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This is to certify that the

dissertation entitled

Impacts of Urbanization on Agricultural
Development in the Northern
Coastal Region of West

Java, Indonesia
presented by

Joyo Winoto

has been accepted towards fulfillment
of the requirements for

Ph . D . degree in Resource Development

 

 

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IMPACTS OF URBANIZATION ON AGRICULTURAL DEVELOPMENT
IN THE NORTHERN COASTAL REGION OF WEST JAVA,
INDONESIA

By

Joyo Winoto

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Resource Development

1995

iii-“i

.‘F- .o-

ABSTRACT

IMPACTS OF URBANIZATION ON AGRICULTURAL DEVELOPMENT IN THE
NORTHERN COASTAL REGION OF WEST JAVA, INDONESIA

By

Joyo Winoto

Current regional development strategy in the North Coastal Region of West Java
(NCR) has favored urban development. Urbanization, in pan induced by the strategy, is
expected to put additional pressure on the sustainability of agriculture in the region—the
”bread basket" of Indonesia. More importantly, urbanization process is also expected to
negatively affect 76 percent (1992) of the rural population engaged in agriculture.

This thesis analyzes the regional urbanization process and its causal factors, its
relationship with regional development, and its impacts on agricultural development to
suggest alternative policy interventions needed to sustain a viable (regional) agricultural
sector. The study employed three sets of data: primary data collected at the village level
for the period of 1982-1992, secondary data derived from the Census of 1980 and 1990,
and secondary data provided by the Project of Land Conversion in Java.

Urbanization in the region was caused mostly by economic stress in nual agricultural
areas rather than increased economic opportunities in the urban areas. The rate of regional
urbanization was higher in urban than in rural areas, indicating a cumulative causation

process or self-reinforcing process of urbanization.

J oyo Winoto

Urbanization has increased agricultural land parcelization, landless farming
households, absentee agricultural land ownership, and agricultural land conversion to non-
agricultural uses. Urbanization has also displaced self-employed farmers to agricultural
laborers and small scale enterprises. Existing regional development strategies have created
rural-urban disparities expressed as measures of economic progress and the provision of
public facilities. Urbanization, therefore, has negatively affected the viability of regional
agriculture and its role as the bread basket of Indonesia, and the welfare of the rural
population engaged in the agricultural sector.

To sustain regional agriculture and to overcome the negative impacts of urbanization
on the welfare of rural populations and rural-urban disparities, in the short-term, the
government must change investment strategies from a focus on urban sectors and areas to
diversion of investments over space to promote the establishment of generative, secondary
cities in the region. In the mid-term, the government must also provide greater local
autonomy, at least, by fostering land use planning initiatives which incorporate policy
measures with incentives to rural populations engaged in agriculture such as creating
transferable land development rights, agricultural tax abatements, subsidies in agricultural

inputs and marketing, and public investments in the rural infrastructure.

Copyright by
JOYO WINOTO

1995

To Leila, Larasita, Bapak, Ibuk, and Petani Indonesia

ACKNOWLEDGMENTS

I gratefully acknowledge the contribution of individuals and institutions both in the
US and Indonesia that have made this dissertation possible. First of all, I would like to
express many thanks to Dr. Gerhardus Schultink, Professor, Department of Resource
Development, Michigan State University, who served as my dissertation director and
advisor during my course work. His friendly advice and continual encouragement
throughout my entire graduate program and his stamina in reviewing a great many drafts
were instrumental to the successful completion of this dissertation. His fatherly advice,
patience, and encouragement have strengthened my commitment to the science and its use
for those who are powerless.

I would also like to thank Dr. Assefa Mehretu, Professor in Economic Geography
and Integrated Study in Social Science; Dr. James Bingen, Professor, Department of '
Resource Development; and Dr. Richard H. Bernsten, Professor, Department of
Agricultural Economics, Michigan State University for serving in my dissertation
committee and for their extremely valuable comments in this study. Special thanks is
expressed to Dr. Mehretu who taught me not only how to learn but also how to teach
efl‘ectively in the enjoyable environment.

Research funding was obtained from several sources. I wish to thank Dr. Agus
Pakpahan, Center for Agro Economic (PAE), Ministry of Agriculture, Indonesia who gave
me an opportunity to incorporate this research in his on-going project of land conversion
in Java. Special thanks is expressed to Ir. Soemaryanto, M8,, project manager, and his

stafl‘ who provided me with full access to project data.

This research could not been completed without personal, financial, and logistical
supports from Dr. Lutfi Ibrahim Nasoetion, Director of the Research Institute, Bogor
Agricultural University, Indonesia. In addition, Dr. Nasoetion was also my academic
advisor in Bogor Agricultural University who encouraged me to pursue my graduate
studies in the Department of Resource Development, Michigan State University. For all
his support and encouragement, I would like to express my deep appreciation.

Additional funding for field research in Indonesia was provided by International
Studies and Programs, the Department of Resource Development, and the Thoman Fellow
Program, Michigan State University. Specifically, I wish to thank Dr. Gil-Chin Lim, Dean
of the International Studies and Programs; Dr. Gerhardus Schultink; and Dr. James
Bingen who made the in-country survey possible.

Special thanks is also due to the several people who helped me complete this
dissertation. Dyah Retno Panuju, Suhadak, and Daud from the Department of Soil
Sciences, Bogor Agricultural University, helped me collect field data with full eagerness
although without any financial rewards. Erlin from the Research Institute Office, Bogor
Agricultural University, facilitated my field research because of her skills in handling all
administrative requirements. Ali Nurmansyah and Rahayu Riana helped me clarify some
statistical concepts.

I would also to thank Herr Soeryantono who helped me improve my computer skills
and helped organize my dissertation. Most importantly, I thank him and his family for

their commitment and for life-long fiiendship.

vii

I would also like to express my gratitude to Proyek Pengembangan Staf dan Sarana
Perguruan Tinggi (Proyek PSZPT), Ministry of Education and Culture, Indonesia for
financially supporting my graduate studies at Michigan State University. A special word
of thanks to Dr. Sitanala Arsyad, Professor and Rector of Bogor Agricultural University,
who made it possible to take a study leave for five years. Also, a special thanks to
Dr. Oetit Koswara, Professor, Department of Soil Sciences, Bogor Agricultural University
who helped me obtain a full scholarship from the Ministry of Education and Culture,
Indonesia. Special thank also due to Dr. Muslimin Nasution, Assistant for the Minister of
Central Bureau of Planning and Development, for his personal support during my graduate
studies.

Finally, I want to thank my wife, Leila, to whom I remain forever grateful for her
love, support, and patience. I cannot thank my daughter, Larasita, enough for traveling
accross the seas and thousands miles to permit me to conduct field research at her age of
26 days. Moreover, Larasita's laughs and cries are part of the excitement in finalizing this
dissertation. My father and my mother who always support and pray for my success must
receive the highest recognition. Special thanks to my older brother, Ir. Soeryo Handoko,
who always loves me and has financially supported me during the field research. Special
thanks also to my beloved sister in law, Tieke, who helped me finalize this dissertation by
staying in the US during the process of writing and helped me type some tables. More
importantly for her patience in taking care of my daughter while I was absorbed in the

writing of this dissertation.

viii

TABLE OF CONTENTS

PAGE
LIST OF TABLE .................................................................................................. xii
LIST OF FIGURES ............................................................................................... xv
ABBREVIATIONS ............................................................................................. xvii
CHAPTER
I. Introduction ......................................................................................................... l
1.1. Background of the Study .............................................................................. 1
1.2. Problem Statement ....................................................................................... 6
1.2.1. The Northern Coastal Region of West Java NCR : Regional
Characteristics and Policies Afi‘ecting Agricultural
Development and Urbanization .......................................................... 6
1.2.2. Research Problems ........................................................................... 14
1.3. Research Objectives ................................................................................... 17
1.4. Organization of Dissertation ....................................................................... 18
II. Impacts of Urbanization on Agricultural Development : A Conceptual
F rarnework ....................................................................................................... 20
2.1. Key Concepts and Definitions .................................................................... 20
2.1.1. Urbanization .................................................................................... 20
2.1.2. Agricultural Development ................................................................ 24
2.2. Impacts of Urbanization on Agricultural Development in the NCR ............. 31
2.2.1. Urbanization and Regional Development .......................................... 31
2.2.2.1. Urbanization : Modernization and Dependency Theories ..... 32
2.2.2.2. Urbanization Theory in the LDC's ....................................... 36
2.2.2. Rural Urban Interactions .................................................................. 40
2.2.3. Impacts of Urbanization and Agricultural Development in
the NCR : A General Hypothesis ..................................................... 43
2.2.4. Specific Research Hypotheses ...................................... ' .................... 48
III. Data Collection and Research Methods ............................................................. 51
3.1. Data Collection Method ............................................................................. 51
3.1.1. Primary Data .................................................................................... 52
3.1.1.1. Sampling Procedures ........................................................... 54
3.1.1.2. Survey Instnrments ............................................................. 56
3.1.2. Secondary Data ................................................................................ 57
3.2. Compilation and Organization of Data ........................................................ S8

3.3. Data Analysis ............................................................................................. 58

3.3.1. Steps of Data Analysis ..................................................................... 58
3 .32. Mathematical Models ...................................................................... 59
3.3.2.1. Rate of Change in Population Density Over Time ................ 59
3.3.2.2. Rate of Change in Population Density Over Space .............. 60
3.3.2.3. Urbanization Process Analysis ............................................. 62
3.3.2.4. Location Quotients and Gini Coefficients ............................ 64
3.3.2.5. Sample Mean Comparisons ................................................. 66
IV. Urbanization and Its Causal Factors .................................................................. 69
4.1. Urbanization in the NCR ............................................................................ 70
4.1.1. Rural-Urban Classification ............................................................... 70
4.1.2. Level of Urbanization ....................................................................... 72
4.1.3. Temporal and Spatial Rate of Change in Population Density ............. 79
4.1.3.1. Temporal Rate of Change in Population Density ................ 79
4.1.3.2. Spatial Rate of Change in Population Density ..................... 83
4.2. Urbanization Process in the NCR ............................................................... 88
4.2.]. Definition of Urbanization Process and Its Causal Factors ................ 88
4.2.2. Factors Determining Urbanization Process in the NCR ..................... 95
4.2.2.1. Push Factors ..................................................................... 102
4.2.2.1.1. Changes in Land Tenure .................................... 102
4.2.2.1.2. Changes in the Agricultural Economy ................ 104
4.2.2.2. Pull Factors ....................................................................... 106
4.2.2.2. 1. The Degree of Industrial Development .............. 106

4.2.2.2.2. Changes in the Availability of Public
Facilities ........................................................... 107

4.2.2.2.3. Changes in the Availability of Pre-college
Educational Development ................................. 108
4.2.2.3. Demographic Factors ........................................................ 109
4.2.3. Village Proximity to Cities and Urbanization Process ..................... 109
V. Urbanization and Agricultural Development ..................................................... 115
5.1. Operational definitions ............................................................................. 117
5.2. Changes in the Distribution of Regional Land Ownership ......................... 119

5.2.1. Changes of Land Ownership Distribution in the NCR

Region ........................................................................................... 119
5.2.2. Changes of Land Ownership Distribution in Rural Areas ................ 121
5.3. Absentee Land Ownership in Rural Areas and the NCR Region ................ 124
5.3.1. Absentee Land Ownership in the NCR Region ............................... 125
5.3.2. Absentee Land Ownership in Rural Areas ....................................... 127
5 .4. Agricultural Land Conversion in Rural Areas and in the NCR Region ....... 129
5.4.1. Agricultural Land Conversion in the NCR Region .......................... 130
5.4.2. Agricultural Land Conversion in Rural Areas ................................. 132
5.5. Impacts of Agricultural Land Conversion on Household Income .............. 133
5.6. Structural Changes in Regional and Rural Village Employment ................ 136

X

VI. Regional Development of the Northern Coastal Region of West Java

(NCR) ............................................................................................................ 143
6.1. Regional Development of the NCR .......................................................... 143
6.2. Rural-Urban Disparities ............................................................................ 146
6.2.1. Regional Economic Progress .......................................................... 148

6.2.2. Marketing Facilities ........................................................................ 153

6.2.3. Educational Facilities ..................................................................... 157

6.2.4. Health Care Facilities ..................................................................... 160

VII. Summary and Policy Implications .................................................................. 163
7.1. Summary of Findings ............................................................................... 166
7.2. Policy Implications ................................................................................... 176
7.3. Needs for Further Research ..................................................................... 181
BIBLIOGRAPHY ................................................................................................ 183

LIST OF TABLES

TABLE PAGE
1. Number of Villages in the Northern Coastal Region of West Java

(NCR) by Population Density Interval in 1980 and 1990 ............................... 73
2. Number of Rural and Urban Villages in the NCR in 1980 and 1990 .............. 75
3. Changing Composition of Rural and Urban Population in the NCR in

1980 and 1990 .............................................................................................. 76
4. Mean of Rate of Change in Population Density between 1980 and

1990 (TRCPD) in the Northern Coastal Region of West Java ....................... 81
5. Mean Comparison of the Temporal Rate of Change in Population

Density (TRCPD) among Sub-regions in the NCR Using One Way

Anova and Least-significant Different (LSD) Multiple Range Tests .............. 82
6. Rate of Change in Population Density (b) Over Distance (SRCPD)

from the Capital City of Kabupaten Using Linear Model with Least

Square Method ............................................................................................. 85
7. List of Causal Factors Expected to Affect Regional Urbanization .................. 90
8. Trends of Causal Factors Expected to Affect Regional Urbanization ............ 96
9. Causal Regional Urbanization Factors ........................................................... 99
10. Statistical Summary of the Multiple Regressions of Urbanization with

Distance factors in the NCR ........................................................................ 1 1 1
11. Statistical Summary of the Multiple Regressions of the Urbanization

Process in the NCR with Dummy Variables of Urban Area and Urban

Area with the Village Proximity to Jakarta, Cirebon, and to the Capital

City of Kabupaten ....................................................................................... 11 1
12. Differences in the Distribution of Household Land Ownership in the

NCR between 1982 and 1992 ..................................................................... 120
13. Differences in the Distribution of Household Land Ownership in the

Rural Areas of the NCR between 1982 and 1992 ........................................ 122

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

Regional Differences in the Hectarage of Absentee Lands and the
Total Number of Absentee Land Owners or Absentee Landlords

between 1982 and 1992 .............................................................................. 125

Differences in the Hectarage of Absentee Lands and the Total Number
of Absentee Land Owners or Absentee Landlords in the Rural Areas

of the NCR between 1982 and 1992 ........................................................... 128

Differences in the Total Land (ha) and Total Land for Each 1,000
Village Population (ha/1,000 village population) for both Irrigated

Land and Agricultural Dryland in the NCR between 1982 and 1992 ........... 131

Differences in the Total Land (ha) and Total Land for Each 1,000
Village Population (ha/1,000 village population) for both Irrigated
Land and Agricultural Dryland in the Rural Areas of NCR between

1982 and 1992 ............................................................................................ 132

Difi‘erences in On-farm, Ofilfarm, and Total Incomes (Rupiah) of
Farming Households Before and After Irrigated Land Conversion

During the Period of 1982 and 1992 ........................................................... 134

Difi‘erences between A fler-Land-Conversion-On-farm Income of
the Households Involved in Land Conversion and On-farm Income of

Those not Involved in Land Conversion, 1992 ............................................ 136
Differences in the Regional and Rural Area's Employment Structure

between 1982 and 1992 .............................................................................. 137
Differences in Regional Industrialization between 1982 and 1992 ................ 144

Location Quotients, Gini Coefficients, Percentage Distribution of the
Number of Telephones, Houses with Electricity, Television, and

Population by Village; and Data for Lorenz Curves in the NCR, 1990 ........ 150

Location Quotients, Gini Coefficients, Percentage Distribution of
Village Marketing Facilities including Number of Markets with
Permanent Buildings, Kiosks selling Agricultural Inputs, Kiosks selling
Agricultural Products, and Population; and Data for Lorenz Curves in

the NCR, 1990 ........................................................................................... 155

24. Location Quotients, Gini Coefficients, Percentage Distribution of

25.

Village Educational facilities including Number of Elementary
Schools, Secondary Schools, High School, and Population; and Data
for Lorenz Curves in the NCR, 1990 .......................................................... 158

Location Quotients, Gini Coeflicients, Percentage Distribution of

Village Availability of Health Care Facilities including Number of

Physician, Traditional Midwives, Health Care Providers, and

Population; and Data for Lorenz Curves in the NCR 1990 ......................... 161

xiv

LIST OF FIGURES

FIGURE PAGE
1. Java Islands and Its Provinces ......................................................................... 3
2. Study Area : the Northern Coastal Region of West Java (NCR) which

consists of Kabupatens Bekasi, Karawang, Subang, and lndramayu ................ 7
3. Distribution of the Villages in the NCR Based on the Village's

Population Density ....................................................................................... 73
4. Distribution of Rural and Urban Villages in the NCR in 1980 and 1990 ......... 75
5. Total Population in Each Sub-region (RI-4; U1-4) of the NCR for

1980 and 1990 .............................................................................................. 76
6. Mean of Rate of Change in Population Density in Each Sub-region

(R1-4',U1-4)ofthe NCR between 1980 and 1990 ........................................ 81
7. Distance Decay Function of Population Density from the Capital City

of Kabupatens Bekasi, Karawang, Subang, Indrarnayu, and in the

NCR in 1990 ................................................................................................ 8S
8. The Relationship between the Actual Values of the Natural Log of

Village's Population Density and Its Predicted Values Derived from

the Analysis .................................................................................................. 87
9. Functional Linkages Among Urbanization, Its Causal Factor, and

Agricultural Development ........................................................................... 116
10. Lorenz Curves for the Distribution of the Households with Telephone,

Electricity, and with Television in Relation to Population, by Sub—

regions of the NCR ..................................................................................... 150
11. Lorenz Curves for the Distribution of Markets with Permanent

Buildings, Kiosks selling Agricultural Inputs, and Kiosks selling
Agricultural Products in Relation to Population, by Sub-regions of the
NCR ........................................................................................................... 155

12. Lorenz Curves for the Distribution of the Number of Elementary

13.

Schools, Secondary Schools, and High Schools in Relation to
Population, by Sub-regions of the NCR ...................................................... 158

Lorenz Curves for the Distribution of the Number of Physician,
Midwives, and Total Health Care Providers in Relation to Population,
by Sub-regions of the NCR ......................................................................... 161

ABBREVIATION

Organizations

GOI Government of Indonesia

CBS Central Bureau of Statistics

PLN Perusahaan Listrik Negara, a government agency providing electricity in
Indonesia

PAE Pusat Penelitian Sosial Ekonomi Pertanian (the Center for Agro Economic
Research)

IPB Institut Pertanian Bogor (Bogor Agricultural University)

Technical Terms

NCR The Northern Coastal Region of West Java, the study area

R1-4 Sub-region 1 to 4 of the rural area

Ul-4 Sub-region 1 to 4 of the urban area

UP Urbanization process in the NCR

TRCPD Temporal Rate of Change in Population Density (people/kmzlyear)

SRCPD Spatial Rate of Change in Population Density (people/ka/km)

GC Gini Coefficient, an index of dissimilarity

LQ Location Quotient, an index of concentration

LSI Large Scale Industry (2 100 employees)

MSI Medium Scale Industry (20 5 employees < 100)

S81 Small Scale Industry (5 5 employees < 20)

Phone Telephones

Elect. Electricity, households with electricity

TV Television

KAI Kiosks selling agricultural inputs

KAP Kiosks selling agricultural products

Elsch Elementary school

Secsch Secondary school

Hisch High school

Mwife Traditional midwives

Care Total health care providers including hospitals, polyclinics, clinics,
maternity centers, and community health care centers

Anova Analysis of Variance

LSD Least-significant Difference

D.F. Degree of Freedom

m Meter

km2 Square kilometer (1,000 m x 1,000 m)

haorHA Hectare(100mx100m)

C Celcius

Rp. Rupiah, Indonesian currency unit

xvii

I. INTRODUCTION

1.1. Study Background
In the last two decades, Indonesia has experienced fast-growing urban population. It

is predicted that almost forty million residents will be added to Indonesia's cities in the
final two decades of this century (Hamer, Steer, and Williams, 1986).

Most of this urban population is concentrated in the most populous island of
Indonesia, Javal (Moochtar, 1992; Soegijoko, 1992; Soemarwoto, 1992', Firman, 1992;
Hill, 1992a; Hill, 1992b; Soernarwoto er a], 1991; Hardjono, 1983; Hugo, 1978). The
recent census shows that 62 percent of the Indonesian population is concentrated on Java
which covers only 7 percent of Indonesian's territory (Poot, Kuyvenhoven, and Johnson,
1990; Hill, 1992a).

The total urban population in Java, in 1980, was 23 million people or 69.70 percent
of the total urban population in Indonesia. The World Bank estimates that the total urban
population in Java will rise to 41 million in the year of 20001. From this figure, Jakarta—
the capital city of Indonesia—has the highest proportion of urban population in Java at

26.46 percent, followed by West Java province at 25.17 percent. Excluding Jakarta, West

 

immuammmpmdbymmmranmummmfiwumumdsormmmm
JayermauanaMandJm Amongtheceislands,Javaisthemostpqnflousmddevelopedislandinthc
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dividedbySprovincecarnong27provinceainIndoneaia. 'l'hepcvincecinJavaare:(i)theapecialprovinceof
Jakata;(ii)flrermvinceofWectJava;(iii)thepmvinceofCentralJava;(iv)thecpccialprovinceonogyakarta;and
(v)theprovinceofEastJava(Figm-el)
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becauaeof:(1)theincreaseofthedynamicofnnal-mbanmigrationasaremltofinfiasuucunedevelopmtinthe
last15yeusinJavamchasthedevelcpmmtofhighwaysinJavaandahhedymicofeconomicdevelopmcntin
theareasmrndbigcitieainJavaasstatedbyFirman(l992;p. 101)

l

 

2
Java has the highest proportion of urban population in Java at 34.24 percent (Harner et
al., 1986) concentrated in the northern coastal region (Hill, 1992b; Soegijoko, 1992;
F irman, 1992) as a result of many economic activities especially industry, trade, and
services, acting as engines of urbanization (Firman, 1992). The location of Java and its
provinces are depicted below (Figure 1).

In his study, Firman (1992) concludes that urban population growth in Java is not
only evident in the big cities—such as Jakarta, Bandung, Cirebon, Semarang, and
Surabaya—but also in: (i) the periphery of such big cities, and (ii) the areas close to the
regional arterial roads connecting large cities. In other words, urbanization process in
Javaoccursnotonlyintheareasaroundbigcitiesbutalsointhecorridorsjoininglarge
cities, such as the area between Jakarta and Cirebon which is usually called as Jalur
Pantar' Utara Jawa Barat or Northern Coastal Region of West Java (NCR).

Urban population growth during the period 1980-1990 has created a
growing corridor along the Northern coasts of Java, extending from
Jakarta to Semarwrg through Cirebon (Firman, 1992; p. 104)

Firman‘s finding confirms McGee's assertion that rapid urban growth in Asia is
accompanied by the emergence of peri-urban regions and urbanized corridors joining big
cities’ (McGee, 1991). McGee (1987 and 1990 cited in Firman, 1992; p. 96) identifies
six characteristics of such urbanized corridors in Asia: (i) very high population density; (ii)
generally but not exclusively wet-rice regions with very small landholdings; (iii) enveloping
big cities in the regions; (iv) invariably characterized by growth of diverse non-agricultural

 

3McGee(1989)inhisartic1e, Urbau'sasiorKotadaasr'? .~ EvolvingPattmofUrbantzation inAsia, calledthe
developmemofuhanizedregicnmchastheNCRasapmcessofkatadmsi. “Kamdeuriisacoinedmrdfin
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Wofmbanndnnlacfivityocanrmginfiresamegeographictantmy'McGee,1989,pp.93-94)

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4
activities; (v) there is considerable interaction between rural and urban activities; and
(vi) with an intense land use mix.

The study of the urbanization process in such a corridor region is a relatively new
phenomenon in the literature of urbanization which usually focuses mainly on the
dynamics of urban centers with analytical frameworks mostly fitting developed nations
rather than developing nations‘ (Bhadra and Brandao, 1993; Datta, 1990). Several studies
in urbanization in the developing nations, admittedly, have analyzed this type of region but
theyusuallytreattheregionasasmallurbancenterwiththesamefirnctionsasthatofa
large urban centers’ (Hardoy and Satterthwaite, 1986; Kabwegyere, 1979; Southall, 1979;
Rondinelli and Ruddle, 1976; Hamer et a1, 1986; Armstrong, Warwick, and McGee, 1985;
Bhooshan and Misra, 1980; Honjo, 1981; McAndrew, 1990). Moreover, the study
concerning the impacts of urbanization on the agricultural development in both pen-urban
and corridor regions is rarely conducted in the developing nations (Bhadra and Brandao,
1993), inchrding Indonesia (Firman, 1992). Consequently, the nature of urbanization and
its impacts on rural and agricultural development in such urbanized corridors in Indonesia

arenot firllyunderstood.

 

4BhadraandBrandao(1993;p.2)assertthat"I'heliteratrneanalyzingurbandeveloprnentislarge. Overthelast
fundecadea,researchershavedealtwithmnnermsrelatedissues,suchaserquanationsfatheerdstenceandgrowth
ddfiakmhfimsfipbmmcfiymwmmmmmmfimmdemcimmofmsector-
medficmncaJvdhbihtymdmmmgmtdmmemmdmhdescmnmgbdamedmbm
development.... Smprisingly,the1iteratrnehasgivenmnch1essattentimtotheimplicationsofm'bandevelopmem
fateddamimfimoffiemoflmdflwfiimbflmnnflmdmhnmm,equivalently,between
agricrrltmeandmagricultme. Maeover,mostoftheeadstingsmdiecfocuscnmedevelopedcmmniesandin
particular,ontheUnited States”. Costaetal. (1989; p. 3), weaver, statesthat,’WhileAsianmbanization is
dmilarinmyrespectstoWestantnbanizafionitisthedifi‘aunasweu'.
slutheirarticle,WSnnllardlntamadiateUrbarCmm,l1ndoymdSanathwaite(l986;p. 6),fcrexamp1e,
matethrn,”...theflamnbmaflahnamediatembmcartaswhichueflnwbmcmtaswithwhichmostm
peopleandnrralarterpliaesinteract Yettherolethatsuehcenterscanplayinsupportingsocialandeconcmic
development within rural areas...is rarely given sufficient attention".

5

Such regional growth complicates problems of regional development in Indonesia
Until recently, Indonesia still does not have comprehensive measures to deal with urban
development and agricultural development in the hinterlands of big cities (Harner et al,
1986). Therefore, macro and micro studies are needed to analyze the changes which
occur in the urbanized corridors to permit the development of comprehensive regional
planning in the future. Among them are studies to analyze: (i) the impacts of the changes
on the regional development as a whole; (ii) the impacts of urbanization on agricultural
development since agriculture is still the most important sector generating household and
regional income, and employment; (iii) the changes in land use patterns and land prices in
theareaimmediatelysurroundingmaincitiesaswellasintheruralareas;(iv)theextent of
agriculturallanduseconversionanditsimpactsonthewelfareofthehouseholdsaudits
impacts on agricultural sustainability; (v) the changes in relationships with the
metropolitan centers; (vi) the changes in the socio-economic conditions in the region and
the impacts on migration—both internal migration in the region and migration to the
metropolitan centers; (vii) the changes in mral and urban employment; (viii) the changes in
the settlement patterns; (ix) the changes in the environmental quality; (x) socio-economic
dispmifiesbetweenmrflmdmbmareasofmeummcorndom;and(rd)flnchanges
inmralanbanhnkageshtheareaandthechmgesinthembMuea-metropohnn
center linkages. The suggested studies associated with the urbanized corridor, its
characteristics, and processes listed by no means provide a complete list of research needs.
Inthisstudy, someaspectsofthe changes ofthe corridorregion, especiallyimpacts of

regional urbanization on agricultural development, are analyzed.

6

This study primarily analyzes the region that can be categorized as a corridor region
joining large cities subject to urbanization with regional characteristics as those described
by McGee (see pp. 2-4). Therefore, this study was conducted in Jalur Pantai Utara Jawa
Barat or the Northern Coastal Region of West Java (NCR), connecting Jakarta and
Cirebon. The NCR consists of four kabupatens‘5 , namely : (i) kabupaten Bekasi; (ii)
kabupaten Karawang; (iii) kabupaten Subang; and (iv) kabupaten lndramayu (Figure 2).
Thisisthemoa urbanized regioninJava(Firman, 1992)andhaslongbeendesignated as

the bread basket of Indonesia (Soemarwoto, 1992).

1.2. Problem Statement

 

The Northern Coastal Region of West Java (NCR) has long been the center of
agricultural development , especially wet-rice production, in Indonesia". It is commonly
referred to as the Iumbrmg pangon Indonesia or bread-basket of Indonesia (Soemarwoto,
1992). It has the best irrigation systems (Soemarwoto et al. 1991) and agricultural
development institutions in Indonesia (Nasoetion, 1994). The development of this region
asanagriculturalproducfioncemflcanbetracedbacktotheDtmhcolonial period.
During this period, the development of the irrigation system along the NCR started.

Following the independence of Indonesia in 1945, and continued by the New Order of

 

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7'AtWWofWeuhn'qumafimowmiumenmhanmregimwmchwlwmmcwmhdof
thetctallmdareaoftheprovince'(HehanussaandHehuwat, 1979). 'I'heNCRisfmmedbyanalluviallowland It
ccnaistslargelyof alluvial riverdepodtsandlaharsholcanic flowdeposits]&mnthevolcanoea(0ngkoscngo, 1979).
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(Ilahude,1979).

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8

Government since 1967, this region has been further developed as the center of food
production through the rehabilitation and expansion of the irrigation systems, and other
agricultural development measures.

Furthermore, it is in this region that the green revolution8 in Indonesia—pioneered by
Bogor Agricultural University—launched in the mid 19605 originated. The policies and
programs implemented by the Government of Indonesia (601) were the rehabilitation and
expansion of irrigation systems, continued investment in the agricultural research capacity,
the implementation of intensification programs by introducing higher agricultural inputs in
the fixed land, the introduction of high yielding varieties, continued provision of highly
subsidized inputs such as fertilizers and pesticides, and the development of the agricultural
extensionservice. Alltheseefi'ortshavemadethcregionasoneofthecentersof
agricultural development contributing to Indonesia's self-aficiency in rice in 1985
(Erwidodo, 1990).

Besides agricultural production subsidies, the 601 also introduces several policies
which affect, directly or indirectly, agricultural development as well as urbanization in this
region

At the macro level, the 601 intended to maintain Indonesia's status as a self-suficient
country in food production, especially rice. Consequently, the status of the NCR as the

breadbasketoflndonesiawillbemaintained. Forthispurpose,theGOIstillmaintainsits

Wpohdesmagrimdnnewchaszdaernfimngflmrmdceihngpficesofagriadnnal

 

swamwmmuammrmmmmmmmmmmwmmd
mamagianmmummswiummmmammmmmmmm
andHazell,1985)

9
products, especially rice; subsidies in the development and rehabilitation of irrigated paddy
lands; the provision of agricultural inputs; and developing a bufi‘er system to anticipate
price fluctuation in agricultural commodities (N asoetion, 1994).

Most importantly, the GOI restricts agricultural land conversion (especially irrigated
paddy land) into non-agricultural uses—a realization that urbanization in this region has
created development pressure on agricultural land. Besides, through Regional
Development Planning, which was introduced by the Local Government of West Java in
1974 (Government of West Java, 1990), the GOI also restricts agricultural land
conversion through Presidential Decree No. 55, 1993, translated into the Governor of
West Java Decision No. 593.05/SK.1785-Pem.Um/1993. In this Presidential Decree, it is
clearly stated that land use and land allocation for development should follow regional
development planning (11.4.1) so that agricultural lands in the NCR are not converted into
non-agricultural uses.

AttireregionalleveLthedevelopmentofthisregioncannotbeseparatedfi'omthe
regional development of Jakarta and West Java as a whole. According to Hill (1992b),
industrial development which was viewed as a necessary condition for economic and
regional development in Indonesia during the last three decades, favored the region due to
its better infinstructure and proximity to the seat of government. It implies that
development efi'orts and investments are mostly allocated to the big cities which become
centers of political power and commercial activity (Honjo, 1981a; Coates, Johnston, and
Knox, 1977; El-Shakhs, 1976). Furthermore, Mehretu (1989) and Mehretu, Wittick, and

Pigozzi (1983) state that regional economic and social development in most LDC's has

10
been characterized by centripetal forces of concentration and agglomeration of public as
well as private investments, favoring the relatively more developed regions.
In Indonesia, city residents have received priority access to centrally
fimded, and heavily subsidized public services, while the much larger,
and poorer population of the countryside, has failed to keep pace.
Metropolitan centers, in turn, have benefited most of all (Hamer et al.,
1986; p. 9)

In this period, the G01 encouraged and subsidized medium and large-scale industries
in this region (Hill's,1992b). Hill's study shows that Java dominates Indonesia's non-oil
manufacturing economy, generating almost three quarters of value-added from medium
and large firms. West Java alone contn‘butes over one thirds of this total, and its industrial
output exceedsthatoftheentireouterislands. Interestingly, most ofthe mediumand
large scale mamrfacturing industries in this region are developed along the NCR where the
prime agricultural land is located. Moreover, the combined Jakarta-West Java value—
added is over 45 percent of the national total, indicative of the very high level of spatial
concentration in Indonesian industrial development.

Industrial development with its backward and forward linkages has attracted more
people to the NCR region In other words, concentrated industrial development has
induced urbanization in this region due to a transfer of resources from agriculture to non-
agriculture and hem rural to more urbanized areas. This transferinchrdes skilled and
rmskilled labor, capital and land resources (Bhadra and Brandao, 1993), and service
provision (Unwin, 1989).

Theincreasedtrmsferofresourcesovertimeismainlydeterminedbythesupplyand

demand of resources in the growing regional economy. Bhadra and Brandao (1993; p.3)

I 1
describes such a transfer process through the following mechanism,
From the demand side, the incentive for resource tramfer arises, in part,
from larger income shares spent on industrial products and services
relative to that on agricultural goods... The supply side effects come
from faster technical progress in industry than in agriculture...and from
significant scale economies in urban production process".

