided some interesting points for discussion during

the focus group’s meeting.

Table 5.3: Percent of the migrant survey
participants who harvested the crops relevant to this
study (Michigan, 2000-02)

 

 

 

 

 

 

 

 

 

 

 

Subsector Year Percent (11 = 10)
Apple 2002 60%

2001 60%

2000 70%
Asparagus 2002 60%

2001 60%

2000 60%
Blueberry 2002 ‘ 20%

2001 20%

2000 40%
Pickle 2002 10%

2001 10%

2000 10%
Other“ (radishes, greer 2002 20%
onions) 2001 20%

2000 20%
a - ‘Other’ includes radishes, onions, and different

types of lettuce.

148

5.2.3.2 Focus Group Participants

According to the focus group participants, their families preferred apples because
they are easy to harvest and it is less demanding to fulﬁll the basket requirements upon
which wages are based. Nevertheless, it was the focus group’s general perception that
apple work is difﬁcult to ﬁnd. Workers frequently return to the same orchard year— after-
year, reducing the number of job openings available to word-of-mouth job seekers.
Likewise, since the number of migrants seeking to ﬁll any remaining harvesting slots is
sufﬁciently high, apple—picking work is available to only a fraction of the migrants.
Ultimately, the focus group discussion suggested that there is a surplus of migrant
workers willing to work in Michigan’s apple sub-sector.

The focus group participants portrayed Michigan’s blueberry sub-sector quite
differently. Although 20% of the survey respondents prefer harvesting blueberries to
harvesting other Michigan crops, the focus group participants described working in the
blueberry sub-sector as a last resort among migrant workers. They described blueberries
as difficult and unpleasant to pick. While the wage value of a bucket of blueberries is on
par with the bin or basket value of apples (or other piece wage cr0ps), a bucket of
blueberries takes signiﬁcantly longer to gather. In addition, since picking blueberries is a
clumsy activity, much of what is harvested is often dropped before the berries are put into
the bucket. According to the focus group, it is much harder to earn a living picking

blueberries than it is to earn a living picking other fruits or vegetables.

149

5.2.4 Wage Preferences“

Regarding wages, the focus group reported that Florida workers generally prefer a
piece rate wage and Texas workers prefer a more precise hourly wage“. Further
discussion revealed a likely reason for this. Word-of-mouth is a common means by
which migrant laborers locate work opportunities. Using their Florida connections or
Texas connections (also known as their social capital ties, as described in Chapter 2),
Florida workers tend to follow the job leads provided by Florida workers and Texas
workers, likewise, follow job leads provided by workers from Texas. Over time, a
migration pattern has been established whereby more Florida workers are employed on
farms where a piece rate wage is the normal method of payment and more workers from
Texas gravitate towards farms that traditionally offer an hourly wage.

Having grown accustomed to one or the other of these payment methods, each
focus group participant was adamant in his or her support of the payment method to
which he or she has grown accustomed over time. For example, the Florida participant
insisted that a piece rate wage is the only acceptable way to earn a living as a migrant
worker. As long as the migrant is a fast picker, he or she will certainly earn more than
someone working for minimum wage elsewhere in the economy. Yet the Texas natives
were opposed to piece rate wages, claiming how easy it is for growers to underpay
migrant workers by using intentionally doctored scales or other improper measuring

equipment. When a grower’s claim contradicts a migrant’s, the Texas workers reported

 

3 Wage preferences were discussed by the focus group only.

‘ Regardless of the payment method, the focus group participants reported that they
choose to do migrant farm work for a host of reasons, including because they like the
work, can stay with their families, or consider themselves unqualiﬁed to do anything
else for language or educational reasons.

150

that the grower typically wins. For this reason, they overwhelmingly prefer being paid a
less disputable hourly wage.

This suggests that two factors might be working together to inﬂuence the
employment destinations of migrant workers: the anticipated social capital ties that lead

workers towards certain farms and the workers’ preference for how wages are calculated.

5.2.5 Individual and Family Income Levelss
Mean individual and family income levels for nine of the ten pilot survey
respondents are presented in Table 5.4. Across the three income categories—
respondent’s family’s income, respondent’s overall income, and respondent’s income
from only Michigan farm work--mean earnings increased yearly from 2000 to 2002.
Mean respondent income from Michigan farm work rose by 9.1% between 2000
and 2001 but by only 2.0% from 2001 to 2002. During these same two intervals, overall
respondent total yearly incomes rose by 16.2% and 21.0%. Considering that the mean
respondent income from Michigan farm work comprised 75% of the respondent’s mean
overall income in 2000, dropping to 60% of the mean overall income by 2002, it appears
that the survey respondents may have augmented their income through work other
than migrant farm labor (Table 5.5). While it is impossible to know from this survey
how respondents are enhancing their incomes, this information should be collected in
a future survey to gain a better understanding of the alternative employment options

that may be competing for a traditional migrant farm worker’s time and energy.

 

5 This information was collected from the pilot survey participants only.

151

Table 5.4: Mean individual and family income statistics among
pilot survey participants (Michigan, 2000-02)

 

 

 

 

 

 

 

 

 

 

Income category“ Mean Standard Number of
deviation responses
Total family 2002: $15,778 6,760 9
income in: 2001: $13,000 5,657 9
2000: $12,000 5,723 9
Respondent’s total 2002: $ 10,1 1 1 5,255 9
income in: 2001: $8,389 4,137 9
2000: $7,222 3,962 9
Respondent’s income 2002: $6,063 2,933 8
from MI farm work in: 2001: $5,944 2,744 9
2000: $5,444 2,651 9
Mean % of family’s
annual income spent 59.4% 21.4 9
in MI:
a - Migrant families generally pool their eamings such that the

respondent’s income is a fraction of the family’s total income.
Despite coming to Michigan as a migrant worker, each respondent
generally worked for pay outside the Michigan agricultural sector
during part of the year.

Table 5.5: Individual income from MI farm work as a percentage
of overall individual income and overall individual income as a
percentage of overall migrant family income (Michigan, 2000-02)

 

 

 

 

Income category Year Mean percent
Respondent’s income from Michigan farm work, 2002 60%
as a % of his/her overall income in: 2001 71%

2000 7 5%
Respondent’s overall income, as a % of the 2002 64%
respondent’s family’s overall income in: 2001 65%

2000 60%

 

 

 

 

152

 

During the last three years, collectively, the respondents’ mean earnings
comprised roughly two-thirds of their families’ incomes. This percentage has remained
fairly steady, implying that the other breadwinner(s) in the family are also continuing to
seek additional work. Otherwise, the individual’s income would be rising as a percent of

the family’s overall income.

5.3 ADDITIONAL MIGRANT FINDINGS
This section explores additional ﬁndings from the Fall 2002 pilot survey and the

February 2003 focus group.

5.3.1 A Potential Explanation for the Shortage of Labor on Blueberry Farms

As described in Section 5.2.3.2, the physical nature of the task may account for
why blueberry growers ﬁnd it more difﬁcult to attract workers than do apple, asparagus,
or pickle growers. Although in concordance with Hypothesis 2 (i.e., that blueberry
growers have greater difficulty locating farm labor than the three other sub-sectors,
primarily because of insufﬁcient housing), the reason for Hypothesis 2 is probably
incorrect. Rather, blueberry growers ﬁnd it difficult to recruit labor because of the
difficult manual labor associated with picking blueberries-mot because of insufﬁcient
housing (as hypothesized).

If blueberry picking is more labor—intensive and it is difﬁcult to earn a living
picking this crop, the number of return laborers should be less than in the other sub-
sectors. However, the data collected from growers do not bear this out. Rather,

blueberry growers reported almost the same number of return workers from previous

153

years as other growers and had the highest percentage of employees returning after ﬁve
years (Table 4.7). This discrepancy may be due to the possibility that migrants who work
on blueberry farms came from a different part of the United States than those who
responded to the Fall 2002 migrant survey. As shown previously, there is some evidence
that Florida workers and Texas workers seek work at different types of farms because of
the different kinds of wages offered on those farms (hourly wages versus piece rate
wages). Therefore, the information reported by the Texas migrants may not fully
explain the shortage of migrant workers on blueberry farms. Only an extensive survey of

migrants from numerous origins can help determine whether or not this is true.

5.3.2 Migrant Incomes and the Poverty Line

A family of five earning less than $21,540 in the United States is considered to be
living below the poverty line (Federal Register, 2003.) As noted previously, the mean
number of migrant family members traveling together is 5.7. Rounding down for a
conservative estimate, the family income of the average respondent to the Fall 2002

migrant survey is at least 27% (or $5,800) below the nation’s poverty line“.

5.3.3 Estimated Percentage of Migrant Farm Earnings Returned to the State of
Michigan as Expenditures
Respondents to the Fall 2002 migrant survey estimated that 60% of their family’s

annual income is typically spent in Michigan (Table 5.4). Assuming that the ratio of the

 

" These ﬁgures do not take into account the income of non-traveling family members
that may have stayed behind in Texas or Florida, or the value of perquisites (e.g.,
housing).

154

family’s migrant farm income to the family’s overall income (i.e., wages earned on-farm
to those earned on- and off-farm) parallels the income ratio obtained for the individual
respondent, their mean family income from Michigan farm work was roughly $9,000 in
2000, $9,200 in 2001, and $9,500 in 2002. Comparing these numbers to estimates of
their mean in-state expenditures7 ($7,100 in 2000, $7,700 in 2001, and $9,400 in 2003), it
is probable that no more than $2,000 per family left the state in any of the three years.

This ﬁnding was corroborated during the focus group discussion when the
participants unanimously stated that they have never seen their families depart with more
than $2,000. Rather, their families spend almost all of their earnings in Michigan before
heading home to Texas or Florida, the intention being to make all clothing and other
purchases while money is still available.

A breakdown of migrant expenditures is presented in Table 5.6. All of the
respondents purchased food--more than $90 worth each week, according to the six
respondents who estimated their weekly food expenditures. Two-thirds purchased

clothing, estimated at $55 per week.8 More than one-half of the ten respondents
paid rent where they lived.9 One-third spent a weekly mean of $75 on daycare, while

only one-fifth of the respondents reported weekly medical expenditures. Clearly, while

 

7 This calculation was based on 60% of the overall mean family income for each of
the three years (Table 5.5).

8 The focus group participants stated that their families’ clothing purchases for the
year were made in Michigan during the harvest season. The small sample size was
likely responsible for the seemingly high weekly cost of clothing. A future study,
based on a larger sample size, would serve to correct this ﬁgure.

9 Three respondents provided rental data. One paid $160/week, the second paid
$280/week, and the third paid $300/week.

155

in-state, migrant workers spend a large share of their income supporting our local
economies.

A surprising ﬁnding is that so many migrants pay rent while in Michigan.
Although the sample size is small and may not be representative of Michigan’s overall
migrant population, this ﬁnding contrasts with the general perception that the low wages

received by migrant workers are somewhat offset by free housing.

Table 5.6: Pilot survey participants’ weekly expenditures, and the estimated
mean weekly cost of these expenditures while living in Michigan
(Michigan, 2002)

 

 

 

 

 

 

 

 

 

 

 

 

 

Type of Percent yes If yes, mean weekly Standard
Expenditure n = 10 expenditure ($) deviation“

Rent 56% $250 76 (3)

Food 100% $90 57 (6)

Daycare 33% $75 35(2)

Medicine 22% $75 NA (1)

Clothing 67% $55 33 (4)
Transportation 1 1% NA NA

a - The number in parentheses indicates the number of respondents who cited a

value for inclusion in the expenditure mean.

5.3.4 Likes and Dislikes About Migrant Farm Work in Michigan

The migrant farm workers that participated in the pilot survey provided useful
information concerning what they like and dislike about migrant farm work in Michigan.
The respondents were asked open-ended questions regarding their top three likes and
dislikes about Michigan farm work. The responses were compiled accordingly,

maintaining the wording used by the migrants as much as possible.

