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AGRARIAN REFORM COOPERATIVES 
IN HONDURAS 



By 

MICHAEL J. MARTIN 



A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL 
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT 
OF THE REQUIREMENTS FOR THE DEGREE OF 
DOCTOR OF PHILOSOPHY 

UNIVERSITY OF FLORIDA 

1996 



Copyright 1996 
by 

Michael J. Martin 



This dissertation is dedicated to my Honduran friends who were patient and kind enough 
to share their rich lives and culture with me. It is also dedicated to my parents, whose 
unquestionable love and concern turned a Central American sojourn into a larger home. 



ACKNOWLEDGMENTS 

This dissertation is the product of the collaboration and assistance among many friends 
in Honduras and the University of Florida. I am especially grateful to my Chair, Professor 
Timothy Taylor, who generously contributed his guidance and support throughout the entire 
research process. The door to his abundant professional faculties was always open. I am also 
very grateful to my Cochair, Professor Uma Leie, whose amiably shared insights in the realm 
of international development have been invaluable in broadening my perspectives. Professor 
Chris Andrew, in whose class I presented the embryonic stages of this dissertation and who 
helped in the conceptualization and identification of the research problem, deserves much 
gratitude, as does Professor James Scale for sharing his rich technical skills and philosophizing 
on techniques and context. I extend a special appreciation to University of Florida President John 
V. Lombardi, who took time out of his busy schedule to serve on the committee. 

My sincere thanks go to Professor Keith Andrews, Director of the Pan-American School 
of Agriculture in Honduras, for providing fieldwork support and guidance. All the extension 
agents and staff at Zamorano have my gratitude for their assistance and friendship. I am indebted 
to the enumerators for turning tedium into fun and for relating so successfully with farmers. The 
farmers who participated in the survey merit particular appreciation for their time and trust. 

I am thankful for my brothers, Jim, Dan and Steve who provided invaluable 
encouragement that reminded me of the benefits of cooperation. I am also indebted to friends 
here in Gainesville who provided moral support when it was crucially needed. 



iv 



TABLE OF CONTENTS 



page 



ACKNOWLEDGMENTS iv 

LIST OF TABLES viii 

LIST OF FIGURES x 

ABSTRACT xi 

CHAPTERS 

1 INTRODUCTION 1 

Objectives 4 

The Arrangement of the Dissertation 5 

2 EVOLUTION OF FORCES THAT INSTITUTED HONDURAN AGRARIAN 

REFORM COOPERATIVES 7 

The Pre-Colonial Period 8 

Agriculture 8 

Land Tenure and Labor 9 

The Colonial Period 10 

Agriculture 10 

Land Tenure and Labor 11 

Independence 14 

Honduran Independence 15 

Honduran Land Tenure 1821 - 1898 17 

Honduran Land Tenure: 1898 - 1940 19 

Campesino Unions and the Design of HARCs during the Cold War 20 

Cuba and Bananas 20 

The Land Reform Law of 1962 22 

Decretos Leyes (Legal Decrees) Nos. 8 ife 170 25 

Agrarian Reform Amid Political Tumult: 1975 - 1988 28 

The Land Titling Program 33 

Collectivization 34 

Incentives in Collectives 34 

Structural Contradictions of Collectives in Agrarian Reforms 36 

HARC Collectivization: Underlying Forces 38 



V 



f 



3 INITIATING EFFICIENCY GAINS: TECHNOLOGY ADOPTION 40 

Introduction 40 

Determinants of Technology Adoption 41 

Methodology 43 

Data and Model Specification 45 

Results 47 

Summary 50 

4 TECHNICAL AND ALLOCATIVE EFFICIENCY: COLLECTIVE VS 

INDIVIDUAL 51 

Productive Efficiency 54 

Technical Efficiency 56 

Allocative Efficiency 59 

Nonparametric Frontiers 62 

Parametric Frontiers 65 

Technical Efficiency vis k vis Technology Adoption 69 

The HARC Stochastic Frontier 71 

Results 76 

Technical and Allocative Efficiencies 80 

Summary 87 

5 TRADITIONAL AND ADVANCED TECHNOLOGY: A COMPARISON OF 

BEANS AND MAIZE 89 

Beans: A Traditional Crop 90 

General Efficiency Comparisons: Maize and Beans 98 

Summary 102 

6 THE INFLUENCE OF HUMAN AND SOCIAL CAPITAL ON TECHNICAL AND 

ALLOCATIVE EFFICIENCY 103 

Introduction 103 

Theoretical Underpinnings of Human Capital 104 

Empirical Applications of Human Capital Components 105 

Education 106 

Training and experience 108 

Health 109 

Religion 110 

Social Capital Ill 

Empirical Model and Data 113 

Maize 114 

Beans 123 

Training and Education: Complements or Substitutes? 131 

Summary 143 



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7 THE NATURE OF HONDURAN AGRARIAN REFORM COOPERATIVES AS 



PRIVATE ENTERPRISES 145 

Introduction 146 

The problem 147 

Cooperative Enterprises and the New Institutional Economics 148 

Why Firms Exist 149 

Cooperatives in the NIE 150 

Contracts 151 

Contracts Related to HARC Basic Grain Production 152 

The Standard Administrative Chart 153 

Transaction Association by Activity 156 

Internal Contracts: The Black Box of the Firm 158 

Labor-labor contracts 159 

Administration-labor contracts 159 

External Contracts: Association with Support Agencies 160 

Campesino unionizing 161 

Land tenure 163 

Technical assistance 163 

Credit 164 

Marketing 165 

Vigilance Committees 166 

The Design of Efficient Institutions 167 

Credible Commitments 168 

Non-credible Commitments 168 

An Empirical Observation: The Guanchfas Cooperative 169 

Summary 171 

8 SUMMARY AND RECOMMENDATIONS 175 

Design of the Analysis 175 

Summary of the Results 176 

Recommendations 178 

Future Research 179 

The Potential Role Private Capital 179 

The Potential Role of NGOs 180 

APPENDICES 

I DATA AND STUDY AREA 181 

II FIELD SURVEY 188 

III REFERENCE LIST 199 

IV BIOGRAPHICAL SKETCH 211 



vii 



LIST OF TABLES 



Table page 

2.1 Distribution of Farmland by Farm Size in Honduras, 1974 29 

3.1 IPM Adoption: Pre-infestation maximum likelihood estimates 49 

4. 1 Average function: Maize ordinary least squares regression 77 

4.2 Frontier function: Maize maximum likelihood estimates half normal distribution ... 78 

4.3 Frontier function: Maize maximum likelihood estimates exponential distribution ... 79 

4.4 Technical and allocative efficiencies for maize half normal truncated distribution . . 81 

4.5 Technical and allocative efficiencies for maize exponential truncated distribution . . 83 

4.6 Differences in efficiency averages between collective and individual parcels 86 

5.1 Average function: Beans ordinary least squares regression 93 

5.2 Frontier function: Beans maximum likelihood estimates half normal distribution ... 94 

5.3 Frontier function: Beans maximum likelihood estimates exponential distribution ... 95 

5.4 Technical and allocative efficiencies: Beans half normal and exponential truncated 

distribution 96 

5.5 Differences in allocative efficiency between an imputed standard wage and zero 

wage for unpaid labor 98 

5.6 Average Technical and Allocative Efficiencies for Maize and Beans 99 

5.7 Coefficients of variation 101 

6.1 Personal and household characteristics - maize 117 

6.2 Physical capital - maize 119 

6.3 Social capital - maize 120 



viii 



6.4 Extension methods - maize 121 

6.5 Experience - maize 122 

6.6 Personal and household characteristics - beans 125 

6.7 Physical capital - beans 127 

6.8 Social capital - beans 128 

6.9 Extension - beans 129 

6.10 Experience methods - beans 130 

6.11 Lecture only - maize 133 

6.12 Publication only - maize 134 

6.13 Lecture and publication - maize 135 

6.14 Lecture and visual aids - maize 136 

6.15 Control group - maize 137 

6.16 Lecture only - beans 138 

6.17 Publication only - beans 139 

6.18 Lecture and publication - beans 140 

6.19 Lecture and visual aids - beans 141 

6.20 Control group - beans 142 

ALL Asentamientos by name, membership and land access 184 

AL2 Comparison of sample averages with national averages 185 



ix 



LIST OF FIGURES 



Figure page 
2.1 Adjudicated land: 1962 - 85 26 

4. 1 Input Requirement Set 57 

4.2 Farrell Technical and Allocative Efficiency 60 

7.1 Administration chart 155 

7.2 Activity chart 157 



X 



Abstract of Dissertation Presented to the Graduate School 
of the University of Florida in Partial Fulfillment of the 
Requirements for the Degree of Doctor of Philosophy 

AGRARIAN REFORM COOPERATIVES 
IN HONDURAS 

By 

Michael J. Martin 
December, 1996 

Chairperson: Timothy G. Taylor 

Major Department: Food and Resource Economics 

Honduran agrarian reform cooperatives (HARCs) perform poorly as economic 
enterprises. HARCs' inefficiency is generally attributed to their collective mode of production 
and to internal mismanagement. In this study, a stochastic frontier production function is 
estimated with cross-sectional maize production data on over 400 individual producers and 28 
HARCs. "Debreu-Farrell" efficiency estimates indicate that collective production is more 
technically and allocatively efficient than individual production. 

Frontier estimates on individual bean production data show much higher allocative 
efficiencies than those of maize. Input requirements for maize are more varied and advanced than 
those of traditional bean production and require adjustments in input mixes. That farmers are 
not optimally adjusting input mixes is attributed to ineffective input distribution systems. 

The most prominent single factor influencing HARC efficiency is commercialization. 
Group mean differences show that farmers who sell more of their output demonstrate higher 
technical and allocative efficiencies for both maize and beans. Commercialization is also a 

xi 



prominent factor in inducing farmers to adopt IPM technologies, as demonstrated by a bivariate 
logit regression. 

Technical and allocative efficiencies are compared for a variety of human and social 
capital group means. Extension is shown to be a substitute for education at low levels of 
education in improving technical and allocative efficiency. However, at higher levels of 
education, different types of extension methods, such as publication circulation, appear to 
complement general education. Education, literacy, health and experience show positive 
influences on efficiency. 

The greater efficiency of collective parcels suggests that the internal dynamics of the 
institutional "black box" of the firm are sound. However, transactions with support agencies are 
undependable as evidenced by ineffective distribution and marketing systems. Failure of implicit 
transaction contracts results from disparate incentives between HARC members and agency 
personnel. 

Collaboration with the private sector, which shares HARCs' economic aspirations, offers 
a means to capitalize on the economies inherent in the cooperative structure and efficiencies 
spurred by commercialization. The few cooperatives which contracted private capital show that 
HARCs can evolve into cooperatives that produce high quality products and generate investment 
returns that significantly increase member income and achieve social goals. 



xii 



CHAPTER 1 
INTRODUCTION 



The Honduran economy deteriorated significantly during the "lost decade" of the 1980s 
(see Hayes 1989) in spite of large infusions of U.S. financial aid. Per capita GDP, which grew 
annually at 2.2 percent between 1961 and 1980, fell at an average annual rate of 0.5 percent over 
the next ten years. Gross domestic investment and the real minimum wage also fell over the 
same period. The share of external public debt to GNP was 1 13.8 percent in 1991, twice the 
1980 level {World Development Report, 1993). Most of those funds were invested in state and 
parastatal agencies that are in the process of being privatized under pressure from the IMF and 
the World Bank. 

In 1991 Honduras' per capita GNP stood at US$ 580 (World De\elopment Report 1993), 
exceeding only that of Haiti in the western hemisphere. Over half of the country's 5.3 million 
inhabitants live in rural areas where absolute poverty, the inability to afford enough food to meet 
minimal nutritional requirements, is more pronounced. About 20 percent of the population is 
unemployed {Europa Yearbook, 1991), but casual observation suggests a high degree of 
underemployment as well. Infant mortality stands at 49 per 1,000 births and stunting afflicts 34 
percent of all children between the ages of two and five (World Development Report, 1993). At 
least 12,000 Honduran children die each year due to preventable illnesses, 25 percent of 
Honduran families suffer from protein deficiency and 62 percent show inadequate caloric intake 
(Barry and Norsworthy, 1990). Seventy-three percent of the population is literate (World 



1 



2 

Development Report, 1993), but functional literacy - the capacity to read sufficiently well to cope 
with modern instructions - is probably lower. 

Unlike its Central American neighbors, no powerful oligarchy emerged in Honduras' 
history as the dominant political and economic force to beget extremes of wealth and poverty. 
Still, incomes and land ownership are skewed. The richest 20 percent earn 63.5 percent of total 
national income while the poorest 20 percent earn 2.7 percent {World Development Report, 1993). 
Four percent of Honduran farms comprise 56 percent of total farmland, while 64 percent of the 
farms comprise nine percent of the farmland (Barry and Norsworthy, 1990). Such distribution 
may be acceptable in developed countries, but the distress of resource maldistribution in an 
agrarian based economy is inversely related to the size of a nation's resource base and directly 
related to the size of its population. It is interesting to note that only one in five Honduran farms 
is worked by its owner. The majority of farmers work under sharecropping or tenancy 
arrangements, or on municipal lands termed ejidos (Kurian, 1987). 

In an attempt to redress the problem of land maldistribution and mral poverty, Honduran 
governments have made sporadic attempts at land reform. Most farmers who wanted to obtain 
land under reforms were obligated to join an asentamiento (precooperative) and work collectively 
with other land reform participants in order to qualify for credit. By 1984, about 294,422 
hectares of land had been allotted to land reform groups. Total membership in the groups, 
however, declined from 61,176, counted at the time of land apportionment, to 48,129 in 1984 
(Instituto Nacional Agrario. 1985). 

Cooperatives are ostensibly preferred because they permit independent farmers to jointly 
make investments in production, storage and marketing activities that they would be unable to 
make individually, and because they provide a sense of security to members who individually can 
be devastated by the uncertainties of agriculture. Cooperatives also serve as educational 



3 

institutions and provide an efficient structure for development agencies to perceive production 
constraints and rural needs so that responses can be formulated in the form of credit and technical 
assistance. Cooperatives are thus intended to achieve both economic and social goals. 

However, Honduran agrarian reform cooperatives (HARCs) often fall into bankruptcy 
or never achieve a position of financial independence even though ample financial and material 
support have been provided. In 1982, 57 percent of the loans to ±e reform sector were 
delinquent (Stringer, 1989). Blame for cooperative failure is commonly placed on members, and 
accusations are heard of corruption, non-cooperation and apathy. But such problems, or at least 
the potential for them, are present to some degree in all firms. Given the extreme poverty in 
Honduras, and the physical and mental frailty that inevitably accompanies it, cooperative failure 
may result from an underinvestment in human capital and institutional flaws which fail to account 
for human capital deficiencies. 

HARCs have a notorious record of inefficiency, owed principally to the high rate of loan 
defaults. The precise nature of the inefficiency, however, has never been rigorously analyzed. 
An abundance of conjectural notions attribute inefficiency to ignorance, corruption or culture. 
Even development plarmers and social scientists are quick to discount cooperatives as infeasible 
forms of association, in spite of their theoretical advantages. 

It is possible that cooperatives do capture some forms of efficiency better than, or at least 
as well as, other forms of organization, but due to persistent bankruptcy they are rejected in 
whole. Do cooperatives fail because production is inadequate? Are cooperatives allocatively 
inefficient, investing in inputs that do not generate a justifiable value with respect to their 
marginal addition to production? Or are they both technically and allocatively efficient, but 
experience financial collapse because they are poorly managed? Distinguishing services that 
coops can perform successfully vis ^ vis those which they cannot will suggest specific aspects of 



4 

policy measures that hold a higher probability of solidifying sustainable cooperative enterprises. 



Objectives 

This dissenation endeavors to examine how HARCs can become more "efficient." The 
concept of efficiency is multi-faceted, related to physical input-output relationships, human capital 
investments, internal firm organization, market operations and relations with public and private 
organizations. The lines between each facet are not always conveniently distinct for the purpose 
of analysis. Efficiency concerns of HARCs are intuitively characterized in three areas: 
technology adoption, a requisite for improving technical efficiency; production efficiency in terms 
of both physical input-output, or "technical," efficiency and price or "allocative" efficiency; and 
institutional efficiency, or the rules that govern HARC operations. All are examined vis k vis 
human capital investments upon which HARCs both depend and are mandated to augment. 

Although HARCs have had a notably poor record in achieving financial viability, little 
research has been done concerning the possible means of rectifying characteristic problems. Thus 
the primary objective of this dissertation is to identify efficiency weaknesses in HARC operations. 
Additionally, this dissertation contributes to the general knowledge of ajricultural development 
concerning aspects of cooperative organizations that depend on human capital investments and 
broadens the scope of empirical cooperative and human capital studies. 

The following objectives are designed to identify aspects of institutional behavior and 
human capital investments characteristic of Honduran cooperatives so that policies may be drawn 
to improve economic performance: 

1. Review the evolution of forces that institutionalized HARCs. 



5 

2. Examine how human capital, extension methods and demographic characteristics 
influence the adoption of integrated pest management (IPM) techniques. 

3. Compare the technical and allocative efficiencies of individual production systems vis 
^ vis collective production systems. 

4. Examine how human capital, extension methods and demographic characteristics 
influence technical and allocative efficiency of individual production. 

5. Examine the complementarity of education and varying extension methods in 
improving technical and allocative efficiency. 

6. Synthesize the results in a new institutional economics (NIE) rubric in a manner which 
yields viable policy alternatives. 

The Arrangement of the Dissertation 

The chapters below probe three principle underlying facets of HARC operations. Chapter 
2 reviews the evolution of forces that instituted HARCs. How human capital influences the 
adoption of advanced technology, an intermediate step in improving and modernizing agriculture, 
is examined in Chapter 3. 

Chapter 4 presents a stochastic frontier model and empirical results of collective and 
individual production systems. Collectivization has been indirectly mandated within the reform 
sector as it has traditionally been a requirement for HARCs to receive credit and support services 
from government agencies and because ownership of individual parcels has been precluded by 
land reform legislation. Technical and allocative efficiencies are compared for collective and 
individual parcels. A stochastic frontier estimation of bean production is presented in Chapter 
5 and compared with maize estimations presented in Chapter 4. Beans are grown using a more 
traditional technology than maize. 

Human and social capital deficiencies are often cited as sources of inefficiency within 
HARCs. Human and social capital are examined directly in Chapter 6 as they pertain to 



6 

allocative and technical efficiency. Chapter 6 further examines the complementarity of education 
and extension techniques in improving technical and allocative efficiency. 

Finally, empirical results are synthesized in Chapter 7 and interpreted within the broader 
discrete institutional framework in which HARCs operate. The gathering of data involved 
extensive fieldwork, dozens of cooperative meetings and contact with government support 
agencies. Relating empirical results to general observations of the operating environment is a 
further means of capitalizing on direct fieldwork. The intention is to identify short-run 
modifications in HARC governance to account for human capital shortages that generally require 
long-run investments. 



CHAPTER 2 
EVOLUTION OF FORCES THAT INSTITUTED 
HONDURAN AGRARIAN REFORM COOPERATIVES (HARCS) 

Agrarian structures in Central America have evolved over the last 500 years in response 
to political and economic shocks. Unlike North America, where agricultural settlements 
completely supplanted Indian communities, Hispanic colonization incorporated indigenous peoples 
to extract scarce labor and foodstuffs. 

Aspects of current Central American agricultural organization can be traced back to 
colonial and even pre-coloniaJ eras. Placing the current system within the context of political 
history reveals institutional transactions (Bromley, 1989) that served to minimize transaction costs 
(Coase, 1937 and Williamson, 1985) for interests that influenced Honduran agrarian reform 
cooperatives (HARCS). Institutions that ostensibly serve HARCs wan-ant reevaluation in the 
post-Cold War world to identify structures that misaligned incentives with enforceable 
responsibilities. Transaction costs may be reduced by reorganization within the constraints of 
available technology and capital investments, major focuses of this study. 

The purpose of this chapter is to review the forces that both motivated and constrained 
Honduran agrarian reform throughout history. Those forces explain peculiarities in the design 
of HARCs, relative to the organization of classical economic firms, that provide a context within 
which to interpret empirical observations. 



7 



The Pre-Colonial Period 



8 



The ancient ethnic conflicts persist in Guatemala and southern Mexico are relatively 
absent in Honduras. However, a review of pre-colonial institutions offers insight into the Spanish 
colonial framework that was established to control indigenous populations and the post-colonial 
tenure systems that emerged. 

Agriculture 

A variety of Indian cultures inhabited Honduras when the Spanish initiated their conquest 
in the sixteenth century. Historical evidence is available for the Mayan society, which stretched 
from western Honduras north to the Yucatan. Information is scarce regarding Indian societies 
that resided in the central and eastern regions.' However, a few reliable observations about the 
pre-colonial Honduran agricultural economy may be obtained from previous studies. 

Maize and beans, which continue to form the basic staples of Central American diets, 
were cultivated in all areas of Honduras along with manioc and sweet potato. Except for a few 
small irrigated systems in the Mayan region, farming in Honduras was rainfed. Remnants of 
gardens and orchards have been found, especially along the banks of rivers where flood waters 
brought natural fertilization. Only the mute dog and the turkey were domesticated for 
subsistence. Tribes in eastern Honduras were more reliant on hunting .ind gathering and were 
generally smaller and more dispersed than those in western and central Honduras. 

Human carriers and canoes formed die only modes of transport. Central American 
Indians used no animal traction and, in spite of impressive Mayan intellectual achievements in 



'A discovery of a burial tomb of "glowing skulls" was recently made in the area, but 
research results are still being processed. 



9 

mathematics, calendrics, architecture and astronomy, never developed the wheel. Trade was thus 
limited primarily to clothing goods such as fabrics and feathers and light agricultural products. 

Swidden agriculture, a constrained form of which is still practiced in Central America, 
was the predominant farming method. This is an extensive system of cultivation which generally 
requires at least two years of fallow for soil rejuvenation. Land was cleared by hand with stone 
axes and cultivated with hoes and digging sticks (the barreta, which is .;till in use). Typically, 
farmers abandoned one site after cultivation and slashed and burned the debris from another, the 
fertility of which had been restored by time and natural vegetation. The length of the 
rejuvenation cycle varied across regions, but at least twice as much fallow land was required to 
sustain output. 

Institutional land constraints have deprived most contemporary Central American farmers 
of the rejuvenation portion of the cycle, although debris from the previous season's crops are still 
burned. Rising populations have further tightened those constraints, contributing to acute social 
and political conflicts. 

Land Tenure and Labor 

The Mayan Empire was never ruled by one authority, but their ;enters were larger and 
more advanced in terms of abstract knowledge, technology and economic diversification than 
other contemporary indigenous populations in Honduras. The degree ( f centralization and the 
bases of economic support and activity varied across settlements and time. The most fundamental 
organization of ancient Mayan society was, as it continues to be, the nuclear family. 

Morley et al. (1983) argue that as class distinctions widened, the Mayan elites coerced 
peasant classes into a feudal relationship whereby the peasants were apportioned land to cultivate, 
the product of which was shared with the nobles. In exchange for their igricultural production, 



10 

as well as military service and non-agricultural labor, the peasants may have received protection 
from outside raiders. 

The chiefdoms in western and central Honduras were primarily dependent on subsistence 
agriculture. They were not as diversified as the Maya, but nobles employed commoners or slaves 
for the goods and services they consumed (Torquemada, 1723). The smaller tribes in eastern 
Honduras were more egalitarian; the only division of labor was based on sex and age. Men 
undertook the clearing of lands and hunting and fishing, while agriculture and child rearing was 
primarily entrusted to women. 

The Colonial Period 

Although Honduras was discovered by Columbus by 1502, colonization was not 
effectively imposed for decades. Other conquests in the new world offered greater reward at less 
expense, owed principally to Honduras' rough terrain, relative lack of processed precious 
minerals and lack of broad social structure. The riches of the Aztec and Inca made the 
opportunity costs of conquering the scattered tribes of Honduras prohibitive to the 
conquistadores. Nonetheless, colonization eventually came and obliterated aboriginal chiefdoms 
and tribes in Honduras. Newson (1986) speculates that by the end of colonial rule, over 90 
percent of the Indian population had been annihilated by slavery, forced labor and disease. 
Miscegenation further eroded Indian communities, giving rise to the predominance of Honduras' 
mestizo population. 

Agriculture 

The Spaniards introduced new crops and agricultural methods, but the technology of 
production and the crops grown on Indian lands changed little. Indigenous foods of maize and 



11 

beans became a fundamental part of the colonialists' diet. The Spanish either produced their own 
conventional grains of wheat and rice, or extracted them as tribute from Indians who had to be 
supplied with implements and draft animals. Converse to current production patterns, wheat 
production expanded in colonial Honduras to meet domestic market demands, though rice did not. 
Rice now constitutes a staple and is produced throughout Central America. Virtually no wheat 
is grown in Central America, though wheat products are becoming increasingly popular, owed 
principally to PL-480 shipments. Colonists also successfully introdu;ed bananas and citrus 
products, commodities that now form the backbone of the Honduran export economy. 

Agriculture in colonial Honduras was dominated by livestock production. Cattle, horses 
and mules found a compatible new environment in the disease and predator-free high grasslands 
of the Honduran savanna. The mule and horse industry flourished to satisfy demands in 
agricultural production, mining and, most importantly, in transport. Indigo, hides and tabasco 
were produced for export to Spain, but were minuscule relative to mining operations (Newson, 
1986). 

Land Tenure and Labor 

The design of colonial institutions was endogenous to the accessibility of indigenous 
populations and the nature of social structures, particularly with respect to labor hierarchy and 
land tenure, that confronted the Spanish. Tribal divisions and warfare, which had been 
accelerated by the Quichi overextending its dominance to other Central American tribes, also 
provided incentives for tribal leaders to collaborate with the militarily s iperior Spaniards. 

According to Newson (1986), the Spanish extracted slaves from easily accessible lowland 
areas in Central America to work in colonial mining operations. In the relatively remote 
highlands, the existence of a jurisdictional structure provided the conquittadores with a low cost 



12 

means to secure a ready labor supply. The Crown granted encomiendai to colonists that in 
essence conferred property rights over the Indians while ostensibly providing the Indians with 
protection and instruction in the Catholic faith. In exchange, colonists were allowed to levy 
tributes in the form of goods or money and, initially, labor, on the Indians. 

Agriculture initially played a subsidiary role to mining in the colonial economy of 
Honduras. Colonists turned increasingly to agriculture as urban living expenses spiraled and 
opportunities for wealth creation declined in urban areas (Macleod, 1983). High food prices also 
served as an inducement to establish agricultural enterprises and supply urban dwellers (Frank, 
1979). Tributes, exacted through encomenderos that often exceeded legal bounds, constituted the 
most important source of Crown revenue. 

Rampant violations of colonial duty and the abdication of protection obligations forced 
the Crown to transfer tribute exaction to local administrators who established labor quotas 
(repartamientos^) in indigenous villages. By that time, disease and forced slavery had taken a 
serious toll on Indian populations, and thus on the available labor supply. Colonists then divided 
up Indian labor for not just public and religious institutions, which had been the original intention 
of the repartamiento, but also for private individuals. The work was so arduous and the pay so 
minimal, laborers suffered malnourishment and were unable to work their own land adequately. 
Poor diets for the Indian workers and their families further weakened their resistance to 
prevailing epidemics. 

Encomiendas and repartamientos served as viable tools of enforcement in areas where 
Indian states and chiefdoms already existed because most Indians were accustomed to paying 



^" Encomienda" comes from the Spanish word encomendar, which means "to entrust." 

^"Repartamiento" is derived from the Spanish word repartir, which means "to divide" or 
"to distribute. " 



13 

tributes to authorities and because the hierarchical structure provided a low cost means of 
exercising control over large populations. In areas absent of large social structures where 
nomadic tribes subsisted on swidden farming, hunting and gathering, the incorporation of Indians 
into the colonial economy was cost prohibitive. The Crown charged Catholic Missions with the 
task of training Indians how to function in the culture diat had over-powered them. However, 
small disparate tribes were only brought under control when their attacks caused costly 
interference in Spanish commerce. In such instances Indians were routinely exterminated or 
captured for slavery. 

Pre-colombian Indian land holdings were technically honored by royal decree. In reality, 
however, Spaniards either ignored the decree or circumvented it by various means. The very act 
of proclaiming property rights to indigenous peoples was a defacto expropriation of the land they 
inhabited. Ultimate ownership rested with the Crown and was exercised on its behalf through 
judicial appointees for mutual economic benefit. 

Land was offered to Spaniards as an incentive for colonization and the conquest of the 
Americas and came to be a valuable source of government revenues necessary to protect royal 
property. Martinez Peldez (1975) contends that the Crown extended property rights to die 
Indians as a means of ensuring their presence to pay the agricultural tributes needed to supply 
mining activities and urban lifestyles. 

In 1591, the Crown instituted two portentous cedulas (decrees) affecting land tenure. The 
first, which ostensibly would have benefitted the Indians, ordered all lands illegally usurped to 
be returned to the Crown. The second cidula, however, granted that illegally owned lands could 
be rightfully purchased. Colonists, by virtue of their much greater wealth and knowledge of 
Spanish law relative to the Indians, were able to circumvent the first cidula to benefit from the 
second. Redistribution of power or influence was confined to Spanish appointees or 



14 

entrepreneurial Creoles who accumulated enough capital to invest in lucrative official positions 
(Brading, 1986). This skewed distribution of land prevails in Honduras. 

The encomienda system lasted longer in Central America than in any other area of 
Spanish America (Newson, 1986). The current demographic complexion of Honduras began to 
take shape as the Indian population was surpassed by the mestizos through slavery, disease and 
miscegenation. Royal Decrees offered no property rights to mestizos as it had to Indians. 
Latifundios expanded through the exploitations of mestizos, who were forced to devote portions 
of their production in exchange for usufruct privileges (Martin6z Pel^ez, 1975). 