More importantly, the resource transfers ”are not only symptoms of the 'development
process' but are themselves active features in the transformation of nrral and urban places”
(Gould, 1982; p.1 cited in Unwin, 1989; p. 13).

The modernization theory of urbanization, furthermore, explains that urbanization
process occurs when the region faces structural economic transformation (Choc, 1981;
p. 101), characterized by the increased relative-share ofthe industrial and service sectors
and the decreased relative-share of agricultural sector in the regional economy (Timmer,
1990). Moreover, ”the rate of urbanization or equivalently the rate of labor redistribution
to the urban-industrial sector is largely dictated by industrialization" (Choc, 1981; pp. 100-
101). Theimplicit assumptionbehindthislineofthinkingisthaturbanizationisanatural
and inevitable consequence of industrialization and modernization (Sharbatoghlie, 1991;
p. 11).

WhatevmreasonbehhdmbadnfionocwrfingmtheNCKtheprocessprnpresaue
on the agricultural resource base, especially on prime agricultural land (Schrnid, 1968),
destined to support and maintain national food self-suficiency (Firman, 1992; Soegijoko,
1992; Soemarwoto, 1992; Soemarwoto et al., 1991).

Parallel to the described industrial development in the NCR the West Java Regional

Development Planning designed in 1974 has accelerated urban-biased development,

12

concentrating investments of development in the primate cities. The accelerated urban-
biased development due to the fact that West Java adopted functional integration rather
than territorial integration9 as its strategy of regional planning with ”growth centers"10 as
the principal instrument of its spatial policy.

Considering its proximity to the capital city, Jakarta, West Java has been designed as
the hinterland of Jakarta (Government of West Java, 1990; p. 4). By the same token, in
West Java, centers of development or growth centers were developed based on the
regional hierarchy (p. 19). Since 1974, West Java has been divided, for this purpose, into
seven functional sub-regions, including : (i) erayah Pengembangan I or WP I (Sub-region
Banten) consists of kabupatens Serang, Pandeglang, and Lebak; (ii) WP II (Sub-region
Botabek) consists of kabupatens Bogor, Tangerang, and Bekasi; (iii) WP 111 (Sub-region
Sukabumi) consists of kabupaten and ltotamadyall Sukabumi; (iv) WP IV (Sub-region
Purwasuka) consists of kabupatens Purwakarta, Subang, and Karawang; (v) WP V
(Sub—region Bandung Raya) consists of kotamdya Bandung and kabupatens Bandung,
Garut, and Sumedang; (vi) WP VI (Sub-region Cirebon) consists of kotarnadya Cirebon,
kabupatens Cirebon, lndramayu, Majalengka, and Kuningan; and (vii) WP VII (Sub-
region Priatim) consists of kabupatens Tasikrnalaya and Ciamis (Government of West

Java, 1990; p. 6 and pp. 19-27).

 

9"Theteuitcrialfaceduivesfiumcmnmmbcndsofsocialmdaforgedbyhistwywithhagivenphce. Furrcticnal
tiesarebasedcnmutualself-interests. GivarinequahfiesattlrestartafimctionalorderisalwayshiemrchicaL
accumulatingpowu'atthetop. Tafitmialrelafimship,mtheoth¢hand,dnughtheywifldscbeclmactuizedby
unthfiesofpowqmetunpaedbythemumalnghumobhgafimswhichflrembasofaterritcrialgroup
clairnficmeachotha'(FriedrnanamlWeaver, 1979;p. 7).
lonwthcerrterisdefinedas'mducedurbanintimthroughacmnbinationofdirectpublicinvestmentsandcrrpital
subsidiestoprivate arterpn'se' (FriedmanarulWeaver, 1979; p. 6).
“Kotnrodyaisadministrativermitequaltomrmicipality

13

Based on this regionalization, the NCR is located in the WP 11, WP IV, and WP VI.
Nevertheless, all four kabupatens in the NCR have been designated for the centers of
agricultural production, except for kabupaten Indrarnayu which is also designated for
development of medium and large scale industries to support the development of Cirebon.
At the kabupaten level, each administrative unit will develop its own center for industrial
and commercial development, usually the capital city (Government of West Java, 1990).

At a broader level of regional development (J akarta—West Java), the economic and
social development were to have focused on the big cities Jakarta and Cirebon, the latter
to balance the development of Jakarta. At the kabupaten level, development efi'orts and
investments were to have focused on the primary city or capital city of the kabupaten.
This regional development strategy has put the agricultural development in the NCR at
risk considering that it was designated as the center of agricultural development with
major government investments in the agricultural sector (Nasoetion, 1994). Therefore,
the development of Jakarta and Cirebon as well as the development of primary cities in
each kabupaten will put some pressure on the agricultural resource base. According to
Friedman and Wulf (1992), this type of policy in regional development will wash out
higher quality ofresources in the rural agricultural hinterlands. Accordingly, smaller cities
or centers of development will be used as outposts by the urban ruling class and urban
interest to achieve three related purposes, such as : (i) to extract a sizable surplus from the
rural economy, chiefly in the form of primary products through a process of unequal
exchange, (ii)toexpandthemarketforgoodsandservicesproducedinurbancenters,and

14

(iii) to ensure stability of the political system that maintains urban domination over the rest

of the region.

111- We
Macro and regional development policies implemented in the Northern Coastal

Region of West Java (NCR) seem to contradict with the Government of Indonesia's
(GOI's) intention to maintain the NCR as the bread basket of Indonesia. Even as the GOI
has launched several policies to protect the agricultural resource base and to maintain
agricultural production level in the NCR, current macro and regional policies put
agriculture under pressure fiom urbanization. This is, in part, induced by regional
industrial development as well as urban-biased development. Moreover, the NCR itself
has also faced massive urbanization in the last two decades (Firman; 1992; Soemarwoto,
1992).

Urbanization in the NCR, both as a corridor region connecting Jakarta-Cirebon and
as a region designated as the bread basket of Indonesia, represents a very interesting
phenomenon in Indonesian agricultural development and regional development. Assuming
that in the long-run Indonesia will be able to maintain and improve food security by
expanding agricultural productions to the Outer Islands or by international trade, it may be
expectedthattheroleoftheNCRasthebreadbasket oflndonesiawillbediminished.
Under this assllnlption, sacrificing agriculture to accelerate regional economic growth
through industrialization might be a feasible option. However, abandoning agricultural
development in this region will not be socially and economically feasible option for three

fundamentalreasons:

15

a. The first reason is that the government has already placed too high of capital investment
in agricultural development in this region so that the opportunity costs will be too high
if agriculture in this region is to be sacrificed (Soemarwoto et al., 1991). The costs is
even higher considering that most of the agricultural land in this area is irrigated
paddyland since it takes more than 10 years to establish paddy land beyond its direct
costs for establishing the irrigation network and its related socio—cconomic costs due to
its different characteristics from dryland (W moto, 1985). Most importantly, although
the relative share of the agricultural sector on the regional economy has been declining
over time, more than 60 percent of the labor force in this region still derives its incomes
from agriculture (Soemarwoto, 1992). This also indicates that the development of the
urban-industrial sector has not been able to absorb the labor surplus from the
agricultural sector (Timmer, 1990). Consequently, the land-labor ratio and labor
productivity per unit of land in agricultural areas will decline (Naylor, 1992) and
incomepercapitawill also decline12 (Eicherand Staatz,1990).

Furthermore, Erwidodo (1990) shows that this conversion process has also resulted in
fiagmentation or disaggregation of agricultural land per household. The total farm
households ofa farm sizes of less than 0.5 ha were 45.7 percent in 1973, a figure
increased to 63.3 percent in 1980. The number oflandless has consistently increased at
a higher ratethan the number ofland owners. The landless amounted to 3.2 percent of

the total farm households in 1973 and in 1980 it increased to 14.9 percent.

 

”Ammgmsmmeumpomedmysommmoglmlmmmnlmsmmemmwmm
excess.

16

b. The second reason is based on the classic studies by Jorgenson (1961), Ranis and Pol
(1961), Enke (1962a; 1962b), and Ranis (1963; 1964). They established the theoretical
relationship between agricultural development and industrialization. They asserted that
agricultural stagnation, especially food shortage, could choke-off growth in the non-
agricultural sectors by making its labor supply less than infinitely elastic.

c. The third reason is based on the conclusion of Pingali, Moya, and Velasco's (1990)
study about the post-green revolution in the Phillippines, Thailand, and Indonesia. For
Indonesia, this study used West Java, a ”rice bowl” province, as a sample. From this
study, they conclude that : (i) there is a trend towards stagnation and/or a decline in
irrigated rice yields and (ii) the rate of degradation of the paddy environment is greater
than the rate of growth in the yield potential. They also asserted, ”while national
average yield [of rice] continues to rise, [the] average yield in the province has been
stagnant” (Pingali et al., 1990; p. 11). This trend can affect net firm household income
sincethestudyshowsthattheincreaseduseofmodemagricultural inputsisnot
followed by an increase in productivity. The decrease in household net income will
discourage firmers to stay in agriculture. In addition, the increased rate of degradation
of paddy environment will reduce long-term agricultural productive capacity of the

region. These imply that agricultural viability ofthe region is at risk.

Therefore, whether or not other regions in Indonesia were able to increase their share
in maintaining the national food security, sustaining agricultural development in this region
is an imperative public policy, short and long-term, especially with focus on the

improvement of welfare of the population employed in the agricultural sector.

17

This study starts with the assertion that urbanization in the NCR and the Jakarta-West
Java Regional Planning have negatively afi‘ected the agricultural development in the NCR.
Therefore, it intends to assess some impacts of urbanization on the agricultural
development. Specifically, the focus of this study is to describe the spatial impacts of
existing regional development policies on the distribution of benefits of the regional
development, especially between rural and urban areas of the region; to analyze the nature
and process of urbanization of the region; to analyze the determinant factors afi‘ecting
urbanization process; and to describe the impacts of urbanization on the agricultural
development especially on the structure of land tenure, land conversion and its immcts on

the household's income, and the structure of rural employment.

1.3. Research Objectives

The general objective of this study is to provide a better understanding of the
urbanization process and its determinants, its relationships with regional development, and
most importantly its impacts on the agricultural development in the Northern Coastal
Region of West Java (NCR), an urbanized corridor region between Jakarta and Cirebon.
The understanding of this general objective provides a useful means to identify alternative
policy interventions to sustain agriculture subject to urbanization. This study addresses
the following objectives :
1. Analyze urbanization in the NCR and identify factors associated with urbanization

process, such as changes in land tenure, changes in agricultural economy, demographic

18

changes, the educational development, the development in public facilities, the
industrial development, and proximity to primary cities.

2. Describe the impacts of urbanization on the agricultural development, especially land
tenure including the structure of land ownership, the degree of absentee land
ownership, and agricultural prime land conversion and its following impact on the
agricultural household‘s income; the impacts of urbanization on the rural and regional
structure of employment; and the impacts of urbanization on rural industrialization.

3. Describe the spatial impacts of urbanization on the distribution of agricultural resource
base, the distribution in the development of public facilities, and the disparities in
economic development in rural and urban within the region.

4. Describe the relationship between urbanization, regional planning, and agriwltural
development in the region.

5. Examine the policy implications of the findings for sustaining agricultural and

development planning in the NCR

1.4. Organization of the Dissertation

The dissertation is divided into seven chapters. Chapter 11 presents the conceptual
frameworlr of the impacts of urbanization on agricultural development. This is a general
hypothesis of the study and is used to derived the specific research hypotheses. It is
derived mainly from the literature of urbanization and agricultural development, and the
implications of current regional development policy on regional agricultural development.
In this chapter, several ambiguous concepts are clarified to state the research direction and

focus.

19

Chapter III presents research methods and the analysis conducted in this study. First,
data collection methods include data characteristics, sampling procedures, enumeration,
questionnaire design, and survey instruments as well as compilation and organization of
data are presented. In this chapter the limitation of primary and secondary data collected
are identified followed by steps of data analysis. Finally, this chapter also presents
mathematical and statistical models employed in this study.

Chapter IV presents the process and characterization of urbanization the region.
First, it presents regional classification with its assumptions, the level of urbanization, and
the rate of change in the level of urbanization. Second, it presents urbanization and
identifies the main factors afl‘ecting the process in the region. The implications of the
urbanization process for agricultural development is also described. Finally, the role of
proximity of village to primary cities in the region is discussed.

Chapter V presents the impacts of urbanization on regional agricultural development,
including land tenure such as changes in the structure of land ownership, absentee land
ownership, agricultural land conversion; impacts of land conversion on the agricultural
household income from farm and off-farm sources.

Chapter VI presents the relationships between urbanization and spatial and social
equity. The distribution of some benefits of development, public facility development, and
the structure of employment are contrasted between rural and urban areas of the NCR

Chapter VII presents summary of the research results and their policy implications for

agricultural and rural development, and the needs for further research.

II. IMPACTS OF URBANIZATION ON AGRICULTURAL DEVELOPMENT :
A CONCEPTUAL FRAMEWORK

2.1. Key Concepts and Definitions

Two important concepts employed in this study are urbanization and agricultural
development. These two concepts, admittedly, are not easily defined because both
concepts represent a broad knowledge spectrum. However, these two concepts are
defined here to operationalize their significance in this study. As such, they reflect: (i) the
body of literature and theories of urbanization and agricultural development, and (ii) their

uses to measure the impacts of urbanization on agricultural development.

2.1.1. W

Urbanization is a term with difl‘erent meanings to difl‘erent scientific disciplines and
specialists (Firman, 1992). For regional economists, urbanization might mean the process
accompanying the structural transformation of the regional economy (Reismann, 1964;
McGee, 1971; Choc, I981; Bhadra and Brandao, 1993). For land resource developers,
urbanization might mean conversion of agricultural lands to non-agricultural uses and the
increase of real estate values (Schmid, 1968). For a sociologist-demographer, the
urbanization process means the migration process fi'om rural to urban areas with its
sociological and spatial consequences (Hauser er al., 1985). For psychologists,
urbanization might mean the changing of personal orientation from maI-a'aditioml to
urbwr—madem way of life (I-Ielmer and Eddington, 1973).

The literature of urban geography provides some fundamental aspects of urbanization

which facilitate the development of indicators of urbanization Breese (1966; p. 3) defined

20

21
urbanization as a ”process of becoming urban, moving to cities, changing fi'om agriculture

to other pursuits common to cities, and corresponding changing of behavior patterns”.
This definition gives information that urbanization involves changing economic orientation
from agriculture to non-agricultural activities and it also involves a migration process from
rural area to urban area. A specific indicator of urbanization was given by Schmid (1968)
when used to descrrbe the increase of land values in the nrral-urban fringe as an indicator
of urbanization. The importance of the growth of non-agricultural activities in defining
urbanization was also emphasized by Sjoberg (1960) when he defined urbanization as the
increase of population density and an increase in heterogeneity of a wide range of non-
agricultural specialists.

Friedman (1966) defines two broad definitions of urbanization which are applicable to
urbanization in the less developed countries (LDC's). First, ”urbanization commonly
refers to the concentration of formerly dispersed populations that are primarily engaged in
farming in a small number of settlements whose principal economic activities are in the
services, trades, and manufactures. The second meaning ”refers to urban modes of
production, living, and thinking originating in these centers and spreading from these to
outlying towns and rural populations” (Friedman and Wolff, 1982; p. 1). This definition is
modified by Williams, Brunn, and Darden (1983; p.5) when they define urbanization as
”a process involving two phases or aspects: (i) the movement of people from rural to
urban places where they engage primarily in non rural firnctions or occupations, and
(ii) the change in life-style from rural to urban with its associated values, attitudes, and

behaviors. The important variables in the former are population density and economic

22
firnctions; the important variables in the latter depend on social, psychological, and

behavioral factors. The two aspects are mutually supportive”.

Urbanization in Indonesia is usually defined based on the Central Bureau of Statistics’
(BPS, 1988) criteria13 . As presented by Firman (1992; p. 97), urbanization in Indonesia is
commonly defined as an area which has: (i) a population density of 5,000 persons per
square kilometer or above, (ii) 25% or fewer agricultural households, and (iii) eight or
more types of urban facilities. Murphey (1966) suggested that the study of urbanization
would be most useful if the researcher used the criteria of urbanization adopted by the
nation where the study was conducted His suggestion was based on his experience in
Indonesia and China where reliable data for the study of urbanization-such as conducted
in MDC's—were not available.

This study, however, will not follow Murphey's suggestion although the Central
Bureau of Statistics has developed urbanization criteria in Indonesia. Instead, it will
follow Friedman (1966) and Williams et al. (1983) definition of urbanization so tint a
single indicator of urbanization can be developed. In a more recent study of urbanization,
this line of thinking in defining urbanization is employed by Sharbatoghlie (1991; p. 51)
when he defines urbanization as ”the process which results in an increasing number of
people living in non agricultural settlements".

Therefore, urbanization, in this study, is defined as a concentration of formerly
dispersed populations accompanied by the changing occupational orientation to non-rural

or non-agricultural functions. Such urbanization can be measured by using at least three

 

l3hhrdonesiamcdiflmfiafimbetmmbmmdrmflmismademthefinagemdemkvelsothaeare
mbanvillages(desakota)andrmalfillages(desa&sa).

23
indicators, namely population density, land rent, and economic functions. However, this

study will use the rate of change in population density to describe urbanization process.
The use of this single indicator as a measure of regional urbanization, in the study area, is
based on simple reason that data of population density is available at the desa (or village)
level and it is monitored by national census period every 10 years. In addition, it is also
based on the theoretical reason proposed by Adna Weber (cited in Berry, 1981; p. 27)
stating that, ”urbanization is a process of population concentration. It proceeds in two
ways: the multiplication of the points of concentration and the increasing in size of
individual concentrations... Just as long as cities grow in size or multiply in number,
urbanization is taking place... Urbanization is a process of becoming. It implies a
movement from state of less concentration to a state of more concentration".

Furthermore, by using the rate change in population density as the indicator of
urbanization process in this region, the logical step followed in this study is to classify the
study area as rural and urban areas based on population density. The classification of rural
and urban areas based solely on population density seems a very simplistic measure
because it does not reflect the dynamic of economic activities in both rural and urban
areas. However, this measure can be used as a surrogate of urban phenomenon by
interpreting less populated area as a real rural area and more populated area as an area
with urban characteristics. Moreover, this measure is commonly used to classify rural and
urban areas (Firman, 1992; Sharbatoghe, 1991; Hwner er al., 1986; Sutton, 1989; El-
Bushra, 1989; Obudho and Waller, 1976; Nath, 1989). The main dificulty in using

population density as the indicator to differentiate rural and urban areas is in determining

24
the cutting point of population density representing the transition between rural and urban

areas. Various studies have used different density level to difl‘erentiate rural and urban

areas.

113- Wm

Agricultural development (AD) adopted in this study will go beyond Hayami and
Ruttan's (1985) conception which puts emphasis on the total production and productivity
of agriculture. It will adopt the concept of Sustainable Agricultural Development (SAD)
with its main focus on the results of agricultural development, namely to maintain and
improve the welfare and well-being of the people who earn their livelihood in agriculture.
It is assumed that agricultural development should be ”directed to the well-being of people
rather than on agricultural grth itself" (Crarner and Jensen, 1988; p. 334). However, in
formulating an operational definition of AD, this study will use an eclectic approach in
such a way that the classic theory of development, the theory of sustainable development,
the classic theory of agricultural development, and sustainable agricultural development
can be linked.

The. starting point in formulating an operational definition of agricultural development
is by tracing back the meaning of development itself. Although development is very broad
concept, literature of development has provided some important components of
development that can be applied in this study.

With the assumption that social and political problems can be overcome if the national
income increases more than the population growth, most development theorists have

equated development with economic development and economic development with

25
economic growth (Eicher and Staatz, 1990). Consequently, development efforts have

mainly been directed to increase national income (Mabogunje, 1981; Santos, 1977; and
Dadzie, 1980). But, the experience of the past decades has shown that social problems
and political upheavals have emerged in countries at all stages of development both in the
countries with rapidly rising per capita incomes and those with stagnant economies (Seers,
1970). Therefore, the theory of development becomes critically questioned by most
development theorists (Gillis er al., 1987; Little, 1982). According to some of these
development theorists, development is a normative concept which is almost a synonym
for improvement” (Okun and Richardson, 1961; Seers, 1970; Colman and Nixson, 1978;
Honjo; 1980; Bhoosan and Misra, 1980; Bryant and White, 1982)

There are two important concepts embedded in such theory of development. The
first is a concept of value that should be followed in the development efl‘orts; and the
second is the concept of inrprovernent. In the value concept, Seers (1970) proposes the
necessary conditions for a universally acceptable norm as the realization ofthe human
personality. Those necessary conditions are enough food (physical necessity) and income
to cover other basic needs such as clothing and shelter; and more importantly the justice
reflected in the income distribution. Accordingly, the concept of improvement represented
in development is overcoming poverty, unemployment, and inequality as well as the
firlfillment of human potential such as freedom, education, and political independence.
Thistheory meannesdevelopmembyusingbroaderindicatorsthanjusttheincreaseof
national income. Moreover, some indicators of development (e.g. basic needs, equity,

poverty reduction) are incorporated in the theory of sustainable development although

26
sustainable development is more than the theory of development proposed by Seers

(1970)

Sustainable development emphasizes moral responsibility which is rooted in the
philosophy that the current generations have a moral obligation toward the future
generations because (Mellert, 1985) : (i) future generations will be essentially the same as
the present generation; (ii) one is born into a given generation by historical accident; (iii)
our survival as species is more important than our individual survival; and (iv) even after
we die, the effect of our life continues. Our obligation is based on the truth that we are
more than unique and separate individuals, living only the immediacy of the now. We are,
rather, parts of much larger whole, one that transcends space and time.

The generic definition of SD is ”paths of human progress to meet the needs of present
generation without compromising the ability of future generations to meet their own
needs” (UNCED, 1987). This definition has firndarnental objectives, meeting current
needs by considering future generations‘ needs, fibrn which we can derive a range of
operational objectives that cut across most previous intellectual and political boundaries
(Lele, 1991).

The concept of sustainable development originated in the context of renewable
resources and has subsequently been adopted as a broad slogan by the environmental
movement. Agriculture, consequently, as one of the foundations of human society and as
a major activity at the human-environment interface, receives most attention of the
operationalization of sustainable development (Lele, 1991). The concept of sustainable

agriculture is still evolving hour the dialogue concerning the issue of agriculture and the

27
environment (Ikerd, 1990). Douglas (1984) identifies three schools of thought in

sustainable agricultural development (SAD).

The first regards SAD as food sufficiency, expand the supply of food with some
combination of more resources and greater productive capacity. For this school of
thought, the problem of sustaining the resource base or of honoring the culture of
agriculture seem less important than the challenge of keeping up with population growth.
Rattan (1990) supports this school of thought. He believes that sustainability is not
enough so that "if the concept of sustainability is to serve as a guide to practice, it must
include the use of technology and practices that both sustain and enhance productivity"
(Ruttan, 1990; p. 402).

The second sees SAD primarily as an ecological question. It concerns the ecological
balance. For this school of thought, the agricultural system which needlessly depletes,
pollutes, or disrupts the ecological balance of natural systems is unsustaimble and should
be replaced by one which honors the longer-term biophysical constraints of nature.
Instead of taking population as given, this approach tends to espouse policies which limit
population to those levels which can be sustained by finite physical environment.

The third is an alternative agriculture or radical agriculture. Its attention focuses
primarily on the efl‘ects of different agricultural systems on the social organization and
arlture of rural life. According to DESFIL (no date) this school of thought resembles the
ecologists in their desire to husband the permanent carrying capacity of renewable

resources, but it difi‘ers from the emphasis on sustainable human communities. Not only

28
rmrst human beings establish stewardship of the earth, they must also establish this sense in

their relations with each other, particularly as it afl‘ects justice and participation.

According to Lockeretz (1986), the last school of thought, compared to the other two
school of thoughts, has broader goals. Accordingly, it can be taken to refer to agricultural
systems that share certain broad goals : (i) to consider the structure of the agricultural
sector which favors small to moderate sized farms, especially independent, family farms
worked by resident owner-operators; (ii) to reduw the ties to the industrial economy by
increasing the self-sufiiciency of farms; (iii) to strengthen local and regional agriculture to
achieve regional food self-suficiency; (iv) to preserve farmland and avoiding firrther
disagregation of farmland; (v) to better protect the agricultural resource values; and (vi)
long-term sustainability through conservation of finite agricultural resource base.

Across these three schools of thought, Schultink (1992a; p. 206) defines SAD as ”the
development and management of natural resources to ensure or to enhance the long-term
productive capacity of the resource base and improve the long-term wealth and well-being
derived from alternative resource use systems, with acceptable environmental impacts".
Therefore, in SAD, policy and objectives should be designed to accomplish one major
goal, namely "the achievement of a sustained flow of benefits which enhance the quality-
of-life of human populations without reducing the long-term productive capacity of our
resource base” (Schultink, 1992a; p. 204).

Fromitspolicypurposes,ontheotherhand,theGovemment ofIndonesia(GOI)has
defined SAD as a ”development in which social benefits exceeds social costs, considering
a long time flame and special consideration for the poor and vulnerable. It implies for

29
present and future generations, continuous improvement in real per capita income and

quality of life, continuous narrowing of income distribution, elimination of physical
suffering due to poverty..." (Tarrant er al., 1987).

In defining agricultural development, Stevens and Jabara (1988; pp. 5-6) suggest that
the following directions are included in the fi'amework of agricultural development. They
propose that agricultural development should be directed to: (i) increase real per capita
income of the population who live in agriculture; (ii) increase food security; (iii) reduce the
number of people in poverty; (iv) achieve the least possible amount of disruption in
cultural values, rural life, and employment; (v) achieve a desired level of equity; (vi)
establish economic incentive arrangement that encourage increased productivity,
creativity, and enterprise; and (vii) increase individual opportunities, economically and
politically.

Based on the previous conceptions of agricultural development, this study defines
agricultural development in the study area as any efl‘ort in agricultural improvemmt
directed to maintain and improve existing agricultural infrastructure, to design a better
structure of agricultural land ownership, and to reduce the increased degree of the
absentee landownership in order to maintain and improve food security of rural
population, to improve the welfare of rural households, to enhance the quality of life of
rural population who earn their living in agriculture, and to reduce rural-urban disparity
without reducing the long-term productive capacity of the agricultural resource base.

The embedded assumption of the definition is that the improvement of rural

agricultural population's food security, welfare, quality of life, and mral-urban equity can

30
be fostered by maintaining and improving agricultural resource base, strengthening better

structure of ownership of agricultural resource base, and reducing the dependency of
agricultural rural areas to the increased absentee landlords through better regional
development strategy. This assumption is justified by several researches which have
previously been conducted by several experts. Smith (1982; p. 19) states that, ”ownership
of wealth, in the form of money, land or other assets, provides direct access to some of the
good things in life by virtue of providing purchasing power or social status". Therefore,
agricultural household's food security, welfare, and quality of life can be attributed to the
secured ownership of agricultural lands as the basis of agricultural production system
(Sen, 1990; Eicher and Staatz, 1990; Stevens and Jabara, 1988; Chuta and Liedholrn,
1990).

Therefore, in this aspect, this study is limited to analyze the changes in the structure of
land ownership; the changes in the degree of absentee land ownership; the changes in
agricultural prime land (or agricultural infi’astructure based on the World Bank's definition
[World Bank, 1994]) and its subsequent impact on the agricultural household income; the
changes in the structure of rural employment; and rural-urban disparities.

Other prominent impacts of urbanization on agricultural development such as changing
quality of agricultural resource base as a result of its intensive uses; soil and water
pollution induced by urban based agricultural management; and environmental impacts of
fertilizers and pesticides are not pursued in this study. The reason is mainly determined by
the fact that the time frame and resources did not allow the pursuit of the topic although it

is realized that maintaining and improving the long-term capacity of agricultural resource

31
base is part of a superior end, ”that of stewardship a region's natural resources in the

interest of future generations” (Schickele, 1954; p.95).
2.2. Impacts of Urbanization on Agricultural Development in the NCR : A
Conceptual Framework
This chapter reviews the literature which will be used as a basis for constructing a
conceptual framework for urbanization and agricultural development in the NCR. Two
dominant theories in urbanization— modernization and dependency theories—originated
from the most developed countries (MDC‘s) which are commonly applied in the study of
urbanization in the less developed countries (LDC‘s) and the urbanization theory
originated from the LDC's are reviewed under section of urbanization and regional
development. The following section review rural—urban interaction. Finally, a general

hypothesis concerning impacts of urbanization on agricultural development in the NCR is

presented in the last section.
111- W

This section reviews two contrasting schools of thought originated from the western
industrialized countries : (i) modernization theory with its basic assumption that
urbanization is a natural process in the region facing structural transformation of its
economy and (ii) dependency theory or center-periphery theory which interprets the
urbanization process in a wider context of a hierarchical system of relations. Another
theory theory of urbanization in LDC‘s, which is often overshadowed by the two previous

theories, is also presented.

32

2.2.1-1- WWW
Several classical studies on urbanization have focused on the western industrial

countries during the eighteenth and nineteenth centuries as a descriptive model of
urbanization in the LDC's. Assumption behind all of these studies is that urbanization is a
natural and inevitable consequence of industrialization and modernization. And, this
process is believed to be repeated in the current urbanization of the LDC's (Sharbatoghlie,
1991). Two classic studies conducted by Gottman (1961) and Reissrnan (1964) can be
used as examples. Both believe that previous urbanization process in the western
industrialized societies are repeated in the LDC's. They have the "same process although
greatly separated in time and place” (Reissman, 1964; p. 168) and "aspect of Megapolis
will probably be repeated in slightly different but not too dissimilar versions in many other
regions of a rapidly urbanizing world" (Gottman, 1961; p. 257).

The implication of this perception is that it is a logical step to adopt the theory and
modelofweuemmdusnializedcwntfiestoumlyzeandexplainummpmcessm
the LDCs. In fact, this line of thinking is still renewed and adopted in the current studies
of urbanization in the LDC's. Bhadra and Brandao (1993) use this model to analyze
impacts of urbanization on land allocation and agricultural development in the LDC's.
McGee (1989; p. 93) suggests that Gottman's prediction ”that Megapolis process will be
repeated in other parts of the world is being proved correct” although he also suggests
"that there are distinctive facets of the phenomenon in the Asian context which reflect the
different patterns of development and incorporation of these countries into the

international system".

33
Choe (1981) asserts that urbanization in the LDC's resembles the western industrial

revolution of the seventeenth and eighteenth centuries. He believed that urbanization
cannot be separated from general economic development policy since balanced urban
growth must be based on a balanced growth of the whole economy and of all the different
regions within a country. Economic development used to be coined with industrialization.
F urtherrnore, Choe (1981; p.101) states that, ”economic development has been followed
by the transfer of population from the low productivity agricultural sector to the much
higher productivity industrial sector, thus at the same time reducing population pressure
on the land and permitting agricultural improvement in the form of conversion to more
modern labor-saving agriculture. The rate of urbanization, or equivalently the rate of
labor redistribution to the urban-industrial sector is largely dictated by industrialization”.

In term of economic development, this process is commonly called as structural
transformation in which the relative share of agriculture in the regional economy and in
regional employment will be declining over time while the relative share of other sectors
will be increasing over time. In this process, agricultural growth is not reduced but its rate
is usually lower than that of other sectors. Tirnmer (1990) shows that combination of
agricultural growth and relative decline of agriculture's relative share in the regional
economy and regional employment is not a paradox but a normal and desirable process
and that continuing public and private investments in agriculture are essential to the
transformation process. Agriculture's relative decline in a region's structural
transformation is caused by two well documented but not widely understood mechanisms.

First, Engel's Law holds that a less-than—unitary income elasticity for products of

34
agricultural sector guarantees that the gross value of sales by farmers will grow less

rapidly than the gross regional product. Second, technical change in agriculture leads to
growing agricultural productivity, measured in terms of output per laborer or per unit of
land, leading to increased supply of farm products. Bhadra and Brandao's (1993)
conception about urbanization and agricultural development is, in fact, the same as tlnt of
Timmer‘s. Furthermore, the combination of slow grth in demand for and increased
supply of farm products leads to failing agricultural prices, which puts pressure on farmers
to move out of agriculture (Eicher and Staatz, 1990). Based on this theory, some
economists use urbanization as an indicator of economic development (Kabwegyere,
1979)

In adopting the western urbanization theory and model for analyzing urbanization
process in the LDC’s, Sharbatoghlie (1991) suggests that careful analysis should be
pursued considering the differences in their socioeconomic and cultural factors. Besides,
the LDC's do not always follow the pattern of industrial revolution as well as
mechanization of agriculture which occurred simultaneously in the Europe and North
America. He further states that,

there is a vast drflerence in the patterns of urban-industrial growth in the

West and developing countries... in [the] developing countries, the

industrial sector, for the most part, has not helped to increase agricultural

output, and methods offarming still remain underdeveloped mule in the

Western industrialization models agriculture acted as a 'residwl storage

tank' for the ever growing manufacturing demand for labor, [ in developing

countries], the mtmufacturing sector has not created enough employment to
absorb the massive influx of rural to urban migrants (Sharbatoghlie, 1991;

p. 13)

35
Without considering such difl‘erences, the policy in regional development in the LDC's

will automatically pro—urban biased, typically they minimize the potential limits to urban
growth and are silent on the issue of over urbanization (Kelley and Williamson, 1982).

Contrasting the view of the modernization theory of urbanization is that of the
dependency theory. The dependency theory was developed to apply in the LDC's.
Different from the previous theory which focuses on internal factors, the dependency
theory focuses on the factors external to the society such as international economic order,
multinational corporations, and core-periphery relations (Sharbatoghlie, 1991). At the
macro level, the dependency theory asserts that economic development of the rich
countries has contributed to the stagnation and underdevelopment of the poor societies
(Baran, 1979; Frank, 1979; Wilber and Weaver, 1979; Harrison, 1985; Amin, 1974;
1975). The two important concepts embedded in this theory are social surplus product
and concentration of elite political power (Sharbatoglie, 1991). These two concepts are
emphasized in its application of this theory at regional level analysis through center-
periphery relations (Friedman, 1973b).

