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UNIVERSITY LIBRARIES

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This is to certify that the

dissertation entitled
Bamboo Production in the Philippines: Financial
Analysis at the Small Farmholder Level

presented by

Nicolas S. Uriarte

has been accepted towards fulfillment
of the requirements for

Ph.D. degree in FONStry

 

 

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Date 4303+ 28; '79,

MS U is an Affirmative Action/Equal Opportunity Institution 0-12771

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MSU Is An Affirmative Action/Equal Opportunity Institution

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BAMBOO PRODUCTION IN THE W:
FINANCIAL ANALYSIS AT THE SMALL FARMHOLDER LEVEL .

By

Nicolas Salazar-Oriana

A DISSERTATION

Suhmittedto
MIchiganSteteUniva-rity
Inperflaimlfillmentoftherequirm
forthedegreeoi'

DOCTOR OF PHILOSOPHY

Department of Forestry
1991

ABSTRACT

BAMBOO PRODUCTION IN THE PHILIPPINES:
FINANCIAL ANALYSIS AT THE SMALL FARMHOLDER LEVEL

By

Nicolas Salamr Uriarte

One significant effort pursued by the Philippine government to remedy
problems of rural poverty and underemployment is bamboo production. This study is a
component of the Bamboo Research and Development Project and focuses on the
financial viability and optimal development schedules for bamboo plantations in three
regions of the country, namely: Region 6, Western Visayas; Region 7, Central
Visayas; and Region 11, Northeastern Mindanao. Species evaluawd were B. blwneana,
B. philippinensis, D. aspen D. uranium, and S. Iwnampao.

Financial viability was estimated by calculating costs and revenue streams over
the 25-year project duration for different management schemes (MS) in three regions
of the country. The optimal development schedules, on the other hand, were
determined using linear programming (LP). The two objective functions used were: (1)
maximize NPV of cash flows and (2) maximize the amount of total employment.
Family labor, land and available loan funds were constraints. Primary (survey) data
and secondary data were used to develop the analyses.

Financial evaluations indicate that S-ha bamboo plantations are financially
profitable in 30 of 32 management schemes evaluated. The NPVs, however, vary
depending on management scheme (i.e., species, spacing, harvest schedule, stock

source, site) and region.

Nicolas S. Uriarte

Development schedules of bamboo plantations vary depending on the amount
of family labor contribution (FLC), represented by household type (HT). Variations in
FLC affect timing of plantation development and ultimately NPVs. Depending on HT,
MS, and region, total hectares developed range from 3.62-5.00 he with NPVs in pesos
(P) ranging from P2,010-P286,832.

Considerable employment may be generated through bamboo producrion. For
S-ha plantations, the amount of labor-use ranges from 1075-11331 person-days over
the 25-year period depending on MS and HT. This is equivalent to fully employing 1-
2 members of a household. Potential income from labor wages is estimamd to range
fi'om P530,625-P887.325. .

Potentials of bamboo production to improve the financial status of poor farmers
through increased employment are great. High demand for bamboo products and
diminishing nattnal supplies provide an impetus for implementing this project.
Analysis results indicate that expanding opportunities for poor farmers can provide

needed income and employment in rural Philippines.

To my mother.

Mrs. Corazon S. Uriarte

iv

ACKNOWLEDGEMENTS

To those who have contributed their time, talent and concerns for the
completion of this work, my sincere thanks and appreciation.

To the Director of ERDB for the confidence and continued support; to the
Bamboo Project Staff for the assistance in data collection; and to the FAO of UN for
providing funds, my deepest gratitude.

To Dr. Larry A. Leefers, as Dissertation Director and Chairman of my
Guidance Committee, thanks for instilling me with the fundamentals and intricacies of
the analytical part of the study, for technical support, and for allowing me to use his
system. His patience and understanding and his personalized mentorship are deeply
appreciated. He is more than a teacher but a personal friend.

To the members of the Guidance Committee: Dr. Daniel Chappelle, Dr. Jeffrey
R. Vincent and Dr. Robert Marty, for their invaluable contributions to the first phase
of my program; to Dr. Karen Potter-Witter and Dr. Michael Gold for their willingness
to be members of my committee, my heartfelt gratitude. To Dr. Robert Manthy, my
special thanks. Working with them is a privilege that I cherish so much.

To Dr. Dan Dizon, for his technical, moral and material help, thank you so
much. You are more than a brother to me.

To my relatives and friends for the intercessions and physical help, they have

V

lighten the burden of my academic struggles, my deepest gratitude. Though names are
not mentioned, my sincere feeling is never diminished.

To my wife Monina, for her love and sacrifices to the extent of yielding her
professional gratification to be with me, thanks. She is instrumental in keeping balance
my life as a student, a father and a provider at the same time. To Nesse and Ken, for
their love and enthusiasm at all times. Surely it has added impetus to my drive for
excellence. Our time together is so wonderful.

Finally, to Sovereign God, the Source. He gives me strength, love and

encouragement all the time. Through HIM, all these things happened

vi

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

LISTOFFIGURES .....................................

TABLE OF CONTENTS

CHAPTER 1. BACKGROUND AND JUSTIFICATION ................

1.1. Introduction ....................................
The Commodity-Bamboo ..........................
Prospective Participants-Small Farmers .................
Target Areas-Public Lands .........................

1.2. Context of the Study ..............................
The People ....................................
The Government and the Economy ...................
Family/Community Structure in Rural

Setting ......................................
Seem/Political Structure Synthesis ....................
Structural Reforms ............................. .

1.3. Objectives of the Study ............................

1.4. Scope of the Study ...............................

1.5. Organization of the Study ..........................

CHAPTER 2. REVIEW OF LITERATURE .........................

I

2.1. Distribution of Bamboo ............................
2.2. Description of Bamboo Species ......................
2.3. Physical and Mechanical Properties
of Bamboo ....................................
2.4. Propagation Methods .............................
2.5.ManagementandCarePractices ......
2.6. Harvesting and Transport ..........................
2.7. Uses of Bamboo .................................
2.8. Factors of Production .............................
Family Labor Participation .........................
Capital Requirements .............................
2.9. Analytical Methods ...............................
Financial Analysis ...............................

vii

Page

X

xii

8
9
10
10

12
13
15
16
19

21
21
22

24
26
29
30
31
33
38
42
43 .
43

Scheduling Techniques ............................ 46

2.10. Summary .................................... 49
CHAPTER 3. RESEARCH MODS ............................ 51
3.1. Introduction .................................... 51
3.2. Optimization Modeling ............................ 51
3.3. Model Formulation ............................... 56
3.4. Data Collection ................................. 59
Cost Production ................................. 59
Yield Data .................................... 59
Farm Gate Prices ................................ 60
Household Profile Survey .......................... 60
3.5. Data Analysis .................................. 61
Financial Analysis ............................... 62
3.6. Repayment of Loan .............................. 64
3.7. Summary ...................................... 66
CHAPTER 4. RESULTS AND DISCUSSIONS ...................... 67
4.1 Introduction .................................... 67
4.2. Survey/Data Results ............................. . . 67
Yield Data ......... ” ........................... 68
Farm Gate Prices ................................ 68
Surplus Household Labor .......................... 71
4.3. Other Assumptions ............................... 74
4.4. Financial Analyses ............................... 77
Bambusa blumeana .............................. 78
Bambusa philippinensis ........................... 81
Dendrocalamus arper ............................. 84
Dendrocalamus merrillianus ........................ q 86
Schizostachywn Iumampao ............. ' ............ 87
4.5. Sensitivity Analysis .............................. 89
Different Scenarios .............................. 90
4.6. Regional Summary of Cash Flows .................... 93
Region 7-Central Visayas .......................... 93
Region 6-Western Visayas ......................... 95
Region 11-Northeastern Mindanao .................... 95
4.7. Plantation Development Scheduling for

Each Management Scheme ........................ 98
.‘ 4.8. Cash Flows of Discounwd Net Benefits ................ 102

4.9. Optimal Development Schedule by Species-
Maximizing NPV ............................... 104

4.10. Optimal Development Schedule by Species-

Maximizing Amount of Employment .................. 109

Region 7-Central Visayas .......................... 111

Region ll-Northeastern Mindanao .................... 113

Region 6-Westem Visayas ......................... 116

CHAPTER 5. SUMMARY AND IMPLICATIONS .................... 119

5.1. Summary of Findings ............................. 119

5.2. Implications of Findings ........................... 125

5.3. Limitations .................................... 128

5 4 Further Research ................................ 130

APPENDIX A. Ranges of Mensnrational Attributes of Bamboo ........... 132

APPENDIX B. Physical and Mechanical Properties of Bamboo ............ 134

APPENDIX C. Classification of Land Area in the Philippines ............. 136

APPENDDI D. Survey Questionnaires and Input Data Forms ............. 138

APPENDIX E. Per Hectare Yield Data . f ........................... 146

APPENDIX F. Projected Yield Data .............................. 153

APPENDIX G. Interest Rates in the Philippines ...................... 160

APPENDIX H. Description of Management Schemes ................... 162
APPENDIX 1. NPV of Management Schemes as Affected by Year of

Planting ....................................... 166

APPENDIX J. Schedules of Plantation Development in Region 7 .......... 170

APPENDIX K. Schedules of Plantation Development in Region 11 ......... 177

APPENDIX L. Schedules of Plantation Development in Region 6 .......... 184

REFERENCES ............................................. 191

LIST OF TABLES

Page
Table 1. Important genera of bamboo in the Asia-Pacific region ........... 23
2. Site requirements and disuibution of five erect bamboo
species in the Philippines ............................... 25
3. Consumption of bamboos in the Asia-Pacific region by
end-use ........................................... 32
4. Breakdown of uses by species in the Philippines ............... 34
5. Allocation of adult work time in Laguna households in
hours per week ........... * .......................... . . 40
6. Children’s time contributions to the household
(average annual hours per child) .......................... 41
7. Average cost of planting material by species in 1989
pesos ............................................. 69
8. Average harvesting and hauling costs per culm by
species in 1989 pesos ................................. 69
9. Average buying prices per culm by quality type and
species in three regions in 1989 pesos ...................... 70
10. Household type, household composition, percent labor
contribution of adult family members and total marketed
labor in 3 regions .................................... 72
11. Amount of labor each household type can commit to bamboo
production by quarter for 3 regions ........................ 75

12. Result of the financial analysis for B. blumeana on flat
terrain with annual harvests at 10% discount rate in 1989
pesos ............................................. 79
x

13a. Result of the financial analysis for a. philt'ppt'nensis

13b.

14.

15.

l6.

17.

18.

19.

21.

at 4x5 m spacing with annual harvests at 10% discount
rate in 1989 pesos .................................... 83

Result of the financial analyis for B. philt’ppinensis
at4x5mspacingwithperiodicharvestsat10% discount
rate in 1989 pesos .................................... 83

Result of the financial analysis for D. asper on
relatively flat terrain with annual harvests at 10%
discount rate in 1989 pesos ............................. 85

Result of the financial analysis for D. mern'liianus on
relatively flat terrain with annual harvests at 10%
discount rate in 1989 pesos in Region 6 & 7 ................. 88

Result of the financial analysis for S. lwnampao at 4x5 m
spacing on relatively hilly terrain with annual harvests
at 10% discount rate in 1989 pesos in Regions 6, 7 & 11 ........ 88

Results of sensitivity analysis for management schemes
that gained highest positive NPV for each species in
3 regions at 10% discount rate in 1989 pesos ................. 91

Plantations developed. funds borrowed and total NPV by
household type in Region 7 at 10% discount rate in
1989 pesos ......................................... 100

Gross returns, development costs and cash flow schedule
for 2 types of farmers in 1989 pesos ....................... 103

. Ranges of NPV based on optimal development schedule for

each species by region at 10% discount rate in 1989 pesos ....... 105

Ranges of labor use (mandays) based on optimal development
schedule for each species by region ........................ 110

. Summary of species having highest NPV, highest labor used

and highest labor availability by region ..................... 126

LIST OF FIGURES

Page

Figrue 1. Map of the Philippines ................................. 18
2. Cash flows of 4 bamboo species planted in Region 7 ............ 94

3. Cash flows of 3 bamboo species planwd in Region 6 ............ 96

4. Cash flows of 4 bamboo species planted in Region 11 ........... 97

CHAPTER 1

BACKGROUND AND JUSTIFICATION

1.1. Introduction

Rina] poverty is widespread in the Philippines. Several efi’orts are underway to
address this problem; one such efi'ort is the Bamboo Research and Development
Project (hereafter referred to as the Bamboo Project). The main objective of this
project is to assist the Philippine Government in creating new somees of employment
and thereby raising the income levels in appropriate rural meat of the country. It is
funded by the Food and Agriculture Organization of the Uniwd Nations (FAO) and
aggressively pm'sued by the government of the Philippines. Specifically, the project
intends to broaden the raw material base, generate jobs, increase income, and
rehabilitate vast denuded areas created by the rampant timber exploitation of the past
three decades. I

Prusuit of this undertaking is driven by a combination of factors having some
collateral implications for the other nual-oriented, poverty-alleviating and
developmental-type programs pursued by the Philippine government. Some of these
programs are: the Comprehensive Agrarian Reform Program (CARP), the Community
Employment and Development Program (.P , and the Integramd Social Forestry

Program (ISF).

2

The Bamboo Project’s focus was the outgrowth of several considerations. First
andfmemostthechoice ofbamboo speciesisborneoutfromtherealizationthata
wide gap between quantity demanded and quantity supplied has been experienced and
will continue to exist in the years to come. Bamboo, though endemic to the country,
has dwindled considerably because of over-exploitation. Conversion of lands to other
uses is another contributory factor to its depletion. As built-up areas expanded to
accommodate the swelling population, total elimination of these species in some areas
has occurred. Though certain areas still contain considerable stands, nansportation of
bamboo products to markets is difi'rcult.

Another compelling reason for encornaging this type of activity is the
recognition that there exists a considerable sm'plus of labor in the anal sector. The
National Economic and Development Authority (NEDA) estimated that while the rural
unemployment rate was only 7.4%, the underemployment figme was a staggering
40.4% (NEDA, 1989). NEDA added that labor productivity in the agricultural sector
has declined considerably from previous years although this sector continues to absorb
the bulk of the labor force.

Promotion of bamboo plantations in the countryside is one possibility that has
great potential for creating employment and increasing income. It has the potential for
profound economic and social implications. The impact is expecwd to extend beyond
household basic needs or community satisfaction. It is hoped that it will affect other
more pressing problems (e.g., social unrest). Relative to the CARP, this project would
serve as an additional option for farmers in improving their well-being.

One goal of Bamboo Project is to provide poor farmers access to government

3
lands for plantation development. Conversion of marginal lands into productive areas
is vital in sustaining the livelihood of the poor people. Moreover, this has a strategic
advantage in some respects because it will mostly involve upland and landless

farmers, the social group most vulnerable to the anti-government campaign.

The Commodity - Bamboo

Bamboos have many uses. Historically, bamboos form the single most
important forest product used by rural communities in Asia and the Pacific (Shanna,
1985). They are so closely intertwined with the lives of the people that it is beyond
comprehension (as one Chinese author said) for one to live in ancient times without
bamboo for a single day. The close relationship between this commodity and the
people is succinctly phrased by the famous poet of the Sung Dynasty (1312 AD), Sn
Dongpo, when he said:

"there are bamboo tiles for shelter, bamboo hats for shading, bamboo paper
for writing, bamboo nuts for carrying, bamboo skin for clothing, bamboo shoes for
wearing, bamboo shoots for eating, and bamboo fitels for fire" (W0 and Ma, 1985).
Its significance is so great, especially in South and Southeast Asia, that it is difficult to
speculate what would have happened to the people in this part of the world without
bamboo. Lessard (1980) hypothesized that if all countries in Asia where bamboo is
abundant are taken into account, then at least one-third of the human race is making
use of this perennial plant.

The Philippines is one of the countries endowed with this valuable resource.

Bamboo plays a distinct role in the lives of Filipinos. In the rural areas, 26% of the

housing units are construcwd from bamboo materials (Philippine Yearbook, 197 5). As

4
one of the most versatile natural materials, bamboo makes possible the development of
various products. The ease with which this material can be worked, its strength, its
durability, and availability makes it eminently suitable for domestic and
commercial consumption (Tamolang et al., 1980). In addition, bamboo is native to the
country and has extraordinary growthl compared to tree Species promoted in domestic
reforestation projects.

In recent years, utilization of bamboo has evolved tremendously from the very
uaditional uses as house consuuction materials and agricultural implements to
furniture and handicrafts. It has become one of the primary materials for banana
pmppingsincecntfingpemimfmsapfingswuecmcefledThefisherymdusnyisalso
getting a large share of the bamboo material due to expanding fishpen operations in
some regions of the country. Prospects in other sectors are even higher as technology
for its utilization is being developed.

The continued growth of bamboo-using industries in the country has
tremendously accelerated the exploitation of the natural stands. Extensive harvesting is
rampant. In some areas, indiscriminate cutting is very noticeable. Pressure is so great
on the demand side that it is contributing heavily to the depletion of the resource. As
indicated by the Forest Management Bureau (FMB) formerly the Bureau of Forest

Development (BFD), only about 15,574 hectares of neutral bamboo stands were left in

 

lThe Guiness Book of World Records (1989) noted that some species of the 45
genera of bamboo have attained growth rates up to 36 inches per day. Observation
in Hawaii indicated that a certain species of bamboo can reach 100 feet in height in
less than 3 months.

5
1980 from the 200,000 hectares smveyed in 1963 (BFD Statistics,1980; PCARRD
Recommends, 1984). As estimawd by Tesoro (1983), these stands may contain a total
of 1.77 million culms (woody stems arising from the rhizomes with a cylindrical form
and comprising a series of nodes and intemodes). This inventory is, however,
insignificant compared to the annual projecwd demand of about 31.27 million culms
(Tesoro, 1983).

The wide gap between quantity demanded and quantity available has resulted
in more harvesting of immature culms. Coupled with the absence of clear government
regulations on management and harvesting, the remaining somee will be continually
threatened. The futlue seems bleak for this commodity given the persistent pressure
from end-users. Reliance on remaining stands to support raw-material requirements is
no longer possible.

Increased consumption of this resource has greater repercussions for the local
people. Recently, prices rose to high levels inhibiting local users from competing with
industrial users. This complaint was raised by some farmers during the conduct of the
ground verification survey of bamboo stands in selected provinces of the Philippines
(Uriarte,1985). Bamboo owners prefer to sell their produce to industrial users rather
than to their co-farmers because prices ofiered by the former are higher. Besides,
industrial users tend to buy in larger quantities so that even lower quality culms can
still command good prices.

The imminent shortage of this valuable resoruee has been recognized by
different sectors of the indusn'y (PCARRD, 1984; DENR, 1988). As a result, the

exploitation of bamboo poles has greatly diminished, and there is concensus that

6
dwindling stock must be replenished. Moreover, what has been a readily available
materialforruralpeoPle seems tooscaleeforthem toacquire,andthereisaclamor
for establishing bamboo plantations.

But addressing simply the concern for expanding the raw-material base may
not be a sufficient solution considering that the need for an equitable distribution of
income is even more pressing. Therefore, it is crucial to evaluate how investments in
this particular activity can afiect the plight of the primary beneficiaries--the small

farmers.

Prospective Participants - Small Farmers

The added concern for farmers is as ~ critical as the concern for the commodity.
Creation of bamboo plantations may help. the government reach the most neglected
segment of Filipino society.

Poverty in the country is deepening. The incidence of the population living
below the poverty tlueshold2 is very alarming. In absolute measure, IBON Databank
Philippines (1983), a private research organization, estimated that about 71% of the
population or approximately 6.6 million households are living below the poverty line.
Although other estimates are less definitive, all groups concerned with the incidence of
poverty in the Philippines are in complete agreement that the upward trend of families

falling below the poverty threshold is continuing. Coupled with the steady contraction

 

2Jur'ado (1979) defines the poverty threshold in the Philippine context as the cut-017r
point below which income cannot buy for the fondly its recommended nutrient
requirements, cannot permit two changes in garment for each family member, cannot
cover the minimal cost of medical care...and cannot afiord to pay roughly imputed
rent and fuel costs for families who meet the food standard.

7

of the economy, it can be surmised that the trend will continue or will even worsen in
the years to come (Miranda, 1988). In relative terms using the Gini coeflicient’, the
National Census and ,Statistics Office (NCSO) indicated that the poorest 60% of the
households, which received only 25% of the total income in 1971, sufiered a father
decline of their share to 22.5% in 1979. This is not a recent phenomenon as Miranda
(1988) indicated because the social struggle waged by the peasants was deeply rooted
in this inequality. President Aquino in her sincere initiative to ofl‘er negotiations for
peace and reconciliation with the insurgents has fully recognized that "the roots of the
insurgency are in the economic conditions of the people and the social structures that
oppress drem"!

The government has a strong anti-poverty agenda. Critics, however, are very
vocal that most programs have short-term implications and merely focus on the
reduction of poverty without any reference whatsoever to income distribution and
distributive justice (IBON, 1987). Therefore, by focusing mainly on rural employment
like the CEDP without the accompanying structural reforms, the government may
encounter difficulty in solving the conflict in the countryside that has bred the poverty

(Miranda,l988).

 

3The degree of inequality is measured using the GINI coefl‘icient: Introduced in
1912 by C. Gini, an Italian statistician. Gini ratio ranges fi'om 0.0 (absolute equality)
to 1.0 (absolute inequality).

‘On Dec. 10, 1986, the Government of the Republic of the Philippines and the
National Democratic Front (NDF), the political arm of the Communist Party of the
Philippines (CPP) entered into a preliminary ceasefire agreement in preparation for a
negotiated peaceful settlement of the present armed conflict between the government
forces and the New Peoples’ Amty (NPA), the military arm of the CPP. The agreement
expired on Feb. 8, 1987 without achieving its objectives.

8
Family labor utilization on farms is very low. Hayami (1978), in his study of
one agricultural village in the Philippines, found that the labor utilization rate was less
than 70% of full capacity even at peak season. The opportunity to find jobs outside
farming is limited, and labor is underutilized especially between planting and
harvesting (Ledesma, 1982). Diversifying the activity of the farmer may, therefore,

lessen the labor surplus and increase productivity.

Target Areas - Public Lands

The Philippine forest resources situation indicated that of the country’s 30.0
million hectares total land area, about 15.0 million are forest lands, 14.1 million are
Alienable and Disposable (A&D)‘ and the remaining 0.9 million hectares are still
unclassified (DENR, 1987). Considering that the bulk of the land is under public
domain, promotion of bamboo production may be easier than other projects (e.g.,
pulpwood plantations, and fuelwood productions) because of the wide adaptability of
the species (Bumarlong, 1985).

Considerable areas are available for bamboo plantation development in
different regions of the country. Attention should be given, however, to tenm'al and
traditional rights mitigating against ownership. In light of this, policies evolving for

democratization of public lands use by projects such as pulpwood plantations,

 

5 Alienable and Disposable refers to all lands which are classified for other
purposes aside fiom forestry. These lands can be converted to agriculture, residential,
commercial, or any other purpose outside forestry. These lands are under the control
of the FMB-DENR, but as soon as these lands are further classified to specific uses,
the jurisdiction is transferred to LMB-DENR.

9
fuelwood production and the recent Integrated Social Fmestry Program may need to be
adopwd (DENR, 1987). For this project, the basic provisions of a leasehold contract
should spell out the details on such delicate aspects dealing with: (1) security of
tenure, (2) continued occupancy of present clearings, (3) size of holdings, (4)
development of forest lands by individuals, and (5) such other provisions that may be
developed in the course of this inquiry. This is also in line with Section 3, Schedule 1
of the Comprehensive Agrarian Reform Program (CARP)‘ which states:

"All lands of the public domain and other lands owned by the government or
by government-owned or controlled corporations, associations, institutions or entities
leased or held by multinational corporations or foreign individuals shall be acquired
and distributed immediately upon the efl'ectivity of RA 6657 (CARP), with the
implementation to be completed within 3 years" (Administrative Order No. 11, Series
of 1988, DAR).

These core programs of the government are very vital in the pursuance of

Bamboo Project.

1.2. Context of Study

Background information about the Philippines is important for understanding
how this project could fit with other programs the government is pursuing. By briefly
looking into some aspects of the country and its people, insights can be gained
regarding the relevance and timeliness of this study. Especially in project design,
historical perspectives are nwded. Lessons from the past are of great value as this

project implementation is pursued. The remainder of this section presents a brief

 

“CARP is the biggest government program instituted under the new leadership of
President Aquino. The underlying principle behind it is the promotion of equity
coupled with the democratization of access to land and the benefits derived from it.

10
sketch of the Filipino pe0ple, the government, the economy, the rural community

structure, and recent reforms.

The People
The population was approximately 58 million in 1988 (NEDA, 1989). Density
was estimated at 492 per square mile with 95% of the area and population found on
the 11 largest islands. The Population Reference Brueau (PRB) estimated a growth rate
of 2.8% and ranked the country as the 17th most populous country in the world.

Average family size is six. Distribution is approximately 70% mral and 30% urban.

The Government and the Economy

A legitimate democratic government is now in place after Filipinos ratified the
New Constitution in a plebiscite held on February 2, 1987. Prior to that, however, the
old regime was t0ppled peacefully in the famous "February Revolution". The challenge
facing the nation is to overcome economic inequities and social injustices remaining
after the change in government.

The Gross National Product (GNP) was valued at US$39.04 billion in 1988.
The growth rate was estimated to range between 5.8-6.0% in 1988, but in previous
years performance was very low. The positive growth in recent years was primarily
driven by the renewed confidence of the business sector in the new government. The
inflation rate was 8% in 1988, much higher than in previous year’s 0.34%. In terms
of jobs, about 35% (or equivalent to 2.6 million Filipinos) were jobless in 1988.
Another 5 million were underemployed out of a total workforce of 21.7 million. Real

earnings in terms of wages received indicated a drop of 6% from 1987 to 1988.

11
The government is heavily depressed economically. Current external debt is
aprroximately US$286 billion with a domestic debt of about US$133 billion. To
service outstanding debt for 1989 alone, an amount of US$33 billion is required.
Overall, the standard of living declined slightly in 1988 with the poor two-
thirds of the population dependent on agriculture suffering the most (World Bank,
1987). A September, 1988 survey by Ateneo de Manila University indicated that about

66% of the families are living below the poverty threshold (Miranda, 1988).

Family/Community Structure in a Rural Setting

In rm'al Philippines, the family is the basic social unit or institution "which
public policy cherishes and protects" (Ortigas and Regalado,l978; Mawda,1967). It is
the center of activities for maintaining society. In terms of economic affairs, the family
is the major unit of both consumption and production. It is the family that decides
which goodsaretobepurchasedandhowtheyaretobeusedTheheadofthefamily,
usually the husband, directs and allocates labor in agricultural occupations which
accumulates capital and which, on occasion, will loan capital to its members. Above
all, it is a prime responsibility of the family to provide nurture and protection for the
young, support for the unemployed and less fortunate members, and care and
companionship for the aged and sick.

These family-oriented values have a profound influence on individuals and
their behavior towards society. If individuals become insecure socially and
economically, it causes some social problems (Maceda, 1967; Andres and Andres,

1987). Family members think that they have no one to fall back upon except the

12
family. As a consequence, the family has become the highest norm of morality-
everything is good that serves the family welfare; everything else is an instrument for
achieving the family’s goal of socio—economic secmity (McMillan and Rivera, 1952;
Andres and Andres, 1987). In addition, families have a high degree of unity and some
traditions bind them closely to their place of birth. Migration to another place often is
difficult.

Several sociologists consider some traits of the Filipino family as barriers to
progress or as divisive factors in the community and even to the nation as a whole
(Maceda, 1967; McMillan and Rivera, 1952; Ortigas and Regalado, 1978; Andres and
Andres, 1987). By their nature, families militate against working together for the

broader common welfare.

Social/Political Structure Synthesis

The Filipino concept of society is segmentary (Weintraub, 1973). Rather than
viewing society as a collective group striving to achieve common goals, Filipinos
perceived it as a system of relationships between people of different heirarchical
levels, bound in a network of mutual obligations. The explanation forwarded by
Weintraub (197 3) is two-fold: (1) the traditional value of reciprocity (utang-na-loob)
and (2) the belief that an individual alone is powerless, with security depending on the
help and protection of a powerful person. Reciprocity and dependency have thus been
key factors in the Filipinos immediate reality. Filipinos view relations among people
and social organizations in general in terms of mutual obligations between the weaker

and the stronger, obligations which are best expressed in terms of the use of power.