Independence 

Latin American revolutions in the 19th century were inspired by their North American 
counterparts and facilitated by Napoleon's incursions into Spain. However, while much of the 
independence rhetoric was similar, the Spanish aristocracy continuec". to rule. Apart from 
forswearing formal titles that eliminated colonial taxes, little else changed for the majority of the 
people. 

Central America was polarized between two forces that would continue to squabble, at 
great expense to economic development, into the twentieth century. The conservatives arose from 
Spanish aristocracy and sought to maintain colonial institutions and social classes without the 
burden of royal tribute. The liberals, comprised mostly of elite bureaucratic professionals that 
formerly served the aristocracy, saw economic benefit in reforms that expanded economic 
opportunity. 

A major source of contention between liberals and conservative-, concerned the Church 
as a formal component of government. The Church conferred moral justification on die 
privileges enjoyed by elite conservatives and was instrumental in quelling the masses. Perhaps 



15 

most destructive to long-run stability and development was the disp;ite on education. The 
conservatives wanted to maintain an elitist system of education under the auspices of the Church, 
while the liberals promoted secular, and ultimately mass, education. Like the Crown, 
conservatives claimed and exercised the right to make ecclesiastical appointments (Barnadas, 
1986). 

Liberals sought to reduce trade barriers and eliminate monopoly rights that conservatives 
held by virtue of their royal commission. Liberals also wanted to ban the nepotism of 
conservatives in governmental, commercial and ecclesiastical positions. 

Both parties were comprised of elite, urban, intellectual interest", and encompassed only 
a small portion of the total population. Notions of broad-based utilitarianism, promoted most 
notably by Jeremy Bentham, provided a philosophical rallying force to revolt against Imperial 
Spain. However, the exact terms of "utilitarian" economic design did not result from such 
popular consensus. 

Honduran Independence 

Honduras experienced three independences in the frenzied rebellions that swept the 
Spanish Americas in the nineteenth century. It was first liberated from Spain as part of what was 
to be the Kingdom of Mexico. Anarchy in Mexico afforded the Audencia de Guatemala an 
opportunity to institute its own autonomous government, Provincias Unidades del Centra de 
America. With the exception of Chiapas, all the states of the Audencia revolted against Mexico 
and joined the Provincias. 

Central American unity, however, was hampered by the surge of hemispheric 
independence that permeated all levels of society. Motivations for local participation and 
autonomy were born of nascent ideals and economic opportunity. Powerful regional caudillos 



16 

(political/military strongmen) in each state provided conservatives the foixes needed to defeat the 
liberals, led by Francisco Morazan, but they ultimately dissolved Central America into five 
independent states. Independence for Honduras was thus a by-product of war strategy rather than 
a popular consensus based on cultural heritage or economic principles. 

Elections notwithstanding, caudillos ruled Honduras from 1839 until the mid twentieth 
century. The private acquisition of public and Church lands, a hallmark of liberal economic 
programs intended to stimulate exports and growth, aroused a symbiotic alliance between colonial 
elites and the Church on the one hand, and Ladino and Indian communities on the other. 
Conservative forces respected Church property rights and supported preservation of ejido lands 
for subsistence farmers, who constituted the majority of the population. Economic growth slowed 
under conservative rule, the country returned to traditions that reflected traditional Hispanic- 
Catholic principles, and subsistence farming gained in prominence vis k vis export agriculture. 

Apprehensions about capitalism also arose from the lack of government capacity to 
administer a broad-based development agenda. Liberals attempted to op-in alarming proportions 
of property to foreign investment. A debilitating shadow over liberal economics was cast by 
William Walker, a U.S. citizen who, in the name of democracy and economic freedom, 
proclaimed himself president of Nicaragua. His group of predominantly Mississippi Valley 
mercenaries recruited after the Mexican-American War expected to receive land in return for 
their services and were extremely unpopular in Honduras, which had proclaimed war on the 
United States to defend Mexico. They represented the detrimental excess of economic 
liberalization: foreign usurpation of domestic resources and political control. Walker, who was 
executed in Honduras after a failed filibuster, severely discredited Liberal policies throughout 
Central America and intensified anti-American sentiments that prevail tc this day. 



17 



Honduran Land Tenure 1821 - 1898 

The land tenure patterns that evolved in post-independence Latin America differed 
substantially from those in North America. The United States and Canada opened their frontiers 
to settlers, allowing for a more equitable distribution of wealth and ensuring property rights to 
people within the political and economic system (ethical considerations regarding the usurpation 
of Indian lands aside). Property rights were much more tenuous in Latin America, owed to the 
continuation of ejido lands and absentee landlordship of large holdings. Agricultural technology 
lagged in Latin America, restricting labor productivity and the consequent labor and food 
surpluses exigent to industrial growth. 

The industrial revolution in the mid 19th century that transformed the global economy 
influenced Honduras' Central American neighbors much more than Honduras. Recorded history 
and data on the 19th century Central American economy are sparse, but some policies and 
especially the reactions to them reveal distinguishing features of Honduras. Coffee plantations 
arose in Guatemala, El Salvador and Costa Rica in response to rising world demand, but did not 
take hold in Honduras until the twentieth century. 

Liberal reforms regained prominence among Honduran political philosophers who also 
contended that, unlike the laissez faire reforms promoted by Francisco Morazan, government had 
a pivotal role to play in economic development. Lacking a bourgeois class, Honduran economic 
strategists considered government necessary to stimulate growth and secure integration with the 
world economy (IHDER, 1980). A new constitution in 1880 mandated the state to establish 
credit for Honduran enterprises and provide the infrastructure necessary to attract foreign 
investment. 

Liberal reform began in 1876 when President ]os6 Maria Medina, under economic 
liberalization pressures from Guatemala, yielded the chief post to Marco Soto (Yankelvich, 1988). 



18 

Soto considered ejido structures inefficient and in 1877 instituted an agrarian law that slated 
coffee, cacao and Indian rubber as favored exports (Guevara, 1983). The intent of the reform 
was to propel Honduran agriculture into modern specialized production. Central to the agrarian 
law was the dictate that municipalities sell any national lands to bidding entrepreneurs at a "just 
price." The government took an active role in designing and monitoring the agricultural system. 
Landowners and laborers of "modern farming units" were exempted from military and civil 
obligations and the tariffs on imported agricultural inputs. The Government established strict 
guidelines regarding such things as fencing, crops and laborers that constituted modern farming 
units. Participating farmers were required to make written reports to demonstrate their 
compliance every six months. 

Interventions to stimulate the production of export crops failed. Reasons for the failure 
are not clear. Coffee, which initially was considered the crop of greatest potential, began a long- 
term decline in world demand soon after the program was mounted (Guevara, 1983). Also, labor 
was not as inexpensive relative to other Central American countries, partially because some ejido 
lands remained inalienable (IHDER, 1980; and Quinones and Argueta, 1978). Rugged terrain 
and poor transportation and communication systems also hindered commerce. 

Government support for transportation infrastructure was hampered by the enormous debt 
it incurred from trying to build a transcontinental railroad earlier in the century. In 1892 the total 
debt was over 73 times annual export volumes. Consequently, foreign investors were reluctant 
to invest in Honduras. The failure to attract upstanding foreign investors rendered Honduras 
vulnerable to riskier international investors who promised great returns but did nothing more than 
further deplete the treasury. The bulk of Honduran agriculture thus remained a decentralized 
system of traditional subsistence farming into the 20th century (Guevara, 1983). 



19 



Honduran Land Tenure 1898 - 1940 

Banana exports began growing along the north coast of Honduras around 1880. Most 
of the production came from small, independent producers who sold their produce to 
intermediaries close to the coast or with river transport vessels. Banana production grew in 
popularity among small commercial farmers. Unlike coffee, the favored export of the 
government, bananas could be grown with relatively little capital investment and along rivers that 
enabled transport. Most important, bananas presaged short-run gains. 

The liberal reforms' hapless attempts to establish a bourgeois class in the 19th century 
were dealt a decisive blow by the emergence of international banana companies. Twentieth 
century commodity production, storage and transportation required capital investments beyond 
the reach of most Hondurans and certainly beyond that of small-scale farmers engaged in banana 
production. Ultimately, foreigners established large banana plantations that sold directly to 
exporters, thus undercutting both small Honduran producers and intermediary transporters 
(Guevera, 1983). 

Honduran land reforms during 1898-1961 reserved public lands for family parcels. The 
Honduran Institute of Rural Development (IHDER, 1980) identified two characteristics of land 
reforms during that period. First, the reforms established inalienable property rights, the intent 
of which was to impede land concentration and proletarianization of rural labor. The 1924 decree 
stipulated that family parcels be 20 hectares (Stokes, 1947). Second, because reform parcels 
were small and used primarily for subsistence crops requiring only about ..00 labor days aimually, 
land reforms provided an abundant, low wage seasonal labor force. The motivations for the 
various decrees during this period have been attributed to the government's desire to spur 
economic growth and generate tax revenue (Villanueva, 1968) and to ameliorate lay-offs in the 
banana industry (IHDER, 1980). 



20 

Most of the pre-Cold War land reform debate was rooted in disputes between campesino 
unions and large American fruit companies. Land reform initiated in the basic grain sector is 
distinct in many ways from land reform in the banana sector. Integral to both sectors were the 
campesino unions that fused political strength among the landless to pressure for land 
redistribution. 

Campesino Unions and the Design of HARCs during the Cold War 

The first campesino unions appeared around the late 1920s. Financed and influenced by 
the communist party (Posas, 1981), they were characterized by the inflaiDmatory Marxist rhetoric 
that began fueling the reactionary backlashes to a broad range of grassroots social organizations 
characteristic of, and crucial to, open democratic societies. Campesino unions were influenced 
by national and international forces which, particularly throughout the Cold War, had enormous 
leverage over the design of HARCs. Those forces arose from political exigencies that, unlike 
the forces that forge autonomous cooperatives, did not necessarily hold economic efficiency - or 
even viability - as a guiding principle. 

Cuba and Bananas 

Two events in the 1950s had dynamic impacts on Honduran agrarian reform, the Cuban 
revolution and the lay-off of over 18,000 laborers on banana plantations. Labor organizing was 
already afoot in Honduras prior to the Cuban revolution. Labor and farm organizations were 
inspired significantly by Cuba, as were academic institutions that could provide scarce technical 
and logistic support for mobilization activities. Massive floods and an unprecedented strike in 
1954 in which 25,000 workers participated gave United Brands incentive to restructure by closing 
operations on marginal lands and by making labor-saving capital investments. The company 



21 

reduced its labor force by 69 percent between 1954 and 1963 (Posas, 1987). Those workers were 
forced to return to subsistence production, but they returned with a new form of human and 
social capital embodied in the capacity to organize for worker rights. 

Campesino unions modeled their organization on urban and banana company union 
mentors, whose objectives and optimal strategies were different from landless farmers. Urban 
and plantation workers tend to be more concentrated than campesinos, allowing for relatively low 
costs of coordinating activities. It was easier to define and achieve consensus on the goals among 
urban and plantation union members than among campesinos. Association with and support of 
internationally polarized "labor" organizations also drew campesinos into conflicts about which 
they had little understanding and to which, by virtue of their geographical dispersion and 
illiteracy, their interests were more vulnerable. 

Two principle campesino unions emerged in Honduras at the inception of the Cold War. 
The first, the National Federation of Honduran Campesinos (FENACH^ was an offshoot of the 
unionizing apparatus of the 1954 strike. Although FENACH was spawned by autonomous local 
organizations largely devoid of revolutionary ideology, two of its three principle leaders were 
militant communists (Posas, 1987). Within two months of the founding of FENACH in 1962, 
another, less radical, campesino organization appeared, the National Association of Honduran 
Campesinos (ANACH). ANACH could claim some lineage to the grassroots 1954 organizations, 
but it also received support from the American Institute for Free Labor Development (AIFLD), 
an AFL-CIO affiliate that received funding from the U.S. Agency for International Development 
(US AID) and from its parent organization, the Inter-American Regional Organization of Workers 
(ORIT). ANACH was clearly a union established by foreign funding as a moderating alternative 
to FENACH. 



22 

Both ANACH and FENACH applied for personeria juridica, which technically confers 
legal recognition on individuals or organizations. In practice it is used as an institutional 
mechanism to support - or leave unmolestedthose in the government's favor. ANACH was 
granted personena juridica two months after solicitation. FENACH, v/hose principle disputes 
were with the Tela Railroad Company (a subsidiary of United Brands), was never granted 
personeria juridica (Posas, 1981). 

One would be hard-pressed to argue, given the collapse of communism, that Marxist 
intellectuals' abstract notions of an ideal society, and particularly its attainment, were in sync with 
the aspirations of uneducated laborers and farmers. On the other hand, opponents of 
communism, however defmed, reacted in Honduras and throughout Lstin America on several 
well documented occasions by means contrary to the democratic ideals which they espoused. 
Cold-War reactions were also evidenced more subtly in development assistance programs. 
Honduran agrarian reform cooperatives became tools of partisan international concerns which 
relegated the long-term benefit of the HARCs subordinate to the attainment of political goals. 

The Land Reform Law of 1962 

The Cuban revolution prompted anti-communist forces within Latin America and the 
United States to respond to landless farm workers as a means of quelling violent uprisings in the 
western hemisphere. The Alliance for Progress, accorded at the Inter /vmerican Conference at 
Punta del Este in 1961, stipulated that aid recipient countries must mount land reform programs 
in order to qualify for assistance. 

Though motivated by political exigencies, land reform also had economic underpinnings. 
The redistribution of idle lands was consistant with the Kaldor-Hicks compensation principle in 
terms of wealth in that resources began generating substantive economic gains; a potential transfer 



23 

could compensate absentee landowners for the negligible utility derived from owning but not 
utilizing the land. Redistribution also constituted a stricter Pareto improvement in terms of 
income in that the former owners derived no income from idle lands. 

The Alliance induced democratically elected President Ram()n Villeda Morales to establish 
the National Agrarian Institute (INA) in 1961. INA was mandated to respond to land petitions 
and coordinate land distribution. It was also charged with providing support services, principally 
the organization and support of cooperatives. 

The Villeda government passed the first land reform law in 1962 that slated not only 
government lands for distribution, but idle private lands as well, thus requiring all lands to serve 
social purposes. Unused lands were ostensibly subjected to progressive taxation or expropriation, 
but ambiguously written laws and ineffectual enforcement capacity mitigated the threat to vigilant 
landowners or land holding companies (IHDER, 1980). Property rights have never been clearly 
defined in Honduras. To the extent that a real -estate market exists in Honduras, INA and the 
judiciary serve as its clearing houses. 

Latifundistas could also legally activate idle lands by establishing cattle ranching 
operations, a convenient activity for absentee landlords that resulted in a threefold increase in 
beef production while domestic consumption of beef declined (Monthly Review, 1985). 
Transferring pastures to crops would apparently be a much more efficient use of the land in terms 
of income, employment and foreign exchange earnings or savings (Garcia et al. 1988). 

Growing popularity of structural reforms, legitimized by the Alliance for Progress, 
pressured Villeda on one side while the landed status quo and banana companies pressured him 
from the other. The opposing forces destabilized a balance that was vulnerable to interference 
by a virtually autonomous military. Villeda's attempts to weaken the military through 
institutional reform enraged commanders who were encouraged by dictators in Nicaragua and the 



24 

Dominican Republic to overthrow the government (Morris, 1984). Subsequently, aspirations for 
land reform were cut short by the coup d'etat in October, 1963, led by Colonel Oswaldo Ldpez 
Arrellano. 

Campesino unions' expanding influence had apparently posed a greater threat than the 
1962 agrarian reform. The military did not reverse the agrarian reform law, but weakened INA 
and destroyed FENACH by ransacking its offices and assassinating its leaders. Consequently, 
the slow rate at which land was being distributed was halved (Bueso, 1987). 

L(3pez's tenure as dictator and later as a not-so-freely elected president was marred by 
traditional bureaucratic corruption. Forces arose to effectively challenge the traditional caudillo 
politics. Labor unions and business organizations recognized mutual benefit in extending 
government participation to all sectors of the Honduran public. A severe hurricane and the 
infamous "football war" with El Salvador mobilized Honduran society ■o work collectively for 
the first time, propagating the wide-spread recognition of governmental rights. The agrarian 
reform of Peru had also inspired younger military personnel, many of whom came firom 
campesino families and empathized with agrarian concerns. 

In 1971 Colonel L6pez ostensibly relinquished control of the political forum to 
democratic elections. The campaign of 1971 brought Ramdn Ernesto Ciuz to the presidency for 
a brief interlude from military rule. Cruz represented the conservative National Party, which 
owed its strength to its alliance with, and the campaign management of, the military. 

The Cruz administration prohibited land "invasions", a dangerous and final recourse 
campesinos had to demonstrate the acuteness of their poverty and thus their resolve. Six 
campesinos who had invaded land in the department of Olancho were cssassinated and several 
others wounded and incarcerated in early 1972. Campesino unions contended land seizures were 
"recuperations" rather than invasions because such land was actually govermnent or ejidal land 



25 

illegally expropriated by latifundistas through forged documents or outright bribery. Sensing 
their alienation from the real political processes, ANACH planned a massive hunger march and 
other actions that threatened social stability. In December the military restored order by 
peacefully relieving Cruz of the presidency and reinstalling General Oswaldo L(3pez Arellano as 
chief of state. 

L(5pez returned to power cognizant of the need to broaden his political base. At a huge 
rally shortly before the coup he emphasized that "The Armed Forces are composed of workers 

and campesinos , the Armed Forces are not enemies of the workers and the campesinos." 

Ldpez, who arose from campesino stock, proceeded to carry out the most extensive agrarian 
reform in Honduran history. 

Decretos Leves (Legal Decrees) Nos. 8 & 170 

Within a month after assuming power, Ldpez promulgated temporary agrarian reform 
legislation. Law Decree Number 8 (popularly referred to as Decreto No. 8). Decreto No. 8 was 
billed as an emergency two-year measure necessary to respond to campesino needs until long- 
term legislation could be designed. Unlike previous agrarian laws that were rendered ineffective 
through myriad loopholes and ambiguities, Decreto No. S bestowed clear, decisive power on INA 
to grant access to lands that were not fulfilling a social purpose. Consequently, the pace of land 
adjudication accelerated dramatically (Figure 2.1). The purpose of Decreto No. 8 was to 
incorporate campesinos into the economy and give willing workers the opportunity to improve 
their livelihoods. 



Tota I and Arab I e 



30, QQD 



40,000 



20,000 



10, 000 





/ - ' * \ 




/ ' ^ \ 

/ ' * \ 
/ / \ \ 


/ 


\ 1 \ V — 1 

' ^ \ / \ ^ 

' ^ \ — - 'A 


■y'l 

/ / 

y ~ " 



1 1 \^^^r ' 1 1 


^.....^..^-^ 

1 1 1 1 1 1 



1962 196'^ 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 

YEAR 

Tota I Arab I e 



Source- IHDER, 1980. 



re 2.1 Adjudicated land: 1962 - 85 



27 

The declared "temporary" nature of Decreto No. 8 and the swiftness with which it was 
implemented reduced the potential for opponents to organize and contributed greatly to its impact. 
More than twice as much total and arable land was adjudicated under the scheduled two year 
enforcement of Decreto No. 8 than the previous ten years under the agrarian reform of 1962. 
Campesino mobilization is considered the pivotal factor that precipitated the reform. 92 percent 
of the groups had to pressure INA in extraordinary ways to obtain land. Over 23,000, or 15 
percent of all rural landless families, (about 140,000 people) were granted land-use rights to 
108,496 manzanas (IHDER, 1980). 

Upon expiration of Decreto No. 8 a new agrarian decree, Decreto No. 170 was enacted. 
Decreto No. 170 consisted of 180 articles that in practice marked a return to legal sidestepping 
and thus a deceleration in reform. Decreto No. 170 granted permanence to the temporary land- 
use permits granted under Decreto No. 8 and maintained the authority to expropriate idle lands. 
However, Decreto No. 170 also denied legal recourse to campesinos that obtained land by 
invasion, a principle means of procuring land under lethargic government agencies. 

Concomitant with the surge of land adjudications was the growth in public credit to serve 
the increasing number of asentamientos'* in the reform sector. The low rate of loan repayment 
to public lending institutions has come to be one of the major criticisms of HARCs. However, 
large farmers have exhibited equivalently high default rates (Lele 1974. IBRD 1975). In 1980, 
the total amount of non-payment in the nonreform sector was more than three times higher than 
in the reform sector (IHDER, 1980), though the non-reform sector repaid 63 cents to the Lempira 
compared to 56 cents for the reform sector. 

*" Asentamientos are considered "pre-cooperatives" in that they have not been awarded 
personerfa juridica, although they invariably belong to a campesino union that is legally 
recognized. Technically, for a group to qualify for status as a coopera.ive, it must be granted 
a personerfa juridica. Legal recognition is reserved for those organizations that have 
demonstrated their good citizenship to the government. 



28 

Administrative corruption is not uncommon in Honduras. General Ldpez was ousted 
from power after the Wall Street Journal alleged he had accepted a millicn-doUar bribe that saved 
United Brands over 75 million dollars in taxes. Loan defaults become more understandable, if 
not excusable, under such circumstances when looked at from the perspective of a politically and 
economically weak campesino. 

Agrarian Reform Amid Political Tumult: 1975 - 1988 

L(3pez was succeeded by General Juan Alberto Melgar Castro in a peaceful coup d'etat 
in April 1975. Melgar's power abided in anti-reform forces intent on curbing the pace of land 
distribution. Over one-half of rural agricultural families were still landless after the reforms 
achieved under the Ldpez regime, 56 percent of the land was still claimed by less than five 
percent of the families (Table 2.1). 



29 



Table 2.1 Distribution of Farmland by Farm Size in Honduras, 1974 



1 Oillt 01Z.V \HCXj . / 


No of Farms 


% 


No. of has. 


% 


Under 1 


jj, III 


1 / . J 


7^ S49 

Z 1 , JtZ. 


n 8 


1 - 2 


1 O /CCA 

io,o5(J 


1 Q Q 






fir 

2-5 


1/CA 


ZD. 6 


L\JJ,0\JJ 




5 - 10 


28,264 


14.5 


201,274 


7.7 


10 - 50 


34,390 


17.6 


729,361 


27.7 


50 - 100 


4,433 


2.3 


301,228 


11.5 


100 - 1,000 


3,304 


1.7 


763,673 


29.0 


1,000 + 


169 


0.1 


395,330 


15.0 


Total 


195,341 


100 


2,62),859 


100 



Source: Stringer, 1984. 



30 

Land invasions continued with little effective response from the government. Landed interests 
belonging to the National Federation of Agriculturalists and Stock Raisers of Honduras 
(FENAGH) began an intimidation campaign against campesino unions and land reform 
proponents. Tensions were manifested in the summer of 1975 when, again in the Department 
of Olancho, ten leaders of the National Union of Campesinos (UNC), two priests and two women 
were murdered at the hands of ranchers and military officers. UNC has endured more violent 
intimidation than any other campesino union in Honduras. 

Frustrated with the Melgar government's unwillingness to provide basic protection and 
its reluctance to enforce provisions pertaining to both idle and ejidal lands, the three national 
campesino unions forged an alliance. The United Campesino Front (FUNC). Melgar responded 
to FUNC with his plan "Operativo Reldmpago Juan A. Melgar Castro." The plan resulted in the 
distribution of 8,722 hectares to 3,160 families. Melgar's reluctance tc either implement legal 
reforms or decisively reverse them angered campesinos and the "Superior Council of the Armed 
Forces" (CONSUFFAA) that installed him. Melgar eventually dismissed heads of INA and the 
Labor Ministry who had been appointed by Ldpez Arellano and were proponents of reform, but 
he was too late to demonstrate control. CONSUFFAA announced Melgir's resignation in 1978 
and installed General Policarpo Paz Garcfa. Paz ruled until 1982, during which time few land 
requests were processed. 

Characterization of campesino unions was often based on association, not unlike the 
McCarthy years in the United States. UNC sprung from rural developm;nt programs sponsored 
by the Catholic Church and assistance from Christian Democratic Party. After the Second 
Vatican Council in 1964 the Catholic Church placed new emphases on ministering to the poor, 
which unsettled traditional power structures throughout Latin America. UNC was a part of the 
General Central of Workers (CGT), an activist organization backed by Christian socialists in 



31 

Latin America. Although founded by 1972, UNC had to wait until 1984 to obtain its personeria 
jurfdica (Posas, 1987). In another instance, Efrafn Diaz Galeas, a former president of ANACH, 
riled financial sponsors by soliciting assistance from UNAH faculty, whom the sponsors 
considered communists. The Executive Committee of ANACH yielded to threats of funding cuts 
by dismissing Diaz. Dfaz later reappeared as the president of the Federation of Agrarian Reform 
Cooperatives (FECORAH). a campesino union that was also delayed fojr years in obtaining its 
personeria jurfdica. 

ANACH, by contrast, long the largest campesino union in Honduras, had been relatively 
unperturbed by the military, owed principally to its alliance with AIFLD. Generous operating 
budgets financed by the AFL-CIO, USAID, and a number of private corporations ranging from 
IT&T and Mobile Oil to Sterling Drug and Bacardi Co., (SITRAUNAH, 1979) gave ANACH 
the capacity to bid organizers away from grassroots unions or hire talented organizers otherwise 
uninterested in union mobilization. ANACH organizers were thus more financially beholden to 
foreign interests than to the campesinos whom they represented. Unions that arise from 
autonomous forces are by nature more democratic in that they must respond to the economic 
needs of their members. Incentives existed in ANACH, on the other hand, to subordinate the 
economic welfare of the HARCs to political priorities. 

This is not to deny that the AFL-CIO had sincere ideological interests in preventing 
unions from being overcome by communist control. However, the principle source of funding 
for AIFLD was the US government (92 percent in 1969). Several members of the original 
AIFLD Administrative Board headed companies that had large financial interests in Latin 
America. 

The strings attached to ANACH were unmasked in 1978 when Antonio Julfn M^ndez 
accused the sitting president of ANACH, Reyes Rodriguez Ar^valo, of fraudulent reelections. 



32 

M^ndez demonstrated the veracity of his charges by congregating a majority of assembly 
representatives in opposition to Rodrfguez. A year later at an ANACK national convention in 
a Lion's Club hall in Siguatepeque, M^ndez again outnumbered Rodrfguez supporters 173 to 109. 
Upon realizing he was at a political disadvantage, Rodriguez abandoned the convention to 
reconvene in a military battalion. Paz Garcia had shown his support for Rodrfguez earlier by 
deporting a missionary priest who had denounced Rodriguez's corruption (Posas, 1987). The 
military did not recognize the majority of ANACH delegates, led by M6ndez and Camilio Padilla, 
but ratified the Ar^valo faction. However, the M6ndez and Padilla coalition received a valuable 
endorsement from the Confederation of Honduran Workers. M^ndez's authority would again be 
unsuccessfully challenged in 1984 by an operative of General Gustavo Alvarez Martfnez, the 
army commandeer responsible for the civillian crackdown and several disappearances in the 
1980s. 

The failures and tribulations of campesino unions cannot be solely attributed to external 
forces. UNC and FECORAH arose from other labor organizations and, like ANACH, were 
always in the process of splintering themselves. The fragmenting of unions was easier to 
accomplish in rural-based unions than in urban or plantation unions because rural systems are 
necessarily less centralized. Regional and local campesino union leaders hold more member 
allegiance than national leaders. 

Under Melgar, INA embarked on a policy that divided its resources between export crops 
and basic grains. The Paz regime slated eight percent of INA's total budget to the basic grain 
sector while designating almost 65 percent to commercial export crops. Bananas account for 
about 22 percent of all national value-added and occupies less than five percent of area planted 
to crops. Basic grains on the other hand, contribute only about 14 percent to value added even 
though it uses about 65 percent of cropland (Stringer, 1987). Critics charged on social grounds 



33 

that land reform had become a colonization project through coerced collectivization and die 
transferring of campesinos from their homes to areas where land was less constraining. On the 
other hand, allocating labor resources to a higher level of employment has distinctive economic 
benefits. 

One persistent aspect of the post- WWII reforms was the attempt to propel the agricultural 
population into modern agricultural production (IHDER, 1980). Neighboring Central American 
countries had more advanced production and higher growth rates, but the maldistribution of 
wealth and income contributed to social upheaval (Bulmer-Thomas, 1989). Honduran reforms 
endeavored to escape that fate. 

The Land Titling Program 

In 1981 Roberto Suazo Cdrdova became Honduras' first democratically elected president 
in 20 years. Suazo campaigned strongly on an agrarian reform platform. The pace of land 
redistribution increased 75 percent over the previous four years. Nonetheless, at the end of 
Suazo's tenure over 125,000 rural families still had no secure access to land (Ruhl, 1989). Rural 
population growth alone fed the landless population faster than the land reform could reduce it. 
Suazo had not satisfied his political mandate with respect to land reform. 

In 1981, at the behest of USAID, the focus of land tenure adjustments switched from 
outright redistribution of public or private lands to land titling. In order to qualify, a farmer 
must demonstrate he has worked a specific parcel of land, but that his tenure was not secure or 
legally binding. The primary intentions of the titling program were to provide workers of the 
land collateral for credit and long term incentives to make land improvjments. The quality of 
soil and the extent to which crops are commercialized influences participation in the land titling 



34 

program (Seligsan and Nesman, 1989). Those factors have also been s'lown to be important in 
the adoption of technology (Martin and Taylor, 1995). 

Structural adjustment measures have encouraged privatization mroughout all sectors of 
the Honduran economy, including the agrarian reform sector. The land reform law of 1992 
opened vast tracts of land for sale by cooperatives in the agrarian reform sector. 