The center-periphery fi'amework, specifically, interprets the urbanization process in a
context of hierarchical system of relations. ”Urbanization is thus perceived as a complex
spatial processes and their associated patterns, although the spatial relations of power. . .are
identified as the critical process to which all others are ultimately related” (Friedman and
Wulfi', 1982; p. 12). Accordingly, the resulting structural inequality among nations, as
well as within nations between urban centers and rural peripheries sustains an exploitative

chain of surplus extraction. The outcome is the underdevelopment of the periphery and

36
growth and expansion of the center (Sharbatoghlie, 1991). It implies that the growth of

primate city produces visible and severe adversities, and the existing trickle down process
from urban to rural are is a naive notion. Irnpulses from the center do not trickle down to
the periphery, but growth and stagnation are polarized (Rondinelli and Ruddle, 1976).

This framework also involves the notion that the powerful urban ruling class and
urban interests establish outposts in the smaller cities for three related purposes, namely :
(i) to extract a sizable surplus fi'om the rural economy, chiefly in the form of primary
products through a process of unequal exchange; (ii) to expand the market for goods and
services produced in the urban centers; and (iii) to ensure stability of the political system
that maintains urban domination on the rest of the region (Friedman and Wulfl‘, 1982).
This process create underdevelopment and backwardness in the periphery and agriculture
(Amin, 1974; 1975). Consequently, it creates, further, insecure and unattractive periphery
and agriculture which drive young and educated rural population to move to urban centers
which are perceived as offering better opportunities for their livelihood (Hugo, 1978;

James, 1985).

2-2-1-2- W

There is an emerging theory of urbanization in the less developed countries (LDC's)
which is usually overshadowed by modernization and dependency theories of urbanization
which are relatively more established. The theory of urbanization in the LDC's is usually
derived from the actual process of urbanization in the LDC's which is believed to have

difl‘erent nature than that in the western hemisphere. The most important development of

37
urbanization in the LDC's is that developed from Asian experience. Costa et al. (1989;

p.3) put this perspective in the following statement,

Pattern of city growth and urban development in Asia are similar to those
in other parts of the [most developed] world In Asia, however, the
demographic magnitude of the urban transformation is unusual. lhe vast
population of [Asian countries] have rapidly expanding urban systems
arising within densely populated country side. Thus, the peculiar
circumstances of city growth in Asia magnify the issues and problems
associated with urbanization to an extent never before seen in the human
history. Asian countries have a living heritage with a rich urban history
over five thousand yews. Moreover, the religious, linguistics, curd ethnic
heterogeneity present in Asian society is unmatched by wry other
continents.

While Asian urbanization is similar in arty respects to Western
urbanization, it is quite different as well. Rural-urban migration, high
density urban cluster, social heterogeneity, inadequate economic
infrastructure, and social stress are common factors in both environments.
But certain elements are drfierent. lhe compact nature of settlement, the
generally greater reliance upon, and development of; basic public
tramportation, the much greater mixing of land uses enhance the less
clearly defined spatial components, characterized the Asian city but not its
Western counterpart.

Classic theses about urbanization process in the Less Developed Countries (LDC's)
were proposed by Sovani (1964) and McGee (1967). Their theses stated that the process
of urbanization in the LDC's seemed improbable to repeat the western or the MDC's
experience in the sense of a transformation fi'om rural to urban societies. In the
developing countries, the concentration of population is commonly faster than the
differentiation of labor. Therefore, the urban development has not always succeeded to
bring large parts ofthe rural areas under its orbit of influence as the case of western
urbanization (Honjo, 1981). Sovani (1964) called the urbanization phenomenon in the
LDC's "over-urbanization" and McGee (1967) called it ”pseudo-urbanization”. It is called

over urbanization because ”at comparable levels of urbanization, the developed countries

38
of today had a correspondingly greater proportion of their labor force engaged in non-

agricultural occupations" (Sovani, 1964; p.113). And, it is called a pseudo-urbanization
for the same reason and especially because it is not similar to the process predicted by
modern theory of urbanization (McGee, 1967).

In pursuing his hypothesis, Sovani (1964) using two indices to find out the existence
of the over-urbanization in the LCD's which involves the percentage of population living
in urban areas and the distribution of the total labor force in the country as between
agricultural and non-agricultural occupations. The first is a spatial index without being an
occupational one and the second is the opposite. Ifthe composition of urban population is
much higher than that who work in manufacturing sector, the over-urbanization exists.
Although this hypothesis is claimed to be specific in the LDC's, the analytical framework
used is actually derived from the modern theory of urbanization because Sovani started his
analysis by comparing the structure of rural/urban population with the structure of
employment such as suggested by modern theory of urbanization. The McGee's analytical
framework of pseudo-urbanization is also rooted fiom such a framework.

Further analysis ofthe causes of such urbanization in the LDC's, using push and pull
theory, most expert agree tlmt urbanization process is mainly determined by push factors
fiom the countryside rather than pull factors of the city, reflecting insecurity of LDC's
countryside (Sovani, 1964; Hauser, 1985). However, Choc (1981) believed that
urbanization process is determined by the dynamic of pull of the city and push from the
countryside that have worked together and that have never been clearly separated in the

real world.

39
The ”pseudo-urbanization” thesis has been revised by Armstrong and McGee (1985)

based on their long study of urbanization in LDC's of Asia and Latin America. They
believe that the series of developments alter l970s—cspecially the growing
interdependence of the world economy and structural adjustment programs—have affected
structural and spatial formation of LDC's in such a way that major cities have become the
crucial elements of national capital accumulation and the centers of difi‘usions. They call
this revised thesis the ”convergence” thesis of urbanization. However, this thesis does not
imply that the urbanization processes among regions in a particular country are the same.
Factors influencing urbanization are specific to a region. Some regions may be mostly
afl‘ected by pull factors or push factors; while others may be determined by both (Choc,
1981)

Further development of urbanization theory in the LDC's, especially in Asia, can be
traced back to the studies conducted by McGee around the issues. The most important
finding of McGee's (1987; 1989; 1990; 1991) study of urbanization in Asia is that the
existence of growing urbanized corridor joining large cities with difl‘erent characteristics as
those predicted by Gottman (1961). According to McGee's study such an urbanized
corridor in the LDC‘s has several characteristics : (i) they have very high population
density; (ii) they are generally but not exclusively wet-rice regions with very small
landholding; (iii) they usually envelope big cities in the regions; (iv) they are invariably
characterized by growth of diverse non-agricultural activities; (v) there is considerable
interaction between rural and urban activities; and (vi) they have intense mixture of land

use.

40
In terms of urbanization process in the LDC's, it is clear that theory of urbanization in

the LDC's is rooted in the modern theory of urbanization although the result of the

analysis might different fi'om that of the western countries.

221- W122:
Rural-urban interactions can be viewed within a broader framework of regional

development through polarized development strategy (Friedman and Weaver, 1979) or
separate issue such as proposed by Unwin (1989). More important than that is grasping
the understanding of rural-urban interaction in such a way that the relationships between
the two can be established or at least understood.

Following Unwin (1989) this Section will focus on the review of three dominant
theories related to rural-urban relationships, including growth poles and urban bias;
generative and parasitic cities; and bottom-up development.

The polarized development is articulated in the growth pole concept of regional
development. This concept suggests that by investing heavily in capital-intensive
industries in the large urban centers, government in the developing countries can stimulate
economic growth that will spread outward to generate regional development. Therefore,
investment in industry at the growth pole would be the engine of development for
agricultural and commercial activities (Rondinelli, 1985). According to Friedman and
Weaver (1979; p. 114) ”this focus on polarized development suggested that rural areas
would take part in the general process of growth diflirsion only to the extent that they

were subject to the impact of the metropolitan economy. Access to large and rapidly

41
growing cities was seen as a major, and possibly even as the principal, variable in rural

development”.

The strategy to put massive investments of development in the urban centers will
create gaps and disparities between urban and rural areas. Myrdal (1957) argues that
growth at favored localities elicits backwash efl‘ect draining rural areas of resources
through ”circular causation process". Development of rural areas can be permanently
retarded unless spread effects exceeds backwash effects. However, Hirschman (1958)
believes that alter a certain point trickle down or spread effects will take over, and
through mutually reinforcing sets of backward and forward linkages growth impulses will
spread slowly over the rural areas, gradually extending benefits to poorer groups as the
economy matures. Hirschman's assertion about trickle down cfi‘ects has been criticized by
several development theorists especially for those who involve in the LDC's development.
Rondinelli and Ruddlc (1976) believe that trickle down process in the rural-urban
interaction is a naive notion considering the circular causation process in the capital
accumulation. Moreover, Lipton (1982) asserts that the power of urban people is such
that they are able to direct disproportionate share of resources towards their own interests
and away from the rural population. Further, Lipton (1982) asserts that the urban biased
development will also create disparities not only between urban and rural areas but also
withinrural areasbccauseoftheexistcnccofanalliancebetweentheurbancliteandthe
richer farmers.

Unwin (1989) corresponds the concepts of ”spread cfl'ect/backwash efl'ect" (Myrdal,

1957) and "trickle down/polarization" (Hirehman, 1958) with ”generative/parasitic” cities

42
(Hozelitz 1957). In the context of development strategy, those concepts can also be

viewed under the Stohr’s (1981) top-down and bottom-up development strategy.

The expected result of rural-urban interactions-in the form of movements of people,
goods, capital, social transactions, and administrative and service provision (Preston,
197 5)—is that reflected in the idea of the spread effects or trickle down through generative
cities. However, such an expected result is hardly achieved through growth pole strategy.
In this context, the bottom-up strategy of development (Stohr, 1981) and the conception
of the role of secondary cities in difiilsing impacts of urbanization (Rondinelli, 1983) are
noteworthy to be revisited.

According to Rondinelli (1983) rural development cannot be pursued in isolation
from the development of cities. He refuses the notion that rural development can be
entirely pursued through bottom-up development; instead, the notion of linkages between
rural and urban areas is very crucial for rural development because the major market for
agricultural surpluses are in urban centers and the public services are commonly located in
urban areas. Instead of focusing the investments in the exclusively rural areas, he
proposes to spread the investment over space in such away that secondary cities can be
created in order to build linkages between rural areas and secondary cities and between
secondary cities and urban centers. He believes that the development of secondary cities
will provide five main beneficial results, namely : (i) it relieves pressures on the largest
cities; (ii) it reduces regional inequalities since it is expected that the secondary city will
spread of the benefits of urbanization; (iii) it stimulates rural economy through the

provision of public services, enlarging rural market, and facilitating the urban center to

43
absorb agricultural surplus of labor; (iv) it provides increased regionally decentralized

administrative capacity; and (v) it helps to alleviate poverty in intermediate cities.

In contrast to the Rondinelli's approach to manipulate the urban hierarchy to spread
the benefit of development, Stohr (1981) proposes a bottom-up development in which
the development to be based primarily on maximum mobilization of each area's natural,
human and institutional resources with the primary objective being the satisfaction of the
basic needs of the inhabitants of that area. This type of strategy is oriented directly

towards the problems of poverty and must be motivated and initially emerge from the

bottom with direct participation of rural areas and the rural population.

 

Every stone thrown in a lake sends ripples in all directions, and every
[policy] has consequences that stretch beyond the mind can encompass
(Mullen and Roth, 1991; Pp. 48-49)

General hypothesis ofthis study is that urbanization process in the Northern Coastal
Region of West Java (NCR) have had adverse impacts on the regional agricultural
development and regional spatial equity. This general hypothesis will have no meaning in
designing alternative regional development and agricultural development policies in the
NCR unless specific aspects of the impacts are determined. Considering Mullen and
Roth's (1991) assertion cited above, this study will focus only on the tangible and
measured impacts of urbanization on the agricultural development by focusing its attention

onlyonthcchangingofthestructureofagriculturallandownership;thechangingofthe

44
degree of absentee land ownership; the changing in agricultural infrastructure (irrigated

paddy lands) and its following impact on the agricultural household's income; the changing
of the structure of rural employment; and rural-urban disparities. By focusing on those
aspects of agricultural development, this study assumes that the improvement of rural
agricultural population's food security, welfare, quality of life, and rural-urban equity can
be fostered by maintaining and improving agricultural resource base, strengthening better
structure of ownership of agricultural resource base, and reducing the dependency of rural
agricultural areas to the increased absentee landlords through better regional development
strategy (see Section 2.1.2).

The fiamcwork developed in this section is based on several considerations, namely :
(i) the applicability of the cited theories and concepts on the previous sections in this study
and in this region; (ii) the implemented regional planning which is urban biased because of
its growth pole strategy; (iii) the fact that the NCR is an urbanized corridor joining two
big cities, Jakarta and Cirebon; (iv) the fact that this region has the best agricultural
infrastructure and agricultural institutions in the country; (v) the fact that the government
of Indonesia still maintain this region as one of the center of agricultural development in
the firture; and (vi) the focus of this study.

The development of the whole region of Jakarta-West Java region ha adopted the
growth pole strategy (Government of West Java, 1990). This strategy can be categorized
as a polarized development strategy (Friedman and Weaver, 1979) which is biased in favor
of urban development (Lipton, 1992), especially Jakarta, Cirebon, and the capital cities of

kabupatens Bekasi, Karawang, Subang, and Indrarnayu. This type of strategy is

45
characterized by large investment in the urban-industrial sector (Rondinelli, 1985) such as

shown by the result of Hill's (1992b) study; while, rural areas would take part in the
general process of growth diffusion only to the extent that they were subject to the impact
of the metropolitan economy (Friedman and Weaver, 1979). The regional planners of this
region hold the belief that the benefit of urban development will spread or trickle over
rural agricultural areas which are very dominant in the region“ such as suggested by
Hirschman (1958) and this belief also used as a basis to develop regional planning of West
Java. Moreover, the development process in this region is connnonly applied through top-
down process (I-Iardjono, 1983)” .

With such a type of regional development strategy, it can be expected that rural-urban
disparities in the distribution of the benefits of development become larger over time
considering the cumulative causation process (Myrdal, 1957) which might happen in the
region. However, the greater gap in the distribution of the benefits of development might
not happen if the prediction of Rondinelli (1983) holds that in this region grows secondary
cities which function to bridge the rural agricultural region with urban centers assuming
that these secondary cities are also generative cities (Hozclitz, 1957). If the gap of the
distribution of the benefits of development become greater, it is expected that rural

agricultural population will move to the urban centers in order to get a better access to

 

MThisassertionwasjnuvenwhenthealnhorinvolvedmdevelopingGrfideinefchakartaDcvelopmcntPlarmingfor
nextfiveyears. MouofflnmgimalplmasmanficeofRegimalDevelopmmtbehevedthatmvesmum
Jakartamrldbarefitthehintalands.

1514ccordingtoI-lardjono(l983;p. 60),flremp-downappruach'mmifestsitselfnotonlymthelhnitedmnnbasof
mmwmmmmmmmwmmnmmmmmmmmmm
'cruh'programmes'

46
public facilities and better economic opportunities which are naturally concentrated in the

urban centers.

Such a regional development strategy will make industrial development concentrated
in the urban areas. It is expected that better quality of rural resources are attracted to
enter the manufacturing sector. If the industrial development is capable to absorb surplus
of agricultural sector, the urbanization process in this region will follow the same path of
the western urbanization process such as described by modern theory of urbanization.
However, the regional data shows that although the relative share of agriculture in the
regional economy has been sharply declining most of the population is still employed in
agriculture. It shows that urbanization process in this region does not work as predicted
by the theory in redistributing employment from the low productivity agricultural sector to
the much higher productivity industrial and service sectors.

The inability of urban-industrial sectors to absorb employment and population growth
in rural areas will put some pressures on agriculture because this sector should employ
more labor and sustain more population on its fixed resource base. Consequently, more
people in the rural area will employ agricultural land which is also declining as a result of
urban expansion. Further consequence of this situation is disaggregation or parcelization
of household agricultural land and increasing landless in the rural areas. It implies that
agricultural households with less than 0.5 ha are forced to seek off-farm activities
(Hardjono, 1983).

Since expansion of urban activities has been accompanied by the increased demand

for land to support residential and industrial estates (Firman, 1992; Schmid, 1968), it is

47
expected that this region's predominantly irrigated paddy land will be converted to other

uses. The urban expansion will also create the increasing number of land speculators
resulted in the increasing number of absentee landlords and increasing acreage of land
owned by absentee landlords. Decreasing irrigated paddy lands in this region will force
agriculture to produce more foods-as a result of increased demand for foods both to meet
the need of increased urban population and increased population growth-with a more
limited resource base and in the middle of no significant breakthrough in agricultural
technology“.

The agricultural land conversion in this region may be dictated by two mechanisms :
(i) market mechanism, and (ii) non-market mechanism. If the land conversion is dictated
by market mechanism, assuming that agricultural households are rational, it is expected
that their income after land conversion is higher than before land conversion. It is mainly
determined by economic rational of the households to sell their lands and to invest the
money to other activities or to invest the money to get more acreage of agricultural lands
in other places. If the land conversion is dictated by non-market mechanism, such as the
government needs the land for development of public facilities, it is expected that
agricultural household income in average will decline.

Based on the previous expected impacts of urbanization on the agricultural
development in the NCIL it is also expected that those impacts—changing land tenure,

changing agricultural economy, changing in demographic factors, public facility

 

“5 Pingali P.L., P.F. Maya, and LE. Velasco (1990), in their article called the Post- Green Revolution Blues in
Asian Rice Production: the Diminished gap betwear Experimart Station and Farmer Yields [Soc Sci. Division,
mtamfideiceRmchmniune,MmflePMprmes],mmmmmcmflymaeismngnificmt
wchmhgicdheahmmghmagriaflunesimemcgrem-molufimhasbemhmchedmmesia

48
development, and industrial development-also afl‘ect urbanization process in the NCR In

the context of push and pull factors, it is expected that urbanization process in this region
is mostly determined by push factors, rural agricultural factors especially changing land
tenure and changing rural agricultural economy. However, this study expects that the
distances of the village (as unit of analysis) to Jakarta, Cirebon, and capital cities of
kabupatens do not play any role in urbanization process in this region because it has very

good transportation system.

2.2.4. if R In th
The specific hypotheses advanced in this study are organized under the following

topics :
A- W
l. The rate of change in the population density in the last ten years is higher in the
urbanareathanthatinthenrralarea.
2. The spatial rate of change in the population density in Bekasi is higher than that in
kabupaten Karawang, Subang, and lndramayu.
3. The urbanization in the NCR is mostly determined by push factors from agricultural
rural areas rather than pull factors of urban areas.
4. Among push factors, the changes in land tenure contribute mostly on the regional
urbanization process.

5. Rate of urbanization is higher in the urban villages than in the rural villages.

49
6. The efi‘ect of village proximity to the primary cities on urbanization process is higher

in the urban villages than in rural villages.

 

1. Regional urbanization has caused a significant increase in land parcelization.
2. Regional m'banization has caused a significant increase in landless farming
households.
3. The percentage of subsistence farmers is not afi‘ected by regional urbanization.
4. Regional urbanization has caused a significant increase in the hectarage of absentee
lands.
5. Regional urbanization has caused a significant increase in the number of absentee
land owners.
6. Regional urbanization has caused a significant increase in the irrigated paddyland
conversion.
6.1. Household's on—fann income afier land conversion is significantly lower than
that before land conversion.
6.2. Household's ofi-farm income afier land conversion is significantly higher than
that before land conversion.
6.3. Total household income afier land conversion is significantly higher than that
before land conversion.
6.4. There is no significant difl‘erence between qfler-land—conversion on-farm income
of the households involved in land conversion with on-farm income of those not

involved inland conversion.

50
7. In the rural areas, urbanization has displaced self-employed farmers into agricultural

labor job and small scale enterprises rather than into manufacturing jobs.

C- W
1. Current regional development policy has caused the benefits of regional economic

progress to concentrate in the urban areas.

2. Current regional development policy has caused development of public marketing
facilities to concentrate in urban areas.

3. Current regional development has not affected the distribution of private agricultural
marketing facilities.

4. Current regional development has caused uneven distribution in the pre-college
educational facilities.

5. Current regional development has caused uneven distribution in the modern health
care providers.

6. Current regional development has not afi‘ected the distribution of the traditional

health care provider.

III. DATA COLLECTION AND RESEARCH METHOD

3.1. Data Collection Method

This study used three sets of data in order to address the research main issues such as
presented in Chapter I. The first was a primary data set collected through village surveys.
This represented sample data of the Northern Coastal Region of West Java (NCR) with
desa or village as a unit of analysis. The second set of data were secondary data provided
by Project of Agricultural Land Conversion in Java which had conducted a survey for
agricultural household involved in irrigated land conversion in the last ten years in the
NCR The third set of data were also secondary data consisting of census data of 1980
and 1990 for the whole region of the NCR with desa or village as a unit of analysis,
including other data related to this study.

This study was originally planned to be fiilly integrated with the existing Agricultural
Land Conversion Project coordinated by personnel of the Center for Agro Econonric
Research (PAE), Indonesian Ministry of Agriculture, Bogor, Indonesia. Unfortunately,
among four kabupatens covered in this study-Kabupatens Bekasi, Karawang, Subang,
and lndramayu—only two of them—Bekasi and Karawang—represented the project's
kabupaten samples in West Java. To cover data collection needs in the other two
kabupatens, the Research Institute and the Department of Soil Sciences, Bogor
Agricultural University (1913)" supported this study by providing logistical requirements

for the field research in the two kabupatens and allocating their personnels to help in data

 

"BogrxAgriculnnalUmvusityisflwmnha'shanemsfimfimmwhichthemnMisminstructorinLandReaource
DevelopmentPIamringandRegional BeonomicandDevelopmentsince 1986.
SI

52
collection“. A questionnaire was used by the enumerators coordinated by both PAE and

[PB were the same. In fact, information collected and captured in the questionnaire was
the combination of general information as well as specific information needed by both this
study and the project.

This chapter describes data collection method for both primary and secondary data,
data compilation and data organization, and data analysis including steps of data analysis

and mathematical models employed in this study.

3-1-1. W
The primary data collected in this study included all information needed to address

the research issues not covered by the census data. Difi‘erent fiom the census data which
represented villages in 1980 and 1990, the primary data collected in this study covered
villages in 1982 and 1992 reflecting up-dated information from the census data, conducted
eachtenyears. Similartocensusdata,theunitofanalysisoftheprimarydataisdesaor
village. One consideration to choose the village as a unit of analysis is that urbanization in
Indonesia is analyzed at the desa or village level so that desa will be difi‘erentiated as desa
kota (urban village) and desa desa (rural village).
The information collected covered a period of 1982-1992. The data includes :

1. General information of the village such as village area (hectare [ha]), total paddy land19

(ha), agricultural dryland (ha), land used for housing (ha), and other lands (ha);

 

l'I’rrrtof themseafordataeollectioninthetwokabupatensandforcollectingsecondarydataforallkabupatens
coveredinthissmdywaspmvidedbydrerjectofJakamfive-YwRegimalPlarmingasacompensationofthe
amhorsmvdvanentmmisprojectwhfle,merenwaspasmanypmvidedbytheamhm
”Paddylmdandhrigatedpaddylmrdisusedintachangeablyinthissmdy.

53 _
. Village population such as total households and total population as well as total number

of men and women;

. Population distribution based on sources of income” such as farmer (land owner),
sharecropper, agricultural labor, small scale enterprise21 , government oflicial, private
sector (entrepreneur)22 , manufacturing labor, and informal sector”;

. Migration including total in—migration by sex and total out-migration by sex;

. Village distance to the cities and market (kilometer [km]) including distance from the
village to Jakarta (km), to Cirebon (km), to the capital city of kabupaten (km), to the
capital city of kecamatan (km); and to the local market mostly used by village
Donulation (Ian);

. Infrastructure and social-economic conditions such as total paved road (km), total
hardened road (km), number and types of public transportation, number and types of
economic institutions existed in the village such as bank or cooperative, number and
type of health care facilities, number and types of educational facilities, number and
types of social and religious facilities such as youth centers or mosques, number of
households with electricity, number of households with television, and number of
household with telephone;

. Village industries including number of small scale industries, medium scale industries,

and large scale industries”;

 

3° BasedonthclargeatsharetothetotalindividualincomeanddemedasmorethanSOpercartofthetotalineomc.
”Smaflscalcarta'priacisdefinedasanacfivityrelatedtombsistcncemafl scaletradewhichdoeaneedoutside
household labor to help the person who involves in this activity.
22I:‘.ntr'eprene:ur(privateser;tor)intlrisrrtlrdyisdefinedaspeoplewhohavetheirownbusineasandtlreyarlehelpedby
outsidehouseholdlabor.
”Informalsociorinrrrissmdyisderinodassnocrivirywhiclrisnorospmrodinrhcdefiniriopormrllroareoororprisr
archas'angkot'driver(angkotissrnallbus)or'ojek' (atransportationsysteminlndonesiausingmotorcycle).

54
8. Paddy land conversion (ha); the price of paddy land (Rp., Rupiah); and the number of

land transactions in the village;

9. Average agricultural wage rate (Rp) in the village based on plowing and harvest
Periods

10. Land ownership of agricultural dryland and paddy land, absentee land ownership of
dryland and paddy land, and number of absentee landlords; and

11. Some qualitative data such as village perception about the urbanization process in the

region or problems with compensation for land conversion.

3-1-l.1.§a.!n§as£msd£r1
The sampling procedure employed follows Barber‘s (1988) sampling process which

consists of five steps, namely :

1. Definition of population, i.e. a collection of all individual elements from which the
samples will be collected. Since the unit of analysis of this study is desa or village, the
population considered in this study was all villages in the NCR region.

2. Construction of a sampling flame or a population frame, i.e. an ordered list of
population elements. The sampling flame or the population frame was developed using
a list of villages and a village-level map of each kabupaten. In this study, the target
population was the same as sampled population” .

3. Selection of a sampling design, i.e. a procedure used to select elements from the

sampling firms: for the sample. There are four sampling designs commonly employed in

 

2‘err'gerrcalcindustryisdcfinedasanirrdustr'ywithmorethanandeqnalto100labors,merliurnscaleindustr'yis
definedasanindusuywithmorcthanequaltoZObutlessthanlOOlaborsqandamallscaleindustryisdefinedasan
industrywithmorethanSbutlessthanZOlabors.
1"'"I‘hctargetpoplrlrrtiorristhcrretoflrll[elments]rclevanttorrparticularstudy.Thesnmpledpopulatiorlcorrsistsof
allthe[elements]listedinthcsampling frame“ (Barber, 1988; p. 206).

55
the data collection including simple random sampling, stratified sampling, systematic

sampling, and cluster sampling (Barber, 1988; Williams, 1986; Berry and Baker, 1968).
According to Barber (1988; p. 216), in terms of efficiency, ”Stratified samples are [the]
best and cluster samples are [the] worst. Random samples usually lie somewhere
between these two extreme. That is, for a given level of precision, stratified samples
require the fewest respondents and cluster sample require the most respondents".

To optimize sampling eficiency (highest confidence level at a given sampling size), the
study used stratified random sample in each kabupaten in the NCR as a sampling
design. Each kabupaten in the NCR was stratified into four strata based on the village
population density reflecting degree of urbanization. The first stratum was the villages
with less than and equal to 750 people per square kilometer; the second stratum was
the villages with population density between 751 and 1500 people per square kilometer;
the third stratum was the villages with population density between 1501 and 2250
people per square kilometer; and the forth stratum was the villages with population
density of more than 2250 people per square kilometer. In each of these strata, the
village samples were randomly chosen.

Total samples of this study were 44 villages or desas. According to the central limit
theorem, samples sizes of 2 30 can be expected to represent sample characteristics on
which basis inferences about the population can be made with confidence. This study
chose 44 villages as research samples, in anticipation that sampling requirement,

especially after stratification, will be firlly met.

56
4. Specification of the information to be collected. The information to be collected in this

study was specified based on the research objectives presented in Section 3.1.1.

5. Collection of the Data. In this study, data collection or data gathering was divided in
two groups. The first group covered kabupaten Bekasi and Karawang and was
coordinated by the Center of Agro Economic Research (PAE). Within this group and
for each kabupaten, data were collected by three enumerators fiom the office of PAE
accompanied by one kabupaten coordinator. The second group which covered
kabupaten Subang and Indranrayu was coordinated by the Research Institute, Bogor
Agricultural University (IPB). Wlthin this group, data collection in both kabupatens
were conducted by three enumerators from IPB accompanied by one coordinatorZ6
who was also responsible for gathering secondary data in all four kabupatens in the
region. All enumerators-both from the PAE and IPB-were trained to ensure that they
understood the questions and concepts. Prior to the training, the coordinators

conducted several meetings to develop the questionnaire and coordinate the survey.

3.1-1-2. W
The main respondents of this survey were the village omcials who were assumed to

be the most knowledgeable about the village situation and were in charge of village
records. The survey was consisted of a single interview with village oficials. To avoid
bias, the survey also conducted interviews with "key informants", usually informal leaders

in the village.

 

2“Authorwrrsthecocrdinatorofthisgroup.

57

112. Wis

Two sets of secondary data were gathered from several sources. The first data set
represented census data of 1980 and 1990. Census data were collected at the desa level
containing information related to population and village economy. These data were
obtained from Bekasi's Ofi'rce of Statistics, Karawang's Office of Statistics, Subang's
Office of Statistics, and Indramayu's Oflice of Statistics. Supplementary census records
for Bekasi 1990 and all village-level administrative maps were obtained from the Central
Bureau of Statistics (CBS), Jakarta and the Ofice of Statistics at provincial level in
Bandung. Other information such as West Java Regional Planning and other related
information were obtained from the Ofice of Regional Planning (Badan Perencanaan
Daerah, Bappeda) in Jakarta, Bandung, Bekasi, Karawang, Subang, and lndramayu; and
from the Ofl'rce of Coordination of National Land Survey in Bogor. The census data
covered all villages in the NCR , a total of 1099 villages.

The second data set related to the impacts of agricultural land conversion on
household income. These data were provided by the Project of Agricultural Land
Conversion in Java, Center of Agro Economic Research (PAE), Ministry of Agriculture,
which had conducted a household survey in the NCR in 1993. The respondents of the
survey were the households involved in land conversion during the last ten years. The
total number of respondents were 100 households consisting of 52 households involved in
land conversion and 48 households not involved in land conversion. For the households

with land conversion, the income—both farm income and ofl‘-farm income-before and

58
alter land conversion was recorded. The survey used a random sampling technique for

each group of agricultural households.

3.2. Compilation and Organization of Data

Primary data and secondary data of the 1980 and 1990 census data were tabulated,
edited, and compiled at Michigan State University (MSU) while the secondary data related
to the household income were compiled and organized by the ofice of PAE, Bogor,
Indonesia. The first two data sets were organized using the standard geographic matrix
recommended by Berry (1964). This standard matrix is widely used in regional economic
analysis. It eases the process of statistical analysis by considering both the spatial and time
dimension. Most inrportantly, this organization of data was compatible with the structure

of data in the SPSS, the analytical sofiware used in this study.

3.3. Data Analysis

3-3-1- W
In order to address the research objectives, the data were analyzed in the following
sequence :

I. The study area was stratified into two main strata, namely rural and urban, based on the
village population density. For the specific purpose of analyzing disparities on both the
distribution of the benefits of regional development and the concentration of resource
base and economic activities, the rural and urban strata were further subdivided into
smaller sub-strata. In Chapter IV, the process of defining the sub-strata in the study

areawillbevisited again;

59

2. Analyzing the level of urbanization in the study area;

3.

Analyzing the process of urbanization in the study area based on the selected variables
of push and pull factors by using a multiple regression model. The regression model
and the definition of urbanization as well as its determining factors are presented in

Section 3.4.1.;

. Calculating the Location Quotient (LQ) and Gini Coeficient (GC), indicators of spatial

concentration and spatial disparities employed in this study, for variables related to
regional agricultural development, regional economy, and regional development in
public facilities. The models used to calculate the LO and GC as well as alternative

measures for spatial disparities are presented in Section 3.4.2.;

. Constructing Lorenz Curves to represent the results of the analysis;
. Assessing the impacts of urbanization on agricultural development; and

. Testing the proposed hypothesis presented in Section 1.4.

33.2- W

The mathematical models presented in this section include models for determining the

rate of change in population density over time and over space; a model to analyze

urbanization process; models for calculating Location Quotients (LQ) and Gini

Coefficients (GC); and models to compare mean of spatial and temporal characteristics.

33-2-1. W

The rate of change is commonly defined as a change in any characteristic or substance

overaperiod oftime. Ifthe rate ofchangeisdefined asSlLthechangeinthe

60
characteristic or substance is defined as SK, and the time needed for the change is defined

as 8T; the mathematical relationship among these three variables can be presented as :

6X
5R — 5T ............................................................... (1)

Using this model, the rate of change in population density in the study area can be
determined by replacing 8R with the rate of change in population density, replacing 8X
with the difference of population density in given time period, and replacing 8T
representing the same time period. For example, if population density in 1982 is k
people/ka and population density in 1992 is m people/kmz, the rate of change in
population density between 1982 and 1992 is equal to (m-k) people/km2 divided by 10

year, indicating annual rate of change in population density.