13

Politics in the Philippines is deeply roowd in the social relationships of a
population composed of a small, land-owning national elite on the one hand, and a
large, impoverished, peasant working class, on the other. This is exemplified by
ownership of private lands which indicates that 10% of population owns 90% of the
land (Freisen, 1988). These social relationships that have traditionally influenced
political behavior can be traced to the periods of colonial rule. Families favored by
colonial governing powers established regional strongholds based on landholdings and
eventually assumed economic and political prominence. The cm'rent political setting in
the Philippines, therefore, can be best understood in the light of historical events that
have shed political thought timing the country’s transformation from a colony to a
republic. The evolution of the Filipino social infrastructme is amply described by
lnfante (1980) in the following quote:

"For the vast majority (Filipinos)...their lives continued to be governed by the
economic guidance of a landlord who maintained a mutually satisfactory patron-client
relationship with his tenants. The latter relationships, together with the closeness of
family ties and associated values and behavior patterns was basic to the social,
economic, and political life of Filipinos. The landlord although customarily taking
about half of the harvest, provided his tenants with various forms of security-cash
loans, rations to tide the family over the preharvest shortage, assistance in family
crisis, financing the education of a promising child, or assuming the important social

role of godparent. In exchange, the tenant ofi'ered a variety of personal services as
well as political and economic loyalty."

Structural Reforms
The highest priority of the government is economic recovery. The overall
strategy, as spelled out in the Medium-Term Development Plan (NEDA, 1988),

emphasizes three key economic principles, namely: (1) greater attention to poverty

l4
alleviation and social justice, (2) acceleration of growth and increased economic
efficiency, and (3) reduced government involvement in the economy and an emphasis
on private initiative. Heavy emphasis will be placed on programs to reduce poverty, to
raise employment particularly in anal areas, and to accelerate agricultural production
and exports (World Bank, 1989).

Threevitalprograms thathave somedirectimpactonthertn'alpeopleandare
being aggressively named by the government are: (1) the Comprehensive Agrarian
Reform Program (CARP), (2) the Community Employment and Development
Programme (.P), and (3) the Integrated Social Forestry Program (ISF).

CARP is the centerpiece program of the present administration. This program
has great appeal to the government because it is believed to form a solid base for
industrial development. Its focus is to increase consumption and investment of the
peasant workers and to stimulate higher demand for industrial products. It is intended
to increase productivity by expanding production of raw materials for industrial
consumption. More importantly, it has wide-ranging implications because (1) it may
undercut the level of support among rural communities for the New Peoples’ Army
guerillas, (2) it encourages agricultural diversification, and (3) it helps stimulate
domestic demand by raising rural incomes, thereby brealdng the cycle of chronic
underconsumption which characterize the country’s economy.

CEDP was launched as a direct government response to rural poverty. The
rationale behind the program is to create jobs through the establishment of rtn'al-based
projects. The employment of excess labor may ultimately increase the purchasing

power of the rural population.

15

This program is envisioned to provide employment opportunities via labor-
intensive development and infrastructure projects such as construction of feeder roads,
school buildings, communal irrigation systems, reforestation, seed production, and
distribution of planting materials.

ISF aims to mobilize forest resom'ces for economic and social progress of the
nation through the involvement of upland farmers (kaingineros) and other occupants of
forest lands who shall be made effective agents of the state in food production and in
rehabilitation of forest lands. The government, on the other hand, shall provide
security of tenure and assist the farmers in improving and sustaining the productivity
of the land. Creation of agroforestry farms is one of the vital components of this

prom-

l.3. Objectives of the Study

The goals of this study are tied to the overall objective of the Bamboo Project
spelled out in the first section of this chapter. Establishment of pilot scale bamboo
plantations in the difl'erent regions of the country is an attempt to bring the project
closer to the people and at the same time to accelerate generation of technology on
bamboo production.

There are two main objectives in this study. The first objective is to determine
the financial viability of bamboo plantations in different regions with difi'erent bamboo
species and family labor availability. To achieve this objective, income streams must
be calculawd using different species and management schemes. In addition, labor

requirements over time and credit extension and repayment schemes must be assessed.

16
The analysis is carried out using the financial analysis procedures commonly applied
in forestry projects. The net present value (NPV) is used as a meastue of the net
incremental farm income for farmers who may engage in bamboo plantations.

The second major objective is to determine the optimal deve10pment schedules
for bamboo plantations based on a 5-hectare module. Two goals (i.e., objective
ftmctions) are considered: (1) maximizing the net present value of cash flows and (2)
maximizing the amount of employment. Models are developed based on the amount of
surplus labor each household type can provide for an appropriate species for a given
region.

The family labor supplied in peso equivalents serves as equity for financial
assistance; a loan equal to three times this. equity can be seemed The Bamboo
Project’s intention is to tap idle labor without disrupting the usual livelihood activities
of the farmers. This project is perceived as increasing labor productivity. Financial
implications are deternrined by how bamboo plantation development proceeds.
Individual household capability plays a major role in determining how the income
streams are afl'ected by the limitations of the family labor contribution. The outcome
may serve as a guide in formulating assistance packages that would best suit the

successful implementation of the Bamboo Project.

1.4. Scope of the Study
Bamboo production, as viewed from this study, is a part time activity. The
study’s framework is only to consider the surplus labor of each household type. The

analysis does not consider the whole farm plan but focuses only on the optimal use of

17
excess family labor. .

Only five species of bamboo are covered in this study. Selection was primarily
based on the demand for the species, availability of yield data, and inclusion of the
species in the pilot plantation projects undertaken by the Ecosystem Research and
Development Bureau (ERDB). Although other species are also commercially utilized,
data inavailability, especially on yield, prohibits inclusion at this time.

Three regions in the country are included in the analysis, namely: Region 6
(Western Visayas), Region 7 (Central Visayas), and Region 11 (Northeastern
Mindanao) (see Figure 1). These regions have shown great promise in the market for
bamboo materials because of the presence of bamboo-using industries. The pilot
plantations in these areas have also performed well timing the initial evaluation in
1989 (ERDB, 1989). Besides, some bamboo owners in these regions are also willing
to share their experiences and records which at this time are not yet available from the
Bamboo Project.

This study utilizes a combination of survey and secondary data. Survey data
include household profiles, farm gate prices, and production costs. Secondary data, on
the other hand, include yield estimates and harvesting and hauling costs.

Since a considerable number of poor farmers are seeking employment
opportunities and access to land, leasehold agreements are believed to provide
sufl'icient tentu'al security for farmers. The 25-year lease period applied to the
pulpwood plantation project, the fuelwood production program, and the ISF are also
used here for ptu'poses of determining the cash flows generated Analyses are based on

a 5-hectare module, which was deemed to be reasonable enough to gauge the income

  

"5' [7263 122:; [23.17" :25
r
‘l
o]
'20 Balance
, o
0‘
~ '
tl'h
Fr
‘16'
I" .
”MS“ it’lrduqua
o
C
l"
. t
O
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10'
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Negros Occidental

a; Region 7 (C. Visayas)

Bohol

Cebu

Negros Oriental
Siquijor

 

3 Region 11 (NE Mindanao)
Davao Norte

Davao Sur

Davao Oriental

Surigao Sur

South Cotabato

Figure 1. Map of the Philippines Showing Regions Included in the Study.

19
efiect for potential bamboo farmers.

Financial analysis is the primary consideration of this study. The financial
measures are sufficient to indicate the capacity of the farmers to repay loans. Clear
identification of beneficiaries links commercial profitability of the project with
concerns for the distribution of income (FAO, 1980).

The pm'ely financial approach is appropriate because all of the production
factors are locally seemed. The domestic availability of the different resom'ces used to
produce the raw-material reflects the economic value except in cases where
government policies distort the price of money. On the output side, the market price
may provide a reasonable approximation of the economic value since the project
outputs are not final consumer goods. They are only additions to the tatal intermediate

supply (FAO, 1980).

1.5. Organization of the Study

Bamboo plantations particularly in the Philippines, are relatively new. While
silvicultural studies have gained some breakthroughs in the past, not one study delves
into the economics of production. Past reliance on natural stands undermines pursuit of
bamboo production studies. Only recently, research and development efforts on
bamboos have been pursued with vigor and determination. This study is part of an
ongoing effort to further examine bamboo’s potential.

The preceding review of the current situation in the Philippines has been
included to show how the Bamboo Project could fit into the other government

programs dealing with rural employment and income expansion. The need for some

20
structural reforms are also nowd because of the clamor for income redistribution and
distributive justice.

Chapter 2 deals principally with the distribution and characteristics of different
bamboo species. Traits of bamboos are discussed to distinguish their relative
advantages cver tree species generally planted in reforestation projects. In addition,
production factors are identified. Factor identification is valuable for assessing how
farmers’ resources can be complemented by government programs. Selecwd studies of
analytical techniques for financial evaluations and activity schedulings are also
reviewed.

Data requirements and scruces, methods for gathering data, model formulation
and the sequence of study analyses are expounded in Chapter 3. The focus on
farmholders was given special attention in the financial analysis and activity
scheduling because of the limited resources farmers can invest in bamboo plantation.

Chapter 4 presents the results from this study’s survey, financial analyses, and
optimal scheduling for plantation development. Results are discussed relative to
species, household type and region. Optimal schedules were developed on the basis of
maximum net present values and maximum amount of labor generated.

In the final chapter, significant findings are summarized with implications for
other bamboo species, for other regions of the country and for other participants of the
Bamboo Project. Shortcomings encountered in the course of the investigation are

1

described and recommendations for further research are identified.

CHAPTER 2

REVIEW OF LITERATURE

This chapter is divided into three main sections. The first section deals with
distribution, characteristics and uses of bamboos. Factors of production are treated in
the next section. Analytical methods emphasizing applications of benefit-cost analysis
and techniques for scheduling management activities over time are discussed in the
last section. Linear programming (LP) is the principal analytic scheduling tool
discussed with a focus on applications concerning small farmers. The appropriateness

of the LP technique and its modifications and extensions are also presented.

2.1. Distribution of Bamboos

The Barnbuseae family is a section of the great natural order Grarnineae, the
grasses (Gamble, 1986). These large tree-like members of the grass family, which are
characteristic of tropical regions, are very useful in localities where they are found.
Their distribution has even extended to subtropical and temperate zones. Some are
found in forests and some on well-drained slopes.

Bamboos are usually gregarious, that is, they dominate the area once
established. Bamboo forests are confined within 15-25 degrees of both sides of the
equator. Locations include southern China, Btuma, Thailand, Laos, Vietnam, India,

21

22
Bangladesh and all of Southeast Asia. Colonies of bamboo are found in Columbia,
Peru, Chile, Paraguay, Bolivia, Madagascar, Mozambique and Rhodesia (Tamolang et
al., 1980).
Bamboos generally grow well in places that have temperature between 88-36
degrees Centigrade (Tamolang et al., 1980) and under a light to moderate canopy of
deciduous species (Shanna, 1980). The distribution of bamboo in the Asia-Pacific

region is presented in Table 1.

2.2. Description of Bamboo Species

Bamboos are perennial giant grasses. The rhizome of bamboo are of two kinds,
namely, those with caespitose culms and those with distant culms. Those with
caespitose culms have rhizomes which are short, knotty, thick, solid growths forming
an entangled network below the surface of the soil from which buds are thrown out
into culms. These are characteristic of the clump-forming erect bamboo species.

Those with distant culms have rhizome which push underground and at intervals send
out rootlets into the soil from which the culms arise singly. Monopodial species are of
this type.

When the young culm emerges and the bud first begins to develop, a conical
growth protrudes from the ground, covered with imbricating sheaths often bright in
color and furnished with blades. Gradually, the cone lengthens, the sheath separates,
the nodes appear, and a full culm is produced. Then usually, one by one, the sheaths
drOp off. The buds at the nodes put out branches, and these produce leaves. Depending

on locality and climate, the timing of this process varies.

23

Table 1. Important genera of bamboos in the Asia-Pacific Region.

 

 

 

 

County No. of Genera
Species
‘ India 136 Bambusa, Dendrocalamus
Bangladesh 33 Bambusa, Dendrocalamus, M elocalamus,
Melocanna, Neohouzeoua, Oxytenanthera
Burma 90 Sinobambusa, Chimonobarnbusa,

Arundinaria, Phyllostachys, Gigantochloa,
Dinochloa, Oxytenanthera, Dendrocalamus,
Dendrochloa, Pseudostachyum,
Schizostachyum, Neohouzeoua,
Cephalostachyum, Melocanna,

Teinostachyum

Philippines 55 Bambusa, Schizostachyum, Dendrocalamus,
Gigantochloa

Indonesia 31 Arundinaria, Dendrocalamus, Bambusa,

Gigantochloa, Nastus, Melocanna,
Phyllostachys, Schizostachyum,

Thyrsostachys

Thailand 50 Thyrsostachys, Bambusa, Dendrocalarnus

China 300 Bambusa, Dendrocalamus, Lingnania,
Sinocalamus, Schizos, Dinochloa,
Pseudostachyurn

Japan 670 Phyllostachys, Sosa, Pseudosasa

Korea 13 Phyllostachys, Pleioblastus, Sasa,
Pseudosasa

Malaysia-Sabah 12 Gigantochloa, Schizostachyurn

Papua New Guinea 26 Schizostachyum, Bambusa

Bhutan 2 Dendrocalamus, Bambusa

New Caledonia 4 Greslania

Sri Lanka’ 14 Dendrocalarnus, Bambusa, Ochlandra

 

 

i
_

Sornces: Sharma, 1985 and Tamolang et al., 1980.

 

24

Woody stems or culms arise from the rhizome. These culms are cylindrical
with a series of nodes and intemodes. Culm wall thickness, culm diameter and culm
height vary. Distribution and site requirements of bamboo species used in the study are

presented in. Table 2.

2.3. Physical and Mechanical Properties of Bamboos

Bamboo compares well and favorably with other constuction materials like
steel, concrete and timber in stength and stiffness per unit area of material, ease and
safety of use (Jansen, 1985).

Espiloy (1985) reported that the physico-mechanical properties of bamboo (e.g.,
relative density, shrinkage, moisture content, static bending and compression parallel
to the grain) are correlated with anatomical characteristics such as fibrovascular
bundles, frequency and dimensions of fibers, and vessels. These properties are
necessary in assessing potential uses of bamboos as building materials for housing,
furniture-making and for general constuction work and in converting them to a variety
of finished products. These properties not only serve as a basis for promoting
acceptance of bamboos but also for improving their market potential.

Stength properties either increase or decrease along the length of the culm
fiom the but to the top (Espiloy et al., 1982; Uriarte et al., 1990). Mensnrational
attributes of bamboos used in the study are shown in Appendix A. Physical and
mechanical properties of four erect bamboo species are presented in Appendix B. No

data are available for B. philippinensis.

25

Table 2. Site requirements and distribution of five erect bamboo species

 

 

 

in the Philippines.
Species Site Requirements and distribution
B. blumeana

B. philippinensis

D. asper

D. merrillianus

S. lumarnpao

 

Moist soil, found throughout settled areas in the
Philippines at low and medium altitude. Luxuriantly
growing along river banks and creeks. Abundant in
Rizal, Camarines provinces, Cavite, Batangas,
Laguna, Pangasinan, La Union, Abra, Ilocos
provinces, Davao Sit and North Cotabato.

Moist soil, growing luxuriantly in areas with rainfall
evenly distributed throughout the year.
Commercially cultivated in Davao provinces.

Moist soil accruing profusely in areas with well
distributed rainfall throughout the year. Grown in
Bukidnon, Agusan Sur and Mt. Makiling in Laguna.

In relatively drier sites at low and medium
elevation. widely distributed in the Philippines
(Rizal, NE Luzon, Pangasinan, La Union, Ilocos
Provinces and Tarlac).

Relatively moist soil. Usually in forest hills.
Naturally growing in Zambales, Bataan, Quezon,
Laguna and Rizal.

 

 

Somce: Lantican et al., 1985.

 

 

26

2.4. Propagation Methods

Erect bamboo species can be propagated using either vegetative (asexual) or
reproductive (sexual). methods. Vegetative methods for propagation includes
combination of culm cuttings, layering, marcotting, and branch cuttings.

In using rhizomes, they are dug and severed from the mother plant and
immediately planted in the field to avoid drying. They can also be grown in the
nursery and allowed to develop for six months to a year before outplanting. Ofi‘sets
from 1-2 year old culms give better results as the rhizomes are young and vigorous
and possess active culm buds. The success of this method depends on the vitality of
the culm bud in the rhizome and the time of the year when the offset is planted
(Banik, 1935). In Japan, cultivation of bamboo by rhizome cuttings has been perfected
(Uchimma, 1980). Generally, the use of rhizomes is limiwd to non-clump forming
species (Uchimura, 1980).

The disadvantage of this method lies in the high cost of labor for excavation
and transportation of the bulky planting stock. Also, only a limited supply of the
planting material is available per clump; thus, this method is not practical for large
plantations.

The second approach to vegetative reproduction is calm cutting. Cuttings of at
least one node and two half intemodes taken tom the middle and the basal portion of
one to thyear old culms are used. In 1980, two-node culm cuttings were directly
planted in a grassland area (Lapis et al., 1980). Results showed that the field survival

rates of B. blumeana and D. merrillianus six months after planting were 25% and

27
35%, respectively. Stn'vival rate of D. asper after 3 months was 32%. S. lumampao
failed to grow. Suzuki and Ordinario (1977) also found that S. lumampao cannot be
easily propagated by culm cuttings.

Experiments showed that rooting can be greedy enhanced by treating planting
stocks with growth hormones like napthalene acetic acid (NAA) at indole butyric acid
(IBA). The cuttings can be directly planted in the field or raised in the nmsery for 6-
12 months. Using B. blumeana and different levels of NAA and IBA, Bumarlong
(1977) showed that 600 ppm NAA gave the highest total dry weight and mean total
length of roots, and 200 ppm gave the highest mean number of roots. Suzuki and
Ordinario (1977) obtained a 45% survival of B. blumeana tested with IBA and 32%
for untreated; 60% for teated D. merrillianus and 53% for untrcawd ones.

A third approach is layering. This can be done by partly bending down two-
year old culms and laying them in the ground so that they can produce roots. When
the shoots appear, the culm is cut at the internode and the layers are planwd
separately. Cabanday (1957) obtained a survival rate of 28% for B. blumeana by
ground layering l-year old culms pruned of branches.

Marcotting is another method of vegetative reproduction. Two-year old culms
are tapped down from the mother culms. These are supported with strong props.
Ordinary garden soil and leaf with molds are placed around the node then wrapped
with coconut husk fibers and tied with fine wire at both ends of the marcotted portion.
Cabanday “(1957) reported a 70% survival rate for 123 marcots of B. blumeana.

The final means of vegetative reproduction uses branch cutting. Branches from

1 to 2-year old culms with three nodal lengths are collected timing the early rainy

28
season. Theycanbeteatedwith lOOppmofNAAtbenpropagatedinasandbed.
ThentheycanbepotteddirectlyorcanbepottedafterZOdays whenithasalready
roowd.

Hasan (1977) found that using branch cuttings instead of ofl'set
overcame the difficulty of scarcity, bulk and weight of planting materials, but that
success in propagation was very limited. His results showed that branch cuttings take
6-30 months to develop into good planting material.

Palijon (1983) obtained a rooting percentage of 83-90% using branch cuttings
of B. blumeana. The same study showed that hormone treatment (100 IAA) enhanced
root and sprout development.

The reproductive (sexual) method pf propagation uses mds gathered from the
m0ther plant. These are readily germinated. In 1980, Lapis et al. conducted tial
plantings of seeds of S. lumampao and found that this species can be successfully
propagated by seeds. However, application of NPK (nitogen, phosporus, potassium)
fertilizer (50 kgll).1 ha and 100 kg/0.l ha) exhibited better growth than that of the
contol seedlings.

The principal disadvantage of this method is the infiequent to rare flowering of
most bamboo species and the production of infertile seeds by most species when they
bloom. Moreover, most species generally die soon or a year after flowering, or
vegetative .‘growth of some species that do not die slackens during the flowering.
Furthermore, the genetic quality of the seeds is less certain than that of asexual
reproduction (U chimura, 1980). Thus, bamboo propagation by seeds is not dependable.

Establishment of bamboo plantations is very critical not only on its dependence

29
on vegetative propagation but also on whether to use direct planting or grow the
planting stocks in the nursery. Results from direct planting using culm cuttings were
unsatisfactory with survival rate ranging from 32-60% even with applications of
growth hormones (Suzuki and Ordinario, 1977; Lapis et al., 1980). For plantation
using nursery-grown stocks, survival rate ranges from 80-93% (Palijon, 1983; ERDB,
1989). With this high survival rate, only one replanting is required to attain the desired

stocking.

2.5. Management and Care Practices

Management of bamboos is based on the physiologic development of the
culms. New culms are produced from the rhizome generally along the periphery of the
clump. Although the culms attain their maximum size in one season, these are not
ready for utilization because they lack strength. Further, for proper development of
new culms and their support, a certain number of culms one or more years old have to
be left. Thus, although bamboos behave like an annual crop, it is not possible to
harvest all the culms annually (Varmah and Banadur, 1980).

Several Japanese scientists found that fertilization increases growth, although
the amount of increase varies more or less according to the composition of the
fertilizer and season of application. They also observed that the stand stucture and
increment are improved remarkably if the culms that have reached an appropriate age
are cut and a suitable number of good quality bamboos are left standing (Suzuki and
Narita, 1975; Ueda et al., 1957 and 1961; Aoki, 1957).

Fertilizing bamboo plantations is not a widespread practice in the Philippines

30

(Lantican et al., 1985). However, weeding or brushing around the plants is carried out
whenever necessary and watering is done when signs of wilting show up after
planting.

In the Philippines, there are no specific rules that regulate felling of bamboos.
In 1976, Virtucio recommended systematic and selective cutting of matured culms to
ensure continuous production of young sheets. The impressive growth and regenerative
characteristics of bamboo and high potential for industial uses are important factors in
its successful management. Robillos (1984) reported that the (1) removal of spiny
branches in and around the lower portions of B. blumeana and (2) decongestion of the
clumps by removing high stumps fiom previous harvesting and cutting of deformed
and overmature culms resulwd in higher eulm production. Treawd clumps produced an
average of 8 culms while untreated clumps produced only 5 eulms per growing season.

Bamboo forests in India, Bangladesh and Burma are generally managed
according to a "culm-selection method". The dead, dying, and oldest culms are thinned
out, care being taken so that one or two manue culms are retained adjacent to the new
culms to give stability (Sharma, .1980).

Bamboo areas should also be protected from fire and gazing animals. About 3-
4 weedings around the plant, hoeing around the plants, earthing up, and mulching

should be done during the first 2 years.

2.6. Harvesting and Transport
In 1986, Robillos repormd that clump-forming bamboo culms should be cut at

about 15 to 30 cm above the gonad, just above the node, in order not to leave a

31
receptacle in which rainwater can collect. Cutting the eulm too high results in
unnecessary waste leading to clump congestion and difliculty in harvesting.

Fellers can cut S. lumampao and D. merrillianus close to the gound Spiny
bamboo like B. blumeana is usually cut about 2 or 3 m above the gound, thus leaving
the best portion of the culm. The dense growth of spiny branches hinders the cutting
of spiny bamboo closer to the gound (de la Cruz. 1989).

The harvesting and tansport of bamboo is generally carried out by manual
means and requires skill, considerable patience and energy. Cutting is generally done
with a small axe, machete (bolo) or bill hook. Minor transport of bamboo is
sometimes mechanized, however, water buffaloes (carabaos) are often used to tansport
bamboo from the clump site to the roadside. Manual skidding of bamboo is also
common but is normally used for short distances up to 300 meters.

The subsequent major tansportation of bamboo is done with small tucks,
agieultural taetors and one or two axle trailers, or with water bufi’aloes pulling small
wagons. River rafting is used for long distance transport of bamboo (Lundel and

Liljibland, 1979).

2.7. Uses of Bamboos

Bamboos are suitable for a variety of purposes because of the strength of the
culms, their straightness, lightness combined with hardness, range in sizes, hollowness,
long fiber length and easy working qualities. These qualities prove to be useful for
many products in rural, urban and industial sectors of many countries (Table 3).

Specific uses for this study’s five different bamboo species in the Philippines are

32

Table 3. Consumption (%) of bamboos in the Asia-Pacific Region by end-use.

 

 

 

County End-Uses (percent)'
H OCP RU P PM OU
Bangladesh 50 10 20 5 10 5
Burma 33 32 32 5 - 1
India 16 16 30 7 17 14
Japan 24 l7 l8 7 4 41
2

 

‘H = Housing
OCP = Other constuction purpos¢s
RU = Rural uses
P = Packaging
PM = Pulp manufacture
OU = Other uses

Source: Sharma, 1985.

33

presented in Table 4.

2.8. Factors 01’ Production

In general, there are three essential but limiting factors of bamboo production,
namely: land, labor and capital. Capital as used in this study refers to the funds, tools
and other materials required in the development of plantations, managing the bamboo
stands, harvesting and transporting culms to roadside.

Land is a fixed resource whose area can be expanded only based on the extent
of open lands suitable and available for bamboo production. Site characterization has
not been conducted to delineate areas for this particular purpose, but based on the
recent land classification using the SPOT imagery, considerable hectarages may be
suitable for bamboo plantations (Appendix C). I

Topogaphically, the Philippines is mountainous having 58% of total land area
over 18% in slope (DENR, 1987). Review of the land classification made in 1986-87,
in line with the mandate of the CARP, indicated that some areas considered as
Alienable and Disposable (A&D) are actually under the forest category because the
slope is 18% and higher" This has resulted in a slight increase of Forest Land to 54%
from the total land area including areas which are yet to be classified (World Bank,
1989). In principle, these lands are public domain.

Land forms the basis for livelihood for a large percentage of Filipinos. For

many tibaal Filipinos across the archipelago, land is not only a means of livelihood but

 

7The main distinctions between A&D and Forest Land are legal and bureaucratic
and not biogeographic. Forest Land may be either steeply sloped or forested. The term
uplands as used in this study refers to the more steeply-sloped areas (above 18%).

34

Table 4. Breakdown of uses by species in the Philippines.

 

 

 

 

Uses Species‘
Bb Bp Da Dm
Walling x x
Thatching and roofing x
Constuction x x
Basket making x x
Cooking utensils x
Mats x
Water buckets/vessels x x
Fuel x x x x
Furniture x x x
Agicultural implements x x x
Rafts/floats L x x
Tool handles x x x
Fence x x x x
Shoots for food x x x x
Cart sheds/roofs x x x
Stakes x x x x
Fishing implements x x
Bridges x x
Barbeque skewers x x x
Trellises x x x x
Handicrafts x x x x
Afforestationlsoil x x x x
Banana props x
‘Bb = B. blumeana Bp = B. philippinensis
Da = D. asper Dm = D. merrillianus 81 = S. lumampao

Sources: Shanna, 1985 and Tamolang et al., 1980.

35
is also a spiritual source and a means of maintaining connectedness with their
ancestors. Land ownership, however, is greatly skewed (Friesen, 1988). This inequity
of land ownership and the resulting poverty of the rural Philippines form the basis for
agrarian unrest and discontent.

Rural programs are to be combined with stuctural reforms in the agrarian
sector to increase farmers’ welfare. Avushay and Srinivasan (1984) found that
government assistance policies without land reform will leave the welfare of each
potential tenant unaltered though affecting the level of output, the extent of tenancy,
and the welfare of the landlord. The increase in surplus of tenants credits as a result of
government subsidization will fully accrue to the landlord as a consequence.

"Land is the lifeblood of the Filipino people" (Friesen, 1988). Dining the
height of the insurgency problem in the South, the Kilusang Magbubukid ng Pilipinas
(KMP), a farmers’ organization warns :

"Fearfid forces still haunt

Our hopes, half won and half aborted

Listen, there will be no peace

Till we reclaim our land. "

Land has psychological and cultmal significance. It is a source of pride and a sense of
personal security.

Rm'al labor is abundant. Of the 21.6 million Filipinos in the labor force, ten
million are employed in agieulture and other related activities. Of these, five million
are landless workers, 2 million are tenants, 1.5 million own land they are filling, while
another 1.5 million farm public lands without the benefit of a title (PCSO, 1985).

Employment of the unorganized rural household sector is difficult if not

36
impossible to quantify and qualify (Laarman et al., 1980). This is due to the many
factors that have some bearing on the activities of farmers. In most cases, farmers
work on their own and do not concern themselves with the time involved in the
various activities they are undertaking. As defined by Byerlee and Eicher (1972), rural
labor demand and supply can be determined at the micro and macro-levels. At the
micro—level, labor demand depends upon such factors as seasonality, efl’ective demand
for the output of the sector, the production techniques employed, and the
availability of other factors such as capital and land. On the supply side, labor is
determined by such factors as health and nutition, family participation in the labor
force, and mobility of labor between small and large farms, farm and non-farm jobs
and different regions. The macro-level focuses principally on the high rate of
population gowth.

Several authors (Mazundar, 1989; Findley, 1987; Ledesma, 1982; Laarman et
al., 1980; Einsiendel, 1968; Maceda, 1967) indicated that social mores of rural
families ensure that all family members get a share of what the family produces and
that they enjoy an income (or consumption level) approximating the average
production of the farm. Obviously, there is no cpen unemployment because aside from
household labor, other relatives and hired workers are also sharing the workload.