156

When asked what they like best about working in Michigan, 70% of the pilot
survey respondents (11 = 10) ranked ‘the availability of housing/living conditions’ among
their top three choices (Table 5.7)‘9,“. Sixty percent ranked ‘better pay and beneﬁts’ in
the top three, followed by ‘weather’ (40%), ‘family time together’ (30%), ‘many farms to
choose from’ (30%), a ‘better work environment than in other places’ (20%), and ‘a
change of scenery from Texas’ (20%).

Table 5.7: Percentage of pilot survey respondents ranking following factor

among their top three positive reasons for working
as migrants in Michigan (Michigan, 2002)

 

 

Factor Percentage of respondents ranking this
factor among top three reasons (n = 10)
Housing/living conditions 70%
Better pay/benefits 60%
Weather 40%
Family time together 30%
Many farms to choose from 30%
Better work environment 20%
Change from Texas 20%

 

 

 

 

Despite its lead in the rankings above, none of the respondents cited
‘housing/living conditions’ as the top-ranked reason for seeking employment in
Michigan. Rather, three of the ten respondents cited Michigan’s ‘weather’ and two cited

‘many farms to choose from’ as their primary reason”.

 

'9 Three of the ten respondents did not offer a third ranking.

" The focus group participants referred to Michigan migrant housing as not very nice
- but better than in the past.

'9 If not noted in the text, the other factors received no more than one vote at the
speciﬁed ranking. This holds true for the remainder of the data presented in this
portion of the text.

157

Among the second-ranked reasons for choosing to work in Michigan, four of the
ten respondents cited ‘better pay/beneﬁts’ and three cited ‘housing/living conditions’.
Among the third-ranked reasons, three of the seven respondents cited ‘housing/living
conditions’.

When asked what they like least about working in Michigan, 66% of the pilot
survey respondents (n = 9) ranked ‘discriminationlmistreatment of workers’ and 56%
ranked ‘housing/utility costs’ among their top three choices (Table 5.8). Forty-four
percent each ranked ‘getting to Michigan hard/dangerous’ and ‘harsh work, low pay’

among the top three reasons. Two of the nine respondents cited the ‘weather’.

Table 5.8: Percentage of pilot survey respondents ranking following factor
among their top three negative reasons for working as migrants in Michigal

 

 

(Michigan, 2002)
Factor Percentage of respondents ranking
this factor among top three reasons
(I) = 9)

Discrimination/mistreatment of workers 66%
Housing/utility costs 55%
Getting to Michigan hard/dangerous 44%
Harsh work, low pay 44%
Weather 22%

 

 

 

 

To summarize, ‘housing’ and ‘better pay/beneﬁts’ led the list of top three reasons
why the pilot survey respondents seek employment in Michigan. These factors were not
the primary positive factors reported by this group of migrants, yet each falls within the
top three reasons cited by a majority of the respondents. ‘Discrimination’, ‘housing/utility
costs’, and ‘the difﬁculties of coming to Michigan’ led the list of top three negatives

associated with migrant farm labor in Michigan. Thus, economic factors were

158

responsible for the positives associated with Michigan migrant labor, while non-

econorrric factors accounted for two of the three negatives.

5.3.5 What Migrants Look For When Seeking Employment

An open-ended question included in the Fall 2002 pilot survey asked the
respondents to identify three primary considerations when seeking employment. As
Table 5.9 shows, these answers are similar to the reasons why migrants like and dislike

farm work in Michigan.

Table 5.9: Percentage of pilot survey respondents ranking following
factors among their top three considerations when seeking farm work in
Michigan (Michigan, 2002)

 

 

Factor Percentage of respondents ranking this
factor among top three reasons (n = 9)

Pay 100%

Housing 100%

Good employer relation ship/ 44%

decent boss

Amount of work 33%

Area around farm 11%

 

 

 

 

One hundred percent of the pilot survey respondents (n = 9) ranked ‘pay’ and
‘housing’ among their top three considerations when seeking employment”. Forty-four
percent ranked ‘amount of work’ in the top three, followed by ‘a good employer

relationship/decent boss’ (33%).

 

’3 One of the ten original respondents offered no rankings for this question, and one
other offered no third ranking.

159

Six of the nine respondents cited ‘pay’ as the top-ranked reason for seeking
employment in Michigan while three cited ‘housing’. An additional ﬁve ranked housing
second. Among the third-ranked reasons, three of the eight respondents cited ‘amount of
work’, while two apiece cited ‘pay’ and ‘good employer relationship/decent boss’.

In summary, economic factors are migrants’ most important considerations when
seeking farm employment. Apparently, migrant workers only take non-economic factors
(e.g., condition of housing, grower personality etc.) into consideration after the most
basic economic needs of the family have been met. This implies that farms offering the
same base level of pay and housing must compete with one another for workers with
respect to housing maintenance”, difﬁculty of the work, and treatment of workers by
employers.

The focus group discussion corroborated these findings, with the words ‘trust’ and
‘respect’ coming up repeatedly. According to the focus group participants, growers who
show respect for their workers will be able to recruit enough employees, as long as the
workers’ most basic economic needs are met. The focus group participants commented

that migrant farm labor is very hard work for very low wages.

5.3.6 Perceived ‘Good’ and ‘Bad’ Farm Characteristics

Respondents to the Fall 2002 migrant survey were asked (in an open-ended
format) to describe the characteristics by which they differentiate between ‘good’ and
‘bad’ farms. As shown in Table 5.10, one-half of the respondents described ‘good’

farms as ones where they are treated nicely and respectfully. Keeping in mind that more

 

“ Housing maintenance was noted by two of the respondents.

160

than one response was possible, migrants characterized a ‘good’ farm as one where the
grower pays them well (40%) and the housing is clean and safe for children (30%).
Weekly pay, bonuses, and pay that are set in accordance with the success of the growing
season are also characteristic of a ‘good’ farm (10% each).

The respondents described a ‘bad’ farm as one where the grower is perceived
as unfair about rightful pay (30%), where the pay does not adequately compensate the
worker for his or her effort (30%), or where too much work is required of the migrant
worker (20%). Twenty percent of the respondents cited poor living conditions-~including
the availability of only outside utilities, no heat, and/or a very small living space--as
indicative of a ‘bad’ farm, while 10% cited a grower with insufﬁcient funds to cash

checks, or who is inconsiderate towards migrant workers.

Table 5.10: Characteristics that migrant workers felt contribute to a
‘good’ and ‘bad’ work environment (Michigan, 2002)

 

 

 

 

 

 

 

 

Characteristic“ Description Percent
(n = 10)
Good -- People treat us nicely - respectfully 50%
-- Grower pays well 40%
-- Housing clean, safe (especially for children) 30%
-- Pay depends on season (if crop good, then pay less) 10%
—- Pay is given weekly 10%
-- A bonus is given 10%
-- No response 20%
Bad -- The grower tries to cheat us 30%
-- Pay too little 30%
—- Require too much work 20%
-- Poor living conditions (i.e., outside utilities, no heat) 20%
-- Farmer has insufﬁcient money to cash checks 10%
-- Farmer rude, selﬁsh, and inconsiderate 10%
-- No response 20%
a - More than one response was possible due to the open-ended nature of

this question.

161

These ﬁndings are consistent with the information provided by the focus group
participants, who cited the importance of decent treatment of, and respect for, migrant

workers.

5.3.7 Migrants’ Perceptions of the Farm Labor Situation and Plans for the Future

Table 5.11 describes both migrant opinions about the number of migrant farm
workers presently migrating to Michigan and what the respondents expect to be doing
one year and ﬁve years from now. Since these data were obtained from only ten
respondents, these results are not statistically comparable to the growers’ responses
(Chapter 4).

Table 5.11: Migrant opinions about the number of workers
coming to Michigan, and future plans (Michigan, 2002)

 

 

 

 

 

 

 

Opinion Percent (11 = 10)
Migrants coming to Michigan:
More 20%
Fewer 70%
No response 10%
Plan to return to Michigan next year:
Yes 90%
No 0%
No response 10%
Expect to come to M1 in five years:
Yes 50%
No 30%
Undecided 10%
No response 10%

 

Seventy percent of the respondents believe that fewer migrants are coming to
Michigan now, compared to in the past. The reasons given are primarily economic in

nature, including that a migrant worker’s life is a hard life that few people choose to live

162

given other economic opportunities, that more people are staying home to ﬁnd jobs, that
insufﬁcient government support is available for migrant families to continue as migrant
laborers, that wages are not increasing as rapidly as migrants would like, that less work is
available (making the trek to Michigan economically unfeasible), and that it is difﬁcult to
ﬁnd adequate housing15 . It is interesting, and a symptom of the perceived problem, that
each respondent had a different explanation about why there may be less labor coming to
Michigan at harvest time. In other words, many explanations may be responsible.

In contrast, only 20% believe there are now more rrrigrants19 coming to Michigan.
One respondent said that he or she is continually running into more and more migrants
from other parts of the United States and Mexico, while the other stated that the work
expected of migrants is now less demanding, in turn attracting more migrants to
Michigan.

At least 90% of the respondents plan to return to Michigan for the 2003 harvest,
while only 50% expect to return in ﬁve years”. Most plan to return to Michigan
because this is the only kind of work they know how to do, and for which lack of a
formal education is not a detriment (n = 7). While they continue to work as migrant
laborers, until they are no longer physically capable, they do not want their families to
stay in the ﬁelds forever. Additional responses were more family-oriented (e.g., spending

time with their families by working alongside them in the ﬁelds (11 = 1) and visiting

family members that reside permanently in the state of Michigan (n = 1)).

 

‘5 For each reason cited, n = 1.
‘6 In one case, no response was given.

‘7 Since many of the respondents are getting older, they had difﬁculty making a ﬁve-
year projection. Each year’s work is more physically challenging than the last.

163

5.4 TWO MIGRAN T PERSPECTIVES

The focus group discussion uncovered contrasting Michigan experiences for two
of the participants-both males in their early 205 who have been conring to Michigan as
migrant workers for many years'“.

Pedro has migrated to Michigan with his family every summer since he was an
infant. His family has returned to the same apple orchard year-after-year, he knows the
grower and his family well. Each year, Pedro’s family stays in the same house.

Michigan has become a second home, where the events of Pedro’s family’s life are
strongly intertwined with those of the grower’s family’s.

Several years ago, when Pedro became a worker on the same farm as his parents,
he already had the grower’s trust. Years of knowing one another had resulted in social
capital. Whereas the grower is obliged to check the harvest claims of other, newer
migrants, he has never doubted Pedro’s work. The respect, trust, and courtesy the grower
shows to Pedro resulted in his determination to do a good job. Pedro is proud of his role
in the orchard and has never felt the compulsion to cheat the grower, or to get even for a
perceived slight.

This sense of mutual trust and respect has resulted in a pleasant work
environment. Until he has completed his education at Michigan State University, Pedro

will continue to work for this grower. In addition, the grower expects Pedro’s family to

return year-after-year. This arrangement provides the grower with trusted labor, Pedro’s

 

'8 Their names have been changed to protect conﬁdentiality.

164

family with a decent, respectful place to live and work, and both parties with a sense of
mutual beneﬁt and involvement.

Mi guel’s perspective is signiﬁcantly different from Pedro’s. Troubled by a
difﬁcult family life in Texas, Miguel left home in his early teens, traveling to Michigan
as a migrant worker. He has worked on many kinds of farms, without the sense of
permanence or loyalty experienced by Pedro. Like other new, not-yet-proven workers,
he has spent much of his time under the close scrutiny of growers, acknowledging their
distrust of him with his own distrust of them. In Miguel’s mind, no grower is honest and
must be watched carefully by the migrants who are in his or her employ.

Having no doubt that all growers are untrustworthy, Miguel is of the mindset that
migrants should cheat growers whenever they can since it is inevitable that growers,
likewise, will cheat migrants at the first opportunity. Miguel described adding soil to the
boxes of produce he harvested--as a means for compensating himself for the obvious and
intentional under-weighing of produce carried out by the grower. Unquestionably, this
sense of distrust leads both parties towards even greater levels of deception and lost
opportunities for a respectful and mutually beneﬁcial work environment.