3.3.2.2. f ' P ' i r c

The rate of change in population density over space is predicted as declining the
farther the distance of the area from the central business district (Blair, 1991; Dicken and
Lloyd, 1990; Rees, 1970). The rate of change in the population density over space is
commonly predicted by general model of a spatial decay function (Res, 1970; p.277;

Blair, 1991; p. 373) presented as :
Dx = Doe'bx ............................................................... (2)

Where : Dx is population density at a distance-x
Do is population density at the urban core
e is a constant, and
X distance fi'om the village to capital city of kabupaten (km)
b is rate of change in population density

61
In the equation 2 above, there is one parameter, b, that can be predicted using

existing data from the study area. Therefore, in this study, parameter estimation is

conducted by transforming equation 2 into a linear model such as presented as :
lan=lnDo-bX:E ................................................. (3)

Where : Dx is population density in each village in the each kabupaten in the NCR

Do is population density at the capital city of kabupaten

X is distance from the village to the capital city of kabupaten

b is rate of change in population density, and

E standard error

By assuming that capital city of each kabupaten in the NCR is also the center of

development in kabupaten, the rate of change of population density over space in each
kabupaten can be determined. Using least square estimators (Neter and Wasserman,
1974; Johnston, 1991; Barber, 1988; Runyon and Haber, 1980; Ott, 1988), the value of
the value of the rate of change in population density (b), the expected value of population
density in the capital city of kabupaten (Do), and the standard error (E) of the regression

model (equation 3) in each kabupaten can be determined through the equations 4, 5, and 6

 

below:
Estimation ofb:
b = w“ 3&1 D” "El—2’7) ........................................ (4)
2XXI-10(z‘l’I-zl’)
Estimation oflnDo:
In Do= m -b7\7 ..................................................... (5)

Estimation ofE:

62

E_‘[22(lani-b—in)(lani—b-in)
n—2

 

 

.................. (6)

Where it = number ofsample villages (l, 2, ..., i)

33-23. W

Urbanization is affected by two groups of factors: (i) rural push factor, and (ii) urban
pull factor. If urbanization, measured as a rate of change in population density, is
expressed as Y, in the general multiple regression model the process of urbanization in the
Northern Coastal Region of West Java (NCR) can be expressed as :

Y = f (rural push factor, urban pull factor) ................... (7)

Suppose that rural push factor which consists of all identified rural factors afi‘ecting
urbanization process in the NCR is expressed in the mathematical form such as 2 (X;), for
i= 1, 2, ..., N and urban pull factor is expressed as 2‘. (Xj), forj = 1, 2, ..., M; then,

equation 7 can be expressed in the multiple regression model such as :

N+M

Y=Ao_1_(n+m)+ K2; A01..(n+m)in E ............... (8)

Where : Y is urbanization process expressed in rate of change in population density

(people/kmzlyear)
Xk represents rural and urban factors afi‘ecting urbanization process in the NCR;

all these factors are stated in the form of their rate of changes, where k = 1,
2, ..., N+M -
AOJ-m are constants (value on when Xk = 0)

A0] .-m are partial regression coeficient, and
E is error term

The partial regression coefi'rcient—the slopes of the relationship between Y and X1_k
when the other variables are held constant—can be used to determine which factors or

variables in the equation significantly determine the urbanization process in the NCR

63
However, to show comparable rates of change, all variables must be measured in the

same scale. This can be obtained by transforming the A coefficient into the [3 coefficient,

using the standardized variable value such as :

ZXk = (Xk - X)/Sx ............................................................. (9)

Where : ZXk is standard Z-score of the variable (Xk) value

X is mean value, and
SK is standard deviation

Equation 8, then, can be transformed as equation 10 below :

N+M

ZYO.1—(n+m)=fio.l-(n+nr)+ ; fior.-(n+rn)Xlr: E ...... (10)

Because we are dealing with Z-scores, the mean of every variable is zero so that the value
of £014”) is zero. Consequently, equation 10 can be expressed as equation 11

below :

N+M

ZYO.l.(n+m)= Z flOI.-(n+m) Xk: E ........................... (ll)

K=I

In order to properly employ a linear model of multivariate analysis (unbiased
estimates), all assumption embedded in the model should be satisfied. The assumptions of
this linear model (Johnston, 1991) are : (i) linearity, partial plot of the dependent and
independent variable must depict linear relationship; (ii) conditional distributions of the
residuals are normal; (iii) means of conditional distribution, for every value of X, the mean
of (Y i - YMry) must be zero; (iv) homoscedascity, equal variances in the conditional

distributions; (v) the value of each observation on the independent variable is independent

64
of all of the values (autocorrelation); (vi) lack of measurement error; and (vii) the residuals

from each partial regression equation are uncorrelated (collineality).

3.3.2.4. W

The Location Quotient (LQ) is an index for comparing an area's share of a particular
activity with the area's share of some basic or aggregate socio-economic activity. The LQ
for a given activity for area i is the ratio of the percentage of the total regional activity in
area i to the percentage of the total base in area i. If A. is equal to the level of the activity
in area i and B) is the level of the base, then LQ; is presented below (Barber, 1988; p.87):

_ Ai/ZAr'
Br/zst

 

LQr

The Gini Coeficient (GC) or an index of dissimilarity (Barber, 1988; p. 90) is used in
this study to measure disparities in the regional distribution of development benefits.
Besides GC, there are several alternative methods that can be used to measure dissimilarity
such as range, relative mean deviation, variance, and standard deviation of the natural log
(Cowell, 1977).

The range measures the difference between the highest and the lowest regional
sample characteristics. This measure ignores the distribution of the spatial characteristics
between the extreme values and is sensitive to outliers. The value of range falls between
zero (equally distributed) and n (fully concentrated). The relative mean deviation looks at
the entire distribution and considers not only extreme values. This measure may produce
the same results fi'om difi‘erent distributions on the same side of the mean. The variance is

a better measure than the relative mean deviation because it is sensitive to difl‘erences from

65

the mean for all observations. However, its major disadvantage is that a distribution could
have a larger relative variation than another and still have a lower variance if the variation
around the mean characteristic level is smaller than the comparative distribution. The
coefiicient of variation is more comprehensive measure than the previous measures and is
sensitive to differences from the mean like the variance, and independent of the mean
characteristic. It has, however, two weaknesses, namely the squaring procedure in its
calculation procedure is arbitrary and it weighs difi‘erences equally. The standard
deviation of the natural logarithm is the most useful measure of inequity, especially if one
is interested in attaching greater weight to differences in extreme characteristic such as the
lower income characteristic per capita. This measure is an appropriate one to analyze
extreme poverty. However, it uses an arbitrary squaring procedure in its calculation and it
is seldom reported so that it creates dificulties in comparative studies of equity (Cowell,
1977)

Among them, the GC is the most common method used to measure dissimilarity of
inequity (Smith, 1982) and has better characteristics compared to the others such as more
sensitive to characteristics difi‘erentials, independent of proportional changes in
characteristics and population, avoids the arbitrary squaring procedure, and a direct
measure of the characteriaic differences (Cowell, 197 7). Therefore, this study uses the
Gilli Coeflicient to measure disparities in the regional distribution of development benefits.

The Gini Coeflicient is measured using the Location Quotients Approach (Smith,
1982). The coefiicient are derived by the following steps:

1. The variables used in Gini Coefficient are selected;

66
2. Reference variables are selected for use in the computation of Location Quotients;

3. Location Quotients are calculated for all sub-regions (see equation 12);
4. The sub-regions are ranked according to their location quotient value; and then

5. The Gini Coefficient is computed according to :

t

ox = (YiXHl - Yi+1Xi) ..................................... (13)

l

N
ll

Where Gx is the Gini Coefiicient of variable X
Xi is the cumulative share of variable X corresponding to Sub—region-i
Y; is the cumulative share of the reference variable corresponding to Sub-
region-i
Two types of Gini Coeficient ratios can be used for this purpose :

1. To determine spatial disparities between sub-regions. When the Gini Coefficient ratio is
close to unity, the set of sub-regions are almost similar in the nature of their spatial
disparity. To the extent that this ratio is different from 1.0, regional differences exist.

2. To determine the changes of inequality over a period of time. It can be calculated as
the ratio of the Gini Coemcient at one point in time with the Gini Coefficient at other
point in time. Ifthere is no significant change of the disparity between the two periods,
the ratio will be close to 1.0. The higher the ratio, the higher the spatial disparity over

time.

3335- Wham
In order to compare regional characteristics between 1982 and 1992, the study used

the t-test method for paired samples to test the proposed hypothesis. Following Barber

67
(1988), Netter and Wasserman (1974), and Runyon and Haber (1990), the procedure and

mathematical presentation of analysis can be summarized as follows.
Suppose that the pair of values expressed as X32; and X925, the matched-pairs is

d, = X32; - ngi; for i = 1, 2, n. Hypothesis concerning the value of sample mean

_ w d —0
difl‘erence, d = —, is conducted by using t-test oft = ——- with degree of fieedom
n Sd/s/l;

 

aw-Exw-E)

ofn-l for 84 = n _1
Hypothesis testing is constructed as follow :

H is :

Ho 1 u: - 142 = in

HA : it; - it; is not equal to it.) (two tailed), or

HA: tr, - u2< m(lowertail),impliesHo: 141' “22w, or

HA: 111- it; > in (upper tail), implies Ho: u; - u; 5 us, or

mision Rule :

RejectHoift<-tanorift>taafortwo-tailedtestwithCF : witness/n

Reject Ho if t < 4,. for lower tail test with CF (confidence interval) : no i to Ss/n

Rejecthift>taforuppertailtestwithCF(confidenceinterval):littlest/n

To compare the characteristics of rural and urban areas, this study uses the t-test for
two independent samples because the two population variances are not known. If the

variances of the two populations are the same, sample variance 1 and sample variance 2

68
_ (nl—l)s,2+(n1-—1)s22

 

are combined using pooled variance, Si, , with degree of fieedom

 

(nl—anZ—I)
(df) of n + n l and t statistic of t ‘ fi- 75 In these uations X refers to
l 2 Sle/nl+1/n2 ' eq ’ 1

sample 1 with number of sample n, and X refers to sample 2 with number of sample n;

__ X'
andthemeanoinscalculatedbe= 2" '.

 

If the variances of the two populations are not the same, the t statistic used to test the

 

it"i-Yi
h thesis is t = . The d ee of fi'eedom for this case is
we Jsf/nnsf/nz egr
(S,2 /n1+S,2 /n2

 

df: (S ,2 lnl)2 /(rr1—1)+(S22 /n2)2 /(n2-l) °

IV. URBANIZATION AND ITS CAUSAL FACTORS

This chapter describes the urbanization and its underlying causal factors in the
Northern Coastal Region of West Java (NCR). The level of urbanization is described on
the basis of the rural-urban classification described in Section 2.1.1 followed by the
analysis of the rate of change in population density or the level of urbanization. In the
analysis of urbanization process, regional pull and push factors are described in detail such
that specific factors affecting the urbanization process can be identified.

To analyze the urbanization process, the study treats the NCR as a single entity
without disaggregating the region into administrative unit of kabupatens or into several
agro-ecological zones. The NCR can be treated as a single entity since all four kabupatens
in the region, according to Firman (1992) and Soemarwoto et al. (1991), have similar
agricultural development problems afl‘ected by urbanization. In addition, at the Jakarta-
West Java regional level, the NCR can be categorized as one agro—ecological zone since
the existence of irrigated lands used for rice cultivation is ubiquitous in the region
(Soemarwoto, 1992), the region consists of similar types of farm management (Erwidodo,
1990), the area is composed of alluvial lowlands (Ongkosongo, 1979), and there are no
significant regional differences in rainfall and temperature with an average yearly rainfall of
about 1880 mm and a temperature range from 27.1 to 29.7 °Celsius (Ongkosongo, 1979;
Ilahude, 1979). Nevertheless, in determining the spatial rate of change in population
density,thisstudyuseskabupatenasabasisofanalysissincethecapitalcityofeach

kabupatenintheNCRisusedasacenterofdevelopmentinthekabupaten.

69

70
4.1. Urbanization in the NCR

Similar to Indonesia's Central Bureau of Statistics (CBS), this study defines
urbanization at the village level (see Section 2.1.1). However, the criteria used to classify
rural and urban villages are difi‘erent fiom the CBS's. This section starts with describing
the process of rural-urban classification followed by the analysis of the level of
urbanization. In the latter analysis, rates of urbanization of urban villages and urban
populations are presented and compared. Finally, this section presents results in the form

of both temporal and spatial rate of change of the population densities.

4.1.1. Windy.
Urbanization in Indonesia is defined at the desa or village level by categorizing the

villages into rural villages and urban villages (Hamer et al., 1986; Firman, 1992). Number
of urban population is defined as the population in the villages categorized as urban. This
study uses the same method but a difl‘erent criterion to classify the rural and urban villages
of the study area.

Several criteria can be used to define urbanization and classify rural and urban areas.
The first is the level of regional economic progress which is commonly approached by
classifying the aggregate measures of the state of economic progress of the region
(Williams et al., 1983). The second is land rent such as applied in the Schmid's (1968) and
Thrall's (1987) study in land conversion fi'om rural to urban uses. The third is population
density which is also a very common measure used to classify rural and urban areas

(Goldberg and Chinloy, 1984; Firman, 1992; Sharbatoghlie, 1991; Hamer et al., 1986;

71
Sutton, 1989; Obudho and Waller, 1976). Finally, the combination of two or more criteria

(Williams et al., 1983; CBS, 1988)

Indonesia's Central Bureau of Statistics (1988) adopts the forth criteria. It classifies a
village as an urban village if population density excwds 5,000 people/kmz, a less than and
equal to 25 percent of agricultural households, and more than and equal to eight urban
facilities” . Although the Central Bureau of Statistics uses multiple criteria, there are very
strong critics in defining the criteria. According to Rietveld (1988), all of the criteria used
to define urban village in Indonesia are very arbitrarily determined. Agricultural
household, for example, is defined as the main job of the head of household while in the
reality there is more than one working household member. The presence of an urban
facility in the village is determined without considering its quality; and more importantly,
there is a characteristic of the village which has no significance contribution in determining
the degree of urbanization such as the existence of an elementary school in the village. In
Java, the elementary school, especially the public elementary school, is present in each
village since the Government through President Instruction has determined each village
should at least have one elementary school. Firman (1992; p. 97) has criticized this
approach by stating that ”these criteria are difiicult to apply because of inconsistency in
result between them".

Difl‘erent from Central Bureau of Statistics (1988) and Firman (1992), this study uses

population density as a single criterion to classify rural and urban areas in the NCR.

 

2"Facilities cmsidered as urban facilities include prirmry school of equivalent, seemxiary school or equivalent, high
school or equivalent, theater, hospital, maternity center, clinic, hardened or paved road, telephrme/post office, market
with permmt building, showing center, bank, factory, restaurrnrt, public electricity, and party-equipment renting

servrce.

72

Reasons to choose this single indicator are : (i) there are no comprehensive measures of
economic progress available at the village level; (ii) there is no formal record nor
comprehensive study about land rent in the NCR that can be used as a basis of the
classification; (iii) population and total area data are well documented in the village level
through lO-year national census so that population density for each village can be derived;
and (iv) there is no complete record of census data of 1980 beyond the data of population
and total area that can be accessed by this study in the Central Bureau of Statistics, Jakarta
and in the Ofice of Statistics both in the kabupatens and in the province. Because of the
forth reason, this study cannot use the Central Bureau of Statistics' criteria since the
complete census data of 1990 cannot be compared with the incomplete census data of

1980.

4.1.2. MW!

This study uses village's population density of 1,500 people/km2 as a cut off to
difi‘erentiate between rural and urban villages in the NCR In other words, villages with
population density of more than 1,500 people/1cm2 are classified as urban villages while
those with less than or equal to 1,500 people/1cm2 are classified as rural villages.

This study finds that the use of CBS's criterion of 5,000 people/km2 results in very
small number of urban villages in the NCR. The analysis shows that from total of 1099
villages in the NCR there are only 18 villages that can be categorized as urban villages in
1980 which increased to 37 villages in 1990. This represents only 1.64 percent of all

villages in 1980 and only 3.37 percent ofall villages in 1990. Table l and Figure 3 present

73
the comparisons of the number of villages categorized as rural and urban areas based on

the village's population density of 5,000 people/km2 in 1980 and 1990.

Table 1. Number of Villages in the Northern Coastal Region of West Java (NCR) by
Population Density Interval in 1980 and 1990.

 

 

 

 

 

 

 

 

 

 

 

Area Pop. Density Nu’mber of Villages Percent of Villages
(people/m2) 1980 1990 1980 1990

R1 5 1,000 760 635 69.15 57.78
R2 1,001-2,000 246 55 22.38 5.00
R3 2,001-3,000 47 325 4.28 29.57
R4 3,001-4,000 18 19 1.64 1.73
R5 4,001-5,000 10 28 0.91 2.55
RURAL 5 5,000 1081 1062 98.36 96.63
U1 5,001-6,000 6 9 0.55 0.82
U2 6,001-7,000 5 5 0.46 0.46
U3 7,001-8,000 1 4 0.09 0.36
U4 8,001-9,000 2 6 0.18 0.55
U5 9,001-10,000 1 5 0.09 0.46
U6 2 10,000 3 8 0.27 0.72
URBAN > 5,000 18 37 1.64 3.37

NCR 1099 1099 100.00 100.00

 

 

 

 

 

 

SourcesofData:1980andl990PopdafionCensusesisswdbyCennalBurenuofStatistiesJakanaand
theOfiicesofStafisficsofKahmatensBekasi,meang,Subang,andIndramyu.

 

   

Nunberolwm
“ a
o
o

 
 

reflfagenumberabl
vmagonrrm berso >

 

”'6 0'5 ' ' ' -
m
U4 U3 U2 U1 RS R4
33 R2 R1
Subregtone (U :Urben; R :Rurat)

 

 

 

Figure 3. Distribution of the Villages in the NCR based on the Village's Population
Density (Source : Table I)

74
The data (Table 1; Figure 3) show that the use of village's population density of 5,000

people/km2 as threshold to differentiate rural and urban areas contradicts with the
assertion that the NCR is the most urbanized and industrialized region in Java
(Soemarwoto, 1992; Firman, 1992; Hamer et al., 1986; Hill, 1992b) since the result of the
analysis shows that there is only very small portion of the NCR that can be categorized as
urban villages. Hamel er al. (1986; p. 14), for example, calculated that 21.00 percent of
the urban population in West Java (1980) was mostly concentrated in the NCR (Firman,
1992). Since urban population in Indonesia is calculated based on urban villages, the high
urban population must reflect the high number of urban villages. The result will be much
lower if the other two CBS's criteria—agricultural households and urban facilities—are
included in the analysis. Therefore, adoption of the CBS's criteria implies that there is a
very low urbanization in the NCR and, comparatively, much lower in other regions in
Java; and, it does not reflect the reality of urbanization in the NCR. In addition, Figure 3
shows that village's population density of 5,000 people/inn2 is not the best threshold to
difl‘erentiate between rural and urban villages in the NCR since it does not depict a clear
distinction of grouping between rural and urban villages.

This study suggests a cutting point of 1,500 people/1cm2 to difl‘erentiate rural and
urban villages. Using this level of population density, the level of urbanization and
urbanization process in the NCR is better represented. The results of the analysis of the
level of urbanization in the NCR are presented in the Tables 2 , Table 3, Figures 4, and

Figure 5.

75
Table 2. Number of Rural and Urban Villages in the NCR in 1980 and 1990 (Classified
based on the Village's Population Density of 1,500 people/km2 as a Cut Off to
Differentiate Rural and Urban Village)

 

 

 

 

 

 

 

 

 

Area Pop. Density Number of Villages Percent of Villages
(people/kmz) 1980 1990 1980 1990
R1 _<_ 375 194 91 17.65 8.25
R2 376-750 368 317 33.48 28.84
R3 751-1125 247 321 22.47 29.21
R4 l,126-1,500 139 147 12.65 13.38
RURAL g 1,500 948 876 86.25 79.71
U1 1,501-1,875 48 69 4.37 6.28
U2 1,876-2,250 27 34 2.46 3.09
U3 2,251-2626 16 21 1.46 1.91
U4 _>_ 2,626 60 99 5.46 9.01
URBAN > 1,500 151 223 13.75 20.29
NCR 1099 1099 100.00 100.00

 

 

 

 

 

 

SourcesofData:1980and1990PoprdationCensusesissuedbyCenflalBrnemrofStafistichakaflaand
the Offices of Statisties of Kabupaten Bekasi, Karawang, Subang, andlndramayu.

 

  
   

Number of Village.
N
o
o

’ “vying-nan} aorta.
vmgenum boron

 

UI R4 R3

Subreglona (151-4 2 Urban; R'l—4 : Rural) .

 

 

Figure 4. Distribution of Rural and Urban Villages in the North Coastal Region of West
Java in 1980 and 1990 Based on the Village's Population Density of 1,500
people/km2 as a Cut Ofl‘ to Difi‘erentiate Rural and Urban Villages (Source :
Table 2)

 

76

 

 

 

 

 

 

 

 

 

 

Table 3. Changing Composition of Rural and Urban Population in the NCR in 1980 and
1990
Area Pop. Density Total Po lulation Percent of Population
(people/kmz) 1980 1990 1980 1990
R1 5 375 443,004 300,792 9.65 4.78
R2 376-750 1,234,220 1,273,079 26.89 20.22
R3 751-1125 1,058,788 1,487,116 23.07 23.62
R4 1,126—1,500 674,900 795,385 14.70 12.63
RURAL 5 1,500 3,410,912 3,856,372 74.31 61.25
U1 1,501-1,875 285,916 410,672 6.23 6.52
U2 1,876-2,250 162,206 203,129 3.53 3.23
U3 2,251-2626 144,922 175,681 3. 16 2.79
U4 _>_ 2,626 586,318 1,650,514 12.77 26.21
URBAN > 1,500 1,179,362 2,439,996 25.69 38.75
NCR 4,590,274 6,296,368 100.00 100.00

 

 

 

 

 

 

 

Sources of Data : 1980 and 1990 Population Censuses issued by Central Bureau of Statistics, Jakarta and
the Offices of Statistics of Kabupatens Bekasi, Karawang, Subang, and lndramayu.

 

Total Population

1000000
1000000
1400000
1200000
1000000
800000
000000
400000
200000

   
      

parathion-90

population-'80
R4 R3

R2 R1

Sub-regions (U14 :Urhan; R1-4 :Raral)

 

Figure 5.

Total Population in Each Sub-region in the NCR for 1980 and 1990 (Source :
Table 3)

 

77
The level of rural and urban villages in the NCR in 1980 and 1990 are summarized in

Table 2 and Figure 4. Rural and urban areas are subdivided fiirther into four sub-regions
(RI-4 and U1-4) based on the difl‘erence of the village's population density of 375
people/km? Sub-regions R1-4 to Ul-4 indicate the degree of urbanization fi'om the most
rural area (R1) into the most urbanized area (U4). The level of rural and urban populations
in 1980 and 1990 and the level of population in each sub—region of the rural and urban
areas are summarized in Table 3 and Figure 5.

Compared to Figure 3, Figure 4 shows village's population density of 1,500
people/km2 provides a clear difl‘erentiation between rural and urban villages in the NCR.
This classification represents the best result among other alternatives that have been
considered in this study.

Table 2 shows that there are 151 urban villages (13.74 percent) in 1980 and increases
to 223 urban villages (20.29 percent) in 1990. This means that average village
urbanization rate in the NCR between 1980 and 1990 is 47.67 percent or 4.77 percent per
year. Table 3 and Figure 5, on the other hand, show that urban population in the NCR
increases from 1,179,362 people (25.69 percent) in 1980 to 2,439,996 people (38.75
percent) in 1990. The average urban population rate between 1980 and 1990 is 106.89
percent or 10.69 percent per year. This result shows that the level of urban population in
the NCR at 25.69 percent in 1980 is higher than that of the level of urban population in
West Java of 21.00 percent such as calculated by Hamer et al. (1986). This result is

expected since the urbanization process in West Java is more concentrated in the NCR

(Firman, 1992).

78
There are differences between urban village growth and urban population growth in

the NCR between 1980 and 1990. In this period, urban population in the NCR increased
by 10.69 percent per year while the urban villages increases by 4.77 percent per year.
This implies that urban population grth in the NCR is determined not only by the
increase of urban villages or changing status of the rural villages into the urban villages but
also by other factors such as changing demographic factors, rural and urban development,
industrialization, and other factors. According to Hamer et al. (1986; pp. iii and 1), ”this
grth is the outcome of millions individual household and business decisions". The
detailed factors affecting urbanization process in the NCR are described in Section 4.2.
Table 2 also shows that the number of villages with a population density of less than
or equal to 375 people/kin2 has decreased significantly fi'om 194 villages (17.65 percent)
in 1980 to 91 villages (8.28 percent) in 1990, a decrease by 53.09 percent or 5.309
percent per year. This decrease also occurred in the sub-region with a population density
of 376-750 people/km2 for which the number of villages has decreased fi'om 368 villages
(33.48 percent) in 1980 to 317 villages (28.84 percent) in 1990. In these sub-regions the
number ofthe villages has decreased by 13.86 percent between 1980 and 1990 or 1.386
percent per year. On the other hand, in the other sub-regions the number of the villages
have increased between 0.576 and 6.500 percent per year in the period of 1980-1990.
These figures show that the number of villages in the NCR with population density of
more than 750 people/km2 have increased in the period of 1980-1990. Among these
regions, the urban areas represents a higher increase as compared to rural areas. Among

the urban areas, the most populous sub-region of urban area (U4) has the highest increase

79
at 65 percent over ten years or 6.50 percent per year in the period of 1980-1990. This

implies that the highest urbanization rate occurs ill the region with highest population
density, an indication of an agglomerative effect of urban population (Bhadra and
Brandao, 1993).

Table 3, on the other hand, shows that between 1980 and 1990 the proportion of
rural population has decreased in all sub-regions of the rural area while the proportion of
urban population has increased, especially in the urban hinge and in the most populous
sub-regions of the urban areas. These figures also imply that an increase in urban
population occurs mostly in the areas characterized by previously higher population

density.

“-3- MW

The rate of change in population density can be used as an indicator of the
concentration of population over time and space. In this study, the temporal rate of
change in the population density (TRCPD) is considered as an indicator of the degree of
urbanization process over a period of time since urban and rural areas are difl‘erentiated by
population density. And, spatial rate of change in population density (SRCPD) indicates
the spatial difl‘erences in the degree of urbanization fi'om capital city of kabupaten to the

countryside.

41.3.1. W
In this study, temporal rate of change in population density (TRCPD) is defined as the

change of the NCR's population density over the period 1980-1990, and is expressed as

80
people/kmzlyear. It is calculated using equation 1, described in Section 3.3.2.1. The

results of the analysis are presented in Table 4, Table 5, and Figure 6. Table 4 presents
the means of rate of change in population density between 1980 and 1990 (TRCPD) in
rural and urban areas as well as in each sub-regions in the NCR. These means are plotted
in Figure 6 so that the patterns of TRCPD fi'om the most urbanized region (U4) to the
most rural region (R1) can be easily seen. Table 5 presents the result of the analysis of
variance (Anova) of the means of the TRCPD in the NCR It also presents the result of
the analysis of mean comparison of the TRCPD in each sub—regions in the NCR using
Least-significant Difi'erent (LSD) tests of the Multiple Range Tests.

Both Table 4 and Figure 6 show that the TRCPD in the NCR is positive between
1980 and 1990. This indicates that population density increased throughout the region.
However, the increase of population density is not evenly distributed between rural and
urban areas and among the sub-regions in rural and urban areas. The TRCPD decreases
from the most urbanized area (U4) to the most niral area (RI). The mean ofTRCPD of
urban area is 115.5708 people/km2/year and that in rural area is 12.7631 people/ka/year.
Statistically, the mean of TRCPD of urban area is very significantly difl‘erent from that of
rural area with confidence level of 99 percent (a = 0.01). The yearly increase of the
population density in the urban area is 9.01 times of that in rural area. Therefore, it can be
interpreted that urbanization in the NCR during the period 1980-1990 increased mostly in
areas with higher population densities. This substantiates the assertion by Henderson
(197 7) that an the accumulation or movement of population in high density (core) regions

occurs through a self-reinforcing process.

 

81

Table 4. Mean of Rate of Change in Population Density between 1980 and 1990
(TRCPD) in the North Coastal Region of West Java (NCR).

 

 

 

 

 

 

 

 

 

 

Area Population Density Annual Rate of Change in Population
(people/kmz) Density (people/kmz/year)
R1 5 375 5.1043
R2 376-750 9.8172
R3 751-1125 14.5185
R4 1,126-1,500 20.0236
RURAL 5 1,500 12.7631
U1 1,501-l,875 19.4939
U2 1,876-2,250 36.5776
U3 2,251-2626 61.0957
U4 22,626 221.2178
URBAN > 1,500 115.5708
NCR 33.6240
SourcesofData: 1980 and 1990 PopulationCensuses issuedbyCentralBurmuofStatisties, Jakartaand

the Offices of Statistics of Kahlpatens Bekasi, Karawang, Subang, and lndramayu.

 

   

rtehange-popdens

Sub-regions (U14 : Urban; R1-4:
Rural)

 

 

 

Figure 6. Mean of Rate of Change in Population Density between 1980 and 1990 in Each
of Sub-regions of the NCR (Source : Table 4).

The accelerated growth of population density over time is further substantiated by

comparing the means of TRCPD among sub-regions in the NCR (Table 5). The analysis

82
shows that TRCPD is the highest in the most urbanized area (U4) at 221.2178

people/km2/year and lowest in the most rural area (R1) at 5.1043 people/ka/year (see
also Table 4).
Table 5. Mean Comparison of the Temporal Rate of Change in Population Density

(TRCPD) among Sub-regions in the NCR using One Way Anova and Least-
significant Different (LSD) Multiple Range Tests

 

 

 

Analysis of Variance (ANOVA)

Source D.F. Sum of Squares Mean Squares F-ratio F-prob.
Among Sub-regions 7 391191667 558845.24 43.33 0.00
Within Region 1091 1407154023 12897.84
Total 1098 1799345690

 

 

 

 

 

 

Multiple Range Tests: LSD Tests with a (a = 0.01; b = 0.05; c = 0.10)

 

 

 

Sub-regions R1 R2 R3 R4 U1 U2 U3 U4
R1 -
R2 -
R3 -
R4 c c -
U1 0 c -
U2 c c c -
U3 b b b b b c -
U4 a a a a a a a -

 

 

 

 

 

 

 

 

 

SourcesofData:1980andl990PopdadonCensuwsisamdbyC‘ennaleeauomefinichakanamd
meOflicesomefisticsofKahipatenBekasLKamwangSubangandlndramayu.

Further analysis using One Way Analysis of Variance (Anova) and Least-significant
Different (LSD) Multiple Range Tests show that very significant differences exist in the
means of TRCPD among sub-regions in the NCR (Table 5). Comparing rural and urban
areas, it seems that the TRCPD's in rural areas are relative consistemly low compared to
those in urban areas. In rural areas, only R4 with TRCPD of 20.0236 people/ka/year

has a higher TRCPD than that of the R1 and of the R2 which have TRCPD of 5.1043 and

 

83
9.8172 people/km2/year, respectively (confidence level of 90 percent or or = 0.10). On

the other hand, in urban areas, the U4 with TRCPD of 221 .2178 people/ka/year has very
significantly higher TRCPD than that of the U1-3 and of the R1-4 (confidence level of 99
percent or or = 0.01). The sub—region U3 with TRCPD of 61 .0957 people/ka/year has a
significantly higher TRCPD than that of U1 and R1-4 (or = 0.05) and also higher than that
of the U2 (or = 0.10). The sub-region U2 with TRCPD of 36.5776 people/km2/year has
higher 'I'RCPD than that of R1-3 (or = 0.10). Finally, sub-region U1 with a TRCPD of
19.4939 people/km2/year has a higher TRCPD than that of R1-2 (or = 0.10).

The existence of the self-reinforcing process of population density growth implies
that—assuming that spatial organization in the NCR is governed by spatial competition
(Mabogunje, 1981; Mehretu, 1989)—peop1e in the region prefer living in urban areas with
high population densities than in rural areas with low population densities. This may imply
that there exists a preference to locate in urban areas due to the perception of a higher
quality of life. This assertion will be visited again in the analysis of urbanization process

in the NCR (Section 4.2).

4.1.3.2. Warm
The spatial rate of change in population density (SRCPD) is defined as the spatial

difl‘erences in the degree of population concentration over distance from the center of the
region (Gould, 1972; Blair, 1991; Dicken and Lloyd, 1990; Rees, 1970). In this study,
SRCPD indicates the spatial differences in the degree of urbanization process from capital
city of kabupaten to the countryside. SRCPD is calculated by using a general decay

function model, a simple negative exponential function described in Section 3 .3 .2.2.

84
This study assumes that the model—which is successfully applied in the developed

countries (Haggett, Clifl', and Frey, 1977; Mehretu, 1989) to predict the decay of
population density from the city center to the countryside—also applies in the NCR. Since
there is no specific city in the NCR that can be referred as a center of the whole region of
the NCR” , this study uses each capital city of the four kabupatens in the NCR as a city
center. Consequently, the analysis of the SRCPD is conducted in each kabupaten in the
NCR and the regional analysis of the SRCPD in the NCR is conducted by assigning
average distance of the village to its capital city of kabupaten.

This research addresses the value of b in each kabupaten and in the whole region. In
predicting such parameters, the equation is transformed into a linear model. Using the
Least Square Method or the Least Square Estimators (Neter and Wasserman, 1974;
Johnston, 1991; Barber, 1988; Runyon and Haber, 1980; Ott, 1988), the value of b, In Do,
and E can be determined by using equation 4, 5, and 6 described in the Section 3.3.2.2.
The results of the analysis are presented in Table 6 and Figure 7. Table 6 presents the
value of b, In Do, and E along with the statistical measures related to the linear model such
as the strength of linear association (r, linear correlation), measure of goodness of fit of
the regression model (r’, coefl'lcient of determination), significant testing of the strength of
the variable relationships (Snedector's F-ratio). Figure 7 presents the result of the linear
relationship between natural log of village's population density and the distance from the
capital city of kabupaten. The figure plots only the positive value of the natural log of the

village's population density by assigning numbers to the regression equations.

 

”ThereisnobigcityintheNCRalthmighthisregimislocatedbetweentwbofthebiggestcifiesmlndonesia,
JakartaandCirebon However,fluencatleastfourunaflercifiesintheNCRwhichalsohappaiasthecapital
citieeofthefourkabupntalsintheNCR.

85

Table 6. Rate of Change in Population Density (b) Over Distance (SRCPD) from the
Capital City of Kabupaten Predicted using Linear Model with Least Square

 

 

 

Method
LinearModel : lan=1nDo -bX:E
NCR Bekasi Karawang Subang Indrama
b 0.044077 0.044255 0.048547 0.043955 0.041708
In Do 1.867912 1.815106 1.807865 1.904647 1.888894
r 0.872140 0.846900 0.892590 0.915010 0.861320

0.760620 0.717240 0.796720 0.837240 0.741870
Adjusted 72 0.760400 0.716040 0.796040 0.836580 0.741030
E 0.395100 0.482440 0.322270 0.286890 0.444110
F-statistic 3485.715 596.0956 1 175.795 1275.720 885.1787
LSig. level29 0.0000 0.0000 0.0000 0.0000 0.000

 

 

 

 

 

 

 

 

SourwsofData:1980and19901bpdafionCmmsesissuedbyCennaanreauomefistichakamand
theOfficesofShfisticsofKahrpatenBekasi,Kamwang,Subangandmdramayu.

 

Ln (population density, peopldka)

 

 

0.00 . . t . . . 4 .
o 5 10 15 20 25 30 :15 40
Distance from Capital City of Kabupatcn (km)

 

 

 

 

Figure 7. Distance Decay Function of the Population Density from the Capital City of
Kabupatens of Bekasi, Karawang, Subang, and lndramayu, and in the NCR in
1990 (Source : Table 6).