In most cases, each family member does only a small share of the work so that
if one or two members of the family are absent, it is easier for the remaining members
of the family to compensate for the shortage by increasing their own share of the total
work requirements (Mazundar, 1989). In short, some family members are disguisedly

underemployed. Although they contribute little or nothing to production, they still

37
account for additional consumption. Therefore, it is possible to use the sm'plus labor in
productive activities outside the farm. Farm output will not be decreased by the
absence of these surplus workers: the possibility of "siphoning-ofi“ these workers
could be used to encourage activities away from the farm. Utilizing this labor source
will increase the total output of the economy, while maintaining the consumption level
either through fiscal measures or market mechanisms as Mazundar suggested. As
observed by Findley (1987) in a rural Northern Philippines setting, the sexual division
of labor calls for women and children to continue and intensify their work in the
agieultural sector, while men seek wage labor nearby or in distant locations as
migrant workers.

A case study by Laarman et al. (1980) of upland workers in the Philippines
indicated that income and employment for most of these people were derived from the
collection of so—called minor forest products.‘ Others were engaged on a part-time
basis to salvage timber for sale as pulpwood and fuelwood or for their own
consumption. Unfortunately, no measure was possible as to how much each person
was earning and how much time was spent on the myriad of activities each one was
undertaking. As Laarman et al. (1980) concluded, the determinant of the rural labor
absorption in the years ahead will be the effort committed to reforestation and
silviculture as the purely extractive logging phase comes to an abrupt end. What is

even more alarming is the increase of upland population. A World Bank study (1989)

 

'Minor forest products connotes a miscellany of leaves, stems, barks, roots, saps,
resins, flowers, nuts, seeds, etc. In 1980, about 85,000 persons were engaged in their
processing and manufacture (as distinguished from collection).

38
indicated a tremendous increase from about 5,868,000 in 1948 to 17,835,000 in 1988.
Population density grew from 39 person per square kilometer in 1948 to 119 in 1988.
This has added more pressure on the ever-deteriorating forest.

There is no questionthatpotential laborintherural sectoris abundant. In
many developing countries, however, the adoption of more labor-intensive methods is
constrained by credit and by wage and price policies that distort the real scarcities of
capital and labor. The imposition of a minimum wage and other extra social benefits
pushes the market rate of hired labor above its social opportunity cost. Society’s cost
of employing labor may be less than the low money wage because the value of an
alternative production program would be low (Laarman et al., 1980).

In terms of nual income, Knight (.1971) provided another view. He
hypothesized that the supply price of labor varies depending on whether the individual
or the household is the decision-making unit. If the marginal productivity of labor is
less than the average productivity, the household as a decision-making unit is willing
to subsidize a migrant relative. On the other hand, for an individual who cannot rent
or sell his land because of the communal landholding system, the average product of
labor is the relevant income. This shows that the agarian system can also determine
the level of the rural income. The rtnal Philippines typifies this condition due to close

family ties, molded in the Filipino culture.

Family Labor Participation
The amount of time devoted to work varies across males and females and

among children. In one survey in Laguna, Philippines, the findings unequivocably

39
indicated that adult women worked longer hours than adult men. The difference is
even more prevalent for nonfann males as a result of the high unemployment rate.

The difference, however, cannot be interpreted to imply inequality in work
effort, since they might be compensawd for by diflerences in the intensity of work
(Folbre, 1983). One hypothesis indicated that women might work more hours than
men simply because the particular type of work they do is less demanding or less
onerous. The mother has the contol of her own work pace, and her activity in the
household is not subject to direct supervision.

Examples of time allocation for adults and for children are summarized in
Tables 5 and 6. In Table 6, marketed work refers to labor that is either an activity
performed on their own farm or horns used to seek employment from ethers’ farms.
Household work, on the other hand, refers to the performance of household chores and
is not valued at a market price for the purposes of this study. These activities include:
cooking, taking care of the children, cleaning the house, doing the laundry, pitching
water and other activities routinely performed by any member of the household.

For activities where labor performed by females is a perfect substitute for jobs
performed by males, distinction between the sexes may no longer be an important
issue. A household’s labor availability for most farming activities, therefore, can be
directly inferred from the number and ages of family members.

There are several forms by which labor is exchanged or purchased in the rural
Philippines. One common form is the so-called Bayanihan in which labor is exchanged
without payments, (i.e., in kind). This is very popular in rice planting where the job is

preferably done in one short period of time. This type of arrangement is called

Table 5. Allocation of adult work time in Laguna households in hours per week.

 

 

 

 

Activity Father’s Mother’s Ratio
Time Time 112
(1) (2)
All households:
Market work 49.41 16.90 2.92
Home 3.44 51.56 .07
production
Total 52.85 68.46 .72
Farm households:
Market work 52.10 16.30 3.20
Home 3.20 50.30 .06
production
Total 55.30 66.70 .83
Nonfarm households:
Market work 45.50 17.70 2.57
Home 3.80 53.30 .07
production
Total 49.30 71.00 .69

t

Source: Evenson et al., 1979.

h

41

Table 6. Children’s time contributions to the household (average annual hours/child).

 
    

   
     
 

 

Age . Marketed Work Household Work Total Work Ratio

 

 

 
 
 

Gm“? (HIS) (HIS) (HIS) (Malc/
(Yrs) Female)
Male Female Male Female Male Female
3—5 0 0 92 137 92 137 0.67
6-8 218 116 200 274 418 390 1.07
9-11 302 434 306 473 . 608 907 0.67
12-14 885 464 351 790 123 125 0.98
15-17 1148 976 454 633 160 171 0.94
18 8: up 1523 1320 170 925 169 224 0.75

 

Source: Cabanero, 1977.

42
Contactrral Reciprocity, in which a voluntary ageement between two or more people
isreaehedtorenderaservicetowardoneanotherinaspecifiedwayforaspecified
time in the future. It is a form of mutual assistance (Hollnsteiner, 1979). It assumes
that the reciprocal acts are equivalent, their amount and form having been explicitly
mo upon beforehand

In harvesting, another form is termed Hunusan (participation by harvest). It is
practiced where any villager can participate in harvesting and threshing, and the goup
of harvesters is entitled to receive one-sixth of the output. From Hunusan, a new
system has evolved called Gama. This system is a form of contactual arrangement
wherein those who want to participate in harvesting agee to weed a field in exchange
for the right to be employed as harvesters . and receive one-sixth of the produce. On
rice farms, this system is very common.

Employment of hired labor is not commonly practiced by small farmers. It is
the small farmers who avail their services to big landowners. According to one study
(Hayami, 197 8), landless workers derived 80% of their income from hired
employment. Hayami added, that on the average, each working family member worked

about 160 days a year on income-generating activities.

Capital Requirements
Capital comes in various forms. The most critical is the availability of funds.
One study in Nigeria on small farms indicawd that access to loans was the major
determinant to attaining optimal income of farmers (Iniodu, 1981). The availability of

borrowed capital allows farmers to adopt improved technology, purchase equipment,

43
and procure additional material inputs. Moreover, it has raised the efficiency of labor.

The fuelwood production project in the Philippines has earmarked funds for
procurement of quality seeds, purchase of fertilizers and other purchased input because
farmers cannot provide these items from their own resources. As Hyman (1983)
indicated, utilization of family labor to the development of fuelwood plantations would
have been minimal if capital were not available.

Another important component of capital is technical assistance. For projects
involving small farmers, commitment by the government to provide technical help is
as important as providing the farmers with funds through loans. For example, the
failure of the fuelwood project in the Ilocos provinces was primarily attributed to

delinquent foresty extension workers (Hyman, 1983).

2.9. Analytical Methods

The preceding sections focused on the nwd and availability of physical and
economic data (and information) on bamboo production. This section presents
backgound literature on how these data relate to financial feasibility and plantation
development. Selected applications of benefit-cost analysis (BCA) and management
activity scheduling techniques are reviewed. Literature covered focuses on short
rotation crops which would use time frames comparable to those needed for bamboo
management.

' Financial Analysis
Generally called "investment planning" or "project appraisal", BCA is widely

used to evaluate the economic efficiency of government actions, projects or progams.

44
It is applied in almost all disciplinary fields.

There are two distinct aspects of project analysis: financial and economic.
Financial analysis takes the viewpoint of individual participants while economic
analysis takes the view of the society as a whole (Gittinger, 1982). In economic
analysis, taxes and subsidies are treated as tansfer payments, whereas, in financial
analysis taxes are teated as costs and subsidies as returns. Market prices are normally
used in financial analysis while adjusted prices (i.e., shadow prices) reflecting social or
economic values are required in economic evaluation. Finally, interest paid on capital
is never separawd and deducted from goss returns in economic analysis, while in the
financial calculations, interest paid on borrowed capital is teated as a cost and
deducted to derive net revenue. 2

A number of studies using BCA have been done in forestry (see for example,
Talbert et al., 1985; Crowell, 1984; Appleton, 1980; Ledig and Porterfield, 1982; Rose
and DeBell, 1978; Bowersox and Ward, 1976). On short rotation crops, Ferguson et al.
(1981) determined the financial viability of hybrid poplar plantations. They found that
the single most important factor affecting performance measures is product sale value
which has two components: yield and market price. A change in either or both could
substantially change the economic attractiveness of an investnent in hybrid poplar
plantations. A study on Paulownia plantations by Hardie et al. (1984) indicated that
well-managed plantations could be profitable provided prices are maintained at current
levels. Expansion of supply beyond the current consumption for the species could
drive Paulownia prices to levels that could make plantations uneconomic. In

evaluating a tee improvement program for western larch, Fins and Moore (1984)

45
found that results were most sensitive to changes in discount rate, site quality and
cone production rate. Even minor changes in factors greatly affected the analysis
outcome.

In the Philippines, two projects of vital interest are pulpwood plantations and
fuelwood production. Ex post financial analyses indicated that pulpwood plantations
yielded positive NPVs whereas fuelwood production had negative NPVs (Hyman,
1983). A number of factors influenced these outcomes. The post-project evaluation of
pulpwood plantations made indicated a modest success. The project succeeded in
recruiting a large number of participants due to (1) expectations of satisfactory
economic returns, (2) provision of technical extension services, and (3) guarantee of a
market for the product. It has, however, been afih'cted with several problems: (1)
abandonment of the sustained-yield agoforesty approach, (2) unanticipated harvesting
difficulties, (3) imposition of government price controls on newsprint that set a cap on
pulpwood value, and (4) selection of species that are prone to typhoon damage.

The fuelwood production project, on the other hand, was a total failure.
Primary causes as enumerated by Hyman (1984) were: (1) unchanging local cultural
attitudes, (2) limited borrowing, (3) inadequate extension services, and (4) dispersed
fuelwood markets. Insufficient retinns drove farmers to engage in planting fruit tees
and in upland rice farming. Additional causes unraveled during Hyman’s census of
participants revealed that (1) a large portion of domestic demand for fuelwood is
collected for free on lands belonging to the government, (2) some sites leased to

farmers are not suitable for fuelwood plantation development, (3) technical assistance

 

46

from the government was not sustained, and (4) species selection was erroneous.

Experiences gained from pulpwood production and fuelwood plantations
provide insights regarding factors that are most relevant in determining the outcome of
the project. These factors are largely not financial in nature. Economic and
financial studies, on the other hand, indicate that analysis results are often sensitive to
changing prices and costs. Hence, sensitivity analyses or numerous management
scenarios are often needed

Scheduling Techniques

Operations research (OR) techniques are commonly applied to seek the best
(optimal) course of action or decisions given limiwd resources. They provide decision
makers with information on which to base. decisions. OR mchniques systematize, in
certain conditions, the process of selecting the most desirable courses of action,
thereby leading to more effective decisions about resources under control. They
provide a way to arrive at decisions rather than simply using intuitive judgements as in
economics.

The second objective of this study deals with maximization. Several OR
wchniques involve optimization. Among them are linear programming, dynamic
programming, recursive programming, goal programming, and integer programming.
Most of these techniques have been applied to agroforesu'y (AF) problems similar to
bamboo production. Betters’ (1988) work focused on the importance of land-use
planning processes in specifying optimal AF systems. His approach enables the analyst
to harmonize traditional methods (i.e., BCA) of economic analysis with a linear

programming framework. The BCA approach takes care of determining the decision

47
variables while optimization methods are used to consider additional constraints and
requirements of problems common to small farms.

Linear programming is the most widely applied optimization technique; it has
been applied to several fields with impressive success. It has proved successful solving
problems in industry, agriculture, economics, transportation and health. Moreover, LP
provides important foundations for the development of solution methods of its
extensions (e.g., dynamic, recursive, stochastic and quadratic methods). These
extensions allow analysis of optimization problems incorporating market demand, time
and probability disuibutions. It has considerable flexibility. Variants of LP include
parametric or sensitivity models. They are used to test effects of price weights,
technical coefficients and resource constraints on the determination of optimal plans.

Application of LP techniques to real world problems concerning small
farmholders has been proven successful. Spencer (197 3) was able to determine the
efficient use of farmers’ resources in the production of rice in Sierra Leone. His one-
period LP model found that there was no correlation between farm size and output per
acre, but there is negative correlation between farm size and total labor use per acre.

In Nigeria. optimal cropping patterns yielding the highest net farm income
were analyzed by use of LP (Iniodu, 1981). Crop specialization was found to be most
profitable, and with the availability of borrowed funds farmers were able to increase
their profit by 30%. Borrowed funds not only allowed farmers to adopt improved
technology, but also enabled them to raise the efficiency of family labor use. Credit,
however, was only economically beneficial within a given range of interest rates.

Extending the ordinary LP to account for the time element was successfully

43
applied by Ogungbile (1980) in evaluating the improved sole-crop production
technology in Nigeria. Use of multi-period linear programming models was in
recognition that production is seldom instantaneous. His findings indicated that farm
size is valuable in determining profitability, because farms that are too small, though
operated most efficiently, will result in low income. Farm power sources are also
important in determining discounwd net income. Comparisons indicated that an oxen-
technology model has the highest net present value followed by a hand-labor system,
and the lowest NPV was derived from use of herbicides.

Another economic evaluation using LP to maximize net return of small
farmholders from agroforesuy was made by Verinumbe et al. (1984). Given the
resource constraints of the farmer and thentype of land to be developed for AF, the
maximum net profit that may be earned from a combination of crops was determined.
Furthermore, they demonstrated the advantage of LP over a simple farm budgeting
approach.

The work of Mendoza et al. (1986) is more comprehensive in the sense that it
can accommodate the various features of agroforesuy. Their conceptual framework of
multiple objective programming (MOP) allows simultaneous evaluation of several
objectives which is not possible in ordinary LP. The availability of several approaches
to generate MOP solutions, depending on the type of problem, makes MOP more

flexible.

l
I

49
2.10. Summary

Review of bamboo as a plantation crop revealed several interesting results. The
potential for commercial-scale bamboo cultivation is great due to the following:

(1). Bamboo has a shorter rotation cycle and grows a large number (i.e., 5-20)
of shoots sitnultaneously in one growing season. It is attractive in terms of crop yield
and earlier harvest compared to hardwood and softwood tree species. This makes
bamboo more suitable for those with limited capital who are interested in relatively
early returns on investments (MacCormac, 1985),

(2). Bamboo has a rapid natural early growth which can be enhanced with the
application of fertilizers. Traditional techniques of growing are relatively effective and
traditional sector demand is increasing. Expanding the raw-material base would
increase supply, and increased development of the processing sector is highly probable
(Garcia, 1986),

(3). Bamboo is well-suited to polycyclic harvesting, having a capacity to
regenerate through its rhizomes. It can be grown on a wide range of sites, has an
interlocking root system and has leaf deposition which can inhibit soil erosion (Austin
at al., 1983), and

(4). Bamboo has potential in pure plantations or in integrated farming systems
(e.g., agroforestry). Factors of production are locally available and abundant except for
capital.

Limitations on farmers’ resources are fully recognized as affecting choice and
adoption of specific technologies. Traditional methods of economic analysis are not

sufl’icient to integrate these limitations (Betters, 1988). Use of OR techniques in

50

combination with valuation techniques to determine economic performance are best
suited to address problems of this type. For this study, there are constraints on labor,
land and budgets. In particular, the capability of LP to maximize income, determine
optimal cropping patterns, and increase yield and labor use is important. If
assumptions regarding LP are met, it may be suflicient to satisfy the analytical
requirements of allocating farmers’ resources in combination with borrowed funds to
optimize returns. Integer programming and modifications advocated by Mendoza et al.
(1986) are inappropriate for the type of single-objective problem at hand. Dynamic
programming, nonlinear programming, and mixed integer programming may provide
alternative techniques for addressing this problem.

The appropriateness of each technique and problems associamd with their

applications are discussed in Chapter 3.

CHAPTER3

RESEARCH METHODS

3.1. Introduction

This study’s objectives of examining financial feasibility and calculating
optimal development schedules require several methods of inquiry. Since no studies
are available on management costs and returns for bamboo, primary data collection is
required. Standard financial analysis (or cash flow) methods are used to examine
financial feasibility. For maximizing NPV,_ of cash flows or amount of employment, an
analytical method that has the capability and flexibility of considering limited
resources simultaneously is required. Optimizing combinations of limited resources to
produce the desired goals (i.e., increasing income and/or employment) of the farmers
is the primary concern of this investigation. This chapter presents an overview of
optimization models-it provides the general framework for the analyses. Then a
specific model is formulated. data inputs are described and the analytic approach is

presented.

3.2. Optimization Modeling
Linear programming (LP) is one of several techniques that is capable of finding
an optimal solution fi'om a number of alternative choices. Traditional methods of

51

52

economic analysis (e.g., BCA) do not have the ability to handle limitations commonly
encountered by farmers. Though they provide a good conceptual framework. they are
limitedinflexibilityandinperforminganalysesonoperationalsystems (Mendozaet
al., 1986). Moreover, BCA does not explicitly consider the additional consu'aints or
requirements to the problem (Betters, 1988). However, the valuation mchniques that
providemeasmesofeconomicperformanceintermsofNPV,B/CrafiosandIRRme
valuable in generating the decision variables used in linear programming analysis.

Linear programming is a mathematical procedure for maximizing (or
minimizing) alinear objective function subjectto anumberoflinearconstraints. Ithas
three main components: (1) an objective function, (2) activities or processes, and (3)
linear resource/personal constraints.

The general model is:

Maximize z = z; (:ij (1)

n I 2
Subject to : Egauxjsq ( )

x, 2. 0 (3)

where: ‘
Z "-1 objective function,
xi = level of the jth activity,

b, = amount of the ith resource,

53
c’ = net revenue of the jth activity.
a“ = amount of ith resources required to produce a unit of jth activity,
m = number of activities, and

n = number of different resoruces.

A linear programming model is subject to restrictive assumptions of additivity
of resources and of activities, divisibility and finiteness of activities and resources and
non-negativity of activities (Dykstra, 1984). In addition, LP is deterministic. It is based
on the single value expectation assumption which indicates that the parameters of the
model are known for certain. These assumptions define the limitations of LP and also
indicate conditions in which it is useful. Other programming model modifications are
available to handle relaxation of most of these assumptions whenever it is required for
a specific problem.

One modification of LP is the multi-period linear programming approach
(MPLP). This is an extension of the LP model that incorporates a time element into
the formulation. The technique of MPLP permits the programming of activities and
restrictions for a finite number of years. Outputs of any one year may become inputs
for the following year. Thus, activities in each year or period represent the best or

optimal plan in terms of the specified time horizon (Ogungbile, 1980).

54

A MPLP model with financial discounting is formulated as:

n k

c tat , (4)

Maxim: e Z = —-7——-7-—

z .1 g (1+!) t
n I k b (5)

Sub act to : a S

j E g1 g; 1.189: 1:
x1e 2 0 ' (6)
where:
t= 1, 2,...k periods;

i= 1, 2,...m activities;

j= 1, 2,...n mm; and

r= discount rate in decimal form.
The variables of the MPLP model have the same interpretations as those of the basic
LP described earlier.

AnotherappmachisdynamicpmgrammingThistechniqueisanofishotof
optimal control theory. Application to production models, however, is severely limited
because of the enormous computations required (Minden, 1968). In fact, it is not
possible to write down a standard mathematical formulation that applies to all dynamic
programming problems (Dykstra, 1984). It requires a certain amount of ingenuity to
recognize that a problem is solvable by dynamic programming procedures.

Recursive programming is another wchnique closely associated with dynamic

programming. It is defined as a sequential optimizing rule with a functional

55
relationship between any given period and preceding periods. The main difference
between MPLP and recursive programming is that the former gives optimal solution
for the entire planning period (under very restrictive assumptions) while the latter
method provides a sequence of optimal solutions, one for each time period. While the
sequential solutions satisfy the maximization for each time period, they do not
necessarily satisfy the conditions for the entire planning horizon (Mendoza et al.,
1986).

Another technique is integer programming. It is an alternative approach
developed to handle problem situations where all or some of the variables are
resuicted to integer values. In this study, all activities can have non-integer solution
values so integer and mixed integer programming are inappropriate.

Nonlinear programming is an appropriate approach if function or at least one of
the constraints is nonlinear. In this method, no general algorithm is available mainly
because of the irregular behavior of the nonlinear functions (Taha, 1987). The
application of the Kuhn-Tucker algorithm is very limited for solving these types of
problems. Nonlinear programming includes separable, quadratic, geometric, and
stochastic formulations. Since the objective function and constraints are heated as
linear in this study for these small-scale plantations, nonlinear programming is not
needed. However, if larger scale operations were used or other problem modifications
occurred, a nonlinear programming formulation may be required.

A non-optimization approach that provides insight into a variety of
relationships is simulation modeling. This approach is suitable when the decision

process is so complex that it cannot be handled by a single analytical procedure.

56.
Simuhfioncanbeusedtogeneratethenecessuysequencesofdamwthesystem’s
behaviorwnichcanmenbeanntymdbyomermchmnueenremaindisadvanmgeof
simulationmodeltechniqueisthatitdoesnotguaranteeanoptimum solutionas
comparedwith solutions generamdbyothertechniques ('l'aha. 1987). ~

Thus,LPisusedindrissmdybecauseithasdreflerdbilitymoptimizerennns
bycombiningscmceresomcessuchashbormapimlandlandfiomtheperspecdve of
srnallfarmers (Iniodu, 1981; Niang, 1980; andOgungbile, 1980). Itcan be extendedto
the multi-period case where time element is incorporated. Verinumbe er al. (1984)
haveevennowdthatLPissuperiormBCAbecauseLPaccountsfortheresomce
bases offarmers. Ptn'thermore,veryefficient methods ofsolutions havebeen

developed for LP problems in real world situations (Taha, 1987).

3.3. Model Formulation

Linear programming provides a satisfactory approach for addressing this
study’s second objective. The detailed formulation is:

Mm Z "" crxrfifiwfiswfi (7)
Meet to = anti 5. b1 (8)
‘n’r‘azzxz 5 b2 (9)

asrxrwarzmee 5— b3 (10)

57

' “4131 “‘4’: “‘43”: ”“13. 5- b4 (11)
mmwwwwwmmse an
«wwwMfiMWWfisky um
aqrxrflnfimn": +9.14%: 5- 31 (14)

mwwawmwmflw¢Esam
nwwwmss (m

ZatotalNPV.

c,=NPV(1989pesos)perhectare;8ubscripttmfmt0thcycaraplantation
was established (1, 2, ....“5).

eahecmesdeveloped: subscriptreferstotheyearaplantationwas
established

a,,=levelofcapital(l989pesos)requiredtoplantinyeartandmaintain
hectaresdeveloped:subscliptyreferstoyearduringtheanalysisperiod
@me. ‘

b, . level ofcapital (1939 pesos) available; subscript refers to year in which
investment/borrowingwasmade.Thisamountisequalto4timesthe
amount of family labor contribution (FLC) by year. Nate that borrowing is
annualbasedonthe amount of FLO-

R, = refers to gross revenue and subscript refers to year the harvest will occur.

5 8
Equation (16) limits each farmer to five hectares. The objective function (Z) is
formulawd to be either in pesos, when maximizing NPV of cash flows or in person-
days when maximizing labor use.

The separate treatment of NPVs for plantations developed in the different years
indicated in the right hand side (RHS) of the objective function accounts for the effect
of plantation scheduling. Delaying establishment lowers NPVs because years with
positive cash flows are shortened and values are discounted. Cash flows beyond 25
yearsareignoredbecausethatistheproposedleasedln'ationandthis is agovernment
land (i.e., farmers cannot sell land).

TheswitchoftheRHSintheconstr'aintsfromb,toR,when thefirstharvestis
realized is a mechanism to evaluate the performance of bamboo plantations. The self-
sustainability of the project is gauged based on how values of RHS can meet the
annual cost requirements of plantations developed from previous years using family
labor in combination with borrowed capital The switch from b, to R, as a RHS is
variable and indicates borrowing has ceased and then a lO-year loan repayment
, schedule has begun. Thus, the revenues and FLC must be able to maintain the
plantations and repay loans. Depending on the rotation of the bamboo species being
analyzed (ranging from 3-7 years), the RHS will shift from b, to R, at different years.

What’s Bestl, a LINDO-based linear programming (LP) software package
(Savage, 1990), was used to generate solutions. Models were developed in a
spreadsheet environment and solved on a microcomputer.

Data used in the LP models include: periodic costs of production by

management scheme (species, spacing, source of planting material, site characteristic,

59
cutting age and cutting cycle) and by region; yield data; harvesting and hauling costs;
farm gate prices for bamboo; family labor, amount of loan; amount of land; discount
and interest rates; and labor cost. While some data were directly entered into the
model, other data were pre-compumd using the traditional analytical methods of
determining economic measures of NPV, BIC ratio and IRR before they were entered
as decision variables. Some data were based on assumptions as further explained

below.

3.4. Data Collection

This study makes use of survey and secondary data. Procedtn'es of how these
data were collected and collated to harmonize data from various sources are outlined
below.

Costs of Production

Production cost information were gathered fiom three pilot projects coordinated
by ERDB and directly administered by the Regional offices of the DENR. Production
input data forms (Appendix Table D l) were distributed to respective project
supervisors in Regions 6, 7, and 11. Completed forms in the regional offices were
fm'ther verified with the ERDB records to make sure that actual activities/expenses
performed/spent in the field tallied with the quarterly financial statement prepared by
the Project Staff. Since pilot projects are relatively new (about 3 years), cost on
maintenance operations before first harvests occur were taken from the records of

ERDB. Harvesting and hauling costs were taken from the study of de la Cruz (1989).

60
Yield Data

Standard bamboo yield tables are not available at this time, and harvests from
pilot plantations are not yet allowable. Therefore, yield data were gathered from the
records of ERDB. Annual harvests for 9 consecutive years (1978-1986) were collawd
and entered into a prepared format (Appendix Table D2) to suit the data requirements
of this study. Data on periodic harvests for B. philippinensis were taken from the
records of Mr. M. Caasi. Harvested culms were segregated by quality classes to reflect
the actual returns differentiated by farm gate prices. Since yield data represent nine
harvests only, projections were made to cover the entire analysis period by simple
linear regression technique. This approach is deemed appropriate because no other data

(i.e., edaphic or climatic factors) are available to use in the estimation of future yields.

Farm Gate Prices
A sru'vey was conducted to determine the current buying prices of bamboo
culms in all three regions. Survey questionnaires (Appendix Table D3) were prepared
and ten respondents were randomly sampled in every region. Buying prices for each

species in each region were tallied and the averages were computed.

Household Profile Survey
A survey instrument in the form of prepared questionnaires (Appendix Table
D4) was used to gather profiles of households included in this study. Thirty
households. were randomly sampled from a population of 102 in Region 6, 90 in

Region 7 and 137 in Region 11 for face—to-face interviews. A preliminary list of

61
householdswasobtainedfromtheBarangay’Oficeprim'totheselectionof
respmdmmSelecdonofsampleswasconfinedmmeasadjacentmthelocadonof

Acombinationofobjecdve(AppendixTahleD4,Quesdonsl-9)andsubjective
(Questions lO-13)methodswasusedtoestimatedrearnountofexcesslabm'.The
objecdvemethodisbasedondreproductionapproachfiommenounalacdvides
undemkenbythefamerswhilemesubjecfivemethodisbasedonmewflfingnessof
drefarmersmcommittheirexnadmembambooproducdonwithomunneeessarfly
disrupdngthenmgulufamjob.Thishnerapproachwuaddeddufingmeconductof
thefieldsmveymrunedyaproblemofnondesponsefm'somequesdmsbyselected
householdsdmingmesmvey’svafidafionphaselndusimsofdireaquesdmswae
suggestedbytheProjectStaffaswellasbyBarangaycouncilmembers.