Collectivization 

Beginning in 1962 land reforms in Honduras reversed the liberal tradition of distributing 
specific parcels to individual families, opting for a collective form of enterprise. In theory, 
collectivization improves efficiency by permitting large "lumpy" investments in production, 
storage, marketing and input purchases that are beyond the capacit) of small, capital-poor 
farmers. Cooperatives also theoretically reduce monitoring costs associat"xi with large enterprises 
and lower transaction costs of providing extension and support services to large numbers of 
farmers. In practice however, collectives have had a poor economic record. Attrition rates have 
always been high in HARCs, averaging over 30 percent between 1962 2nd 1985 (Bueso, 1987). 
Loan default rates were also disproportionately higher for HARCs than for individual farmers. 
More than half of the National Bank of Agricultural Development's (BANADESA) loans to the 
reform sector were delinquent as of 1982 (Stringer, 1989). 

Incentives in Collectives 

The conditions under which voluntary collectivization might occur are the focus of 
agricultural production cooperative (APC) theory (Putterman 1986, 1989; Bonin, 1987; Carter, 
1987) which contrasts the behavior of collective production based on va^ing work and revenue 
sharing rules. APC theory customarily attributes cooperative failure to "shirking," the 



35 

relinquishment of individual responsibility to other members. The problem is that widespread 
shirking leaves many responsibilities unfulfilled and negatively impacts cooperative performance. 
The important question, however, is not if shirking occurs, but whether it overrides gains in 
efficiency arising from worker collectivization. 

APC theory does not take into account the role of human capital. Two of the collective 
production systems often alluded to in discussions of APC theory, the Kibbutz in Israel and the 
Hutterite communities in the U.S., place a high value on human capital investments. Nor does 
APC theory - or the cooperative literature in general - distinguish the types of monitoring costs 
that different cooperatives may be more successful in reducing. Illiterate members cannot carry- 
out simple bookkeeping procedures and are obviously ill-equipped to oversee complicated 
contracmal obligations. On the other hand, landless farm laborers are capable of monitoring the 
unspecialized agricultural labor tasks to which they are accustomed. The shirking alleged by 
Alchian and Demsetz (1972), would be relatively more difficult to accomplish under such 
circumstances than the financial rent-seeking cited by Jensen and Mecklirg (1979). To the extent 
that dignity is derived from labor, shirking may be unlikely to occur. Fieldwork is one of the 
few endeavors available to HARC members, and one in which pride is evidenced in traditional 
folklore, dance and song. 

The exact nature of HARC breakdown caimot be easily attributed to shirking - at least 
at the level of manual labor. In fact, a common charge leveled against campesinos is that they 
are simple people who "love to work with their machetes in their milpcs (cornfields)," but that 
they are disinterested about the more cerebral matters of managing technologically advanced 
enterprises. HARCs' dismal financial history may abide in elements other than the technical 
inefficiency implied by shirking. Even firms that are one hundred percent technically and 



36 

allocatively efficient could be ruined by financial mismanagement - especially if institutions do 
not safeguard interest holders from "opportunism with guile" (Williamson, 1985). 

Structural Contradictions of Collectives in Agrarian Reforms 

The justification for land reform sits on tenuous ground when cooperatives are promoted 
as part of the reform to capture economies of size'. Many reform advocates contend that skewed 
land distribution results in inefficiency because small farmers are consid^jred to be more efficient 
than large farmers (See Corner and Kanel 1971; Berry and Cline 1979; Cornia, 1985). On the 
other hand, development planners impose cooperative structures in an attempt to capture 
efficiencies that are supposedly absent in large operations. The economic argument for agrarian 
reform cooperatives are thus fallacious unless large collective enterprises could attain greater 
efficiency than those that are individually operated. 

This may be a tenable proposition for land reform coopera.ives in Honduras and 
elsewhere in Central America. Honduran agrarian structures are still emerging from precapitalist 
modes of production and are often still characterized by absentee ownership and sharecropping 
practices that maintain traditional production methods. By the same token, cooperatives have 
lacked the managerial skills in both production technology and administration needed to exploit 
the potential for economies of size. Scale economies that require specialization exact transaction 
costs for monitoring because production processes become less personal (Bardhan, 1989), 
partially, at least, explaining why sharecropping practices persist (Alchi;m and Demsetz, 1972). 
But the cooperative naturally reduces monitoring costs because members are owners and bear 

^ Economics traditionally treats efficiencies obtained from the simultaneous expansion of all 
inputs as economies of scale. Economies of size, on the other hand, occurs when long term, 
often "lumpy" and not necessarily simultaneous, investments lower the average total cost of 
production. Economies of size is used here because it is more comprehensive and thus more 
precisely represents efficiencies sought by the process of collectivization. 



37 

substantial peer pressure on one another. The desire to collaborate in a productive manner was 
quite noticeable among the majority of HARC members. 

Size economies in HARCs are likely to become increasingly attainable as technological 
advances are adopted because long-run capital investments such as farm machinery, input 
inventory, transportation and storage equipment reduce per unit costs of output. Such 
investments provide new opportunities for coop members to exploit comparative labor advantages, 
underscoring the importance of the division of labor to carry out specialized tasks and a 
managerial workforce which can dedicate its time to identifying and implementing profitable 
activities. Many of those opportunities depend on labor talents that can emerge only through 
concomitant investments in human capital. The combination of monitoring cost reduction gained 
through collectivity, and the division of labor gained through human capital may thus allow for 
the capturing of size economies beyond the grasp of large individual farms or poorly skilled 
cooperatives. 

Beyond efficiencies in production, collectives reduce costs incurred by service delivery 
agencies. New technologies inevitably require a learning process and are aggressively promoted 
by input suppliers who exploit the glamour appeal those technologies hold on traditional farmers. 
Cooperatives are efficient structures for technical and support agencies to monitor operations and 
provide agricultural training to large numbers of farmers. Budgets in developing countries are 
inadequate to employ enough support personnel and extension workers to train and monitor 
individual farming operations. In cooperatives training is conducted through seminars from 
professional instructors and, more importantly, transferred through other members (Martin and 
Taylor, 1995). 



38 



HARC Collectivization: Underlying Forces 

It is difficult to discern precisely why the collective was adopted as the predominant form 
of operation and production in the Honduran agrarian reform sector. Stringer (1984) attributes 
collectivization to Roberto Sondoval Corea who was appointed Director of INA in 1968. 
Cardona (1979) ascribed the origins of collectivization to Jorge St. Siegens, a Romanian 
economist who was contracted at the recommendation of UNESCO to serve as the Technical 
Director and Professor of the Autonomous University of Honduras (UNAH). Posas (1987) 
claims Virgilio Carias, Head of the Economic Research Institute at UNAH, initially promoted 
the Israeli mode of production in the successful and broadly renowned Guanchfas Cooperative 
on the North Coast. 

Although the origin of collective production is unclear, one thing is certain: HARCs have 
lacked proper incentive structures and enforcement mechanisms of contracts, particularly with 
government support agencies, have been notoriously weak. Property assurances are also firagile. 
HARC members hold no individual title to specific parcels. In fact, very few HARCs technically 
own the land which they work collectively. 

The motives for imposing collective production, through denial of credit and technical 
assistance to individual farmers, are seen in almost all the official organizations that support the 
HARCs. The government appreciates collectivization as HARCs can absorb additional farmers 
who are more reluctant to risk their lives invading land than to arrange an agreement with HARC 
members for formal admittance (IHDER, 1980). Collectivization also permits large financial 
transactions to be made between loan agents and a few campesino union officials, outside the 



39 

scrutiny of individual HARC members. "Soft-state" governments such as Honduras are 
vulnerable to nepotism and rent-seeking agency staff that could detrimentally exploit HARCs. 

The notion of collectivization was also supported by nongovernmental entities in 
Honduras for political, not economic, reasons. The campesino unions maintain more political 
control over collectives than they could over individual farmers who, once owning a land parcel, 
would be less dependent on the union and more difficult to mobilize. Cold War development 
planners also found collectives (within a free enterprise rubric) to be a means of mollifying 
communist supporters in allied countries. 



CHAPTER 3 
INITIATING EFFICIENCY GAINS: 
TECHNOLOGY ADOPTION 

Introduction 

Technology adoption lies at the foundation of improving production efficiency in the 
agrarian reform sector of Honduras. Technological change has rapidly become available to 
HARC members whose production systems, rooted in ancient Mayan traditions, are still practiced 
throughout Central America. Slash and burn methods of field preparation developed reflexively 
over generations as farmers sought to maximize efficiency within the physical and institutional 
parameters imposed on them. Abundant land resources of Mayan civilizations allowed farmers 
to abandon fields long enough to become naturally rejuvenated. Fields allowed to lie fallow for 
several years benefit from the natural growth of vegetation and composting which restore essential 
nutrients to the soil. Unlike their ancestors, however, modern-day Central American farmers are 
not afforded the luxury of moving on to another parcel of naturally rejuvenated land. Colonial 
institutions and population growth have tightened land constraints and forced farmers to cultivate 
the same land every year. Perennial cultivation tires the soil and gradually lowers yields from 
traditional production methods. 

Worsening soil fertility has provided impetus for farmers to seek and experiment with 
various technologically advanced production methods. Expanded markets and complementary 
technologies have provided further impetus. The capacity of farmers to respond to such pressures 
often corresponds to their ability to purchase complementary human capital, either in themselves 



40 



41 

or through hired labor. Small farmers usually lack the funds to purchast, necessary assistance for 
technology adoption. 

Environmental strain has also motivated development institutions to promote 
environmentally friendly, or "sustainable," technologies. High-input strategies of the "green 
revolution" depend on non-renewable natural resources. International agricultural development 
institutions are now mandated to simultaneously pursue environmentally friendly and productivity 
enhancing technologies (GREAN, 1995). Integrated pest management (IPM) technologies are 
considered crucial to environmentally friendly components of agricultural systems. 

Integrated pest management strategies require the identification of, and the complex 
interactions among, organisms that occur in the crop system. IPM attempts to introduce 
biological control agents that are compatible with management schemes and the ecological 
dynamics of the agricultural system. The ultimate goal is to develop minimally disruptive 
methods of managing pests that do not reduce the value of agricultural output. Those 
technologies are being developed, but perhaps more challenging is the effective promotion of 
technology adoption among farmers in developing countries. This chapter addresses that task. 

Determinants of Technology Adoption 

Education and extension have long been considered indispensable to technology diffusion 
and the correction of attendant economic disequilibria (Schultz, 197.t). Lack of skill and 
knowledge lie at the root of production inefficiencies which have restricted production systems 
in developing countries from reaching their technical frontiers. 

The level of human capital in Central American farmers in general and Honduran farmers 
in particular is low. Functional literacy levels in rural Honduras stands at about fifty percent 
(World Fact Book 1988). Institutional factors also influence the accessibility and appropriateness 



42 

of technology. Land tenure arrangements of small farms in Central America are tenuous, 
increasing the risk associated with new technologies. Credit is available on a sporadic basis, 
reducing producers' capacity to sustain newly adopted technologies. Farm and household size 
vary in the region as well, playing important roles in the selection of technologies. 

Technology transfer in rural Honduras is confronted with some formidable obstacles. 
Assistance programs to introduce new technologies are often criticized fcr not taking into account 
a common farmer's opportunity set, production constraints and, perhapj most important of all, 
his mental preparedness to respond to assistance. If outside technology is introduced to an area 
that lacks the skills to interpret and screen relevant information, then the "spill in" of the 
technology will not occur. 

In developing countries, much of the social science literature regarding technology lies 
outside economics, focusing on normative notions related to political and social aspects of 
production (Roy and Clark 1994). Birkhaeuser, Evenson and Feder (1991) review several studies 
related to the determinants technology adoption and efficiency. Jamison and Lau (1982) 
indicated that education positively influences productivity and technology adoption of Thai 
farmers. Khaldi (1975) and Pudasaini (1983) indicate that education improves allocative 
efficiency progressively more as the rate of technology adoption increases. 

Martin and Taylor (1995) showed that producers of commercial crops and members of 
cooperatives are more inclined to adopt new technologies than subsistence and independent 
farmers. Their results also demonstrated that T&V training methods lave a multiplier effect 
through personal contact of experts and friends, and are very effective in motivating technology 
adoption in contrast to impersonal multi media techniques. 

This chapter examines the adoption of integrated pest management (IPM) techniques 
developed by the Integrated Pest Management Program (Spanish acronym MIPH) of the Pan 



43 

American Agricultural School. MIPH promoted IPM procedures among HARCS in the study 
area (See Appendix I for data and study area). 

IPM technologies merit inquiry on three counts. First, they are specific technologies 
which can be investigated in depth with a few questions (See Appendix II for the survey 
instrument). The second refers to the word "integrated" in the term "integrated pest 
management." IPM technologies integrate several other production technologies ranging from 
soil preparation to the point of harvest. Other technologies such as fertilizer application or row 
spacing may be components of IPM, but they do not depend on other technologies to the same 
degree as IPM. Thus IPM technologies serve as a proxy for the adoption of comprehensive 
systems. Finally, IPM is pertinent to cooperative organizations because IPM techniques often 
work more effectively at the level of common property (Rook and Carlson 1985; Meister 1980). 

MIPH randomly assigned four different training types to HARCs in the sample. One 
group was set aside with no training to serve as a control group against which extension efforts 
could be measured. The training types were: 

1. Printed material only 

2. Lectures only 

3. Lectures and printed material 

4. Lectures, printed material and electronic visual aids. 

Trained agronomists visited the groups on a regular basis to give lectures and/or supply 
printed information. MIPH focused on common problems faced by basic grain producers and 
suggested cost-effective means for overcoming them. 

Methodology 

The effectiveness of technology is ultimately gauged by the increased efficiency or profit 
of farmers. However, a necessary intermediate step in that improvement is the actual adoption 



44 

of the technology, the simple yes or no decision of the farmer. Technologies exist that reduce 
costs and alleviate environmental strain, but often do not spillover into widespread use. 

Determining what influences the decision to adopt under various circumstances holds 
policy relevance. Education and extension budgets are limited. Identifying the characteristics 
of farmers that make them amenable to new technologies and the means by which those 
technologies can be taught will permit scarce rural education and extension funds to be invested 
more effectively. Evaluating adoption rates requires far less data dian evaluating actual 
production responses and may be conducted at early stages of extension and education programs 
to monitor the relative effectiveness of promotion techniques. 

A common procedure in technology adoption studies is to examine dichotomous adoption 
decisions as a function of factors related to the farm production system or the farmer's 
background. Most studies enumerate site visits to measure die impact of extension services 
(Birkhaeuser. Evenson and Feder, 1991). A few have attempted to directly identify the source 
of the farmer's knowledge regarding a technology (J.K.Harper, et al. 1990; Martin and Taylor 
1995). This study analyzes IPM adoption rates of HARCs as a function of human capital factors 
and different types of extension programs in which HARCs had agreed to participate. The link 
between extension and farmer contact is measured directly by the group extension method and 
thus need not be asked. 

Analyzing the decision to adopt or not adopt a given technology in a regression equation 
requires the specification of a binary dependent variable. Probit or logit models (Maddala 1983, 
Takeshi 1981). have been used extensively to investigate factors that influence technology 
adoption. The basic linear form of these models is given by: 



45 



(3.1) 



% = /3'Xi + e 



where 



= 1 if adopt 



4 



= 0 otherwise 



It follows that 
(3.2) 



Prob{3?i = 1) = Prob (e-, > -jS'xd 
= 1 - F(-/3'Xi) 



where F is the cumulative distribution function for e. 

The estimation procedure of the logistic function is maximum-likelihood because OLS 
yields biased estimates (Burrows 1983; Domenich and McFadden 1975). Several studies have 
employed logit regressions to examine technology adoption in agriculture in the United States 
(Schaible and Whittlesey 1991; Harper et-al. 1990; and Zepeda 1990) and a few in developing 
countries (Martin and Taylor 1995; Palanigounder 1989; Jamison and Lau, 1982). 

Two regressions are run. One for adoption prior to pest infestation, and one for adoption 
after infestation. Farmers were never asked directly whether or not they adopted a recommended 
technology. Rather, enumerators gave farmers open ended questions regarding pest management 
practices. A response was scored as a correct adoption if it corresponded to recommendations 
made in the extension program. Adoption practices were queried regarding six prevalent pests. 

Data and Model Specification 

Farm size, human capital, labor availability and land tenure are considered important 
characteristic variables that explain adoption rates (Feder et al. 1985). The following logit model 
includes three sets of variables which influence farmers' decisions to adopt new technologies. 
The first set (variables associated with parameters /3, to iS^) relates to the propensity to adopt 
technologies, the second set (variables on parameters 0j to /Sio) represents experience with 



46 



advanced inputs, and the third set (variables on parameters 0u to |S,4y relates to the mode of 



technology promotion employed by MIPH: 



{3.3)Adopt = /3o + I3,LT30 + I3.GT50 + ^^Primary + fi.Qass + ^^old + ^flousehold + 
^jParaiso + ^f,Seed + (3gHerbicide + ^iJnseaicide + ^.uFenilzer + ffi^Lecture 
+ iS^iPublication + jS^^Lecturepub + ^^^ctureaid + ji^f^Prevent 

Where: 



Adopt = 1 if farmer adopted the technology, 0 otherwise. 

LT30 = 1 if farmer's age less than 30, 0 otherwise 

GT50 - 1 if farmer's age greater than 50, 0 otherwis j. 

Primary = Number of years of primary schooling. 

Class = 1 if farmer attended literacy class, 0 otherwise. 

Sold = Proportion of output sold. 

Household = Number of household members. 

Parafso = 1 if producer is from the region of El Parafso , 0 otherwise. 

Seed — Years of experience with hybrid seeds 

Herbicide = Years of experience with herbicide 

Insecticide = Years of experience with insecticide 

Fertilizer = Years of experience with fertilizer 

Lecture = 1 if group received extension lectures without additional 
teaching aids, 0 otherwise 

Lectureaid = 1 if group received lectures accompanied by electronic visual 

aids, 0 otherwise 

Lecturepub — 1 if group received both lectures and printed extension 

publications, 0 otherwise 

Publication = 1 if group received printed extension publications and no 

personal lecture, 0 otherwise 



47 

Results 

The logit regression is displayed on Table 3.1. The model appears to "fit" the 
data well, correctly classified estimates (based on a fifty-fifty classification scheme) 
amounted to 93.46 percent and the model x^, which tests the overall significance of the 
model, is significant at the one percent level. 

The higher the proportion of output sold (Sold) shows a strong influence to adopt 
technology. Primary education has a positive influence {Primary), but not as strong as 
attendance at (literacy) Class. The Class coefficient could indicate more a personality 
type than a transformation in thinking to adopt new technologies; farmers amenable to 
becoming literate might be similarly amenable to adopting new production techniques. 
Class would thus represent a predisposition to new technologies than an actual change in 
thinking to adopt technology. The positive sign on Household supports the Boserup 
hypothesis in that as constraints tighten on production systems, more advanced methods 
are adopted. Farmers over the age of 50 seem less amenable to adopting new techniques 
than their younger compaileros . The regional variable Paratso had a positive influence 
on adoption, a result that could be attributed to better extension services or a more 
activist campesino union prominent in the region (ANACH). 

The only significant result among variables attempting to represent experience is 
shown on the coefficient of hybrid seed. One of the primary goals of MIPH was to help 
farmers with a history of pesticides misuse. Pesticides had been aggressively promoted 
by retailers and some government extension agents. IPM technologies, by virtue of their 
not relying solely on pesticide use, present additional obstacles to optimal technology 



48 

diffusion. Integrated pest management requires different modes of technology transfer 
than traditional pest prevention strategies because commercial pesticide p -omoters benefit 
from the latter and are often in conflict with the former(Agudelo and Kaimowitz 1991). 

In terms of extension methods, both Lecture and Lectureaid registered positive 
and significant influences on adoption. Bodi forms of extension provided personal 
contact, an important if expensive extension method demonstrated influential in Martin 
and Taylor (1995). Publication, which provided only printed materials is insignificant. 
However, it is somewhat perplexing in that Lecturpub, which also provided personal 
extension, is insignificant. 



49 

Table 3.1 IPM Adoption: Pre-infestation maximum likelihood estimaxs 



Variable 


Coefficient 


Std. Error 


Wald Statistic 


Significance 


Constant 


-3.437 


0.422 


66.239 


0 


LT30 


-0.320 


0.274 


1.3632 


0.243 


GT50 


-0.663 


0.246 


7.2979 


0.0069 


Primary Education 


0.089 


0.046 


3.6389 


0.0564 


Class 


0.4028 


0.1834 


4.8266 


0.028 


Sold 


0.542 


0.198 


7.4896 


0.0062 


Household 


0.057 


0.034 


2 912 


0.0879 


Parai'so 


0.374 


0.194 


3.7263 


0.0536 


Experience with: 










Seed 


0.127 


0.034 


14.2069 


0.0002 


Herbicide 


-0.069 


0.041 


2.8689 


0.0903 


Insecticide 


-0.0386 


0.0369 


1.0907 


0.2963 


Fertilizer 


-0.059 


0.037 


2.5177 


0.1126 


Type of extension: 










Lecture 


0.524 


0.249 


4.4292 


0.0353 


Lectureaid 


0.632 


0.262 


5.3276 


0.0158 


Leaurepub 


0.060 


0.282 


0.0452 


0.8317 


Publication 


-0.322 


0.291 


1.2242 


0.2685 



Chi-Square df Significance 

-2 Log Likelihood 1102.132 2432 1.000 

Model Chi-Square 80.088 15 .000 

Improvement 80.088 15 .000 

Goodness of Fit 2473.165 2432 .000 



Predicted 



Observed 


0 


1 


Percent Correct 


0 


2288 


0 


100.00% 


1 


160 


0 


0.00% 



Overall 



93.46% 



50 



Summary 

Technology adoption is a critical first step for increasing the efficiency of HARC 
production. Improving the diffusion of advanced technologies is becoming increasingly 
important in Central America as traditional slash and burn methods of production deplete the 
agricultural resource base which must serve to feed rising populations. 

IPM techniques offer a comprehensive "proxy" to examine technological packages 
because they incorporate various aspects of the production system. IPM techniques also offer a 
more precise means for examining the effectiveness of public extension programs because socially 
optimal remedies of IPM are often at odds with those that are commercially optimal. 

This chapter examined IPM technology adoption as a function of human resource factors. 
Three sets of influences were considered, extension type, experience with inputs, and the 
demographic factors that predispose producers to opt for new techniques. The model yielded 
notable insights. The proportion of output sold is positively correlated with the decision to adopt 
technology. Older farmers appear less likely to adopt, but literacy class and, to a lesser extent 
primary schooling, are shown to be positively correlated with adoption. Lectures, both alone and 
accompanied with visual aids positively influenced adoption. 



CHAPTER 4 
TECHNICAL AND ALLOCATIVE EFFICIENCY: 
COLLECTIVE VS INDIVIDUAL 



One of the most important economic policy issues facing restructuring and developing 
countries concerns the relative efficiency of collective and individual enterprises. Cooperatives'' 
theoretical potential has been superseded by the observed and dismal le-el of their failure. The 
term "collective" is rarely heard in the popular and business media without pejorative antecedents: 
"inefficient," "lethargic," "bureaucratic-heavy," etc.. Many of the economic problems of 
formerly communist countries and of poorly performing developing countries are attributed to 
the waste incurred by collective organizations. 

Inefficiency obviously exists in cooperatives, but its precise nature is unclear. Furubotn 
and Pejovich (1970) predicted that cooperatives would degenerate in a capitalist environment as 
workers/owners have relatively less incentive to make long-run capital investments. However, 
cooperatives in France, Italy, and parts of the former Yugoslavia have notable success records. 
And recent studies from Northern Italy (Bartlett, et al. 1992), and the former Yugoslavia (Boyd, 
1987; and Piesse, et al., 1996) suggest that cooperatives are more efficient than private 
enterprises. 



'There are several types of cooperatives. Some organize economic agents for specific 
mutually beneficial activities such as marketing or input purchases. Unless otherwise noted, the 
term cooperative in this dissertation refers to full production cooperatives in which resources are 
communally owned, labor is pooled in production and revenues are shared. 

51 



52 

Conventional wisdom attributes inefficiency of collectives to "shirking," or the abdication 
of personal work responsibilities. However, it is not clear whether shirking is most detrimental 
at the level of the worker or at the management level. 

Two articles laid the groundwork for the issue of shirking in labor-managed firms. 
Alchian and Demsetz (1972) concentrate on the worker level, contending that individuals of a 
collective enterprise lack adequate incentive to monitor coworkers because they do not receive 
the residual claim awarded to managers of private capitalist firms. Even if one member is 
appointed the task of monitoring, they argue, the monitor/manager has no authority to hire and 
fire, and has no incentive to efficiently utilize and maintain fixed capital because the individual 
portion of capital returns is less than the personal trade-off between labor and leisure. 
Alternatively, Jensen and Meckling (1979) submit that shirking inefficiencies are most 
problematic at the level of management. They consider it "naive" to believe that managers of 
collectives would take the same pains to "seek out high pay-off new proje;ts, to weed out projects 
which have negative pay-offs, to control waste and shirking, etc." without an addiuonal claim on 
returns. 

The distinction between worker shirking and management shirking is an important one. 
The alleviation of widespread worker shirking involves substantial monitoring costs and may be 
an exogenous social characteristic unresolvable by policy modifications. The success of the 
Israeli Kibbutz, for example, as well as Amish and Hutterite communities in the United States, 
is often attributed to pre-existing religious bonds that preclude labor shirking. Management 
inefficiencies, on the other hand, are more easily overcome through restructuring and incentive 
realignments. 

Different sources of shirking generate characteristically different inefficiencies. The 
selection of inputs is determined through management, but the actual input use is exercised by 



53 

workers. Suboptimal selection of inputs results in allocative inefficiem-y. However, any input 
combination can be used in a technically efficient manner, and is a function primarily of worker 
responsibility". 

If "net-shirking," shirking so extensive that it over-rides gains achieved by economies of 
size, occurs at the worker level as posited by Alchian and Demsetz (197',), technical efficiencies 
will be lower on collective systems than individual systems. Allocati\ e inefficiencies may be 
caused by two factors. Allocative inefficiencies could well be the result of management 
disincentives, as maintained by Jensen and Meckling (1979). However, allocative inefficiencies 
could also result from friction in input distribution systems, which are notably inefficient in 
Honduras. 

This chapter compares technical and allocative efficiencies of HARC individual and 
collective maize production systems. Most research on issues related to :ollective vs. individual 
production, beginning with Ward's "firm in lllyria" (1957) is theoretical in nature. Empirical 
studies are rare because data sets comparing collective and individual enterprises are lacking. 
A recent article by Carter, et al. (1996) examined Honduran agrarian re.brm cooperatives. The 
authors estimated a standard OLS production function regression which included a dummy 
variable on collectivity which suggested that collective organization had a positive effect on 
production. The same study showed that 90 percent of surveyed H \RC members did not 
consider shirking a problem. This chapter is intended to contribute to tiie empirical side of the 
discussion. 



^0 the extent that workers are not properly trained and motivated, technical inefficiency may 
also be attributed to management. However, in the case of HARCs, management makes no 
decisions regarding the training of workers. HARCs exist in large part to provide training to 
farmers who have demonstrated motivation through political activism. 



54 

The first section of this chapter reviews the theoretical underpinnings and statistical 
methodologies used to estimate and analyze efficiencies. The second section presents and 
discusses the statistical results. 

Productive Efficiency 

The terms productivity and efficiency are often used interchangeably, but subtle 
differences are noted in die contexts in which they are used and thus in their evolving definitions. 
Productivity is defined, in its simplest form, as output obtained per unit of input. Productivity 
measures are usually ratios of output to total or partial input. Such ratios are relative to each 
other and thus cannot comprehensively differentiate sources of productivity changes. Measures 
of total factor productivity (TFP), calculated as monetary values or as weighted combinations of 
physical inputs, fail to distinguish differences in technology as well as the effectiveness with 
which the technology is implemented. 

Efficiency measures, by contrast, are derived by measuring the variation in the 
input/output relationship to a technical maximum. That maximum is specified by a neo-classical 
production function and thus represents the maximum output or frontier 1 jvel of output attainable 
from a given set of inputs. The distance between the observed input/output relationship and the 
frontier production function reveals inefficiencies associated with any input combination. 

Frontier measurements of the observed technical maximum offer the most suitable vehicle 
for accomplishing objective three^ in Chapter One of this study and illuminating policy options. 
Productivity measures, because they are devoid of theoretical constructs and because they are 

'Objective #3 is: Compare the technical and allocative efficiencies of individual production 
systems vis ^ vis collective production systems. 



55 

often partial measures, do not offer adequate means to compare efficiencies across groups of 
producers. A farmer wiio owns one donicey may appear more efficient than one who owns ten 
even though the one-donkey owner has made gross overinvestments in machinery and equipment. 
Frontier productions, on the other hand, simultaneously encompass all inputs in a theoretical 
framework from which efficiency estimates may be derived. 

The inclusion of all relevant factors, including human capital and institutions, conceivably 
places everyone on the optimal frontier, rendering frontier and "average" functions 
indistinguishable (Miiller, 1974). However, production functions can be reliably estimated in 
terms of scarce material resources whose impact can be quantified and measured in marginal 
terms. Human capital and institutions, on the other hand, while important to the production 
process, do not lend themselves to precise evaluation for two reasons. First, they are a nebulous 
concepts that cannot be described by cardinal numbers. Years of schooling and courses 
completed yield exact numbers, but there is no way to calibrate the quantity and quality of 
knowledge that actually contributes to production. Institutions that govern resource use are 
important policy alternatives for improving the efficient use of scarce material resources, but are 
similarly incapable of numeric characterization. Second, there is no rigorous theory to guide 
analysis of the marginal relationships human capital and institutions hold with production. 

Frontier functions are, however, useful tools in determining how human capital 
investments and organizational alternatives directionally alter the efficient use of scarce resources. 
Thus inquiry can be made into the human capital attributes and institutional parameters of 
producers operating close to the frontier. Are they more educated? Does family background 
inspire greater efficiency? Are they better trained and experienced? What rules govern their 
actions? 



56 

Such information is useful to policy makers wanting to identify human resource 
investments and rules and regulations which have the highest payoff. Knowledge of human 
capital distinguishes human resource investments that enhance the "value of the ability to deal 
with disequilibria" (Schultz, 1975) caused by changes in technology. Similarly, organizational 
designs may be identified that contribute to the efficiency of over-all material resource use. 