 

2”Ii-test with significant level of or = 0.0000 means that the regression model is fitted with confidence
level of more than 99 percent

86
All statistical measures used ill this analysis show that the model fits the situation in

the region, including all kabupatens. The values of linear correlation (r) in all regions are
very high with the values between 0.85 and 0.92, indicating a very strong predictive
relationship between village's population density and the distance from the capital city of
kabupaten. Furthermore, F-tests show that the relationships between village's population
density and the distance from the capital city of kabupaten in all regions is very
significantly strong with confidence level of more than 99 percent (see footnote 3). The
values of the coefl'lcient of determination (12) are also very high in all regions with the
values between 0.72 and 0.84. These indicate that the distance from the capital city of
kabupaten explains 72 to 84 percent of the variance of the village's population density in
the study area.

However, the values of the expected result—b or the SRCPD—are very low in all
regions with values of 0.0441, 0.0443, 0.0485, 0.0440, and 0.0417 for the NCR, Bekasi,
Karawang, Subang, and lndramayu, respectively. This means that in Bekasi, for example,
for each kilometer farther from the capital city of kabupaten the population density
declines by 0.0443 people per square kilometer. This implies that there is no significant
difl‘erentiation in the population density over distance from the capital city of kabupaten.
Therefore, the rank size rule may not be the probable distribution of population in the
NCR. In other words, such as found by Mehretu (1983) in his study of Cities of Sub-
saharan Afiica, the simple negative exponential function, which has been very successful

model for the developed countries, is not representative for the NCR.

87
Beyond the statistical reliability of the model, the actual value of the natural log of

village's population density is plotted against its predicted value derived from the analysis
(Figure 8). This plot shows whether the model is over or under estimate the actual value

of the village's population density.

 

+-+—-'

    

Predicted value Mpopuletlon density). ppllka]

LbbLo—Nunuouaoa

 

 

 

 

Figure 8. The Relationship between the Actual Values of the natural Log of Village's
Population Density and Its Predicted Values Derived from the Analysis.

The 45°-line in the Figure 8 indicates a perfect model of prediction. If the model has

a good prediction capability, the actual values of the natural log of the village's population

density will be scattered around the line. In fact, in this study, the actual values of the

natural log of the village's population density are concentrated below the line. It indicates

that the model provides an over estimation of actual values and also indicates that the

model does not represent the condition in the region.

88
4.2. The Urbanization Process in the NCR

This section describes the urbanization process and its underlying causal factors in the
NCR between 1982 and 1992. Instead of using census data for 1980 and 1990, the study
uses the primary survey data for years of 1982 and 1992 to analyze the urbanization
process in the region. The primary survey data cover a wide range of information related
to rural and urban characteristics affecting urbanization. These data are not included in

the census.

42.1. W
The level of urban population is defined as the population in the urban areas consisting

of the villages with population density of more than 1,500 people/km? The rate of change
of the village's population density, consequently, indicates the process of urbanization and
is used, in this study, as its indicator.

Urbanization according to Hamer et a1. (1986) is determined by a complex set of
individual household and business decisions. According to pull and push factor theory of
tn'banization (Sovani, 1964; Choe 1981), regional factors afl‘ecting urbanization are
grouped into ntral and urban factors. Rural factors are related to the agricultural and rural
conditions which force population to migrate or ”concentrate” to urban areas. Urban
factors are those urban conditions which draw people to migrate or ”concentrate” to urban
areas. In the literature of urbanization (see Chapter II), rural factors are commonly
referred to as push factors and urban factors are identified as pull factors. However, there
is also other factor that cannot be categorized as one of the groups such as demographic

factor which naturally occurs both in the rural and urban areas.

89

Since the time dimension is a critical variable in the urbanization process, the study
investigated annual rates of change of all factors expected to affect urbanization, including
push and pull factors. As in Section 4.1.3.1., the rate of change for all the factors in this
analysis is calculated using equation 1 (Section 3.3.2.1.).

According to pull and push theory (see Chapter II), urbanization is a firnction of push
factors fiom agricultural rural area and pull factors of urban area. Therefore, the annual
rate of change in regional population density is a function of the annual rate of change in
the push factors, the annual rate of change in the pull factors, and the annual rate of
change related to demographic factors. This relationship is investigated in this study using
a linear multiple regression model (Section 3.3.2.3.) to identify specific causal factors
affecting urbanization. The process uses stepwise multiple regression instead of
simultaneously multiple regression to identify a multivariate equation with factors that
represent critical causal of urbanization (Johnston, 1991).

The factors that are expected to affect regional urbanization are summarized in
Table 7. The rural push factors expected to afi‘ect urbanization (X;) are the regional
changes in land tenure and the regional cimnges in the agricultural economy between 1982
and 1992. The regional changes in land tenure include the accelerated agricultural land
parcelization, the increase in the absentee agricultural land ownership, and the increase in

agricultural land conversion. The regional changes in agricultural economy include the

90

Table 7. List of Causal Factors Expected to Afi‘ect Regional Urbanization (The indicators
and the identified variables [stated in their annual rate of change] were
determined prior to conducting Linear Multiple Regression Analysis).

 

 

 

 

 

 

   
   

 

   
    
   
  
   

 

 

 

 

Factors Indicators Identified Variables (Stated as Their Annual
Rate of Cha_nge)
Rural/Push W in Land Te_r_r_n_re:
(X0 1. Agricultural land parcelization . X1, Households without dryland (%)
(X1 -10) I . X2, HOIISChOI$ mm paddyland (%)
k. x3. Households with < 0.5 ha dryland (%)
Kl X4, Households with < 0.5 ha paddyland (%)
. X5, Households with 0.5-1.0 ha dryland (%)
f. X6, Households with 0.5-1.0 ha paddyland (%)
g. X7, Households with >1 .0-2.0 ha dryland (%)
Lh. x,, Households with >r.o-2.o ha paddyland (%)
i. X9, Households with > 2 ha dryland (%)
j. X10, Households with > 2 ha paddyland (%)
L2. Absentee land ownership (Xl 1-12): .X“, land owned by absentee landlords (ha)
F. X”, Number ofabsentec landlords per 1000 village
population
3. Agricultural land conversion . X”, Agricultural land (%)
(X1344) I F X14. WW (%)
WW:
“I. Agricultural labor wage rate (X15): Ia. X15, Agricultural labor wage rate during the
Plowing Period (Rp.)
5. Agricultural land price (X16) : . X16, Average agricultural land price (Rpmillion)
6. Village employment structure . X17, Ayicultural labor (%)
(xi-1-22) 3 - X18, TOW farmer (%)
. X19, Sakap / sharecroppers (%)
X20, Small scale enterprise (%)
. X21, Small scale industry (%)
. X22, Informal sector (%)
Urban/Pull 1. Degree of Industrial development . Y1, Number of large scale industries
(Y) in 1,000 village population (Y I .3) : . Y2, Number of medium scale industries
. Y3, Number of small scale industries
2. Availability of public facilities a. Y., Number of clinics per 1,000 village population
(Ya): .Ys, Number ofbanksper 1,000 village population
. Y6, Number of public transportation (vehicles per
1000 village population) .
Y7, Length ofpavedruads (km per 1,000 village
population)
3. Availability of pre-college . Y3, Number of kindergarten
erhrcational facilities per 1,000 . Yo, Number of elementary school
villagepopulatioMYm): .Ym, Numberofsecondary school
Y“, NW 011 h1g1! SChOOl
Demographicl. Populationgrowth(Z,): ZhPopulationgrowthinthevillage
(gt) 2. Migrgtion (Z2) : a. 24, Net migration in the village
Una-moon} Rate of change in the village's Rate of change in the village's population density
Prone-I (UP) population density (Um (UP)

 

 

 

91
decrease of real agricultural labor wage rate, the increase of agricultural land prices, and

the changes in the structure of village employment. These factors combined likely affect
urbanization due to migratory pressure on rural population's decreased economic
opportunities in rural areas.

The selected variables for agricultural land parcelization determined prior to linear
multiple regression analysis are :

1. X1 : the annual rate of change in the percentage of household without agricultural
dryland,

2. X2 : the annual rate of change in the percentage of household without paddyland,

3. X3 : the annual rate of change in the percentage of household with less than 0.5 ha

agricultural dryland,

4. X4 : the annual rate of change in the percentage of household with less than 0.5 ha
paddyland,

5. X5 : the annual rate of change in the percentage of household with 0.5-1.0 ha
agricultural dryland,

6. X5 : the annual rate ofchange in the percentage ofhousehold with 0.5-1.0 ha paddy-
land,

7. X1 : the annual rate of change in the percentage of household with more than 1020
ha agricultural dryland,

8. X3 : the annual rate of change in the percentage of household with more than 1.0-2.0
ha paddyland,

9. X9 : the annual rate of change in the percentage of household with more than 2.0 ha
agricultural dryland, and

10. X10: the annual rate of change in the percentage of household with more than 2.0 ha
paddyland.

92
Selected variables on absentee land ownership determined prior to linear multiple

regression analysis are :

1 l. X": the annual rate of change in the percentage of land owned by absentee landlords,
and .

12. X12: the armual rate of change in the number of absentee landlords per 1,000 village
population.
Selected variables on agricultural land conversion determined prior to linear multiple
regression analysis are :

13. X13: the annual rate of change in the percentage of total agricultural land converted
into non-agricultural uses, and

14. X“: the annual rate of change in the percentage of paddyland converted into non-
agricultural uses.
The variable on agricultural labor wage rate determined prior to linear multiple
regression analysis is :

15. X15: the annual rate of change in the average agricultural labor wage rate during the
plowing period (Rp./year).

The variable on agricultural land prices determined prior to linear multiple regression
analysis is :
16. X16: the annual rate of change in the average agricultural land prices
(Rp. million/year).
Selected variables on the structure of village employment determined prior to the
linear multiple regression analysis are :
l7. X17: the annual rate of change in the percentage of the agricultural labor,

18. X“: the annual rate of change in the percentage of the total farmer,

93
19. Xno: the annual rate of change in the percentage of the sharecroppers,

20. X20: the annual rate of change in the percentage of the population working in small
scale enterprises,

21. X2; : the annual rate of change in the percentage of the population working in small
scale industries, and

22. X22: the annual rate of change in the percentage of the population working in the
informal sector.

The pull factors of urban areas (Yj) expected to afi‘ect urbanization are the degree of
industrial development, the availability of public facilities, and the availability of pre-
college educational facilities. These were the three identified principal pull factors which
would likely draw population towards urban areas to realize economic opportunities.

Selected variables on the degree of industrial development determined prior to linear

multiple regression analysis are :

1. Y; : the annual rate of change in the number of large scale industries per 1,000 village
Population,

2. Y2 : the annual rate ofchange in the number ofmedium scale industries per 1,000
village population, and

3. Y3 : the annual rate of change in the number of small scale industries per 1,000
village population,

Selected variables on the availability of public facilities determined prior to linear
multiple regression analysis are :
4. Y4 : the annual rate of change in the number of clinics per 1,000 village's population,

5. Y5 : the annual rate of change in the number of bank per 1,000 village's population,

94

6. Y6 : the annual rate of change in the number of the public transportation (vehicles per
1,000 village population), and

7. Y7 : the annual rate of change in the length of the paved road (km per 1,000 village
population).
The selected variables on the availability of pre-college educational facilities

determined prior to linear multiple regression analysis are :

8. Y3 : the annual rate of change in the number of kindergarten per 1,000 village
poolllation.

9. Yo : the annual rate of change in the number of elementary school per 1,000 village
population,

10. Ylo: the annual rate ofchange in the number ofsecondary school per 1,000 village
population, and

l 1. Y“: the annual rate of change in the number of high school per 1,000 village
population,

In addition, total village population increase, expected to affect urbanization, due to
population growth and migration is identified. This increase cannot attributed to push
factors nor pull factors. Therefore the factors afi‘ecting such an increase is treated
separately md are, in this study, identified as demographic factors (Zk).

The variable selected for population growth prior to linear multiple regression analysis
is :

1. Z, : the village population growth.

The variable selected for migration prior to linear multiple regression analysis is :

2. Z2 : the rate of change in the village net migration.

95
Therefore, the relationship between urbanization, defined as the rate of change in

village population density, and factors that affect the process of urbanization (UP) can be

statedas:

22 11 2
UP=f(ZXi,ZYj,ZZ/r)
i=1 i=1

Fl

Where : UP is the degree of regional urbanization
22
Z Xi are push factors
i=1

11
Zl’j are pull factors

Fl

2
22]: are demographic factors

k=l
This mathematical relationship is investigated using a linear multivariate model. Since
multivariate regression is conducted using a stepwise method, final results will not include

all identified variables. Final results are presented in the next section.

4.12. W

Before presenting the results of the linear multiple regression analysis of urbanization
process in the NCR, this section starts with presenting the magnitude of trends of all
variables investigated. The summary of trends of all the variables is presented in Table 8.
A positive sign of the mean rate of change of each variable represents the fact that the
variable has increased annually during the period of 1982-1992. On the other hand, a
negative sign of the mean rate of change represents that the magnitude of the variable has

decreased annually during the same period.

96

Table 8. Trends of Causal Factors Expected to Afi‘ect Regional Urbanization. Positive
and Negative Means of the Rate of Change for Each Variable Represents an
Increase or Decrease during the Period of 1982-1992

 

Factors Indicators Identified Variables (Stated as Their Trend
Annual Rate of Change)

 

 

Rural/Push :

(X1) 1. Agricultural land parcelization (X140) . X1, Households without dryland +
. X2, Households without paddyland +
. X3, Households with < 0.5 ha dryland -
. X4, Households with < 0.5 ha paddyland -
. X3, Households with 0.5-1.0 ha dryland -
. X6, Households with 0.5-1.0 ha paddyland -
. X1, Households with >1.0-2.0 ha dryland -
. Xs, Households with >1 .0-2.0 ha paddyland -
'. X9, Households with > 2 ha dryland -
'. X10, Households With > 2 ha paddyland -
.X11,landownedbyabaalteelandlords +
. X12, Number ofabsentee landlords +
. x13, Asricultmul land -

.XlaPaddyland .

2. Absentee land ownership (X1 l-12):
3. Agricultural land conversion (X1344) I

E. Agricultural labor wage rate (x51:

.X15,Agricultm'allaborwagerate

 

 

  
 

 

 

5. Agricultural land prices (X15) : . X16, Average agricultural land prices +
6. Village employment structure (X1142) I X11, Agricultural labor +
. X13, Farmer -
. X19, Sakap/sharecroppas +
. X20, Small scale enterprise +
. X11, Small 80816 industry +
. XE Informal sector +
Urban/Pull 1. Degree of industrial development . Y1, Number of large scale industries +
(Y1) (Ym) : . Y2, Number of medium scale industries +
. Y3, Number of small scale industries +
+
2. Availability of public facilities (Yul) : . Y4, Number of clinics +
. Y5, Number of banks +
. Y6, Number of public transportation +
Y1, Length of paved roads +
+
3. Availability of pie-college educational . Yo, Number of kindagarten +
facilities (You) : . Yo, Number of elementary school +

. Ylo, Number of secondary school

Yll, Number oh high school .

Demographic l.Populationgrowth(Zr): 21, Population growthinthevillage -
(A) LMigation (24) : Net migra_tion in the villagg +

Urbanhatloa Rate of change in the village’s population Rate of change in village's population density «1-
Process (UP) density (UP) (UP)

 

 

 

 

 

 

97
Table 8 shows that regional push factors from the agricultural rural area for the period

of 1982-1992 are characterized by the changes in land tenure and changes in the
agricultural economy. Changes in land tenure are characterized by an increase in
agricultural land parcelization or land disaggregation. Specifically, Table 8 shows that the
percentage of landless households has increased while all categories of both agricultural
drylands and paddylands have decreased. Moreover, it also shows that the hectarage of
total agricultural lands as well as paddylands have decreased, indicating agricultural land
conversion to other uses. These phenomena are reinforced by the facts that the number of
absentee landowners and the hectarage of lands owned by the absentee landowners in the
same period have increased in the NCR.

For the same period, changes in the agricultural economy are characterized by a
decrease in the real agricultural labor wage rates30 and an increase in the real value of
agricultural land prices31 .

Changes in the NCR's agricultural economy are also followed by changes in the
structure of village employment. The percentage of population working as agricultural
labors and the percentage of the sharecroppers have increased while the percentage of
farmers (agricultural land owners) has decreased for the same period. Non-agricultural
regional employment, on the other hand, has increased. This increase is characterized by
an increase in the percentage of population working in small scale enterprises, in small

scale industry, and in the informal sector.

 

1""l'hererrlrigriculttn'allrtborrtvngerateiscalculrltedbriaedontheaver'agevillage'swagerateintheplowingperiod
andconva'tingthe l982valueinto 1992 valueusinginflatiourateof9percent.
3‘rhetigtieultutttlitiiitlptioeisottleultttotituitionotithetlweiugepiioeorltuuliuiliettample villagesandthcvalueof
1982iseonvertedintothevalueOt‘l992byusinginflationrateof9percent

98
Table 8 also shows that regional pull factors in the period of 1982-1992 are

characterized by the increasing number of industries, public facilities, and pro-college
educational facilities. The increasing number of regional industries is characterized by
increases in the number of the large scale industries, medium scale industries, and small
industries for every 1,000 village population. The increasing number of regional public
facilities is characterized by increases in the number of clinics, bank, public transportation
(vehicles), and length of the paved road (km) for every 1,000 village population. The
increasing number of regional pre—college educational facilities is characterized by
increases in the number of kindergartens, elementary schools, secondary schools, and high
schools for every 1,000 village population.

Regional population growth 1992 is lower than that in 1982 while regional net
migration is higher in 1992 than that in 1982.

The next question is to determine which of the factors have caused an increase in the
rate of change in regional population densities. Specifically, which variables were the
principal causal factors in determining regional urbanization during 1982-1992.

To answer this question, all factors including push, pull, and demographic factors (see
Table 7 and 8) were regressed with the change in the village's population density, as the
dependent variable (Table 9). A multiple step-wise regression analysis was used and all
assumptions and requirements of the model (see Section 3.3.2.3) were satisfied in this

analysis.

99

Table 9. Causal Regional Urbanization Factors including T-tests Significant (Sig),
Standardized Partial Regression Coefficient (ll-Coefficient), and Degree of
Urbanization Process Explained by the Variance of Each Variable (Variance).

 

 

 

 

 

 

 

 

 

 

 

 

 

Factors Indicators Variables (Stated as Their Sig. B Variance
Annual Rate of Orange) (70}
Rival/Push Wurst (28.16%)
(45.40 %) 1. Agicultural land parcelization : X1, Households with zero dryland c 0.621 1.35
(7.16 %) sts, Households with < 0.5 ha
dryland a 1.299 1.73
in, Households with 0. 5-10 ha
paddyland c 0.454 1.31
on, Households with >1 .o-2.o ha
paddyland - -0. 163 2.47
X10. Households with > 2 ha
- -0. 101 0.30
2. Absentee land ownership: 9(11, Land owned by absaltee a 1.251 6.92
(8.62 %) landlords
Din, Ntuuber of absentee landlords b 0.310 1.70
3. Agricultin'al land conversion : X13, Agricultural land a 1.550 9.03
( 12.38 %) 2X14, Paddyland c 0.555 3.35
(17.24 %)
4. Agricultmallaborwagerate: x.,,Agticultuiallshoiwogetote c 0.173 2.12
(2.12%)
5. Agricultural landprices: Dru. Average agriculttnal landprices r .0273 4.97
(4.97 %)
6. Village employment structure : X11, Agricultural labor d 0.188 2. 55
(10.15 %) X“, Farmer a 0.654 5.37
X4234 Informal sector a 0.795 2. 23
Urban/Pull 1. Degree of industrial development Y1, Number of large scale industries - -0.147 7.43
(24.72 96) (7.43 %)
2. Availability of public facilities Y4, Number of clinics a -0.833 3.48
(11.09 %) Y5, Number of banks c 0.180 3.83
Ye, Number of pub. transp. vehicles d 0.229 2.00
Y1, Length of paved reads a 0.579 1.78
3. Availability of pie-college Y9, Number of elementary school a 0.842 4.48
educational facilities Yto, Number of secondary school e 0.202 1.72
(6.20 %)
Demographic 1. Population growth : 21, Population growth in the village d -0.527 2.43
(6.72 '/o) (2.43 %)
2. Migration : Z2, Net migration in the village b -0.580 429
(4.29 %)
Urbanization Rateofchangeinthevillage's Rateofchangein village's
Process (UP) pow-lotion density WP) porllllllliOIl density (UP)
(76. 84 %)
Summary Statistics: Significance Level of T-test :
Samplesize :44villages azlpercent d:15percent
MultipleR :0.87656 b:5percent e220percent
R-square :0.76835 c:10percent f:25percent

Adj. R-square :0.50196
Sig. F-statistic: 0.0099

 

100

Since this regression analysis involves a lot of independent variables, one might
suspect that multiple correlation (collinearity) among independent variables may exist.
This study has, specifically, measured the collinearity using the tolerance of the variable
and variance inflation factors (VIF). Results show that there is no multiple correlation
existed among the independent variables included in the final equation.

Factors determining urbanization in the NCR are presented in Table 9. Variables
representing the push factors in the linear regression equation are households with zero
dryland (X1), households with < 0.5 ha dryland (X3), households with 0.5-1.0 ha
paddyland (X6), Households with > 1.0-2.0 ha of paddyland (X3), and households with >
2.0 ha of paddyland. These variables are used to indicate the degree of regional land
parcelization. Both variables of the absentee land ownership are included in the equation,
including land owned by the absentee landlords (X11) and number of absentee landlords
(X12). Variables of agricultural land conversion (X13) and paddy land conversion (X14) are
both included in the equation. Other push factors included in the equation are agricultural
labor wage rate (X15), average agricultural land price (X16), agricultural labor (X17),
farmers (X13), and informal sector (Xio).

The pull factors included in the equation are number of large scale industries (Y1),
number of clinics (Y4), number of banks (Y5), number of public transportation vehicles
(Y5), length of the paved roads (Y7), number of elementary schools (Y9), and number of
secondary schools (Yw). And, both variables of demographic factors, population grth

(Z1) and net migration (22), are retained in the equation.

101
Therefore, the final of linear multiple regression equation expressing the factors

affecting the urbanization process in the NCR can be stated as :
UP=f(X1+X3+X6+Xs+Xlo+Xu+X12+X13+X14+X15+X16+
X” + X“ + X22 + Y1+ Y4+ Y, + Y6+ Y, + Y9+ Y“) + Zl-t-Zz)

Table 9 also summarizes the partial regression coeficients. Since not all variables
retained in the equation have the same measure, the partial regression coefficients are
standardized using B-Coeflicient so that the strength of the efl‘ect among the factors can
be compared. The last column of the Table 9 summarizes the percentage of variance of
each factor that explain the variance of the urbanization process in the NCR In addition,
the percentage value in the bracket of each indicator or each group of factor represents the
total variance of each indicator or variance of each group of factor that accounts for the
variance of the urbanization process in the NCR.

The results indicates that the linear multiple equation provides a good explanatory
model of regional urbanization process since the value of the multiple correlation
coeficient (R), the index of the strength of relationship between UP and all factors, is very
high (0.87656). In addition, the linkage efl‘ects between UP and all factors in the equation
is statistically very significant (or = 0.0099) with confidence of more than 99 percent.
Combined the push, pull, and demographic factors explain 76. 84 percent of the variance in
the urbanization process in the NCR. In other words, the causal factors account for 76.84
percent of the regional urbanization. From this 76.84 percent, push factors contribute
45.40 percent or 59.08 percent of the explained variance. The pull factors and

demographic factors, on the other hand, contribute 24.72 percent or 32.17 percent of the

 

102
explained variance and 6.72 percent or 8.75 percent of the explained variance. This

implies that urbanization in the NCR is determined by both push and pull factors but the
push factors have stronger effect on the regional urbanization. The strength of push
factors is almost twice (1.84 times) as that of the pull factors.

A more detailed discussion of each variable (push, pull, and demographic factors)

associated with the regional urbanization is provided in the following sections.

4.2.2.1. [ugh Fggtgrs
Push factors accounts for 45.40 percent of the equation's explained variance of 76.84

percent. It means that 59.08 percent of the explained urbanization process in the NCR is
determined by agricultural rural factors. Push factors can be grouped further into changes

in land tenure and changes in the agricultural economy of the NCR.

4.2.11.1.Wm
The changes land tenure explain 28.16 percent of the urbanization process in the

NCR This means that changing land tenure contributes 62.03 percent of the push factors
in urbanization. The total contribution of the changes in land tenure is determined by
three groups of factors, namely : the increase in agricultural land parcelization, the
increase in absentee land ownership, and the increase in agricultural land conversion into
non-agricultural uses. '

The increase of the agricultural land parcelization contributes 7.16 percent of the
explained urbanization. This explanation is 25.43 percent of the changing land tenure or

equal to 15.77 percent of the total push factors of the urbanization. There are five

103

variables used to explain the contribution of the increase of agricultural land parcelization
in explaining urbanization process in the NCR. Those variables are households with zero
dryland (X1), households with < 0.5 ha dryland (X3), households with 0.5-1.0 ha
paddyland (X6), households with >1 .0-2.0 ha paddyland (X3), and households with > 2.0
ha paddyland (X10). Among these variables, a decrease in the percentage of households
with < 0.5 ha dryland (X3) appears to afi‘ect urbanization very significantly with confidence
level of 99 percent (or = 0.01), and contributes 1.73 percent of the explained urbanization
or 24.16 percent of the total agricultural land parcelization. An increase in the percentage
of landless households (X1) and a decrease in the percentage of households with 0.5-1.0
ha paddyland (X6) also affect urbanization at confidence level of 90 percent (a = 0.10) by
contributing 1.35 percent and 1.31 percent variance in the urbanization or 18.85 percent
and 18.30 percent of the total agricultural land parcelization.

The increase of the absentee land ownership contributes 8.62 percent to regional
urbanization. This explanation reflects 30.61 percent of changes in land tenure or 18.99
percent of the total push factor in the urbanization. Two variables are used to explain the
contribution in the increase of absentee land ownership associated with regional
urbanization, including the increased hectarage of the land owned by the absentee
landlords (X11) and the increased number of absentee landlords (X12). ' The increased
hectarage of the land owned by the absentee landlords is highly correlated with regional
urbanization (confidence level 99 percent or or = 0.01) by contributing 6.92 percent of
total variance, or 80.28 percent of the absentee land ownership, or 24.57 percent of

changes in land tenure. The increased number of absentee landlords also significantly

104
determines urbanization process (confidence level 95 percent or a = 0.05) contributing

19.72 percent to absentee land ownership or 6.04 percent to changes in land tenure.

The most important efi‘ect on urbanization in the NCR results from the changes in
land temrre (and also from push factors) is mostly determined by the increase in the
conversion of agricultural land. This increase contributes 12.38 percent to regional
urbanization. This explains 43.96 percent of the changes in land tenure or 27.27 percent
of the total push factors associated with urbanization. Two variables are used to explain
the contribution of the agricultural land conversion to urbanization, including the
decreased hectarage of the total agricultural land (X13) and the decreased hectarage of the
total paddy land (X14). The decreased hectarage of total agricultural land affects regional
urbanization very significantly (99 percent confidence level or a = 0.01), contributing 9.03
percent of the explained urbanization, 72.94 percent of the agricultural land conversion, or
32.07 percent of the changes in land tenure. The decreased hectarage of paddy land also
affects regional urbanization (90 percent confidence level or a = 0.10) by contributing
3.35 percent ofthe explained variance urbanization, 27.06 percent ofthe agricultural land

conversion, or 11.90 percent of the changes in land tenure.

4-2-2-1-2- Wm:
Changes in the agricultural economy explain 17.24 percent of the regional

urbanization variance. This is equal to 37.97 percent of the push factors associated with
the urbanization. The total contribution of changes in the agricultural economy is

determined by three groups of factors such as the decrease of real agricultural labor wage

105
rates, the increase in agricultural land prices, and changes in the village's structure of

employment.

Decreased agricultural labor wage rates, represented by the variable of real
agricultural wage rate (X15), affects regional urbanization at 80 percent confidence level
(or = 0.20), contributing 2.12 percent to urbanization variance. This accounts for 12.30
percent of the changes in the agricultural economy or 4.67 of the total push factors.

Increased agricultural land prices, represented by the variable of average agricultural
land prices (X15), affect regional urbanization at 75 percent confidence level (a = 0.25),
contributing 4.97 percent to the regional urbanization. This accounts for 28.83 percent of
changes in the agricultural economy or 10.95 percent of the total push factors.

Changes in the structure of village employment explain 10.15 percent of the regional
urbanization. This accounts for 58.87 percent of changes in the agricultural economy or
22.36 percent of the push factors. Three variables are used to represent changes in the
structure of village employment in explaining urbanization. These variables are the
increase in the percentage of agricultural labor (X17), the decrease in the percentage of
number of farmer (X13), and the increase in the percentage of the population engaged in
employment in the informal sector (X22).

The increased percentage of agricultural labor explains 2. 55 percent of the
urbanization and accounts for 25.12 percent of changes in the structure of village
employment or 5.62 percent of changes in the agricultural economy (80 percent of
confidence level or or = 0.20). The decreased percentage of the number of farmers afi‘ects

tu'banization very significantly (99 percent confidence level or a = 0.10), explaining 5.37

106
percent of the variance in urbanization, 52.91 percent of changes in the structure of village

employment, or for 31.15 percent of changes in the agricultural economy. Finally, the
increased percentage of informal sector also significantly affects the urbanization (90
percent confidence level or a = 0.10) and explains 2.23 percent of urbanization, or 21.97
percent of changes in the structure of village employment, or 12.94 percent of changes in

the agricultural economy.

4333- Missing
Pull factors explain 24.72 percent of regional urbanization. This is equal to 32.17

percent of the regression's explained total variance of 76.84 percent. In other words, pull
factors account for 32. 17 percent of the known urbanization factors identified in the NCR
which is less than the contribution of push factors of 45.49 percent.

Pull factors can be grouped into the degree of industrial development, changes in the
availability of public facilities, and changes in the availability of pre-college educational

facilities. The contributions of each group described in the following sections.

4-22-2-1- WW
Other than expected, the degree of industrial development does not afi‘ects regional

urbanization. From the three variables identified prior to analysis (see Table 7 and Table
8), only one variable is retained in the linear multiple regression equation-the number of
large scale industries for every 1,000 village population (Y1). Although this variable
accounts for 7.43 percent of the explained variance in regional urbanization, statistically

this factor is not significance (confidence level only at 47 percent or or = 0.53).

107

4.2.2.2.2. Chgngas in the Avgfl' hill}! of Pgblig Fggilitias
Changes in the availability of public facilities explain 11.09 percent of the regional

urbanization or 44. 86 percent of the pull factors. Four variables represent changes in the
availability of public facilities after completion of the linear multiple regression analysis.
These variables are the increase in the number of clinics for every 1,000 village population
(Y 4), the increase in the number of banks for every 1,000 village population (Y 5), the
increase in the number of public transportation vehicles for every 1,000 village population
(Y 5), and the increased length of the paved roads for every 1,000 village population (Y7).

The increased number of clinics for every 1,000 village population very significantly
appear to affect urbanization very significantly with confidence level of 99 percent
(a = 0.01) and explains 3.48 percent of the urbanization, 31.38 percent of changes in the
availability of public facilities, or 14.08 percent of the pull factors. The increased number
of banks for every 1,000 village population explains 3 .83 percent of the urbanization and
appears not very significant (confidence level 80 percent or a = 0.20). It accounts for
34.54 percent of changes in the availability of public facilities or 15.49 percent of the total
pull factors.

The increased number of public transportation vehicle for every 1,000 village
population appears afl‘ects regional urbanization (confidence level 85 percent or a = 0.15).
It explains 2.00 percent of urbanization, 18.03 percent of changes in the availability of
public facilities, or 8.09 percent of the total pull factors. The increased length of the
paved roads for every 1,000 village population very significantly affects urbanization

(confidence level 99 percent or a = 0.01). It explains 1.78 percent of the urbanization

108

process or accounts for 16.05 percent of the development of public facilities or accounts

for 7.20 percent of the pull factors which explain the process.

4.2.2.2.3. thnges in 1h; Ang' 9111;: 91' P1332113; Mggtigng Fggilitig
Changes in the availability of pre-college educational facilities explain 6.20 percent of

regional urbanization, accounts for 8.07 percent of the known urbanization process and
represents 25.08 percent of the total pull factors associated with urbanization. Two
variables which represent changes in the availability of pre-college educational facilities are
retained alter the regression analysis. These variables are the increased number of
elementary schools for every 1,000 village population (Y9) and the increased number of
secondary schools for every 1,000 village population (Yio).

The increased mrmber of elementary schools for every 1,000 village population
appears to affect regional urbanization very significantly (confidence level 99 percent or
or = 0.01). It explains 4.48 percent of urbanization, 72.26 percent of changes in the
availability of pre-college educational facilities, or 18.12 percent of the total pull factors.
On the other hand, the increased number of secondary schools for every 1,000 village
population appears to be of limited importance in urbanization (confidence level 80
percent or a = 0.20). It contributes 1.72 percent to urbanization, 27.74 percent of
changes in the availability of pre-college educational facilities, or 6.96 percent of the total

pull factors.

109

4.2.2.3. gemggranhg' Factggs
Demographic factors contribute only 6.72 percent or 8.7 5 percent of the explained

urbanization in the region. Surprisingly, population growth (Z1) appears to be of limited
significance in urbanization (confidence level 85 percent or or = 0.15) and explains only
2.43 percent of urbanization or 36.16 percent of the demographic factors. On the other
hand, the increase of net migration in the region significantly afi‘ects urbanization
(confidence level 95 percent or or = 0.05) and contributes 4.29 percent to urbanization.

This contribution accounts for 63.84 percent of the demographic factors.

413- WM

This section describes the efi‘ect of the village proximity to the center of development
or to the central city on regional urbanization. Specifically, it describes whether the village
proximity to the city significantly affects the urbanization and to which extend proximity a
factor in explaining urbanization.

Cities considered as the centers of development in this study include : (i) Jakarta, the
capital city of Indonesia located on the west side of the NCR; (ii) Cirebon, the city
developed by the Government of West Java to balance the development of Jakarta,
located on the east side of the NCR; and (iii) the capital city of each kabupaten in the
NCR (see Figure 2). Therefore, the location of the village relative to Jakarta, Cirebon,
and capital city of kabupaten, respectively, are analyzed and described.