3.5.DataAnalysis
Theanalysisissplitintotwoparts.Thefirstpartdealsstrictlywiththe
financialviabilityofbambooprodnctionbasedonthedifierent managementschemes
indneeregiomofthecolmuyflhesecmdpmrexplmesdrepossibifityofhowmnafl
farmers’ involvementinthedevelopmentofbambooplantationsafiectsplantation
devehpmemmhedulingTheevaluafionisbasedonthefamflylaborconnibufion
(FIQofsmanfummT‘woobjecdvefuncdomueuMmardmizingnetpmsent

l
s

 

’Borangay is the smallest atbninistrative unit of the government. The governing
council is headed by a Borangay Captain with eight members elected at large.

62
value and maximizing labor use. The former is of specific interest to farm families

while the latter may have broader social implications.

Financial Analysis

Three discounted measures were used to evaluate the feasibility of investments
in bamboo production. These measures based on financial criteria are: net present
value (NPV), benefit-cost ratio (BIC), and internal rate of return (lRR).

Net present value is defined as the discounted value of expected future returns
minus the discounted value of funue costs, using the appropriate discount rate.
Gittinger (1984) described this meastue as the most straightforward calculation (i.e.,
discounted cash flow stream) of project worth. It is interpreted as the present worth of
the income stream accruing to the individual or entity. In practice, it is easier to
compute NPV by discounting the incremental net benefit stream or incremental cash
flow.

The formal selection criterion for the NPV of a project worth is to accept all
independent projects with a zero or greater NPV when discounted at the opportunity
cost of capital (Gittinger,1984; Mishan, 1982). No ranking of acceptable, alternative
independent projects is possible with the NPV criterion because it is an absolute, not a
relative measure. This means that small projects cannot be compared to big projects by

just looking at the NPVs. The functional form is presented in Equation 17.

" B-C
NPV = ' ‘ (17)
gr: (1+i)‘

 

63

where:

B, = benefit (pesos) in each year,

C, = cost (pesos) in each year,

t = 1, 2, ..., 11 years, and

i = discount rate in decimal.

Internal rate of return is the discount rate that makes the NPV of the net
benefit stream or cash flow equal to zero. It is the maximum interest rate that a project
could pay for the resources used if the project is to recover its invesunent and
operating costs and still break even. In other words, it is the average annual percentage
rate of return earned on all invested capital over the project’s life. It is one of the very
useful measrnes of project feasibility. ‘

The formal selection criterion for the IRR of project worth is to accept all
independent projects having an IRR equal to or greater than the opportunity cost of
capital. It should be noted, however, that lRR of a series of values such as cash flow
can exist only when at least one value is negative. If all the values are positive, no
discount rate can make the present worth of the benefit stream equal to zero.

Projects cannot be ranked with confidence on the basis of the IRR, though it
varies from project to project Only a rough approximation can be made based on the
cut-off rate of the opportunity cost of capital. In other words, it cannot be known with
certainty that one project contributes relatively more than the other if both projects

have an IRR greater than the cut-off rate.

64

The NPV formula including IRR is shown in Equation 18.

may . 2': 3i . o as)
M (ls-Hilly

Benefit-cost ratio is obtained when the present worth of the benefit stream is
divided by the present worth of the cost stream. This measure is highly dependent on
the discount rate. The higher the discount rate, the smaller the resultant BIC. It is
useful in measuring how much costs could rise without making the project
economically unattractive.

The formal selection criteria for the BIG ratio measme of project worth is to
accept all independent projects with a BIC ratio of l or greater when the costs and
benefits streams are discounted at the opportunity cost of capital. Caution, however,
must be observed in the case of a mutually exclusive projects (Gittinger, 1984). The

BIC ratio formula is presented in Equation 19.

i 3'
BIC = :42? (19)

I

M (1+i)‘

 

 

3.6. Repayment of Loan
The scheme for servicing borrowed funds adapted in this study assumes equal
installments with interest capitalized. This means that a farmer is not required to pay

any amount, even the interest, during the grace period. The interest due is, in effect

65
added to the principal of the loan (Gittinger, 1982). Remittances for loan are made in
a series of equal installments beginning in the first harvest year.

The grace period is the time interval between plantation establishment and the
time of first harvest. It varies between 3-7 years depending on the type of species.
Repayment of the principal plus the capitalized interest is assumed to be in 10 equal
annual installments commencing at the end of the grace period. For species where
harvest is possible at year 4, the loan servicing is complete by year 13, but for species
whose first harvest may not take place till year 8, the repayment extends to year 17.

The formula for an equal annual payment is presented in Equation 20.

= P ram" (20)
' (l+i)"-l

where:

A = equal annual payment,

P = present total amount at the end of the grace period,

n = repayment period, and

i = interest rate.
Values generated in Equation 20 are undiscounted and are entered in the analysis as
additional cost. In the LP problem, the payments are treated in constraints as annual

costs and in the NPV objective function, as present values.

3.7. Summary

Linear programming as an analytical technique has the flexibility and capability
deemed appropriate for the type of problem at hand. Linear programming (LP)
procedures can be readily modified to accommodate specific requirements of the
problem. Close linkage of LP methods with traditional economic approaches to
evaluating financial profitability of investments is an additional advantage. These two
approaches are complementary for the type of analysis required in this study.
Furthermore, availability of LP software programs which can be readily modified to

suit the goals of the users makes this technique appealing.

CHAPTER4

RESULTS AND DISCUSSION

4.1. Introduction

This chapter consists of three sections. The first section focuses on the
survey/data results. It describes the type of data obtained from secondary sources and
those that were gathered from the survey. Also included are additional assumptions
used in the analyses. The second section deals with the financial analysis. Individual
management schemes (MS) were evaluated to determine the efi'ects of the difl'erent
factors on the viability of bamboo management. This is followed by a section on
bamboo plantation development scheduling.- Family labor contribution (FLC) based on
household type together with other limiting factors (e.g., land and borrowing) were
evaluated. Linear programming (LP) models were used to test the effects of these
factors on net present values (NPV) and total amount of employment. Optimal

solutions were generated based on individual species by household type in each region.

4.2. Survey/Data Results

The choice of whether farmers grow their own planting stock or buy planting
stock fi'om‘ nurseries is one decision that has wide ranging implications. Field survey
results indicate variation in cost of materials. Nursery grown stocks are more
expensive than buying culms because of the cost of propagating the material as

67

68
indicated in the survey (Table 7). Cost differences were also observed for harvesting
and hauling (Table 8). These values are used as inputs in calculating NPVs for the
different schemes and regions.
Yield Data

Basic yield data for B. Blumeana is presented in Appendix Tables El and E2;
for B. philippinensis in Appendix Tables E3 to E6; for D. asper in Appendix Tables
E7 and E8; for D. merrillianus in Appendix Tables E9 and E10; and for S. lumampao
in Appendix Table E1 1. Projected yields are likewise presenwd in Appendix F.

For B. blumeana, per hectare yield ranges from l,026-l,407 culms at 7x7 m
spacing and 489-670 culms at 10x10 m spacing. For B. philippinensis, when planed
on flat terrain, per hectare yield ranges from 5,858-6,l6‘7 culms while on hilly terrain,
the yield is from 5,428-6,093 culms. For D. asper, the yield is final 975-l,216 culms
at 7x7 m spacing and from 465-665 culms when planted at 10x10 m. The yield for D.
merrillianus ranges from 904-l,166 culms at 7x7 m spacing and from 430-555 at
10x10 m. For S. lumampao, the projected yield per hectare ranges from 3,240-4,460
culms.

Farm Gate Prices

Buying prices vary within and between species and between regions. Culm
quality is one important factor in the determination of price. Straight culms are highly
desirable in construction while longer culms are preferred in the fishing indusuy. For
banana props, smaller sizes and shorter poles are required Weaving and production of
fancy items need thin-walled species. Average farm gate prices for each species in

each region are presented in Table 9.

69

Table 7. Average cost of planting material by species in 1989 pesos (P).

 

 

Species Type of Planting Price (Pesos)
Material‘

B. blumeana culm P40/culm
A nursery grown P25/stock

B. philippinensis culm P5/culm
nursery grown PlO/stock
D. asper culm P30/culm
nursery grown P20/stock
D. merrillianus ‘ culm P25/culm
nursery grown P20/stock

S. lumampao culm P5/culm
PIG/stock

== 1

nursery grown

 

   

'Nursery grown refers to stocks purchased by the farmers from independent
producers for outplanting. Culms refers to young bamboo poles which are
suited for growing as planting stock and to be raised by the farmers.

Source: Survey data.

Table 8. Average harvesting and hauling costs per culrn by species in 1989 pesos (P).

 

 

Species Harvesting Hauling Total Cost
(P9808)

B. blumeana P2.00Iculm Pl.00/culm P3.00Iculm

B. philippinensis P0.25/culm P0.25/culm P0.50/culm

D. asper Pl.50/culm Pl.00/culm P2.50/culm

D. merrillianus Pl.00/culm Pl.00/culm P2.00/culm

s. Iumarnpao P0.25/culrn P0.25/culm P0.50/culm

 

Source: de la Cruz (1989).

70

Table 9. Average buying prices per culm by quality type and by species in 3 regions
in 1989 pesos (P).

 

 

 

Species Quality‘ Region
6 7 11

B. blumeana high P20.00 P25.00 P20.00
ave. P1800 P2000 P1800
low P15.00 P15.00 P15.00

B. philippinensis normal - - P2.50
over-s - - P4.00

D. asper high - P2000 P1800
low - P15.00 P15.00

D. merrillianus high Pl7.00 P17.00 -
low P15.00 P15.00 -

S. lumampao - P300 P300 P300

 

 

'For B. blumeana, high quality calms are those that are straight, 10 meters or
longer; average quality are those that are below 10 meters but not shorter than 8
meters and relatively straight; low quality are those of smaller and shorter culms and
usually crooked.

For B. philippinensis, normal sizes are those that attained at least 16 feet in
length with a base diameter of 2.5 inches and bigger; culms whose length exceeds 32
feet are classified as oversized. Those culms that are crooked and less than 16 feet
and base diameter of less than 25 inches are rejected.

For D. asper, high quality are those that attained 15 meters or longer in
length and relatively straight; those that are crooked, smaller, and shorter are
classified as low quality.

For D. merrillianus, high quality are those culms that are relatively straight,
at least 8 meters in length, and a base diameter of not less than 4 inches. Those that
are crooked, smaller, and shorter than 8 meters are considered low quality.

For S. lumampao, no strict classification is adapted. Selling/buying is based
on number of calms harvested without particular concern on length and diameter,
although extremely smaller and immature culms are discarded.

Source: Survey data.

7 1
Surplus Household Labor

Household as used in this study refers to a single dwelling unit composed of
not only the immediate members of the family (i.e., parents and children) but also
other members of the clan living with the family. Household type (HT) refers to its
composition (number of persons).

Six household types per region were identified on the basis of thirty samples
interviewed in each region. Amount of family labor contribution (FLC) varies. Labor
availability varies with the number of working members of the family. Another
variation of FLC is seasonal fluctuation. When dry and wet months are distinct
(Climatic Type 1), characteristic of Regions 6 and 7, fluctuation is apparent because
conflict arises from other farm activities. But when rainfall is evenly distributed
(Climatic Type 4), other farm activities can be adjusted as is the case in Region 11.

Total marketed labor for each household type based on percent contribution of
all adult family members is presented in Table 10. An adult is a person 15 years old
and older regardless of gender. Young children are those below 15 years old, but not
younger than 10 years old Small children are those below 10 years old Other refers
to those that are not members of the immediate family.

The amount of labor each household can commit to bamboo production is
computed based on labor availability of the husband, wife and adult children only.
This assumption is based on the premise as noted by Findley (1987) that in the rural
Philippines, division of labor calls for women and young children to intensify their
work in the field, while men and adult children seek wage labor nearby. The survey

results confirm this finding. In most cases, husbands seek employment for wages to

‘72

Table 10. Household type (HT), household composition, percent labor contribution
of adult family members and total markemd labor in 3 regions.

       

Household Family Contribution of Total Labor

 

 

 

 

 

 

 

Type (HT) Composition Family Member to in Person-
’ Markewd Labor-(%) days
HT 1 Husband 100 264
Wife 25 66
1 Adult 50 132
1 Young 0 0
2 Small 0 0
Total 462
HT2 Husband 100 264
Wife ., 50 132
2 Adult 25 132
2 Young 0 0
Total 528
I-IT3 Husband 100 264
Wife 66
1 Young 0 0
2 Small 0
Total 330
HT4 Husband 100 264
Wife 50 132
1 Young 0 0
.‘ 1 Small 0 0

 

Total 396

 

73

Table 10 (continued)

 

Household Family Contribution of Total Labor
Type (HT) Composition Family member to in Person-
Marketed Labor (%) days

 

 

 

 

 

HTS Husband 100 264
Wife 25 66
1 Adult 100 264
1 Young
3 Small

Total 594

HT6 Husband 100 264
Wife . 50 132
2 Adult 100 528
1 Young 0 0

Total 924

 

 

Som'ce: Survey data.

74
meet the cash needs of the family.

The amount of FLC provides the basis of classifying households into 6 types.
Typing is based on the number of respondents for a particular group. Those with most
respondents are classified as household type 1, the second highest number of
respondents as household type 2 and fm'ther down to household type 6. Thus,
household type numbers reflect the relative abundance of family labor for a given
household

Family labor availability is affected by seasonal differences roughly reflected
by quarters as presented in Table 11. In Region 6, FLC ranges from 104096 of total
marketed labor depending on quarter; in Region 7, FLC ranges from 10-50%; and in
Region 11, FLC is stable at throughout the year at 30%. The amount of excess labor
varies by household type and region. For example, there are only 76 person-days of
labor available in household type 3 in Region 6. Household type 6 has much more
available labor; this provides more equity if needed for plantation development.

In the analysis, total annual labor was considered instead of quarterly labor
availability because of the prevalence of labor exchange between farmers. Required
labor requirements can easily be secured from other farmers in case where family
labor availability is not sufiicient. The assumption of taking the total labor to serve as

equity will allow farmers more flexibility in scheduling their on-farm activities.

4.3. Other Assumptions
Assumptions are necessary in virtually all economic analyses. The following

assumptions were made for this study:

75

Table 11. Amount of labor each household type (HT) can commit to bamboo
production by quarter (% of person—days in column 4 of Table 10) for 3

 

 

 

 

 

 

 

 

 

 

regions.

Region Qtr‘ 96 Household Types
1 2 3 4 5 6
6 l 25 29 33 20 24 37 57
2 40 46 52 32 39 59 92
3 10 11 13 8 9 14 23
4 20 22 26 16 20 28 46
Total 108 118 76 92 138 218
7 1 30 34 39 24 29 44 69
2 50 57 ‘66 41 49 74 115
3 10 11 ' 13 8 9 14 23
4 20 22 26 16 20 28 46
Total 124 144 89 107 160 253
11 l 30 34 39 24 29 44 69
2 30 34 39 24 29 44 69
3 30 34 39 24 29 44 69
4 30 34 39 24 29 44 69

96

 

3 = July-September
4 = October-December

Source: Survey data.

76

1. Discount Rate = 10%. This is the real interest rate. This was computed from
the average lending rate of the Central Bank of the Philippines minus the
average inflation rate fiom 1983-1990. The interest rates for the past eight
years are shown in Appendix F. While the discount rate is fairly stable the
lending rate fluctuates from year to year as a result of inflation. For
purposes of this analysis, the 9.86% is conservatively rounded to 10%. The
real lending rate calculated from the Central Bank data was also 10% and

used as a basis for repayment of loan.

2. Tax Rate = 5% of gross sales of the product.

3. Land Rent = PlOO/hectare/year.

4. Time Frame = 25 years based on a Leasehold Contract (Lease) of 25 years

renewable for another 25 years based on the some established criteria.

5. Area Limit = 5 hectares per family.

6. Family labor contribution by household type as shown in Table 11 is
assumed to be constant throughout the plantation development phase, which
is limited to the first five years from the time when a Lease is awarded It is

fluther assumed that no major change in FLC is expected to occur for the 5-
year period

7. Borrowed Funds = up to 3 times the amount of FLC in peso equivalents.

The loan is annually provided from the time of approval of the Lease until
first harvest is realized

8. Labor Wage = P75 per person-day based on the minimum wage for

agricultural worker in 1989.

77
Assumptions 2-5 are based on existing policy applied from other projects (i.e.,

fuelwoood plantations and agroforestry).

4.4. Financial Analyses

This part of the analysis provides estimates of returns assuming farmers have
all the resources needed to develop and manage the plantations without borrowing
funds. Other assumptions regarding these analyses are mentioned in the prewding
section in Chapter 3. Thus, the only concern here is to determine if investment in
bamboo production pays. Factors considered in bamboo management are species,
spacings, site, harvest age and schedule. Seasonal variation was not included because
of data limitations.

The net present value (NPV), the Benefit-cost ratio (BIC), and the internal rate
of return (IRR) of the different management schemes included in the analysis are
presented for each species. Each scheme is evaluated to determine its financial
performance so that individual farmers can have a wide array of choices in the event
they finally decide to engage in bamboo production. Regional variations are also
considered because of the difl’erences in the market prices of the product (Table 9).
Other factors of production, however, are assumed to be the same across regions
because primary sources of the data are government-administered projects. Labor
wages, cost of materials and other miscellaneous expenses relative to the development
of pilot plrlntations are equal according to the records of the Project Staff, Bamboo

Research and Development Project.

78
Bambusa blumeana
This species is widely used in all three regions covered in this study. The
values of NPV between regions are different (Table 12). The most important factor
influencing the variation is the difference in bamboo market price. All management
schemes passed the NPV criterion in all regions. However, file NPV difference is large
across regions. Comparing the NPV of the same scheme between regions, Region 7
Scheme 1 (i.e., 7x7 m spacing with a "grow" stock some and first cut in year 7) has
a value of P56,823, whereas, only P37,340 is realized in Regions 6 and 11. This wide
variability is solely attributed to the difference in the market price. Regional variation
in prices or costs for a given scheme could lead to profit in one area and possibly
losses in another. 1
Evaluation of the different management schemes indicawd that spacing,
establishment of farmer’s own nursery (raising their own planting stock) and harvest
schedule are all critical factors in bamboo management. At 7x7 or spacing with
farmers producing their own planting stock, and assuming all other factors constant,
the highest attainable NPV is P56,823 as compared to only P22,555 at 10x10 m
spacing. Reduction in income attributed to spacing is large so that in project design
this factor should be carefully considered Long-term studies on spacings are needed.
However, when bamboo stands are properly managed and an adequate number of
young and healthy culms are retained, productivity is enhanced (Uchimm'a, 1980).
Concerns that closer spacings may result in early overcrowding and subsequent
reduction in culm yields may not pose a problem. Bamboo stands can be manipulawd

to allow continuous regeneration at high levels.

79

Table 12. Results of the financial analysis for Bambusa blumeana on flat terrain with
annual harvests at 10% discount rate in 1989 pesos (P).

-—

Spacing

 

 

 

 

 

 

Region Stock Source' First Cut PNV BIC IRR

(m) (P) (‘70)

Grow Buy

7 7x7 x Year 7 56823 1.83 21.9
6 8t 11 7x7 x Year 7 37340 1.57 18.7
7 7x7 x Year 7 57827 1.85 22.4
6 & 11 7x7 x Year 7 38344 1.56 19.1
7 7x7 x Year 8 45033 1.67 18.9
6 & 11 7x7 x Year 8 27658 1.41 16.1
7 7x7 x Year 8 46036 1.69 119.3
6 & 11 7x7 x Year 8 28662 1.43 16.5
7 10x10 x Year 7 22555 1.60 18.1
6 8t 11 10x10 x Year 7 13280 1.35 15.2
7 10x10 x Year 7 22908 1.62 18.3
6 8t 11 10x10 x Year 7 13633 1.37 15.4
7 10x10 x Year 8 17007 1.47 15.8
6 & 11 10x10 x Year 8 8736 1.24 13.3
7 10x10 x Year 8 17358 1.48 16.0
6 8e 11 10x10 x Year 8 9087 1.25 13.5

 

'Buy- farmers purchase planting stock fiom a nursery.

Grow- farmers grow their own planting stock.

80

Whether farmers will establish their own nlnseries or buy planting stock ready
for outplantin g is another choice which has important implications on profitability.
Raising bamboo planting stock is technically diflicult because of its dependence on
vegetative propagation. Techniques for mass propagation through other means are yet
to be developed Buying planting materials ready for outplanting may, therefore, be
preferred to raising planting stock. The highest NPV for a scheme which includes
raising planting material (i.e., MSl), all other factors constant, is slightly lower at
P56,823 whereas the comparable scheme which directly buys nursery stock (i.e., M82)
is P57 ,827 .

Harvest schedule and first harvest age are two other factors of importance in
the management of bamboo plantations. For this species, the harvest schedule is
annual once it commences in year 7 or 8. If the harvest schedule begins in year 7,
culms 3 years old andolder are harveswd Ifthe schedule begins in year 8, culms 4
years old and older are harvested While the properties of a 3-year old bamboo culm
are not much different to a 4-year old in terms of physical and mechanical
characteristics, the timing of the first harvest is very critical.

The highest attainable NPV if harvest schedule commences in year 7 is
P57,827. By postponing the harvest schedule by one year (i.e., from 7 to 8) and using
an older minimum culm age (i.e., 4 instead of 3), the NPV is reduced by 20% or
down by P1 1,791. This has wider implications to the overall performance of the
plantations: If at year 7, the clumps have not yet fully developed to allow harvesting,
postponing the first harvest by another year would decrease the expected NPV by as

much as 20%. It seems apparent, therefore, that maintenance operations and protection

81
meastnes are very critical in optimizing returns from engaging in bamboo plantation.
Thetimefactoris sovital thatcare andmanagementofthestands shouldnotbetaken
for granted
Bambusa philippinensis

The hunt of production from this species is markemd to the banana plantation
owners in Region 11. No other region is engaged in plantation development of this
species at present. In Region 11 several private individuals are involved in planting the
species. Management schemes employed by a private grower in the region form the
basis of the financial analysis of this species.m

Evaluation of the eight (8) management schemes indicate a very high NPV for
all schemes. Like B. bambusa, all schemes passed the financial-analysis criterion for
acceptability. Variations, however, are apparent due to sites, harvest schedule, and
source of planting stock. Spacing is not considered a variable because only 4x5 m
spacing is used throughout the plantation from which data were gathered

Plantations on a relatively flat terrain (i.e., 18% slope or less) yield more than
those on hillsides, ceteris paribus. This is reflected in a high NPV of P44,623 per
hectare on flat sites compared to only P31,829 on steeper terrain. The difference is
very significant . However, considering that not everyone could acquire the most
productive sites, developing plantations on hilly terrain is still a worthwhile

undertaking from an NPV perspective. Working conditions are also totally difl'erent

 

”Mr. M. Caasi provided data on plantation establishment and yield. Labor on
person-days were converted into pesos (P) and yield in terms of number of culms were
converted into pesos based on the current buying prices of the banana growers.

82
between sites (pers. comm., M. Caasi). More favorable conditions are obtained in
relatively flat terrain. Due to diflicult working conditions in hilly areas, development
costs are much higher. This has significant efl‘ects on the reduction of NPV along with
differences in yield (Appendix Tables E3 and E5).

Harvest schedules are critical. One practice is annual while the other is
periodic. Annual harvests are for culms 1-year old and older commencing in year 4
and leaving behind shoms and younger culms. The highest NPV for annual harvests is
P44,623 (Table 13a). For periodic harvesting, the practice is to conduct the first
harvest in year 4 with subsequent harvests every three years thereafter. This means
thatsecondharvestisperformedinyear7, thirdharvestinyear lOandsoon. The
highest NPV for this practice is P38,150 (Table 13b); much lower than the comparable
annual harvest as shown in Table 13a.

The unequal occurrence of benefits between the two methods affects NPVs
because of the discounting process. In periodic harvesting, there are years that no
benefits are possible, though in some years the benefits are much higher than those for
stands managed under annual harvests. It is alleged that as clumps grow and mature,
emerging shoots begin to grow bigger. Hence, culms size may increase beyond the
specifications of the banana growers. Research on this aspect has just started and
information is limited in predicting the performance of the bamboo stands subject to
these different regimes.

The efl'ects of site on NPV are significant. On relatively flat sites, the
highest attainable NPV is P44,623 while in hilly terrain, NPV drops to P31,829,

ceteris paribus. This is explained by the difference not only in yield but also by the

83

Table 13a. Result of the financial analysis for B. philippinensis at 4x5 m spacing with
annual harvests at 10% discount rate in 1989 pesos (P) in Region 11.

fl
:7

 

 

 

 

Site Stock Source' NPV (P) BIC IRR(%)
Flat Hilly Grow Buy
it x 43014 1.48 28.0
x x 44623 1.51 29.8
x x 31470 1.35 22.5
x x 31829 1.36 22.8

‘See footnotes in Table 12.

Table 13b. Result of the financial analysis for B. philippinensis at 4x5 m spacing with
periodic harvests at 10% discount rate in 1989 pesos (P) in Region 11.

 

 

 

 

 

Site Stock Source' NPV(P) BIC IRR(%)
Flat Hilly Grow Buy
x x 36692 1.42 24.0
x x 38150 1.45 25.4
x x 21770 1.24 18.0
x x 22213 1.25 18.3

 

‘See footnotes in Table 12.

84
production cost. Stock source is also important in the establishment of bamboo
plantations. Buying bamboo stock is more desirable than having farmers grow their
own stock. The difference in NPV is P1,609. Although success in raising planting
stocks for B. philippinensis is much higher than for other species (pers. comm., Caasi),

wchniques have not yet been simplified for mass adoption.

Dendrocalarnus asper

Geographic distribution of this species is very limited. Although the culm
possesses a remarkable quality suitable for various uses, its productive capacity is not
comparable to the other endemic species. The market price is also much lower than B.
blumeana because preference for this species has not yet developed.

Though all six management schemes passed the NPV criterion in both Regions
7 and 11, the NPVs are relatively lower than those of B. blumeana (Table 14). Price
differentials between regions have profound effects to NPV as well. While in Region 7
the highest NPV is P29,615, only P23,299 is possible in Region 11. Ceteris paribus,
one possibility of improving the financial feasibility of this species in Region 11 is in
the improvement of market prices. On the other hand, assuming price stagnates, NPV
may be remedied by inducing higher productivity. Marginal increases in yield may
lead to increased sales.

Spacing is also very critical. While all management schemes have positive
NPVs, thedifference in values is very significant. The highest attainable NPV at 7x7
m spacing in Region 7 is P29,615, whereas increasing the spacing to 10x10 m drops

the NPV to only P6,l32. This is due to the direct correlation of spacing and yield

85

Table 14. Result of the financial analysis for D. asper on relatively flat terrain with
annual harvests at 10% discount rate, in 1989 pesos (P).

 

 

Region Spacing Stock Source‘ First Cut- PNV BIC IRR

 

 

 

(m) (P) (%)
Grow Buy

7 7x7 x Year 7 26066 1.38 16.5
11 7x7 x Year 7 19749 1.29 15.2
7 7x7 Year 7 29615 1.46 17.5
11 7x7 Year 7 23299 1.36 16.1
7 7x7 x Year 8 20018 1.31 14.7
11 7x7 x Year 8 14380 1.22 13.5
7 7x7 Year 8 20991 1.33 15.0
11 7x7 Year 8 15353 1.24 13.8
7 10x10 x Year 7 5143 1.13 12.2
11 10x10 x Year 7 2108 1.05 10.9
7 10x10 Year 7 6132 1.16 12.7
11 10x10 Year 7 3097 1.08 11.4

 

'See footnotes in Table 12.

86

The earlier the first harvest is realized the higher the NPV. When harvest
commences at year 7 with cutting of culms 3-years old and older, the highest NPV
possible is P29,615 in Region 7. Delaying the first harvest by a year and cutting culms
4-year old and older, drops the NPV to P20,991. The 29% loss in NPV is large
considering the financial status of the farmers.

The difference in NPV attributed to source of planting stock is not as high as
those from other factors. Buying planting stocks has an NPV of P29,615 compared to
only P26,066 to those that grow their own. Whenever nmseries are available in the
locality, farmers should be advised to buy planting stock. The difference of P3,549 is a

considerable amount to poor farmers.

Dendrocalarnus merrillianus

Data available and basic assumptions used in the analysis indicated that only
four of the six management schemes pass the NPV criterion. The lower yield of this
species relative to the others and the lower price it commands in the market are the
two principal causes for these results. Increases in price may be difficult to achieve
because of inherent characteristics of the species—it is shorter and often crooked with
shorter intemode intervals and an almost solid base. However, productivity could be
enhanced through application of fertilizers and proper maintenance of the clumps.
Increases in yield, however, should be evaluated to determine the marginal gain from
the additioiral inputs. Generally, this species has not yet found its way into industrial
markets, hence, the lower price. According to this study’s sm'vey results, this species

is marketed only to other users in the locality or to other farmers.