Pedro and Miguel are both articulate students. Yet they exhibit signiﬁcant
attitudinal differences about their roles as migrant farm laborers in Michigan. Pedro
sympathizes with his employer, reckoning that earning a living as a grower is almost as
difﬁcult as earning a living as a migrant worker. Miguel, on the other hand, is
undisguisedly distrustful of his employer, who he describes as earning money hand-over-

ﬁst by underpaying migrant workers.

165

Although nothing more is known about the two growers described by Pedro and
Miguel above, it is likely that social capital (e. g., how their relationship impacts their
ability to work together) is at least partially responsible for these two individuals’

attitudinal differences.

5.5 A COMPARISON OF GROWER AND MIGRANT DA TA, AND SOCIAL
CAPITAL FINDINGS
An important goal of this research is to identify areas of commonality and
dissonance between Michigan growers and migrant farm workers. As a way to improve
communication between the two groups, and the work environment experienced by both
parties, this section explores the perceptual similarities and differences detected in the
responses supplied by growers and migrants. It also presents the social capital ﬁndings

that help to explain these perceptual differences.

5.5.1 A Comparison of Opinions Reported by Growers and Migrant Farm
Workers in Michigan
The perceptual differences noted between growers and migrants can be
categorized, by topic, as follows: job search and recruitment, migrant housing and
perquisites, wages, reasons for (and solutions to) the perceived decline in migrant farm

labor, and characteristics of a satisfactory work environment.

166

5.5.1.1 Job Search and Recruitment

During the 1998 through 2000 growing seasons, no signiﬁcant differences were
observed in the year-to-year migrant worker retention rates. Despite widespread
complaints that labor was getting harder to recruit, growers retained the same percentage
of workers as the previous year. In fact, 73% of the growers reported having verbal
agreements with past workers, which implies that the traditional core of workers is not
shrinking.

Ninety percent of the migrant respondents consider it easy to ﬁnd work in
Michigan. Since only one of the ten respondents returns to the same farm year-after-year,
this suggests that mi grants do not consider verbal agreements between growers and
migrants a necessary precursor to employment. Migrants with long years of experience
in Michigan know the ‘good’ farms at which to seek employment. In addition, word-of-
mouth plays an important role in pointing workers towards worthwhile harvesting
opportunities.

Growers and migrants share a similar unenthusiastic view of the matching
services offered in Michigan. Established as a mechanism by which growers and migrant
workers can be paired up for harvesting activities, survey results indicate that growers
tend not to use these services while migrants have sufﬁcient other connections through

which to locate harvesting work'“.

 

’9 The State Monitor Advocate of Michigan stated in a recent conversation that the
matching services provided by the state of Michigan are better used than indicated by
this study. He stated that the expression ‘matching services’ may have been
misunderstood by grower and migrant respondents. It is also possible that other
subsectors, as yet to be identiﬁed, make better use of this state resource, accounting
for the discrepancy.

167

5.5.1.2 Migrant Housing and Perquisites

It was initially thought that many migrants live off-farm because of a housing
shortage, particularly in the blueberry subsector. Yet more than 80% of the grower
respondents supplied housing to their farm workers. In fact, the mean number of
migrants for whom housing was available on any given farm greatly exceeded the mean
number of workers employed or needed. This phenomenon may be explained by housing
that is in poor condition and therefore uninhabited.

Migrants reported that they prefer to choose their own accomodations whenever
possible, which is consistent with the statement by a majority of them that they pay rent
while doing harvesting work. This is also consistent with the ﬁnding that 50% of the
growers had migrants that live off-farm, despite underutilized housing available on their
farms. Although uninhabited, growers could still claim that housing is available for
migrants who work on the farm. 1

In terms of perquisites, it is interesting to note that apple and pickle growers
reported providing more perquisites to migrants than blueberry or asparagus growers.
Yet, based on the migrant survey and focus group interviews, migrant workers seldom
consider in-kind provisions (such as laundry facilities or end-of-season ﬁestas) as

perquisites to supplement their harvest earnings.

5.5.1.3 Wages
Growers and migrants reveal a contrasting description of wages paid. The grower
data suggest real wage payments exceed the state-mandated minimum wage by 46% and

standardized wages exceed the minimum wage by 24%. In contrast, the migrant workers

168

were adamant that they typically do not receive a wage as high as the minimum wage.
Furthermore, the focus group participants stated that growers regularly cite regulations
that enable them to reduce migrants’ eamingszo.

One possible explanation for this is a lack of understanding on the part of the
migrants regarding the federal mandate that growers with farms Of a certain size must
withhold taxes, social security, and Medicare from rnigrarlts’ paychecks. Likewise,
agriculture is exempted from paying one and a half times the minimum wage for
overtime and growers can legally deduct rent from paychecks, if workers sign a consent
form. These are rules that migrants may not be aware of, thus contributing to their belief

that growers are treating them unfairly.

5.5.1.4 Reasons For (and Solutions To) the Decline in Migrant Farm Labor

Both growers (68% of respondents) and rrrigrants21 anticipate a decline in the
availability of migrant labor over the next few years, primarily because of increasing
opportunities available to unskilled workers elsewhere in the economy. In fact, ten
percent of the growers reported anticipating going out of business in the near future, in
part because of the projected costs associated with the cost of labor when demand

exceeds supply.

 

9° For example, the focus group participants argued that growers frequently tell
migrant workers that by providing them with housing and utilities, they are exempted
from having to pay overtime wages, and thus do not—although migrants are expected
to work overtime.

2' Three of the ten pilot survey respondents do not plan to be here in ﬁve years while
seven out of ten reported fewer migrants coming to Michigan now than in the past.

169

One of the more remarkable ﬁnding of this research concerns the
recommendations put forth by growers about how to correct for the anticipated worker
shortfall. Every recommendation looked past the farm gate for a solution. Growers
recommended interventions such as the use of seasonal permits for foreign workers,
federally guaranteed minimum crop prices, and the relaxation of government regulations.

In sharp contrast, the migrant respondents and focus group participants
emphasized the importance of higher wages, satisfactory housing, working on a farm
where they feel valued and respected, and where the grower displays honesty and
integrity. The migrants reported that they do not mind the hard work associated with
farm labor but do mind a work environment where they feel degraded or treated unfairly.
Thus, ﬁnding ways to increase wages, improve housing, and treat migrant workers in a
fair and courteous manner may enable growers to more easily attract migrant workers. A

future study of migrants will be useful towards verifying these initial ﬁndings.

5.5.1.5 Characteristics of a Satisfactory Work Environment

The above ﬁnding leads directly into the characteristics of a satisfactory work
environment, as described by the migrant students who participated in the February 2003
focus group. Both the respondents to the pilot survey and the focus group participants
reported that economic and non-economic factors contribute to a positive farrrr
experience. Although migrants often seek farm work as a lifestyle choice, it is frequently
because they have few other opportunities.

Although migrants primarily consider economic criteria (such as wages) when

seeking farm work, they consider non-economic criteria as soon as the most basic

170

economic needs of the family have been met. Such criteria include the physical condition
of the house in which they are expected to live, the difﬁculty of the work they are

expected to do, and the grower’s reputation as a fair and respectful employer.

5.5.2 Social Capital Implications of this Research

The secondary criteria (after housing and wages) that migrants consider when
seeking employment (Section 6.2.1) are consistent with social capital theory, as described
in Chapter 2. For example, if wage rates are equal, a migrant worker prefers to work on a
farm where the employer recognizes his or her worth, and the migrant feels trusted and
respected““. As such, the non-economic environment of a farm is strongly inﬂuenced by
the quality of personal interaction between growers and migrant farm workers. A more
comfortable and, hence, more ‘attractive’ environment exists on farrrrs where grower-
migrant relations are enhanced by signiﬁcant amounts of bridging social capital”.

Despite the small sample size, the information gathered through the migrant pilot
survey and focus group is consistent with social capital theory. For example, the
inherited kernels of commonality described in Chapter 2 help to explain the divergent
migration paths followed by a majority of migrant workers from Texas and Florida.
Texans, through experience and exposure, have taught other Texans to prefer work on

farms where hourly wages are paid. Floridians, on the other hand, lead newcomers from

 

“2 Recalling Section 5.5, Pedro enjoys his work on a speciﬁc Michigan farm because
of the decades-long social capital his family has shared with the grower’s family.
Encouraged by this relationship, Pedro returns year-after-year to the same farm,
which enhances the economic well being of both the grower and the migrant family.

“9 Bridging social capital encompasses employer-employee relations, in which two

parties from potentially different backgrounds develop a sense of caring for one
another through a positive working relationship.

171

Florida towards farms where piece rate wages are paid. Social capital theory provides an

explanation for these migration patterns that economic theory cannot.

5.6 CONCLUSION

Because the information provided in this chapter is based on the responses of only
18 migrants, a large-scale survey of migrant farm workers in Michigan is recommended,
utilizing similar questions as those described in this chapter. The purpose of the survey

would be to conﬁrm or reject the migrant ﬁndings reported in this dissertation.

172

CHAPTER 6

SUMMARY, CONCLUSIONS AND POLICY RECOMNIENDATIONS

6.1 INTRODUCTION

The main ﬁndings of this research are two-fold. First, three-quarters of the
respondents to the grower survey reported having sufﬁcient labor in 2000. Of the 25%
reporting insufﬁcient labor, half could not harvest a portion of their crop while 75%
harvested some of their acres late. Second, the pilot study and focus group results
suggest that although migrants consider pay a primary factor in choosing a place of
employment, the work environment is also a strong consideration.
Thus, the conclusions and policy recommendations that follow are relevant for sustaining
the long-teml availability of labor and improving grower-mi grant relations that impact
farm success and productivity, even on farms not presently experiencing labor

recruitment problems. They are immediately relevant to growers presently experiencing

labor recruitment problems.

6.2 SUMMARY OF THE MAIN RESEARCH FINDINGS
This section summarizes the research ﬁndings in the context of the hypotheses put

forth in Chapter 1. A separate summary is provided for each hypothesis.

173

Hypothesis 1: Growers who provide housing will be able to more easily recruit and
retain migrant farm labor.

The results were mixed regarding this hypothesis. First, housing and ease of
recruiting were not signiﬁcantly correlated for any of the three years. Thus, the
provision of housing by a grower was not a strong indicator of the ease with which he or
she was able to locate sufﬁcient labor. Second, although none of the pilot survey or focus
group respondents chose housing as what they like best about working in Michigan, 70%
of the pilot survey respondents consider it among their top three considerations when
seeking farm work in Michigan.

These ﬁndings suggest that housing provision may not be the key factor

responsible for whether or not growers can ﬁnd sufﬁcient labor. Nevertheless, it is an

important factor.

Hypothesis 2: Apple, asparagus, and pickle growers have an easier time recruiting
migrant farm labor than blueberry growers.

The results supported this hypothesis'. First, during 1998 through 2000, a
statistically signiﬁcant greater percentage of blueberry growers reported having difﬁculty
hiring sufﬁcient labor compared to other growers. Second, compared to other growers, a
smaller percentage of blueberry growers provided migrant housing in 2000. This
difference was statistically signiﬁcant between apple and blueberry growers.

However, the focus group participants raised an interesting point related to this

issue. When asked if the shortage of migrant farm workers on blueberry farms was

 

' The premise for this hypothesis was that blueberry growers were thought to provide
less housing opportunities than growers in the other three subsectors.

174

related to a shortage of housing, they said no. Rather, they unanimously stated that
blueberries are a very hard, ﬁnancially unrewarding crop to pick (Section 5.2.3). They
would rather pick any crop other than blueberries, and would only work on blueberry
farms as a last resort. This may explain why the availability of migrant housing was

found to be unrelated to sufﬁcient labor.