The proximity of the village to city is measured by its distance (kilometer, km) to the
city and defined as :

l 10
l. The village is classified as close to Jakarta if the distance of the village to Jakarta is 5

150 km and the village is classified as far from Jakarta if the distance of the village to
Jakarta is > 150 km.

2. The village is classified as close to Cirebon if the distance of the village to Cirebon is
5 150 km and the village is classified far from Cirebon if the distance of the village to
Cirebon is > 150 km.

3. The village is classified as close to the capital city of kabupaten if the distance of the
village to the capital city of kabupaten is _<_ 20 km and the village is classified as far
from the capital city of kabupaten if the distance of the village to the capital city of

kabupaten is > 20 km.

In the analysis, the proximity of the village to the city is treated as a dummy variable.
Such a dummy variable is introduced into a multiple regression equation presented in
Table 9 (previous section). The dummy variable can be set in the regression model by
defining the variable as :

D, is 1 ifthevillageisclosetoJakarta,0ifnot; or

D; is 1 ifthe village is close to Cirebon, 0 ifnot; or

D3 is 1 if the village is close to the capital city of kabupaten, 0 if not.

Suppose that the linear multiple regression equation presented in Table 9 is denoted
asUP thentheefi‘ectofthevillageproximitytoJakartaonurbarrizationcanbestatedas
UP, = UP + D]. Similarly, proximity efi'ect of the village to Cirebon is stated as
UP; = UP + D2 and proximity effect of the village to the capital city of kabupaten is

defined as UP3 = UP + D3. This analysis follows Johnston (1991) who believes that the

111
use of dummy variable in this type of analysis is more advantageous than the use of

conventional analysis of variance. He states that, "Dummy variables can be used as an
alternative analysis of variance procedure, with the added advantage over the conventional
method that the partial regression coefficients can be used, where relevant, to test whether
each group mean is significantly different fiom the mean represented by the constant.
More importantly, they can also be used in combination with continues variables, those
measured on interval or ratio scales [while dummy variables are measured on nominal
scale]. This allows both conventional regression methods and analysis of variance of the
residuals to be performed in a single procedure” (Johnston, 1991; pp. 113-114).
The results of the analysis are summarized in Table 10. The first column of the table
is a statistical summary of the regression equation which has been presented in Table 9
(UP). The next columns (UP1- UP3) represent statistical summaries of the regression
analysis afier the distance factor (D,- D3) is introduced into UP.
Table 10. Statistical Summary of the Multiple Regressions of Urbanization with Distance
Factors in the NCR Expressed as without (UP) and with (UPH) Dummy
Variables and Their Significance (F -significance)', the Explained Variance of
the Village Proximity to Jakarta (UP,), to Cirebon (UP;), and to the Capital

City of Kabupaten (UP3); and Its Significance in Afl‘ecting the Urbanization
Process (Di-significance)

 

 

 

 

Statistical UP UP, UP; UP3

Summary (as Table 9) (UP + D,) (UP + D2) (UP + D3)
Multiple R 0.87656 0.88427 0.87800 0.88371
Multiple R-square 0.76835 0.78194 0.77088 0.78094
Adjusted R—square 0.50196 0.50649 0.48147 0.50424
F—significance 0.0099 0.0118 0.0165 0.0121
Standard Error 25.2067 25.2067 25.8379 25.2643
Di-significance 0.2902 0.6521 0.3091
Explained Variance 1.36 % 0.25 % 1.26 %

 

 

 

 

 

 

112

Table 10 shows that by introducing the dummy variable of the village proximity to
Jakarta (DI) the explained variance of the urbanization process in the NCR increases from
0.76835 to 0.78194. It means that the village proximity to Jakarta explains 1.36 percent
of the urbanization process. This explanation is statistically insignificant due to the fact
that D, is only significant at the level of or = 0.2902. However, considering that Jakarta is
the most developed city in Indonesia and has been recognized as the city of migrants,
proximity of villages to Jakarta can be considered as having an efi'ect on regional
urbanization if, and only if, the type I error)2 is allowed at or = 0.30 (or confidence level of
70 percent).

Table 10 also shows that even when the type I error at confidence level of 70 percent (
ct = 0.30), proximity of villages to Cirebon and to the capital city of kabupaten are not
statistically significance in afi‘ecting regional urbanization. Proximity of villages to
Cirebon is only statistically significance at a = 0.6521 (confidence level of 34 percent) and
explains only a very small percentage (0.25 percent) of the urbanization process.
Similarly, proximity of villages to the capital city of kabupaten is only statistically
significance at a = 0.3091 (confidence level of 69 percent) and explains 1.26 percent of
urbanization.

Further analysis pursued in this section and presented below, aims to determine

whether proximity of the urban villages to the cities significantly affects regional

 

3’"Atypelerr'orinastatisticrrltestoflrypotherrisiscornmitterlwhenadecisionismadetorejectanullhypotlresis
whichisactuallytr'ue. Theprobabilityofcornmittingatypelerrorisa(alpha)' (Barber, 1988', p. 265).

113
urbanization. In other words, it analyzes whether the distance of the village-city of the

urban area of the region significantly affect urbanization.

As before, dummy variables are introduced to represent urban villages of the NCR
(D.) (defined in Section 4.1.1.) into the regression equation presented in Table 9.
Suppose the urbanization process in the urban areas is denoted as UP. and is defined as
UP. = UP + D.. The efiects of proximity of the villages to Jakarta, Cirebon, and the
capital city of kabupaten (DI-D3), then, can be assessed by introducing DI-D3 into UP..
Therefore, UPs, UP5, and UP. represent linear multiple regression equations incorporating
the effect of proximity to the cities in urbanization process in the urban areas. The results
of the analysis are summarized in Table 11.

Table 11. Statistical Summary of the Multiple Regressions of the Urbanization Process in

the NCR with Dummy Variables of Urban Area and Urban Area with the
Village Proximity to Jakarta, to Cirebon, and to the Capital City of Kabupaten

 

 

 

 

 

 

 

 

Statistical UP. UP, UP, UP.

Summary (UP + D.) (UP+D.+D,) (UP+D.+D2) (UP+D.+D.)
Multiple R 0.90117 0.90998 0.90306 0.91041
Multiple R-square 0.81211 0.82806 081551 0.83542
Adjusted R-square 0.57478 .058925 055928 0.60684
F-Significance 0.0041 0.0043 0.0070 0.0032
Standard Error 23.3980 22.9965 23.8206 22.4983
Di-significance 0.0490 0.2127 0.5717 0.1217
Explained Variance 4.38 °/. 4.13 °/. 4.72 °/. 6.71 %

 

Table 11 shows that the dummy variable of urban area (D.) significantly afi'ects
urbanization in the NCR (confidence level of 95 percent or a = 0.0490). In other words,
the acceleration of the urbanization process in the NCR is higher in urban area than that in
rural area, indicating, again the self-reinforcing nature as described in Section 4.1.3.1.

This also shows that proximity of urban villages to Jakarta afi'ects the urbanization process

 

1 14
with confidence level of 78 percent (or = 0.2127) and is higher than the effect of the village

proximity to Jakarta for the whole region (confidence level of 70 percent or a = 0.2902)
(see Table 10). This indicates that village distance to Jakarta only influences urban areas.
Proximity of urban villages to Cirebon does not significantly affect regional urbanization
since it is only significance at a = 0.5717, indicating that Cirebon does not influence the
whole region of the NCR (Table 10) neither the urban area of the NCR (Table 11). On
the other hand, the proximity of the urban villages to the capital city of kabupaten appears

to have Significant efl‘ect on urbanization ( confidence level of 87 percent or or = 0.1217).

V. URBANIZATION AND AGRICULTURAL DEVELOPMENT

The relationship between urbanization and agricultural development in the NCR
presented in Section 2.2. is summarized below (Figure 9). This relationship is affected by
both national and regional development policies, namely maintaining the region as the
bread basket of the nation and the adoption of a hierarchical regional development
strategy (see also Section 1.2.1). Urbanization and agricultural development are two
processes which affect each other by direct or indirect linkages, including through
urbanization with its underlying causal factors.

The increased regional urbanization affects agriculture by putting additional pressure
on the agricultural resource base and, at the same time, the increased demand for food in
urban areas forces the agricultural sector to increase productivity with a reducing resource
base. An increase in agricultural economic activity, on the other hand, stimulates
urbanization by inducing regional industrial development through the redistribution of
labor among rural and urban sectors (see Section 1.2.2). On the contrary, a government
policies undermining a viable agricultural sector forces people to seek better economic
opportunities in urban areas.

Urbanization, in turn, is influenced by push factors fiom rural agricultural areas, pull
factors of urban areas, and demographic factors. In other words, agricultural development
also afl‘ects regional urbanization. Moreover, each of the push factors also affects the
regional urbanization (see Sections 2.2.1.2.; 2.2.3; 3.3.2.3; and 4.2.). For example,

regional urbanization is very significantly affected by increased agricultural land

115

116

 

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117
conversion into non-agricultural uses (see Table 9 in Section 4.2.2.) and such a conversion

also affects agricultural viability in rural areas.

Section 4.1. describes the level of urbanization in the NCR. It shows that in the last
ten years the number of urban villages in the NCR have increased from 151 villages to 223
villages (fi'om 13.74 percent to 20.29 percent). This means that in the period of analysis,
the village urbanization rate in the region is 47.67 percent or 4.77 percent per year.
Similarly, the urban population has increased from 1,179,362 people to 2,439,996 people
(from 25.69 percent to 38.75 percent). This means that, during this period, the
urbanization rate related to population growth in the NCR is 106.89 percent or 10.69
percent per year.

With such a high annual urbanization rate, it can be expected that regional agricultural
development is negatively affected. This chapter describes the changes in regional
agriculture accompanying the regional urbanization process in the period of 1982-1992.
To focus the analysis, however, the various impacts on agricultural development are

defined before describing the results of the research.

5.1. Operational Definitions

As presented in Section 2.1.2., this study defines agricultural development in the NCR
as any effort in agricultural improvement directed to maintain and improve existing
agricultural infi'astructure, to design a better structure of agricultural land ownership, and
to reduce the increasing absentee landownership to maintain and improve food security of

rural population, to improve the welfare of rural households, to enhance the quality of life

118
of rural population who earn their living in agriculture, and to reduce rural-urban disparity

without reducing the long-term productive capacity of the agricultural resource base.

The implicit assumption in this definition is that the improvement of rural food
security, welfare, quality of life, and rural-urban equity can be enhanced by maintaining
and improving the agricultural resource base, strengthening the structure of ownership of
the agricultural resource base, and by reducing the dependency of agricultural rural areas
on the increasing trend in absentee land ownership through regional development
strategies. Some studies which support this assertion are described in Section 2.1.2.

This study is designed to analyze the changes of the structure of land ownership, the
changes of the degree of absentee land ownership, the changes of agricultural prime land
(or agricultural infi'astructure based on the World Bank's definition [World Banlg 1994])
or agricultural land conversion with its following impact on the agricultural household's
income, the changes of the structure of rural employment, and rural-urban disparities in
the period of 1982-1992. This chapter describes the first four topics, while rural-urban
disparities will be described in Chapter VI.

Other prominent impacts of urbanization on agricultural development such as the
changing quality of the agricultural resource base as a result of its intensive uses, soil and
water pollution induced by urban based agricultural nranagement, and environmental
impacts of fertilizers and pesticides are not pursued in this study. The reason for not

pursuing these themes is described in Section 2.1.2.

1 19
5.2. Changes in the Distribution of Regional Land Ownership

This section describes the structural change of land ownership of dryland and paddy
land both in the rural wea in the NCR and in the NCR as a whole. Structural changes in
land ownership are assessed at the village level by comparing the structure of 1992 with
that of 1982. Statistical mean comparisons are conducted by using t-tests for paired-
samples method such as presented in Section 3.3.2.5.

The results of the analysis are summarized in Table 12 and Table 13. Table 12
summarizes the comparison between the percentage of households with different land
sizes (drylands and paddylands) within the NCR region in 1982 and 1992. Table 13
summarizes the comparison between the percentage of households with different land

sizes (dryland and paddylands) in the rural areas within the region in 1982 and 1992.

5-11- W

The structure of agricultural land ownership in the NCR between 1982 and 1992 has
changed very Significantly (T able 12). The changes put sustainable agricultural
development at risk, especially those designed to improve the welfare of the people
engaged in agriculture, because of increased diseconomies of scale due to land
parcelization. The analysis shows that the percentage of landless households has increased
during the analysis period. Specifically, the percentage of households without agricultural
dryland and paddy land grew very significantly (confidence level of 99 percent or
a = 0.01). Households without agricultural dryland increased from 47.66 percent in 1982
to 56.64 percent in 1992 and households without paddyland increased from 43 .48 percent

in 1982 to 53.41 percent in 1992. This means that households without paddyland grew

 

respectively.

Table 12. The Differences in the Distribution of Household Land Ownership in the NCR
between 1982 and 1992

120
faster than those without dryland, an increase of 22.84 percent and 18.84 percent,

 

 

 

 

 

 

 

 

 

 

 

Variable Percent of Households with Land Mean of Paired Significant

Difl‘erences Differences
1982 1992

Dryland :

0 HA 47.6639 56.6427 -8.9789 *"“

< 0.5 HA 32.3098 30.8595 1.4502

0.5 - 1 HA 12.1532 8.5748 3.5784 """‘

>1 - 2 HA 5.2080 3.1732 2.0348 "*‘l'

> 2 HA 2.1645 0.7380 1.4266 "*"”"

Paddyland :

0 HA 43.4802 53.4057 -9.9255 ""*

< 0.5 HA 27.4689 27.0698 0.3991

0.5 - 1 HA 16.4220 12.0536 4.3684 **"*

>1 - 2 HA 9.2136 5.7011 3.5125 "1'"

> 2HA 3.5350 1.6350 1.9000 "1'"

Source : Primary Data (Village Survey)

Significance Level :

t 20 m tit 10 M iii"!!! 1 ml

tfi 15 W 0". 5 W

The increase of regional landless households is not significantly associated with the
decrease of the percentage of households with < 0.5 ha dryland or < 0.5 ha paddyland.
Although households with < 0.5 ha dryland and households with < 0.5 ha have decreased
fiom 32.31 percent in 1982 to 30.86 percent in 1992 and from 27.47 percent in 1982 to
27.07 percent in 1992, respectively, this decrease is not significantly difl'erent. This
indicates that the percentage of subsistence farmers in the region remain largely the same

during the period. Regional agricultural development has, therefore, been unable to

reduce the percentage of subsistence farmers.

 

121
However, the increase of regional landless households is associated very significantly

with the decreases in the percentage of households with _>_ 0.5 ha dryland and that with
3 0.5 ha paddy land during the period of analysis (confidence level of 99 percent or
or = 0.01). Households with 0.5-1.0 ha dryland and those with 0.5-1.0 ha paddyland have
decreased very significantly between 1982 and 1992 from 12.15 percent to 8.57 percent
and from 16.42 percent to 12.05 percent, respectively. These decreases are the greatest
among other land divisions. For the same period, households with >1 020 ha dryland
and those with >1 .0-2.0 ha paddyland have decreased very significantly fiom 5.21 percent
to 3.17 percent and fiom 9.21 percent to 5.70 percent. The decrease ofthe percentage of
household with this hectarage of paddyland is greater than those of dryland (39.16 percent
and 38.11 percent, respectively). Finally, the percentage of households with > 2.0 ha
dryland decreased less than that of paddyland. Households with > 2.0 ha dryland
decreased by 65.74 percent fi'om 2.16 percent in 1982 to 0.74 percent in 1992. Similarly,
the households with > 2.0 ha paddyland decreased by 53.67 percent from 3.54 percent to

1.64 percent.

5.2.2. . ,

 

Changes of the agricultural land ownership distribution in rural areas of the NCR
during the 1982-1992 period are of the same magnitude as those ofin the NCR as a
whole. Landless households increased and the households with agricultural landholdings
decreased. No significant changes exist in the percentage of households with < 0.5 ha

agricultural lands and those with < 0.5 ha of paddyland in the period of 1982-1992.

122
Results of the analysis of changes in the distribution of the agricultural land ownership in

the rural areas are summarized in Table 13.

Table 13. Difi‘erences in the Distribution of Household Land Ownership in the Rural

Areas of the NCR between 1982 and 1992

 

 

 

 

 

 

 

 

 

 

 

Type and Percent of Households with Land Mean of Paired Significant
Size of Land Difl‘erences Difl‘erences
1982 1992

Dryland :
0 HA 49.9700 58.4400 -8.4700 "”*
< 0.5 HA 28.5488 27.6554 0.8933
0.5 - 1 HA 12.1075 8.5271 3.5804 *""
>1 - 2 HA 6.3692 4.3267 2.0425 "”
> 2 HA 2.5496 1.0708 1.4787 "*“
Paddyland :
0 HA 47.4821 55.9400 -8.4879 *"”
< 0.5 HA 26.9838 25.4217 1.5621
0.5 - 1 HA 13.6300 10.9513 2.6788 ""
>1 - 2 HA 9.4188 5.7129 3.7058 "*
> 2 HA 3.4096 1.7192 1.6904 "*"
Source : Primary Data (Village Survey)
Significance Level :

10 percent “‘"* 1 percent
5 percent

‘ 20 percent ”‘
.. 15 m i...

It shows that the percentage households without agricultural drylands and paddylands
increased very significantly in the period of 1982-1992 (confidence level of 99 percent or
or = 0.01), an increase from 49.97 percent to 58.44 percent and from 47.48 percent to
55.94 percent, respectively. This means that the percentage of households without
dryland increased by 16.95 percent and that without paddyland increased by 17.82
percent. Households with < 0.5 ha agricultural dryland and those with < 0.5 ha paddyland

decreased insignificantly during the period.

123
Households with 0.5-1.0 ha agricultural dryland decreased very Significantly fi'om

12.11 percent in 1982 to 8.53 percent in 1992 (confidence level of 99 percent or
o. = 0.01), a decrease of 29.56 percent. Households with >1 .0-2.0 ha agricultural dryland
decreased significantly from 6.37 percent in 1982 to 4.33 percent in 1992 (confidence
level of 95 percent or or = 0.05), a decrease of 32.03 percent. Also, the percentage of
households with > 2.0 ha dryland decreased very significantly from 2.55 percent in 1982
to 1.07 percent in 1992 (confidence level of99 percent or a = 0.01), a decrease of 58.04
percent.

On the other hand, the percentage of households with 0.5-1.0 ha paddyland decreased
very significantly by 19.66 percent, a decrease fi'om 13.63 percent in 1982 to 10.95
percent in 1992 (confidence level of 99 percent or or = 0.01). The percentage of
households with >l.0-2.0 ha paddyland decreased significantly by 39.38 percent, a
decrease from 9.42 percent in 1982 to 5.71 percent in 1992 (confidence level of 95
percent or a = 0.05). The percentage of households with > 2.0 ha dryland increased very
significantly by 49.56 percent, decreases fi'om 3.41 percent in 1982 to 1.72 percent in
1992 (confidence level of 99 percent or a = 0.01).

The analysis shows a very significant increase in agricultural land parcelization during
the period of 1982-1992, characterized by an increasing landless households. Agricultural
land parcelization puts agricultural development at risk since it threatens the welfare of the
population engaged in agriculture due to diseconomies of scale of agricultural enterprise
(Toner, 1979; Dunford, 1981); and Lockeretz, 1986). Moreover, the combined efi'ects of

increased absentee land ownership (described in Section 5.3) and increased agricultural

124

land conversion (described in Section 5.4) in rural areas undermines the role of the region
as the bread basket of Indonesia. This effect may be mitigated through future

consolidation of agricultural lands.

5.3. Absentee Land Ownership in Rural Areas and the NCR Region

Regional urbanization is commonly accompanied by increased prices of agricultural
lands. Due to a knowledge of regional land use plans, land speculators can acquire
agricultural lands proposed for urban development. This increases the hectarage of land in
rural areas owned by the people from outside rural areas. In the NCR, the increased
hectarage of land owned by the outsiders, however, is not merely determined by the
increased land speculation but also determined by other factors such as increased
investment in agricultural land as a hedge against inflation.

In the sociological terms, the Sland owned by the outsiders is usually referred to as
absentee land and controlled by absentee land owners or commonly called as absentee
landlords. In the NCIL the parallel terms are commonly used such as ”tanah gontai" and
"tuna tanah" (or ”spekulan” to indicate land speculators).

This section describes the changes in the degree of absentee land ownership in the
rural areas and the region as a whole during the period of 1982-1992, including changes in
the hectarage of absentee lands and the number of absentee landlords. However, this
study does not difi‘erentiate between the absentee lands caused by land speculation or
other investments in agricultural lands by urban inhabitants.

The method used to assess changes in absentee land ownership is identical to that

used in distributional changes in land ownership.

125

5.3.1. Awntee mg OwngLship in ghg NCR Rggiog
This section describes the changes in absentee land ownership in the NCR between

1982 and 1992. Results of the analysis are summarized in Table 14 in which absentee
ownership of dryland, paddyland, and total land are presented.

Table 14. Regional Differences in the Hectarage of Absentee Lands and the Total Number
of Absentee Land Owners or Absentee Landlords between 1982 and 1992

 

 

 

 

 

 

 

 

 

 

 

Lands Owned by and the Total in the Village Mean of Significant
Number of Absentee Landlords Paired Differences
in the Village 1982 1992 Difi‘erences

ha ha ha

Total Absentee Land :

l. Dryland 12.4530 87.8927 -75.4398 """

2. Paddyland 34.0455 48.4470 -14.4016 *“"

3. Dryland and Paddyland 46.4985 136.3397 -89.8412 ***"
no. no. no.

Total Absentee Landlords with:

1. Dryland 3.3409 11.0000 -7.6591 "*"

2. Paddyland 25.0909 29.7273 -4.6364 ***

3. Dryland and Paddyland 28.4318 40.7273 -12.2955 *""”"

Source : Primary Data (Village Survey)

Significance Level :

a 20 percent «a 10 m eases 1 mm

" 15 percent "" 5 percent

The total absentee lands and the number of absentee landlords in the region increased
very Significantly between 1982 and 1992 (confidence level of 99 percent or a = 0.01).
Average absentee lands in the region, which was assessed at the village level, increased by
89.84 ha, an increase from 46.50 ha in 1982 to 136.34 ha in 1992. It means that total
absentee lands in the NCR increased by 193.20 percent during the period of 1982-1992 or
19.32 percent annually. Average mrrnber of absentee landlords, on the other hand,

increased by 12.30, an increase from 28.43 in 1982 to 40.73 in 1992. Therefore, the

 

126
average number of absentee landlords increases by 43.26 percent or 4.33 percent annually.

The total hectarage of absentee lands increased faster than the number of absentee
landlords, indicating more concentrated absentee land ownership.

Comparing the total hectarage of absentee lands of dryland and paddyland, it shows
that increased absentee hectarage can be attributed to an increase in absentee dryland.
Average absentee dryland in the region increased very significantly by 75.44 ha, an
increase from 12.45 ha in 1982 to 87.89 ha in 1992 (confidence level of99 percent or a =
0.01). This means that the total absentee dryland in the NCR increased by 605.94 percent
during the period of 1982-1992 or 60.59 percent annually. Average absentee paddyland,
meanwhile, increased very significantly by 14.40 ha, an increase from 34.05 ha in 1982 to
48.45 ha in 1992 (confidence level of 99 percent or a = 0.01). This means that the total
absentee paddyland in the NCR increased by 42.29 percent during the period of 1982-
1992 or 4.23 percent annually.

This pattern of increase in absentee dryland is accompanied by a higher number of
absentee landlords acquiring dryland than those acquiring paddyland. Average number of
absentee landlords with dryland increased by 229.34 percent within period of 1982-1992
or 22.93 percent annually, an increase fi'om 28.43 in 1982 to 40.73 in 1992 (confidence
level of 99 percent or a. = 0.01). Meanwhile, the average number of absentee landlords
with paddyland increased only 18.49 percent or 1.85 percent annually, an increase from
25.09 in 1982 to 29.73 in 1992 (confidence level of 90 percent or a = 0.10).

While it is more economical to invest in paddyland than that in dryland, the high

increase of absentee dryland in the NCR might be attributed to the increased land

 

127
Speculation in the region because the land speculators usually have on-hand information

regarding rural lands allocated for urban uses which is rarely an irrigated land (see Section
1.2.1.). This is especially important given existing the Government of Indonesia's policies

prohibiting conversion of paddyland to non-agricultural uses.

5.3.2. A n 11 hi ' h A
Changes in absentee land ownership in the rural areas of the NCR during the period

are more staggering than those in the region as a whole. Absentee land ownership in the
rural areas for the period of 1982-1992 is summarized in Table 15. It shows that the
degree of absentee land ownership in the rural area is much greater than that in the whole
region of the NCR

Table 14 and 15 show that in 1982 the average hectarage of absentee lands and
number of absentee landlords at the regional level were 46.50 ha and 28.43, respectively.
This is smaller than that in the rural areas which are 67.88 ha and 40.38, respectively. In
1992, the figures of the NCR are 136.34 ha and 40.73 which are also less than those of
rural areas with 198.86 ha and 54.42, respectively.

Changes in land ownership in rural areas, however, is similar to that in the region.
Table 15 shows that total absentee lands and the number of absentee landlords in rural
areas increased very significantly between 1982 and 1992 (confidence level of 99 percent

or or = 0.01).

128

Table 15. The Differences in the Absentee Land Ownership and the Number of Absentee
Land Owners (Absentee Landlords) in the Rural Areas of the NCR between

 

 

 

 

 

 

 

 

 

 

 

1982 and 1992
Lands Owned by and the Total in the Village Mean of Significant
Number of Absentee Landlords Paired Difl‘erences
in the Village 1982 1992 Differences

ha ha ha

Total Absentee Land :

1. Dryland 18.2138 134.4054 -116.192 ""

2. Paddyland 49.6667 64.4563 ~14.7896 ""*

3. Dryland and Paddyland 67.8805 198.8617 -130.9812 "***
no. no. no.

Total Absentee Landlords with:

1. Dryland 2.2083 12.3750 -10.l667 ""5

2. Paddyland 38.1667 42.0417 -3.8750

3. Dryland and Paddyland 40.3750 54.4167 -14.0417 "*"

Source : Primary Data (Village Survey)

Significance Level :

t 20 percent 5" 10 percent “m“ 1 percent
" 15 percent *”’“ 5 percent

Average absentee land increases from 67.88 ha ill 1982 to 198.86 ha in 1992, an
increase of 130.98 ha. This means that total absentee lands in the ma] areas increased by
192.96 percent during the period of 1982-1992 or 19.30 percent annually. Average
number of absentee landlords in rural area, meanwhile, increased from 40.38 in 1982 to
54.42 in 1992, an increase of 14.04. Therefore, the number of absentee landlords
increased by 34.77 percent in the period of 1982-1992 or 3.48 percent annually. Similar
to the comparison at regional level, the increase in absentee land is larger than the increase
in the number of absentee landlords, indicating that absentee landlords is becoming more
concentrated.

Comparing the total hectarage of absentee lands (dryland and paddyland), Table 15

shows that the increase in absentee land in the rural areas can be more attributed to the

129
increased in absentee dryland. Average absentee dryland increased significantly by

116.192 ha, an increase from 18.21 ha in 1982 to 116.192 ha in 1992 (confidence level of
95 percent or a = 0.05). This means that absentee dryland in rural areas increased by
638.06 percent during the period of 1982-1992 or 63.81 percent annually. Absentee
paddyland, meanwhile, increased very significantly fi'om 49.67 ha in 1982 to 64.46 ha in
1992 (confidence level of99 percent or or = 0.01), an increase of 14.79 ha. This means
that absentee paddyland in rural areas increased by 29.78 percent during the period of
1982-1992 or 2.98 percent annually.

Increases in absentee dryland is accompanied by a higher number of absentee
landlords acquiring dryland rather than paddyland. The average number of absentee
landlords with dryland increased very significantly by 460.18 percent within period of
1982-1992 or 46.02 percent annually, an increase from 28.43 in 1982 to 40.73 in 1992
(confidence level of 99 percent or a = 0.01). However, the average number absentee
landlords with paddyland increase insignificantly, indicating that the absentee paddyland in

nrral areas is also becoming more concentrated in absentee ownership.

5.4. Agricultural Land Conversion in Rural Areas and the NCR Region

According to Schmid (1968) and Firman (1992), regional urbanization is
accompanied by the increased demand for land to support residential and industrial estates.
Since urban land is limited, the agricultural lands are commonly put under pressures for
conversion to non-agricultural uses to keep up with urbanization. Therefore, it is
expected that agricultural lands in the NCR are under pressure of conversion to non-

agricultural uses.

 

130
This study assesses the changes of total agricultural lands in the rural areas and in the

region as a whole between 1982 and 1992. The main focus of this assessment is to see
whether irrigated lands are mostly converted to non-agricultural uses. This addresses the
concern to preserve the region's importance as the bread basket of Indonesia.

The following sections describe the results of the analysis of agricultural land
conversion in rural areas and in the region as a whole. The method used to assess land use

change between 1982 and 1992 are the same as in the previous chapters.

5.4.1. WWW

Results of the analysis of changes in the total agricultural land between 1982 and
1992 in the NCR region are summarized in Table 16. It includes the magnitude of
irrigated land and agricultural dryland conversions both in total hectarage and weighted
hectarage by number of the village population. This shows that the average irrigated land
decreased significantly with confidence level of 99 percent (a = 0.01) and that the
average agricultural dryland decreased Significantly with confidence level of 85 percent
(a = 0.15), indicating that agricultural land conversion afi‘ects mostly irrigated land, the
pillar of agricultural productivity of the region.

Average irrigated land hectarage decreased by 73.18 ha (25.62 percent) in the period
of 1982-1992 or 2.56 percent annually, a decrease from 285.69 ha in 1982 to 212.52 ha in

1992. This decrease is also very significant when the total hectarage of irrigated land is

weighted by the number of village population.

 

131

Table 16. Differences in the Total Land (ha) and Total Land for Each 1,000 Village
Population (ha/1,000 village population) for both Irrigated Land and
Agricultural Dryland in the NCR between 1982 and 1992

 

 

 

 

 

 

 

 

 

 

Type of Agricultural Land Total in the Village Mean of Significant
Converted Paired Differences
into Non-agricultural Uses 1982 1992 Differences
ha ha
Irrigated Land :
1. Total Hectarage 285.6945 212.5166 73.1778 *****
2. Total Hectarage for Each 58.2595 34.1545 24.1050 **"'"
1,000 Village Population
ha ha
Agricultural Dryland :
1. Total Hectarage 67.3977 49.1259 18.2718 ‘1‘
2. Total Hectarage for Each 14.7352 8.0759 6.6593 *"
1,000 Village Population
Source : Primary Data (Village Survey)
Significance Level :
s 20 m sea 10 W ass-11a 1 percent
it 15 m I... 5 mm

The average agricultural dryland, on the other hand, decreased by 18.27 ha or 27.11

percent in the period of 1982-1992 or 2.71 percent annually (confidence level of 85

percent or significant at a = 0.15), a decrease from 67.40 ha in 1982 to 49.13 ha in 1992.

The confidence level of the loss of agricultural dryland is higher (confidence level of 90

percent or a = 0.10) ifthe hectarage ofagricultural dryland is weighted by the number of

village population.

 

132

541- MW
Changes in the total agricultural land between 1982 and 1992 in rural area of the

region are sunnnarized below (Table 17).

Table 17. The Differences in the Total Land (ha) and Total Land for Each 1,000 Village
Population (ha/1,000 village population) for both Irrigated Land and
Agricultural Dryland in the Rural Areas of the NCR between 1982 and 1992

 

 

 

 

 

 

 

 

 

 

 

Type of Agricultural Land Total in the Village Mean of Significant
Converted Paired Differences
into Non-agricultural Uses 1982 1992 Differences
ha ha
Irrigated Land :
1. Total Hectarage 382.3441 286.5920 95.7521 "*"
2. Total Hectarage for Each 80.9563 47.1675 33.7888 ""*
1,000 Village Population
ha ha
Agricultural Dryland :
1. Total Hectarage 78.3896 55.9579 22.4317
2. Total Hectarage for Each 19.71 13 9.9446 9.7667 **
1,000 Village Population
Source : Primary Data (Village Survey)
Significance Level :
a 20 W ass 10 W cease 1 mm

In 15 percent ms 5 percent

Irrigated land and agricultural dryland conversions are summarized in total hectarage
and weighted by the village population. In rural areas, the village's average irrigated land
decreased very significantly (confidence level of 99 percent or or = 0.01) while the average
agricultural dryland decreased insignificantly. This indicates that agricultural land
conversion includes mostly irrigated land. This represents an average decrease by 25.04
percent or 2.50 percent annually, a decrease from 382.34 ha in 1982 to 286.59 ha in 1992
(confidence level of 99 percent or a = 0.01). This decrease is also very significant when

the total hectarage of irrigated land is weighted by the number of village population

 

133
(confidence level of 99 percent or a = 0.01). The average agricultural dryland conversion

is, on the other hand, insignificant. Weighted by number of village population, this
decrease is, however, significant (confidence level of 85 percent or a = 0.15).

It is clear that land conversion analysis in rural areas and in the region as a whole
show that irrigated land has been mostly sacrificed in the process of urbanization. This
process undermines the future sustainability of the regional agriculture especially in

maintaining its contribution to the national food self-suficiency.

5.5. Irnpacts of Agricultural Land Conversion on Household Income

At the regional level, the increased irrigated land conversion is risking the NCR
capability to maintain its key role as the bread basket of Indonesia. At the household
level, it is not always true that those who are involved in irrigated land conversion will
have diminished welfare.

This study assessed the impacts of irrigated land conversion on the welfare of the
households involved in irrigated land conversion. Using data from the Project of Land
Conversion in Java, Center for Agro Economic Research (PAE), this study compared the
welfare of the farming households before and alter irrigated land conversion. The data
represent on-farin, off-farm, and total income of 52 households involved in irrigated land
conversion in the NCR over the last ten years (see Section 3.1.2. ). In this study, the
household welfare is measured by total household income per year. The household
income value before land conversion is converted into the 1992 value, the year after the
land conversion household income is measured, using an inflation rate of 9.0 percent per

year. With the standardized value of income, the level of income before and alter land

 

 

134
conversion can be compared using t-tests for paired-samples method such as discussed in

Section 3.3.2.5.
Results of the analysis are summarized in Table 18. It includes average households
income on-farm, oE-farm, and total income before and after land conversion.