87

Average buying price is the same in two regions where this species is being
cultivawd Only management schemes with 7x7 m spacing pass the NPV criterion
(Table 15). All others failed to pass the test. In comparison to other species, the
highest attainable NPV for this species is P12,667; this is considerably below those of
the three other species discussed above.

Improvement in N PVs is attainable in cases where discount rate is lower than
10% (Table 15). This means that if a slightly lower real discount rate was used, the

other schemes would have passed the NPV criterion.

Schizostachyum lumampao

Like B. blumeana, this species is highly demanded in all 3 regions covered by
the study. Since the market price on the average is the same in all 3 regions, only one
set of management schemes was analyzed Results can be directly applied to any of
the three regions of the country.

All four management schemes gained positive NPVs (Table 16). Values of the
NPVs, however, vary widely depending on harvest schedule, cutting age of the culm
and source of planting stock.

When first harvest is in the fifth year and culms 1-year old and older are
harvested, the highest attainable NPV is P7 ,677. This scheme assumes that subsequent
harvests are conducted annually. On the other hand, if the first harvest is delayed by a
year, and the demand is for culms 2-years old and older, the NPV drops to P1,402.
The loss of 81% in NPV is very significant. This indicates that if material preference

is 2—year old, the farmers will incur a huge reduction in profit if they intend to

88

Table 15. Result of the financial analysis for D. merrillianus on relatively flat terrain
with annual harvests at 10% discount rate in 1989 pesos (P) in Regions 6

 

 

 

and 7.
Spacing Stock Source' First Cut PNV (P) B IRR (%)
(m) Grow Buy
7x7 x Year 7 11381 1.18 13.3
7x7 x Year 7 12667 1.20 13.8
7x7 x Year 8 3100 1.05 10.9
7x7 x Year 8 6143 1.10 11.8
10x10 x Year 7 (1522) 0.95 9.2
10x10 x Year 7 (1320) 0.96 9.3

 

= —'
4

‘See footnotes in Table 12.

Table 16. Result of the financial analysis for S. lumampao at 4x5 m spacing on
relatively hilly terrain with annual harvests at 10% discount rate in
1989 pesos (P) in Regions 6, 7, and 11.

 

 

 

Stock Source' First Cut NPV (P) B/C IRR (%)
Grow Buy
x Year 5 6802 1.12 12.8
x Year 5 7677 1.14 13.3
x Year 6 523 1.01 10.2
x Year 6 1402 1.03 10.5

 

‘See footnotes in Table 12.

 

89
continue supplying the market. Improved marketing may be nwded A good
understanding of the characteristics of this species relative to its physical, mechanical
and chemical properties is important. This may help in marketing the species.
As with other species, buying stock ready for outplanting is an advantage. The
NPV is higher by P875 if farmers choose to buy stocks from legitimate producers
rather than to grow their own stocks. However, in areas where no nurseries are

producing bamboo stock, farmers have to grow them.

4.5. Sensitivity Analysis

Gittinger (1982) defines sensitivity analysis as an analytical technique used to
systematically test potential earning capacity of a project if actual events differ from
the initial estimation made in the pro-planning evaluation. It evaluates the change that
results fi'om changing some key variables, though the result may or may not warrant
change in the decision. If carefully applied, sensitivity analysis can overcome some of
the weaknesses of using a deterministic approach (Duvigneau and Prasad, 1984)
because it provides flexibility of the utilization of the results. Its main objective is to
modify assumptions on key variables (e.g., costs, yields, prices, etc.) thereby testing
project viability as affected by different scenarios. It allows objective judgement on
the riskiness of the project under alternative assumptions. From the analyst’s point of
view, a fairly accurate assessment of the strengths and weaknesses of an investment
can be determined It is also valuable in projecting impacts of changing factors over
time.

Forestry investments are subject to some uncertain events as enumerawd by

90
Price (1989), namely: (1) drought, floods and attacks by insects; (2) new technological
advances; (3) human factors, such as illegal felling and arson; (4) changing markets
for products and inputs; and (5) political factors.

Bamboo production is not an exception. As such, probable outcomes from
variations of some assumptions previously made are evaluated Selected scenarios are
based on changing costs and prices by 10%. Results are based on the effects on NPV
of the different schemes. The sensitivity analyses focus only on those schemes that had

the highest NPVs for each species and region.

Different Scenarios

Results of sensitivity analyses of management schemes that gained the highest
NPV for each species in every region are presenmd in Table 17. Percentage changes in
NPV are presented for comparison to the percentage changes in costs and prices.
Complete results for all schemes are available from the author.

Results show that in Region 7, all schemes for B. blurneana posted positive
NPVs. For the scheme with the highest NPV, the value went down from P57,827 to
P50,996; thus, a 10% increase in cost (Scenario 1 or 81) led to a loss of 12% in NPV.
For D. asper, two schemes failed to pass the NPV criterion; that is, the NPVs turned
negative. The scheme yielding the highest NPV declined by 22%, down from P29,615
to P23,111. Of the six schemes evaluated for D. merrillianus, only three schemes
passed the .NPV test. The NPVs of other schemes turned negative. Reduction in NPV
for the scheme with the highest NPV was 49%, down from P12,667 to P6,485. For S.

lumampao, only two of the four schemes had positive N PVs regardless of region. The

91

Table 17. Results of sensitivity analyses for management schemes that gained highest
positive NPVs for each species in 3 regions at 10% discount rate in 1989

 

 

 

 

 

pesos (P).
Region Species L Original Percent NPV Loss
NPV (P) by Scenario‘
SI 82 S3
7 B. blumeana 57827 12% 22% 34%
D. asper 29615 22% 32% 54%
D. merrillianus 12667 49% 59% *
S. lumampao 7677 40% 53% *
6 B. blumeana 38344 18% 28% 46%
D. merrillianus 12667 49% 59% "‘
S. lumampao ” 7677 40% 53% *
11 B. philippinensis 44623 20% 30% 50%
B. blumeana 38344 18% 28% 46%

 

'Sl= Scenario 1. Production cost increased by 10%. ‘
82: Scenario 2. Price reduced by 10%.
SB= Scenario 3. Combination of Scenarios 1 & 2.
* = NPV ttn'ns negative.

92
NPV loss, however, was high at 40%, a drop from P7,677 to only P4,589.

While all schemes for B. blumeana had positive NPVs in Region 6, the loss
was greater in comparison to Region 7. The NPV dropped from P38,344 to P31,514 or
a net loss of about 18%. For D. merrillianus and S. lumampao, the results are the
same as in Region 7.

Results for B. blumeana in Region 11 are the same as in Region 6. ForD.
asper only three of the six schemes posted positive NPVs. The loss was much greater
than in Region 7 at 28%, down from P23,299 to P16,795. All 8 schemes for B.
philippinensis still retained positive NPVs. The loss, however, was 20%, down from
P44,623 to P35,806. Like B. blumeana, the farmers still retained considerable income.
Results for S. lumampao are the same in Regions 6 and 7.

Price decline is seen to happen in some areas where non-industrial users are
prevalent. How farmers decision will be influenced in the event that market prices are
reduced by 10% (Scenario 2 or 82) was also evaluated

The effect on NPVs from reduction in price is greater than the effects of
increased production costs. In Region 7, the loss for B. blumeana was 22%, down
fi'om P57,827 to P45,214. For D. asper the loss was 32%, down from P29,615 to
P20,150. Reduction for D. merrillianus was 59%, down from P12,667 to P5,218 with
four of six schemes turning negative NPVs. The loss to S. lumampao was 53%, down
from P7 .677 to only P3,595. However, two schemes failed to gain positive NPVs.

In Region 6 the loss of NPV for B. blumeana is higher at 28%, down from

P38,344 to P27,679. For D. merrillianus and SJumampao, the results are the same as

in Region 7.

93

The results obtained in Region 6 for B. blumeana are the same as in Region
11. For D. asper the loss was 38%, down from P23,299 to P14,465. The loss to B.
philippinensis was 30%. NPV drops from P44,623 to P31,343. For S. lumampao the
results are the same as in Regions 6 and 7.

The combined effects of Scenarios 1 and 2 are additive (Scenario 3 or 83).
Bamboo species whose combined loss to increase in cost and decrease in price is less
than 100%, still attained positive NPVs (Table 17). This is true for B. blumeana, in all
3 regions; for B. philippinensis in Region 11; and for D. asper in Regions 7 and 11.
The other two species (i.e. , D. merrillianus and S. Ironampao), however, failed to pass

the NPV test.

4.6. Regional Summary of Cash Flows "

Management schemes that gave the highest NPV for each species in every
region were chosen and graphed to discern how particular species perform relative to
the others based on annual discounted cash flow of net benefits. Other schemes, of

course, would yield different cash flows.

Region 7 - Central Visayas
Of the four species planted in Region 7, S. lumampao exhibited the earliest
positive cash flow commencing in year 5 while the other 3 species did not gain
positive cash flows till year 7. The timing of positive cash flows is governed by the
assumption on first harvest in combination with the harvest age of the culms. The

relationships of cash flows for four species is depicted in Figure 2. The earlier harvest

 

 

 

 

20000«
1
J
150004
J
A 10000:
0_ .
v i
g .
O scoot
..J
“F l
I 1
(Q o
O l
O .
LIJ .
E -5000«
3 .
o .
O 1
m 4
5 -10000«
e—e S. Iumompoo
45000, a—a D. merrillianus
‘ El—EJ D. osper
. 9—9 B. blumeono
“20000 1 5' '1‘o""1'5"fi12'o"j'2'5
YEAR

Figure 2. Discounted Cash Flow of Net Benefits of 4 Bamboo Species in Region 7.

95
for S. lumampao is an advantage over the other species from the vantage of the small
farmers who are in dire need for cash at the earliest time possible.

B. blumeana posted the highest positive discounted net cash flow. Though
positive cash flow may not occur until year 7, the benefits derived thereafter are
consistently higher throughout the analysis period High demand for this species as
reflected in its higher market price conuibutes to this result.

D. asper had higher discounted cash flows than D. merrillianus and S.
lumampao, but consistently lower than B. blumeana. D. merrillianus, on the other

hand, was superior to S. lumampao but not comparable to the other two species.

Region 6 - Western Visayas
Comparison of the three species planted in Region 6 is shown in Figtne 3. The
behavior of the discounted cash flows of net benefits is similar to Region 7, though
actual values for B. blumeana and D. merrillianus are slightly lower. The difference is
solely attributed to lower buying prices in Region 6. Despite the lower prices, the
NPVs for B. blumeana and D. merrillianus are still higher than that of S. lumampao.

Species preference, therefore, still favors B. blumeana.

Region 11 - Northeastern Mindanao
Of the four species evaluated in Region 11, B. blumeana and B. philippinensis
have the highest NPVs (Figure 4). The advantage of B. philippinensis over B.
blumeana is its earlier harvest which commences in year 4. For subsistence farmers, it

is important to gain earlier returns because of the need to raise cash. This is further

 

 

 

 

15000-1
J
lOOOOj
A 1
0- 5000«
V i
g 4
O 1
_J t
“I' o
3: .
m J
<( .
o .
Q -SOOO-I
DJ .
'—
Z 1
D
8 .
(fl ~10000“
C3 .
-tsooo~ A—A D. merrillianus
‘ <>—<> S. lumompoo
. 9—9 B. blumeono
"20°00 ' "s t'o'fl't's'fij'z'ofl'Tz‘s
YEAR

Figm'e 3. Discounted Cash Flow of Net Benefits of 3 Bamboo Species in Region 6.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

25000n
20000;
l
1
15000:
A 1
a. 4
100003
B l
O 4
_J .
U— i
| scoot
I 4
(f) 1
< .
o o‘
o .
LLJ .
l.—
g .
O #5000?
O l
<_/_> .
Q 1
400001
H S. lumompoo
. v—v B. hili inensi:
-150004 p pp
. G—El D. osper
l
. 0—9 B. blumeono
-2ocoo .. - 11,- . - . , . , - - . s - . - . . , - - -.fi
0 5 to 15 20 25
YEAR

Figure 4. Discounted Cash Flow of Net Benefits of 4 Bamboo Species in Region 11.

98
exemplified by a very high initial harvest of B. philippinensis.

D. asper is closely behind the other two species. With the favorable weather in
Region 11, this species may be grown with the other two provided market prices
improve. Net present values for S. lumampao are consistently lower than those of
other species but always positive. This indicates that planting of this species is still

profitable provided all assumptions in the analysis are met.

4.7. Plantation Development Scheduling for Each Management Scheme

Individual LP models were generated by matching individual household types
(HT) with the different management schemes (MS) for appropriate bamboo species in
three regions of the country. This analysis provides insight regarding the development
schedule that is most efficient for individual species given individual management
constraints. Management schemes are described in Chapter 3 and in Appendix H.
NPVs of the different management schemes as afl‘ected by year when planting starts
by region are presented in Appendix 1. Complete results indicating the NPV, the
number of hectares developed by year and the total labor used (PLO) in Region 7 are
presented in Appendix I. Results for Region 11 are shown in Appendix K, and results
for Region 6 are presented in Appendix L.

The FLC was found to be binding and clearly influences timing of plantation
development. As amount of labor conuibution increases, borrowing can also increase
(loan amount is up to 3 times the family labor in peso equivalents) allowing farmers to
be in a better position for developing more area in the first few years of the project.

The capacity of the farmers to develop larger areas in the earlier years substantially

contributes to higher NPVs.

The models developed satisfactorily met the constraints imposed on the
problem. Solutions indicate that in the earlier years, all available resom'ces except land
are used up to allow development of more plantations. As imposed on the model,
plantation development is sequential whereby resomces are allocated in such a way
that in the succeeding years provision for maintenance of those previously established
plantations are jointly determined with the extent of additional hectares to be
established in the same year. The provision of constraints throughout the entire
dtuation of the Leasehold Contract further ensures that as soon as harvests start, the
project is assured to be self-supporting. This is vital considering that borrowed funds
must be repaid in a specified period of time.

A vivid illustration on how B. blumeana plantation development proceeds,
given the limitations imposed on FLC, is presented below. Three household types
(HT) in Region 7 were chosen to represent the range of family labor available: the
least (HT3), the average (HTl) and the most (HT6). Management Scheme 1 (M81)
was matched with these three HTs, and LP models were generated MSl assumes an
initial harvest at year 7 so that borrowing is allowable up to year 6.

For HT3 which can only provide 88 person-days or a peso equivalent of
P6,675 per annum, the family is allowed to borrow to as much as P20,025 per year (3
x P6,675). As such, HT3 accumulate an annual capital of P26,700. To maximize NPV,
the model indicated that the farmer has to fully utilize his labor, as well as, the
borrowing for the full 5 years as shown in Table 18. In the sixth year, however, the

borrowing drops to only P12,616 as most activities are confined to maintenance and

100

Table 18. B. blumeana plantations deve10ped, funds borrowed and total NPV by
household type (HT) in Region 7 at 10% discount rate in 1989 pesos.

—-

 

 

 

 

 

 

 

 

E Year Funds Bdrrowed Area Developed NPV
(Pesos) (ha) - (Pesos)
3 1 20,025 1.50
2 20,025 0.94
3 20,025 0.71
4 20,025 0.59
5 20,025 0.50
6 12,616 -
Total 112,741 4.24 211,803
1 1 27,900 2.10
2 27,900 1.31
3 27,900 " 0.98
4 24,231 0.61
5 14,075 -
6 12,819 -
Total 134,915 5.00 259,037
6 1 56,925 4.56
2 22,314 0.44
3 8,313 -
4 3,770 -
5 1,250 -
6 925 -
Total 93,497 5.00 280,387

 

 

101
protection services only. Under "Area Developed", the schedule indicated that fewer
hectares are developed each year. Since part of the constraint is to confine
development in the first 5 years, this HT was not able to develop the total 5 hectares.
A surplus of 0.76 ha remained unplanted To develop the 4.24 ha. HT3 needs a total
loan of P112,741. The total NPV is calculated at P211,803.

For HT 1 which can provide a total of 124 person-days or a peso equivalent of
P9,300 per annum, the family can accumulate a total of P37200 annual capital
including the allowable borrowings. With this amount, the farmer is better off
developing more area than with HT3. The LP model indicated that the NPV increases
to P259,037. The borrowings followed the same pattern as in HT3 but the decline
occurs earlier. For this HT, the borrowing” decreased beginning in year 4 and continued
to decline until the first harvest occurs. The five hectares were fully developed Total
borrowing was P134,915.

Household type 6 (HT6) which can contribute the most number of person-days
at 253, or a peso equivalent of P18,975, could raise up family’s annual capital to
P75,900. With this amount, HT6 can develop 4.56 ha in the first year and the balance
of0.44hainthe secondyear.Interrnsofloan,I-I'I‘6madefulluseofitinthefirst
year only. Beginning in year 2, borrowing abruptly drops and continues to decline
until year 6. To develop the 5-ha lot, HT6 borrows a total of P93,497. Household’s
capability to develop more area in the earlier years allows a higher NPV of P280,3 87.

The direct correlation of the family labor contribution to the NPV is further
explained by the dependency of the borrowings on the family labor resource. The

provision that borrowing should not be more than three times the family labor

102

contribution in peso equivalent compounded the limitation on family’s capability to
develop more area. For instance, where family labor is more limited, the 5 hectare
limit is not fully developed. Where family labor is relatively abundant, the family is
constrained only by the timing of when planting starts. The timing is very important
because of its implications to NPV. As plantation establishment is delayed, the NPV
declines. As more areas are developed in earlier years, higher NPVs are expected

Three of the species follow similar harvest schedules as B. blumeana. Having a
rotation of five years and longer, B. philippinensis exhibited a different development
schedule for farmers with less labor. The possibility of an earlier harvest occmring in
the 4th year after planting allows small farmers to develop additional areas even
though borrowing has aheady ceased Since the LP model is formulated with
constraints on the entire planning period the proceeds for the earlier harvests can be
saved and used for planting additional areas in years 4 and 5. As it tinned out,
development in year 4 is even higher than in year 1 or from previous years because
farmers are in a better position fi'om earlier returns. Without the possibility of deriving

benefits in year 4, more areas will remain undeveloped for farmers with less labor.

4.8. Cash Flows of Discounted Net Benefits

Farmers that could provide the required inputs without borrowing funds have a
different cash flow schedule than those that provide a family labor as equity for
borrowingOCI‘able 19). In the former case, the cash flow considers all actual costs
occurring in the same year. Discounting takes effect as soon as the money is spent. In

the case of the latter, the repayment of borrowed funds are not directly reflected in the

103

Table 19. Gross returns, development cost and cash flow schedule for two types of
farmers (with & without borrowing) in 1989 pesos (P).

 

 

 

 

‘Year (hxms
iRennns
Chet (inddknw (Run Chshflknv
1 0 37200 -37200 9300 -9300
2 0 37200 ~37200 9300 -9300
3 0 37200 -37200 9300 -9300
4 0 33531 -33531 9300 -9300
5 0 23375 -23375 9300 -9300
6 0 21119 -21119 9300 -9300
7 76771 34298 42473 66439 10332
8 102033 35916 66117 68057 33976
9 115300 35996 79304 68137 47163
10 138456 38913 99543 71054 67402
11 128672 39689 88983 71830 56842
12 129809 39005 90804 71146 58663
13 128525 37804 90721 69945 58580
14 125167 35783 89384 67924 57243
15 128064 34884 93180 67025 61039
16 127644 34735 92909 66876 60768
17 128152 34940 93212 34940 93212
18 128244 35139 93105 35139 93105
19 127680 35125 92555 35125 92555
20 127680 35125 92555 35125 92555
21 127680 35125 92555 35125 92555
22 127680 35125 92555 35125 92555
23 127680 35125 92555 35125 92555
24 127680 35125 92555 35125 92555
25 127680 35125 92555 35125 92555

 

104
year bon'owed funds are spent but rather they are brought forward (compounded)
including the interest to some later years when harvest is realized This means that
farmers have to shoulder the cost of borrowing (time value of money), which is
assumedtobea10%rateinrealterms(seeAppendixG).Whatappearascostsinthe
earlier years are family labor contribution only. The borrowed funds only enter as
costs when repayment commences. The assumption for repayment to be made in 10
equal annual installments, however, allows farmers to have some considerable latitude
in repayment. This indicates that it takes a longer time for farmers without funds to
enjoy higher cash flows than for those who can provide their own capital (Table 19).
The cash flow schedules are difl'erent for farmers who do not borrow and those who
do. As borrowed funds are paid in full, chsh flows for both types of farmers are equal.
The remaining analyses are based on the use of borrowed funds; this is consistent with

economic reality in the rural Philippines.

4.9. Optimal Development Schedule by Species-Maximizing NPV

As previously described (see Appendix H), there are several ways to manage a
particular bamboo species in a plantation. Management schemes (MS) vary according
to source of planting stock, spacing, harvest schedule and harvest age. To choose the
optimal development schedule and scheme from among the schemes for a particular
species, LP models were created by allowing choice among alternative MS for a given
species by region and household type. The same types of constraints were entered and
tested for all 6 household types in each region. The following discussion is organized

by species and region for maximizing NPV (Table 20).

105

Table 20. Ranges of NPVs based on optimal development schedule for
each species by region at 10% discount rate in 1989 pesos.‘

 

 

 

 

 

Region Species Management Ranges of NPV
Scheme” (Pesos)
7 B. blumeana M82 222,936-286,832
D. asper M818 105,879-145,216
D. merrillianus M824 47 ,007-65 ,592
S. lumampao M830 38,371-49,035
11 B. blumeana M82 151,987-191,611
B. philippinensis M810 187,550-222,050
D. asper M818 89,117-115,378
S. lumampao M830 . 41,085-49,569
6 B. blumeana M82. 120,323-186,693
D. merrillianus M824 40,141-6l,402
S. lumampao M830 23,042-37,150
'Maximizing NPV

I’These are optimal schemes for each species in each region for all household
types. The management schemes are fully described in Appendix H.

Net present value, area planted by year and total labor used are presented in
Appendices J, K and L.

106

The optimal schedule and scheme for B. blumeana is M82 in all 3 regions for
all 6 household types (see Appendices J, K and L). The NPV ranges fi'om P120,323-
P286,832 depending on household type and region. The use of NPV as the only
measme to determine the optimal scheme indicated that M82 is preferable over the
other seven schemes cmrently employed by farmers. The amount of labor contribution
did not in any way affect the choice. To optimally manage B. blumeana, a farmer has
to (1) purchase planting stock from legitimate producers to minimize costs and
mortality, (2) use 7x7 m spacing, (3) start harvesting at year 7 with subsequent annual
harvests, and (4) begin with a cutting age of 3 years old and older. In case harvesting
is delayed by a year or 4—year old culms are demanded this scheme is still a better
choice over the others assuming that corresponding adjustments are also made in the
other schemes. If no producers for planting stock (i.e., nluseries) are available locally,
farmers have the next best alternative scheme as an option. Management Scheme 1
(MS 1), which assumes that farmers have to produce their own planting materials
comes out to be the next best choice in comparison to the other schemes. The NPV,
however, is slightly lower (between 4% to 6% lower than M82) depending on
household type and region. Since the optimal model was selected from individual
models previously generated, the comparison can be directly inferred from Appendices
J, K, and L.

For B. phillipinensis, which is planted only in Region 11, the optimal solution
for all household types is M810. This scheme produces the highest NPV from among

the 8 schemes for this species. The NPV ranges from P187,570-P222,051 depending

107
on household type. As prescribed in this scheme, the farmer has to (1) purchase
planting material from legitimate producers, (2) use a 4x5 m spacing, (3) start
harvesting in year 4 with subsequent annual harvests, and (4) begin with a cutting age
of 1 year old and older. Even if the first harvest is delayed, this scheme is still far
better than the other schemes, provided corresponding adjustment is applied to the
other schemes. The next best alternative scheme for this species is M89. This is
appropriate in case planting stock ready for outplanting is not available in the area.
This scheme assumes that the farmer has to produce the planting stock. Switching to
the next best scheme reduces NPV by about 45% depending on household type. Since
two distinct sites (relatively flat and hilly terrain) were analyzed for this particular
species, site specific schemes must be determined so that NPV implications can be
evaluated On relatively hilly sites, the optimal scheme is M814. Though NPVs are
relatively high, they are approximately 30% lower than those calculated for flat sites
using M810. Complete results are presented in Appendix K.

D. asper is planted in Regions 7 and 11. Considering the six schemes of this
species, the optimal solution for all household types is M818 except for HT3 (HT
which has the least labor). HT3, which could not afford to develop the full 5 hectares
using M818, uses slack area to develop a less intensive scheme. In Region 7, for
example, the balance of 0.69 ha using an individual model approach was developed in
combination with M822 when all schemes for D. asper were combined The full
development of 5 ha, 4.31 ha for MS 18 and 0.69 ha for M822, subsequently increases
the NPV from P105,879 to P110,096 or an increase of P4,217. Total labor also

increases from 6132 to 6697 person-days. In Region 11, the development of an

108
additional 0.35 ha increases the NPV fi'om P89,117 to P90,197. The strategy is to
develop 4.65 ha using M818 and 0.35 ha using M822.

Of the six schemes evaluated for D. merrillianus in Regions 7 and 6, only 4
schemes yielded positive NPVs. The other 2 schemes, therefore, were:excluded The
optimal scheme is M824 regardless of household type. M824 is superior from the
NPV perspective, values range from P40,141-P62,592 depending on household type
and region. This scheme prescribes that farmer has to (1) buy planting stock from
legitimate growers, (2) use 7x7 m spacing, and (3) set cutting age at 3 years old and
older with annual harvesting commencing at year 7. In case bamboo nurseries are not
available in the locality, the next best option is M823. This scheme requires that the
farmer has to grow the planting stock. All other treatments are the same as in M824.
If the switch fi'om M824 to M823 is inevitable, the NPV is reduced by as much as 11-
15% depending on the household type: Of course, the household type that suffers the
largest percentage decline is the one that can provide the least labor. However, despite
the reduction, NPV is still high. Complete results are shown in Appendices J and L.

For S. lumampao, the optimal scheme is M830 for all household types in all 3
regions. From the NPV standpoint, this scheme stands out over the other 3 schemes
used in the analysis. Provided there is a demand for culms 1 year old and older, M830
is the best option. In this scheme, it is prescribed that a farmer has to: (1) buy nursery-
grown stock ready for outplanting, (2) use a 4x5 m spacing, (3) conduct the first
harvest at year 5 with subsequent annual harvests, and (4) set the cutting age at 1 year
old and older. In areas where bamboo nurseries are not yet available, farmers have to

grow their planting stock. The next best option in this case is M829. The switch to

109
M829 would reduce the NPV by 9-13% depending on household type and region. The
NPV, however, still remains relatively high. From the farmers’ standpoint, either
scheme is still a worthwhile undertaking. Complete results are shown in Appendices J,

K, and L.

4.10. Optimal Development Schedule by Species-Maximizing Amount of
Employment

As mentioned previously, promotion of bamboo plantations are not driven
solely by an objective of increasing income. Implications for generating employment
are also important. Since managing bamboo plantations is labor-intensive, an
evaluation of how much labor is required. relative to the number of hectares developed
is important. The policy implications are wide-ranging because the results would serve
as the basis for selecting the optimal scheme that would yield maximum employment.
This may, of course, be different from results obtained by maximizing NPV.

The LP problem was reformulated by combining total labor requirements over
the 25-year planning horizon as the objective flmction, but retaining all the constraints
used in maximizing NPV. The analyses were run in similar fashion by allowing choice
among all available schemes for particular species by region. Calculations were made
for each household type since they are determinants of the family labor contribution.
The subsequent discussions, therefore, focus on how decisions for selecting the

optimal schemes are to be canied out for each species in each region by each

household type to satisfy the objective of creating more employment (Table 21).

110

Table 21. Range of labor use (person-days) based on optimal development
schedule for each species by region.‘

 

 

Region Species Management Labor-Use
Scheme” (Person-days)

7 B. blumeana M81 6,446-7,968

D. asper M817 6,160—7,785

D. merrillianus M823 5.5526537

S. lumampao M829 6,086-7,054

11 B. blumeana M81 6,953-7,993
B. philippinensis M89 11,940—12,797

D. asper M817 7,045-7,808

S. lumampao M829 6,674-7,07 5

6 B. blumeana M81 5.5057930

D. men'illianus M823 4,741-6,508

s. lumampao M329 4,777-7,ozr

 

‘Maximizing amount of employment.

l’These are optimal schemes for household types whose FLC is more than 100
mandays (i.e., HT], HT2, HTS, and HT6). HT3 and HT4 have optimal shemes
similar to Maximizing NPV or a combination of 2 schemes. Management
schemes are fidly described in Appendix H.

Net present value, area planted by year and total labor used are presented in
appendices J, K, and L.