Hypothesis 3: Large farms (wherein farm size is defined in terms of total farm
acreage, crop earnings, and estimated total farm earnings) have an easier time
recruiting and retaining migrant farm labor than small farms.

The data did not support this hypothesis. No statistically signiﬁcant association
was noted between farm size and whether or not a grower had sufﬁcient farm labor in
1998-2000. This was true for all deﬁnitions of farm size: total farm acreage, crop
earnings, and estimated total farm earnings. Thus, these results indicate that farm size is

not a likely inﬂuence on a grower’s ability to attract sufﬁcient labor to his or her farm.

Hypothesis 4: Higher real wages lead to easier recruitment and retention of
workers.

The results of this study were inconclusive regarding Hypothesis 4. The grower
analysis did not support this hypothesis while the migrant analysis did. Based on the data
obtained from growers, real wage levels were not found to have a statistically signiﬁcant
correlation with the ability of growers to recruit sufﬁcient migrant labor at harvest time in
2000. Nor did real wage levels have a statistically signiﬁcant correlation with the

percentage of migrants who had worked previously on the same farm or who had worked

175

on a particular farm for ﬁve or more years (Pearson correlation). Thus, the grower results
do not support the hypothesis that growers who pay higher real wages can more easily
recruit and retain workers.

In contrast, the migrant results indicate that higher wages are among the top three
incentives for migrants to seek work in Michigan. Although discussed as wages rather
than estimated real wages (as calculated in Chapter 4), this ﬁnding suggests that wages
inﬂuence where migrants seek employment and, by association, must impact the worker
retention rates on farms. Although additional data collected from migrants will clarify

the implications of this finding, the results from growers and mi grants are presently

mixed.

Hypothesis 5: By taking into account migrant housing and other perquisites, real
migrant wages are ultimately higher than the minimum wage, service sector wages
received by workers elsewhere in the economy.

As discussed in Chapter 4, standardized and real migrant wages are well above
the $5.15/hour state-mandated minimum wage rate in Michigan“. Eighty-eight percent of
the apple growers paid two to three dollars above Michigan’s minimum wage of $5.15
per hour while two-thirds of the asparagus and blueberry growers paid from one to two

dollars above minimum wage. The mean standardized hourly wage paid by pickle

 

2 Nevertheless, the migrant students who participated in the focus group consistently
remarked that they have seldom, if ever, received minimum wage for their harvesting
activities, which suggests that this issue needs further study. This has been
particularly true during the last ﬁve growing seasons, which the migrants described as
weather-compromised, difﬁcult seasons during which wages were lower than usual.

176

growers was $5.94/hour, with four of the ﬁve pickle growers paying less than a dollar

above minimum wage.

Hypothesis 6: Spanish-speaking growers have an easier time recruiting and
retaining labor than growers who lack this ability.

Generally speaking, the analysis did not support this hypothesis. Less than one-
half of the growers reported any ability to speak Spanish and, among those who do, their
mean proﬁciency level was only 1.5 (on a scale of 1 to 5, with 5 being a ﬂuent speaker).
Although a weak statistically signiﬁcant relationship was noted between a grower’s
ability to speak or understand some Spanish (regardless of ﬂuency level) and having a
sufﬁcient number of migrants in 2000 (chi-square = 3.1, sig = .078), non-significant
results were obtained for 1999 and 1998. Likewise, non-signiﬁcant associations were
obtained between levels of ﬂuency and having a sufﬁcient number of migrants in any of
the three years.

These ﬁndings may be attributable to the ﬁnding that Spanish ﬂuency was
generally low across growers“. Since the analyses were based on only minor ﬂuency
differences, and the ﬂuency levels were of a rudimentary nature, the correlation between
Spanish ability and recruitment/retention rates were non-signiﬁcant. Furthermore, the

survey did not explore the availability of Spanish-speaking supervisors or translators to

migrants on farms.

 

3 The migrant farm workers who took part in this survey corroborated this ﬁnding,
stating that since they have met so few Spanish-speaking growers, Spanish ﬂuency is
not a useful criterion for them when seeking farm employment.

I77

Hypothesis 7: Growers whose workers return year-after-year are better able to
recruit and retain migrant farm labor.

The Pearson correlation between sufﬁcient labor and the percent of migrants
returning to the same farm for ﬁve or more years is signiﬁcant, although sufﬁcient labor
is not signiﬁcantly correlated with the more general category of percentage of workers
who have worked on the farm in previous years. Thus, the analysis supports the

hypothesis that growers with a high percentage of long-term return employees are better

able to access sufﬁcient quantities of migrant farm labor.

Hypothesis 8: Growers whose migrants return year-after-year have lower
transaction costs associated with locating and retaining farm labor.

It was not possible to directly test this hypothesis using the data from the grower
survey, although anecdotal evidence obtained from the migrant workers supports this
hypothesis. As noted in the perspective comparison of Section 5.5, in which one migrant
family has returned to the same Michigan farm for dozens of years, a long, trusting
relationship has developed between a mi grant’s family and a Michigan grower’s family.
Although not explicitly stated, the grower has no search costs associated with continually
attracting this family to his farm, nor does he or she find it necessary to expend extra time

or money monitoring the harvesting activities of this group of workers.

178

Hypothesis 9: Perceptions of growers and migrants differ regarding what
inﬂuences recruitment and retention.

The analysis supported this hypothesis. Whereas growers describe wages,
housing, and perks as tools for attracting migrant farm workers to their farms, migrants
describe housing, wages, grower honesty, and respectful treatment of workers as key
factors they seek in a satisfactory work environment. In other words, growers may
undervalue demonstrably fair and respectful treatment of workers as a factor that

inﬂuences the work environment in ways likely to attract sufﬁcient numbers of workers.

Hypothesis 10: A signiﬁcant percent of migrant earnings are returned to the state
of Michigan through local purchases.

The analysis supported this hypothesis. As shown in Table 5.5, migrants reported
spending at least 60% of farm earnings in Michigan, purchasing such items as food,
clothing, and medicine. The focus group participants suggested that this ﬁgure is
probably low, because it may not take into account non-traditional spending venues like
yard sales where migrants reported that signiﬁcant spending takes place. Generally
speaking, the focus group participants reported that their families return to Texas with no

more than $2,000. Thus, most of their earnings remain in the state of Michigan.

6.3 RECOMMENDATIONS
Several ﬁndings highlight the direction of the recommendations that follow.
First, only a small percentage of growers reported ﬁnding it difﬁcult to hire sufﬁcient

farm labor at harvest time (25%), while even fewer reported being at risk of losing their

179

farms in the near future because of insufﬁcient labor. Second, 68% of the growers
reported believing that it will be increasingly difﬁcult to ﬁnd sufﬁcient farm labor in the
future. Third, most growers reported that they cannot signiﬁcantly raise migrant wages
because of low crop prices and the high costs associated with farming. Fourth, even if
wages could be increased, this may not solve the problem of attracting workers for
growers presently experiencing a labor shortage. This is because migrants reported fair,
respectful treatment by employers as one of their criteria when seeking employment and
follow word-of-mouth advice about avoiding employment on farms where their deﬁnition
of fair treatment is not met. Whether justiﬁed or not, a grower who has been labeled
unfair by migrants will carry this label well into the future.

Three recommendations are offered in response to these ﬁndings. The ﬁrst
recommendation is that the state of Michigan should fund additional research into
migrant farm labor issues in Michigan, which focuses on both the migrant population that
chooses to work in Michigan and the Michigan growers who rely on migrant labor. First,
a study should be conducted to expand on and verify/negate the ﬁndings of the migrant
pilot study presented in this dissertation. The purpose of this research would be to gather
statistically comparable baseline data against which future migrant data could be
contrasted. This study should incorporate questions similar to those asked in the present
study, but state questions more clearly. Such a study would help to reconcile the
contradictions between the information reported by growers and migrants, as reported in
this dissertation. Second, Michigan growers should be surveyed periodically, preferably
every two to three years, covering a broader spectrum of subsectors that hire migrants

than the present research analyzed. The ﬁndings presented in this dissertation would

180

serve as a benchmark against which future data could be compared and the periodic
collection of similar data would provide policymakers with an accurate assessment of
migrant farm labor market trends.

The second recommendation is that a new line of migrant-related research should
be initiated, which focuses more speciﬁcally on the ﬁnding that wages are the primary
driving force behind migrants’ decisions about where to work. Given that rrrigrant wages
are low, relative to most jobs within the United States economy, this study should explore
the potential for marketing crops harvested by Michigan migrant labor as fair wage cr0ps
(i.e., fair wage blueberries, fair wage apples, fair wage asparagus, etc.), similar to the fair
wage coffee niche industry that has boosted the wages of coffee harvesters employed by
participating growers in Central America in recent years.

The third recommendation proposes that the state of Michigan proceed with its
aborted plan to establish a task force geared towards improving communication between

Michigan growers, migrant farm workers, and consumers. These recommendations are

discussed below.

6.3.] Additional Research into Migrant Farm Labor Issues in Michigan

The following sections explore the three recommendations in greater detail. The

two parts of the ﬁrst recommendation are presented in separate sections.

181

6.3.1.1 Extension of the Migrant Pilot Survey to a Statistically Comparable Number

of Migrants

Periodically, the state of Michigan, in collaboration with other states, conducts
information sessions to attract migrant workers to northern U.S. agricultural regions. A
short written survey (similar to the pilot migrant survey) should be administered to
migrant workers attending these sessions. The purpose of this survey should be to collect
data from the migrants, which could be compared to the data collected from the growers.

Michigan’s Employment Services Agency projects that 600-1,000 surveys could
be completed and returned over the course of three days. Although this total includes
migrants who choose to work in states other than Michigan, the number of migrants who
traditionally seek Michigan employment would be sufﬁciently high to conduct the

analysis required to compare migrants’ responses to the results obtained from the growers

surveyed for this dissertation.

6.3.1.2 Periodic Collection of Migrant-Related Data from Michigan Growers

Given that the grower data collected for this dissertation represents baseline data
that can serve well into the future, it is recommended that similar data be collected every
two to three years in the state of Michigan. The Michigan Agricultural Statistics Service
(MASS) would be the ideal agency for conducting such a survey because MASS
regularly conducts agricultural surveys throughout Michigan. Nevertheless, given the

nature of MASS’s survey work (that consists exclusively of close-ended questions), a

182

shortened, modiﬁed survey would need to be developed“. This survey could be
conducted in conjunction with MASS’s annual grower household surveys, which covers
all subsectors rather than just the four subsectors studied in this dissertation.

These data would provide the information required to monitor migrant labor
market trends over time and across subsectors. As in this dissertation, the questions
would focus on recruitment and retention of migrant farm workers, numbers of migrant
hires per farm and subsector, whether or not growers are experiencing a labor shortage,
how severe the shortage is in a given year, the role of wages and perquisites in attracting
migrants to farms, the characteristics of farms experiencing a labor shortage, and
numbers of return workers by farm and subsector. Given the expectation of 68% of the
grower survey respondents that migrant labor will continue to decline into the future, this
information would be useful to growers, migrants, extension agents, researchers, and

policy-makers.

6.3.1.3 Research into the Possibility of Offering Fair Wage Crops in Michigan
Implementation of a study to explore the fair wage concept in the context of

migrant farm worker wages in the United States would be valuable. Given the recent

establishment of fair wage coffee imported from Central America, fair wage crops in

Michigan niche markets may have the capacity to improve the economic welfare of the

 

‘ All open-ended questions would have to be deleted or rephrased into close-ended
questions, as the survey implementation process and data entry mechanism followed
by MASS would prohibit their inclusion.

183

Michigan migrant workers that harvest those crops“. Migrants reported wages as an
important factor in their decision about where to work, thus lending credence to the need
to conduct a study that explores this issue in greater depth.

One can argue that the current marginal cost to the grower is not synchronous
with the marginal beneﬁt to society for having a crop provided for consumption (Pindyck
and Rubinfeld, 1989). By paying higher wages to migrants employed by participating
growers, and by using niche market marketing practices to advertise that higher wages
are paid for particular crop brands, higher consumer prices are legitimized and the
product becomes attractive to consumers, even at its higher price. In theory, the higher
consumer price would help to close the gap between the crop’s marginal cost and beneﬁt
to society.