Technical Efficiency 

The most widely used efficiency measures are rooted in the writings of Debreu (1951) 
and Farrell (1957). The Debreu-Farrell measure of technical efficiency is defined as the 
equiproportionate reduction of all inputs that produces a demonstrated optimal level of outputs. 
Conventionally, it is the ratio of observed output to optimal output for a given set of inputs. 
Thus, unity represents 100 percent efficiency and a fraction less than one indicates a measurable 
level of inefficiency. 

The conventional base within which efficiency is evaluated is the production technology. 
Technology establishes the limits at which inputs are capable of producing given levels of output. 
Let inputs x and outputs q be represented respectively by: 

X = (xi, X., X3,...xJ e R" 

q = (Qi, 02, q3,---qJ ^ R"- 

The input requirement set of the production technology is 
(4.1) l(q) = {x: (q, x) is attainable), 

which represents all combinations of inputs, efficient and inefficient capable of producing q„. 
R(q) is shown in Figure 4.1 as the shaded area. 




Figure 4.1 Input requirement set 



58 

The boundary set of inputs in Kq) shows the least amount of inputs necessary to produce with 
the current level of technology. Along the boundary, reduction in any input would reduce output 
or require additional use of a substitute input in x. The boundary set is defined by the isoquant 

(4.2) $(q) = {x: X e Itl(q) and Xx ^ R(q) if 0 < X < 1}, 

which excludes infeasible input combinations in R°. The concept of efficiency requires <l>(q) to 
be convex, or at least quasi-convex relationship, as efficient input combinations use as little of 
each X; as possible to produce q. 

The Debreu-Farrell measure of technical efficiency can be formally interpreted as 

(4.3) TE(q, x) = min{d\ Bx G a(q)} < 1." 

Optimum efficiency yields a technical efficiency measure of unity, which is identical to the 
isoquant 

(4.4) $(q) = {x: TE(q, x) = 1}. 

If one assumes only one product is produced, the production technology may be described 
using a production function, and its associated isoquants. A prjduction function is a 
mathematical form that relates the maximum possible output attainable from given quantities of 
a set of inputs. 

(4.5) q = q(x) = max{q: x € a(q)}. 

The Debreu-Farrell technical efficiency measure is expressed by the ratio 

(4.6) TE(q,x) = q/q(x). 

The observed level of output, q, cannot be greater than the maximum level of output q(x), 
delineated by the input-output combinations of the most efficient producer s. Clearly, then, TE(q, 



"The Debreu-Farrell technical efficiency measure is the inverse of the distance function 
(Shephard 1953, 1970) where 

D(q, X,) =max{e: {xld) G a(q) > 1}. 



59 

x) < 1 because the production function is a technological frontier that can be achieved, but not 
exceeded, by technically efficient producers. 

AUocative Efficiency 

Technical efficiency is derived solely from the input-output relationship; prices, and thus 
any notion of cost minimizing behavior, are absent. AUocative efficiency, defined as the optimal 
combination of inputs to produce a given level of output, is residually obtainable from cost- 
minimizing frontier. Given input prices associated with the input vector x 

(4.7) w = (w„w„W3,...wJ E R", 
and a cost minimizing frontier is represented by 

(4.8) c(q,w;T) = min,{w^x: I/TE(q,x;T) < 1} 

where t is a vector of parameters representing optimum technology. The ratio of the frontier cost 
function to the actual cost incurred yields a measure of economic efficiency (Farrell, 1957) 

(4.9) EE = c(q,w;T)/x\v^ 

where x'^ is the vector of actual inputs and is the price vector. AUocative efficiency is the 
ratio of economic efficiency to technical efficiency 

(4.10) AE = EE/TE = wV/TE(q,x)). 

AE < 1 as EE < 1 = TE*AE, economic efficiency can only be unity if full technical and 
allocative efficiency are achieved. 

Technical and allocative efficiencies are illustrated in Figure 4.2. 



60 




Figure 4.2 Farrell technical and allocative efficiency 



61 

The unit isoquant 1° represents a frontier production function utilizing inputs Xj and Xj. A 
technically efficient producer is represented by B, which lies on the production frontier. A 
producer operating at point B or any oUier point along the frontier cannot reduce any one input 
without either increasing another input or reducing the level of output. Point A, on the other 
hand, represents an inefficient producer, who utilizes more inputs than B to produce the same 
level of unit output. The producer at point A can reduce input use without any reduction in the 
unit level of output represented by 1°, The technical efficiency measure is then: 
(4.11) TE = II B II / II All ■\ 

Many producers, given differences in managerial and work skills, are likely to fall short of the 
technically efficient frontier. The amount by which a producer lies below the optimal production 
frontier can be regarded as a measure of inefficiency and may be accounted for by human capital 
and institutional differences. 

The Debreu-Farrell technical efficiency is a "radial" measure in that, if the isoquant is 
weakly convex, producers located on the portion of the isoquant where the slope is zero or 
infinite are considered technically efficient. The Debreu-Farrell definition of technical efficiency 
is thus not as restrictive as that proposed by Koopmans. Koopmans (1951) defined technical 
efficiency as the state where increasing one output requires a decrease in another output or an 
increase in at least one input; and the reduction of one input requires an increase in another input 
or results in reduced output. Clearly, more efficiency is attainable if reducing one input results 
in no reduction of output, a necessary condition for Koopmans, but rot for Debreu Farrell. 
However, while slack* may pose some problems for mathematical programming estimates, it 

'In vector notation || X || = (Sx;-)''^, vi. 

*"Slack" refers to the range of an isoquant which may have a slope of zero or infinity. In 
such a range, a producer may be considered technically efficient, even iiough he could reduce 
one input quantity an maintain the same level of output. 



62 

does not hamper econometric techniques because functional forms (e.g. Cobb-Douglas) preclude 
slack. 

The concept of allocative efficiency, a measure of cost minimizing performance, is 
depicted in Figure 4.2 as well. In order to minimize costs, production must be set at a level 
where the ratio of input prices equals the marginal rate of technical substitution, or point E on 
Figure 4.2. Allocative efficiency is measured by the distance separating the price line and the 
efficient isoquant: 

(4.12) AE = ||C||/||B|| . 

Allocatively efficient producers adjust input mixes where the marginal rate of technical 
substitution is equal to the price ratio. Producers can be technically efficient but allocatively 
inefficient. Allocative inefficiency may be a result of management deficiency or it may appear 
when input markets are distorted. Institutions are thus more important to allocative efficiency 
than to technical efficiency. Both technical and allocative efficiency approach unity as they 
achieve optimum or "frontier" efficiency. 

Two empirical methodologies have predominated Debreu-Farrell efficiency measurement, 
non-parametric frontiers and parametric (predominantly econometric'' frontiers. They are 
discussed in the following two sections. 

Nonparametric Frontiers 

Farrell's approach (1957) is considered non-parametric and deterministic because the 
convex hull of input-output ratios is constructed by mathematical programming techniques. 
Mathematical programming techniques obtain the convex hull of the input requirement set that 
represents the smallest input combinations for a given level of output. Data Envelopment 
Analysis, a management science and operations research approach originally proposed by 



63 

Charnes, Cooper and Rhodes (1978, 1981) and recently discussed in Seiford and Thrall (1990), 
dominate recent nonparametric applications. 

Data envelopment analysis (DEA) was originally proposed as a technique for evaluating 
the efficiency with which a group of operating units transforms inputs into outputs (Charnes, 
Cooper, & Rhodes, 1978). DEA has been applied primarily to public sector institutions where 
prices are absent or unreliable. Consequently, most DEA studies involve technical efficiency 
only, although allocative efficiency can be calculated given sufficient price data. 

DEA is formulated as a fractional linear program, continuing along the same math 
programming path initiated by Farrell. In concept, the procedure maps input-output data to find 
the subset of most efficient producers who comprise the frontier against which other producers 
are compared. The most efficient units in the group define a production function that is linear 
in a "piecewise" fashion. Input-output relationships are linear at each piece of the function 
between efficient units, although they are not necessarily linear across all efficient units. The 
function describes a hyperplane "efficient surface" equal in dimensions to the number of inputs 
and outputs. Input-output relationships for the remaining units are then evaluated relative to this 
efficient surface. DEA has always been an attractive alternative for measuring efficiency 
because it imposes no functional form on the data. 

The basic DEA approach is given by the specification of a transformation function T, 
restricted by constant returns to scale and strong disposability: 
(4.13) T = {(x,q):Xe<x, q<Qe, eeR^} 

where x is an nxl vector of inputs, q is an mxl vector of outputs and V denotes the number of 
producers. X is the nxk matrix of observed inputs and Q is the mxk matrix of observed outputs. 
The vector 0 serves as a measure of intensity for any activity (x;, q;). Technical efficiency 
measures for each producer i, are obtained by minimizing the ratio of xtual output to frontier 



64 

output subject to observed input/output relationships. They are calculated with mathematical 
programming techniques: 

(4.14) TE,(Xi,qi) = Min X. 

St: 

xe<x 

Qe>qA 

0eR% 

where \ represents the level of inefficiency of the ith producer. 

The program produces a scalar efficiency measure for each unit by selecting weights 0 
that maximize the ratio of a linear combination of the unit's outputs to a linear combination of 
its inputs. This efficiency measure is constrained so that the weights selected must be feasible 
and cannot result in an efficiency ratio greater than that observed for the most efficient unit in 
the group. 

Later developments have unencumbered Farrell's original programming approach from 
the assumptions of constant returns to scale (Banker, et.al., 1984) ana strong disposability of 
inputs and outputs (Fare, et.al., 1985, 1987). Nonparametric frontiers are advantageous in that 
they only require that the functional form of the technology be nondecreasing and concave. DEA 
methods are particularly useful in modeling operational processes that do not conform to standard 
market assumptions, such as in nonprofit firms or regulated industries. Nonparametric methods 
may also be used to test for cost minimization or profit maximization (Varian, 1984) and have 
demonstrated the potential for economies of scale that went undetected by econometric estimates 
(Banker et al., 1986). However, nonparametric efficiency measures are severely limited by the 
lack of statistical properties. Moreover, they attribute all measurement error to inefficiency, 
allowing nothing for random uncontrollable events, and by the same token are very sensitive to 
outliers. 



65 



Parametric Frontiers 

The predominance of parametric frontiers employ statistical methods to analyze the 
transformation of inputs into outputs. Prior to the emergence of frontier functions, the 
conventional model that was estimated took the form 

(4.15) q = q(x,T)-e 

where q(x,T) is the production function, q and x are vectors of outputs and inputs respectively, 
T represents technology and e is the random error. OLS necessarily assumes the expected value 
of the disturbance term, e, is zero because it estimates parameters of variables by minimizing the 
sum of the squared errors. However, neo-classical production theory defines the production 
function as the maximum output obtainable from a given set of inputs. In the absence of random 
error, e > 0 because observed levels of output cannot exceed the theor'3tical maximum. 

Aigner and Chu (1968) proposed a "parametric deterministic" procedure to calculate the 
frontier with mathematical programming techniques. They generalized a function with a one- 
sided error term which required all output levels to lie on or below the calculated frontier. 

(4.16) q < q(x;^) 

where j3 represents the frontier "estimates". The resulting linear programming function took the 
form: 



66 



R 

(4.17) '=1 

s.t. 

i 0 i = i,..,« 

p ^ 0. 



The quadratic formula is the square of the bracketed term of the objective function. The measure 
of inefficiency is given by the ratio of the actual level of output to the frontier level of output. 

Although the programming approach yields parameters, it precludes the testing of 
statistical confidence in that no standard errors can be computed. The estimation procedure also 
imposes a structure on the technology and is sensitive to outliers. 

Schmidt (1976) showed that OLS estimation of Aigner and Chu's formulation yields best 
linear unbiased estimates of the slope coefficients, but not of the intercept. He also showed that 
Aigner and Chu's linear programming estimates are maximum likelihood if the error is non- 
negative and has an exponential distribution 

(4.18) f^e) = -exp(-«/(p) tfiO 

<P 

where <p is the distributional mean and is the variance. A half-normal distribution of the 
(non-negative) error yields maximum likelihood estimates for the quadratic programming 
technique (Schmidt. 1976): 



67 



(4.19) fie)—^ejj>i-e'l2(^) 

However, Schmidt acknowledged that both maximum likelihood estimators violate the regularity 
conditions in that the range of the observed dependent variable is depeident on the parameters 
being estimated. 

A major advantage of estimating frontiers with econometric techniques is that they render 
statistical properties to efficiency measurements. Parametric frontie: estimations impose a 
structural form on the technology, but unlike nonparametric methods they provide statistical 
measures, account for uncontrollable shocks and are less vulnerable to outliers. Early parametric 
techniques (Schmidt, 1976; see also Fersund et al., 1980) yielded "full 'rontier" measures that, 
like nonparametric measures, attributed all deviations from the frontier to inefficiency (e ^ 0). 

Attributing all deviation from the frontier is unrealistic in that it does not account for 
random uncontrollable events beyond the purview of management. Tne "stochastic frontier" 
(Aigner Lovell and Schmidt. 1977; Battese and Corra, 1977; and Meeusen and van den Broeck, 
1977) allows for random deviation from the frontier owed to measurement error or events beyond 
the control of the producer. The error term of the production functiori (4.5) in the stochastic 
frontier is comprised of two components: 
(4.20) e = {V- u) 

where v has a symmetric distribution which captures random effects and exogenous shocks across 
firms; and the one-sided error, « > 0, captures technical efficiency of a firm relative to the 
stochastic frontier. Thus the estimated frontier accounts for stochastic characteristics that are 



68 

likely to aifect any production system, isolating systematic effects in the measurement of technical 
inefficiency. 

If u is assumed to have a half-normal distribution the associated log-likelihood function 

is 

(4-21) ^M,a,X) = -Mna-K + ^[lnT(-^)-^(^)^ 

where X = aja,, a- = a^-la,-, and is the cumulative distribution function of the standard 
normal distribution. As ^ <» , X ^ 0, systematic inefficiency increases relative to random 
inefficiency. 

Assuming m is exponentially distributed yields the likelihood function 
(4.22) _^ 

which is parametized in <p and a^. 

Although Aigner et al. (1977) characterized the variances of w and v within the residual 
e, they were not able to break the residual into its two components for each observation. 
Efficiency scores were calculated as averages for the entire sample where a„ = V{2/Tr). 
Decomposition of the variances for each observation, a distinguishing attribute of mathematical 
programming techniques, remained beyond the scope of statistically generated frontiers until 
Jondrow, Lovell. Materov and Schmidt (1982) derived the conditional distribution (M; | e). By 



69 

specifying a functional form for the distribution of u given the composed error term e, Jondrow 
et al. demonstrated that point estimates of efficiency are obtainable for each observation. The 
expressions for the expectation of u given e of the half-normal and exponential models are 

(4.23) EluM-^l-^^^^-^} and 

(4.24) £[„|,i = (e.-,a,^ + M^5^L:l^^ respectively. 

T[(«,-<Po^K 

These indirect measures of u are unbiased. However, they are not ccnsistent because with a 
mean truncated at zero, the variance of the coefficients can never be zeio. 

Stochastic frontiers have been used in LDC's to measure the effectiveness of credit 
programs (Ekanayake, 1987; and Taylor, Drummond and Gomez, 1986). Several studies 
examined extension programs (Kalirajin and Shand, 1985; Kalirajan, 1984; Kalirajan and Finn, 
1983; and Bravo-Ureta and Evenson. 1994) and education (Kalirajan, 1990; and Pinheiro, 1992). 
The stochastic frontier has also been used to identify firm and managerial characteristics that 
influence efficiency (Seale, 1990). 

Technical Efficiency vis ^ vis Technology Adoption 

A philosophical distinction needs to be made regarding technology in the empirical 
examination of technology adoption and technology in a production frontier. The previous 
chapter examined technology adoption and the factors that influence it. Certain IPM technologies 



70 

were identified as superior based on engineering designs and experiments. Technical efficiency 
is based theoretically on the same concept regarding input-output relationships. However, 
technical efficiency is examined based on the observed best practice among farmers in the 
sample. It is possible then that farmers appear to achieve optimum efficiency even though they 
did not employ the optimum possible technology because they use fewer of the inputs of 
suboptimal technologies. Graphically, the actual isoquant may lie between the best practice 
isoquant 1° and the origin in Figure 4.2. 

Most technical efficiency studies recognize that it is virtually imoossible to construct the 
technically efficient frontier from engineering knowledge. Even simple agricultural production 
systems are too complex. It was that insurmountable challenge that lead Michael Farrell (1957) 
to propose the construction of the isoquant based on the observations of best practice producers. 
The only assumption necessary in input-input space is convexity, which is virtually synonymous 
with efficiency. 

Technology adoption studies can assume recommended technologies are optimal because 
they focus on specific, comprehensible aspects of production. To the extent to which 
technologies are developed and recommended based on a broad assessment of all inputs available 
to producers, and the most efficient producers adopt those technologies, the observed frontier and 
the actual or potential frontier are identical. The MIPH program endeavored to design programs 
that both incorporate farmers' available inputs and to communicate them to farmers. The IPM 
technologies developed by MIPH are relatively more comprehensive than most in that they 
incorporate several production facets related to pest control. However, MIPH technologies 
carmot represent the entire gamut of possibilities available to farmers. 

In sum, the coefficients on technology adoption (3.3) and the coefficients on the frontier 
production functions in the following sections of this chapter have slightly different interpretations 



71 

with respect to technology. The former refers to available technology as determined by 
engineering studies related directly to the physical input-output relationship; the latter refers to 
an observed technological optimum as demonstrated by "best practice" producers. 

The HARC Stochastic Frontier 

Most problems associated with parametric frontiers concern the data to which the method 
is applied. Relevant variables concerning human capital and institutional characteristics are rarely 
available. When relevant variables are available, they often cannot be included in the estimations 
because they present degrees of freedom problems due to limited samples. 

Field surveying for this study was carried out in a manner designed to overcome these 
problems. Data were gathered on several aspects of HARC operations to expand the explanatory 
power of the models and sufficient observations were obtained to avoid problems with degrees 
of freedom. The stochastic frontier function thus appears to be the best suited for evaluating 
various aspects of HARC efficiency. 

Standard criticisms of technical efficiency methods (Milon, 1987) do not apply to HARCs 
or the environment in which they operate. Contractual relations, with the exception of internal 
labor contracts which are documented, do not vary across HARCs, unmarketed factor inputs are 
included in the analysis and the means and ends of the HARCs are arguably homogeneous. 
Externalities, while important to broader welfare considerations than considered here, would not 
likely have much of an influence on efficiency measurements because harmful inputs are not used 
nearly as extensively in HARC basic grain production as they are in developed countries. 

Data on collective and individual production systems were u^ed to estimate HARC 
frontier parameters for maize production. The Cobb-Douglas model is selected as the functional 
form for its convenient properties. The general form of the Cobb-Douglas is 



72 



k m n 

(4.25) q ' AY[x^'Y[h:'Y[c':'u 

i=l 1=1 j=l 



where q is a producer's output, A is a given level of technology which "shifts" the ftinction in 
response to technological changes, represents the set of i = l...n inputs and the fij's are the 
corresponding input coefficients. The standard production function estimates output q, solely as 
a function of physical inputs x^. However. Jensen and Meckling {\919^ suggested an extended 
form of the production function which recognized that production did not occur in a physical 
vacuum. Knowledge h, (human capital) and "organizational forms" O; also influence the level of 
output by their parameters and y-^ respectively. 

The Cobb-Douglas has several convenient properties. and 52/3,= 1 the form 

is concave. Thus, assuming the firm minimizes costs and factor supply and product demand 
functions are continuously differentiable on their domains, the input denand and output supply 
functions are continuously differentiable everywhere on their respective domains, a very useful 
property for interpreting results. The Cobb-Douglas is homogeneous and thus provides a means 
for examining returns to scale in that 52/3i= 1 characterizes constant reiurns to scale, 52/3; > 1, 
increasing returns to scale; and 52/3i< 1, decreasing returns to scale. However, the elasticity of 
substitution remains unity for all levels of output, weakening scale obser'ations. Most important 
for this study, the dual cost function, necessary for the calculation of allocative efficiencies, can 
be derived directly from the Cobb-Douglas production function. 

Although considered restrictive in some instances, the Cobb-Douglas was developed for 
and has been used extensively in agriculture in both developed and developing countries. 



73 

Moreover, functional form has been shown to have minimal impact on efficiency estimates (Kopp 
and Smith, 1980). 

The systematic element is seen in the right-hand side of 4.25 in that ^ represents one- 
sided efficiency disturbance : 

k m n 

(4.26) g = AH xf'H ^/'« " « ^^"^^ 

i=l j=l i=l 

and q* frontier output. The specific model estimated for maize production is: 



(4.27) InMaize = (3, + l3,\nLand + p.^nLabor + ^^\nSeed + ^^InFertilizer + 
^^XnHerbicide + jS^lnLandprep + ^jCollectiviry + ^^Paratso Region + 
PJLecture + ^.oPublicatio + ^.^Lectureaid + ^^Xecturepub + e 



where: 




Variable 


Coefficient 


Tecnology (A) 


Constant 


Land 


Land measured in manzanas* 


Labor 


Labor measured in work days 


Seed 


Seed measured in pounds 


Fertilizer 


Fertilizer measured in quintals 


Herbicide 


Herbicide measured in pounds 


Landprep 


Total cost of land preparation 


Collectivity 


Degree of collective work arrangements" 


Paraiso Region 


= 1 if producer is from the region of El Parafso, 0 




otherwise. 


Lecture 


- 1 if group received extension lectures without 




additional teaching aids, 0 otherwise 


Publication 


= 1 if group received printed extension publications and 




no personal lecture, 0 otherwise 



74 



Lectureaid = 1 if group received lectures accompanied by electronic 

visual aids, 0 otherwise 

Lecturepub = 1 if group received both lectures and printed extension 

publications, 0 otherwise 

'Manzana = 0.705 hectare 

"Parcels used completely in the collective mode are scored as one, those planted prior to jarcelization are scored as one 
half, and those for which the only collective activity land preparation are scored as one fourth. Completely individual 
production is registered as zero. 

is the constant term on the technology variable A in 4.24. Different levels of 
technology "shift" the function. Land, Labor, Seed, Fertilizer, Herbicide, and Land Preparation, 
represent continuous variable inputs and thus are in log form. 

Human capital and organizational form variables are included in the production function 
because they may have a direct impact (Battese, Coelli and Colby, 1989). All extension 
techniques are included in the model as dummy variables. The variabl j for the control group, 
which received no extension assistance, is necessarily excluded to avoid a singular matrix. 
Collectivity, the variable representing organizational form (Jensen and Meckling, 1979), is 
calibrated according to the point at which collective operations are yielded to the individual 
responsibility of each HARC member. In some HARCs land is prepared collectively, but 
planting and all subsequent cultivation is conducted individually. A few HARCs with large 
individual parcels do not partition land until planting and initial applications of fertilizer are 
completed. The Collectivity variable is included in the model for maize to provide additional 
means of examining the extent to which collectivization at various degrees influences production. 

Production functions are estimated with the maximum likelihood technique (equations 
4.20 and 4.21). The half-normal and exponential distributions are assumed for the one-sided 
error. The distinctive effect each distribution has on the frontier is not well known (Bauer, 
1990), but Greene (1990) suggests that there is not much difference between the two. Maximum 



75 



likelihood estimates and technical and allocative efficiencies were estimated using the LIMDEP 
software program. Technical efficiencies from 4.24, are: 



Allocative efficiency (4.10) is calculated by analytically deriving the dual cost frontier 
(Kopp and Diewert (1982) and Bravo-Ureta and Rieger (1991)) to obtain a measure of economic 
efficiency (4.9). It is not necessary to estimate the cost function as a regression equation. 
Rather, the coefficients from the production function are incorporated into the cost function which 
is a dual representation of the production function. 

Total cost is a function of input prices and output, the minimization of the costs of 
producing given levels of output. The cost function reveals all the economically relevant 
information about the technology (Shephard, 1970; Cornes, 1992). Varying price vectors reveal, 
through the assumptions of cost minimization and convexity, ranges of input mixes that are 
observed technically efficient. The dual cost frontier is: 



The cost function parameters a and m, are analytically derived directly from the estimated 
parameters of the production function (4.24) where: 



(4.26) 



TE 




(4.27) 



(4.28) 



, Jk=^[in..pf']-'". 



76 



Results 

Information on the study area and data are in Appendix I. The human capital survey is 
in Appendix II. Ordinary least squares (OLS) estimates are displayed on Table 4. 1 . Tables 4.2 
and 4.3 display maximum likelihood (ML) estimates of the stochastic frontier where half normal 
and exponential distributions are assumed for the truncated distribution component, (m). The 
Cobb-Douglas model fits the maize production data well. The of the OLS is 0.88. All but 
one of the standard physical input variables, herbicide, are significant at the 0.01 probability level 
for all three regressions. 

The value of X = aja, is 5.1 and significant at the 0.05 level. This suggests that 
relatively more of the variation in the model is attributed to random, not systematic influences. 
As X approaches infinity, the average and frontier functions converge 

Coefficients of the Cobb-Douglas production function represent output elasticities for each 
input. The average function indicates that a one percent increase in land, ceteris paribus, would 
generate a 0.46 percent increase in output. Frontier estimates indicate a similar increase in land 
would yield a 0.56 increase in output, 0.09 higher than the average. The coefficient on Seed is 
higher in the average function than in the frontier functions, though the difference is less notable. 
There appears no appreciable difference between average and frontier functions for the 
coefficients on Labor, Fertilizer, Herbicide, and Land Preparation. 

The variables Collectivity and Paraiso Region are positive and significant. The 
parameters on extension variables are inconsistent with the results of those estimated in the 
technology adoption model of the previous chapter. Lecture and Publication and Publication 
only, the only two extension variables that were not significant in the logit regression that 
measured technology adoption, are both positive and significant in the frontier function. 



77 



Table 4.1 

Average function: Maize 
ordinary least squares regression 



Variable 


Coefficient Std 


. Error 


t-ratic 


Prob|t| >x 


Constant 


2.295 


0.231 


9.938 


0.000 


Land 


0.464 


0.066 


7.028 


0.000 


Labor 


0.129 


0.039 


3.287 


0.001 


Seed 


0.175 


0.058 


3.010 


0.003 


Fei^ilizer 


0.035 


0.012 


2.839 


0.004 


Herbicide 


0.016 


0.007 


2.2.12 


0.026 


Land Preparation 


0.044 


0.017 


2.533 


0.011 


Collectivity 


0.112 


0.016 


6.900 


0.000 


Paraiso Region 


0. 151 


0.041 


3.691 


O.OUU 


Lecture 


0.052 


0.060 


0.861 


0.389 


Publication 


0.212 


0.069 


3.055 


0.002 


Lecture and Visual Aids 


0.039 


0.058 


0.672 


0.501 


Lecture and Publication 


0.171 


0.062 


2.756 


0.006 


Observations: 


405 








R-squared: 


0.877 


Adjusted R-squared: 


0.873 


F[ 12, 392]: 


233.246 








Log-likelihood: 


-153.314 


Restr.(fi 


= 0) Log-1- 


-577.919 


Amemiya Pr. Criter.: 


0.821 


Akaike Info.Crit.: 


0.133 



78 



Table 4.2 

Frontier function: Maize 
maximum lilcelihood estimates 
half normal distribution 



Variable 


Coefficient 


Std. Error 


t-ratio 


Prob|t| >x 


Constant 


2.806 


0. 194 




r\ AAA 


Land 


0.556 


0.052 


10.784 


A AAA 

0.000 


Labor 


0.122 


0.028 


4.317 


A AAA 

0.000 


Seed 


0.116 


0.043 


2.690 


A AAT 

0.007 


Fertilizer 


0.023 


0.009 


2.540 


A A 1 1 

0.01 1 


Herbicide 


0.011 


0.006 


1.693 


A AAA 

0.090 


Land Preparation 


0.049 


0.013 


3.738 


A AAA 

0.000 


Collectivity 


0.085 


0.014 


5.997 


A AAA 

0.000 


Paraiso Region 


0.099 


0.034 


2.872 


0.004 


Lecture 


0.020 


0.059 


0.336 


0.737 


Publication 


0.129 


0.062 


2.088 


0.037 


Lectureaid 


0.093 


0.054 


1.717 


0.086 


Lecture and Publications 


0.131 


0.059 


2.209 


0.027 




2.856 


4.057 


0.704 


0.481 


<ni/(Tv 


5.098 


2.400 


2.124 


0.034 


Va^v + ff^u 


1.031 


0.526 


1.961 


0.050 


Log-Likelihood: 


-117.0200 









Variance components: a^(v) = 0.03935 ff^(u) = 1.02273 



79 



Table 4.3 

Frontier function: Maize 
maximum lilcelihood estimates 
exponential distribution 



Variable 


Coefficient 


Std. Error 


t-ratio 


Prob|t| >x 


Constant 


2.800 


r\ 1 TO 

0. 176 




n (\c\t\ 
U.UUU 


Land 


0.559 


0.049 


11.360 


A AAA 
U.UUU 


Labor 


0.123 


0.027 


4.557 


A AAA 
U.UUU 


Seed 


0.115 


0.042 


1.151 


A AA/C 

U.UUo 


Fertilizer 


0.022 


0.009 


O CI 1 

2.511 


Ann 
U.Ulz 


Herbicide 


0.010 


0.006 


1 /;oo 
1.O50 


A AQ1 

u.uy 1 


Land Preparation 


0.050 


A A 1 '5 

0.013 


j.y^i 


A AAA 
U.UUU 


Collectivity 


0.086 


0.014 


6.258 


0.000 


Paraiso Region 


0.095 


0.033 


2.854 


0.004 


Lecture 


0.015 


0.056 


0.271 


0.787 


Publication 


0.125 


0.060 


2.039 


0.037 


Lecture and Visual Aids 


0.097 


0.053 


1.830 


0.067 


Lecture and Publication 


0.127 


0.057 


2.230 


0.026 


<P 


3.524 


0.280 


12.:'75 


0.000 


(TV 


0.198 


0.017 


11.547 


0.000 


Log-Likelihood: 

Variance components: a^(v) 


-114.7641 
= 0.03907 


a^(u) = 0.08053 







80 



It would be imprudent to argue that any of these dummy variable estimates represent 
precise measurements of the influence each bears on production. However, they do provide 
valuable directional indicators. Thus the absolute values are less relevant than the sign of the 
variables or relative extremities. 