111

Region 7 - Central Visayas

To maximize on-farm labor, the optimal scheme to develop B. blumeana
plantations for all household types except one in Region 7 is M81. Depending on
household type, the difi‘erence in labor required is about 153-171 person—days over the
25-year period relative to the next labor-intensive scheme (i.e., M82, which has the
highest NPV). Results fi'om this analysis indicate that choice for either the maximizing
employment or NPV can be narrowed down to two from the eight schemes evaluated
for B. blumeana. Since five out of six household types are capable of developing the
5-ha plot, the increased labor requirement stems from production of their own planting
stock as required in M81. This is the difference between M81 and M82.

The only household type whose solution differs from the others is HT3. This
HT, which has the least labor, has M82 as the optimal strategy. The major reason for
this choice is that more hectares could be developed using M82. About 4.37 ha can be
developed from M82 and only 4.24 ha by using M81. The labor difference is only 46
person-days. The amount of labor incmred in nursery operation is more than
compensated by the labor required for developing and maintaining the additional 0.13
ha plantation. The slack area remains undeveloped (Appendix J).

For D. asper, solutions for all household types except HT3 included M817
only. This scheme requires an additional 226-245 person-days over the 25-year period
relative totthe next labor-intensive scheme, M818. M817 requires farmers to grow
their planting stock, while M818 does nm. The development strategy is the same as

the result obtained when maximizing NPV (Appendix J).

1 12

HT3 yielded an interesting result. To allocate the 6,831 person-days, M817 is
selected and scheduled in the same manner as in maximizing NPV; 6160 person-days
were utilized The balance of 671 person—days were used to develop the remaining
0.82 ha in year 1 with M822. This generates an additional NPV of P5003. By
maximizing labor therefore, in the combined approach, the NPV increases from
P94,748 to P99,751. Though the total NPV is still lower by P6128 from M818, the
amount of labor increase was 699 person-days. This indicates that by combining the
different schemes, the amount of labor use can still increase.

Solutions for D. merrillianus include M823 only for all household types except
HT3. The difference in person-days ranges from 170-192 over the 25-year planning
period relative to the next most labor-intensive scheme, M824. Since these five
household types were able to develop the total 5 ha, the difference can be fully
attributed to the person-days required in nursery operations.

For HT3, the optimal scheme for maximizing labor use is M824. Though this
scheme does not require nursery operation to be handled by farmers, the extent of
areas planted determines the increase in labor use. Though the increase relative to
M823 is only 51 person-days, M824 is also the scheme with highest NPV. Using
either approach (maximizing NPV or labor), therefore, yields the same result. The
strategy for plantation development is presented in Appendix J.

For S. lumampao, the solutions for all household types except HT3 included
M829 only. This scheme requires farmers to produce their own planting stock. The
difference ranges fiom 178-192 person-days depending on household type over the 25-

year period relative to the next most labor—using scheme is solely attributed to the

1 13
activities incurred in raising the planting materials. The development su'ategy is
presented in Appendix J.

For HT3, the optimal scheme is M830. This scheme does not require that
production of planting material be undertaken by the farmer. It allows farmers to
develop more hectares than the next most labor-using scheme. This scheme also has
the highest NPV. Maximizing either labor or NPV for this household type and species

therefore, yields the same result (Appendix J).

Region 11 - Northeastern Mindanao

Optimal solutions for managing B. blumeana for all household types except
HT3 included M81 only. M81, as defined in Appendix G, requires farmers to grow
their planting stocks. The difference in labor use ranging from 147-165 person-days
depending on household type over the 25 -year period relative to the next most labor-
intensive scheme is solely attributed to the additional labor required for nursery
operations. (Appendix J).

Similar to Region 7, the optimal scheme for HT3 is M82. This scheme has the
highest NPV also. The objective of maximizing either labor or NPV for HT3 gives the
same result. The difference of only 50 person-days from M81 indicated that despite
the nursery activities included in MS 1, the additional area of 0.15 ha developed with
M82 more than compensated the labor needed for growing the planting stock. Toml
hectares developed using M81 is only 4.57 ha while with M82, the area increases to
4.72 ha (Appendix K). The labor required to develop, maintain and harvest the

additional 0.15 ha is far more than the labor needed to grow the planting stock.

1 14

B. philippinensis is viewed differently from the other species because then: are
two distinct sites included in the analysis. Though this species is planted in Region 11
only, the clear distinction between the 2 sites is worth examining. To fully appreciate
the result, the schemes are further broken down into two sites: relatively flat terrain,
using MS9-MS 12 and hilly areas, using M813-M816.

Using all the schemes available for relatively flat terrain for all six household
types, M89 turned out to be the best scheme to maximize labor. HTl can generate
11,387 person-days; HT2, 11,507; HT3, 11,147; HT4, 11,267; HTS, 11,615; and HT6,
11,831 person-days. The labor difference relative to M810 ranges from 62-87 person-
days over the 25-year period depending on household type. The difference is solely
attributed to labor required in nursery operations. The next most labor-intensive
scheme is M810 which has the highest NPV also. This means that whenever mowing
of planting materials is not really possible switching to M810 still creates considerable
jobs.

For hilly terrain, the optimal scheme for all household types included M814
only. This scheme does not require farmers to produce their own planting stock.
However, it allows farmers to develop more areas of plantations. The ability to plant
more hectares in the earlier years requires labor more than that needed in the nursery
operations. The amount of labor (person-days) generated by household type are as
follows: HT1, 12,299; HT2, 12,432; HT3, 11,866; HT4, 12,166; HTS, 12,553 and
HT6, 12,797. Results are ptesented in Appendix It

If all the management schemes for B. philippinensis are combined optimal

scheme for all household types except HT3 included M814 only. The development

1 15

strategy is exactly the same as above. The HT3, however, being not capable of
developing 5 ha, combined M810 and M814 and came up with a difl'erent strategy.
The new schedule increases the person-days to 11,940 and all the 5 ha were
deve10ped In MS 14, 1.48 ha was developed in year 1; 1.68 in year 2; 0.56 in year 3;
1.61 in year 4 and 0.48 in year 5. The total person-days was 11,532 and the total NPV
was P125,441. In M810, 0.02 ha was planted in year 1; 0.05 in year 2; 0.01 in year 3;
none in year 4 and 0.11 in year 5. Total person-days was 408 and the NPV generated
was P6,378. The combination of M810 and M814 increases the NPV to P131,819
from Pl28,900 with individual LP approach.

For D. asper, optimal solution for all household types except HT3, include
M817 only. The main difference is on thy. amount of labor required to mow the
planting materials. This scheme can generate labor (person-days) of 7,550 for HTl;
7,626 for HT2; 7,435 for HT4; 7,681 for HTS; and 7,808 for HT6. The next best
option MS 18 which has the highest NPV also. The difference is about 223-243 person-
days over the 25-year period depending on household type (Appendices K).

For HT3, optimal scheme is MS 17 in combination with M822. The strategy for
M817 is exactly the same as the individual LP run. Total labor generated was 6,645
person-days. NPV was P79,771. The slack of 0.49 ha in M817 was developed in year
1 with M822. Total labor generated was 400 person-days. Combined labor increases to
7,045 and the NPV increases to P81279.

The scheme that provides the most labor for S. lumampao is M829 for all
household types except HT3. This scheme requires farmers to mow their planting

materials. Person-days needed to grow the swdlings is the major factor for the

1 16
increase in labor use. To develop M829, the total labor (person-days) required are :
6,880 for H'I‘l; 6,929 for HT2; 6,797 for HT4; 6,978 for HT‘S; and 7,075 for HT6.
Labor requirement for M829 is meater by about 180-191 person-days over the 25-year
period relative to the next most labor-using scheme, M820 (Appendix K).

To maximize labor use, the solution for HT3 included M829 and M831. The
strategy is to develop 1.46 ha in year 1, 1.07 in year 2, 0.93 in year 3, 0.79 in year 4,
and 0.30 in year 5 with M829. Total labor use was 6,108 person-days. With M831,
0.15 ha was planted in year 1; none in year 2; 0.02 in year 3; 0.01 in year 4; and 0.27
in year 5. Total labor generated was 6,674 person-days. As previously described both

M829 and MS31 require farmers to mow their own planting stocks (Appendix K).

Region 6 - Western Visayas

Solutions for household types capable of developing 5 hectares of B. blumeana
included M81 only. These are HT1, HT2, HTS and HT6. This scheme requires farmers
to mow their planting stock. Total employment (person-days) generated are: 7,570 for
HTl; 7,683 for HT2; 7,756 for HTS and 7,930 for HT6. Total labor use is higher by
about 153-169 person-days over the 25-year period relative to the next most labor-
intensive scheme depending on HTs (Appendix L).

Solutions for household types 3 and 4 whose labor contribution is not sufficient
to develop the 5 ha included M82 only. The opportunity of farmers to develop more
area of bamboo plantation with M82 allows use of more labor. The labor requirement
for the additional area is more than that required in putting up the nlusery. This

scheme (M82) has the highest NPV also. Either maximizing NPV or employment, the

1 17
results are the same. To develop M82, HT3 can generate 5,505 person-days. This is 40
person-days more than MS 1. HT4 ,on the other hand can generate 6664 person-days.

To manage D. merrillianus solutions for household types that have labor
capable of developing the 5 ha plot included M823 only. These are HT 1, HT2, HT‘S,
and HT6. Total labor gener for each HT‘ are 6,294, 6,328, 6,383 and 6,508 person-
days respectively. This scheme generates 169- 195 person-days over the 25-year period
relative to the next most labor-intensive scheme depending on HT. M823 requires
farmers to produce their own planting stock (Appendix L).

Optimal scheme for HT3 and HT4 is M824. This scheme has the highest NPV
also. This scheme allows the farmers to develop more hectares of bamboo plantation
over M823. Total labor (person-days) generated are 4,741 for HT3 and 5,739 for HT4.
The results indicate that labor required to plant and manage the additional 0.16 ha for
HT3 and0.20haforI-IT4ismorethanthatneededtomowtheplanting stockLabor
difference is relatively small if viewed over the 25-year period. Additional
employment of only 44 person—days for HT3 and 53 person-days for HT4 may be
insignificant.

Solutions for HT2, HT‘S and HT6 to manage S. lumampao included M829
only. The other HTs (i.e., HT1, HT3 and HT4) require combination of 2-3 schemes to
maximize employment.

The strategy for HT2, HTS and HT6 is to develop the 5 ha plot and labor
generated were: 6,813, 6,874 and 7,021 person-days, respectively. M829 as described
requires farmers to produce their own planting stock. The additional labor needed for

nursery activities made the difference.

118

For HTl to maximize labor, a combination of M829 and M832 is required To
develop M829, a total of 6,444 person-days is generated The strategy is to develop
1.75 ha in year 1; 1.00 ha in year 2; 0.94 in year 3; 0.74 in year 4; and 0.36 in year 5.
The balance of 0.21 ha was developed using M832. About 277 person-days were
generated to develop 0.21 ha. Planting schedule is 0.06 ha in year 1; 0.11 in year 2;
and 0.40 in year 5. The combined labor generated was 6,720 person—days.

For HT3, strtegy is a combination of M830, M831 and M832. Total person-
days generated was 5,489. The schedule with M830 is to plant 0.37 ha in year 1; 0.45
inyear2; and0.52inyear3.Noplantingisdoneinyears4and5. Laborusedwas
1,763 person-days. With M831, 0.16 ha is planted in year 1; 0.27 in year 2; no
plantingwasmadeinyears 3 and4; and0.10inyear5. Totallaborusedwas721
person-days. With M832, planting is 0.81 ha in year 1; 0.06 ha in year 2; 0.16 in year
3; 0.56 in year 4 and 0.57 in year 5. Total labor generamd was 3,005 person-days. The
result was totally different from the previous run where NPV was maximized

Optimal scheme for HT4 is the same with HT3. Combinations M829, M831
and MS32 are required to maximize employment. Labor generated was 1,808 person-
days in M829, 2,422 in M829, and 2,282 person-days for M832. Grand total is 6,511
person—days. For M829, planting schedule is 0.40 ha in year 1; 0.17 ha in year 2; 0.68
in year 3; 0.20 in year 4 and no planting in year 5. For M831, planting schedule is
0.50 ha in year 1; 0.86 ha in year 2; no planting in year 3; 0.39 in year 4; and 0.04 in
year 5. For M832, Planting is 0.68 ha in year 1; no planting in year 2; 0.12 in year 3;
0.03 in year 4; and 1.02 ha in year 5. Total labor generated has risen by 728 person-

days using the combined approach.

CHAPTER 5

SUMMARY AND IMPLICATIONS

Two main objectives are addressed in this study. The first is to determine the
financial viability 0f bamboo plantations in different regions with different bamboo
species and family labor availability. The second objective is to determine the optimal
development schedules for bamboo plantations based on a 5-hectare module. Two
objective functions (goals) are considered: (1) maximizing the net present value of
cash flows, and (2) maximizing the amount of employment.

Major findings from this study are reviewed and discussed in this chapter along
with their implications to other bamboo species, to other regions of the country and to
other participants of the project. Finally, limitations of this research are addressed and

opportunities for fmther research are identified

5.1. Sununary of Findings

Bamboo plantations, in general, are a viable undertaking from a financial
perspective. Of the 32 schemes evaluated involving 5 species, only 2 schemes (M827
and M828) failed to meet the financial analysis criteria. That is, the NPVs were
negative, the B/C ratios were less than unity and the IRR values were below the real
discount rate used (i.e. 10%) in the analyses as shown in Table 15. The outcomes of

119

120
the other 30 schemes, however, were very impressive.

Management schemes vary with species, spacing, cutting age, cutting schedule,
site characteristics and the requirement for farmers to produce their own planting
materials or buy planting stocks ready for outplanting from established nurseries in the
region. Appendix H describes these schemes in detail. Natural characteristics of the
species as described in Appendices A and B are determinants of their final use.

The first phase of the financial analysis, which assumes development of 1
hectare bamboo plantations across regions without regard to family labor availability,
demonstrates the attractiveness of the project. Planting B. blumeana in Region 7 can
generate NPVs ranging from P17,007-P56,823 depending on the management scheme
for the 25-year planning horizon. In Regions 6 and 11, realizable NPVs are from
P8,736—P37,340. For B. philippinensis which is planted only in Region 11, NPVs range
from P21,770-P44,623 depending on the scheme. D. asper can generate NPVs ranging
from P5,143-P29,615 in Region 7, while in Region 11, the NPVs range from P2,108-
P23,299. For D. merrillianus, the positive NPVs range from P3,100-P12,667. NPVs
for S. lumampao which are applicable to 3 regions ranges from P523-P7,677
depending on management scheme.

The main difference of NPVs bemeen regions for a particular species was
primarily attributed to the farm gate prices presented in Table 7. Buying prices vary
considerabhy across regions. Species that meet the requirements of the industries (e.g.,
construction, furnitlne, cottage, fishing, and banana plantations) command higher
prices than those that are traded between local people only. Culm quality is another

factor that differentiates prices. Quality classifications are based on the size of the

121
culm (i.e., length and diameter), straighmess, and culm wall thickness. Even within
species, price differences are common because of these variations.

Spacing is another component that has a meat influence on the financial
outcome of the plantation. Spacings have direct correlation with yield Closer spacings
allow more clumps per hectare and subsequently more culms are produced For B.
blumeana, the loss in NPV of increasing spacing from 7x7 m to 10x10 m ranges from
60-64% depending on regions; for D. asper, the loss in NPV ranges from 80-89%; and
for D. merrillianus, NPVs turn negative if spacings are increased from 7x7 111 to
10x10 m in both Regions 6 and 7.

Harvest schedule (i.e., age of culm, first harvest, annual and periodic) is
another factor that has an influence on the overall performance of the plantation.
Postponing the first harvest by a year for B. blumeana creates losses in NPV ranging
from 20-25% depending on region; for D. asper, NPV loss ranges from 23-27%; for
D. merrillianus, NPV loss is 50%; and for S. lumampao, the loss in NPV is 81% if the
demand is for 2 year old culms rather than for 1 year old culms.

Though only B. philippinensis was subjected to 2 cutting schedules, annual and
periodic, results indicate that annual harvesting is superior to the periodic schedule.
Annual harvesting yields NPV higher by 14.5%. Annual harvest schedules also allow
farmers to earn sufiicient cash flows regularly whereas cash flows from periodic
harvesting fluctuates from year to year. Careful plantation development and
managemeirt could overcome the problem of fluctuations, but farm yields would be
lower.

Recognition of site variability is as important as the other factors that were

122
included in distinguishing management schemes. The effect of site differences not only
affect the cost of development, but the yield as well. As shown in Table 13a, relatively
flat site yields NPVs aproximately 29% higher than those on hilly terrain.

The choice by farmers to mow their planting materials or to buy planting stock
ready for outplanting is included as an option. In some regions of the country,
commercial mowing of planting stock is not yet available. From all species evaluated
buying planting stocks ready for outplanting is preferable to farmers putting their own
nursery if maximizing NPV is the objective function. Although the difference in NPVs
is small ranging from 2-11% depending on the species, the timing of coming up with
suficient number of planting stock for a given year may pose problems for some
farmers. ‘

Bamboo plantations, like other biological undertakings, are subject to some
uncertain events beyond the conuol of farmers. As such, sensitivity analyses were
conducted to test the financial performance of the project in the event that selecmd
factors change (Table 17).

The effect on increasing production costs by 10% to NPV is large. In Region
7, loss in NPV ranges from 12-49% depending on the species. For Region 6, the loss
in NPV ranges from 18-40%; and in Region 11, the loss in NPV ranges from 18-49%.
From an NPV perspective, the project is still profitable even after income taxes of 5%
from moss‘sales are deducted

Loss to NPV from 10% reduction of farm gate prices is considerably higher
than losses from the cost sensitivity analysis. In Region 7, loss in NPV ranges from

22-59% depending on species; in Region 6, NPV loss ranges from 28-59%; and in

123
Region 11, NPV loss ranges from 28-53%. The project is still profitable, though
income loss is meater than in Scenario 1 where production cost is increased by 10%.
Thus, the project performance was found to be more sensitive to depression of farm
gate prices for bamboo products than increase in production cost.

The combined effects of increasing cost and reducing price by 10% are
profound Of the five species evaluated only 3 species yield positive NPVs. For those
species that yield positive NPVs, the losses range from 34-66% depending on region.

Optimizing deve10pment schedules for bamboo plantations based on a 5-ha
module indicated that family labor contributions (FLC) over time were the most
binding constraints; this is true especially in the early years of development. No test
was done to evaluate the capability of hoh sehold types with higher FLCs if area is not
limited Without question, some household types could develop additional area if the
constraint on land were relaxed For household types where FLC is less than 100
person-days (i.e., HT3 in 3 regions and HT4 in Region 6), development of the whole
5-ha is not possible regardless of species. But for HTs where FLC is over 100 person-
days, development of S-ha is attainable; plantation development schedules, however,
vary.

Maximizing NPV of cash flows indicamd that the higher the FLC, the higher is
the NPV. As more family labor is available, corresponding borrowing also increases.
The higher capital accumulated allows more hectares to be developed in the earlier
years. As more hectares are developed in the earlier years, higher NPVs result This is
due to the discounting effect and fewer years with positive cash flows for those

hectares established in- later years.

124

For maximizing NPV, the optimal solution for B. blumeana for all household
types in all 3 regions is M82. NPV ranges from P120,323-P286,832 depending on HT
and region. For B. philippinensis, the optimal scheme is MS 10 for all HTs. The NPVs
range from P187570-P222,051 depending on HT. The scheme that yielded optimal
schedule for D. asper is M818. With this scheme, NPV ranges fi'om P89,1l7-P145,216
depending on HT and region. For D. merrillianus, the optimal scheme is M824. With
this scheme, NPV ranges from P40,141-P62,592 depending on HT and region.
Solution for S. lumampao is M830 for all HTs and regions. With this scheme, NPV
ranges from P23,042-P49,569 depending on HT and region. The wide variability of
NPVs between species can be attributed to the differences in yield and prices fiom
region to region. 1

Maximizing the amount of employment yielded results different from
maximizing NPV. For HTs which are capable of developing the whole 5 ha within the
5-year period the solution is to adopt schemes requiring the farmers themselves to
raise their own planting stocks. The additional person-days required in the nursery
operations generally led to the increase in labor requirement. Another factor that
influences the choice is spacing. As spacings get closer, more person-days are nwded
to prepare the site, plant the area, maintain the plantations and harvest the culms. The
last factor that contributes to higher labor use is site quality. As terrain gets
increasingly difficult to manage, more labor is required to perform similar activities
than on flat terrain.

For farmers whose FLCs are more limited the optimal solution is not

dependent on schemes requiring the farmers to mow their own planting stocks, but on

125
schemes that would allow them to develop more hectares of bamboo plantations. The
solution was typically a combination of 2-3 schemes. By combining the different
schemes, farmers were able to develop the whole S-ha, and this contributed much to
the increase in labor use. Though NPVs declined in most cases, the values are still
positive. In some instances however, the optimal solution for maximizing NPV is the
same as the optimal solution for maximizing amount of employment. Summary of
results for species with highest NPV and highest amount of labor-use for the entire

analysis period (25 years) are presented in Table 22.

5.2. Implications of findings

Promotion of bamboo plantations in the countryside is both appealing fi'om a
political standpoint and financially attractive from a farmer’s perspective. The study
results indicate that despite the very limited input (i.e., family labor), households can
invest in bamboo production, returns are very significant in terms of added income.
The assumption of considering sluplus labor as the sole basis of a family’s
contribution (and equity basis) assures the farmers that their normal livelihood
activities are not jeopardized Involvement in bamboo plantations would be a matter of
putting their slack time to some productive use. A government promam using this
slack time as equity could be very beneficial to farmers who do not have real assets to
serve as collateral.

The high return generated even for part-time bamboo farmers suggests wide
adaptability of the results. This indicates that other participants interested in investing

their resources in bamboo plantations may be feasible. However, land cost must be

126

Table 22. Summary of species having highest NPV, highest labor use, and highest
labor availability by Region at 10% discount rate in 1989 pesos.

   
    

 

Species Region Highest Values

 

 

 

FLC" NPV Labor
(Person-dayS) (PCSOS) (Person-(law)

B. blumeana 7 253 286,832 7,968
218 186,693 7,930

11 276 191,611 7,993

B. philippinensis 11 276 222,051 11,831
D. asper 7 253 145,216 7,785
11 276 115,328 7,808

D. merrillianus 7 ~ 253 62,592 6,537
218 61,402 6,508

S. lumampao 7 253 49,035 7,054
218 37,150 7,021

11 276 49,569 7,075

 

 

‘FLC= highest annual family labor contribution. These are
contributed by household type 6 in all regions.

127
added if it is not a government sponsored promam. Those that can provide the capital
without borrowing are in a better position because they will not be paying for the cost
of money. Those with extensive landholdings have the opportunity to develop more
plantations.

The structural component of allowing farmers access to public lands through
Leasehold Connects has wide-ranging implications. While active involvement of
government and funding agencies is required in the initial years to complement the
limited resources farmers can put up as equity, structm'al arrangements allow farmers
to be self-reliant and to become small enterpreneurs. As time passes, public assistance
promams can be shifted to other deserving clients as bamboo plantations become self-
sustaining. 8

The financial analysis clearly demonstrawd that as soon as first harvest is
realized the plantation can generate income more than sufficient to service the
borrowed funds and cover the other costs as shown by high NPVs of cash flows. This
is due, in part, to the government’s ability to bear the risk of the initial investment by
delaying loan repayment until harvests are realized Inclusion, therefore, of other
bamboo species fiom other regions is not difficult if similar conditions exist. Special
attention should be given to demand-side/market forces because bamboo production is
highly sensitive to changing prices.

The tremendous deficit of bamboo materials in recent years due to conversion
of lands to. other uses and mismanagement of natural stands in some areas can be
aumnented through bamboo plantations. Study results indicate that financial returns are

more than sufficient to meet the production costs. The added income farmers can

128
generate is a strong motivation for them to engage in bamboo mowing. The results
however, should not be viewed as a framework for total farm planning. Bach farmer is
unique that models developed may serve only as a qualified guidelines in making use
of farmer’s excess labor to bamboo management. Indications as to what species and
timing of development farmers may adopt were demonstrated by the study’s results.

The continuous cover bamboo stands can provide is an added advantage from
an environmental perspective. It stabilizes soil and water flow. Besides, bamboos can
also be developed in pure plantations or can be integrated into amoforestry farms.

Revenue from taxes cannot be underestimated The gross sales tax of 5% levied
on all products derived from bamboo plantations can generate a sizeable amount
income to the government. This money could be channeled to support other public
projects related to conservation and management of natural resom'ces.

All respondents signified interest in bamboo plantations. This overwhelming
response is an indication of the attractiveness of the project, but this should not be
interpreted as a pre-condition for acceptability. Unless problems raised by the farmers
on financing, land acquisition, technical assistance, continuity of the project and
product marketing are resolved this project will suffer the same predicament as the
fuelwood production project (Hyman, 1983) or the dendrothermal plantations (Durst,

1989).

5.3. Limitations
Several limitations were encountered in the conduct of this investigation. These

are related principally to limitations on data needed in the analysis.

129
Time and data constraints are notable. For example, standard yield tables for
bamboo species are not available at present. Direct inference of yields gathered from
other regions posed problems of estimation because of climatic variability and edaphic
differences. In addition, plantations where yield data were gathered were established
for plu'poses different from this study. Thus, yield data for various schemes were not
empirically developed using systematic silvicultm'al strategies.

Reliance on nationally set minimum wage is another limitation. Variations
between regions in terms of hiring/exchanging labor may not reflect the actual wages
received by farmers. Other cost information are also limited because most of the data
were gathered from government-administered pilot projects. However, the approach
used provides a consistent framework forganalysis.

Another limitation is the household type classification. The typing based on 30
samples stn'veyed per region may not be a valid representative of the region because
sampling was confined to areas adjacent to the pilot projects for purposes of this
study. Farmers non-response to some important questions pertaining to income,
harvests and landholdings may have masked some important information valuable in
characterizing the households. Typing of households, therefore, as used in this study
should be refined as data on family profiles become available. However, the data
provided a basis for examining the effect of labor availability on optimal management
schemes.

The: optimal schedules developed should not be treated as a farm planning
guide because the analysis was limited to the optimal use of Stu-plus labor only. The

results may be different if bamboo plantations were intemated with the other farm

130
activities of the farmers.

The " sweat equity" (allowing farmers to borrow capital 3 times the FLC
without collateral in terms of real asset) assumption though used for short-term crops
was never tried for long-term projects. This is where political will is put to test on
how sincere the government is in helping the poorest of the poor.

The assumption on the discount rate (i.e., 10%) is also a limitation because this
is the government rate. The riskiness of the project from private point of view may
require higher discount rates and may not be attractive to small farmers. Finally, the
deterministic nature of the models used may not account for the changes that may

happen beyond the control of the farmers or the government.

5.4. Further Research

The pioneering nature of this investigation contributed to its focus. That is,
empirical data were gathered from various regions regarding labor availability, prices,
costs, and yields. The focus on the supply-side does not present a complete picture of
the status of bamboo in the Philippines nor does it deal with site-specific analyses. A
number of research gaps still exist regarding production and consumption of bamboo.

One aspect of major concern is production of planting stocks. Dependence on
vegetative propagation is difficult for large-scale plantations because culm cuttings are
bulky, desu'uctive, and expensive to transport. Further studies on propagating planting
stock through tissue-culture and other methods are important and are of immediate
concern. Until mass propagation is possible through inexpensive means with high

survival rates, open acceptance of bamboo management by farmers can not be assured

131
Related to this is the need to determine the effect of fertilization on commercial-scale
plantations. Information of this natme is valuable for evaluating the marginal gains of
using additional inputs to enhance productivity.

Integration of bambdo production to total farming systems should be studied
Evaluation is important on how farmers allocate family labor to a combination of
subsistence and income generating activities. Research concerning earlier returns on
bamboo management should be explored because it afl’ects decision on the choice of
the species, timing of development and product diversification. Shoot production is
one avenue that is worthwhile pursuing.

To refine the determination of returns, detailed buying prices of raw materials
must be related to the specific end-products for which bamboos are used It has been
observed that differences in prices vary depending on the end-use for which the
material is purchased A complete picture of bamboo production and consumption
status is valuable in determining the total economic impact of the species to the
Philippine economy.

On the supply-side (production), silvicultural studies must be pursued to -
develop refined yield tables that would account not only spacings and harvest schedule
but also edaphic and climatic factors. Site specific yield tables are valuable in
predicting future harvests.

On the demand-side (consumption), the marketing structure should be studied
Marketing schemes for bamboos are not yet developed in a manner comparable to
other foresz products. The role of middlemen should be studied because their

presence may have masked the real potential returns from selling/buying bamboos.

APPENDICES

APPENDIX A

Ranges of Menslu'ational Attributes of Bamboo

133

Table A1. Ranges of mensurational attributes of bamboo species used in the study.