The fair wage pilot study should explore both demand and supply-related issues.
First, both consumer and grower attitude surveys should be conducted to explore the
potential interest in fair wage crops. Second, the study should identify a group of
producers willing and able to risk entering into a fair wage agreement with other growers,
all of who would have to agree to pay higher wages based on the good-faith assumption
that consumers would respond positively to the reasoning behind higher niche market
prices. Third, the study should identify several stores, in key up-scale consumer areas,
that would also be willing to participate in the pilot study. Fourth, the study should
establish a partnership with a marketing ﬁrm whose role would be the development of a

successful advertising campaign on behalf of the fair wage commodity.

 

5 The fair trade coffee concept is based on a fair price for the cr0p, which results in a
higher income for the producers who own the crops. In Michigan, a key difference
would be to offer higher wages to migrants in response to the implementation of
higher, fairer prices.

184

6.3.2 Steps to Improve Communication Between Michigan Growers and Migrant

Farm Workers

Finally, it is recommended that the state of Michigan reinstate its aborted plans to
establish a task force whose purpose would be to improve communication between
growers, migrants, and consumers. To accomplish this, Michigan’s Employment
Services Agency should be encouraged to play a leading role in the guidance of this task
force. The task force should be comprised of state ofﬁcials (including representatives
from the Jobs Commission and the Michigan Department of Agriculture), Migrant
Counsel representatives, migrant workers, growers, extension agents from around the
state, and relevant scholars whose expertise would provide valuable insights to such a
commission.

Communication enhancements could include semi-annual newsletters, which
would be made available to both growers and migrants, as a means for learning more
about the economic and cultural problems faced by each other. Sponsoring seminars or
training programs, geared towards both growers and migrants that address cultural
awareness issues and ways for improving communication between growers and migrants,
would also be useful. To avoid interfering with important work times, the farmworker
seminars and training programs should be conducted in Florida and Texas during the off-
season by states that send recruitment teams to these two areas. Likewise, grower
seminars addressing cultural and communication issues should be conducted during the

winter months at subsectoral extension meetings.

185

The task force should also organize a series of annual seminars for growers and
migrants. The purpose of these seminars would be to encourage increased interaction
between the two groups in a non-farm setting. Social capital theory shows that increased
interaction can lead to increased trust and respect over time, a primary goal of the
proposed task force.

Last, the task force should consider developing an educational curriculum geared
towards informing young Michigan residents about the essential role of the migrant farm
worker in our economy. School age children would be the ideal target audience for this
campaign. Just as our communities have gained strength through tolerance by having
Michigan children learn more and earlier about the beneﬁts of diversity, our communities
would be strengthened by introducing mi grant-oriented curricula to early elementary
education programs. Such curricula should include a history of migrant farm workers in
Michigan, where the migrants come from, how migrant lifestyles are similar to and
different from those of permanent residents, the kind of work that migrants do, and how
migrant efforts enrich the lives of Michigan residents. A secondary beneﬁt to this
curriculum addition would be an easier acceptance of migrant children (by other children)
as they move into and out of Michigan classrooms. The lessons learned by introducing
this curriculum could last a lifetime for permanent and transitory students alike, in turn

encouraging the long-term return of migrant families to our state.

186

6.4 CONCLUSIONS AND RECOMMENDATIONS FOR FUTURE RESEARCH

The main limitation of this study was the small number of migrant workers
recruited to participate in the survey and focus groups. Although much useful
information was obtained from these respondents, it is not directly comparable to the
grower data.

A second limitation was the inability to interview growers and migrants from the
same farms. Interviewing growers and migrants who had worked together would have
generated valuable insights about the grower-mi grant relationship, as well as the
economic and social capital underpinnings of the farm environment. Unfortunately,
growers are not always amenable to having their workers distracted from their work in
the ﬁeld to answer questions, and migrants are frequently reluctant to be interviewed.

A third limitation was that the migrant and grower data were not collected in the
same year. Given that labor availability evolves from year-to-year, in the future these
data should be collected from both migrants and growers in the same year in order to
better reﬂect their shared experiences.

A fourth limitation is that insufﬁcient wage information was collected for three of
the four subsectors. Whereas wage data were gathered from blueberry growers for three
years, only one year of wage data were gathered from the three other subsectors. Thus, it
was not possible to determine if wages increased from year-to-year across any or all
subsectors, a ﬁnding that would have provided stronger evidence of a labor shortage.

A ﬁfth limitation concerns the difﬁculty of collecting reliable social capital data.
Initially, it seemed possible to gather these data from growers and migrants by asking

questions about their interactions with each other. However, since the sample size shifted

187

to include hundreds of growers but less than two-dozen migrant farm workers from
different farms, it was not possible to rigorously evaluate the role of social capital.
Furthermore, even if the size of the migrant and grower samples had been comparable, it
is apparent that social capital variables are difﬁcult to identify and measure.

Because of these limitations, future research should focus on collecting data from
growers and migrants who work together on the same farm. It would be especially
helpful if these data could be collected every second or third year from similar sample
populations in order to better document trends in migrant farm labor availability. The
task force described above could facilitate collection of these data.

Future research should also focus on developing improved social capital proxies
that could be incorporated in a regression model. Given that both economic and non-
economic criteria contribute to migrant decision-making about where to seek
employment, it would be helpful to better delineate the precise impact of each factor
under ceteris paribus conditions.

Finally, similar studies in different subsectors and regions around the country
should be carried out to generate information required to improve the grower-migrant

experience throughout the nation.

188

APPENDICES

189

APPENDIX A Ms. Pamela Riley Miklavcic

ORIGINAL SURVEY INSTRUMENT 202 Agriculttue Hall
(same basic format for all grower types) Michigan State University
East Lansing, MI 48823
j Fall 2000
Dear Apple Grower, ,

My name is Pam Miklavcic. I am conducting a study of recent migrant farm labor
experiences in the apple, blueberry, pickle, and asparagus subsectors of Michigan. The
purpose of this study is to analyze Michigan’s migrant farm labor situation, from the
perspective of the grower. This study is important to the Michigan plant industries for two
reasons. First, the state extensively relies on migrant workers to harvest its numerous labor-
intensive crops. An increasing shortage of workers, for example, may imply an inability to
harvest crops on time, incurring potentially heavy ﬁnancial and quality losses for
unharvested fruits and vegetables. Second, Congress intermittently considers legislative
changes that could signiﬁcantly inﬂuence the farm labor supply. I expect this study to better
inform this debate.

The information I collect from other growers and you will be used to complete my
Ph.D dissertation in the Department of Agricultural Econorrrics at Michigan State University.
This study is a collaboration between the Department of Agricultural Econonrics and the
Michigan Agricultural Experiment Station.

Your participation in this study is strictly VOLUNTARY. The survey will take
approximately 30 minutes to complete. You are free to NOT ANSWER any of the questions
in the survey. Nevertheless, I hope that you will agree to answer all my questions since your
full participation will best enable me to properly analyze the migrant farm labor situation in
Michigan.

All of the information that you provide will be kept CONFIDENTIAL. This means
that your answers to my questions will not be shown to anyone else. No one will know your
answers but me and your identity will be protected in any report based on the data. Your
privacy will be protected to the maximum extent allowable by law.

If you have any questions about this study, you can contact me, Pam Miklavcic, at
(517) 351-0735 or by e-mail at rileypam@msu.edu. You can also contact my adviser,
Professor Richard Bemsten, Department of Agricultural Economics, Michigan State
University, 211E Agriculture Hall, East Lansing, MI or phone Professor Bemsten at (517)
355-3449. If you have any questions regarding your rights and role as a human subject of
research, please contact Dr. David Wright, Michigan State University, 248 Administration
Building, East Lansing, M] or phone Dr. Wright at (517) 355-2180.

You indicate your voluntary agreement to participate by completing and returning
this questionnaire.

Sincerely,

Pamela Riley Miklavcic

190

A Survey of Apple Growers about Their
Migrant Farm Labor Experiences
in Michigan

Fall 2000

You indicate your voluntary agreement to participate by
completing and returning this questionnaire.

Please return your completed questionnaire
in the enclosed envelope to:

Pamela Riley Miklavcic
Phone: (517) 351 -0735

The Department of Agricultural Economics
202 Agriculture Hall
Michigan State University 0 East Lansing, MI 48824-1039

In collaboration with
The Michigan Agricultural Experiment Station

191

 

ID#

I. OPENING QUESTIONS

The purpose of this survey is to learn more about your migrant
farm labor needs and your experiences with migrant farm labor.
All questions pertain only to APPLES during the 2000 harvest
season unless stated otherwise. First, we have some screening
and Opening questions for you.

01

02

03

04

In 2000, did you grow apples? (Please check one.)

DYES IF YES, GO ON TO 02.

DNO IF NO, PLEASE RETURN THE SURVEY IN THE ENVELOPE PROVIDED.
THANK YOU FOR YOUR TIME.

In 2000, in what county was most of your apple
acreage?

 

Did you hire migrant labor to help with your 2000 apple harvest? (A
migrant laborer is defined as someone who works 150 days or less

for you and maintains a permanent residence In a distant coungg
state or county.) (Please check one.)

DYES IF YES, GO ON TO 04.
EINO IF NO, PLEASE SKIP TO QUESTION 58 ON PAGE 16.

About what percent of your 2000 apples were
harvested by migrant laborers? °/o

 

or your total 2000 migrant labor force:

05

06

About what percent worked previously on
your farm? %

 

About what percent have worked five or
more years for you? °/o

 

192

 

ID #
Of your total 2000 migrant labor force (continued):

Q7How did you go about recruiting migrant laborers to work on your farm?

(Check all that apply, and indicate about what percent of your 2000 aggle
labor force was found that way.)

 

 

 

 

 

CHECK ALL THAT APPLY: °/o APPLE LABOR (2000):
I HAD A VERBAL AGREEMENT WITH
PAST WORKERS %
I USED STATE MATCHING SERVICES °/o
I HIRED WORKERS THROUGH A
CREWLEADER %
I USED THE H2A PROGRAM °/o
I HIRED WORKERS WHO SOUGHT
WORK AT THE FARM "/0
OTHER (Please explain.) °/o

 

 

 

 

 

 

QBWhen did you begin your search for migrant
laborers for the 2000 aggle harvest? (month/year)

QQFrom which state or foreign country do the bulk of
your migrant workers come?

 

ll. YOUR 1998, 1999, AND 2000 APPLE HARVEST SEASONS

We now have some questions for you about each of your past three aggle
harvest seasons.

Q10How many migrant workers ger day (on

 

 

average) did you hire for your apple harvest? 2000 lday
1999 lday
1998 lday

 

193

 

ID#

01 1 For the aggle harvest, were you able to hire as many migrant workers as
you needed? (Please check each year with a “yes” or “no".)

2000 El YES or Cl NO -) IF YES FOR & YEARS, SKIP TO
024 AT THE TOP OF PAGE 7.
1999 El YES or D NO

1998 D YES or D NO —9 IF NO FOR ANY YEAR, GO ON TO 012.

IF NO FOR ANY YEAR:

012" you exgrienced a labor shortage during
harvest time, how many more migrant workers

 

 

(on average) did you need per day? 2000 lday
1999 lday
1998 lday

 

QlSDid this labor shortage result in any unharvested
apples? (Please check one.)

D YES —) IF YES, GO ON TO 014.
CI NO ——) IF NO, PLEASE SKIP TO O16.

 

 

 

 

 

 

IF YES:

Q14Roughly how many acres of aggles were

left unharvested due to this labor shortage? 2000 acres
1999 acres
1998 acres

015This represented an approximate 10$:

of how much money ggr acre? 2000 Slacre

1999 Slacre
1998 Slacre

 

194

 

|D#

Oi GDid this labor shortage result in any apples being harvested later than

CI
D

the ogtimal time?