Technical and AUocative Efficiencies 

Technical and allocative efficiency measures are presented in Tables 4.4 and 4.5. 
Collective efficiencies are the calculated efficiency measures for the collective parcel of each 
HARC, and individual parcel efficiencies are presented as averages for each HARC. The 
standard deviations of individual technical efficiency averages are less than a third of the average 
for all but two cases, suggesting that technical eftlciency does not vary substantially within 
HARCs. The uniformity of efficiencies within HARCs may be explained by the communication 
provided by cooperatives as they are in part established to facilitate communication across large 
numbers of farmers. Empirical evidence (Martin and Taylor, 1995) attests to the facilitating role 
cooperatives play in communication. It was also observed throughout the course of fieldwork 
that new inputs and new techniques were duplicated by other farmers within HARCs, in some 
cases reenforcing errors. 

The most salient feature regarding the efficiency measures is that individual parcels are 
no more efficient than collective parcels. In fact, efficiencies based on the half normal (Table 
4.4) and exponential (Table 4.5) distributions show that collective parcels are more technically 
efficient than individual parcels for 11 of the 16 HARCs that employed both modes of 
production. Thus one of the greatest theoretical arguments, and easily '^he most touted political 
arguments against collective forms of enterprise, shirking, shows no empirical basis. 



81 



Table 4.4 

Technical and allocative efficiencies 
for maize 
half normal truncated distribution 

Technical Efficiency Allocative Efficiency 

Unpaid Labor 
w=0 w=5 

HARC Individual Collective Individual Individual Collective 



Ideas en Marcha 


.80 




.37 


.42 






(.07)' 




(.10) 


(.10) 




El Boqueron 


.41 


.78 


.08 


.09 


.24 




(.16) 




(.09) 


(.09) 




Empalizada 


.71 


.87 


.30 


.32 


.32 




(.15) 




(.24) 


(.23) 




El Benque 


.71 




.18 


.22 






(.19) 




(.13) 


(.15) 




Los Bienvenidos 


.76 


.91 


.14 


.20 


.47 




(.13) 




(.11) 


(.09) 




El Esfuerzo 


.81 




.33 


.33 






(.06) 




(.05) 


(.05) 




Los Peregrinos 




77 


1 


.J J 


.jj 




(.08) 




(.12) 


(.10) 




Esquilinchuche 


.79 




.30 


.37 






(.19) 




(.20) 


(.20) 




San Nicolas 


.52 


.50 


.14 


.17 


.13 




(.55) 




(.18) 


(.23) 




Los Almendros 


.70 


.79 


.15 


.24 


.38 




(.10) 




(.11) 


(.07) 




La Esperanza 


.73 


.79 


.17 


.24 


.24 




(.14) 




(.13) 


(.12) 




Santa Cruz 


.77 




.28 


.37 






(.11) 




(.15) 


(.15) 




Cayo Blanco 


.75 


.84 


.10 


.12 


.25 




(.14) 




(.06) 


(.06) 




Zopilotepe 




.79 






.24 


Guaymuras 




.91 






.42 



Table 4.4 

Technical Efficiency 



HARC Individual Collective 



La Concepcion 


a 1 


Q1 




10 


46 




(. 10) 




c 1 n 


( OR) 




San Juan de Linaca 


.OJ 


on 
.yu 


. jj 








(.(JO) 






( \2) 




L,a rllZUnCd 


. / o 




24 


28 






( 09.) 






( 09) 




1 empiscapa 






20 


17 












C 08"> 




La rroviaencia 


.00 


.JO 






16 










( \6) 




19 de Abril 


.70 


.74 


.16 


1 o 

.18 


.26 




(.21) 




(.11) 


(.10) 




El Coyolar 


.86 


.32 


.37 


.36 


.05 




(.07) 




(.07) 


(.08) 




El Plomo 


.77 


.81 


.22 


.20 


.29 




(.14) 




(.12) 


(.07) 




Los Dos Naranjos 


.82 


.87 


.31 


.31 


.43 




(.06) 




(.05) 


(.06) 




Los Venecianos 


.76 




.21 


.22 






(.11) 




(.11) 


(.12) 




La Libertad 


.72 


.54 


.19 


.19 


.10 




(.15) 




(.12) 


(.11) 




Montanuelas 




.80 






.34 



82 

Ailocative Efficiency 

Unpaid Labor 
w=0 w=5 
Individual Individual Collective 



' Standard errors are in parentheses. 



83 



Table 4.5 



Technical and allocative efficiencies 
for maize 
exponential truncated distribution 



HARC 



Technical Efficiency 



Individual 



Collective 



Allocative Efficiency 
Unpaid Labor 
w=0 w=5 
Individual Individual Collective 



Ideas en Marcha 
El Boqueron 
Empalizada 
El Benque 
Los Bienvenidos 
El Esfuerzo 
Los Peregrinos 
Esquilinchuche 
San Nicolas 
Los Almendros 
La Esperanza 
Santa Cruz 
Cayo Blanco 
Zopilotepe 
Guaymuras 
La Concepcion 



.82 
(.06)' 

.41 
(.16) 

.72 
(.15) 

.72 
(.20) 

.77 

(.13) 

.82 
(.05) 

.79 
(.07) 

.80 
(.19) 

.52 
(.55) 

.71 
(.10) 

.74 
(.14) 

.79 
(.11) 

.76 
(.14) 



.82 
(.10) 



.79 
.87 

.91 

.78 

.51 
.80 
.79 

.84 
.80 
.91 
.92 



.46 
(.09) 

.11 
(.12) 

.37 
(.24) 

.23 
(.14) 

.17 
(.13) 

.41 
(.05) 

.39 
(.13) 

.34 
(.21) 

.15 
(.20) 

.20 
(.14) 

.22 
(.15) 

.34 

(.17) 
.12 
(.08) 



.52 

(.08) 

.12 
(.12) 

.40 
(.23) 

.27 
(.16) 

.25 

(.11) 
.41 

(.05) 

.45 
(.09) 

.42 
(.21) 

.18 
(.26) 

.32 
(.09) 

.31 
(.12) 

.45 
(.14) 

.14 
(.06) 



.31 
(.12) 



.37 
(.08) 



.31 
.38 

.51 

.46 

.18 
.48 
.32 

.31 
.31 
.46 
.51 



Table 4.5 84 

Technical Efficiency Ailocative Efficiency 

Unpaid Labor 
w=0 w=5 

HARC Individual Collective Individual Individual Collective 



San Juan de Linaca 


.86 


.91 


.38 


AC 


CQ 
.DO 








(.06) 




(.16) 


(.13) 




La Puzunca 


.80 




.30 


.35 






(.08) 




(.13) 


(.08) 




Tempiscapa 


.75 




.25 


.22 






(-12) 




(.10) 


(.08) 




La Providencia 


.69 


.56 


.24 


.29 


.23 




(.22) 




(.18) 


(.17) 




19 de Abril 


.71 


.76 


.20 


.23 


.36 




(.21) 




(.13) 


(.11) 




El Coyolar 


.87 


.32 


.44 


.43 


.06 




(.06) 




(.07) 


(.08) 




El Plomo 


.79 


.82 


.27 


.24 


.36 




(.14) 




(.13) 


(.07) 




Los Dos Naranjos 


.83 


.88 


.38 


.38 


.49 




(.05) 




(.05) 


(.05) 




Los Venecianos 


.78 




.28 


.27 






(.10) 




(.13) 


(.13) 




La Libertad 


.74 


.55 


.24 


.24 


.15 




(.14) 




(.14) 


(.12) 




Montaiiuelas 




.81 






.43 



' Standard errors are in parentheses 



85 



Two of the five remaining HARCs show individual parcels are only scarcely higher. 
Individual technical efficiencies for Los Peregrinos and San Nicholas (the only for which the 
standard error is higher than the average) exceed their collective measures by one and two points 
respectively. Differences are much greater in the remaining cases where collectives are more 
technically efficient; at least nine points for seven HARCs, two show five point differences and 
the remaining two HARCs register differences of four points. 

Allocative efficiencies are markedly lower than technical efficiencies for both collective 
and individual systems, and vary proportionately across HARCs with technical efficiencies. 
Curiously, allocative efficiencies increase for 16 of the HARC individual production systems, in 
both the half-normal and exponential distributions, when the standard wage of five lempiras is 
imputed for free labor.' The average allocative efficiency for the imputed wage is 0.05 greater 
than the same average when no wage is imputed, a difference that is significant at the .01 level 
of probability. Higher allocative efficiencies for the case of imputed wages suggests that there 
is an opportunity cost for labor on individual parcels vis k vis other opportunities available to 
farmers. If labor had been over-employed on individual parcels, allocative efficiencies would 
decrease when the standard wage is imputed. It would suggest that the shadow price of labor for 
HARC households is less than the average wage. 

This result is somewhat contrary to that of Nguyen and Martinez (1979), who found that 
productivity of the ejido sector in Mexico declines when the market wage is imputed for free 
labor. The difference here is that allocative efficiency is a more precise measure, reflecting 

'Since paid and hired labor was aggregated into one input, wage rates were calculated as total 
cost of labor divided by the amount of both free and hired labor. When all labor was free a 
nominal .01 value, .002% of the standard L5.00 wage rate, was imputed for all free labor as it 
would be mathematically impossible to calculate allocative efficiency with a zero value for any 
free input. It can be considered a minor opportunity cost. 



86 

optimum input mixes as opposed to monetary input-output relationships. It may be that HARC 
members have competing coop-related responsibilities or opportunities that preclude them from 
devoting free labor to individual parcels. Work outside the cooperative is limited in rural 
Honduras. 

Averages of technical and allocative efficiency differences between collective and 
individual systems for all HARCs and only those with mixed systems are displayed on Table 4.6. 

Table 4.6 Differences' in efficiency averages between collective and individual parcels 

Mixed* HARCs All HARCs 

Half Exp Half Exp 

Technical Efficiency 

Difference 0.00 -0.00 -0.02 -0.02 

(0.01)^ (0.06) (0.55) (0.66) 

Allocative Efficiency 
wage 0 

Difference 0.09 0.08 0.06 0.05 

(1.82**) (1.53*) (1.32*1 (1.03) 

wage = L5.00 

Difference 0.04 0.03 0.01 -0.00 
(0.86) (0.59) (0.19) (0.05) 

' Collective average less individual average 

^ Efficiency scores exclusively for HARCs that had both individual and collective or "mixed" production systems. 

' t statistics are in parentheses 

" Significant at the level of . 1 probability level. 

~ Significant at the level of .05 probability level. 



87 

There is, on average, no statistically significant difference in technical efficiency between 
collective and individual parcels. The only significant difference in mean efficiency scores occurs 
in allocative efficiency when free labor receives no direct remuneration. Collective parcels in 
this instance are more allocatively efficient. The significance is attributed to the low level of 
allocative efficiency when free labor is not imputed a wage. 

Summary 

The most significant result of this chapter is that collectivs parcels appear more 
technically and allocatively efficient than individual parcels. The chapter begins by reviewing 
the theoretical and empirical developments of the Debreu-Farrell efficiency measures. A frontier 
production function is estimated, rather than a conventional production function, because the 
former reveals the observed maximum that provides a benchmark against which efficiency can 
be measured. Three functions are estimated, an average OLS function and two maximum 
likelihood functions, one with a half-normal distribution and another with an exponential 
distribution. The estimated frontier function has a two component error that differentiates 
random (stochastic) error from systematic (inefficiency) error. 

The explanatory value of all three models is high. All but one of the coefficients of the 
average function are similar to those of the frontier functions. The land coefficient is higher in 
the frontier function than in the average function, suggesting that the most efficient producers 
obtain a higher return from land than most producers. Collectivization ';ontributes positively to 
production, as the collectivity variable is positive and significant. 

Technical efficiency is calculated based on the most efficient input-output relationship 
revealed by the frontier. Allocative efficiency, a measure of optimum resource allocation, is 
calculated based on input prices vis ^ vis the frontier. The results challenge conventional wisdom 



88 

in that collective producers appear to be more technically and allocatively efficient than individual 
producers. More important, the results indicate more precisely the nature of HARC failure. The 
main problem appears attributable more to managerial problems (Jensen and Meckling 1979) than 
to the popular notion of "shirking" (Alchian and Demsetz, 1972). 

Finally, individual producers are more allocatively efficient when a standard wage is 
imputed for free labor, indicating that there is an opportunity cost for labor devoted to individual 
parcels. Collective allocative efficiency is also significantly higher than allocative efficiency of 
individual producers when labor is imputed a standard wage - a significance that disappears when 
the wage is not imputed. 



CHAPTER 5 

TRADITIONAL AND ADVANCED TECHNOLOGY: 
A COMPARISON OF BEANS AND MAIZE 



Although maize is a crop rooted in ancient Central American tradition, and is even a 
central focus of the Mayan religion, technical aspects of maize production have been modified 
due to land constraints and accessibility of new technologies. Current production processes of 
maize are much different than those developed by indigenous civilizations. Machinery is used at 
various levels - tilling, seeding, spraying and, though not in harvesting, usually in shelling. 
Hybrid seeds, which require supplemental fertilizer and pesticide inputs, as well as advanced 
storage, are in routine use. Much of the input mix for corn production is directly dependent on 
input distribution systems, the malfunctioning of which can reduce allocative efficiency. 

Bean production, on the odier hand, still resembles the processes developed centuries ago 
and uses relatively few inputs. The principle inputs are land, labor and seeds, most of which are 
available within the family farm. Beans are usually planted in postrera vith a long wooden stick 
called a barreta between rows of drying corn plants. Corn stalks serve as poles on which bean 
vines can be strung to dry and to enhance photosynthesis. Bean production also restores nitrogen 
to the soil which is valuable for the next year's corn production. Bsyond being agronomic 
complements, maize and beans are nutritional complements. They supply more protein when 
consumed together than the sum of their individual protein contents. Maize and beans form the 
basic staples of the Honduran diet. 

This chapter presents production function estimates of beans parallel to those of maize 
in the previous chapter. Technical and allocative efficiencies for bean production are also 

89 



90 

presented. Unlike in the case of maize, beans are produced exclusively on individual parcels; 
no comparisons can be made with respect to collective production. 

The main purpose of this chapter is to compare the results of bean production efficiencies 
with those of maize to draw policy insights relevant to technology and input markets. It is 
hypoUiesized that technical efficiencies will be higher for beans than for maize because bean 
production technologies are more traditional relative to those of maize. It is further hypothesized 
diat allocative efficiencies will be higher for beans than for maize because bean production relies 
on fewer inputs that do not depend on input markets. 



Beans: A Traditional Crop 

The Cobb-Douglas form, which was used in the case of maize, is also used for beans. 
The general form of the Cobb-Douglas is: 

i=l i=l 



where q is output, A is a given level of technology which "shifts" the function in response to 
technological changes, x, represents the set of i = l...n inputs, h^ represents human capital and 
the fiiS and a|S are the corresponding coefficients. 

As in the case of maize, the Cobb-Douglas form is estimated usmg cross-sectional bean 
data (4.26). The simpler technology employed in bean production is reflected in the production 
function: 



91 



(5.2) InBeans = 

where: 
Variable 

Technology (A) 
Land 
Labor 
Seed 

Paraiso Region 
Lecture 
Publication 
Lectureaid 
Lecturepub 



/3„ + ^^inLand + ^.InLabor + ^^XnSeed + ^J^aralso Region + 
^^Lecture Only + ^J^ublication Only + ^jLecture and Visual Aids + 
ff^cture aiui Publication + e 



Coefficient 
Constant 

Land measured in manzanas' 
Labor measured in work days 
Seed measured in pounds 

= 1 if producer is from the region of El Parafso, 0 
otherwise. 

= 1 if group received extension lectures without 
additional teaching aids, 0 otherwise 

= 1 if group received printed extension publications and 
no personal lecture, 0 otherwise 

= 1 if group received lectures accompanied by electronic 
visual aids, 0 otherwise 

= 1 if group received both lectures and printed extension 
publications, 0 otherwise 

* Manzana = 0.705 hectares 

The variables for beans are similar to those for maize. ^„ is the constant term on the 
technology variable A in 5.2. Land, Labor and Seed represent continuous variable inputs and 
thus are in log form. All extension techniques are included in the model as dummy variables. 

Average and frontier functions are displayed on the following three tables (5.1 - 5.3). 
Coefficients on the physical inputs of land, labor and seed are positive and significant for average 
and frontier estimations. The difference between the frontier and the average functions is less 
apparent for beans than for maize; aja^. is insignificant. Bean cycles are unpredictable in 
Honduras, influenced significantly by drought and floods and hence much more encumbered by 
risk and uncertainty than maize. 



92 

A notable distinction between maize and bean functions appears in the relative magnitudes 
of the labor and land coeftlcients. The elasticity of labor with respect to output is much higher 
in the case of beans than that of land. Beans are grown in postrera when seasonal demands for 
coffee harvesting are high. The relatively high labor elasticity value may also be explained by 
the risky nature of bean production. Farmers expressed the challenges associated with growing 
beans brought on by erratic weather from one year to the next. The year the data were gathered, 
rainfall was considered fair-to-good. Risk-averse farmers may have sought alternative forms of 
employment because annual returns to labor in bean production have been, on average, much 
lower. 

The extension variables demonstrate the same pattern that emerged in the technology 
adoption logit regression in Chapter three. All the extension coefficients that involve personal 
contact are positive and significant at the five percent level for the average function. However, 
Publication is not significant in any regression, and Lecturepub is not significant in the frontier 
functions. These results are contrary to those in the case of maize. 

Technical and allocative efficiencies for beans are displayed on Table 5.4. All efficiency 
scores are given by HARC as averages of individual producers. 



93 



Table 5.1 



Average function: Beans 
ordinary least squares regression 



Variable 



Coefficient 



Std. Error t-ratio 



Prob 1 1 1 > X 



Constant 


-1.836 


0.410 


-4.473 


0.000 


Land 


0.165 


0.085 


1.935 


0.053 


Labor 


0.624 


0.083 


7.476 


0.000 


Seed 


0.239 


0.092 


2.586 


0.010 


Lecture 


0.544 


0.110 


4.947 


0.000 


Publication 


0.238 


0.132 


1.802 


0.072 


Lecturepub 


0.229 


0.110 


2.093 


0.036 


Lectureaid 


0.457 


0.088 


5.211 


0.000 


Paraiso Region 


-0. 142 


0.090 


-1.582 


0.114 



Observations: 
R-squared: 
F[ 8, 169]: 
Log-likelihood: 
Amemiya Pr. Criter. 



178 

0.642 Adjusted R-squared: 
37.830 

-103.018 Restr.(fl=0) Log-1: 

1.259 Akaike Info.Crit.: 



0.625 

-194.359 
0.206 



94 



Table 5.2 Frontier function: Beans 

maximum likelihood estimates 
half normal distribution 



Variable 


Coefficient 


Std. Error 


t-ratio 


Probit! >x 


Constant 


-L331 


U.Oo4 




U.UjZ 


Land 


0.190 


n f\oo 

O.Ooo 


o 1 *n 
Z.lT) 1 


n (Yx 1 


Labor 


0.616 


0.079 


n non 

l.lol 


n C\C\C\ 

u.uuu 


Seed 


0.226 


0.100 


2.250 


0.024 


Lecture 


0.493 


0.123 


4.013 


0.000 


Publication 


0.175 


0.174 


1.007 


0.314 


Lecturepub 


0.181 


0.106 


1.708 


0.088 


Lectureaid 


0.429 


0.083 


5.157 


0.000 


Paraiso Region 


-0.149 


0.091 


-1.638 


0.101 




-0.253 


4.687 


-0.054 


0.957 


OU/ffV 


1.276 


0.980 


1.302 


0.193 


V ff^v + a^u 


0.534 


0.398 


1.343 


0.179 


Log-Likelihood: 
Variance components: 


-101.8082 
(t2(v) = 0.10864 ff2(u) 


= 0.17695 







Table 5.3 



Frontier function: Beans 
maximum likelihood estimates 
exponential distribution 



Variable Coefficient Std. Error t-ratio Prob 1 1 1 > x 





-1.452 


0.403 


-3.601 


0.000 


Land 


0.188 


0.087 


2.160 


0.031 


Labor 


0.613 


0.078 


7.834 


0.000 


Seed 


0.224 


0.098 


2.291 


0.022 


Lecture 


0.503 


0.120 


4.189 


0.000 


Publication 


0.174 


0.162 


1.075 


0.282 


Lecturepub 


0.187 


0.105 


1.7V8 


0.075 


Lectureaid 


0.431 


0.082 


5.2^-5 


0.000 


Paraiso Region 


-0.139 


0.089 


-1.573 


0.116 


<P 


4.065 


1.688 


2.4C8 


0.016 


crv 


0.359 


0.048 


7.491 


0.000 



Log-Likelihood: -102.4021 

Variance components: a^{v) = 0.12893 o^{u) = 0.06052 



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98 

General Efficiency Comparisons: Maize and Beans 

Table 5.5 shows the difference in means for allocative efficiency between a near zero 
wage for unpaid labor and an imputed standard wage for unpaid labor. As in the case of maize, 
imputing a wage for unpaid labor increases allocative efficiency for bean farmers. The difference 
in group means is statistically significant at the .01 level of probability. 

Table 5.5 

Differences in allocative efficiency between an imputed standard wage and zero wage for 

unpaid labor 



Half-normal Exponential 



Maize 



Difference 0.04 0.05 

(9.54)'*** (9.88)- 

Beans 

Difference 0.08 0.05 
(6.85)'" (4.89)- 

' t statistics are in parenthesis 
"Significant at the .01 probability level 



99 

Contrary to maize, allocative efficiencies for beans are statistically and significantly 
higher than technical efficiencies at the .01 level of probability (Table 5.6). Allocative 
efficiencies are understandably lower than technical efficiencies in the case of maize because input 
distribution systems are notably inefficient. Allocative efficiency may be easier to achieve for 
low input, traditional farming because it requires the same production-mix decisions that have 
been made for centuries and throughout a farmer's life. Technical efficiency, on the other hand, 
may vary in conjunction with a farmer's health or age. 

Table 5.6 

Average Technical and Allocative Efficiencies for Maize and Beans 



Maize Beans 

Technical Efficiency 

Half-Normal .76 .67 

(.15y (.12) 

Exponential -77 .79 

(.15) (.10) 

Allocative Efficiency w 0 

Half-Normal .24 .89 

(.14) (.15) 

Exponential .30 .87 

(.16) (.13) 

Allocative Efficiency w = 5 

Half-Normal .28 .97 

(.14) (.04) 

Exponential .35 .92 
U5) C05) 



Numbers in parentheses are standard deviations 



100 

In general, technical efficiencies are comparable to those of maize, lower for the half- 
normal but higher for the exponential distribution start (Table 5.7). The markedly low technical 
efficiency for beans calculated from the frontier of the half-normal distribution is difficult to 
interpret. It is statistically significantly different from the technical efficiencies for maize. 
However, it is also statistically significantly different from the technical efficiency for beans 
calculated from the half-normal distribution. 

The most notable result is that allocative efficiencies are strikingly higher for beans than 
for maize. The difference between maize and beans in this regard may be attributed to 
differences in the number and accessibility of inputs used in the production process. Maize 
production depends on hybrid seeds, fertilizer, and pesticides that are not always available in the 
market. Bean production, on the other hand, primarily employs land labor and seeds, all inputs 
available to households that do not depend on input markets. This underscores the importance 
of ensuring that inputs are available to farmers as they are encouraged to adopt more advanced 
technologies. 

Variation in efficiency is less pronounced in bean production than in maize production. 
Table 5.6 shows coefficients of variation (CV)^ for maize and bean production. CVs are less 
in bean production for all variables, but are notably less for allocative efficiency. This is 
attributed to the simple and traditional technology employed in bean production relative to maize. 
Most farmers, regardless of age or strength, are cognizant of optimum input mixes in bean 
production and have access to necessary inputs. Maize technology is more advanced and depends 
on inputs that are not universally accessible. The variation drops for both crops when the 
standard wage of five lempiras is imputed, suggesting that producers are accounting for the 
opportunity cost of free labor (i.e. all are relatively closer to the optimum). 



'The coefficient of variation is the standard deviation as a percentage of the mean. 



Table 5.7 Coefficients of variation 





Maize 


Beans 


Technical efficiency 






Half normal 


19.74 


17.91 


Exponential 


19.48 


12.66 


Allocative efficiency w = 0 






Half normal 


58.33 


16.85 


Exponential 


53.33 


14.94 


Allocative efficiency \v = 5 






Half normal 


50.00 


4.12 


Exponential 


42.86 


5.43 



102 

Summary 

This chapter estimated frontier production functions for individu?J bean parcels of HARC 
members exactly as in the case of maize. An average OLS function and maximum likelihood 
functions which assumed half-normal and exponential distributions for the truncated error term, 
u, were estimated. Technical and allocative efficiencies were calculated based on the optimum 
input-output relationship observed from the estimated stochastic frontier. 

The most notable observation results from the comparison of maize and bean efficiency 
measures. Technical efficiencies of bean farmers are comparable to those of maize, but allocative 
efficiencies are strikingly higher than maize allocative efficiencies. Unlike in the case of maize, 
allocative efficiencies of beans are higher than bean technical efficiencies. Moreover, there is 
less variation in bean allocative efficiencies - especially when the standard wage is imputed. 

The contrasts between maize and bean production may be explained by the fact that bean 
production involves a simpler, traditional technology for which inputs are fewer in number and 
more readily available than maize production. Allocative efficiencies for beans are 
understandably higher because the primary inputs of beans, labor, land and seeds, are easily 
obtained by HARC households. Allocative efficiencies are also subject to less variation because 
traditional technologies depend on knowledge learned early in a farmer's life and, unlike technical 
efficiencies, are less dependent on physical or mental stamina. The low and variable allocative 
efficiency scores for maize underscore the importance of establishing efficient input distribution 
systems. 



CHAPTER 6 
THE INFLUENCE OF 
HUMAN AND SOCIAL CAPITAL 
ON TECHNICAL AND ALLOCATIVE EFFICIENCY 

Introduction 

The development of modern technologies necessitates continuous investments in human 
and social capital so that workers and enterprises can properly employ new production techniques. 
The mere adoption of new technologies (examined in Chapter 3) does not ensure that potential 
efficiency will be attained. The optimum investment mix in human and social capital maximizes 
the technical and allocative efficiencies presented in the previous two chapters. HARCs provide 
efficient structures through which investments can be made in the mental, physical and social 
capacity of H ARC members. 

Among of the main objectives behind the establishment of HARCs are the education and 
social integration of campesinos who historically have been socially and politically 
disenfranchised from die educated and economically dominant ruling clais. Human capital, and 
more recently social capital, are recognized in mainstream economic analysis as integral 
components to optimally operating economies. Cooperatives are often the first form of secular 
organization to which campesinos, who are strongly independent and often distrusting, belong. 
Cooperatives serve as a means through which extension beneficiaries can be concentrated and 
hence magnify the impact of extension efforts. Perhaps more imponant, evidence indicates 
(Martin and Taylor, 1995) that cooperatives reenforce extension efforts through members' 
learning from each other. The importance of human and social capital to HARCs' broad social 

103 



104 

mission is obvious, but beyond tlie scope of this dissertation. The purpose of this chapter is to 
focus on how human and social capital influence the efficiency of HARC production. 

Theoretical Underpinnings of Human Capital 

Almost all the classical economists recognized the general value of human capital to 
society. Adam Smith acknowledged in "The Wealth of Nations" that improvements in the skill, 
dexterity and judgement of workers were fundamental to economic progress and increasing 
economic welfare. However, the theory of human capital was merely suggested and not 
developed in any meaningful sense by the classical economists. 

The concept of human capital appeared sporadically throughout this century'. But the 
theory of human capital was not established, according to Blaug (1976), until it was given special 
precedence in a 1962 supplemental volume of the Journal of Political Economy. Gary Becker 
published an article which served as an analytical structure for much later work in human capital. 
The issue included an article by Theodore Schultz, who argued that laborers actually operate as 
capitalists, investing in knowledge and skills that yield commensurate returns in the labor market. 
He expanded the theoretical framework, suggesting human capital be broadened to include not 
just men or improved factors, but the economic productivity of education. Concurring with the 
findings of Edward Dennison (1962), Schultz offered human capital theory as an explanation for 
the large residuals or "technical change" that resulted from economic growth. A seminal article 
by Jacob Mincer, which recognized that learning occurs in both schooling and on-the-job training, 
was also published in this same issue. 



'See, for example, Marshall (1920), Dublin and Lotka (1930), J.R. Walsh (1935) and 
Friedman and Kuznets (1945). 



105 

Human capital research diverged onto two complementary paths. The first focused on 
the relation between human capital and earnings distribution-. The second provided a theoretical 
groundwork for human capital which could identify the sources of productivity and growth 
(Griliches. 1964; T.W. Schuitz, 1963). It has been the orientation of human capital studies in 
LDC's and is the focus of this chapter. 

Human capital investments generate returns to personal utility that are not reflected in 
enhanced productivity or increased earnings. A good liberal arts education, for example, not 
only prepares people to compete and communicate more effectively in industry, it augments their 
capacity to appreciate and discriminate between a broader range of consumption items. Healthy, 
educated people have stronger physical senses and mental faculties to sense and esteem the 
aesthetic aspects of goods and services. Increases in utility resulting from human capital 
investments are unaccounted in many human capital studies, rendering empirical estimates of 
human capital benefits based solely on earnings or productivity artificially low. 