 

 

 

Attribute Species‘
Bb Da Dm 81
Culm Length (m) 11.2-20.0 13629.2 6.1-13.0 6.5-11.0
No. of Nodes 32.0-53.0 33.0-68.0 20.0-58.0 11.0-25.0
Length of
Internodes (cm)
Butt 14.0-35.5 16.6415 10.0-26.0 14.0-55.5
Middle 33.3-46.6 44.0-72.5 16.5-32.0 42.4-76.0
Top 27.0-37.6 24.3-58.0 27.5-35.5 43.2-72.8
Internode
Diameter (cm)
Butt 6.3-10.8 12.1-18.8 4.9-8.2 3.8-7.3
Middle 7,211.3 92315.4 4.47.5 5.47.0
Top 4.3-7 .6 448.7 2.2-5.1 2.7-4.7
Culm Wall
Thickness (cm)
Butt 1.38-3.80 1.79-3.63 1.8-4.50 0.50-1.6
Middle 0.603.17 0.85-1.44 l.3-2.50 0.30-0.9
Top 0.44-0.69 0.56-0.95 1.3-2.50 0.30-0.9

 

‘Bb = Bambusa blumeana
Da = Dendrocalamus asper

Dm = Dendrocalamus merrillianus
81 = Schizostachyum lumampao

Source: Uriarte et al., 1990.

APPENDD( B

Physical and Mechanical Properties of Bamboo

135

Table B1. Physical and mechanical properties of bamboos used in the study.

 

 

 

 

Property Species‘
Bb Da Dm Sl

Moisture Content 82.21 121.03 98.44 123.88
(%)
Relative Density 0.65 0.55 0.59 0.53
Shfinkagc (%)

Thickness 12.45 12.85 11.29 15.44

Width 7.12 8.53 7.77 1.27
Maximum Crushing
Strength (MPa)

Nodal 492.15 411.07 402.18 382.58

Internodal 495.87 ' 421.71 444.91 342.36
Static Bending
Stress at 257.79 170.73 611.64 179.44
proporu‘onal limit (MPa)
Modulus of 335.65 234.22 900.82 202.07
rupture (MPa)
Modulus of 134.32 127.18 87.91 94.34
elasticity (1000 MPa)

 

 

Source: Uriarte et al., 1990.

‘See footnotes of species in Table A1.

APPENDIX C

Classification of Land Area in the Philippines

137

Table C1. Classification of land area in the Philippines from SPOT survey.

#17

 

 

_
_¥ -7

 

Land Cover Area (’000 ha)
Forest 7,226
Pine 81
Mossy/Unproductive 246
Dipterocarp 6,629

Closed 2.435
Open 4,194
Manmove 149
Extensive Cultivation 11,958
Open in Forest 30
Grassland 1,813
Mixed 10,114
Intensive Cultivation 9,729
Plantation 5,336
Coconut 1,133
Other 91
Coconut and Cropland 3,748
Other and Cropland 365
Cropland 4,392
Fishponds 205
Fishponds from Manmove 195
Other Fishponds 10
Other Lands/Lakes 542
Unclassified Area 546
TOTAL 30,205

 

Source: Solna, Sweden, 1988.

APPENDIX D

Survey Questionnaires and Input Data Forms

139
Table D1. Production input data form.

 

Species:
Spacing:
Region :
Type of Input: Labor (person-days) [ ] Cost (P) [ ]

 

 

 

f r

Items Year

Q1 Q2 Q3 Q4 Total

 

 

A. Procurement of
planting materials
1. Planting stock
a. rhizome
b. culms
c. branch
(1. others
2. Labor

a. excavating

 

 

 

 

 

 

 

 

 

b. cutting

 

c. preparation

 

B. Transport to nursery]

 

plantation site
1. Truck hire
2. Man/animal hire
3. Labor
a. loading
b. unloading

c. distribution

 

 

 

 

 

 

 

 

 

 

 

 

Table D1 (continued)

140

 

 

=

Items

Year

 

Q1

Q3

Total

 

C. N msery operation
1. Tools/materials
a. shovel
b. trowel
c. bolo
d. plastic bags
e. net
f. others
2. Labor
a. preparation
b. potting
c. setting up
D. Care & Maintenance
1. Fertilizer
2. Labor
a. watering
b. cleaning
c. fertilizer
E. Transportation to
plantation site
1. Truck hire
2. Man/animal hire
3. Labdr
a. loading

c. distribution

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table D1 (continued)

Items

141

 

Q1

Q3

T0tal

 

F. Plantation
establishment
1. Tools/materials
a. bolo
b. mass cutter
c. shovel
d. pickrnattock
e. hole digger
2. Labor
a. boundary survey
b. brushing
c. staking
d. hole digging
e. planting
G. Maintenance
1. Fertilizer
2. Labor
a. weeding
b. fertilizer
application
c. replanting
d. fireline
construction

e. others

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

142
Table D1 (continued)

 

 

Items Year _

 

Q1 Q2 Q3 Q4 Total

 

H. Harvesting

 

1. Tools

 

a. chainsaw

 

b. bolo

 

c. bow saw

 

2. Labor

 

a. felling

 

b. preparation

 

1. Transportation

 

1. Truck hire

 

2. Man/animal hire

 

3.Labor

 

a. loading

 

b. unloading

 

 

 

 

 

 

c. piling

 

143
Table D2. Yield (harvested) data form.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Species:
Spacing:
Region :
Yield (No. of culms)
Number Year _ Year __
H A L H A
H = high quality

A = average quality
L = low quality

144
Table D3. Buying price questionnaire.

1. Name of Respondent/Title:
2. Name of Firm:
3. Address of Firm:

 

 

 

Q1. Whattypeoffirm are you engaged in? Choosefrombelow:
[]Construction []Cottage []Furnitlue
[]Fishing []Banana []Food
[lPulpandPaper Mothers

Q2. What type of products are you producing? What species?
Product Species

 

 

 

 

 

 

 

 

9:59P?

 

 

Q3. How much do you pay for the raw materials?
Species ~ Price

 

 

 

 

 

 

 

 

.V‘PP’N?‘

 

 

Q4. What is your average consumption per month? Your projected demand?
Species Average/mo. Projected

 

 

 

 

 

 

 

 

 

 

 

 

999939!"

 

 

 

Q5. Where do you get your raw materials?
Species Source/Location/Distance

 

 

 

 

 

 

 

 

S‘PPP!‘

 

 

145
Table D4. Household profile questionnaire.

1. Name of Respondent:
2. Address:

3. Age:

4. Status: [ ] Married [ ] Single [ ] Widow [] Widower

 

 

Q1. Do you have children? [ ] Yes [ ] No

Q2. How many? What are their ages and gender?
Age Gender

 

l.
2.
3

 

Q3. Do you own the farm? [ ] Yes [] No Location:

 

Q4.Areyouworkingas[ ]owner [ ]tenantor[ ]hiredlabor?

Q5 . How many hectares are cultivated?

 

Q6. What type of crops are mowing?
Crops Hectare Yield (unit)
1. rice
2. corn
3. root crops

4. Others

 

 

 

 

 

Q7. How much time do you spend workin g/week?

 

Q8. What percentage of your time is dev0ted to farming your land?

 

 

 

Your time %
Your wife %
Your children %
Q9. What are your other sources of income? 1. __ 2.

Q10. How much are you earning outside farming?

Q11. The government is planning to promote bamboo plantations. Are you interested
to engage in bamboo farming? [ ] Yes [ ] No

Q12. How much time can you devote to bamboo plantation? _

Q13. What problem do you forsee when you decide to go into bamboo plantation?
1. 2. 3.

 

APPENDIX E

Per Hectare Yield Data

147
Table E1. Per hectare yield (number of culms) data for B. blumeana at 7x7 m spacing.

 

 

 

 

Harvest Year High Average Low Total
Quality Quality Quality
1978 918 367 550 1,835
1979 732 305 183 1.220
1980 676 257 153 1,026
1981 844 352 211 1,407
1982 713 297 178 1,188
1983 737 307 184 1,228
1984 700 292 174 1,166
1985 704 294 176 1,174
1986 751 313 188 1.252

 

I E

Source: ERDB, 1989.

Table E2. Per hectare yield (number of culms) data for B. blumeana at 10x10 m

 

 

spacing.
Harvest Year High Average Low Total
Quality Quality Quality
1978 487 175 262 874
1979 348 145 88 581
1980 293 122 74 489
1981 402 168 100 670
1982 340 142 84 566
1983 351 146 88 585
1984 333 139 83 555
1985 " 335 140 84 559

1986 358 149 89 596

=—

 

Source: ERDB, 1989.

148

Table E3. Per hectare yield (number of culms) data for B. philippinensis at 4x4 m

spacing in relatively flat terrain with annual harvesting.

 

 

 

 

 

Harvest Year Normal Oversize Total
Size
1978 14,625 4,875 19,000
1979 4,625 1,542 6,167
1980 4,625 1,542 6,167
1981 4.625 1.541 6,166
1982 4,397 1,459 5,856
1983 4,397 1,459 5,856
1984 4,398 1,460 5,858
1985 4,410 1,470 5,880
1986 4,410 1,470 5,880

 

Source: ERDB, 1989.

Table E4. Per hectare yield (number of culms) data for B. philippinensis in relatively
flat terrain with periodic harvesting (every 3 years).

 

 

Harvest Year Normal Oversize Total
Size
1977 14,625 4,875 19,500
1980 13,875 4,625 18,500
1983 13,192 4,378 17,570
1986 13,230 4,410 17,640
1989 13,432 4,410 17,842

 

Source: Caasi, 1989.

149

Table E5. Per hectare yield (number of culms) data for B. philippinensis in hilly
terrain with annual harvesting.

1 L

 

 

Harvest Year Normal Oversize Total
Size
1978 12,349 3,866 16,215
1979 4,134 1,295 5,429
1980 4,134 1,295 5,429
1981 4,133 1,295 5,428
1982 4,094 1.282 5,376
1983 4,095 1.282 5,377
1984 4,095 1.282 5,377
1985 4,637 1,456 6,093
1986 4,637 1,456 6,093

 

Table E6.. Per hectare yield (number of culms) data for B. philippinensis in hilly

Solmce: ERDB, 1989.

 

 

 

 

terrain with periodic harvesting.
Harvest Year Normal Torsize Total
Size

1977 12,349 3,866 16,215
1980 12,401 3,834 16,235
1983 12,281 3,844 16,125
1986 12,852 4118 16,970
1989 12,845 4,032 16,877

W

Source; Caasi, 1989.

150

Table E7. Per hectare yield (number of culms) data for D. asper at 7x7 m spacing.

 

 

 

 

Harvest Year High Quality Low Quality Total
1978 1,058 705 1,763
1979 711 474 1,185
1980 730 486 1,216
1981 644 429 1,073
1982 610 490 1,000
1983 585 390 975
1984 711 474 1,185
1985 590 392 982
1986 715 478 1,193

 

I

Source: ERDB, 1989.

 

Table E8. Per hectare yield (number of culms) data for D. asper at 10x10 m spacing.

 

Harvest Year High Quality Low Quality Total

 

1978 504 336 840
1979 339 226 565
1980 347 232 579
1981 327 211 538
1982 297 188 485
1983 279 186 465
1984 338 226 664
1985 293 189 482
t 1986 341 227 568

 

 

 

Source: ERDB, 1989.

151

Table E9. Per hectare yield (number of culms) data for D. merrillianus at 7x7 m

 

 

 

Spacing. :

Harvest Year High Quality Low Quality Total
197 8 746 746 1,492
1979 639 426 1,065
1980 560 372 932
1981 582 378 960
1982 700 466 1,166
1983 548 364 912
1984 556 370 926
1985 544 360 904
1986 572 368 940

 

 

Source: ERDB, 1989.

Table E10. Per hectare yield (number of culms) data for D. merrillianus at 10x10 m

 

 

 

spacing.

Harvest Year High Quality Low Quality Total
1978 354 354 708
1979 304 203 507
1980 266 178 444
1981 328 219 547
1982 333 222 555
1983 260 174 434
1984 265 176 441
1985 258 172 430

.‘ 1986 258 172 430

 

}

Source: ERDB, 1989.

152

Table E11. Per hectare yield (number of culms) data for S. lumampao
at 4x5 m spacing in hilly terrain.

-
—_’

 

 

Harvest Year Yield
197 8 5,945
1979 4,460
1980 3.240
1981 3,240
1982 3,870
1983 3,965
1984 3.340
1985 3,390
1986 3.275

 

 

Source: ERDB, 1989.

APPENDD( F

Projected Yield Data

154

Table F1. Projected per hectare yield for B. blumeana at 7x7 m spacing.

 

 

Harvest Year High Average Low Total
Quality Quality Quality
16th 738 310 172 1,220
17th 709 329 186 1,224
18th 722 298 216 1,236
19th 690 323 192 1,205
201h 741 31 1 180 1,232
218t 725 302 181 1,208
22nd 725 302 181 1,208
23rd 725 302 181 1,208
24th 725 302 181 1,208
25th 725 302 g 181 1,208

 

Table F2. Projected per hectare yield for B. blumeana at 10x10 m spacing.

 

Harvest Year High Average Low Total
Quality Quality Quality
16th 351 147 82 580
17th 340 149 83 572
18th 360 122 93 575
19th 354 138 76 568
20th 348 140 88 576
21st 345 144 86 575
22nd 345 144 86 575
23rd : 345 144 86 575
24th 345 144 86 575

25th 345 144 86 575

4-
_-_’

 

155

Table F3. Projected per hectare yield for B. philippinensis at 4x5 or spacing with
annual harvesting in relatively flat terrain.

 

a -
-’

 

Harvest Year Normal Size Oversize Total
13th 4,622 1,346 6,018
14th 4,608 1,420 6,028
15th 4,592 1,400 5,992
16th 4,460 1,481 5,941
17th 4,472 1,468 5,940
18th 4,520 1,455 5,975
19th 4,485 1,468 5,953
20th 4,518 1,482 6,000
21st 4,477 1,470 5,947
22nd 4,477 1,470 5,947
23rd 4,477 1,470 5,947
24th 4,477 1,470 5,947
25th 4,477 1,470 5,947

 

Table F4. Projected per hectare yield for B. philippinensis in relatively flat terrain with

 

 

periodic harvesting (every 3 years).
Harvest Year Normal Size Oversize Total
6th 13,432 4,410 17 .842
7th 13,432 4,410 17 ,842

8th 13,432 4,410 17,842

 

 

156

Table F5. Projected per hectare yield for B. philippinensis at 4x5 m spacing in hilly
terrain with annual harvesting.

 

 

Harvest Year Normal Size Oversize Total
13th 3,617 1,206 4,823
14th 3,282 1,094 4,376
15th 3,282 1,094 4,376
16th 3,282 1,094 4,376
17th 3,282 1,094 4,376
18th 3,282 1,094 4,376
19th 3,281 1,094 4,375
20th 3,282 1,094 4,376
21st 3,282 1,094 4,376
22nd 3,281 1,094 4,375
23rd 3,282 1,094 4,376
24th 3,282 1.094 4,376
25th 3,281 1.094 4,375

 

Table F6. Projected per hectare yield for B. philippinensis in hilly terrain with periodic

 

 

harvesting.

Harvest Year Normal Size Oversize Total
6th 9,845 3,282 13,127
7th 9,845 3.282 13,127
8th 9,845 3,282 13,127

 

157

Table Fl. Projected per hectare yield for D. asper at 7x7 m spacing.

 

 

Harvest Year High Quality Low Quality Total
16th 690 428 1,118
17th 672 421 1,093
18th 649 442 1,091
19th 700 429 1,129
20th 650 440 1,090
21st 652 435 1,087
22nd 652 435 1,087
23rd 652 435 1,087
24th 652 436 1,088
25th 652 . 435 1,087

 

Table F8. Projected per hectare yield for D. asper at 10x10 m spacing.

 

 

Harvest Year High Quality Low Qujaliy Total
16th 318 205 523
17th 320 210 530
18th 296 221 517
19th 332 198 530
20th 300 215 515
21st 311 207 518
22nd 311 207 518
23rd 311 207 518
24th ’ 311 207 518
25th 311 207 518

 

158

Table F9. Projected per hectare yield for D. merrillianus at 7x7 m spacing.

 

 

 

Harvest Year _ High Quality Low Quality Total
16th 582 366 948
17th 602 335 937
18th 596 380 976
19th 590 400 990
20th 584 394 978
2lst 574 370 944
22nd 574 370 944
23rd 574 370 944
24th 574 370 944
25th 574 370 944

 

 

Table F10. Projected per hectare yield for D. merrillianus at 10x10 m spacing.

 

 

 

Harvest Year High Quality Low Quality Total
16th 260 178 438
17th 272 156 428
18th 290 148 438
19th 268 184 452
20th 270 182 454
21st 265 175 440
22nd 265 175 440
23rd 265 175 440
24th : 265 175 440

440

25th 265 175

 

159

Table F11. Projected per hectare yield for S. lumampao at 4x5 m spacing in hilly
terrain.

Harvest Year Yield

 

14th 2,865
15th 2,985
16th 3,135
17th 3,210
18th 3,060
19th 3,155
20th 3,095
21st 3,095
22nd 3,095
23rd 3,095
24th 3,095
25th 3,095

APPENDIX G

Interest Ratestin the Philippines

161

Table G1. Interest rates in the Philippines from 1983-1990.

 

 

 

Source: IMF, 1991.

A

Year Lending Rate Inflation Rate Discount

(%) (%) Rate (%)
1983 19.24 11.19 8.05
1984 28.20 16.09 12.11
1985 28.61 17.11 11.50
1986 17.53 7.90 9.63
1987 13.34 4.26 9.08
1988 15.92 6.98 8.94
1989 19.27 9.63 9.64
1990 24.54 14.65 9.89
Total 166.65 87.81 78.84
Average 20.83 10.98 9.86

 

APPENDIX H

Description of Management Schemes

163

Table H1. Description of the different management schemes which form the basis of
the financial analysis in the study.

 

=_ :1 = =

 

Management Scheme Code Description
Scheme
M81 BbS7FWN 3A B. blumeana, planted at 7x7 m spacing in

relatively flat terrain, farmers mow own
planting stock, cutting age is 3 years old
harvesting starts at year 7 with subsequent
annual harvests.

M82 BbS7NN3A Similar to scheme 1 except procurement of
planting stock. This scheme, farmers has
the option to buy planting stock ready for

outplanting.

M83 BbS7FWN4 Similar to scheme 1 except cutting age is 4
years old and harvest starts at year 8.

M84 BbS7FNN4A Similar to scheme 2 except cutting age is 4
years 61d and harvest starts at year 8.

M85 BbSOFWN3A Similar to scheme 1 except spacing is
changed to 10x10 m.

M86 BbSOFN N 3A Similar to scheme 2 except spacing is
changed to 10x10 m.

M87 BbSOFWN4A Similar to scheme 3 except spacing is
changed to 10x10 m.

M88 BbSOFNN4A Similar to scheme 4 except spacng is
changed to 10x10 m.

M89 BpS4FWN1A B. philippinensis planted at 4x5 or in

relatively flat terrain with farmers raising
own plantting stock. Cutting is 1 year old
first harvest is at year 4 with subsequent
annual harvests.

 

164

Table H1 (continued)

 

 

Management Scheme Code Description
Scheme
M810 BbS4FNN1A Srmrlar' ' to scheme 9 except farmers has the option
to but planting stock ready for outplanting.
M811 Bp84FWNlP Similar to scheme 9 except harvest is periodic.

First harvest is at year 4, subsequent harvests
every 3 years thereafter (year 7, year 10, ...).

M812 BpS4FNN1P Similar to scheme 10 except harvest is periodic.
First harvest is at year 4 with subsequent harvests
every 3 years thereafter.

M813 BpS4HWN1A Similar to scheme 9 except area is hilly (slope
over 18%).

M814 BpS4HNN1A Similar to scheme 10 except area is hilly.

M815 BpS4HWN1P Similar to scheme 11 except area is hilly.

M816 BpS4HNN1P Similar to scheme 12 except area is hilly.

M817 DaS7FWN3A D. asper, planmd at 7x7 m spacing in relatively

flat terrain. The farmer has to raise own planting
stock. Cutting age is 3 years old with subsequent
annual harvests.

M818 DaS7FN N3A Similar to scheme 17 except the farmers has the
option to buy planting stock ready for outplanting.

M819 DaS7FWN4A Similar to scheme 17 except cutting age is 4 years
old and first harvest starts at year 8.

M820 DaS7FNN4A Similar to scheme 18 except cutting age is 4 years
old and first harvest starts in year 8.

M821 DaSOFWN3A Similar to scheme 17 except spacing is 10x10 m.

M822 DaSOFNN3A Similar to scheme 18 except spacing is 10x10 m.

 

 

 

Table H1 (continued)

165

 

 

Management Scheme Code Description
Scheme

M823 DmS7FWN3A D. merrillianus planted at 7x7 m spacing in
relatively flat terrain with farmers raising own
planting stock. Cutting age is 3 years old and
first harvest starts at year 7 with subsequent
annual harvest.

M824 DmS7FNN3A Similar to scheme 23 except farmers has the
option to buy planting stocks ready for
outplanting.

M825 DmS7FWN4A Similar to scheme 23 except cutting age is 4
years old and first harvest starts in year 8.

M826 DmS7NN4A Similar to scheme 24 except cutting age is 4
years old and first harvest starts in year 8.

M827 DmSOWN3A Similar to scheme 23 except spacing is changed
to 10x10m.

M828 DmSONN3A Similar to scheme 24 except spacing is changed
to 10x10m.

M829 SlS4HWN1A S. lumampao planted at 4x5 m spacing in hilly
terrain. The farmers mow own planting materral,’
cutting age is 1 year old first harvest starts in
year 5 with subsequent annual harvest.

M830 81D4HNN1A Similar to scheme 29 except farmers has the
option to buy planting stocks ready for
outplanting.

M831 SlS4HWN2A Similar to scheme 29 except cutting age is 2
years old and first harvest starts in year 6.

M832 SlS4I-INN2A Similar to scheme 30 except cutting age is 2

years old and first harvest starts in year 6.

i
_7

APPENDIX I

NPV of Management Schemes as Affected by Year of Planting

167
Table I1. Per hectare NPV of different management schemes in Region 7 as affected
by year when planting starts at 10% discount rate in 1989 pesos.

 

 

 

 

Scheme No.‘ Year Planting Starts

-Year1 Year2 Year3 Year4 YearS
M81 56,283 51,657 46,961 42,692 38,811
M82 57,827 52,570 47,791 43,446 39,497
M83 45,033 39,386 34,252 29,585 25,342
M84 46,036 40,298 35,081 30,339 26,028
M85 22,555 19,757 17,213 14,900 12,797
M86 22,908 20,078 17,504 15,165 13,038
M87 17,007 14,713 12,627 10,731 9,008
M88 17,358 15,032 12,917 10,995 9,248
M817 27,471 23,984 20,815 17,934 15,314
M818 29,615 25,892 22,507 19,430 16,633
M819 20,018 17,167 14,575 12,219 10,078
M820 20,991 18,052 15,380 12,951 10,743
M821 5,143 4,222 3,384 2,622 1,930
M822 6,132 5,121 4,201 3,365 2,606
M823 11,381 9,630 8,037 6,590 5,274
M824 12,667 10,798 9,100 7,556 6,152
M825 3,008 2,017 1,117 299 (445)
M826 6,143 4,868 3,708 2,654 1,696
M827 (1522) (1680) (1824) (1954) (2073)
M828 (1320) (1497) (1657) (1803) (1935)
M829 9,063 7,837 6,722 5,709 4,788
M830 9,938 8,633 7,446 6,367 5,386
M831 2 3,704 2,693 2,046 1,458 924
M832 4,284 3,492 2,773 2,119 1,524

—
__

‘See Appendix H for description of management schemes.

MS9-16 = not included in Region 7.

 

 

168
Table 12. Per hectare NPV of different management schemes in Region 11 as affecmd
by year when planting starts at 10% discount rate in 1989 pesos.

: =

 

 

 

Scheme No. Year Planting Starts
Year 1 Year 2 Year 3 Year 4 Year 5
M81 37,340 32,730 28,538 24,728 21,264
M82 38,344 33,642 29,368 25,482 21,949
M83 27,658 23,927 20,536 17,453 14,650
M84 28,662 24,840 21,366 18,207 15,336
M85 13,280 11,485 9,854 8,370 7,022
M56 13,633 11,806 10,145 8,635 7263
M57 8,736 7,354 6,098 4,956 3,918
M58 9,087 7,673 6,388 5,220 4,157
M59 43,014 38,365 34,140 30,296 26,805
M510 44,623 39,828 35,469 31,507 27,904
M511 36,692 30,581 28,123 25,889 20,760
M812 38,150 31,907 29,329 26,985 21,756
M513 31,470 27,977 24,801 21,914 19,290
M514 31,829 28,304 25,098 22,184 19,535
M515 21,770 17,249 16,064 14,987 11,083
M516 22,213 17,562 16,431 15,320 11,386
M517 21,621 18,771 16,179 13,823 11,682
M818 23,299 20,254 17,486 14,969 12,682
M519 14,380 12,145 10,114 8,268 6,589
M520 15,353 13,031 10,919 8,999 7,254
M521 2,108 1,512 971 478 30
M522 3,097 2,412 1,788 1,221 706
M829 -‘ 9,063 7,837 6,722 5,709 4,788
M530 9,938 8,633 7,446 6,367 5,386
M531 3,404 2,693 2,046 1,458 924

M832 4,284 3,492 2,773 2,1 19 1,524

 

169

Table 13. Per hectare NPV of different management schemes in Region 6 as affecwd
by year when planting starts at 10% discount rate in 1989 pesos.

 

 

 

Scheme No.‘ Year Planting Starts

Year 1 Year 2 Year 3 Year 4 Year 5
M51 37,340 32,730 28,538 24,728 21,264
M52 38,344 33,642 29,368 25,482 21,949
M53 27,658 23,927 20,536 17,453 14,650
M54 28,662 24,840 21,336 18,207 15,336
M55 13,280 11,485 9,854 8,370 7,022
M56 13,633 11,806 10,145 8,635 7,263
M87 8,736 7,354 6,098 4,956 3,918
M88 9,087 7,673 6,388 5.220 4,157
M523 11,381 9,630 8,037 6.590 5274
M524 12,667 10,798 9,100 7,556 6,152
M525 3,008 2,017 1,117 299 (445)
M526 6,143 4,868 3,708 2,654 1,696
M527 (1522) (1680) (1824) (1954) (2073)
M528 (1320) (1497) (1657) (1803) (1935)
M529 9,063 7,837 6,722 ' 5,709 4,788
M830 9,938 8,633 7,446 6,367 5,386
M831 3,404 2,693 2,046 1,458 924
M532 4,284 3,492 2,773 2,119 1,524

 

‘See Appendix G for description of management schemes.

MS9-22 = not planted in Region 6.

\

APPENDIX J

Schedules of Plantatiorl Development in Region 7

171

Table I 1. Maximum net present value (NPV), hectares planted by year and total labor
used (TLU) in person-days for difl‘erent management schemes (M8) for
household type 1 in Region 7 at 10% discount rate in 1989 pesos.

 

 

 

 

 

MS‘ NPv (P) ‘ _A—rea Planted by Year (ha) TLU
1 2 3 4 5
1 259,037 2.10 1.51 0.98 0.61 - 7,683
2 265,936 2.24 1.34 0.99 0.43 - 7,530
3 197,747 2.10 1.31 0.98 0.61 - 7,508
4 204,859 2.24 1.34 0.99 0.43 - 7.355
5 106,437 2.85 2.02 0.13 - - 4,240
6 108,692 2.94 2.06 - - - 4,122
7 79,840 2.85 2.02 0.13 - - 4,160
8 81,984 2.94 2.06 - - - 4,067
17 119,052 1.96 1.29 0. 1.00 0.75 - 7,490
18 129,994 2.07 1.33 1.02 0.58 - 7,258
19 85,123 1.96 1.29 1.00 0.75 - 7,315
20 90,682 2.07 1.33 1.02 0.58 - 7,133
21 23,171 2.63 1.94 0.43 - - 4,158
22 28,383 2.85 2.04 0.11 - - 4,035
23 48,658 2.08 1.38 1.08 0.46 - 6,328
24 55,653 2.26 1.43 1.10 0.21 - 6,152
25 10,375 2.08 1.38 1.08 0.46 - 6,228
26 25,472 2.26 1.43 1.10 0.21 - 6,052
29 39,720 2.08 1.39 1.23 0.30 - 6,833
30 44.298 2.20 1.42 1.26 0.12 - 6,655
31 \ 13,775 2.08 1.39 1.23 0.30 - 6,803
32 ' 18,149 2.20 1.42 1.26 0.12 - 6,575

 

‘M89-16 = not included in Region 7.
M827 & 28 = not included having negative NPVs.

 

172

Table 12. Maximum net present value (NPV), hectares planted by year and total labor
used (TLU) in person-days for different management schemes (MS) for
household type 2 in Region 7 at 10% discount rate in 1989 pesos.