 

 

 

YES —> IF YES, 60 ON TO 017.
NO —-> IF NO, PLEASE SKIP 'ro O19.
IF YES:
QI7Roughly how many acres were
harvested late? 2000 acres
1999 acres
1998 acres

01 8This represented a loss of about how

 

much money Er acre (for example,
due to reduced apple quality?) 2000 $

 

1999 t
1998 $

 

 

01 QDuring the last three yam, what were the three most imgortant reasons
why you have experienced a migrant labor shortage on your farm? (Please rank
by placing a 1, 2, or 3 next to the boxes representing your top three
reasons, 1 being most important.)

DUE] EICI CID

_R_ANK TOP THREE ONLY:

TOO FEW MIGRANTS ARE COMING TO MICHIGAN NOW.

THE MATCHING SERVICES IN MICHIGAN (FOR INTRODUCING

EMPLOYERS TO EMPLOYEES) ARE INSUFFICIENT.

I CANNOT PROVIDE ENOUGH HOUSING THAT MEETS FEDERAL STANDARDS.
TIGHTER RESTRICTIONS ARE NOW IN EFFECT DUE TO RECENT CHANGES IN
lMMlGRA TION AND NA T URALIZA TION SERVICE REGULATIONS.
HIGHER-PAYING FARMWORK CAN BE FOUND ELSEWHERE.

HIGHER-PAYING 11%-FARMWORK CAN BE FOUND ELSEWHERE.

OTHER. (Please explain.)

 

 

 

195

 

ID#

QZODuring the last three years, to REDUCE your labor needs, have you made
any specific changes in your farming operation? (Please check one box.)

D YES —-) IF YES, GO ON TO 021.
D NO -) IF NO, PLEASE SKIP TO 022.

F YES:

 

021 Please describe what you have done.

 

 

 

 

 

 

 

022 During the last three years, to ATTRACrT more migrant labor, have
you made any specific changes in your farming operation? (Please check one.)

D YES —-) IF YES, GO ON TO 023.
CI NO -) IF NO, PLEASE SKIP TO 024.

IF YES:

 

023 Please describe what you have done.

 

 

 

 

 

 

 

196

 

ID#

024How many non-migrant farmworkers gr day (on average)
worked in your apple orchards? (Please include
family members.) 2000

 

1 999

 

1 998

 

III. PRE-HARVEST SEASON

Although seasonal harvest labor is the focus of this research,

we have a few questions about your labor needs during the rest
of the growing season.

025For each of the past three years, have you had any trouble hiring year-
round labor (for example, tractor drivers?) (Please check “yes” or “no” for
each year.)

2000 [1 YES or D NO —+ Eggs FOR guy YEAR, GO ON TO 026.
1999 I: YES or El NO —) Mg FOR _A_I.L_ YEARS, SKIP TO 027.
1998 0 YES or Cl NO

ILY_E_; FOR ANY Leg:

 

026Explain your trouble hiring year-round labor and why it occurred. (Please
write in the space provided.)

 

 

 

 

197

 

ID#

027Have you had trouble hiring labor during other gak aggle grlods (for
example, during non-harvest activities like pruning or thinning?) (Please mark
“yes” or anon.) .

2000 El YES or Cl NO —) IF YES FOR 531 YEAR, GO ON TO 023.

1999 El YES or Cl NC —> IF NO FOR 5g. YEARS, SKIP TO 029.
1998 El YES or CI NO

IF YES FOR ANY YEAR:

QZBExplain your trouble hiring this “other (i.e., non-harvest) peak period
labor” and why it occurred. (Please write in the space provided.)

 

 

 

V. MIGRANT PERKS

The following questions will be used to determine the total
compensation for migrant workers in Michigan. These include
actual wages ﬁg additional benefits that employers provide

such as housing, rent, and utilities. (individual regorts will
remain confidential.)

In 2000, during the aggle harvest season:

029What was the most common wage rate you paid to migrant workers?

$ per

 

 

(either by hour,
basket, piece?)

Q3ODid you provide any migrant housing on your farm? (Check one.)

D YES —) IF YES, GO ON TO 031.
D NO —) IF NO, PLEASE SKIP TO 042.

198

 

ID If
IF YES:

 

Q31 How many single migrant workers could
you house?

 

QSZHow many migrant families (including
extended families) could you house?

 

O33How many workers (on average) were in the
typical family that you employed on your farm? [family

 

0340id any of these migrant workers pay rent
while living on your farm?

D YES ——) IF YES, GO ON TO 035.
CI NO —) IF NO, PLEASE SKIP TO 038.

IF YES:

 

035Under what condition did migrant workers pay rent?
(Check the one most important reason that applies to your farm.)

CHECK ONE:

[3 IN ALL CASES

U ONLY WHEN TRAVELING WITH A LARGE NUMBER OF
NON-WORKING FAMILY MEMBERS

El ONLY WHILE WORKING ON ANOTHER FARM

El OTHER (Please explain.)

 

 

 

 

 

O36How much rent did single migrant workers pay?

3 per
(either by day, week, month?)

199

 

ID #
In 2000, during the apple harvest season (continued):

O37How much rent did migrant families pay?

3 per
(either by day, week, month?)

QSBDid any of these migrant workers pay utilities while
working on your farm?

CI YES —9 IF YES, GO ON TO 039.
El NO —-) IF NO, PLEASE SKIP TO 042.

IF YES:

 

039Under what condition did migrant workers pay utilities?
(Check the one most important reason that applies to your farm.)

CHECK ONE:

IN ALL CASES .
ONLY WHEN TRAVELING WITH A LARGE NUMBER OF
NON-WORKING FAMILY MEMBERS

ONLY WHILE WORKING ON ANOTHER FARM

OTHER (Please explain.)

EIEI EIL'I

 

 

 

 

 

O40How much did Single migrant workers pay for utilities?

$ per
(either by day, week, month?)

041 How much did migrant families pay for utilities?

$ per
(either by day, week, month?)

200

 

ID It
In 2000, during the apple harvest season (continued):
Q42Did any of your migrant workers live off-farm?

CI YES —) IF YES, GO ON TO 043.
D NO —) IF NQ, PLEASE SKIP TO 046.

IF YES:

 

Q43How many migrant workers lived off-farm?

 

O44Where did they live? (Please check the most frequently-encountered
housing situation.)

CHECK ONE:

IN MIGRANT HOUSING ON A NEIGHBORING FARM
IN OUARTERS THEY SECURED THEMSELVES
OTHER (Please explain.)

L'IEIEI

 

 

 

 

 

O45How many miles did non-housed migrants travel
daily to work on your farm (on average, one way?)
miles

Q460id you provide any other “perks” - besides housing, rent,
and/or utilities - to migrant workers on your farm?

El YES —) IF YES, GO ON TO 047.
CI NO —> IF NO, PLEASE SKIP TO 048.

20]

 

ID #
In 2000, during the apple harvest season (continued):
IF YES:

Q47What additional “perks” did you provide? For example, did you provide day

care for kids, transportation for Shopping or health needs, end-of-harvest fiestas,
telephone access, laundry facilities, end-of season bonus etc? (Please list and

estimate value per worker per day.)

PERK VALUE/WORKER PER HARVEST SEASON
(ROUGH ESTIMATE)

$lseason

 

$/season

 

$lseason

 

$lseason

 

 

$lseason

 

$lseason

202

 

ID #
In 2000, during the apple harvest season (continued):

O48What services were available to your migrant workers, roughly how far (w
my, In miles) were these services from where the majority of your workers
lived, and which services were available on-farm? (Please place a check next
to the services provided and include the miles for off-farm services.)

 

 

 

 

 

SERVICES OFF-FARM ON-FARM

RELIGIOUS SERVICES [3 miles D
SCHOOLS FOR KIDS D miles D
MEDICAL CARE [:1 miles D
A GROCERY STORE [3 miles D
A CLOTHING/ALL-PURPOSE

STORE [3 miles D
MIGRANT SERVICES FOR

SEEKING JOBS [3 miles D

 

OTHER(S) (Please explain
on following lines.) [I] miles [3

 

 

 

 

 

 

203

 

ID II
VI. PAYROLL QUESTIONS

Now we have some migrant payroll questions for you, as they
relate to the operations of your farm.

For each of the past three years:
O49What were your earnings from apple sales? (Please check one.)

$0 - $9,999

$10,000 - $19,999
$20,000 - $29,999
$30,000 - $39,999
$40,000 - $49,999
$50,000 - $74,999
$75,000 - $99,999
$100,000 - $149,999
$150,000 +

CIDCIDDCIDDEJ

Q50Your migrant worker payroll was about what greent of your total farm
ograting exgnses? '

 

 

2000 °/o
1 999 °/o
1 998 "/o

 

QSIAbout what percent of total farm earnings were from apple sales?

 

 

2000 %
1 999 %
1 998 %

 

052If migrant labor was not available, how much would you have to pay a;
worker gr day (roughly)?

$ worker/day

204

 

ID #
VII. THE FUTURE

Now, a few questions about the future.

053m 2001, do you expect to need more, less, or the same number of
migrant workers? (Please check one.)

CI MORE
CI LESS
D THE SAME

054In five years, do you expect to need more, less, or the same amount of
migrant labor? (Please check one.)

[3 MORE
D LESS
III THE SAME

055In five years, what factors will increase/decrease your future need for farm
labor? (Please explain on the lines below.)

Increase:

 

 

 

 

 

Decrease:

 

 

 

 

 

205

 

ID#

056In five years, do you expect the future avallabllig of migrant workers to
be higher, lower, or the same? (Please check one.)

D HIGHER
CI LOWER
D THE SAME

057What could be done to increase the future supply of migrant labor (ex.,by

you, state/federal government, local agencies?) (Please respond on the lines
below.)

 

 

 

 

 

 

 

 

 

 

 

 

VIII.EXPERIENCE

We would now like to ask some questions about your farming
and non-farming experiences.

Since high school, how many years have you:

 

058 Worked on a farm? years

059 Grown apples on a farm?

 

 

years
060 Been responsible for running a farm (for

example, as a farm operator?) years
061 Hired migrant labor? gears

 

206

 

ID#

 

 

 

 

In 2000:

062 How many acres was your farm acres

063 How many acres did you plant to acres
annual crops?

064 How many acres of apples did you acres
grow?

In a ypical year:

065 How many days long is your apple harvest?

065 How many days long is your apple days
harvest?

 

066 Do you also work off-farm? (Please check one.)

[3 YES —-) IF YES, GO ON TO 067.
El NO -) IF NO, PLEASE SKIP TO 068.

IF YES:

 

0670n average, how many hours per week
do you work off-farm?
hours/week

 

068About how many extension meetings do you
attend each year?

 

06900 you Speak or understand Spanish? (Please check one.)

[I YES —> IF YES, GO ON TO 070.

CI NO -) IF NO, PLEASE READ THE TEXT FOLLOWING 070.

207

 

ID#

0700n a scale of one to fivg, how fluent are you in Spanish?
1 2 3 4 5

BASIC FLUENT
VOCABULARY

IF YOU HIRED MIGRANT LABOR IN 2000, YOU HAVE
COMPLETED THE SURVEY. THANK YOU FOR YOUR TIME.

IF YOU DID NOT HIRE MIGRANTS IN 2000, PLEASE GO ON TO
071.

208

 

ID If
IF YOU DID NOT HIRE MIGRANT LABOR IN 2000:

071 Have you ever hired migrants for your apple harvest? (Please check one.)

D YES -) IF YES, GO ON TO 072.
D NO —-) IF NO, SKIP TO 077.

IF YES:

 

072For how many years did you hire migrant labor to
help with your apple harvest?

 

073|n what year did you stop using migrant labor for your
apple harvest?

 

074Why did you stop using migrant labor? (Please explain on the lines below
or on the back.)

 

 

 

075Are your net earnings from apples higher, lower, or the same since you
stopped hiring migrant labor?