Empirical Applications of Human Capital Components 

The theoretical bases of how human capital affects productivity is intuitive. Empirically, 
however, it is difficult to identify adequate measures which represent tne authentic underlying 
factors. Years of schooling is easily measured, but education is not. Extension and health 
improve productivity, but both are related to several other factors that cloud measurement. 
Empirical measures thus provide no reliable precise elasticities but they do often provide valuable 
directional results against which the theory may be examined. 

Knowledge is by far the most important and conventional human capital factor. People 
acquire and store knowledge through various forms of mental activity. Workers may approach 

'See Mincer (1958); Becker and Chiswick (1966); and Blaug (1976). 



106 

a task equipped with formal education, parental and peer guidance, specific training, and 
experience. It is virtually impossible to sort out all the factors that influence the knowledge base 
of any individual, much less the aggregate. In order to facilitate empirical testing, knowledge 
is considered to emanate from three identifiable factors: education, training and experience. Two 
other human capital factors not directly associated with knowledge, healti and religion, will also 
be considered. All five factors, by nature of their being imbedded in each human being, 
simultaneously influence each other. 

Education 

General education refers to basic schooling in the "three R's. " Distinct from the learning 
acquired through job training and work experience, education expands mental capacity and 
indirectly contributes to the capital stock of laborers, managers and entrepreneurs (Sheffield, 
1975). Education enhances the cognitive ability of workers and dei;ision makers to better 
understand and cope with complex relations that underlie production processes. 

Often considered as a useful precursor to direct job training, general education imbues 
the human input factor with critical thinking capacity; heightening the- productivity of direct 
training and work experience. Simple skills such as literacy and numeracy are essential to any 
training program, but even more advanced education in the arts and sciences are generally 
considered useful to communication and decision making. Farmers better employ advanced 
technologies if they understand fundamental principles upon which those technologies are 
developed. 

In a continuously modernizing economy, where agricultural research alters production 
techniques and non-farm firms provide inputs or input substitutes previously produced locally, 
education becomes increasingly important to capacitate farmers to efficiently exploit new 



107 

technologies and opportunities. Furthermore, sufficient time is rarely if ever available to 
reallocate resources so that a new level of equilibrium is reached. Production environments 
change so rapidly that new changes occur before the old ones can be fiilly adopted. Thus, the 
equilibrated "full efficiency" state achieved in traditional agriculture (Schultz, 1964) almost 
always lies beyond the reach of farm people, emphasizing the need to augment the cognitive 
ability to deal with disequilibria. Empirical evidence of Schultz and others corroborates the link 
between education and productivity.' 

Virtually ail human capital studies measure education in terms of schooling. The 
assumption is necessarily made, usually implicitly, that education is homogeneous. This may be 
reasonable for education within regions, but it is less so for studies which cross regional, and 
especially cultural, boundaries. A further problem is that non-measurable factors closely 
correlated with education may be the root cause of efficiency improvements, but remain 
unrecognized by models which cannot include them. For example, better educated farmers are 
more likely to have greater exposure to the evolving social and economic apparatuses of the 
developed sector than poorly educated farmers, an exposure that could bear a stronger influence 
on productivity than education. Learning that occurs at home or in collective work arrangements 
and innate ability are likewise unaccounted for. "Screening" is another problem associated with 
analyzing the economic effects of education. Are individuals hired for better paying jobs because 
their education has made them more productive, or does their degree act as a bogus signal of 
productivity to employers? Fortunately, members of Honduran agrarian reform cooperatives 
arguably form a homogeneous group with respect to education, social networking and outside 
opportunities. 



' See Jamison and Lau (1982) for a good review. See also Khaldi (1975); Pudasaini (1983); 
T.W. Schultz (1964); Wu (1977); Huffman (1974); Jamison and Lockheed (1987); Kalirajan and 
Shand (1985); and Behrman and Wolf, (1984). 



108 



Training and experience 

Training and woric experience, apart from education, are imporant means of improving 
the broadly defined human capital component of knowledge. Several studies have examined the 
impact of training on productivity. Recent studies, especially from developed countries suggest 
a high pay-off from worker training.* 

Substitutability of training programs with general education is a poorly understood but 
important relationship, given the relative low cost of training programs. Huffman (1977) and 
Jamison and Lau (1982) report evidence which suggests that education can be substituted for 
training or extension. However, complementarity between education aid training may also be 
observed if the effectiveness of various extension and training methods were examined for 
farmers of differing educational levels. 

Agricultural training in LDC's is usually designed to complement farmers' paucity of 
knowledge. The benefit of general education may not materialize in training programs because 
those programs were designed for uneducated farmers. Depth of i.istruction and training 
materials may be unnecessarily uniform and cost ineffective because programs are designed to 
reach all farmers. The question arises, is it possible to target farmers by demographic 
characteristics in order to optimize productivity through training? It would be interesting to 
examine die effects of a variety of training programs across farmers of varying educational levels, 
although no such empirical studies have been done. 

The data set gathered for this study includes both variables needed to advance this 
research, years of schooling and a variety of extension techniques. The Integrated Pest 

^For developing countries see Jamison and Lau (1982); Shapiro and Miiller (1977); Behrman 
et al. (1985); and Kalirajan and Shand (1985). For developed countries see Mincer (1989); and 
Vaughan (1989). 



109 

Management Program of Honduras (Spanish acronym MIPH) offered one of four different types 
of extension assistance to each HARC in the study. One HARC received lectures only, one 
lectures and publications, one lectures accompanied by electronic visual aids, and one group of 
HARCs received IPM publications without lectures. If education enhances extension it may be 
detected through the influence of varying extension types on different educational levels. 

Health 

Health is perhaps the most important human capital factor which influences productivity 
both directly and, through its effect on education, indirectly. Malnourished laborers do not have 
the caloric fuel necessary for much of the heavy work of traditional agricultural. Moreover, 
malnourishment and lack of sanitation make people more vulnerable tc disease, which in turn 
lowers productivity and the subsistence output on which many depend. The cycle is self- 
perpetuating. 

A theoretical link between health and productivity was formulated in Liebenstein's 
efficiency wage hypothesis (1957). The essence of this hypothesis is that, under certain 
circumstances which pertain to LDC's, increasing food consumption improves productivity. 
Starting at a level of daily energy intake that merely covers basal metabolism, productivity 
increases at an increasing rate, implying that very low wages induce labor deficits because caloric 
intake is so low. 

Empirically, there are many problems in measuring the effect of nutrition on productivity 
or work performance. Specialists disagree on what constitutes the necessary level of consumption 
because individual metabolisms vary. There is also a problem in measuring the energy required 
to carry out certain tasks. In LDC's, work is frequently seasonal and can vary a great deal in 
intensity. There are also lags in noticing the result of nutritional investments. Severely 



110 

malnourished people would show dramatic improvement almost immediately, but less 
undernourished people who may benefit from increasing the protein or vitamin content of their 
diet show positive results at a slower rate. The most serious malnutrition problems occur among 
people who become physically limited for life because of early childhood malnutrition. For these 
and other reasons, empirical studies conducted thus far have yielded little proof to support 
Liebenstein's theory.' Most assumed measures of current physical stature, such as height and 
weight or limb circumference, reflect nutritional background.* 

Religion 

Economics is fundamentally agnostic. Neoclassical theory goes to great lengths to avoid 
interjecting even minor personal biases into its analyses. Religion is largely absent from 
economic, or even human capital, theory. Nonetheless, religion plays an integral role in human 
capital development and has been the focus of recent research. Religion enhances the explanatory 
power of earnings variation models formerly constrained to differences in race and sex. Religion 
bears strong influence on family values, skills, endowments, goals and culture, which in turn are 
determinants of earnings and productivity. 

Tomes (1985) distinguishes "religious capital" from human capital in that it includes 
"ethical and moral codes of behavior governing consumption, the allocation of time and 
interpersonal relationships." He considers religious capital to be a vital foundation for the 
standard human capital factors which contribute to productivity and earnings power. Most 



' Bliss and Stern (1978); Immink et al. (1982); Behrman et al. (1985); and Audibert (1985). 
*Immink et al. (1982); Mook and Leslie, (1986); and Jamison, (1986) 



Ill 

empirical studies regarding religion have examined how religion influences earnings differentials 
and fertility.' 

Little dieoretical or empirical research has been conducted on religious capital in LDC's. 
Religion played a crucial role in the history of Honduras. The CaAolic Church, still the 
predominant religious organization, underwent dramatic theological changes in the early 1960s 
that have forced a reassessment of the traditional social structures the Church helped establish in 
Latin America. "Liberation theology" holds that wealth should be shared more equitably, 
particularly when extremes of wealth and poverty exist. The church encouraged people to form 
"base communities" and delegated more responsibility to them to practice their faith. Calling for 
wealth redistribution and encouraging small community enterprises obviously has special 
relevance for agrarian reform cooperatives. A number of Protestant "Evangelical" churches have 
also grown in Central America over the last 20 years. They espouse no unified theology, but 
generally hold that people should bare sufferings of this world for greater contentment in the 
afterlife. Unlike liberation theology, Evangelical churches take few political stands, but they do 
discourage drinking that in excess dampers productivity. 

Social Capital 

The term "social capital" has had various meanings throughout recent history and across 
regions. In communist societies, social capital referred to communally owned plant and 
equipment. Social capital has also been considered natural resources upon which future 
generations depend (Toman 1994), as public housing (Spence, 1993), o: as the employment of 
unproductive labor as an overhead cost (Smith, 1993). 



'See Brenner and Kiefer (1981); Becker and Tomes (1976, 1983 and 1984); Chiswick (1983); 
and Meng and Sentance (1984). 



112 

A growing body of literature in sociology and political science is examining various 
aspects of what is broadly considered "social capital." The concept, as measured by civic 
involvement and satisfaction with government, has special relevance for cooperatives. Putnam 
(1993) attributes higher incomes in northern Italy, which also has a successful record of 
cooperative development, to a higher level of social capital. Social strictures in northern Italy 
are more "horizontal" than in southern Italy, which maintains a preference for hierarchical 
system. Helliwell and Putnam (1995) further fmd that social capital has a positive influence on 
equilibrating income levels and on the rate of percapita income convergence. These results have 
important implications for HARCs. which hold increases in, and the eqi.ilibration of, income as 
fundamental goals. 

HARCs are prominent instruments for the Honduran government in making the same 
attempt Italy made, namely to transfer technology and make physical and human capital 
investments in predominantly rural areas. Social capital is worthy of examination to the extent 
that it is complementary to conventional forms of investment. Cable and Fitzroy (1980) consider 
social interaction a neglected area of study in labor managed firms. The lack of incentives that 
property rights theory (Furubotn and Pejovich, 1972) and internal organization theory (Alchian 
and Demsetz, 1972) contend characterizes cooperatives fails to take into account social dynamics 
that may overcome individual incentive problems. This chapter examines social capital through 
interaction between religion, games and music as demonstrated by mcreases technical and 
allocative efficiency. 



113 

Em pirical Model and Data 

The tables below display differences in mean efficiencies for HARC members grouped 
by several demographic categories. Corresponding t statistics evaluating the significance of the 
means differences are presented below each difference. The t test is: 



X, - Xj 

(6.1) t = -i 



where X; represents the mean efficiency estimate of group i, and 



(6.2) 



^ 



where n^ is the number of observations for group i and S'i is the sample variance of group i. If 
t > t„.ni +n2-2 there is a "significant" difference between the groups. In other words, there is 
less than an a percent chance that a positive difference between the means is attributed to 
sampling variability rather than to a difference in population means. 

Tables 6. 1 - 6.5 and 6.6 - 6. 10 below display the differences in means for various groups 
of maize and bean farmers respectively. Many of the variables fall into one of two mutually 
exclusive categories (e.g. a respondent was either literate or not). For order categorical 
variables, comparisons were made for groups above and below the average (e.g. efficiency scores 
were compared for the group that had more than the average number cf school years with the 
group that had less than the average number of school years). 



114 



Maize 

Table 6. 1 shows efficiency differences based on various demographic characteristics. The 
most striking result emerges in Proportion output sold. Farmers vho market on average 
proportionately more output are more technically and allocatively efficient than farmers who 
market less. This result indicates that "hillside farmer" programs, which are designed to improve 
efficiency and environmental protection and which are popular among policy makers, will have 
limited impact because most hillside farmers are near-subsistence producers. 

By contrast, producers who supplement their income with Outside work register a 
significantly positive difference in allocative efficiency, but only when the full wage is imputed. 
The Labor/land ratio differences are negative and statistically significant for allocative efficiency 
when the full wage rate is imputed, indicating that farmers with relatively little personal land have 
a low opportunity cost of labor. 

The only other significant difference in terms of technical efficiency on Table 6.1 is 
observed between those above the age of 50 and their younger counterparts. The negative sign 
indicates that older men tend to be less efficient. Given the rigors of fieldwork, one can 
understand how younger men would hold an advantage at hard labor. Allocative efficiency is 
also greater for farmers under the age of 30. That the negative values for older men and the 
positive values for younger men reduce in significance when the standard wage is imputed 
suggests that older men have a higher opportunity cost for their labor in individual production 
than younger men. 

A positive and statistically significant difference is demonstrated between allocative 
efficiencies of farmers who are more Literate and have more Primary schooling and Cognitive 



115 

capacity,^ indicating that more intelligent, better educated farmers are more capable of adjusting 
input mixes to take advantage of relative input price differences. 

Farmers with larger families are less allocatively efficient than farmers with smaller 
families, but only when the wage for free labor is zero. Larger families are not significantly less 
allocatively efficient when the standard wage is imputed, indicating that larger families have a 
higher opportunity cost for labor than smaller families. This result may seem curious in light of 
the conventional belief that rural children in developing societies are used extensively in farm 
production. However, children in Honduras now attend school on a routine basis, which divests 
production of labor that is necessarily supplanted by capital to meet increasing family food needs. 

Table 6.2 shows the differences in efficiency over varying health factors. Larger farmers 
are more technically and allocatively efficient than smaller farmers, as demonstrated by Weight, 
Arm circumference and Leg circumference. It stands to reason that larger farmers would be 
more technically efficient, given the arduous labor involved. The fact that larger farmers are also 
more allocatively efficient as well may stem from the fact that smaller farmers often suffered 
malnourishment at a young age, which impaired mental capacity. Eye sight is the only other 
factor to register a significant result, for allocative efficiency. It too nay be correlated with 
greater mental faculty. 

Table 6.3 displays efficiency differences across various social capital factors. Religion 
is a prominent form of social capital, the primary initiative behind the establishment of many 
HARCs and a congregating force in rural Honduras. Catholics appear statistically and 
significantly more allocatively efficient than noncatholics, perhaps because base communities offer 
a forum for interaction. Evangelicals are statistically and significantly less technically and 



'As measured by Raven's colored matrices test. 



116 

allocatively efficient than nonevangellcals. Their allocative inefficiencies become stronger and 
more significant when the standard wage is imputed. 

Perhaps the most interesting results are the efficiency differences as they relate to various 
forms of extension methods (Table 6.4). Those who received a lecture unaccompanied by 
pamphlets or visual aids {Lecture only) register higher technical and allocative efficiencies. All 
other significant results are negative, suggesting that supplementary teaching aids are 
counterproductive tools in extension efforts. The maize technical efficiency differences on 
extension methods are perplexing in light of the fact that the only extension variable that is not 
positive and significant' in all three maize production functions is Lecture. The difference could 
be explained by the fact diat the control group, which was excluded from the production function 
regressions to avoid a singular matrix, is now included in the group against which Lecture only 
is compared. Control group shows negative and significant allocative efficiencies, which 
indicates that those HARCs that did not receive any extension assistance were significantly less 
adept at adjusting input mixes to an optimum. 

Finally, Table 6.5 shows efficiency differences for farmers with above average levels of 
experience. Experience with herbicides and insecticides appears most helpful in improving 
efficiency. To some extent, no single input should be considered apart from the others in that 
hybrid seeds require fertilizer and pesticides to maximize potential; it is a package. However, 
pesticides constitute the most complicated component of the package. Improper pesticide 
application could override benefits derived from hybrids and fertilizer, thus permitting the only 
difference in experience to be manifested in pesticides. 



'At the 0.1 level of significance. 



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Beans 

Results of how demographic and human capital variables influence efficiency are less 
significant for beans than for maize. The lack of significance may be attributed to less variation 
in bean efficiencies (see Table 5.7), and to the fact that the number of bean observations (178) 
is half the number of maize observations (387). 

Table 6.6 shows differences in the efficiency of bean production across various personal 
and household characteristics. The only variable to show a significant difference in technical 
efficiency is Proportion output sold. Producers who sell more of their output are also more 
allocatively efficient when the standard wage is imputed. The levels of significance are strong. 
These results corroborate those of maize: commercial farmers show a higher propensity to 
operate more efficiently. 

Producers with high labor to land ratios are also more technically efficient and 
allocatively efficient when unpaid labor receives no wage. Not surprisingly, and similar to the 
case of maize, the difference in allocative efficiency becomes negative for farmers with high 
labor/land ratios when the standard wage is imputed. 

Literate farmers appear more allocatively efficient than illiterate farmers, but schooling 
and cognitive capacity show little influence. Unlike the case of maize (Table 5.3), bean 
production is still based primarily on a traditional technology that, holding to Theodore Schultz's 
finding in Transforming Traditional Agriculture (1964), cannot be improved by education alone. 
Older producers are more allocatively efficient when the wage is near zero, but significandy less 
so when the standard wage is imputed, indicating older farmers see less opportunity cost in 
devoting free labor to bean production. Similar to the case of maize, allocative efficiency is less 
for farmers with larger than average size families, as indicated by the negative sign. 



124 

Health factors show only a few significant differences in efficiency (Table 5.10). Bean 
production requires more labor than maize, but usually over half of it is devoted to harvesting 
and shelling. Hired labor is often brought in for those tasks, thus clouding the effect of health 
influences. Social capital factors (Table 5. 1 1) again indicate that Catholics are more allocatively 
efficient than non-Catholics. 

Differences in efficiency attributed to extension methods (Table 5.12) do not counter the 
results obtained for maize production. Lecture only and Lecture and publication register a 
positive influence on allocative efficiency at a near zero wage rate. Control group is again shown 
to be less technically and allocatively efficient than groups that received some form of extension 
training. 



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131 

Training and Education: Complements or Substitutes? 

Maximizing the knowledge of farmers in a target area requires that scarce extension and 
educational resources be distributed to the activity with the highest opportunity cost. Evidence 
of substitutability between education and training (Huffman, 1977 and Jamison and Lau, 1982) 
is based on homogeneous training programs. The four extension programs designed and 
implemented by MIPH may have different effects on farmers of varying educational backgrounds. 
Publications, for example, are not very useful to illiterate farmers. Visual aids may enhance the 
instructional capacity of a lecture for all educational levels, or they may distract from the 
substance of the lecture - particularly for farmers unaccustomed to them. 

Tables 6.11 - 6.15 (Maize) and 6.16 - 6.20 (Beans) show technical and allocative 
efficiency differences for different extension techniques at increasingly higher levels of education. 
Maize farmers belonging to HARCs that received a lecture only (Table 6.11) were more 
allocatively efficient than other farmers at all levels of education, suggesting that training can be 
substituted for general education to improve efficiency. However, all the efficiency differences 
in the control group (Table 6.15) are negative and significant for farmers that have at least one 
year of primary education. This indicates that complementarity exists between education and 
training. 

Complementarity between education and extension can be seen at higher levels of 
education for other extension types. Perhaps the most interesting result is that farmers with 
higher levels of education demonstrate statistically significant greater efficiency in groups that 
received publications only for both maize and beans (Tables 6.12 and 6.17). Publications are a 
significantly cheaper means of information diffusion than personal contact with extension agents. 
In the case of maize, lectures and visual aids differences (Table 6.14) are negative and 
statistically significant with no primary schooling, but become positive and statistically significant 



132 

at higher levels of education. Similarly, for lectures and publications (Tables 6.13), differences 
are negative and statistically significant at low levels of education, but are not significantly 
different at higher levels of education. These results suggest that complementarity between 
extension aids and education exists at higher levels of education. 



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143 

Summary 

This chapter reviewed the theoretical and empirical features of human and social capital 
studies. Human capital, the development of which is a fundamental goal of HARCs, is 
undoubtedly important to production. However, the maimer in which it influences production 
is not guided by formal theory. Empirical human capital studies also encounter specification 
problems in that conventional components of human capital, such as knowledge and health are 
presumed to be captured by education and height and weight. Social capital is similarly devoid 
of formal theory and has been examined in few empirical studies. The general notion underlying 
social capital is that it appears in forms of social interaction that are not necessarily directly 
related to work. Thus religion, games and music were considered as forms of social capital in 
how they influence efficiency. 

Differences in technical and allocative efficiency of individual HARC maize and bean 
producers were examined in five groups: personal and household characteristics; physical capital; 
social capital; and extension and experience. Maize provided more significant differences than 
beans, because maize data had more variation and degrees of freedom. 

The most prominent characteristic associated with higher efficiency is the proportion 
output sold. Producers appear to be more efficient the more they commercialize their output. 
Lecture only stands out as the most effective extension method as measured by efficiency. 
Primary schooling and literacy positively influence efficiency. Age shows an inverse relationship 
with efficiency, especially for maize. Catholic farmers appear more efficient than non-catholic 
farmers, perhaps because base community organizations provide communication fora. Health, 
as measured by height and weight and limb circumference, show positive influences on technical 
and allocative efficiency. Experience, particularly with herbicides and insecticides, appears to 
enhance efficiency in maize production. 



144 

Finally, this chapter examined the complementarity of education for different types of 
extension methods. The Lecture only group showed a strong correlation with allocative 
efficiency at all levels of education, suggesting that training and education are substitutable. 
However, farmers with at least one year of education in the control group appeared statistically 
and significantly less efficient than their counterparts that received some form of extension and 
training, suggesting that education and training are complements at higher levels of education. 
Complementarity at higher levels of education also emerges from the Publications only tables of 
maize and bean producers and from the general pattern of maize tables for Lectures and 
publications and Lectures and visual aids. 



CHAPTER 7 
THE NATURE OF 
HONDURAN AGRARIAN REFORM COOPERATIVES 
AS PRIVATE ENTERPRISES 

The preceding chapters consider aspects of HARCs in a neoclassical economic 
framework, which evaluates the production function in static marginal relationships. Broader 
discrete relationships, on the other hand, form the boundaries of institutions that matter and 
cannot be captured by mathematical or statistical models. According to Jensen and Meckling 
(1979), the production function cannot be adequately evaluated without addressing institutions that 
govern production: 

...the production function of the firm depends on the specificaticn of rights and the laws 
or rules of the game governing contracting. The maximum attainable output of a firm is 
then not purely a matter of "physical" possibilities given the technology and knowledge; 
the production function depends on the contracting and property rights system within 
which the firm operates. 

The purpose of this chapter is to frame neoclassical findings about HARCs in a broader and 
dynamic institutional setting that takes into account contracts and property rights. The analysis 
pursues an understanding of what Williamson (1991) terms "discreet structural alternatives," as 
opposed to marginal variations. 

This chapter is intended to make two academic contributions. First, important efficiency 
questions persist regarding the public or private provision of services such as education, 
communication and commodity exchange. HARCs and coop support agencies present an unusual 
mix of public and private enterprises that could contribute to the growing body of institutional 
economic thought and provide solutions to policy makers assisting HARCs. 

145 



146 

There is also a noticeable gap in the literature between cooperative theory (Abrahamsen, 
1976; Cobia 1989) and organization theory (Chandler, 1990). The latter primarily treats 
hierarchical management issues of large private firms, and the former describes the various rules 
and regulations that can govern a cooperative. Williamson (1985) considers institutional aspects 
of producer cooperatives understudied, and calls for further research to determine their benefits 
and costs. 

Observations were made throughout the course of fieldwork (and two years of Peace 
Corps service) which serve to illuminate the broader implications of the neoclassical analysis and 
explain areas of debility in HARC operations. Ultimately, this chapter is concerned with 
examining institutional options which may improve HARC performance. 

Introduction 

HARCs in general are conceded to be inefficient as reflected by the high rate of loan 
defaults. They absorb scarce national reserves, and have prompted influential Honduran sources 
to call for their dismantling'. With respect to the sample in this study, only eight of the 27 
HARCs claimed to hold no outstanding debt for the purchase of short-term variable inputs. 
Large regional cooperatives that made substantial fixed capital investments have also fallen into 
insolvency. 

Desertion rates reflect part of the problem. According to USAID (1978) and INA (1985), 
HARCS endured a 20 - 40 percent membership decline between 1968 to 1984. Barham and 
Childress (1992) attribute the abandonment in part to the large number of people required to 
invade land, and the relatively fewer number of people constituting the optimum coop size. 



'Numerous reports have appeared in the major Honduran newspapers, including El Tiempo, 
La Tribuna and La Prensa. 



147 

Incentives are also geared to encourage abandonment of disenchanted laborers or managers 
responsible for misinvestments: HARC members have a right to compensation for duties 
performed if they leave the coop, but they are not beholden to any debt outstanding. 

The problem 

The results of this study challenge conventional wisdom (Alchian and Demsetz, 1972; and 
Jensen and Meckling, 1979) in that collective production systems appear more technically and 
allocatively efficient than individual systems. Thus, the problem with cooperatives appears to 
lie in the financial management of the enterprises, not in production. This lends promise to 
cooperatives as viable enterprises because, whereas production inefficiencies resulting from 
ineffectual worker incentives and shirking cannot be easily remedied, management problems can 
be overcome by identifying sources of institutional weaknesses. So the question arises, if HARC 
failure cannot be attributed to the inefficiency of collective production, where can the causes be 
found? 

Perhaps a solution can be found by a more detailed examination of the HARC as a firm, 
which neoclassical theory consigns to a black box. A great deal of economic activity occurs 
within firms (Barnard, 1938; Chandler, 1990) and, in the case of HARCs, between firms and 
government agencies. HARCs are governed by a conglomeration of implicit and explicit rules 
which vary in their degree of enforceability and thus credibility. Those institutions, regarded by 
North (1992) as "formal rules (statute law. common law, regulations), informal constraints 
(conventions, norms of behavior, and self imposed rules of behavior); and the 
enforcement characteristics of both" provide the context within which marginal insights can be 
evaluated to clarify misconceptions and/or contradictions. 



148 

Cooperative Enterprises and the New Institutional Economics 



The "new" institutional economics (NIB) is distinct from traditional institutional 

economics (e.g. Commons 1934, Veblen 1899) in that it takes a positive rather than a normative 

approach. The body of literature in the new institutional economics has not yet reached an 

integrated, cohesive theory (Furboton and Richter, 1991). Indeed, the definition of "institutions" 

varies among the experts: 

the humanly devised constraints that structure political, economic, and social interactions. 
They consist of both informal constraints (sanctions, taboos, customs, traditions, and 
codes of conduct), and formal rules (constitutions, laws, property rights) (North, 1991); 

sets of ordered relationships among people which define their rights, exposures to the 
rights of others, privileges, and responsibilities (Schmid, 1972); 

Institutions can be demarcated into two classes: (1) conventions; and (2) rules or 
entitlements (Bromley, 1989); 

regularities in behavior which are agreed to by all members jf a society and which 
specify behavior in specific recurrent situations" (Schotter, 1981) 

Conceptual tools also inevitably differ and are usually refined to suit particular 
circumstances. The rationale for institutional economics, to account lor the shortcomings of 
neoclassical theory, holds as much intuitive appeal as it does challenge in application. In spite 
of the widespread acknowledgement of Coase's postulate that the choice between organization 
within the an economic unit or through the market forms the nature of the firm's existence, 
empirical applications are sparse (Coase. 1991). However, elements of NIE are emerging which 
provide means for expanding insights of neoclassical analysis of the "bl ick box" or firm. 



149 

Why Firms Exist 

According to Coase, the existence of a firm rests not on some technological base, which 
was the conventional wisdom prior to his seminal 1937 article, but primarily on the minimization 
of transaction costs, the costs of doing business. If transaction costs wers zero, labor and capital 
could be traded across households or individuals. Using an example from The Wealth of Nations, 
the manufacturer of pins would find it very costly to obtain labor services through the market 
from the households of the sharpener and the head maker. Delivery and collection of pin 
components alone would involve prohibitive costs, but the process of determining prices and 
negotiating individual exchanges also impose costs. Contracting labor services under one roof 
where the sharpened pin can be handed directly to the head maker considerably reduces the cost 
of conducting organizational transactions. 

Institutions are important to any economic system which involves positive transaction 
costs because, as Coase (1991) rationalized, 

"what are traded on the market are not, as is often supposed by economists, physical 
entities but the rights to perform certain actions...." 

Campesino unions altered land tenure patterns to broaden member rights to market labor services 

in a manner formerly restricted by dominant share tenancy systems. Landless farm laborers 

banded together to obtain for their actions a greater share of the return to the land to which they 

had devoted their labor and to gain greater control, via cooperatives, over firm management 

which governs their actions. Institutions then, particularly legal instruments at the disposal of 

policy makers, are critical to expanding the rights to "perform certain actions," a fundamental 

goal of both classical economics and HARCs. 



150 

Cooperatives in the NIE 

Most of the empirical NIE literature regarding transaction costs deals with explicit 
contracts between firms in developed countries (Williamson and Masten, 1995). Implicit 
contracts are recognized as being just as important, but diey require assessments that are more 
subjective in nature. Producer cooperatives, which are woven together with implicit contracts, 
have received little attention in economics literature. The term only appeared in ten references 
contained in the ECONLIT database (there are of course scores of articles on cooperatives, but 
they concern autonomously formed firms with clearly defined property ■•ights). 

Corporative enterprises have a notable survival record in France and Italy and have been 
successful in East Asia (Asian Productivity Organization, 1989). Recent empirical evidence from 
Italian and French cooperatives (Bartlett et. al., 1992; Estrin and Jones, 1992) and the famously 
successful Mondragon cooperative in the Basque region of Spain suggest that labor managed firms 
are even more efficient than private firms. 