MS‘ NPV (P) Area Planted by Year (ha) TLU

 

 

 

1 2 3 4 5
1 265,964 2.44 1.52 1.04 - - 7,780
2 272,457 2.60 1.56 0.85 - - 7,619
3 205,320 2.44 1.52 1.04 - - 7,605
4 211,977 2.60 1.56 0.85 - - 7,444
5 108,047 3.31 1.69 - - - 4,259
6 110,042 3.41 1.59 - - - 4,138
7 81,159 3.31 1.69 - - - 4,179
8 83,094 3.41 1.59 - - - 4,083
17 123,792 2.27 1.50 .. 1.16 0.06 - 7,589
18 134,885 2.41 1.54 1.05 - - 7,353-
19 88,998 2.27 1.50 1.16 0.06 - 7,414
20 94,542 2.41 1.54 1.05 - - 7,229
21 23,920 3.05 1.95 - - - 4,186
22 28,949 3.31 1.69 - - - 4,054
23 50,807 2.41 1.60 0.99 - - 6,396
24 57,670 2.62 1.66 0.72 - - 6.210
25 11.590 2.41 1.60 0.99 - - 6.296
26 26,849 2.62 1.66 0.72 - - 6,110
29 41,062 2.42 1.61 0.97 - - 6,899
30 45.572 2.56 1.65 0.79 - - 6,713
31 14,554 2.42 1.61 0.97 - - 6,869
32 18,921 2.56 1.65 0.79 - - 6,633

 

 

 

 

 

‘MS9-16 = not included in Region 7.
M827 & 28 = not included having negative NPVs.

173

Table 13. Maximum net present value (NPV), hectares planted by year and total labor
used (TLU) in person-days for difierent management schemes (M8) for
household type 3 in Region 7 at 10% discount rate in 1989 pesos.

 

 

 

 

 

MS‘ NPV (P) Area Planmd by Year (ha) TLU
1 2 3 4 5
1 211,803 1.50 0.94 0.71 0.59 0.50 6,400
2 222,936 1.60 0.96 0.71 0.59 0.50 6,446
3 159,085 1.50 0.94 0.71 0.59 0.50 6,251
4 168,643 1.60 0.96 0.71 0.59 0.50 6.293
5 99,799 2.05 1.45 1.12 0.38 - 4,155
6 102,050 2.11 1.48 1.13 0.28 - 4.039
7 74,399 2.05 1.45 1.12 0.38 - 4,075
8 76,526 2.11 1.48 1.13 0.28 - 3,984
17 94,748 1.40 0.93 .. 0.72 0.60 0.53 6,160
18 105,879 1.49 0.95 0.73 0.61 0.53 6,132
19 67,244 1.40 0.93 0.72 0.60 0.63 6,014
20 67.288 1.49 0.95 0.73 0.61 0.53 6,025
21 20,920 1.89 1.39 1.08 0.64 - 4,069
22 25,984 2.04 1.47 1.11 0.38 - 3,951
23 39,780 1.49 0.99 0.77 0.63 0.55 5,501
24 47,007 1.62 1.03 0.79 0.64 0.55 5.552
25 7.536 1.49 0.99 0.77 0.63 - 4,813
26 20,508 1.62 1.03 0.79 0.64 0.55 ' 5,460
29 33,197 1.49 0.99 0.88 0.73 0.36 5,988
30 38,371 1.58 1.02 0.91 0.75 0.43 6,086
31 11,213 1.49 0.99 0.88 0.73 0.62 6,267
32 15,395 1.58 1.02 0.91 0.75 0.62 6,233

 

‘MS9-16 = not included in Region 7.
M827 & 28 = not included having negative NPVs.

174

Table J4. Maximum net present value (NPV), hectares planted by year and total labor
used (TLU) in person-days for difi‘erent management schemes (M8) for
household type 4 in Region 7 at 10% discount rate in 1989 pesos.

r

 

 

 

MS‘ NPV (P) Area Planted by Year (ha) TLU
1 2 3 4 5
1 250,820 1.81 1.13 0.85 0.70 0.51 7,562
2 257,880 1.93 1.16 0.86 0.71 0.35 7,415
3 188,765 1.81 1.13 0.85 0.70 0.51 7,387
4 196,065 1.93 1.16 0.86 0.71 0.35 7,240
5 103,644 2.46 1.75 0.79 - - 4,205
6 105,789 2.53 1.78 0.69 - - 4,086
7 77,550 2.46 1.75 0.79 - - 4,125
8 79,599 2.53 1.78 0.69 - - 4,031
17 113,445 1.69 1.12 0.86 0.73 0.60 7,367
18 124,226 1.79 1.15 '8 0.88 0.73 0.45 7,141
19 80,538 1.69 1.12 0.86 0.73 0.60 7,192
20 86,128 1.79 1.15 0.88 0.73 0.45 7,016
21 22,314 2.27 1.68 1.05 - - 4,125
22 27,372 2.46 1.76 0.78 - - 4,000
23 46,075 1.79 1.19 0.93 0.76 0.33 6,243
24 53,063 1.95 1.24 0.95 0.77 0.10 6,073
25 9.060 1.79 1.19 0.93 0.76 - 5,786
26 23,704 1.95 1.24 0.95 0.77 0.10 5,973
29 38,129 1.80 1.20 1.06 0.88 0.06 6,753
30 42,590 1.90 1.23 1.09 0.78 - 6.574
31 12,852 1.80 1.20 1.06 0.88 0.06 6,723
32 17,113 1.90 1.23 1.09 0.78 - 6,494

 

‘MS9-16 = not included in Region 7.
M827 & 28 = not included having negative NPVs.

175

Table 15. Maximum net present value (NPV), hectares planted by year and total labor
use (TLU) in person-days for different management schemes (M8) for
household type 5 in Region 7 at 10% discount rate in 1989 pesos.

 

 

 

MS‘ NPV (P) ' Area Planmd by Year (ha) TLU
1 2 3 4 5
1 269,426 2.71 1.69 0.60 - - 7,827
2 276,180 2.89 1.73 0.38 - - 7,668
3 209,105 2.71 1.69 0.60 - - 7,652
4 216,041 2.89 1.73 0.38 - - 7,493
5 109,076 3.68 1.32 - - - 4,271
6 111,116 3.79 1.21 - - - 4,150
7 82,003 3.68 1.32 - - - 4,191
8 83,976 3,79 1.21 - - - 4,095
17 126,178 2.53 1.67 .. 0.80 - - 7,637
18 137,368 2.68 1.72 0.61 - - 7,399
19 90,950 2.53 1.67 0.80 - - 7,462
20 96,502 2.68 1.72 0.61 - - 7,274
21 24.233 3.39 1.61 - - - 4,197
22 29,319 3.67 1.33 - - - 4.066
23 51,987 2.68 1.78 0.54 - - 6,432
24 59,022 2.91 1.85 0.24 - - 6,249
25 12,257 2.68 1.78 0.54 - - 6,332
26 27,772 2.91 1.85 0.24 - - 6,149
29 41,890 2.69 1.79 0.52 - - 6,939
30 46,499 2.84 1.84 0.32 - - 6,754
31 15,034 2.69 1.79 0.52 - - 6,909
32 19,483 2.84 1.84 0.32 - - 6,674

 

‘MS9-16 = not included in Region 7.
M827 & 28 = not included having negative NPVs.

176

Table J6. Maximum net present value (NPV), hectares planted by year and total labor
used (TLU) in person-days for different management schemes (MS) for
household type 6 in Region 7 at 10% discount rate in 1989 pesos.

Area Planted By Year (ha)

i

 

 

MS‘ NPV (P) TLU
1 2 3 4
1 280,387 4.28 0.72 - - 7,968
2 286,832 4.56 0.44 - - 7.082
3 221,087 4.28 0.72 - - 7,793
4 227,668 4.56 0.44 - - 7,627
5 112,777 5.00 - - - 4,315
6 114,541 5.00 - - - 4,190
7 85,036 5.00 - - - 4,235
8 86,791 5.00 - - - 4,135
17 133,844 3.99 1.01 - - 7,785
18 145,216 4.23 0.77 - - 7,540
19 97,218 3.99 1.01 - - 7,610
20 102,698 4.23 0.77 - - 7,415
21 25,715 5.00 - - - 4,250
22 30,660 5.00 - - - 4,110
23 55,574 4.24 0.76 - - 6,537
24 62,592 4.60 0.40 - - 6,345
25 14,285 4.24 0.76 - - 6,437
26 30,209 4.60 0.40 - - 6,245
29 44,390 4.25 0.75 - - 7,054
30 49,035 4.50 0.50 - - 6,862
31 16,486 4.25 0.75 - - 7,024
32 21,020 4.50 0.50 - - 6,782

 

 

‘MS9-16 = not included in Region 7.

M827 & 28 = not included having negative NPVs.

APPENDIX K

Schedules of Plantation . Development in Region 11

17 8
Table K1. Maximum net present value (NPV), hectares planted by year and total labor
used (TLU) in person-days for difi'erent management schemes (M8) for
household type 1 in Region 11 at 10% discount rate in 1989 pesos.

 

is

 

 

MS NPV (P) Area Planted by Year (ha) TLU
1 2 3 4 5

1 168,253 2.30 1.44 1.08 0.18 - 7,745
2 175,139 2.45 1.47 1.08 - - 7,594
3 123,364 2.30 1.44 1.08 0.18 - 7,570
4 129,831 2.45 1.47 1.08 - - 7,419
5 63,038 3.13 1.87 - - - 4,253
6 64,916 3.22 1.78 - - - 4.131
7 41,090 3.13 1.87 - - - 4,173
8 42,919 3.22 1.78 - - - 4,076
9 190,106 2.14 1.04 0.79 1.03 - 11,387
10 200,085 2.35 1.03 0.79 0.83 - 11,317
11 159,181 2.14 1.04 " 0.79 1.03 - 10,820
12 168,114 2.35 1.03 0.79 0.83 - 10,749
13 138,096 2.08 1.03 0.81 1.09 - 12,160
14 140,018 2.12 1.03 0.81 1.04 - 12,299
15 92,240 2.08 1.03 0.81 1.09 - 11,826
16 94,514 2.12 1.03 0.81 1.04 - 11,727
17 95,467 2.15 1.42 1.10 0.34 - 7,550
18 104,307 2.27 1.46 1.11 0.15 - 7,321
19 61,992 2.15 1.42 1.10 0.34 - 7,375
20 67,469 2.27 1.46 1.11 0.15 - 7,196
21 9,272 2.88 2.10 0.01 - - 4,180
22 14,159 3.12 1.81 0.06 - - 4,046
29 40,648 2.28 1.52 1.20 - - 6,880
30 45,109 2.42 1.56 1.02 - - 6,692
31 14,314 2.28 1.52 1.20 - - 6,875
_3_2 18,640 2.42 1.56 1.02 - - 6,812

 

179
Table K2. Maximum net present value (NPV), hectares planted by year and total labor
used (TLU) in person-days for different management schemes (MS) for
household type 2 in Region 11 at 10% discount rate in 1989 pesos.

 

 

 

 

 

M5 NPV (P) Area Planted by Year (ha) TLU
1 2 3 4

1 172,818 2.64 1.65 0.71 - 7,815
2 179,300 2.81 1.69 0.50 - 7,655
3 127,056 2.64 1.65 0.71 - 7,640
4 133,214 2.81 1.69 0.50 - 7,480
5 63,863 3.59 1.41 - - 4.268
6 65,782 3.70 1.30 - - 4,147
7 41,725 3.59 1.41 - - 4,188
8 43,5 89 3.70 1.30 - - 4.092
9 195,785 2.45 1.20 0.91 0.45 11,507
10 206,342 2.70 1.18 0.91 0.21 11,445
11 163,554 2.45 1.20 " 0.91 0.45 10,915
12 172,996 2.70 1.18 0.91 0.21 10,852
13 142,188 2.39 1.18 0.93 0.51 12,287
14 144,297 2.43 1.18 0.93 0.46 12.432
15 94,785 2.39 1.18 0.93 0.51 11,932
16 97,149 2.43 1.18 0.93 0.46 11,835
17 98,516 2.46 1.63 0.91 - 7,626
18 107.230 2.61 1.67 0.72 - 7,388
19 64.382 2.46 1.63 0.91 - 7,451
20 69,699 2.61 1.67 0.72 - 7,263
21 9,528 3.31 1.69 - - 4.192
22 14,520 3.58 1.42 - - 4,065
29 41,683 2.62 1.74 0.64 - 6,929
30 46,267 2.77 1.79 0.44 - 6,744
31 14,914 2.62 1.74 0.64 - 6,924
32 19,342 2.77 1.79 0.44 - 6,664

I

 

180
Table K3. Maximum net present value (NPV), hectares planted by year and total labor
used (TLU) in person-days for different management schemes (M8) for
household type 3 in Region 11 at 10% discount rate in 1989 pesos.

 

j

 

 

Ms NPV (P) Area Planmd by Year (ha) TLU
1 2 3 4 5

1 142,722 1.62 1.01 0.76 0.63 0.54 6,903
2 151,987 1.73 1.04 0.77 0.63 0.54 6,953
3 103,794 1.62 1.01 0.76 0.63 0.54 6,743
4 111,724 1.73 1.04 0.77 0.63 0.54 6,788
5 59,354 2.21 1.57 1.21 0.01 - 4,182
6 61,305 2.27 1.59 1.14 - - 4,063
7 38,255 2.21 1.57 1.21 0.01 - 4,102
8 40,125 2.27 1.59 1.14 - - 4,008
9 178,748 1.51 0.74 0.56 2.20 - 11,147
10 187,570 1.66 0.72 0.56 2.06 - 11,060
11 138,477 1.33 0.78 "0.61 1.89 - 9,781
12 150,332 1.32 0.83 0.64 2.03 - 10,101
13 125,212 1.47 0.72 0.57 1.53 0.57 11,548
14 128,900 1.50 0.72 0.57 1.61 0.55 11,866
15 67,858 1.24 0.78 0.63 1.16 - 8,902
16 69,958 1.24 0.79 0.63 1.18 - 8,903
17 79,771 1.52 1.00 0.77 0.65 0.57 6,645
18 89,117 1.61 1.03 0.79 0.66 0.57 6,615
19 50,940 1.52 1.00 0.77 0.65 0.57 6,487
20 5,626 1.61 1.03 0.79 0.66 0.57 6,499
21 7,838 2.04 1.50 1.16 0.30 - 4,094
22 12,804 2.20 1.58 1.20 0.02 - 3,977
29 35,808 1.61 1.07 0.95 0.79 0.39 6,459
30 41,085 1.71 1.10 0.98 0.80 0.41 6,499
31 12,005 1.61 1.07 0.95 0.79 0.57 6,670
32 16,201 1.71 1.10 0.98 0.80 0.41 6,419

l

 

181
Table K4. Maximum net present value (NPV), hectares planted by year and total labor
used (TLU) in person-days for different management schemes (M8) for
household type 4 in Region 11 at 10% discount rate in 1989 pesos.

L

 

 

 

 

 

MS NPV (P) Area Planted by Year (ha) TLU
' 1 2 3 4 5
1 161,245 1.96 1.23 0.92 0.76 0.13 7,633
2 168,161 2.09 1.25 0.93 0.72 - 7,486
3 117,693 1.96 1.23 0.92 0.76 0.13 7,458
4 124,159 2.09 1.25 0.93 0.72 - 7,311
5 61,492 2.67 1.89 0.44 - - 4,223
6 63,509 2.75 1.93 0.32 - - 4,105
7 39,900 2.67 1.89 0.44 - - 4,143
8 41,830 2.75 1.93 0.32 - - 4,050
9 184,427 1.82 0.89 0.67 1.61 - 11,267
10 193,827 2.01 0.88 0.67 1.44 - 11,188
11 154,808 1.82 0.89 " 0.67 1.61 - 10,726
12 163,233 2.01 0.88 0.67 1.44 - 10,646
13 133,825 1.77 0.88 0.69 1.66 - 12,033
14 135,739 1.81 0.87 0.69 1.63 - 12,166
15 81,995 1.50 0.94 0.76 1.40 - 10,757
16 84,533 1.50 0.95 0.77 1.43 - 10,758
17 91,093 1.83 1.21 0.94 0.79 0.23 7,435
18 99,814 1.94 1.24 0.95 0.80 0.07 7,212
19 58,564 1.63 1.21 0.94 0.79 0.23 7,260
20 64,042 1.94 1.24 0.95 0.80 0.70 7,087
21 8,636 2.46 1.82 0.72 - - 4,142
22 13,620 2.66 1.91 0.43 - - 4,019
29 38,999 1.95 1.30 1.15 0.60 - 6,797
30 43,494 2.06 1.33 1.18 0.43 - 6,617
31 13,357 1.95 1.30 1.15 0.60 - 6,792
32 17,661 2.06 1.33 1.18 0.43 - 6,537

 

182
Table K5. Maximum net present value (NPV), hectares planted by year and total labor
used (TLU) in person-days for different management schemes (M8) for
household type 5 in Region 11 at 1% discount rate in 1989 pesos.

 

 

 

 

MS NPV (P) Area Planted by Year (ha) TLU
1 2 3 4 5
1 176,680 2.98 1.86 0.16 - - 7,873
2 183,132 3.17 1.83 - - - 7,711
3 130,181 2.98 1.86 0.16 - - 7,698
4 136,328 3.17 1.83 - - - 7.536
5 64,688 4.05 0.95 - - - 4,283
6 66,647 4.17 0.83 - - - 4,163
7 42,360 4.05 0.95 - - - 4.204
8 44,259 4.17 0.83 - - - 4,108
9 200,936 2.76 1.35 0.89 - - 11,615
10 211,028 3.05 1.33 0.62 - - 11,538
11 167,620 2.76 1.35 " 0.89 - - 11,005
12 176,947 3.05 1.33 0.62 - - 10,939
13 146,179 2.69 1.33 0.98 - - 12,408
14 148,227 2.75 1.33 0.93 - - 12,553
15 97,258 2.69 1.33 0.98 - - 12,036
16 99,650 2.75 1.33 0.93 - - 11,938
17 100,775 2.78 1.84 0.38 - - 7,681
18 109,769 2.94 1.89 0.17 - - 7,445
19 66,153 2.78 1.84 0.38 - - 7,506
20 71,635 2.94 1.89 0.17 - - 7,320
21 9,785 3.73 1.27 - - - 4,208
22 14,830 4.04 0.96 - - - 4.078
29 42,718 2.95 1.97 0.08 - - 6,978
30 47,248 3.13 1.87 - - - 6,787
31 15,515 2.95 1.97 0.08 - - 6,973
32 19,937 3.13 1.87 - - - 6.707

 

183
Table K6. Maximum net present value (NPV), hectares planted by year and t0tal labor
used (TLU) in person-days for different management schemes (M8) for
household type 6 in Region 11 at 10% discount rate in 1989 pesos.

 

 

 

 

 

 

M5 NPV (P) Area Planted by Year (ha) TLU
1 2 3 4 . 5
1 185,167 4.67 0.33 - - - 7,993
2 191,611 4.98 0.02 - - - 7,828
3 137,048 4.67 0.33 - - - 7,818
4 143,219 4.98 0.02 - - - 7,653
5 66,401 5.00 - - - - 4,315
6 68,165 5.00 - - - - 4,190
7 43,679 5.00 - - - - 4,235
8 45,433 5.00 - - - - 4,135
9 211,979 4.34 0.66 - - - 11,831
10 222,051 4.78 0.22 - - - 11,745
11 175,363 3.90 0.55 " 0.55 - - 11.216
12 182,445 3.90 0.55 0.55 - - 11,091
13 154,631 4.22 0.78 - - - 12,646
14 156,699 4.31 0.69 - - - 12,797
15 101,400 3.54 0.76 0.70 - ‘ - 12,201
16 103,530 3.54 0.76 0.70 - - 12,091
17 106,271 4.36 0.64 - - - 7,808
18 115,328 4.62 0.38 - - - 7,565
19 70,460 4.36 0.64 - - - 7,633
20 75,875 4.62 0.38 - - - 7,440
21 10,542 5.00 - - - - 4,250
22 15,487 5.00 - - - - 4,110
29 44,863 4.63 0.37 - - - 7,075
30 49,569 4.91 0.09 - - - 6,885
31 16,760 4.63 0.37 - - - 7,070
32 21,344 4.91 0.09 - - - 6,805

 

I E E

APPENDD( L

Schedules of Plantation Development in Region 6

185

Table L1. Maximum net present value (N PV), hectares planted by year and total labor
used (TLU) in person-days for difl‘erent management schemes (MS) for
household type 1 in Region 6 at 10% discount rate in 1989 pesos.

- ‘

MS‘ NPV (P) gArea Planmd by sea (ha) TLU

 

 

1 2 3 4 5
1 157,457 1.83 1.14 0.86 0.71 0.47 7.570
2 164,270 1.95 1.17 0.86 0.71 0.31 7,423
3 114,628 1.83 1.14 0.86 0.71 0.47 7,395
4 120,997 1.95 1.17 0.86 0.71 0.31 7,248
5 60,649 2.48 1.76 0.76 - - 4,207
6 62,627 2.56 1.79 0.65 - - 4,088
7 39.251 2.48 1.76 0.76 - - 4,127
8 41,148 2.56 1.79 0.65 - - 4,033
23 46,259 1.81 1.20 " 0.94 0.77 0.28 6.249
24 53,271 1.97 1.25 0.96 0.78 0.05 6,080
25 9,144 1.81 1.20 0.94 0.77 - 5,840
26 23,847 1.97 1.25 0.96 0.78 0.05 5,980
29 27,480 1.81 1.11 0.94 0.74 0.38 6,692
30 31,935 1.92 1.13 0.96 0.74 0.25 6,545
31 1,028 1.81 1.11 - - - 4,077
32 4,050 1.92 1.13 0.96 - - 5,291

 

‘MS9-22 = not included in Region 6.
M827 & 28 = not included having negative NPVs.

186

Table L2. Maximum net present value (N PV), hectares planted by year and total labor
used (TLU) in person-days for different management schemes (M8) for
household type 2 in Region 6 at 10% discount rate in 1989 pesos.

 

 

 

 

MS‘ NPV (P) Area Planted by Year (ha) TLU
1 2 3 4 5
1 164,317 2.10 1.31 0.98 0.61 - 7,683
2 170,97 1 2.24 1.34 0.99 0.43 - 7.530
3 120,178 2.10 1.31 0.98 0.61 - 7,508
4 126,443 2.24 1.34 0.99 0.43 - 7,355
5 62,335 2.85 2.02 0.13 - - 4,240
6 64,390 2.94 2.06 - - - 4,122
7 40,549 2.85 2.02 0.13 - - 4,160
8 42,512 2.94 2.06 - - - 4,067
23 48,657 2.08 1.38 " 1.08 0.46 - 6.328
24 55,653 2.26 1.43 1.10 0.21 - 6,152
25 10,375 2.08 1.38 1.08 0.46 - 6,228
26 25,472 2.26 1.43 1.10 0.21 - 6,052
29 29,023 2.08 1.27 1.08 0.57 - 6,813
30 33,448 2.20 1.29 1.10 0.41 - 6,632
31 1,181 2.08 1.27 - - - 4,681
32 4,650 2.20 1.29 1.10 - - 6,074

 

 

‘MS9-22 = not included in Region 6.
M827 & 28 = not included having negative NPVs.

187

Table L3. Maximum net present value (N PV), hectares planted by year and total labor
used (TLU) in person-days for different management schemes (M8) for
household type 3 in Region 6 at 10% discount in 1989 pesos.

MS‘ NPV (P) Area Planwd by Year (ha) TLU
1 2 3 4 5

 

 

 

1 112,989 1.29 0.80 0.60 0.50 0.43 5,465
2 120,323 1.37 0.82 0.61 0.50 0.43 5,505
3 82,170 1.29 0.80 0.60 0.50 0.43 5,338
4 88,448 1.37 0.82 0.61 0.50 0.43 5,374
5 55,380 1.75 1.24 0.96 0.82 0.24 4,098
6 57,421 1.80 1.26 0.96 0.82 0.15 3,983
7 35,196 1.75 1.24 0.96 0.82 0.24 4,018
8 37,120 1.80 1.26 0.96 0.82 0.15 3,928

23 33,970 1.27 0.85 " 0.66 0.54 0.47 4,697

40,141 1.38 0.88 0.67 0.55 0.47 4,741

25 6,435 1.27 0.85 0.66 0.54 - 4,110

26 17,513 1.38 0.88 0.67 0.55 0.47 4,662

29 19,338 1.28 0.78 0.66 0.52 0.27 4,709

30 23,042 1.35 0.79 0.68 0.52 0.33 4,777

31 724 1.28 0.78 - - - 2,869

32 2,850 1.35 0.79 0.68 - 3,723

ar L

‘MS9-22 = not included in Region 6.
M827 & 28 = not included having negative NPVs.

51’

188

Table L4. Maximum net present value (N PV), hectares planted by year and total labor
used (TLU) in person-days for difl‘erent management schemes (MS) for
household type 4 in Region 6 at 10% discount rate in 1989 pesos.

 

 

 

 

MS‘ NPV (P) Area Planmd by Year (ha) TLU
1 2 3 4 5
1 136,776 1.56 0.97 0.73 0.61 0.52 6,616
2 145,655 1.66 1.00 0.74 0.61 0.52 6,664
3 99,469 1.56 0.97 0.73 0.61 0.52 6,462
4 107,069 1.66 1.00 0.74 0.61 0.52 6.505
5 58,625 2.11 1.50 1.16 1.23 - 4,167
6 60,674 2.18 1.53 1.17 0.12 - 4,050
7 37,693 2.11 1.50 1.16 0.23 - 4,087
8 39,637 2.18 1.53 1.17 0.12 - 3,995
23 41,121 1.54 1.02 " 0.80 0.65 0.57 5,686
24 48.592 1.67 1.06 0.82 0.66 0.57 5,739
25 ~ 7,790 1.54 1.02 0.80 0.65 - 4,975

26 21.200 1.67 1.06 0.82 0.66 0.57 5,644
29 23,409 1.54 0.94 0.80 0.63 0.32 5,07 1
30 27,893 1.64 0.96 0.82 0.63 0.39 5,783
31 876 1.54 0.94 - - - 3,473
32 3,450 1.64 0.96 0.82 - - 4,507

 

‘MS9-22 = not included in Region 6.
M827 & 28 = not included having negative NPVs.

 

189

Table 15. Maximum net present value (NPV), hectares planted by year and total labor
used (TLU) in person-days for difl'erent management schemes (M8) for
household type 5 in Region 6 at 10% discount rate in 1989 pesos.

 

 

 

 

 

MS‘ NPV (P) Area Planted by Year (ha) TLU
1 2 3 4 5

1 168,909 2.33 1.46 1.10 0.11 - 7,756
2 175,555 2.49 1.49 1.02 - - 7,601
3 123,894 2.33 1.46 1.10 0.11 - 7,581
4 130,169 2.49 1.49 1.02 - - 7,426
5 63,120 3.17 1.83 - - - 4.255
6 65,003 3.27 1.73 - - - 4,133
7 41,153 3.17 1.83 - - - 4,175
8 42,986 3.27 1.73 - - - 4,078
23 50,364 2.31 1.53 " 1.16 - - 6,383
24 57,163 2.51 1.59 0.90 - - 6,196
25 11,340 2.31 1.53 1.16 - - 6,283
26 26,503 2.51 1.59 0.90 - - 6,096
29 30,035 2.32 1.41 1.20 0.70 - 6,874
30 34,479 2.45 1.44 1.11 - - 6,689
31 1,314 2.32 1.41 - - - 5,210
32 5,128 2.45 1.44 1.11 - - 6,609

 

 

 

‘MS9-22 = not included in Region 6.
M827 & 28 = not included having negative NPVs.

190

Table L6. Maximum net present value (N PV), hectares planted by year and total labor
used (TLU) in person-days for different management schemes (M8) for
household type 6 in Region 6 at 10% discount rate in 1989 pesos.

 

 

 

MS‘ NPV (P) Area Planted by Year (ha) TLU
1 2 3 4 5

1 180,644 3.69 1.31 - - - 7,930
2 186,693 3.93 1.07 - - - 7,761
3 133,389 3.69 1.31 - - - 7,755
4 139,222 3.93 1.07 - - - 7.586
5 66,402 5.00 - - - - 4,315
6 68,165 5.00 - - - - 4,190
7 43,679 5.00 - - - - 4,235
8 45,433 5.00 - - - - 4,135
23 54,547 3.65 1.35 " - - - 6.508
24 61,402 3.97 1.03 - - - 6.313
25 13,704 3.65 1.35 - - - 6,408
26 29,396 3.97 1.03 - - - 6,213
29 32,641 3.66 1.34 - - - 7,021
30 37,150 3.88 1.12 - - - 6,828
31 2,010 3.66 1.34 - - - 7,016
32 6,414 3.88 1.12 - - - 6,748

 

‘MS9-22 = not included in Region 6.
M827 & 28 = n0t included having negative NPVs.

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