Table 18. Difi'erences in On-farm, Ofilfarm, and Total Incomes (Rupiah, Rp.) of Farming
Households Before and Alter Irrigated Land Conversion during the Period of

 

 

 

 

 

1982-1992.
Sources 011 Mean of Household Income Mean of Paired Significant
Income (Rp./Y ear) Differences Difference
Before Land Conversion After Land Conversion
fight-farm 1,576,587.62 2,102,767.88 -526,l80.26 ""
-farm 1,460,608.96 2,075,777.40 -615,168.44 ""*
Total 3,037,196.58 4,178,545.29 -1,141,348.71 "*"

 

 

 

 

 

 

 

Source: HmsehddvaeyConmaedbymerjeaongriadmrdIandComemionmJavameCenmr
for Agro Economic Research (PAE), 1993.

Significance Level :

* 20 percent ”" 10 percent "m" 1 percent

5‘ 15 percent "" 5 percent

Table 18 shows that total household income afier land conversion is very significantly
higher than that before land conversion (confidence level of 99 percent or a = 0.01).
Income increases fiom Rp. 3,037,196.58 to Rp. 4,178,545.29, an increase of Rp.
1,141,348.71 or 37,58 percent. This indicates that the welfare of the households increased
due to the conversion of irrigated land.

Comparing total income with on-farm and ofllfarm income, Table 18 also shows that
on-farm and off-fann household incomes afier land conversion are significantly higher than
those before land conversion. It is expected that the ofl-farm income is higher after land

conversion.

135
Surprisingly, the result of the analysis also Shows that the on-farm income is higher

after the households conducting land conversion. This is unlikely true unless the
households involved in land conversion acquire more agricultural land after land
conversion. Further analysis conducted in this study verifies the suspicion. In fact,
average household irrigated land significantly increases from 1.0665 ha per household
before land conversion to 1.2628 ha per household after land conversion, an increase of
0.1962 ha per households (confidence level of 95 percent or a = 0.05). This indicates that
the households uses the return from land conversion to further invest in other irrigated
lands, resulting in higher hectarage of irrigated land.

An additional question pursued in this study is whether the household's decision to
convert land economically rational. If it is, then, it may be expected that regional land
conversion is primarily dictated by market prices and that government policy does not
significantly affect household decisions regarding land conversion.

The decision is an econonrically rational one if on-farm incomes of the households
not involved in land conversion is insignificantly difi‘erent from the after land-conversion
on-farm income of those involved in land conversion. For the purpose of this analysis,
on-farm income after land conversion of those households involved in land convern'on is
compared with on-farm income of households not involved in land conversion using the
t-test for two independent samples (see Section 3.3.2.5). The samples of the households
not involved in land conversion is also based on the data provided by the Project of Land
Conversion in Java (see Section 3.1.2. for detail). The result of the analysis is presented in

Table 19.

136

Table 19. Difli‘ences between A fter-Iand-Conversion-On—farm Income of the Households
Involved in Land Conversion and On-farm Income of Those not Involved in
Land Conversion, 1992

 

Mean of Household Income Mean of Significant
(Rp./Year) Differences Difference

After Land Conversion No Land Conversion

 

 

lOn-farm 2,102,767.88 1,564,273.75 53 8,494. 13

 

 

 

 

 

 

 

Source : Household Survey Conducted by the Project of Agricultural land Conversion in Java, the Center
for Agro Economic Research (PAE), 1993.

Significance Level :

‘ 20 percent “" 10 percent ”"" 1 percent

“ 15 percent "" 5 percent

It shows that no significant difference exist in the means of the on-farm income of
those not involved in land conversion and the after land-conversion on-farln income of
those involve in land conversion. This indicates that farm households in the NCR will
convert their land if it is economically profitable; otherwise, they will not. This implies
also that the government will not be able to restrict agricultural land conversion in the
NCR unless the govermnent promotes indirect policy measures in the agricultural and
nrral sectors which enhance farm household incomes and profitability of agricultural

enterprises.

5.6. Structural Changes in Regional and Rural Village Employment

Modernization theory of urbanization asserts that urbanization is accompanied by
regional structural change in employment. In other words, regional urbanization is
accompanied by a decrease of percentage of population working in agricultural-related
activities and increases in the percentages of people employed in industrial and service-

related activities.

 

137
This section describes structural changes of regional and rural employment in the

NCR assessed at the village level during the period of 1982-1992. The primary focus of
the analysis is to determine if the percentage of people employed the agricultural sector in
the region during the last ten years has decreased; and, whether the trend also occurs in
the nrral areas. The analysis uses a paired t-test similar to the previous in Section 3.3.2.5.

The results of the analysis are summarized below (Table 20).

Table 20. Differences in the Regional and Rural Area's Employment Structure between

 

 

 

 

 

 

 

 

 

 

1982 and 1992
Percent of Population Mean of Significant
Types of Employment Paired Differences
1982 1992 Differences
In E NCR :
Agricultural Labor 22.4864 22.2720 0.2143
Farmer (operator) 24.0291 12.2289 11.8002 ""*
Sharecroppers (sakap) 20.1564 14.7836 5.3727 ”"*
Manufacturing Labor 1 1.9532 22.4200 -10.4668 "*"
Small Scale Enterprise 7.5334 11.0880 -3.5545 "*"
Government Oficial 4.4484 6.1586 -1.7102 "*“
Private Enterprise 4.0159 5.7039 -1.6880 "*"
Others 5.3780 5.3452 0.0327
Inthe Rm MofmgNCR:
Agricultural Labor 28.5929 34.8946 -6.3017 "
Farmer (operator) 31.1454 17.9908 13.1546 ""*
Sharecroppers (sakap) 26.1000 22.9992 3.1008
Manufacturing Labor 2.5258 6.2729 -3.7471 ""*
Small Scale Enterprise 7.1371 11.8246 -4.6875 ""
Government Oflicial 1.7463 3.1683 -1.4221 *”*
Private Enterprise 0.7646 1.2521 -0.4875 *""""
Others 1.9883 1.5996 0.3887
Source : Primary Data (Village Survey)
Significance Level :
“ 20 percent “W 10 percent "*" 1 percent
0* 15 mt *tlt 5 mm

 

 

138
Regional and rural structural changes in employment during the period of 1982-1992

are identified. Since the analysis is conducted at the village level, the types of employment

described in this study are somewhat difi‘erent from those usually used in the analysis of

regional structural change of employment in the regional economic literature. Village

employment, in this study, is classified on the basic of the largest share (more than 50 %)

of employment contributing to total individual income. Eight types of employment are

identified :

1. Agricultural labor, percentage of the village population engaged in agriculture by
providing labor input to farm enterprises.

2. Farmers, percentage of the village population engaged in agriculture by operating their
own agricultural enterprises.

3. Sakap/sharecroppers, percentage of the village p0pulation engaged in agriculture
through either land leases or sharecropping.

4. Manufacturing labor, percentage of village population supplying labor input to
manufacturing sector.

5. Small scale enterprises, percentage of the village population engaged in subsistence,‘
small scale trade without labor inputs outside the household.

6. Government officials, percentage of the village population employed in the public
sector.

7. Private enterprises, percentage of the village population employed in the local business
sector using outside labor input.

8. Others, percentage of the village population engaged in other activities.

 

139
At the regional level, Table 20 shows that village employment in 1982 is composed

of 22.49 % agricultural labor, 24.03 % farmer, 20.16 % sharecropper, 11.95 %
manufacturing labor, 7.53 % small scale enterprise, 4.45 % government oficial, 4.02 %
private enterprise, and 5.38 °/o others. This employment structure is very significantly
different from 1992, in which, the village employment was composed of 22.27 %
agricultural labor, 12.23 °/o farmer, 14.78 °/o sharecropper, 22.42 °/o manufacturing labor,
11.09 % small scale enterprise, 6.16 % government omcial, 5.70 % private enterprise, and
5.35 % others.

Although there is no significant change in the percentage of agricultural labor, the
percentages of farmer and sharecropper have decreased very significantly in the region
during the period 1982-1992 (confidence level of 99 percent or a = 0.01). The percentage
of self-employed farmers decreased by 49.11 percent from 24.03 percent in 1982 to 12.23
percent in 1992. The percentage of sharecroppers decreased by 26.67 percent from 20.16
percent in 1982 to 14.78 percent in 1992.

Employment in the manufacturing, small scale enterprises, the government sector, and
the private enterprise sector, meanwhile, grew very significantly in the region during 1982-
1992 (confidence level of 99 percent or a = 0.01). Employment in the manufacturing
sector increased by 87.62 percent from 11.95 percent in 1982 to 22.42 percent in 1992.
Small scale enterprise employment increased fiom 7.53 percent in 1982 to 11.09 percent
in 1992, a growth of 47.28 percent. Employment in the government sector increased by

38.43 percent, an increase from 4.45 percent in 1982 to 6.16 percent in 1992. Finally,

 

140
private enterprise employment increased from 4.02 percent in 1982 to 5.70 percent in

1992, a growth of 41 .79 percent.

These figures show that at the aggregate regional level of the NCR, a decrease of
employment in the agricultural sector is accompanied by a high increase of employment in
the manufacturing sector. In other words, the regional structural change of employment
is characterized by a decrease of employment in the agricultural sector and shift of
employment to the manufacturing sector. It means that urbanization in the NCR is
accompanied by a structural change of employment such as asserted in modern
urbanization theory.

On the other hand, the structural change of employment in the nrral areas of the NCR
is of a different magnitude than that of the region as a whole. In rural areas, village
employment in 1982 is composed of 28.59 % agricultural labor, 31.15 % farmer, 26.10 %
sharecropper, 2.53 °/o manufacturing labor, 7.14 °/o small scale enterprise, 1.75 %
government sector, 0.76 % private enterprise, and 1.99 % others. This structure is
significantly difi'erenr fiom that in 1992, during which, village employment was composed
of 34.89 % agricultural labor, 17.99 % farmer, 23.00 % sharecropper, 6.27 %
manufacturing labor, 11.82 % small scale enterprise, 3.17 % govemment sector, 1.25 %
private enterprises, and 1.60 % others.

Different fi'om the regional aggregate, it shows a significant increase in the percentage
of agricultural labor in the nrral areas from 28.59 percent to 34.89 percent, an increase of
22.04 percent (confidence level of 80 percent or a = 0.20). The percentage of farmer

decreased very significantly by 42.25 percent fiom 31.15 percent in 1982 to 17.99 percent

 

141
in 1992 (confidence level of 99 percent or a = 0.01). No significant decrease is apparent

in the percentage of sharecroppers during the same period.

Employment in manufacturing and private enterprises in rural areas grew very
significantly during this period (confidence level of 99 percent or or = 0.01). Meanwhile,
employment in small scale enterprises and the government sector grew significantly
(confidence level of 95 percent or or = 0.05). Manufacturing employment increased by
147.73 percent from 2.53 percent in 1982 to 6.27 percent in 1992. Small scale enterprise
employment increased from 7.14 percent in 1982 to 11.82 percent in 1992, a growth of
65.55 percent. Government employment increased by 81.14 percent from 1.75 percent in
1982 to 3.17 percent in 1992. Finally, the private enterprise employment increased from
0.76 percent in 1982 to 1.25 percent in 1992, a growth of 64.47 percent.

Five fundamental difi'erences between nrral and regional structural changes of
employment exist. First, to the period, rural employment is still dominated by agricultural
employment. Second, the percentage of agricultural labor in rural areas increases
significantly at 22.04 percent. This increase is much higher than that in the region at only
0.95 percent. Third, although employment in the manufacturing sector in nrral areas
increased very significantly, the increase is higher than that in the region at 147.73 percent
and 87.62 percent, respectively, but its absolute value is much less than that of the region.
Forth,theincreaseofsmallscaleenterpriseishigherinruralareasthanthatintheregion
at 65.55 percent and 47.28 percent, respectively. Finally, the employment ratio in private

enterprisesintheruralareasismuchlessthanthatintheregionasawhole.

 

142
These figures imply that at the regional level : (i) a decrease of the employment in the

agricultural related activities is followed by a significant increase in the employment in the
manufacturing industries and small scale enterprises; and (ii) a decrease in the percentage
of self—employed farmer is not followed by an increase in employment in the agricultural
sector, an indication that manufacturing industries and small scale enterprises have the
capacity to absorb farmers displaced from the agricultural sector. Meanwhile, for rural
areas the figures imply that : (i) a decrease of the employment in the agricultural sector is
not followed by a significant increase in the employment in the manufacturing sectors; and
(ii) a decrease in the percentage of self-employed farmers is followed by an increase in
employment in agricultural laborer and small scale enterprises, an indication that displaced
farmers in rural areas are either being employed as future agricultural laborers or entering

the labor force of small scale enterprises.

VI. REGIONAL DEVELOPMENT OF THE NORTHERN COASTAL REGION
OF WEST JAVA (NCR)
6.1. Regional Development of the NCR

Regional development of the NCR cannot be separated from regional development of
Jakarta-West Java as a whole, in which West Java has been designated as the hinterland of
Jakarta (see Section 1.2.1. and Section 2.2.3.). In this regional development framework,
sectoral development, especially industrial development, which is "deemed saturated” in
Jakarta is to be developed in West Java (Hamer et al., 1986). This indicates that
development in the region favors areas with better infi'astructure and proximity to the seat
of government. Since the NCR has a better infrastructure and proximity to Jakarta, the
industrial development in West Java is more concentrated in this region (Hill, 1992b).

This study confirms Hill's assertion that the government policy to subsidize medium
and large-scale industries (see Section 1.2.1) results in a higher degree of industrialization
in the region. Instead of calculating the value added, this study assesses the increased
number of industries during the period of 1982-1992. The increased number of industries
indicates a higher degree of industrialization in the NCR

Table 21 summarizes the result of mean comparison in the number of industries
between 1982 and 1992. In this analysis, the industry is categorized as : (i) large scale
industry, i.e. an industry with more than or equal to 100 employees; (ii) medium scale
industry, i.e. an industry with more than or equal to 20 but less than 100 employees; and
(iii) small scale industry, i.e. an industry with more than or equal to 5 but less than 20
employees. Changes in the degrees of regional industrialization are assessed at the village
level using the method presented in Section 3.3.2.5.

143

144

Table 21. Differences in Regional Industrialization between 1982 and 1992

 

 

 

 

 

 

 

 

 

 

 

Number of Industries in the Mean of Significant

Types of Industry Villag: Paired Differences
1982 1992 %-Change Difi‘erences

In the NCR :
Large scale industry (LSI) 0.0909 4.4091 4750.50 -4.3182 ””*
Medium scale industry (MSI) 0.7273 2.6136 259.36 -1 .8864 *"
Small scale industry (SSI) 6.0909 11.0455 81.34 -4.9545 ""
LSI /1,000 village population 0.0177 0.7709 4255.37 -0.7S32 "*“
MSI/l,000 village population 0.1343 0.4052 201.71 -0.2709 *"
SS1/1,000 village population 0.9514 2.1286 123.74 -1 . 1773 ""
Source : Primary Data (Village Survey)
Significance Level :
e 20 W on 10 W on“ 1 page,“

“ 15 percent “" 5 percent

Table 21 shows that the village's average number of large scale industries increased
very significantly from 0.0909 in 1982 to 4.4091 in 1992, an increase of 4.3182 or
4750.50 percent during the period or 475.05 percent annually (confidence level of 99
percent or a = 0.01). The figure also increased very significantly after the number of large
scale industries is weighted by the village population. The village's average number of
medium scale industries increased significantly from 0.7273 in 1982 to 2.6136 in 1992, an
increase of 1.8864 or 259.36 percent during the period or 25.94 percent annually
(confidence level 01‘ 90 percent or a = 0.10). The level of significant of the increased
number of medium scale industries is the same afier it is weighted by village population.
This study also finds that the small scale industries in the NCR increased very significantly
during this period, namely an increase fi'om 6.0909 in 1982 to 11.0455 in 1992, an

increase of 4.9545 or 81.34 percent during the period or 8.13 percent annually.

 

145
In correspondence with the regional development of Jakarta-West Java which

resulted in the increased number of industries of all scales, the NCR region is also affected
the regional development of West Java.

The regional development master plan of West Java was developed in 1974
(Government of West Java, 1990) and is updated every five years along with the five-year
plan for national development. According to this master plan, regional development in
West Java adopts a functional integration rather than a territorial integration as its strategy
of regional planning with " growth centers" as the principal instrument of its spatial policy
(see Section 1.2.1). In this study, a growth center is defined as "induced urbanization
through a combination of direct public investments and capital subsidies to private
enterprise" (Friedman and Weaver, 1979, p.6). Functional integration, meanwhile, is
formed on the basis of mutual self-interests among regions. Given inequalities at the start,
a functional integration is always hierarchical with accumulating power at the top. On the
other hand, the territorial integration is derived fiom common bonds of social order forged
by history within a given place. Although they will also be characterized by inequalities of
power, territorial relationships are tempered by mutual rights and obligations which the
members of a territorial group claim from each other (Friedman and Weaver, 1979;
Friednrarr, 1988).

Such a regional development strategy is biased towards the advantage of urban
development (Friedman, 1988) and characterized by large investment in the urban-
industrial sector (Rondinelli, 1985). There are two important problems associated with

urbanization driven by such a regional development strategy (see Chapter IV). First,

I46
agricultural development will be negatively affected by urbanization (see Chapter V).

Second, rural areas would take part in the general process of growth diffusion only to the
extent that they were subject to the impact of the urban economy (Friedman and Weaver,
1979). In other words, the urbanization process is not associated with social urbanization
and increasing opportunities for development in rural areas (Mehretu, 1989). Therefore, it
can be expected that there are rural-urban disparities in the distribution of the development
benefits as a result of a cumulative causation process (Myrdal, 1957) or self reinforcing
process (see Section 4.1.3.1.)

The previous chapter described changes in several aspects of agricultural
development along with regional urbanization of the NCR. The following section
describes the extent of nrral-urban disparities in the distribution of some benefits of
economic progress, distribution of marketing facilities, and the availability of educational

and health care facilities.

6.2. Rural-Urban Disparities

Rural-urban disparities, in this study, are defined as an uneven distribution of goods,
resources, incomes, and services between rural and urban areas of the NCR (Matthews,
1983). This study does not assume that nrral-urban disparities in the region are created by
lack of resources in the nrral areas and the inability to keep up with the development of
urban areas such as proposed by several studies of regional disparities (Phillips, 1978).
Instead, it assumes that the existence of rural-urban disparities is created by regional

development policies, especially for the regional components that can be affected by the

147

process regional development and its underlying policies. The assumption is based on the
fact that regional policies applied in the NCR favor urban development (see Section 6.1).
This study accepts the fact that distributed regional components resulting from
development contribute to the welfare of the region's inhabitants without entering into the
debate whether those components are subjective or objective measures of rural-urban
disparities. In the literature of regional disparities, assertions about the components
distributed are still not conclusive. Some use distribution of income per capita, wealth, or
a combination of income and wealth as a measure of regional disparities (Smith, 1982).
Others use and develop indicators of well being, quality of life, or standards of living as a
measure of regional disparities (Knox, 1974; Kuz, 1978; Schultink, 1992). According to
Matthews (1983), the meanings of those equity or quality-of-life measures remain vague
and seem to overlap with few clear prescriptions of what is involved in any assessment of
them. Therefore, this study uses only the available census data of 1990 as measures of
rural-urban disparities. This includes some aspects of economic progress, including,
inrprovernents of marketing facilities, educational facilities, and health care facilities which
may result from regional development and afi‘ect the well being of the region's inhabitants.
The distribution of those measures are assessed using the Gini Coefficients (G03) and
the Lorenz curves. The Gini Coeficient is a system measure in which it can describe the
magnitude of the distribution with only using one single coeficient. A value of the GC
ranges between 0 and 1. The value of GC close to 0 indicates equal distribution and the
value of close to 1 indicates unequal distribution. The distribution can also be seen in the

Lorenz curve in which the degree of inequality is shown by how far the Lorenz curve

148
departs fiom the diagonal or equal-share line (Smith, 1982). The proportion of the total

area below the diagonal that is above the Lorenz curve is also a measure of the GC. Since
the GC and Lorenz curve are system measures, the spatial concentration of specific
components are measured using Location Quotients (LQ's). Using the LQ’s, the
concentration of the components in each sub-region of the NCR can be compared. A
value of LQ less than 1 indicates that the sub—region's share in the components in question
is less than the region's share; and, the value of LQ more than 1 indicates that the sub-
region's share is higher than that of the whole region.

The methods used to calculate the values of the GC's and LQ's, and the method used
to construct Lorenz curve are presented in Section 3.3.2.4. The data used to analyze
rural-urban disparities are 1990 census data. The analysis addresses the results of the
development process reflected in the spatial distribution to public benefits. This study
does not consider distribution of development benefits among social strata due to limited

availability data.

611- Wm
Several studies in the NCR indicate that there has been a significant progress in the

economy of the region. This progress is indicated by the increased relative share of
industries and services with their increased value added contributions to the regional
economy (Hill, 1992b, Soemarwoto, 1992). In addition, this study also indicates that in
the last ten years there were significant increases in the number of industries of all scales,
the percentage of population engaged in the manufacturing sector, the numbers of

economic institutions (such as banks), and improvements in public transportation and its

I49
infrastructure, educational facilities, and health care facilities (see Table 8 and Table 21).

All of the increases indicate a growing regional economy.

Since the regional development policies have been in favor of urban development, it is
expected that the benefits of growing regional economy are concentrated in urban areas
and a small portion of the region's inhabitants. In this study, the benefits of a growing
regional economy are indicated by the increased number of households with telephone,
electricity, or with television—indicators of the increased household economic well-being.
Using these indicators, the spatial distribution of benefits of regional economic
development can be assessed. The results of the analysis are summarized in Table 22 and
Figure 10.

Table 22 summarizes : (i) the Location Quotients (LQ's) of the households with
telephone, households with electricity provided by PLN (Perusahaan Listrik Negara)—a
monopolistic agency providing electricity to the nation, and households with television for
each sub—regions of the NCR; (ii) the Gini Coemcients (GC's) of those indicators in nrral
areas, urban areas, and the NCR; (iii) the distribution (percentage) of the indicators and
population in each sub-regions of the NCR; and (iv) the cumulative percentages of the
indicators and population which indicate the concentration or distribution for specific
percentage of population in the region.

Figure 10 presents Lorenz curves showing the inequality in the distribution of the

NCR households with telephone, electricity, or with television in relation to the NCR

population.

150

Table 22. Location Quotients (LQ); Gini Coefficients (GC); Percentage Distribution
Number of Telephones (Phone), Houses with Electricity (Elect), Television
(TV), and Population (Pop) by Village; and Data for Lorenz Curve in the

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cum. % NCR Population
25 El 8 8 8 8 3 8 8

 

.é

 

 

 

 

 

W

0

700 mm

Om%d‘Aqxuof&.Huyu

 

 

 

NCR, 1990.
ImtionQuotients Percentage Cumulative
Region Q) Distribution Ptarcentages ‘)
Phone Elect TV Phone Elect TV m Phone fl Elect TV REL.
R1 0.50 0.17 0.26 3.86 1.33 1.97 7.68 85.27 10.39 33.41 10.39 58.22 10.39
R2 0.00 0.41 0.32 0.04 11.16 8.67 27.06 89.31 12.46 39.01 12.46 62.84 12.46
10 0.08 0.74 0.38 2.37 21.27 11.02 28.76 93.17 20.14 43.26 15.04 66.28 15.04
R4 0.12 0.98 0.55 1.75 13.92 7.80 14.27 95.19 27.33 52.32 22.23 70.54 22.23
U1 0.28 1.26 0.59 2.02 9.06 4.26 7.19 95.84 29.91 66.24 26.50 78.34 26.50
U2 0.25 1.65 1.33 0.65 4.25 3.44 2.58 97.59 44.18 87.51 65.26 89.36 65.26
U3 1.95 2.71 2.23 4.04 5.60 4.62 2.07 99.96 72.94 98.67 92.32 98.03 92.32
U4 8.21 3.22 5.60 85.27 33.41 58.22 10.39 100 100 100 100 100 100
Gieroefl'rcient SourceofDatasPopulationCensusof1990
(CC)
NCR 0.77 0.30 0.51 ‘) CumulativePercentagesarecalculatedbasedontherankoftheirloeation
Rural 0.41 0.18 0.09 quotient values, and are used to construct Lorenz Curve
Urban 0.46 0.1_8 0.04

Figure 10. Lorenz Curves for the Distribution of the Households with Telephone, with
Electricity, and with Television in Relation to Population, by Sub-regions of
the NCR (Source : Table 22)

151
The Gini Coefiicient of the households with telephone in the NCR is 0.77, indicating

that households with telephone are unequally distributed in the region. This high value of
the GC is also represented by the distance of the Lorenz curve to the equal-share line.

The Location Quotient values show that the households with telephone are
concentrated in the most urbanized region, U3 and U4 with values of 1.95 and 8.21,
respectively. This indicates that most of the households with telephone are located in the
most urbanized area (U4). The population of U4 represents only 10.39 percent of the
NCR population but enjoys 85.27 percent of total number of telephones in the region.

The number of households with telephone between rural and urban areas also seems
very unevenly distributed. The total population of the urban areas is 22.23 percent of the
NCR population and enjoy 91.98 percent of total telephones in the region. On the other
hand, 77.77 percent of the NCR population who live in the rural areas enjoy only 8.02
percent of total telephones in the region.

Both within rural and urban areas, the households with telephone are also unequally
distributed. These are indicated by high values of Gini Coemcients of the households with
telephone both in rural and urban areas of 0.41 and 0.46, respectively. This indicates that,
besides urban population, only the elite p0pulation in rural areas enjoys this convenience.

The distribution of households with electricity is similar to the distribution of
households with telephone and is more concentrated in urban areas. However, its
concentration is less than that of households with telephone. The Gini Coefiicient of the
households with electricity in the region is 0.30 compared to that of the households with

telephone of 0.77. Nevertheless, this GC value also indicates that the households with

152
electricity is unequally distributed in the region. This unequal distribution of households

with electricity can also be seen in the Lorenz curve of Figure 10.

The values of the LQ's show that the households with electricity are more
concentrated in urban areas with the values between 1.26 in U1 and 3.22 in U4 than in
rural areas with the values between 0.17 in R1 and 0.98 in R4. Region U4 with a
population of 10.39 percent of the regional population enjoys 33 .41 percent of the facility
provided by the government. Comparing rural and urban conditions shows that urban
areas with population of 22.23 percent of the NCR population enjoy 52.32 percent of the
electricity while rural areas with population of 77.77 percent enjoy only 47.68 percent of
this convenience. Mthin rural and urban areas, on the other hand, households with
electricity seem equally distributed with the same GC value.

With the advanced telecommunication technology of satellites and with the capability
to cover all Indonesian islands, it is expected that television would be found relatively
equallydistnbutedinlndonesia. Thisstudyfindsthatthatiscertairrly notthecasesince
there is disparity in the regional distribution of the households with television in the NCR,
the most developed region Indonesia.

The Gini Coefficient of the households with television in the NCR is 0.51, an
indication of unequal distribution. This unequal distribution can also be seen in the Lorenz
curve of the households with television of Figure 10.

The LQ values also show that the households with telephone are more concentrated
in the most urbanized region, U2-4 with values of 1.33, 2.23, and 5.60, respectively. This

indicates that most of the households with television are located in the most urbanized

153
area (U4). The U4 with population of only 10.39 percent of the NCR population enjoys

58.22 percent of total television in the region.

The distribution of the households with television between rural and urban areas also
seems very unequal. Urban areas with a population of only 22.23 percent of the NCR
population enjoy 70.54 percent of the total television in the region.

Within rural and urban areas, households with telephone are also unequally
distributed. These are indicated by high Gini Coefficients of households with telephone
in rural and urban areas of 0.41 and 0.46, respectively. This indicates that only the elite
population in the rural areas might enjoy this convenience. While, within rural areas and
urban areas, households with televisions seem equally distributed with the values of the
GC's of 0.09 and 0.04, respectively.

The unequal distribution of the three indicators show that the benefits of the growing
regional economy of the NCR are enjoyed mostly by urban population and by a small

portion of the rural population.

632- W
This section assesses the distribution of regional marketing facilities in the NCR. It

assesses the distribution of the marketing facilities for agricultural inputs, marketing
facilities for agricultural products, and local markets with permanent buildings.

Since the NCR is the most established agricultural region in the country, it is
expected that marketing facilities for agricultural inputs and outputs would be located in
rural areas or equally distributed in the whole region. This study uses number of kiosks

selling agricultural inputs (KAI) as an indicator of marketing facility for agricultural inputs

154
and number of kiosks selling agricultural products (KAP) as an indicator of marketing

facility for agricultural products. While, market with permanent buildings is used to
indicate the degree of government efi‘ort in developing the local economy since all local
markets are developed and managed by the government.

The results of the analysis are summarized in Table 23 and Figure 11. Table 23
summarizes : (i) the Location Quotients (LQ's) of the markets with permanent buildings
(market), kiosks selling agricultural inputs (KAI), and kiosks selling agricultural outputs
(KAP) for each sub-regions of the NCR; (ii) the Gini Coeflicients (GC's) of those
indicators in rural areas, urban areas, and the NCR; (iii) percentage distribution of the
indicators and population in each sub-regions of the NCR; and (iv) cumulative percentages
of the indicators and population in the NCR

Figure 11 presents Lorenz curves showing the inequality in the distribution of market
with permanent buildings (market), kiosks selling agricultural inputs (KAI), and kiosks
selling agricultural products (KAP) in relation to the NCR population.

Such as expected, the results of the analysis show that kiosks selling agricultural
inputs (KAI) and those selling agricultural products are evenly distributed in the region
andintherural areas. TheGiniCoeficient ofthe distribution ofKAI intheregion and in
rural areas are 0.04 and 0.03, respectively. The Gini Coeficient of KAP, on the other
hand, in the region and in rural areas are 0.15 and 0.08, respectively. These indicate that

both Kiosk selling Agricultural Inputs (KAI) and Kiosks selling Agricultural Products

(KAP) are equally distributed in the region.

155

Table 23. Location Quotients (LQ); Gini Coefficients (GC); Percentage Distribution of
Village Marketing Facilities including Number of Markets with Permanent
Buildings (Market), Kiosks selling Agricultural Inputs (KAI), Kiosks selling
Agricultural Products (KAP), and Population (Pop); and Data for Lorenz
Curves in the Northern Coast of West Java (NCR), 1990.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Location Quotients Percentage Cumulative
Region (LQ) Distribution Percentages ‘)
MammMmmma mammal
R1 0.42 0.86 0.71 3.20 6.64 5.46 7.68 288010.39 2.93 2.58 6.46 2.58
R2 0.86 0.98 0.75 23.20 26.58 20.20 27.06 34.40 12.97 5.28 4.65 28.28 12.97
R3 0.56 1.07 1.00 16.00 30.75 28.89 28.76 37.60 15.04 20.85 18.92 57.17 41.73
R4 0.67 1.09 0.72 9.60 15.57 10.30 14.27 48.00 22.23 51.60 47.68 62.83 48.92
U1 1.45 1.02 0.79 10.40 7.36 5.66 7.19 71.20 49.29 58.96 54.87 83.03 75.98
U2 2.17 1.14 2.50 5.60 2.93 6.46 2.58 80.80 63.56 85.54 81.93 93.33 90.25
U3 1.55 1.14 0.58 3.20 2.35 1.21 2.07 96.80 92.32 92.18 89.61 98.79 97.93
U4 2.77 0.75 2.10 28.80 7.82 21.82 10.39 100 100 100 100 100 100
Gini Coefficient SourceofData : Population Census of 1990
(GC)
NCR 0.26 0.04 0.15 ‘)CumulauvePercentagesarecalculatedbasedcntherankoftheirlocation
Rural 0.10 0.03 0.08 quotientvalues,andareusedtoconstructlbrenzCurve
Urban 0.13 0.09 0.22
1D
”
m +w-_~
g 70 —o—KKAA\IID
a. +Mnka
g. I)
g ..
‘3 .o
i
E so
10
10
no rs fl II 0 N D 711 N n rm
OnSSofMlhet'lgFacfli-a

Figure 11. Lorenz Curves for the Distribution of Market with Permanent Building
(Market), Kiosks selling Agricultural Inputs (KAI), and Kiosks selling
Agricultural Products (KAP) in Relation to Population, by Sub-regions of the
NCR (Source : Table 23).

156
Especially for input kiosks, the Lorenz curve shows that the line is close to the equal-

share line (Figure 11) indicating that spatial distribution is quite equal. This is also
supported by the values of LQ's which are relatively identical for all sub-regions of the
NCR.

However, the Gini Coefficient of the markets with permanent buildings in the region
(0.26) is higher than the other two indicators. This indicates that spatial inequality exist
in the distribution of government markets with buildings as presented by the large area
between Lorenz curve and equal-share line of Figure 11.

The values of LQ's show that markets with permanent buildings are more
concentrated in urban areas with values between 1.45 and 2.77 as compared to nrral areas
with values between 0.42 and 0.67. Urban areas with population of 22.23 percent of the
NCR population enjoy 48.00 percent of facilities while rural areas with population of
77.77 percent enjoy only 52 percent of the facilities.

The distribution of the three indicators shows that marketing facilities developed by
the government (markets with permanent buildings) tend to concentrate in urban areas
while marketing facilities developed through the private initiatives (KAI and KAP) tend to

be more equally distributed in the NCR.

157

6.2.3. Edgcationg! Facilities

This section describes the distribution of pre-college educational facilities in the NCR
which includes the number of elementary schools, the number of secondary schools, and
the number of high schools. The results of the analysis are presented in Table 24 and
Figure 12.

Table 24 summarizes : (i) the Location Quotients (LQ's) of elementary schools
(Elsch), secondary school (Secsch), and high school (Hisch) for each sub-regions of the
NCR; (ii) the Gini Coeficients (GC's) of the indicators in rural areas, urban areas, and the
NCR; (iii) percentage distribution of the indicators and population in each sub-regions of
the NCR; and (iv) cumulative percentages of the indicators and population in the NCR.
Figure 12 presents Lorenz curves showing the inequality in the distribution of number of
elementary schools, secondary schools, and high schools in relation to the NCR
population.

The Gini Coefficient of elementary school the NCR is 0.04 indicating the elementary
schools are evenly distributed in the region such as presented by its Lorenz curve which is
close to the equal-share line of Figure 12.