CI HIGHER
D LOWER
CI THE SAME

076Please explain why your net earnings from apples have changed - or stayed
the same - Since you stopped hiring migrant labor to help with your apple
harvest. (Explain on the lines below - or on the back.)

 

 

 

0770n average, during the 2000 apple harvest, how manv non-
migrant farm-workers per day worked in your apple orchards?

 

078|n 2000, how many year-round laborers did you employ?

 

YOU HAVE COMPLETED THE SURVEY. PLEASE RETURN IT IN
THE ENCLOSED ENVELOPE. THANK YOU FOR YOUR TIME.

209

Your comments will be appreciated, either here or in a separate envelope.

 

 

 

Thank you for your help.

Please return your completed questionnaire in the enclosed envelope to:
THE DEPARTMENT OF AGRICULTURAL ECONOMICS
202 Agriculture Hall
Michigan State University
East Lansing, MI 48824-1039

210

 

 

APPENDIX B - SUPPLEMENTAL SURVEY ID#
FOR BLUEBERRY GROWERS

A Short Survey of Michigan Blueberry Growers
Who Did Not Hire Migrant Farm Labor in 2000

****************************

You indicate your voluntary agreement to participate by
completing and returning this questionnaire.

Please return your completed questionnaire
in the enclosed envelope to:

Pamela Riley Miklavcic
Phone: (517) 351-0735

The Department of Agricultural Economics
Lindon Robison . 3038 Agriculture Hall
Michigan State University 0 East Lansing, MI 48824-1039

In collaboration with
The Michigan Agricultural Experiment Station

i***************************
The purpose of this second survey is to learn about your past

experiences hiring migrant farm labor for your blueberry
harvest.

01 Have you ever hired migrants for your blueberry harvest? (Please check
one.)

D YES -) IF YES, GO ON TO 02.
D NO —> IF NO, SKIP TO 07.

IFYES:

 

02 For how many years did you hire migrant labor to help
with your blueberry harvest?

 

03 In what year did you stop using migrant labor for your

 

blueberry harvest?

211

 

ID#

04Why did you stop using migrant labor? (Please
explain on the lines below - or on the back.)

 

 

 

 

05Are your net earnings from blueberries higher, lower, or the same since
you stopped hiring migrant labor?

D HIGHER
EI LOWER
CI THE SAME

06 Please explain why your net earnings from blueberries have changed - or
stayed the same - since you stopped hiring migrant labor to help with your
blueberry harvest. (Explain on the lines below - or on the back.)

 

 

 

07 On average, during the 2000 blueberry harvest, how many

non-migrant farmworkers per day worked in your blueberry
fields?

 

08 In a typical year, your blueberry harvest lasts how many days?

 

09 In 2000, how many year-round laborers did you employ?

 

We would now like to ask some questions about your farming
and non-farming experiences.

Since high school, how many maps have you:

 

 

 

010 Worked on a farm? years
011 Grown blueberries on a farm? years
012 Been responsible for running a farm (i.e., as a farm

operator)? gears
013 Hired migrant labor? years

 

212

In 2000:

014 How many acres was your farm?
015 How many acres did you plant to annual crops?

016 How many acres of blueberries did you grow?

In a typical year:

017 Do you also work off-farm? (Please check one.)
D YES 4 IF YES, GO ON TO 018.
E] NO —> IF NO, PLEASE SKIP TO 019.

IF YES:

018 On average, how many hours per week

019 About how many extension meetings do you
attend each year?

020Do you Speak or understand Spanish? (Please check one.)

D YES —-9 IF YES, GO ON

a NO—) IF NO, YOU HAVE COMPLETED THE
THANK YOU FOR YOUR TIME.
IF YES:

0210n a scale of one to five, how fluent are you in Spanish?

1 2 3 4 5
BASIC FLUENT
VOCABULARY

 

ID#

acres
acres

acres

hours/week

 

YOU HAVE COMPLETED THE SURVEY. PLEASE RETURN IT
IN THE ENCLOSED ENVELOPE. THANK YOU FOR YOUR

TIME.

213

APPENDIX C Ms. Pamela Riley Miklavcic
MIGRANT FARM WORKER SURVEY 202 Agriculture Hall
Michigan State University

East Lansing, MI 48823

September 2002
Estimade Trabajader Agricola Migrante de Michigan,

Mi nombre es Pam Miklavcic. Estey conduciendo un estudio de las experiencias
migraterias recientes del trabajo agricela en la manzana, el esparrage, mores azules
(blueberry), y pepinos prickling en les subsecteres de Michigan. El prepesite de este estudio
es analizar la situacien migrateria del trabajo agricela de Michigan, desde la perspectiva de
ambos trabajaderes migrateries y rancheres/cultivaderes agricelas. Un estudio extensive fue
conducido de les cultivaderes/rancheres en el inviemo del 2000. Esta encuesta de
trabajaderes migrantes servira come complemento a la encuesta de les
cultivaderes/rancheres.

Mi meta es mejorar el ambiente Iaberal en les campos de Michigan haciende le
siguiente: l) entender mejor les factores que inﬂuyen en la decisien de ambos les migrantes
que buscan trabajo en campos particulates y 103 rancheres que siguen ciertas practicas
particulares para empleo y retencien, 2) lecalizacien de areas prebleméticas de cemunicacien,
y 3) diseminacien de esta infennacien en circules donde puede ser utilizada para mejorar
relaciones entre el empleado y el patron.

La infermacién que ceIeccienaré cen esta encuesta seré utilizada para cempletar mi tesis
para mi Ph.D 0 Doctorado en el Departamento de Economia Agricola en Michigan State
University. Este estudio es en celaberacién con la Estacién de Experimentos AgriceIas de
Michigan.

Su participacien en este estudio es estrictamente VOLUNTARIO. Esta encuesta
duraré apreximadamente treinta minutes. Si no desea participar, e si preﬁere no responder a
cualquiera de mis preguntas, no habran penalidades ni pérdida de beneficies. Es libre de NO
CONTESTAR cualquiera de las preguntas en la encuesta. Aunque este sea asi, espero que
este de acuerde en responder todas las preguntas. Su participacién cempleta me permitira
analizar apropiadamente Ia situacien rnigrateria del trabajo agricela en Michigan lo mejor
posible.

Teda la infermacien que usted provee es CONFIDENCIAL. Este signiﬁca que nadie
sabre sus respuestas mas que yo, y su identidad seré protegida en cualquier reperte basado en
la infermacién. Su privacidad sera protegida a] grade maxime de la ley.

Si tiene algunas preguntas sebre este estudio, usted puede comunicarse conmigo, Pam
Miklavcic, a] teléfono 517-351-0735 0 per correo electrénice a ripleypam@msu.edu.
También puede comunicarse con mi consejero, el Prefeser Richard Bersten, del
Departamento de Economia Agricola en Michigan State University, 211 E. Agricultural Hall,
East Lansing, MI 0 puede llamarle a1 517-355-3449. Si tiene alguna pregunta relacionada
con sus dereches y con su papel come un sujeto de investigacién humane, favor de
comunicarse con el Dr. Ashir Kumar, Michgian State University, 248 Administration
Building, East Lansing, MI 0 puede llamarle 31 517-355-2180.

Usted indica su acuerde veluntarie para participar a] ﬁrmar abaje y al centestar las
preguntas siguientes.

Sinceramente,
Pamela Riley Miklavcic

 

Firma del Trabajader Agricola Migrante

214

Encuesta de Trabajader Migrante Sebre las
ExperienciaS de Trabaje Agricola en Michigan

Verane del 2002

Qa al trabaiader agricela migrante antes de empezar la entrevista:

Usted indica su acuerde voluntarie de participar respendiendo
verbalmente a las siguientes preguntas. La entrevista puede ser
terminada a cualquier hora, y puede rehusar centestar cualquier
pregunta con la cual no se sienta cemedo. El centenido de esta

encuesta sera guardada cempletamente anenimo.

Esta encuesta esta cenducida per:

Pamela Riley Miklavcic, Cadidata Doctoral
Teléfene: (517) 351-0735
Cerree electronice: rileypam @ msu.edu
1207 Chartwell CWS, East Lansing, MI 48823

El Departamento de Economia Agricola
The Department of Agricultural Economics
202 Agriculture Hall

Michigan State University . East Lansing, MI 48824-1039

En celaberacien con
Estacien de Experimentos Agricolas de Michigan.

The Michigan Agricultural Experiment Station

215

1) (,Cuantes aﬁes ha trabajade usted come trabajader agricela migrante en Michigan?

 

2) [En un ane, cuantes meses pasa usted en Michigan?

3) (,Cuande esta en Michigan, trabaja usted cen cualesquiera de las cesechas siguientes
manzanas, esparrage, mores azules e blueberry, pepinos prickling?

4) LDende esta su residencia permanente?

 

5) LCen cuantes adultes (incluyéndese usted misme) viaja cen usted?
6) (,Cen cuantes nifies e niiias viaja usted?
7) LCual es el patron tipice de trabajo durante el ane? (centinué al derse si es necesarie)

ESTADO COSECHA FECHA DE COMIENZO FECHA QUE FINALIZO

 

 

 

 

 

 

 

 

 

 

8) (“En que estade preﬁere trabajar usted?
LPer que?

 

 

 

 

 

9) LCen que cesecha preﬁere trabajar usted?
LPer que?

 

 

 

 

 

10) LBS fécil e dificil encentrar trabajo en Michigan? FACIL DIF'ICIL

216

ll) LNembre tres aspectes positives relacionades con el trabajo en Michigan?

 

 

l.
2.
3

 

12) gNembre tres aspectes negatives relacionades sobre el trabajo en Michigan?

 

 

l.
2.
3

 

13) LCuales son las tres cesas mas impertantes que busca usted cuande busca trabajo
agricela?

 

1.
2.

 

3.

 

14) LCeme encuentra usted lugares en donde trabajar?

 

 

 

 

 

15) LDescriba un “buen” ranche e campe en Michigan en el cual usted ha trabajade?

 

 

 

 

 

16) LDescriba un campe e ranche “male” en Michigan en el cual usted ha trabajade?

 

 

 

 

 

217

17) LQue salaries recibe usted de las cesechas mencienadas en la pregunta #2 arriba?

 

18)1,Page usted per el alquiler de su ultimo lugar de empleo en Michigan per la cesecha
antedicha?

81 NO

19) LQue gratiﬁcacienes recibie en su ultimo lugar de empleo per la cesecha mencienada
anteriermente (alquiler, utilidades, dispesicien de guarderia, cemidas, asistencia medica,
transporte)? (centinué al derse si es necesarie)

 

 

 

 

GRATIFICACION
1.
2.
3.
20) Sus ingreses individuales durante un ane tipice sen: $
21) Su ingrese de una temperada tipica en Michigan es: $

 

22) Les ingreses de su familia durante un aﬁe tipice en Michigan son:

55

 

23) Les ingreses de la familia fueren mas altos e mas bajes que el aﬁe pasade? S H

L

24) {Les mismes ingreses se mantuvieren igual, fueren mas altos, e mas bajes que hace des
aﬁes?

I A B

25) LApreximadamente que percentaje de les ingreses anuales de su familia fueren gastades
durante su estancia en Michigan?
%

 

26) LNembre las cince cesas mas signiﬁcativas en las cuales usted gasta su dinere mientras
esta en Michigan (alimentes, repa, alquiler, guarderia, etres servicies, etc)?

 

 

 

 

.U'PPJNI"

 

218

27) {En sus recen'ides e viajes, usted tiene la impresien de que vienen trabajaderes a buscar
trabajo a Michigan ceme en el pasade? SI NO
LPer que si e per que no?

 

 

 

 

 

28) LPlanea regresar a Michigan eI aﬁe prexime? SI NO
29) LEspera regresar a Michigan dentre de cince aﬁes? SI NO

30) LHay alge que usted quisiera decirme sebre ser un trabajader agricela migrante que no le
haya preguntade pere que debe saber para mi encuesta? (continue al derse si es necesarie)

 

 

 

 

 

219

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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BIBLIOGRAPHY

221

Alreck, Pamela L. and Settle, Robert B. 1985. The Survey Research Handbook.
Hemeweed, IL: Irwin, Inc.