The dynamics that contribute to cooperative success or failure are not well understood. 
Theoretical exercises" regarding cooperative operations are based on restrictive assumptions with 
respect to objective functions and work rules. It may prove more insightful to consider internal 
cooperative relations as they are influenced by the official agreements and implicit contracts upon 
which cooperative alliances depend. Knowledge about the viability of contracts under varying 
legal and social constraints would lend more precision to the task of designing efficient 
corporative organizations. 



^See Prychitko and Vanek, 1996. 



151 



Contracts 

Transaction costs are inversely related to the efficacy of contracts. The nature of 
contracts thus matters to collective enterprises such as HARCs that are bound by both internal 
and external contracts. The ideal transaction is "sharp in by clear agreement; sharp out by clear 
performance" (Macneil, 1974). Unclear agreements and obscured performance weaken the 
confidence critical to effective corporative enterprises. The benefits derived from contract are 
jeopardized in the presence of bounded rationality or "limited cognitive competence" and 
opportunism or "self-interest seeking with guile" (Williamson, 1985). Both are notably present 
in HARCs. 

Contracts can be supplanted by the market when standardized assets are exchanged, even 
in the presence of bounded rationality and opportunism. The identity of parties related by 
exchange is unimportant in that assets may be acquired elsewhere; continued relations are 
unnecessary. However, when asset specificity or non-homogeneous assets, exist, there is the 
potential for some agents to secure "quasi-rents" generated by the uniqueness of the assets they 
control. In the case of HARCs, asset specificity characterizes the services and inputs that are 
ostensibly obtainable from government support agencies and/or private firms. 

Exchanges in which all three are present, bounded rationality, opportunism and asset 

specificity, require a governance structure to ensure the integrity of the transaction. Efficiency 

is served when organizational structure is adjusted to minimize transaction costs which vary 

according to such things as capital holdings, frequency and risk. According to Williamson 

(1985), the organizational imperative becomes this: 

"Organize transactions so as to economize on bounded rationali:y while simultaneously 
safeguarding them against the hazards of opportunism." (p. 32). 



152 

No task could be more appropriate for the viability of HARCs. One tould argue that such an 
imperative applies to any type of economic organization. However, most organizations which 
develop autonomously economize transactions in a safeguarding fashion because participants are 
protecting their interests. Transactions in Honduran cooperatives merit .special attention because 
the environments in which they operate were established by outside sources whose incentives did 
not necessarily coincide with those of the coop members. The following sections review those 
institutional apparatuses surrounding HARCs and HARC production processes. 

Contracts Related to HARC Basic Grain Production 

Most of the contracts associated with HARCs are implicit, the oroad outlines of which 
are documented in plans drawn with support agencies and in minutes ov meetings. At the time 
data were gathered, various agencies assisted HARCs in drawing up plans for the upcoming 
planting seasons. Normally, maize is planted in primera. Beans are planted in postrera between 
the rows of dried maize stalks. 

HARCs in good credit standing receive loans from the National Agricultural Development 
Bank (BANADESA). Those who have credit problems solely with BANADESA normally 
receive credit and assistance from the Natural Resource Ministry (RR.NN.). HARCs that have 
outstanding loans with both those institutions can obtain credit from the National Agrarian 
Institute, INA. Loans are usually granted at the beginning of the season on a lump sum basis, 
but deductions must be solicited and recorded for each input purchase. 

Typically, an agronomist from one of those three lending/development institutions is 
assigned to the cooperative/borrower. The decision-making process varies depending on the size 
and social dynamics of each HARC, but agronomists' recommendations are not commonly 
disputed. In a few HARCs with marginally qualifiable credit standing, agronomists insist on 



153 

"managing" the production as one collective unit to a point where profitable output is assured, 
after which time land is permitted to be parceled to individuals. 

After target levels of production are developed, solicitations are made to the credit agency 
to release ftinds for input purchases, sometimes including labor costs for coop members. Often 
these decisions are made by the agronomist alone, and, in the case of large HARCs, in 
conjunction with a few coop administrators. 

Postrera maize is harvested between September and November (o amortize debt. Initial 
harvests are stored for household consumption. HARCs have an ostensible contract to sell 
surpluses at guaranteed prices to the Honduran Institute of Agricultural Marketing (IHMA), the 
national grain marketing board. Usually, however, they sell to intermediaries, known principally 
as coyotes. 

Bean production occurs exclusively on individual parcels. Credit is provided to some 
HARCs for bean production as well, though for much smaller sums as beans require fewer 
inputs. Bean output may be sold to IHMA for guaranteed prices as well, but is usually sold to 
middlemen who own transport vehicles. 

The Standard Administrative Chart 

A standard administrative chart illustrating HARC internal and external associations is 
displayed on Figure 7.1. Ail HARCs incorporate labor, most of which is unspecialized. 
Management and peer instruction, two elements that represent fundamental reasons for forming 
cooperatives, are also incorporated. Management gives rural farm laborers power over their lives 
and, in most HARCs. members are required to serve periodically in official management 
positions. The mere act of collectivization reduces barriers that formerly prohibited peer 
instruction, a service that would involve transaction costs among individual, unassociated farmers. 



154 

A few relatively large groups own machinery and storage facilities. Smaller HARCs do not 
produce the volume necessary to justify incorporation of such lumpy investments and acquire 
them through the rural service market, from parent regional coops, or from government agencies. 

Three government agencies provide production assistance to HARCs, INA, RR.NN. and 
BANADESA. All three provide credit and technical assistance. INA is also charged with the 
very delicate task of providing land-use rights and ultimately, to those few groups which make 
all the payments, full ownership title to land. RR.NN. on occasion supplies variable inputs, 
including seed, fertilizer, pesticides and machinery services. The principal private enterprises 
that serve HARCs are input suppliers and intermediary supply purchasers. The national grain 
marketing board, IHMA, purchases output at ostensibly guaranteed prices. 

Explicit contracts are devised for credit and land titling. Technical assistance is a part 
of the credit contract, but roles of technical advisors are not listed in great detail. Technical 
agents are usually given authority to control the dispersion of credit funds, a rational instrument 
intended to protect lender interest, that can be used to influence HARC decisions. 



155 



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Transaction Association by Activity 

Figure 7.2 shows a transaction map by activity, rather than by organizational entity as 
in Figure 7.1. The minimization of transaction costs associated with activities constitutes the 
economizing action which gives rise to the firm. Property rights of activities are consigned to 
organizations by explicit laws. The use of those activities, to generate independent and efficient 
HARCs or to absorb HARCs to serve agency interests, depends on the viability of contracts 
governing agency - HARC relations, the institutional environment. 

Purchase and sale contracts, which represent the exchange of money for inputs or outputs, 
are displayed by dashed lines in Figure 7.2. Solid lines represent service and support contracts 
for which no money, outside member or administration fees, are exchanged. Explicit contracts 
are indicated by black lines, implicit contracts by gray lines. All explic.t contracts are assumed 
to be transparent and implicit contracts non-transparent. Thin dotted lines depict the coopting of 
another entity that is enabled by not fulfilling implicit contracts. 

The purpose of the diagram is to identify implicit contracts and examine their reliability. 
The activities in Figure 7.2 illustrate the contracts that govern transactions for the "right to 
perform certain actions" (Coase, 1991). Figure 7.2 thus represents a more fundamental picture 
of relations of the black box or firm than Figure 7.1. Transactions wiJi particular entities are 
not necessary to the basic needs of HARCs; transactions that acquire rights to perform essential 
actions are necessary. Assessing the acquisition of those rights renders a more precise illustration 
of HARC weaknesses and how they may be resolved. 

Incentives are of a different nature in the two diagrams. In the standard administration 
chart, incentives are aligned within each organization. In the activity chart, by contrast. 



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158 

incentives are characterized by the nature of the contract that governs the transaction and by the 
relative position of the activity. If the contract is not a credible commitment, and is not 
buttressed by a credible threat, then the right to perform the action is jeopardized. 

The manner in which transaction costs are minimized, through the market or through 
internal organization, is not the same for private firms as for quasi-autonomous firms. Most of 
the NIE and transaction cost literature deals with autonomous capitalistic jnterprises (Williamson, 
1985) or macroeconomic issues of public welfare (Bromley, 1989). HARCs are micro-enterprises 
that cannot be considered capitalist or even autonomous. HARCs thus present a third type of 
transaction cost minimization alternative beyond the market and internal organization: contract 
with mass social organizations and government entities of potentially dissimilar incentives. The 
discussion below considers the incentives and viability of ostensible constraints associated with 
the parties of each activity. 

Internal Contracts: The Black Box of the Firm 

The HARC is represented by a thickly lined box, the black box of the firm. Internal 
contracts are both explicit and implicit. Formal, apriori established regulations, or "rules of the 
game" provide a broad governance structure for cooperation among HARC members. They are 
determined by institutional transactions (Bromley, 1989), or what Davis and North (1971) term 
the institutional arrangement. For example, requirements with respect to meeting attendance, 
fmes for missed work days and election processes form recognized and enforceable parameters. 

Many regulations, particularly those governing monetary dealings such as input purchases 
and output price negotiations, render discretion to HARC central administrators. That discretion 
is insulated by ignorance when information is lacking to the asemblea general (general assembly) 



159 

through illiteracy or high transaction costs of acquiring information. The larger and more 
complicated the coop, the more elusive is operational information. 

Labor-labor contracts 

HARC members contribute labor to an enterprise in which they expect fellow members 
to share their labor. That collective plots are relatively more technically and allocatively efficient 
than individual plots suggests that implicit contracts across laborers may hold. The greater 
efficiency may be attributed to better organization, but if labor commitments are relatively weak 
on collective parcels it is not enough to override gains in efficiency resulting from better 
organization. Given the centrality of labor to basic agricultural production, collective or 
individual, it appears that internal implicit labor contracts are strong. 

Administration-labor contracts 

Administration of HARCs takes on many forms. Ostensibly, officers are elected on 
regular intervals and serve terms established in cooperative guidelines. The elected officials are 
responsible to formally represent the HARC to outside interests and sign formal, explicit 
contracts. Often, however, real authority rests with one or a few individuals. When HARCs 
were initially contacted for participation in this study, some presidents directed inquiries to 
strong-minded individuals who held no elected posts. Their dominance A'as also often observed 
through the dynamics of HARC meetings. 

Ultimate authority rests with the asemblea general, which approves operating plans, but 
the details are carried out by central administrators. It is a logical arrangement. Even if all 
HARC members had the capacity to review potential production technologies and financing 
arrangements, which few do, the time involved in acquiring, sorting and processing relevant 



160 

information would entail significant transaction costs. Ideally, administrators would allocate 
H ARC resources to those activities which have the highest opportunity costs to the collective unit. 

The viability of implicit contracts between central administrators and labor is difficult to 
objectively determine. Some HARCs had fallen into unwarranted debt because of unscrupulous 
administrators, who were subsequently ostracized by the other coop members. However, an 
important constraint on HARC administrators at the local level is the relatively small amount of 
credit extended on an annual basis. Unlike large capital investments, which are less open to 
scrutiny and offer substantial sums for opportunism, short term loans are small and invested 
piecemeal within the cooperative unit. Thus implicit labor-administrator contracts form more 
credible commitments. This is not to argue that contractual dealings, including credit and the 
purchase of inputs, between administrators and technical assistance agencies enjoys the same 
degree of credibility. Still, the relatively minor gains obtainable from the low credit level, and 
the credible threat attending localized operations, inhibit administrators from indulging in 
activities which would jeopardize long-term opportunity and thus Jie welfare of HARC 
operations. The main weakness of the administration-labor contract is attributed to inadequate 
human capital. 

External Contracts: Association with Support Agencies 

The maimer in which transactions are organized with supporting agencies is just as 
important to the cooperatives as internal transaction arrangements. Operating designs of HARCs 
almost always result from external imposition, rather than the autonomous will of the campesinos. 
In early stages of coop development, paternalism and external assistance are inevitable to generate 
long run, self reliant and voluntary cooperatives (Lele, 1981). HARCs are constructed under the 
guidance of strong personalities within the group, the parent camp^.sino organization and 



161 

government agencies related to agriculture, agrarian reform and cooperative development. Just 

one agency, the National Agrarian Institute (INA) 

"intervenes in project design, feasibility study, technical and administrative assistance for 
credit acquisition from national and international lending institutions and processing 

and/or business agreements with national and international companies Large 

(cooperative) projects.... are managed with almost total government agency support and 
direction from the formation and transfer of the group and the granting of land to the sale 
of the product." (Cardonap. 102-103) 

Other government agencies and campesino unions exert similar influence over the cooperatives, 

rendering the coops vulnerable to state exigencies or the political priorities of the party in power. 

The administration-labor contracts are distinct from contracts HARC administration 

manages with external agents. The bitter disputes between HARCs and support agencies, with 

both sides charging the other with mismanagement, are not attributable to ineffectual 

administration-labor contracts. When support agencies and HARCs come to loggerheads, usually 

the majority of the HARC goes along with the official position. 

Campesino unionizing 

The foundations for unions are different from those of cooperatives. Unions are founded 
on political organizing and require a large number of members to be effective. Cooperatives are 
founded on capital and must at least achieve solvency if they are to survive and satisfy any other 
objective. Cooperatives may be large, as demonstrated by those in the United States where they 
have increasingly taken on a product processing role to provide value-added margins to declining 
rural communities. But producer cooperatives are by nature relatively smaller than unions 
because the transaction costs associated with coordinating workers in dissimilar situations are 
high. Individual producer cooperatives face problems specific to their lo;al areas and situations, 
problems that cannot be addressed by broad policies of large umbrella organizations. Coop 
members feel a much stronger sense of ownership of their coops than they do of the campesino 
unions to which they are also members because communication is local and visible. 



162 

Incentives are ostensibly similar for campesino unions and the HARCs they spawned, 
namely the operation of economically vibrant enterprises. However, the constraints placed on 
individual administrators of campesino unions vary significantly from those of HARC 
administrators. HARC administrators are closely scrutinized by members who almost always live 
in the same community. Decisions made in campesino unions, on the other hand, are open to 
a cluster of close associates who constitute a relatively small proportion of the entire unit. Coop 
administrators are more immediately beholden to HARC members' interests than are union 
administrators. Union power is often built on small clusters of association within the larger 
union. Problems arise when union administrators exploit HARCs through violation of implicit 
contracts that serve to incorporate HARCs into serving the larger purposes of union 
administrators at the expense of HARCs. At that point HARCs begin to lose autonomy and 
cannot be fully considered "firms." 

Nor can campesino unions be considered autonomous political institutions, given the 
national and international forces which sought to influence them. Campesino union management 
handles large sums of money for both local support organizations and for development assistance 
on capital intensive investments. The latter is usually worked out with the government agencies 
that provide technical assistance and, in the case of international funding, breign agencies. Large 
regional cooperatives, such as CARAOL, made substantial capital investments in deals worked 
out between campesino unions, government credit agencies and private suppliers. Several 
concerns were heard among HARC members, who were ultimately responsible for repayment, 
that provisions were not made for equipment maintenance and, perhaps more importantly, 
competing investments had higher opportunity costs. 



163 



Land tenure 

Land tenure is tenuous in Honduras, nonetlieless legal documents exist between INA and 
each official HARC through their campesino unions. Very few HARCs own their land, but are 
given permission to use land. 

The challenging task of balancing intense, partisan political dispu:es involving land tenure 
falls on the National Agrarian Institute (INA). It is INA's responsibility to clarify poorly defined 
land rights in an agrarian-based economy between traditional landed interests and landless 
campesinos who claim land is underutilized and not fulfilling a social purpose. Two former 
heads of INA, Sandoval Corea and Ponce Cimbar, acknowledge INA^ has had difficulties in 
distinguishing public lands from private lands (CEDOH, 1992). Perhaps because of the high 
stake political battles, INA has played a rather capricious role in Honduran resource policy and 
the Honduran economy. 

Sandoval (CEDOH, 1992) expressed concern about the conflic: of interests that arises 
when the land tenure institute, INA, gives any funding to campesino groups, large or small. INA 
evolved from an agency entrusted to settle property rights disputes to a development agency that 
provided credit and tens of thousands of dollars to campesino unions fo. education and training 
projects. Land tenure instability has, aside from the obvious long-run problems, short-run 
consequences for HARC performance to the extent that members' expectations about the viability 
of the enterprise diminishes their investments in it. 
Technical assistance 

Technical assistance, which ultimately governs credit and input supply is managed by one 
or more of the government support agencies, INA, RR.NN., or BANADESA. The individuals 
employed to provide technical assistance are not necessarily evaluated according to the success 



164 

of the HARC operations for which they are entrusted. Agencies are placed under the auspices 
of politicians whose authority rests on their ability to remain in office. To the extent that HARC 
performance contributes to prevailing political priorities, HARC interests will be served. 
However, at most, HARC interests take on secondary importance and may be discounted entirely 
to the extent that ignorance and complexity obscures institutional transparency. If contracts do 
not hold as they are designed, HARCs may be absorbed into the larger, politically geared national 
institutions that provide technical assistance, and must serve the objectives of those organizations 
above their own. They may take on the detrimental characteristics of the notoriously inefficient 
"state-run farms." 

Oversight of technical assistance is relegated to each HARC. However, administrators 
responsible for reviewing and negotiating agreements for technical assistance, which includes 
credit and input purchases, may not be literate. 

The principal architect of the historic 1968 land reforms, Roberto Sandoval Corea, 
expressed bewilderment at the manner in which international development agencies supplied 
funding for projects without effective controls. Sandoval also charged that subsequent state 
financing of campesino unions had a corrupting influence and thwarted the reform movement 
(CEDOH, 1992). Corruption, which the Cold War accelerated markedly in Honduras during the 
"lost decade" of the 1980s (Hayes, 1989), is widely recognized as a pervasive influence in the 
Honduran economy. 

Credit 

Virtually all seasonal credit for variable inputs comes from government agencies. Credit 
contracts are written so that the cooperative is ultimately responsible for repayment. Almost all 
loans are unmortgageable and given on a short-term basis for annual operating expenses. No 



165 

individual, including an elected official, is technically accountable for repayment. Holding 
institutions rather than individuals responsible for credit operations presents a credit risk, 
particularly in the absence of auditing services. 

Credit from government agencies is usually granted for the upcoming growing season and 
must be repaid at harvest. Defaulted loans incur substantial transactions costs for both lending 
agencies and HARCs. Outstanding debts compel HARCs to seek alternative sources of funding 
with intermediaries, who provide inputs or cash at high interest that is deducted from the forward 
purchase price. Ties with government agencies under such circumstances jeopardize potential 
earnings because the government marketing board, IHMA, may withhold payment to clear past 
debts. By the same token, government lending agencies incur larger transaction costs of 
monitoring defaulted groups in order to recoup previous losses. 

Marketing 

Most HARC output is sold to the national marketing board, IHMA or intermediaries. 
The harvesting and selling of grain is visible to all members, who uf ually participate in the 
process. Grain prices paid by IHMA are supposedly guaranteed by futures' notices, but the rules 
governing maize grading and pricing are inconsistent and have disappointed some HARCs. 

A marketing incident of a HARC in the sample illustrates the role of transaction costs and 
the importance of enforceable contract. Rather than sell to an intermediary, the HARC attempted 
to incorporate transportation into its operations by renting a truck and delivering the maize 
directly to IHMA. However, IHMA quoted a price considered unsatisfactory by the HARCs 
members. After waiting at the gate for two days trying to negotiate a higher price and paying 
truck rental charges, the HARC ultimately sold to an intermediary for a i.igher price than offered 
by IHMA. The intermediary sold the grain to IHMA, demonstrating clearly that IHMA was 



166 

willing to pay a higher price than that offered to the HARC. The incident reveals a breakdown 
in the contract between IHMA and the HARC and another, illicit, contract between intermediaries 
and IHMA. The notion that prices are unreliable would discourage HARCs from incurring 
transportation charges to sell to IHMA, thus reducing the efficiency of HARC operations in 
general. 

The theory of transaction costs also serves to explain why IHMA administrators may 
choose to deal with a few intermediaries rather than several grain producers. Conceivably, the 
same extra-official commission that motivated the higher price for die intermediary could also be 
negotiated directly with each HARC. But negotiating one commission with one or a few 
intermediaries to exercise price discrimination requires fewer transactions be made. It also 
alleviates the cost of risk associated with several producers who may not wish to engage in such 
transactions. 

Intermediaries can provide a valuable and efficient service, but only when they operate 
in a competitive environment and hold no extra-official price advantage over HARCs. 
"Information asymmetries" (Williamson, 1985) impose risks that increase the transaction cost of 
incorporating transportation higher than the cost of acquiring transportation in the market. 
Intermediaries' potential for monetary gain expands to the extent Uiey can exen monopsony 
control. Contracts that maintain credible marketing commitments would improve the efficiency 
of HARC operations and production distribution. 

Vigilance Committees 

Vigilance committees technically exist in HARCs to ensure that all contracts, internal and 
external, are carried out according to their stated purposes. However, vigilance committee 
members are often illiterate or not functionally literate enough to comprehend all the details 



167 

associated with overseeing dealings with which they are unaccustomed. Even when they are 
capable of reviewing records, it involves another task on top of a heavy labor load, not to 
mention confrontations with friends. 

Proprietorship of vigilance is consigned, logically, to each HARC. After all, a main 
purpose of cooperative enterprises in LDCs is to empower impoverished individuals to look after 
their own best interests rather than be dependent on traditional elites. However, a contradiction 
arises when cooperative organizations are entrusted with the responsibility to oversee operations 
that, because of their complexity, involve significant external assistance and are by the same 
token beyond the comprehension of most members. HARCs are not kibbutzes, which survive 
under similar organizational structures because they have impressive levels of human and social 
capital. The question arises, can proper oversight be given to HARC interests in the absence of 
an oversight capacity necessitated by the level of technical assistance provided? 

The Design of Efficient Institutions 

The administrative flow chart in Figure 7. 1 differs in style and substance from the activity 
flow chart in Figure 7.2. The administrative chart shows official associations between HARCs 
and external support and market agencies. The activity chart outlines contracts that exist to 
facilitate the exchange of rights. The rights of technical assistance and credit are supplied by the 
government to HARCs in exchange for the right to ameliorate civil tensions by developing 
lucrative economic enterprises among the politically troublesome disenfranchised. However, 
policy mechanisms intended to exchange those rights breakdown becausi credible commitments 
are not made. Either explicit contracts are not enforced, or implicit contracts are based on norms 
or customs that do not exist. 



168 

Williamson (1985) distinguishes credible commitments from credible threats in that the 
former are "reciprocal acts designed to safeguard a relationship" and "are undertaken in support 
of alliances and to promote exchange," whereas the latter involve "unilateral efforts to preempt 
an advantage. " The financial breakdown of HARCs indicates that credible commitments were 
not made in some areas of operation that were not safeguarded by credible threats. 

Credible Commitments 

Credible commitments are valuable assets to an economic enterprise because they involve 
no ex poste transaction costs. For example, if guaranteed prices are not offered at the time of 
sale, producers have to incur the cost of legal recourse. Similarly, if borrowers refuse to repay 
loans, lenders incur costs of pursuing payments. 

The only notable credible commitments made in HARC operations, the labor-labor 
contract and the administrator-labor contracts, occur within the black box or corporative 
enterprise that constitutes a HARC. Fortunately, the labor-labor contract is the most necessary 
of all credible commitments because it is the one that is virtually impossible to remedy by 
institutional modifications. The transaction costs of preempting, monitoring and recovering lost 
labor would not be worth the payment to labor. Conversely, transactions that cover larger cost 
items such as input purchases, credit disbursements and marketing are more concentrated and thus 
justify some additional ex ante or ex post transaction costs. 

Non-credible Commitments 

Non-credible commitments necessitate credible threats throu:?h various contractual 
mechanisms. Government support agencies and campesino unions both have incentives to 
incorporate HARC enterprises to serve their own operations. Indeed, evidence of the regional 



169 

cooperatives such as CARAOL and the manner in which technical jobs are doled out to political 
appointees indicates that commitments between external sources requires some credible threat. 

Ostensibly, HARCs hold legal recourse to ensure their best interests are being served. 
However, HARCs do not have the human capital or administrative capacity to carry out the task. 
HARC administrators are susceptible to being inveigled into options tha: may not necessarily be 
in the best interests of the HARC. thus jeopardizing the viability of the labor - administrator 
contract. Transparency of operations is virtually non-existent in relations between HARC 
administrators and government support personnel. Lenders of funds, both national and 
international have not imposed adequate auditing controls. The requirement of auditing, 
particularly as an a priori condition of a lending agreement, serves as a viable threat to preempt 
unwarranted advantage in transactions. 

An Empirical Observation: The Guanchfas Cooperative 

The institutional concepts developed above account for why HARCs may fail or remain 
weak, but do they also correspond to success cases? The Guanchfas cooperative on the north 
coast of Honduras, which was extolled as a model by all proponents of collectivization, provides 
an interesting case study. 

Observers of Guanchfas were quick to attribute its success tc its collective form of 
operation, ignoring other factors absent in cooperatives sponsored oy the goverrunent or 
campesino unions. Guanchfas was not initially successful in paying off its loans when it operated 
as a basic grains cooperative. It became modestly profitable when it abandoned basic grains for 
plantains, but could not obtain government support for cash crops (McCommon, et al. 1985). 

Guanchfas then turned to Standard Fruit's independent banana growers program. 
Standard Fruit agreed to purchase most of Guanchfas' production and provided scarce technical 



170 

assistance, credit and inputs. Guanchi'as' success may be attributed to two aspects of the 
institutional design that prevented systematic leaks common to the basic grain sector. 

First, Standard Fruit had a financial interest in providing inputs and technical support in 
a timely fashion and in overseeing compliance. In the basic grain sector by contrast, government 
extension and loan agents are governed by political rather than economic oversight. Government 
agents collaborate with agency superiors and coop leaders whose best personal interests do not 
necessarily coincide with making cooperatives financially sound enterprises. A potential HARC 
loan default is likely to draw a greater response from a company representative responsible for 
generating returns to company capital than it would from a government representative. 

Second and perhaps more significantly, Standard Fruit had control over Guanchfas' output 
and lived up to purchase agreements. Cooperatives in the basic grain sector face more than one 
buyer. If they sell directly to the Honduran Institute of Agricultural Marketing (IHMA), 
outstanding loan charges are deducted from the bill of sale. IHMA also reneged on promises to 
purchase grain from farmers at guaranteed prices (USAID, 1982), imposing a higher risk burden 
on cooperative planning. Farmers gain a higher return from coyotes (intermediaries) who offer 
nominally lower prices than IHMA, but whose real prices, adjusted for lean charges and artificial 
quality deductions, are higher. 

The success of the working arrangement with Standard Fruiv is demonstrated most 
significantly by the increase in income to Guanchfas' members. The average annual income 
increased from 800 lempiras in 1969, the first year of the program, to 4,484 lempiras in 1980, 
over three and a half times higher than the average income in Honduras. Investment returns have 
been turned back into new capital equipment, member housing and social services in education 
and health. 



171 

Standard Fruit signed agreements with two other coops whic'i were also successful, 
although not as remarkable as Guanchias. The arrangement is mutually beneficial. Workers gain 
control over production resources, and Standard Fruit maintains stable political relations and 
portrays a good image. Standard Fruit created a cooperative in March of 1996, not with an 
existing HARC. but by granting land and capital to a group of employees. Both Standard Fruit 
and the United Fruit Company intend to turn over more resources to workers to quell political 
opposition and worker strikes, which have proven quite costly in recent years. 

Summary 

The previous chapters demonstrate that HARC breakdown cannot be attributed to labor 
shirking theorized by Alchian and Demsetz (1992). This chapter attempts do differentiate further 
the underlying defects by examining HARCs in a broader institutional context. It is also an 
attempt to contribute to the institutional economics literature, which provides few guideposts for 
the analysis of cooperatives. 

Property rights and the contracts which govern the behavior of HARCs and associated 
agencies formed the core structure of the analysis. Incentives that are potentially present in each 
were also examined heuristically in light of statistical results and observations made throughout 
the course of fieldwork. A standard administrative chart was compared to an activity chart which 
delineated transactions for inputs and services vital to HARC performance. 

Internal contracts, including implicit contracts, appear to hold. The credibility of Labor- 
labor contracts is demonstrated by the higher technical and allocative efficiencies of collective 
parcels over individual parcels. Administrator-labor contracts also appear to be credible, 
demonstrated by the greater scrutiny that exists at the local level and the minor gains relative to 
risk associated with breaking agreements. 



172 

Contracts between external agents and coop administrators, on the other hand, are less 
dependable, primarily because they are exercised without proper oversight and across parties of 
disparate incentives. The contract breaks down because there is a weakness of purview that 
conventional lenders would require over operations in which their funds are invested. 

Marketing contracts between IHMA and HARCs have also been unreliable, usually to the 
detriment of HARCs. Marketing contracts lack credibility because they are unaccountable and 
involve direct monetary transactions with government agents who art beholden primarily to 
political sponsors. 

If all contracts functioned ideally, "sharp in by clear agreement; sharp out by clear 
performance," (MacNeil, 1974) HARCs would be more independent and commercially vibrant. 
The problem is that contracts are not clear and are not enforceable, injecting risk and 
undercontldence in HARC development - an undertaking which, by its collective nature, requires 
stability and assurance of mutual success. Vigilance is ironically relegated to the HARCs, 
institutions established in large part to develop in the long run the human capital to oversee 
technically advanced operations. HARCs lack the human capital in which some cooperatives, 
notably kibbutzes, are richly endowed. Provisions to account for short-run human capital 
deficiencies may be necessary. 

Independence of HARCs is threatened to the extent that their incentives do not correspond 
to those of government support agencies and campesino unions. HARCs become components of 
a larger government or political enterprise when contracts do not hold. Little wonder they have 
generated many of the same criticisms leveled against state-run farms. HARCs' identity as firms 
which minimize transaction costs is obscured because the instruments they rely on to carry out 
transactions, the contract, is not credible. 