Although all values of the LQ's in the urban areas are higher than those in rural areas,
the difi‘erences are very small indicating that the elementary school are evenly distributed
in all sub-regions of the NCR. Both within rural and urban areas, elementary schools are

evenly distributed with the GC values of 0.01 and 0.05, respectively.

158

In contrast to the distribution of elementary schools, the distribution of secondary

schools are more concentrated in urban areas with a regional GC value of 0.23. This is

also reflected by The Lorenz curve (Figure 12).

Table 24. Location Quotients (LQ); Gini Coefficients (GC); Percentage Distribution of
Village Educational Facilities including Number of Elementary Schools (Elsch),
Secondary Schools (Secsch), High School (Hisch), and Population (Pop); and

Data for Lorenz Curves in the Northern Coast of West Java (NCR), 1990.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cumulative Pecan of NCR Population

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Location Quotients Percentage Cumulative
Region (LQ) __ Distribution Percentages ‘)
Elsch Secsch Hisch ElschISecsch Hisch _PoL Elsch M [Secsch Pop Hisch Pop
R1 0.98 0.39 0.18 7.50 3.04 1.35 7.68 2.71 2.07 29.49 10.39 50.22 10.39
R2 0.95 0.63 0.38 25.64 16.97 10.31 27.06 15.85 12.46 32.72 12.46 56.50 12.46
R3 0.96 0.82 0.42 27.68 23.64 12.11 28.76 19.01 15.04 43.02 19.65 66.81 19.65
R4 0.91 0.78 0.44 13.05 11.11 6.28 14.27 26.13 22.23 45.24 22.23 69.95 22.23
U1 0.99 1.43 1.43 7.12 10.30 10.31 7.19 33.63 29.91 68.88 50.99 76.23 36.50
U2 1.22 0.86 1.22 3.16 2.22 3.14 2.58 61.31 58.67 79.99 65.26 88.34 65.26
U3 1.31 1.56 3.03 2.71 3.23 6.28 2.07 86.95 85.73 96.96 92.32 98.65 92.32
U4 1.26 2.84 4.83 13.14 29.49 50.22 10.39 100 100 100 100 100 100
Gieroefiicient SourceofDatarPopulation Censusoi 1990
(GC)
NCR 0.04 0.23 0.48 ‘)Cumu1ativePercentagesareca1culatedbasedontherankoftheirlocation
Rural 0.01 0.08 0.06 quotient values, and are used to construct Lorenz Curve
Urban 0.05 0.18 0.25

Figure 12. Lorenz Curves for the Distribution of the Number of Elementary Schools

(Elsch), Secondary Schools (Secsch), and High Schools (Hisch) in Relation to
Population, by Sub-regions of the NCR (Source : Table 24)

159

The Location Quotients show that secondary schools are the most concentrated in the
most urbanized area (U4) with a LQ value of 2.84 followed by U3 with the LQ value of
1.56 and U1 with the LO value of 1.43.

The Gini Coefficient of high schools in the NCR is 0.48 indicating an uneven spatial
distribution of high schools in the region. This unequal distribution can also be seen in the
Lorenz curves of high schools of Figure 12.

The values of LQ's show that high schools are clearly most concentrated in the urban
areas (Ul-4) with values ranging between 1.22 in U2 and 4.83 in U4. The share of the
regional population for urban areas is only 22.23 percent but they contain 69.95 percent of
high schools in the region. In addition, high schools among urban sun-regions are not
evenly distributed such as indicated by the GC value of .25.

The distribution of the three indicators of educational development in the NCR shows
a clear hierarchical distribution of public educational facilities. This distribution reflects an
educational development policy with basic educational facilities equally distributed in the
region with a concentration secondary educational facilities in several regional centers
with the notion that a rural populations who wish to pursue higher education are expected

to go to the regional centers.

160
6.2-4- W

This section describes the distribution of health care facilities in the NCR including
the number of physicians, traditional midwives, and total number of health care providers
which is the summation of number of hospitals, polyclinics, clinics, maternity centers, and
community health care centers. It is important to note that traditional midwives in the
region provided an extended services to local communities in addition to perform delivery,
such as a general treatment of other illnesses. The results of the analysis are summarized
in Table 25 and Figure 13.

Table 25 summarizes : (i) the Location Quotients (LQ's) number of physicians,
traditional midwives (mwife), and total health care providers (care) for each sub-regions of
the NCR; (ii) the Gini Coeficients (GC's) of the indicators in nrral areas, urban areas, and
the NCR; (iii) percentage distribution of the indicators and population in each sub-regions
of the NCR; and (iv) cumulative percentages of the indicators and population in the NCR.
Figure 13 presents Lorenz curve showing inequality in the distribution of physicians,
traditional nridwives, and health care providers in relation to the NCR population.

The Gini Coefficient of physicians in the NCR is 0.63 indicating that physicians are
unevenly distributed over the region. Physicians in the region are concentrated in the most
urbanized region (U4) with the value of LQ of 6.74 followed by U2 with the value of
2.43. The urban areas (U 14) which share to the regional population of only 22.23
percent have 80.50 percent of physicians in the region. The rural areas, on the other hand,

which share regional population of 77.77 percent have only 19.50 percent of physicians in

161

Table 25. Location Quotients (LQ); Gini Coefficients (GC); Percentage Distribution of
Village Availability of Health Care Facilities including Number of Physician
(Physician), Traditional Midwives (Mwife), Health Care Providers (Care), and
Population (Pop); and Data for Lorenz Curves in the Northern Coast of West

Java (NCR), 1990.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

LoeationQuotients Percentage Cumulative
lRegion (LQ) Distribution Percentaes‘)
PhEMwifeCare Mwife!Care£P_hys_Pop_MwifeliP_—<m Care P_op
R1 0.30 1.00 0.82 7.67 7.68 70.08 10.39 3.42 2.58 20.97 10.39
R2 0.16 1.06 0.86 28.76 27.06 75.10 12.46 5.97 4.65 23.48 12.46
R3 0.22 0.94 0.84 21.63 28.76 79.15 19.65 34.73 31.71 26.54 15.04
R4 0.40 0.98 0.92 19.44 14.27 80.50 22.23 42.40 39.39 44.87 34.97
U1 0.56 0.86 0.86 6.18 7.19 88.42 42.16 52.75 49.78 68.06 62.03
U2 0.52 1.33 1.19 3.42 2.58 90.73 49.84 72.19 69.71 74.24 69.22
U3 2.43 1.23 1.21 2.55 2.07 95.75 72.94 93.82 92.81 93.74 92.32
U4 6.74 1.00 2.02 10.35 10.39 100 100 100 100 100 100
Gieroeflicient Sourceof Data : Population Census of 1990
QC)
NCR 0.63 0.03 0.12 *)CumulauvePercentagesarecalcu1atedbasedcntherankofthcirlocauon
Rural 0.17 0.02 0.02 quouentvalues,andareusedtoconstmctlbrenzCurve
Urban 0.40 0.20 0.17
I)» =i=%=e
5 i +Damn
'3 m, —o—deivra
g, +Cm
n. so
6 50..
Z
“5 to
*1 a)
e
5 20
".1ssaszssam
Ctm%of1~1ulthCleRdIedFmiliies

Figure 13. Lorenz Curves for the Distribution of the Number of Physicians, Midwives, and

Total Health Care Providers (Care) in Relation to Population, by Sub-regions
of the NCR (Source : Table 25)

162
the region. Within urban areas, the physicians are also unevenly distributed among the

sub-regions with the GC value of 0.40.

If physicians represent modern treatments in health care, the midwives represents
traditional care in child birth. The assessment shows that traditional midwives are evenly
distributed over space indicating that traditional treatments in health care are still popular
both in nrral and urban areas of the NCR. This also indicates that this traditional
distribution is rooted in the local culture and is more eficient in delivering services to the
regional population. Table 25 and Figure 13 show that traditional midwives are evenly
distributed over all sub-regions of the NCR with the GC value of 0.03. The LQ values are
also similar among the sub-regions.

The Gini Coefiicient of total health care providers in the NCR is 0.12 indicating that
the health care providers are evenly distributed over space. However, the values of LQ
arestillhigherisurbanareasthanthoseinruralareasindicatingthaturbanareasenjoyeda

larger share of health care providers than nrral areas.

 

 

VII. SUMMARY AND POLICY INIPLICATIONS

Urbanization in the Northern Coastal Region of West Java (N CR), both as a corridor
region connecting Jakarta-Cirebon and as a region designated as the bread basket of
Indonesia, represents a very interesting phenomenon in Indonesian agricultural and
regional development. The region has the best irrigation systems and agricultural
development institutions in Indonesia. It has long been the center of agricultural
development and has been used as a model of agricultural development in Indonesia. This
agricultural region currently faces massive urbanization pressures due to regional
industrialization and regional development policies favoring urbanization.

Several agricultural development policies have shaped the agriculture in the region.
At the national level, the Government of Indonesia's (GOI's) goal was to maintain
Indonesia's rice self-sufiiciency, i.e. the. status of the mid-eighties. Consequently, the
status of the NCR as the bread basket of Indonesia will likely be maintained. For this
purpose, the GOI still maintains its current agricultural policies such as regulating floor
and ceiling prices of agricultural conunodities, subsidies in the development and
rehabilitation of irrigated paddylands, the provision of agricultural inputs, and the
developing a bufl‘er system to anticipate price fluctuations in agricultural commodities.
Most importantly, through a Presidential Decree and regional development planning, the
GOI restricts agricultural land conversion (especially irrigated paddy land) into non-
agricultural uses, reflecting the reality that urbanization has created development

pressures on agricultural lands.

163

164
However, regional development policies implemented in the NCR seem to contradict

with the GOI's intention to maintain the region as the bread basket of Indonesia. Regional
development of the NCR is a part of the development of Jakarta~West Java. In the
framework of Jakarta-West-Java regional development, West Java is designated as the
hinterland of Jakarta. More importantly, sectoral development, especially industrial
development, which is "deemed saturated" in Jakarta is to be targeted for West Java. This
indicates that development favors areas with a better infrastructure and proximity to the
seat of government. Since the NCR has a better infrastructure and proximity to Jakarta,
industrial development in West Java is more concentrated in this region.

In correspondence with the regional development of Jakarta-West Java which has
resulted in industrial concentration, the NCR region is also affected by the regional
development of West Java. The regional development plan of West Java adopts a
functional integration rather than a territorial integration as its strategy of regional
planning with ”growth carters" as the principal instrument of its spatial policy. The
growth center policy is an induced urbanization through a combination of direct public
investments and capital subsidies to private enterprises (or the private sector). Functional
integration, meanwhile, is a strategy based on the mutual self—interests among regions.
Given inequalities at the start, functional integration is always hierarchical with
accumulating power at the top. On the other hand, although it is characterized by
inequalities of power, territorial relationships are tempered by mutual rights and

obligations among members of the territorial group.

165
A regional development strategy based on a functional integration is biased towards

urban development and characterized by large investment in the urban-industrial sector.

Two important problems are associated with urbanization driven by such a regional

development strategy, namely :

1. Agricultural development will be negatively afi‘ected by urbanization since development
of urban sectors is viewed as the major determinant of regional development.

2. Rural areas would take part in the general process of growth diffusion only to the
extent that they were subject to the impact of the urban economy. In other words, the
urbanization process is not associated with social urbanization and increasing
opportunities for development in rural areas. Therefore, it can be expected that there
are rural-urban disparities in the distribution of the development benefits as a result of a
cumulative causation process or self reinforcing cycle.

The general objective of this study was to provide a better understanding of the
urbanization process and its causal factors, its relationships with regional development,
and most importantly its impacts on the agricultural development in the region. The
underlying notion was that a better understanding of urbanization as an interactive process
provides a useful means to identify alternative policy interventions to sustain a viable
agricultural sector. Therefore, this study addressed the following objectives :

1. An analysis of urbanization in the NCR and the identification of associated factors such
as changes in land tenure, in the agricultural economy, in demographics, educational
opportunities, and the development in public facilities, industrial development, and

proximity to primary cities.

166
2. A description of the impacts of urbanization on the agricultural development, especially

land tenure including the structure of land ownership, the degree of absentee land
ownership, and agricultural prime land conversion and its subsequent impact on
agricultural household income, and on the nrral and regional structure of employment.

3. A description of the spatial impacts of urbanization on the distrrbution of agricultural
resource base, the distribution of public facilities, and the disparities in economic
development in the rural and urban areas within the region.

4. A description of the functional relationship among urbanization, regional planning, and
agricultural development in the region.

5. An examination of policy implications regarding sustainable agricultural and overall
development planning in the NCR.

This chapter summarizes the research findings, presents potential policy implications

of these findings, and identifies needs for further research.

7.1. Summary of Findings

Five important findings results from this research, including : (i) regional urbanization
process and its underlying causal factors; (ii) level of regional urbanization; (iii) impacts of
urbanization on the regional agricultural development, especially on the structure of land
ownership, the degree of absentee land ownership, agricultural prime land or agricultural
land conversion with its subsequent impact on the agricultural household income, and the
structure of nrral employment; (iv) regional industrialization, and (v) rural-urban

disparities.

167
1. Process of Urbanization.

Regional urbanization during the period of 1982-1992, as measured by rate of change
in population density, is caused by three groups of factors : (i) rural factors or push
factors, (ii) urban factors or pull factors, and (iii) demographic factors. Multiple
regression analysis found that 76.84 percent of urbanization can be explained by those
three groups of causal factors. From this total explanation, rural factors contribute 45.40
percent or 59.08 percent of the explained urbanization. Urban factors contribute 24.72
percent or 32. 17 percent of the explained urbanization and demographic factors contribute
6.72 percent or 8.7 5 percent of the explained urbanization.

Among rural factors, increase in the agricultural land parcelization (i.e. increased
landless households and decreased households with agricultural lands) contributes 28.16
percent or 36.65 percent of the explained urbanization or 62.03 percent of the rural
factors. The contribution of the agricultural land parcelization in explaining regional
urbanization is higher than all pull factors (24.72 percent). Changes in the agricultural
economy (i.e. decreased real agricultural labor wage, increased nrral land prices, and
changes in the village structure of employment) contributes 17.24 percent or 22.44
percent of the explained urbanization or 39.97 percent of rural factors. Increase in the
agricultural land conversion contributes 12.38 percent or 16.11 percent of the explained
urbanization or 27.27 percent of rural factors. Finally, increase in the absentee land
ownership contributes 8.62 percent or 11.22 percent or 18.99 percent of rural factors.

Among urban factors, increases in the availability of public facilities explains mostly

the regional urbanization and followed by increases in the availability of pre—college

168
educational facilities. Surprisingly, besides the facts of the increased industrialization in

the region, this factor insignificantly affects the regional urbanization. Total contribution
of demographic factors on explaining the regional urbanization, meanwhile, only 6.72
percent

These finding show that urbanization process in the NCR is mainly dictated by
worsening condition of agricultural and rural factors in the period of analysis.

Regarding the proximity of the villages to the cities, the analysis shows that village
proximity to Cirebon and to the capital cities of kabupatens do not significantly affect
urbanization in the NCR. Proximity of the villages to Jakarta, meanwhile, afiects regional
urbanization with confidence level of 70 percent. The proximity of the villages in urban
area (urban villages) to Jakarta afi‘ects urbanization process with confidence level of 78
percent. Moreover, the dummy variable of urban area afi‘ects urbanization process with
confidence level of 95 percent, an indication that that urbanization process in the region is

accelerated in the urban areas through self-reinforcing cycle.

2. mdnfficginnalfllbamzatinn
Level of urbanization is defined at the desa or village level by categorizing villages

into nrral villages and urban villages. Number of urban population is defined as the
population in the urban villages. V

Using village's population density of 1,500 people/1cm2 as a cut off to difi‘erentiate
rural and urban villages in the NCR, this study finds that during the period of 1980—1990
the number of urban villages in the region have increased from 151 villages to 223 villages

or fi'om 13.74 percent to 20.29 percent. This means that in this period, the village

 

’19.,

s . ..otmma 4

169
urbanization rate in the region is 47 .67 percent or 4.77 percent per year. Similarly, the

urban population has increased from 1,179,362 people to 2,439,996 people or from 25.69
percent to 38.75 percent. This means that, during this period, the urbanization rate related
to population growth in the NCR is 106.89 percent or 10.69 percent per year.

The analysis of temporal rate of change in population density (TRCPD), furthermore,
shows that population density increased throughout the region. However, the TRCPD
decreases from the most urbanized area to the most rural area. The mean of TRCPD of
urban area is 115.57 people/kmzlyear and that in nrral area is 12.76 people/kmzlyear,
indicating that annual increase of the population density in the urban area is 9.01 times of
that in rural area. This means that regional urbanization rate is higher in the areas with
higher population densities. This situation may imply that there exists a preference to
locate in urban areas due to the perception of a higher quality of life.

The analysis of spatial rate of change in population density (SRCPD), a spatial
differences in the degree of population concentration over distance from the capital city of
kabupaten, shows that the values of SRCPD are very low in all kabupatens in the region.
The SRCPD in the NCR, Bekasi, Karawang, Subang, and lndramayu are 0.0441, 0.0443,
0.0485, 0.0440, and 0.0417, respectively. This means that in Bekasi, for example, for
each kilometer farther fiom the capital city of kabupaten the population density declines by
0.0443 people per square kilometer. This implies that there is no significant differentiation
in the population density over distance fiom the capital city of kabupaten. Therefore, the

rank size rule may not be the probable distribution of population in the NCR. In other

170
words, the simple negative exponential function, which has been very successfiil model for

the developed countries, is not representative for the NCR.

3. frb'inon 'lr lom

The analysis shows that such a high annual regional urbanization rate is accompanied
by increase in land parcelization characterized by increased landless households, increase
in absentee land ownership, increase in agricultural land conversion to non-agricultural
uses, and structural changes in the village employment both in rural areas and in the NCR
as a whole. The impacts are, however, more staggering in rural areas.

The analysis, at the regional level, shows that the percentage of landless households
has increased during the period of analysis. Households without agricultural dryland
increased by 18.84 percent and those without paddy land increased by 22.84 percent. The
increase of regional landless households is not significantly associated with the decrease of
the percentage of households with < 0.5 ha dryland or < 0.5 ha paddyland. This indicates
that the percentage of subsistence farmers in the region remain largely the same during the
period. Regional agricultural development has, therefore, been unable to reduce the
percentage of subsistence farmers. However, the increase of regional landless households
is associated very significantly with the decreases in the percentage of households with
2 0.5 ha dryland and that with 2 0.5 ha paddy land during the period of analysis.

In the rural areas, changes of the agricultural land ownership have the same
magnitude as those in the NCR as a whole. Landless households increased and the
households with agricultural landholdings decreased. The percentage households without

agricultural drylands and paddylands increased very significantly by 16.95 percent and

171
17.82 percent, respectively. The percentage of households with > 2.0 ha dryland and

those with the same hectarage of paddy land decreased by 58.04 percent and 49.56
percent, respectively.

The analysis also shows that the urbanization is accompanied by increased absentee
land ownership. At the regional level, the total absentee lands and the number of absentee
land owners increased very significantly by 193.20 percent and 43.26 percent or by annual
increases of 19.30 percent and 4.33 percent, respectively. The total hectarage of absentee
lands increased faster than the number of absentee landlords, indicating more concentrated
absentee land ownership.

The increased absentee lands can be attributed mostly to an increase in absentee
dryland rather than to an increase in absentee paddyland. Absentee dryland in the region
increased by 605.94 percent during the period of 1982-1992 or 60.59 percent annually.
Absentee paddyland, meanwhile, increased 42.29 percent during the same period or 4.23
percent annually.

This pattern of increase in absentee dryland is accompanied by a higher number of
absentee landlords acquiring dryland than those acquiring paddyland. Average number of
absentee land owners with dryland increased by 229.34 percent or 22.93 percent annually
and those with of paddde increased only by 18.49 percent or 1.85 percent annually.

While it is more economical to invest in paddyland than that in dryland, the high
increase of absentee dryland in the NCR might be attributed to the increased land
speculation in the region because the land speculators usually have on-hand information

regarding rural lands allocated for urban uses which is rarely an irrigated land. This is

 

’E

 

 

172
especially important given existing the Government of Indonesia's policies prohibiting

conversion of paddyland to non-agricultural uses.

In the rural areas, changes in absentee land ownership are more staggering than those
in the region as a whole. The total absentee lands and the number of absentee land owners
during 1982-1992 have increased by 192.96 percent and 34.77 percent or 19.30 percent.

Comparing the total hectarage of absentee lands (dryland and paddyland), the analysis
shows that absentee dryland increased by 638.06 percent or 63.81 percent annually.
Absentee paddyland, meanwhile, increased by 29.78 percent or 2.98 percent annually.
This pattern is also accompanied by a higher number of absentee land owners acquiring
dryland rather than paddyland. The number of absentee land owners with dryland
increased by 460.18 percent or 46.02 percent annually while those with paddyland did not
increase significantly, indicating that the absentee paddyland in rural areas is also
becoming more concentrated in the hand of absentee owners.

The analysis of agricultural land conversion along with the urbanization process in the
region shows that, at the regional level, the irrigated land decreased by 25.62 percent
during the period of 1982-1992 or 2.56 percent annually while the agricultural dryland
decreased by 27.11 percent or 2.71 percent annually. In the rural areas, the irrigated land
decrease by 25.04 percent during the period of analysis or 2.50 percent annually while the
agricultural dryland did not decrease significantly. This indicates that agricultural land
conversion in the rural areas includes mostly irrigated land, a pillar of regional agricultural

production.

173
At the regional level, the increased irrigated land conversion has put additional

pressures on the NCR capability to maintain its key role as the bread basket of Indonesia.
At the household level, however, this study finds that the households involved in land
conversion are better ofi‘. The total household income increased by 37.58 percent by
converting the land. This study also finds that land conversion in the NCR is mostly
dictated by market price mechanism and that government policy does not significantly
afi‘ect household decisions regarding land conversion.

Regarding the analysis of structural changes in the village employment, this study
finds that there exist five fundamental differences between rural and regional structural
changes of employment. First, in the period of 1982-1992, rural employment is still
dominated by agricultural employment. Second, the percentage of agricultural labor in
rural areas increases significantly at 22.04 percent. This increase is much higher than that
in the region at only 0.95 percent. Third, although employment in the manufacturing
sector in rural areas increased very significantly, the increase is higher than that in the
region at 147 .73 percent and 87.62 percent, respectively, but its absolute value is much
less than that of the region. Forth, the increase of small scale enterprise is higher in rural
areas than that in the region at 65.55 percent and 47.28 percent, respectively. Finally, the
employment ratio in private enterprises in the rural areas is much less than that in the
region as a whole.

These figures imply that, at the regional level : (i) a decrease of the employment in the
agricultural related activities is followed by a significant increase in the employment in the

manufacturing industries and small scale enterprises; and (ii) a decrease in the percentage

174
of self—employed farmer is not followed by an increase in employment in the agricultural

sector, an indication that manufacturing industries and small scale enterprises have the
capacity to absorb farmers displaced from the agricultural sector. Meanwhile, for rural
areas the figures imply that : (i) a decrease of the employment in the agricultural sector is
not followed by a significant increase in the employment in the manufacturing sectors; and
(ii) a decrease in the percentage of self-employed farmers is followed by an increase in
employment in agricultural laborer and small scale enterprises, an indication that displaced
farmers in rural areas are either being employed as fiiture agricultural laborers or entering

the labor force of small scale enterprises.

4. WM
Degree of regional industrialization is measured by changes in the numbers of large

scale industries, medium scale industries, and small scale industries. Large scale industry is
defined as an industry with more than or equal to 100 employees. Medium scale industry
is defined as an industry with more than or equal to 20 but less than 100 employees. Small
scaleindustryisdefinedasanindustrywithmorethanorequalto5butlessthan20
employees. This study finds that during the period of 1982-1992 the degree of
industrialization has increased very significantly. The number of large scale industries
increased by 4750.50 percent during the period or 475.05 percent annually, an increase
from 0.0909 in 1982 to 4.4091. The mrmber of medium scale industries increased by
259.36 percent during the period or 25.94 percent annually, an increase fi'om 0.7273 in
1982 to 2.6136 in 1992. The number ofsmall scale industries increased by 81.34 percent

during the period or 8.13 percent annually, an increase fiom 6.0909 in 1982 to 11.0455 in

 

 

175
1992. These figures show that the development of medium and large scale industries in

the region occurs just recently, in the last ten years, indicating recent growing regional

economy.

5. Rural-Qrbg Dispm'ties

The study finds that there exists rural-urban disparity in the distribution of the benefits
regional economic progress in 1990. This is indicated by the high values of the Gini
Coemcients (GC) of households with telephone, electricity, or with television in which
their GC values are 0.77, 0.30, and 0.51 percent respectively. The economic progress in
the region is more concentrated in urban areas since the Location Quotients (LQ) of the
three indicators are higher in urban areas than those in nrral areas.

The marketing facilities of the kiosks selling agricultural inputs and those selling
agricultural products are evenly distributed in the region with the GC values of 0.04 and
0.15, respectively. However, markets with permanent building are unevenly distributed in
the region with the GC of 0.26 and most of them are concentrated in urban areas such as
indicated by its LQ which is higher in urban areas than in rural areas.

The elementary schools are evenly distributed in the region with the GC of 0.04 and
the LQ's of relatively similar between nrral and urban areas. The secondary schools are
unevenly distributed in the region with the GC of 0.23 with concentration mostly in urban
areas indicated by its LQ which is higher in urban areas than in nrral areas. The high
schools, meanwhile, are also unevenly distributed in the region with higher GC of 0.48
with concentration mostly in urban areas indicated by its LQ which is higher in urban areas

than in rural areas.

176
The study also finds that physicians are mostly concentrated in urban areas in which

with only 22.23 percent of regional population, the urban areas enjoy 80.50 percent of the
physician in the region (GC = 0.63). On the other hand, traditional midwives and total

health care providers are evenly distributed in the region with GC's of 0.03 and 0.12,

respectively.

7.2. Policy Implications

Research findings suggest that without any further government policy interventions in
both regional and agricultural development future agricultural sustainability cannot be
maintained. This implies that the role of this region as the bread basket of Indonesia will
be threatened. Therefore, the urbanization process in the region is undermining the filture
of Indonesia's self-suficiency in rice. More importantly, the welfare of the population
engaged in agricultural related activities which is 49.28 percent of regional population or
75.88 percent of total rural p0pulation (1992) will also be afi‘ected by the process.

These assertions are supported by the research findings which show that urban and
industrial development have displaced self-employed farmers through increased
agricultural land conversion and increased absentee land ownership. The logical
adjustment process commonly pursued by rural population is to disaggregate the
household agricultural land by means of land conversion and land sales. This land
parcelization results in diseconomies of scale in agricultural enterprises which provides for
additional disincentive for rural population to remain in agriculture. The combined efl‘ects
of increased agricultural land conversion, increased absentee land ownership, and

increased land parcelization will decrease both regional agricultural productivity and

 

 

I77
agricultural production. 0n the other hand, the increased degree of regional

industrialization has been unable to absorb the population displaced fi'om the agricultural
sector. Consequently, they enter the labor force of small scale enterprises or remain in
agriculture as laborers. Since these last forms of employment are characterized by low
economic productivity, the urbanization process, indirectly, diminishes the welfare of nrral
population.

The research findings also suggest that the existing urbanization process will
complicate problems of regional development. The NCR regional development is pursued
through a growth center policy, urbanization is induced by a combination of direct public
investments and capital subsidies to private enterprises to create urban centers which are
expected to difi‘use economic growth into rural areas. The research findings show that the
expected trickle down efi‘ects into rural areas does not occur in the NCR. In fact, the
economic progress and development of public facilities are still concentrated in the urban
areas such as presented by the analysis of rural-urban disparities. Moreover, urbanization
intheregionismostlydeterminedbypushfactorsfi'omagriculturalruralareasinstead of
caused by increased opportunities in urban areas. This implies that, without further
government intervention, future rural-urban dispmties will increase and that increased
economic stress in agricultural nrral areas will drive resource flow into urban areas,
creating further rural-urban disparities.

To sustain the role of this region as the bread basket of Indonesia and to improve the

welfare of rural population engaged in agricultural related activities, government must,

 

 

 

I78
therefore, initiate a broad-based rural development strategy. The strategy must include

policies on :

1. Agljfllturfl land consolidation. Agricultural land consolidation is mainly directed to
mitigate negative effects of diseconomies of scale in agricultural enterprises which
commonly create disincentives for the rural population to remain in agriculture. It is
urgently needed in the region for two fundamental reasons, namely : (i) current regional
industrial and high productivity service sectors are still unable to absorb population
displaced from the agricultural sector, and (ii) to maintain and improve regional
agricultural productivity and outputs by creating economies of scale in agricultural
enterprises.

2. ' ' ' ' ' ultural l d conversion. This policy should be pursued by the
government through indirect policy measures instead of by introducing legislation
which in reality is diflicult if not impossible to enforce. This study shows that household
decisions on land conversion are mainly dictated by land prices and, in fact, increase
farm household welfare. Since this is a decision dictated purely by economic motives, a
direct measure such as the Presidential Decree will be unable to afi‘ect household
decisions regarding land conversion. Assuming that such decree can be enforced, field
observations show that farm households actually change the status of irrigated to non-
irrigated land by making the land idle around two years and subsequently convert this

land to non-agricultural uses.

l79
3. Minimizing absentee land ownership. This policy is directed to make agricultural

enterprises in rural areas economically competitive so that there is no incentive to sell

land.

 

4. Strengthening rurm. This study shows that urbanization is mostly affected by
push factors associated with rural life. Therefore, to indirectly reduce urban migration,
rural areas must be developed to balance urban attraction.

The integrated rural development involving four potential policy initiatives above can

be approached by two scenarios:

 

1. Scenario I : The government still maintains the current regional development strategy, _
namely a growth center policy in which urbanization is induced by a '
combination of direct public investments and capital subsidies to private
enterprises to create urban centers which are expected to diffuse
economic growth into rural areas.

Under this scenario, rural development is pursued along with urban development
(Rondinelli, 1983). Within this framework, the notion of linkages between rural and

urban areas is viewed as very crucial for rural development since major markets for

agricultural surpluses are in urban centers, while the public services are commonly
in ‘
Li? l

located in urban areas. Instead of focusing investments exclusively on rural areas or
urban areas, investment is diversified over space in such manner that secondary cities
can be created to build linkages between nrral areas and secondary cities and between
secondary cities and urban centers. In other words, the focus of this scenario is to
create generative secondary cities which are expected to : (i) relieve pressures on the
largest cities; (ii) reduce regional inequalities since it is expected that secondary cities

will difi‘use the benefits of urbanization; (iii) stimulate the rural economy through the

 

180

provision of public services, enlarging rural market, and facilitating the absorption of
agricultural surplus of labor by urban centers; (iv) provide an increased regionally
decentralized administrative capacity; and (v) help alleviate poverty in intermediate-
sized cities (Rondinelli, 1983).

If the expected roles of the generative secondary cities can be met in the NCR
development, the agricultural sector will develop as a result of expanded local markets
for agricultural products. It discourages, indirectly, agricultural land conversion since
agriculture will remain profitable. In turn, it reduces land parcelization which

commonly results from land conversion. More importantly, this strategy may result in a

 

higher quality of rural life and indirectly will reduce urbanization. ‘

2. Scenario H : The government still maintains current regional development strategies
but gives greater autonomy to local authorities create land use planning
initiatives (Scenario I + greater local autonomy).

Under this scenario, scenario I is broadened with increased local autonomy to

determine local land use destinations. Therefore, in addition to developing generative

secondary cities, the local government must develop regional land use planning and

 

control so that factors afi‘ecting regional agricultural sustainability identified in this
study can be addressed directly and efi‘ectively. Planning must reflect regional
agricultural development goals and its undermining factors in maintaining the region‘s
position as the bread basket of Indonesia. The system of rewards and penalties is to be
incorporated within the fiamework of land use control. The government may buy land
development rights from the people who intend to convert their land to non-agricultural

uses to ensure that land remains in agricultural production. The government may also

 

181
introduce agricultural tax incentives for agricultural development. Similarly, the

government may subsidize the agricultural sector in the provision of agricultural inputs
and marketing of agricultural products, and improve the rural infrastructure. These
policy instruments may reduce agricultural land conversion which undermines the

sustainability of agricultural (development) in the region.

7.3. Needs for Further Research

Further research related to this study may address: (1) proposed policy
recommendations summarized in Section 7.2., (ii) impacts of urbanization on agricultural
development not discussed directly in this study and viewed as very important for firture
agricultural development in the NCR, and (iii) research related to the fact that the NCIL
both as a corridor region adjoining two big cities Jakarta and Cirebon and as major food
production region, faces fundamental changes due to the urbanization of the areas

surrounding Jakarta and Cirebon.

1. Further Research Related to Proposed Polig Recommendations

Policies directed to agricultural land consolidation may accentuate populations
displaced from agriculture. Therefore, before pursuing these policies, further research is
needed to: (i) determine the optimum size of land holdings subject to specific level of
agricultural employment and a specific minimum level of income for rural populations, and
(ii) assess the impacts of land consolidation. In pursuing policies to minimize agricultural
land conversion, the government needs to initiate research to identify direct and indirect

policy measures which guarantee the improved profitability of agricultural enterprises.

 

 

182

2. Further Research Relrged to Impacts of Urbanization on Regional Agicultural
Development

Other prominent impacts of urbanization on agricultural development such as the
changes in the quality of the agricultural resource base as a result of intensive use, soil
and water pollution impacts, and other cumulative environmental impacts of fertilizer and
pesticide use need to be addressed. This additional research is needed to evaluate more

comprehensive impacts of urbanization on agricultural development.

3. Further Research Related to the NCR as a Changing Corridor Regjga

At the regional level, furthermore, the government must adopt and develop
comprehensive measures to deal with urban industrial development and agricultural
development in the hinterlands. To design a comprehensive strategy to deal with changes
in the NCR, the following macro and micro studies are needed to analyze : (i) the
magnitudes of the social and economic changes in the NCR; (ii) changes in land use
patterns and land prices in the area immediately surrounding major cities as well as in
rural areas; (iii) changes in relationships among the region and the metropolitan centers;
(iv) changes in regional socio-economic conditions and its impacts on migration—both
internal migration in the region and migration to metropolitan centers; (v) changes in
settlement patterns; (vi) changes in environmental quality; and (vii) changes in rural-urban
linkages within the region and changes in the urbanized area-metropolitan center linkages.
These research recommendations do not necessarily provide a complete list of research

priorities.

'- 1?? - ,
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