Amin, A. 1996. Beyond associative democracy. New Political Economy, I (3), 309-333.

Andersen, Curt. “Higher wages, worker availability key to migrant worker
compromise”. Business News, The Associated Press. July 22, 1998.

Apente, Robert. 1995. NAFTA and Mexican Mi gratien to Michigan and the US. July
14. Julian Samera Research Institute, Working Paper No. 25, Michigan State
University, East Lansing, MI. (17 pp)

Baker, Susan Gonzales and Espitia, Marilyn. 2000. “From Latin American Immigrant to
‘Hispanic’ Citizen: The Role of Social Capital in Seeking US. Citizenship.”
Social Science Quarterly, Volume 81, Number 4, December (pp.1053-1063).

Baker, Wayne. 2001. Social Capital, Executive Excellence; Prove; Aug, p. 9.

Balderrama, Francisco E. 1995. Decade of Betrayal. Albuquerque, NM: University of
New Mexico.

Baron, Robert A. and Markman, Gideon D. 2000. Beyond social capital: Hew social
skills can enhance entrepreneurs' success, The Academy of Management
Executive; Ada; Feb (pp. 106-1 16).

Bemsten, Richard H. 1998. Changes in Michigan Agriculture: 1950 to 1987. Ag
Experiment Station Special Reports - SPOOOOOI, July 28 Michigan State
University Extension, Michigan State University, East Lansing, MI.

Bourdieu, Pierre. 1986. "The Forms of Capital”. In Handbook of Theory and Research

for the Sociology of Education (Richardson, John 6., Ed.) New York: Greenwood
(pp. 241-258).

Bustamante, Jorge A. 1992. Interdependence, undocumented migration, and national
security. In U. S. -Mexico Relations — Labor Market Interdependence
(Bustamante, J erge A., Clark W. Reynolds, and Raul A. Hinojosa Ojeda, Eds.)
Stanford, CA: Stanford University Press (pp. 21-41).

Bustamante, Jorge A., Clark W. Reynolds, and Raul A. Hinojosa Ojeda (Eds). 1992.

U. S. -Mexico Relations - Labor Market Interdependence. Stanford, CA: Stanford
University Press.

222

Cable News Network. 1999. Web site address:
httpzllwww.cnn.cemlUS/9608/20lminimum.wage.sign/graph_minimum.wage.gif.

Denner, Jill, Douglas Kirby, Karin Ceyle and Claire Brindis. 2001. “The Protective
Role of Social Capital and Cultural Norms in Latino Communities: A Study of
Adolescent Births”, Hispanic Journal of Behavioural Sciences, Vol. 23, No. 1,
February, pp. 3-21.

DSS Research. 2001. Arlington,TX. Web site address:
httpzllwww.dssresearch.cem/library/general/mailresp.asp

Dunn, John M. 1999. The gloomy green giant. Florida Trend; St. Petersburg; Volume
41, Issue 9, Jan 01, page 8.

Federal Register. 2003. 2003 HHS Poverty Guidelines. Vol. 68, Ne. 26, February 7, pp.
6456-6458.

Ferris, John N. (Jake). 2000. An Analysis of the Importance of Agriculture and the Feed
Sector in the Michigan Economy. Staff Paper 00-11, May, Department of
Agricultural Economics, Michigan State University, East Lansing, MI (27 pp.).

Field, Simon. 2001. Does team spirit make economic sense? Organisation for Economic
Cooperation and Development. The OECD Observer; Paris; Summer, pp. 55-56.

Glaeser, Edward L., David I. Laibsen, Jose A. Scheinkman, and Christine L. Seutter.

2000. “Measuring Trust.” The Quarterly Journal of Economics, August, pp. 811-
846.

Geldberger, Arthur S. 1991. A Course in Econometrics. (Cambridge, Massachusetts:
Harvard University Press.)

Granovetter, Mark. 1973. “The Strength of Weak Ties.” American Journal of Sociology
78: 1360-80.

Granovetter, Mark. 1982. “The Strength of Weak Ties: A Network Theory Revisited.”
pp.105-30 in Social Structure and Network Analysis, edited by Peter V. Marsden
and Nan Lin. Beverly Hills, CA: Sage.

Guerin-Genzales, Camille. 1994. Mexican Workers and American Dreams (New
Brunswick, NJ: Rutgers University Press).

Hansen, Eric. 1992. Status and Potential of Michigan Agriculture - Small Fruit Crops,

Report Number 58, September, Michigan State University Agricultural
Experiment Station, Michigan State University, East Lansing.

223

Hemer, Robert C. and J ehn F. Kelly. 1992. Status and Potential of Michigan
Agriculture - Vegetable Crops. Ag Experiment Station Special Reports -—
SR599201, Michigan State University, East Lansing, MI, 21 pp.

Hill, EB. 1939. Types efFarming in Michigan

Howell, Leon. 2001. Beycetting pickles, The Christian Century; Chicago; Jan 3-Jan 10,
(pp. 6-8)-

Kelly, Erin. “Bill would make it easier to bring in migrant farm workers”, Gannett News
Service, Gannett Company, Inc. July 21, 1998.

The Labor Research Association. 2003. New York, NY. Web site address:
http://www.laberresearch.erg.

Lightsey, Ed. 1999. “Hispanic, Creole workers flocking to Georgia's farms”,
Georgia Trend; Atlanta; Sep 01, p. 28.

Lin, Nan. 2001. "Building a Network Theory of Social Capital". In Social Capital:
Theory and Research (Nan Lin, Karen Cook and Ronald S. Burt, Eds.) New
York: Aldine De Gruyter (pp. 3—29).

Lyon, Fergus. 2000. “Trust, Networks and Norms: The Creation of Social Capital in

Agricultural Economics in Ghana.” World Development, Vol. 28, No. 4, pp. 663-
681.

Maddala, G. S. 1990. Limited-dependent and qualitative variables in econometrics.
(Cambridge, England: Cambridge University Press.)

Massey, Douglas J. 1986. “The Social Organization of Mexican Mi gratien to the United

States.” American Academy of Political and Social Science Annals. Volume 487,
September, pp. 102-113.

Massey, Douglas S., and Kristin E. Espinosa. 1997. “What’s Driving Mexico-US.

Migration? A Theoretical, Empirical, and Policy Analysis.” American Journal of
Sociology 102:939-99.

McCracken, Jennifer A., Jules N. Pretty, and Gordon R. Conway. 1988. An Introduction
to Rapid Rural Appraisal for Agricultural Development. London, England:

International Institute for Environment and Development.

Michigan Agricultural Statistics Service. 2000. “Michigan Agricultural Statistics 1999-
2000”. Web site address : http://www.nass.usda.gev/mi.

Michigan Department of Agriculture (Michigan Agricultural Statistics Service). 1999.
Michigan Rotational Survey - Vegetable Inventory 1997-98.

224

Michigan Department of Agriculture (Michigan Agricultural Statistics Service). 1998.
Michigan Rotational Survey - Fruit Inventory 1997-98.

Michigan Department of Agriculture. “Migrant labor housing inspection program”,

Michigan Department of Agriculture Annual Report I 997. Michigan Agricultural
Statistics Service, 1997.

Miklavcic, Pamela R. 1995. Determinants of F arm Household Participation in
Rwanda ’s Banana Wine Subsector. MS Thesis, Michigan State University.

Nerusis, Marija J. 1991. The spss Guide to Data Analysis, for SPSSIPC+, 2ml Edition.

Phillips, Julie A. and Douglas S. Massey. 2000. “Engines of Immigration: Stocks of
Human and Social Capital in Mexico.” Social Science Quarterly, Volume 81,
Number 1, March (pp. 33-48).

Pindyck, Robert S. and Daniel L. Rubinfeld. 1989. Microeconomics. (New York:
Macmillan Publishing Company).

Reynolds, Clark A. 1992. Will a free trade agreement lead to wage convergence?
Implications for Mexico and the United States. In U.S.-Mexico Relations - Labor
Market Interdependence (Bustamante, Jorge A., Clark W. Reynolds, and Raul A.
Hinojosa Ojeda, Eds.) Stanford, CA: Stanford University Press (pp. 477-486).

Rebisen, Linden J. A White Paper on the Relevance of Social Capital for the College of
Agriculture and Natural Resources (CANR). 1999. Staff Paper No. 99-59,
December, Department of Agricultural Economics, Michigan State University,
East Lansing, MI. (30 pp.)

Robison, L., and A. Allan Schmid (1991). Interpersonal relationships and preferences:
evidence and implications. In R. Frantz, et al., (Eds), Handbook of Behavioral
Economics, Vol. 2B. Behavioral Decision Making (pp. 347-358). Greenwich,
CT: JAI Press.

Robison, Linden J. and M. E. Siles. Social Capital and Household Income
Distributions in the United States: I 980, 1990. Department of Agricultural
Economics Report N e. 595 and the Julian Samera Research Institute Research
Report No. 18, Michigan State University, East Lansing, Michigan, October 1997.

Robison, Linden J. and Marcelo E. Siles. December 2000. Social Capital: Sympathy,

Secie-Emetienal Goods, and Institutions. Staff Paper No. 00-45, Michigan State
University, East Lansing, MI.

225

Robison, Linden J., Marcelo E. Siles, and A. Allan Schmid. 2001. Social Capital and
Poverty Reduction: Toward a Mature Paradigm. Prepared for the International
Invitational Conference, “Social Capital and Poverty Reduction in Latin America

and the Caribbean: Toward a New Paradigm,” held September 24-26, 2001, in
Santiago de Chile.

Roccisano, Rose. “Local growers having difﬁculty ﬁnding enough workers to harvest
their crops”, Fremont News Messenger. July 1998.

Rechin, Refugio I. 1989. The Changing Nature of American Agriculture and Its Impact

on Hispanic Farm Labor: Topics for Research and Analysis, Working Paper No.
3, October, University of California, Davis.

Salant, Priscilla and Dillman, Den A. 1994. How to Conduct Your Own Survey. New
York: John Wiley and Sons, Inc.

Schaetzl, Randall J. 2002. Geography of Michigan and the Great Lakes (GEO333, an
undergraduate course offered at Michigan State University). Web site address:
http:l/www.gee.msu.edu/geo333/index.html.

Schmid, A. Allan. 2000. “Affinity as social capital: its role in development”. The
Journal of Socio-Economics 29, pp. 159-171.

Schmucker, Jane. “Migrant shortage threatens harvest for local farmers”, Toledo Blade.
July 12, 1998.

Schweikhardt, David B. 2000. Reconsidering the Farm Problem Under an
Industrializing Agricultural Sector. Staff Paper #00-15. June. Department of
Agricultural Economics, Michigan State University, East Lansing, MI (26 pp.)

Strauss, John. 1984. “Marketed Surpluses of Agricultural Households in Sierra Leone”,
American Journal of Agricultural Economics, Volume 66, no. 3, pp. 321-331.

United States Department of Labor. 2003. Minimum wage statistics offered by

Employment Standards, Administration, Wage, and Hour Division. Web site
address: http://www.dol.gev/esa.

Valdes, D. N. 1992. Divergent Roots, Common Destinies? Latino Work and Settlement
in Michigan, University of Minnesota, Occasional Paper No. 4, May (Obtained
from The Julian Samera Research Institute, MSU).

Vargas, Zaragosa. 1997. Citizens, Immigrants, and Foreign Wage Workers: The
Chicana/o Labor Refrain in US. Labor Historiography, J SR1 Occasional Paper

Ne. 19, June, Julian Samera Research Institute, Michigan State University, East
Lansing, NH.

226

Verhovek, Sam Howe. 2002. Immigrant Laborers Feel Stranded in Paciﬁc Northwest as
Day Jobs Dry Up. New York Times, January 27.

227

   

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