173 

The cooperative model presented in this chapter was developed in light of observed 
failures, but also conforms to cooperatives which have enjoyed substantial success through 
contracting with a private firm. The most notable, Guanchfas, demonstrated its capacity to 
function as a profitable, independent enterprise when it contracted with the Standard Fruit 
Company. Standard Fruit overcame the incentive problems inherent in the governmental and 
political organizations that ostensibly provide support, and Guanchfas evolved into a cooperative 
that produces high quality products and generates investment returns that significantly increase 
member income and achieve social goals. 

According to the cooperative model presented in this chapter, HARCs have the internal 
dynamics necessary to survive, but encounter problems with external agents whose incentives do 
not coincide with those of HARCs. Contracting with a private enterprise whose success depends 
on the economic success of the HARCs has shown itself to be a viable i olution to the problems 
that prohibit HARCs from emerging as independent and financially sound firms. The 
arrangement may appear as an increasingly appealing alternative in the future as Central America 
is opened to free trade and as autonomous political forces demand the integration of poor people 
into an economy that provides opportunities for all. 

This is not to suggest that government support agencies do not have a useful role to play 
in HARC operations. Guanchfas was aided completely by Standard Fruit because the company 
was large enough to provide all technical assistance. Most economic opportunities for HARCs 
dwell in the small-scale supply of products to local markets in expanding towns and cities. 
Perhaps some of the very skilled agronomists and technicians who have received training in 
Honduran agricultural colleges could acquire funding to contract with HARCs. Structuring 
incentives through tax breaks or other means for skilled agriculturalists could inject capital into 
HARC operations in a manner which safeguards lender interests. They would still depend on 



174 

government support for research and technical assistance. More research needs to be done to 
compare the costs of such an endeavor with other rural development programs. 

Cooperatives serve as a viable organizational mode to transfer technology for the 
production of nontraditional commodities, and private agents provide capital and technical 
assistance. Most importantly, the collaboration is based on mutually beneficial economic, not 
political, incentives. 



CHAPTER 8 
SUMMARY AND RECOMMENDATIONS 

Colonial forces confined Honduran campesinos to share tenancy systems that precluded 
human capital investments and advances in agricultural technology and marketing. Unionization 
of banana workers and the revolution in Cuba precipitated domestic and international pressures 
for agrarian reform. Those reforms gave limited land access to groups of farmers who were 
encouraged, through support services and through denial of individual land titles, to work 
collectively. HARCs' poor performance record was attributed to the collective mode of 
production and to internal mismanagement. 

Design of the Analvsis 

The analysis begins at the base level of technology. A logit regression examines a range 
of factors that influence technology adoption. Stochastic frontier production functions are 
estimated for maize and beans. Debreu-Farrell technical efficiency, the ratio of observed output 
to optimal output for a given set of inputs, is calculated for each producer from the observed 
frontiers. 

A producer's response to prices are reflected in allocative efficiency, which measures the 
adjustment of input mixes relative to input prices. It is an estimate of costs incurred 
unnecessarily given the actual level of technical efficiency. Allocative efficiency is calculated 
from an analytically derived cost function. 



175 



176 

In conjunction with other data, profiles of efficient producers are drawn from technical 
and allocative efficiencies. The most important aspect of the HARC profile involves the 
efficiencies of collective parcels relative to those of individual parcels. Human and social capital 
factors are examined by comparing the group means of technical and allocative efficiency 
averages. A comparison of advanced and traditional technologies is made by contrasting 
advanced maize production with traditional bean production. 

Finally, the empirical results are interpreted within a broader institutional model that 
examines the viability of internal and external implicit HARC contracts. The model is premised 
on the Coasian notion that a firm's existence is not based fundamentally on technology, but on 
transaction cost minimization. Economizing action is thus reviewed in transaction components 
and governance mechanisms. The model is empirically applied to the notably successful 
cooperative Guanchfas, which was cited by many advocates of collectivization as a paradigm 
worth replicating. 

Summary of the Results 

Collective production systems emerged in this analysis as being more technically and 
allocatively efficient than individual systems. The collectivity variable in the maize regression 
is also positive and statistically significant for average OLS and frontier estimations. These 
results counter conventional notions that cooperatives fail because laborers and managers have 
incentives to shirk work responsibilities. They also conform to direct survey evidence that 
shirking on collective parcels is not observed by HARC members. That collectives are more 
efficient reveals an important policy option for transferring technology, improving agricultural 
production and integrating the rural poor. 



177 

That collective parcels are more efficient to the institutional "black box" of the firm 
suggests that the internal dynamics of the cooperatives are sound. Mutual agreements of laborers 
to carry out work responsibilities is a necessary condition to achieve collective efficiency. 
Agreements between HARC managers and workers are also reliable, due to local scrutiny and 
the low return associated with managerial shirking at the local level. 

However, transactions with support agencies are unreliable due tc the disparate incentives 
of HARC members and agency personnel. Commitments with external agencies are not credible 
and are not braced by a credible threats. Implicit contracts with external entities do not hold 
because HARCs' administration and internal vigilance, unlike the Israeli Kibbutz upon which 
HARCs were modeled, lack the necessary human capital to oversee complicated transactions. 
The unreliability is reflected in the low allocative efficiencies for maize and in poor marketing 
services. HARCs' potential for success is also demonstrated by the cooperatives which contracted 
for support from the private sector, most notably Guanchfas. 

A prominent result that emerges both in technology adoption and technical and allocative 
efficiency is the significance of the proportion of output sold. The more commercialized farmers 
become, the more prone they are to correctly adopt new technologies ond the more efficiently 
they operate. The positive benefits of commercialization also suggest that HARC members 
respond to markets and that profit maximization is a fundamental cooperative goal. 

Maize allocative efficiencies are significantly lower than th)se of beans. Maize 
production relies on more advanced technology and on a broader range of inputs than bean 
production. Unavailability of inputs reduces the allocative efficiency of production in that 
producers cannot adjust input mixes to minimize production costs. The low allocative efficiencies 
for advanced maize production systems underscore the importance cf effective distribution 



178 

systems, particularly as the Honduran economy attempts to improve its agricultural technology 
and efficiency. 

Extension methods in general bear significant influence on technology adoption and 
efficiency, as demonstrated by extension coefficients in statistical regressions and efficiency 
measures. Personal instruction, unaccompanied by teaching aids, appears most effective in 
reaching farmers regardless of their prior education, and may be a substitute for education at low 
levels of education. However, other forms of extension, including publication circulation, appear 
as complements to different types of extension at higher education levels. Complementarity of 
education with certain extension types renders greater flexibility in designing extension programs. 
For example, the per unit costs of reaching rural farmers are much lower for publication 
circulation than training and visit extension. 

Human capital variables yielded predictable results. Investments in health and education 
are shown to stimulate technology adoption and improve production efficiency. Experience, 
particularly with herbicides and insecticides, also enhances efficiency. 

Religion is the only social capital variable that appears to influence efficiency. Social 
capital is treated tangentially in this study, as the methodology does not lend itself to examining 
complex social fabrics. Nonetheless, social capital is gaining prominence in the economics 
literature and constitutes worthy future research with respect to cooperatives. 

Recommendations 

Policy makers in Central America are faced with the difficult task of balancing social and 
economic integration of the rural poor while simultaneously expanding export programs in 
response to structural adjustment pressures from international donors. They also face the 
challenge of supplying growing urban populations with nontraditional foods that provide the 



179 

various nutrients of a healtiiy diet. The results which emerge from this study suggest that 
cooperatives are an important policy option which may assist them in meeting those objectives. 

Cooperatives provide the economies of size that permit the lumoy investments required 
by the nontraditional commodities in which Central America has a comparative advantage. 
Cooperatives also serve as a proficient means for transferring the advanced technologies needed 
to produce those commodities. The important policy question is: Can cooperatives serve as 
efficient organizational forms in terms of production? The evidence to date, as measured by 
tlnancial performance, is that they cannot. 

However, this study shows that cooperatives are organizational forms which enhance 
technical and allocative efficiency in production. Cooperative failure is not attributable to 
shirking, but to unreliable contracts with support agencies whose incentives are based more on 
politics than economics. The results of this study, and successful cooperatives such as Guanchfas 
that have received solid private sector support, bear that out. Moreover, HARC members appear 
amenable to profitable nontraditional ventures, as demonstrated by the positive influence of 
commercialization on performance. 

Future Research 

Two policy paths could be pursued to address problems that burden HARCs, the details 
of which are grounds for future research. The first involves the attraction of private capital and 
attendant management expertise, the second the restructuring of support agencies. 

The Potential Role Private Capital 

Policies designed to attract private capital investments to cooperatives would be beneficial 
in meeting the dual needs of rural development and achieving export grcwth. Private managers 



180 

of capital funds have the incentives to carry out the daily myriad tasks involved in operating a 
competitive and complex enterprise. Agreements designed to generate investment returns would 
benefit both investors and cooperatives and would serve broader national development goals. 

Net social benefits of attracting private capital merit examination relative to those 
associated with government assistance programs that are intended to develop poor rural areas. 
Perhaps private capital would have to be attracted at some cost, but may be a more efficient way 
of achieving social goals than direct government assistance. The mechanisms and incentive 
schemes for drawing private capital thus merit investigation. 

The Potential Role of NGOs 

Restructuring support agencies to be more operationally transparent and to align agency 
incentives with HARC incentives would be beneficial. Perhaps non-governmental organizations 
(NGOs) could lend assistance in this endeavor. NGOs dedicate dependable but meager resources 
to directly attack underdevelopment and often accomplish more than government agencies. If 
NGOs could direct their scarce resources toward improving the functioning of government 
support, not in decision-making but in the auditing necessary to insure that those decisions are 
carried out, the pay-off would be much higher. 

NGOs assemble a great deal of expertise capable of conducting the types of simple audits 
required by HARCs. Transferring human resources from direct de\elopment assistance to 
auditing government development programs would have a multiplicative effect on NGO efforts. 
It would combine meager NGO funding with government funding to secure the fulfillment of 
government development goals. Future research could examine how NGOs could be employed 
to complement ongoing government programs. 



APPENDIX I 
DATA AND STUDY AREA 

Integrated Pest Management Program of Honduras CMIPH') 

The Integrated Pest Management Program (Spanish acronym MIPH) mounted a three year 
pest management training and extension program in 1985. Operating through the Pan-American 
Agricultural School (Spanish acronym EAP) in Zamorano, Honduras, MIPH provided four 
different training techniques to 27 randomly selected HARCs in the El Parafso and Olancho 
regions of Honduras. HARCs were randomly divided to receive different types of training with 
respect to agronomy and pest management. One group was set aside with no training to serve 
as a control group against which extension efforts could be measured. The training types were: 

1 . Printed material only 

2. Lectures only 

3. Lectures and printed material 

4. Lectures, printed material and electronic visual aids. 

Trained agronomists visited the groups on a regular basis to give lectures and/or supply 
printed information. MIPH focused on common problems faced by basic grain producers and 
suggested cost-effective means for overcoming them. 

The Sample 

MIPH selected a sample of HARCs between 1985 and 1988 to participate in the pest 
management program. The HARCs were chosen at random by .extension agents, then 
subsequently and randomly assigned to receive one of the above training techniques. 



181 



182 

Data on the groups analyzed in this study were gathered between November, 1987 and 
June, 1989. A two-month sondeo was conducted at the outset to determine the strategy for 
surveying in light of the proposed research objectives and the availability of logistical support. 
All the cooperatives were contacted during the sondeo to secure their agreement to record data 
for a one year production cycle. 

Fieldwork was carried out through the primera (the heavier of two rainy seasons which 
occurs from May to August) and postrera (September to December) production seasons of 1988 - 
89. Corn is the principle crop in primera and red beans are grown in postrera. Crossectional 
data were gathered for one production season. Fortunately, both primera and postrera brought 
good to average rains during the data gathering period. 

MIPH randomly selected the HARCs from among basic grain cooperatives in the two 
regions. The types of training offered to the HARCs were also selected on a random basis. The 
data gathered comprise a sample of basic grain HARCs, but the entire population of HARCs and 
HARC members who participated in the MIPH program. 

Most of the HARC members had an individual corn plot and over half had an individual 
bean plot. Individual production data were collected by literate coop members or children of 
coop members trained in each cooperative to maintain investment records on all activities 
pertaining to individual land parcels. 

Gathering production data is a difficult task, made more challenging by the distrust that 
people naturally feel about revealing economic and financial records. Cooperatives provide an 
excellent network for collecting accurate data in that trust need not be established with every 
individual but just with someone trusted within the cooperative. Although the author met every 
HARC member in this study, personal relations were more closely - and efficiently - cemented 



183 

with a trusted person within the HARC who could observe production practices and elicit the 
confidence necessary to obtain accurate records. 

Nonetheless, it would be imprudent to argue that distrust was totally allayed, but the 
establishment of trust and personal relations - that began with many HARCs during my Peace 
Corps service - significantly improved the accuracy of data that would be offered to enumerators 
unfamiliar to HARC members. It should be noted that collective yield data were the most 
challenging to gather, in that outstanding debts threatened the extraction of surplus revenues if 
such information were divulged to debtor institutions. The provision of yield data on individual 
production posed little if any risk. Input records were also readily available as most farmers 
enjoy talking about their individual production practices. Lending institutions maintained records 
of coop purchases for all collective and some individual parcels. 

Human capital and demographic data were gadiered over a period of three months in 
1989. The survey was designed through interviews with HARC members and extension 
personnel from MIPH and government agencies. It was tested extensively in cooperatives that 
were not included in the sample but operate in the sample areas. 

Of the 27 HARCs in the sample, 19 had a fully collective maize parcel and 25 had 
production systems that were completed under individual responsibility. The distribution of coop 
size in terms of membership and land access varied. Table AI.l compares nationwide average 
with sample averages for member and landholdings per asentamiento and landholdings per socio. 
Table AI.2 provides a breakdown of asentamiento names, members and land access per group 
and per socio. 



184 



Table AI.l. Asentamientos by name, membership and land access 
Group Members Collective Individual 


Total 


Per Soci 


Ideas en Marcha 


1 A 

14 




1 AA 

100 


100.00 


7.14 


El Boqueron 


12 


50 


24 


74.00 


6.17 


Empalizada 


16 


62 


15 


77.00 


4.81 


El Benque 


7 




5 


5.00 


0.71 


Los Bienvenidos 


23 


44.5 


12.5 


57.00 


2.48 


bl tsfuerzo 


24 




140 


140.00 


5.83 


Los Peregrines 


1 o 

18 


66 


36 


102.00 


5.67 


Esquilinchuche 


11 




16 


16.00 


1.45 


San Nicolas 


7 


12 


11.5 


23.50 


3.36 


Los Almendros 


14 


57 


23 


80.00 


5.71 


La bsperanza 


18 


102 


30 


132.00 


7.33 


Santa Cruz 


1 o 

Is 




92 


92.00 


5.11 


L.ayo tsianco 




35 


5 


40.00 


4.44 


Z/Opiiotepe 


11 


75 




75.00 


6.82 


uudyiuuroS 


o 


An 
47 




47.00 


7.83 


Ld v^oncepcion 


10 




1 O 

38 


168.00 


4.42 


San Juan de Linaca 


A O 


15 


47 


62.00 


1.29 


La Puzunca 


15 




90 


90.00 


6.00 


Tempiscapa 


7 


10 


14 


24.00 


3.43 


La Providencia 


30 


45 


115 


160.00 


5.33 


19 de Abril 


23 


29 


23 


52.00 


2.26 


El Coyolar 


13 


14 


26 


40.00 


3.08 


El Plomo 


9 


46 


8.5 


54.50 


6.06 


Los Dos Naranjos 


14 


110 


70 


180.00 


12.86 


Los Venecianos 


8 


28 


4 


32.00 


4.00 


La Libertad 


14 


20 


40 


60.00 


4.29 


Montanuelas 


10 


28 




28.00 


2.80 



185 



Table AI.2. Comparison of sample averages with national averages 



Land per 
Asentamiento 



Socios per 
Asentamiento 



Land per Socio 



Nationwide 



212.98 
(154.35) 



22.44 
(8.8) 



9.04 
(2.76) 



Sample 



90.52 
(53.35) 



16.04 

(9.75) 



8.27 
(5.86) 



The Surveys 



Quantifiable production and demographic data were gathered in the regions of Olancho 
and El Parai'so, Honduras. General information was also gathered as a byproduct of the 
numerical data obtained for statistical analysis. These regions share similar terrain and cultural 
characteristics. Data were recorded on the entire gamut of cooperative operations. The human 
survey instrument (appendix) was designed to obtain information regarding the health and 
educational background of each HARC member, his living conditions and social affiliations with 
the cooperative. The purpose of collecting data regarding the personal characteristics of HARC 
members and facets of social interaction was to distinguish features that influence HARC 
efficiency and operations. 

Short to long-term endogenous factors were surveyed to facilitate the delineation of 
policies that improve HARC efficiency and performance. Besides short-term IPM training 
techniques, longer term components such as schooling, housing and health data were gathered 
to amplify the explanatory power of statistical modeling. Exogenous factors such as age, family 
size and types of social interaction were also included to render information regarding the 



186 

responsiveness of characteristic clusters and thus determine, apriori, which groups are more 
inclined to operate efficiently and are relatively more amenable to extension services. 

A test regarding integrated pest management techniques was £lso administered in the 
survey to examine the effectiveness of the varying training techniques tc which the cooperatives 
were exposed. Farmers were never asked directly if they adopted a given technology, as such 
questions are known to bias responses. Rather, they were asked open-ended questions free of 
suggestions about their production and pest management practices. Responses were scored as 
correct only if they conformed to the instructions given by MIPH. 

All individual data take the household parcel or parcels, not the household itself, as the 
unit for which all inputs and activities were measured. Financial resources simply did not permit 
measurement of all household activities. The argument could be made that competing household 
production activities will bear an influence on efficiency and adoption measurements. The 
relative degree of importance that the individual parcel plays in the household utility function 
could vary, rendering the coefficients vulnerable to bias and an overestimation of the disturbance 
variance. However, it is reasonable to assume that opportunities available to agrarian reform 
households are minimal. If they were not, they could not participate in the reform. The only 
activity that may compete with other activities is coffee harvesting. But this occurs primarily in 
the first three months of the year, when most basic grains have been harvested. Moreover, given 
the intensity of land disputes, the efficiency of land units, not household units, assumes primary 
importance. The number of outside economic endeavors is documentet! in the human resource 
survey and may, through the inclusion of dummy variables, account for some efficiency variation. 

Observations were made on cooperative operations throughout the data gathering period. 
It was necessary to attend dozens of cooperative meetings and maintain close contact with support 
agencies in order to obtain data and information. Close association with the cooperatives and 



187 

cooperative agencies provided an excellent opportunity to observe how actual HARC performance 
deviated from desired HARC performance. Amiable assistance from MIPH and government 
agronomists was invaluable in corroborating data to account for discrepancies and ensure data 
reliability. Such observations will be useful in interpreting statistical results. 



APPENDIX II 
FIELD SURVEY 



ENCUESTA DE RECURSOS HUMANOS 
Grupo 

Encuestador: Fecha / / Hora : 



I INFORMACION GENERAL 
\. Nombre 



2. Edad 

4. Dirreccidn 

5. Estado civil Casado 

Soltero 
Viudo 



6. ^Donde Nacid? Jamastran 

El Sur 
Guayape 
Linaca 
Otro: 

8. Sf no naci(5 en esta zona: 

iQuQ afio lleg(3 aquf a esta zona? 

9. Ano que se uni(3 el grupo 

10. Cargo en el grupo 

desde 

11. Cargos que ha tenido: Presidente: aiios 

Vice Presidente: aiios 

Ttisorero: aiios 

Secrataria: aiios 



188 



189 



12. (,Antes de hacerse socio del grupo, 
que hacia usted para ganar la vida? . 



Asdariado Alquilaba tierra 
Otro: 



13. (,Cree usted que ser miembro del grupo aumenta(A), 

baja (B) o no cambia (N) lo siguiente?: Seguridad 

Consumo de comida 

Sueldo 

Dignidad 



14. Numero de miembros de la casa: 

Rela- 

Nombre ci(3n Edad Educ Pep Nombre 



1 
2 
3 
4 
5 
6 



10 



11 



12 



* HO = hijo, HNO = hermano 
II. PRODUCCION 

1. ^.Cuantos anos tiene de trabajar con 



Rela- 
cidn Edad Educ Pep 



J L 



semillas mejoradas en bolsa? 

herbicidas? 

veneno de plagas? 

abono? 



;Relcalque mucho que las preguntas 2-24 referien solamente a la arcela individual 
por la cual el archivero llevo el control! ;Ubique al asociado al:a mentalmente en 
una manera conversacioal 
y por cada pregunta refieranse a esa parcela! 



2. Por cada uno de los siguientes insumos preguntele al asociado si utilizd el producto o no en 
su parcela individual Si contesta "no" escriba "no" a la derecha del colon, y si contesta "sf" 
ponga el numero de aiios tiene de trabajar con tal producto a la derecha del colon 



190 



3. (,Utiliz(5 otros insumos que no estan mencionado arriba? Sf No 

Si contesta "si." ,;,CuaIes son? 

: 9 : 9 : > 

4. ^Como prepard la tierra de su parcela individual? Tractor 

Bueyes 



Azaddn 
Barreta 



5. (.Cuantos pases de arado hizo en primera en su parcela individual?. 

6. (.Cuantos pases de rastra hizo en primera en su parcela individual?. 



7. iQue tipo de arado utiliz6 en su parcela individual? Disco 

Vertedera 
Row plow 
De palo 

8. iCon que surque<3 la labranza? Bueyes? 

Maquina? 
No surqued 

9. ^En su milpa individual que distancia tiene entre: surcos? 

posturas? 

10. i,Cuantas semillas puso por postura 

(por ej. 2:3 O 3:3) en su parcela individual en: maiz? : 

friiol? : 

1 1 . En su parcela individual sembrd frijoles en Primera 

Postrera 



12. Para usted: ^Cuantas barras cuadradas tiene una tarea? 

iQUE NO LEA A LOS ASOCIADOS LAS RESPUESTAS DE PREGUNTAS SOBRE 
LAS PLAGAS #13 - #22 (O SEA JUEGOS DE RESPUESTAS QUE SON TRAZADAS!) 
DEJE LA PREGUNTA ABIERTA PARA QUE CONTESTE EN SU PROPIA MANERA. 



13. Sigamos en la misma parcela individual. 

/■Antes de encontrar algunas Gallinas Ciegas 

este ano, hizo algo usted para prevenirlas ? No hizo nada 

Prepard bien el suelo 

Aplicd veneno 

Otro: 



191 



i,La Gallina ciega infestd esa parcela este ano? Sf No 

Si contesta "No" pasen a #14 

^Hizo muestreo? Sf No 

^Cuantas tareas de a _ se le infestd? 

^,Como la combatid usted? No hizo nada 

Prepard bien el suelo 

Aplicd veneno 

Otro: 

^.Logrd controlaria? Sf No 

14. Sigamos en la misma parcela individual. 

(,Antes de encontrar algunos Cogolleros 

este ano. hizo algo usted para prevenirlos? No hizo nada 

Lluvia los matd 



Aplicd veneno. 
Otro: 



^El Cogollero infestd esa parcela este ano? Sf No 

Si contesta "No" pasen a #15 

^Hizo muestreo? Sf No 

(.Cuantas tareas de a _ se le infestd? 

i,Como lo atacd usted? No hizo nada 

Lluvia lo matd 

Aplicd veneno 

Otro: 

i,Logrd controlarlo? Si No 

15. Sigamos en la misma parcela individual. 

( Antes de encontrar algunas langostas 

este ano, hizo algo usted para prevenirlas? No hizo nada 

Cruzd la milpa 
Controld zacate 

Aplicd veneno 

aro: 

iha Langosta (Gusano Medidior)infestd esa parcela 

este ano? Sf No 

Si contesta "No" pasen a #16 

(,Hizo muestreo? Sf No 

^.Cuantas tareas de a _ se le infestd? 

^Como la atacd usted? No hizo nada 

Cruzd la milpa 
Controld zacate 



■Aplicd veneno. 
Otro: 



(.Logrd controlaria? 



Sf No 



192 



16. Sigamos en la misma parcela individual. 
(;,Antes de encontrar algunas Babosas 
este aiio, hizo algo usted para prevenirlas ? 



;Cuando? 



. . . . No hizo nada 
Cebo 

Controld malezas 
Basura trampa 
Matanza nocturna 
Prepard terreno 
Quema rapido 

Otro: 

En primera 

En postrera 



iLa Babosa infestd esa parcela este aiio?Si No 
Si contesta "No" pasen a #17 

^Hizo muestreo? Sf No 

^Cuantas tareas de a _ se le infestd? 

(.Corno la atacd usted? No hizo nada 

Cebo 

Controld malezas 
Basura trampa 
Matanza nocturna 
Quema rapido 
Otro: 

^.Logrd controlarla? Si No 



17. Sigamos en la misma parcela individual. 

( Antes de encontrar algunas tortugillas 
este aiio, hizo algo usted para prevenirlas? 



No hizo nada 

Prepard bien el suelo 
Insecticida 



Otro: 



La Tortugilla infestd esa parcela este aiio? SI No 

Si contesta "No" pasen a #18 

^Hizo muestreo? SI No 

i,Cuantas tareas de a _ se le infestd? 

(,Como la atacd usted? No hizo nada 

Insecticida 

Otro: 



t,Logrd controlarla? 



Si No 



193 



18. Sigamos en la misma parcela individual. 

^ Antes de encontrar algunas empoascas 

este aiio, hizo algo usted para prevenirlas ? No hizo nada 

Lluvia la maX6 

Insecticida 

Otro: 

;,La Empoasca infestd esa parcela este ano? Sf No 

Si contesta "No" pasen a #19 

^Hizo muestreo? Sf No 

^Cuantas tareas de a _ se le infest(5? 

^Como la atac6 usted? No hizo nada 

Lluvia la mat(3 

Insecticida 

Otro: 

^,Logr6 controlarla? Sf No 

19. Sigamos en la misma parcela individual. 

(,Antes de encontrar algunas picudos de la vaina 

del frijol este aiio, hizo algo usted para prevenirlos? No hizo nada 

Controld malezas 



Destruyd rastrojos 
Control quimico 

Otro: 



iEl picudo de la vaina del frijol 

infestd esa parcela este afio? Sf No 

Si contesta "No" pasen a #20 

iWizo muestreo? Sf No 

^Cuantas tareas de a _ se le infestd? 

^Como lo atac6 usted? No hizo nada 



Controld malezas 
Distruyd rastrojos 

Control quimico 

Otro: 

(.Cuando lo hizo? 

t,Logrd controlarlo? Sf No 



20. iOtro plaga? 



^.Cuantas tareas de a _ se le infestd? 



^Como lo controls? 



194 



iOtro plaga? 

(.Cuantas tareas de a _ se le infest(3? 
^Como lo control^? 



21. Sigamos en la misma parcela individual. ^El zacate infestd esa parcela 

en el tiempo critico del desarroUo del mafz Sf No 

22. Sigamos en la misma parcela individual. ^EI zacate infestd esa parcela 

en el tiempo critico del desarrollo del frijol Sf No 



23. Sigamos en la misma parcela individual. 

i,La hoja ancha (monte o hierba) infest(5 esa parcela en 

el tiempo critico del desarrollo del mafz Sf No 



24. Sigamos en la misma parcela individual. 

t,La hoja ancha (monte o hierba) infesto esa parcela en 

el tiempo critico del desarrollo del frijol Sf No 

25. (.Que opina usted? 

(,Cual m^todo de produccidn pretlere en la cooperativa? Colectivo 

Individual 
Los dos 

III. EDUCACION DEL SOCIO 

1. Anos cumplidos en la escuela primaria 

secundaria 

nocturna 

2. ^Participd en la campaiia de alfabetizacidn? Sf No 

3. ^Sabe leer usted (como periodico)? Sf No 

4. ^Sabe escribir usted? Sf No 

Si contesta "sf" a #3 o #4: 

i,Donde lo aprendi(3? 

5. i,Sabe su madre leer? Sf No 

i,Sabe su padre leer? Sf No 



6. Cursos de capacitacidn que ha recibido en cuanto a: 

cooperativismo. 
agricultura 



195 



8. ^,Usted ya sabe mucho de la agricultura, 
de donde ha aprendido lo mas? 



INA Parientes Trabajando en finques grandes 
RR.NN. Experiencia Buenos agricultores 
MIPH Socios Otro: 



9. i,De donde ha aprendido mas sobre el manejo de plagas? 

INA Parientes Trabajando en finques grandes 
RR.NN. Experiencia Buenos agricultores 
MIPH Socios Otro: 



IV. AFILIACIONES SOCIALES 



1. (,Tiene usted parientes quienes son socios del grupo? Sf No 

Numero de: 

hermanos cunados 

primos suegros 

hijos yernos 

padres tios 

sobrinos 



2. (.Pertenece usted a alguna religion? Sf No 

si contesta "no" pasen a #3 

^.Cual religion? Catdlico 

Evangel ico 
Otro 



3. (,Participa usted en actividades deportivas 



con otros socios del grupo? Sf No 

si contesta "no" pasen a #4 

i,Cuales depones? Futbdl 

Dados 



Naipes 
Billar 
Otros 

4. ^Participa usted en actividades musicales 



con otros socios del grupo? Sf No 

si contesta "no" pasen a #5 

5. ^Participa usted en actividades religiosas 

con otros socios del grupo? Sf No 

i,Cual religion? Catdlico 



Evangel ico 
Otro_ 



196 



6. t,Tiene hijos que participan en actividades 

con hijos de los otros socios del grupo? Nada 

Deportes 
Religion 
Escuela 
Otro: 



7. (,Puede identificar usted el miembro del grupo quien 
tiene la mayor influencia (no necesariamente un oficial)? Si No 

Si contesta "sf:" ^.Quien es? 



V. MEDIDAS DE SALUD 



1 i,De donde consigue el agua de la casa? Rio 

Pozo 
Llave 
Quebrada 
Otro: 



2 iSt hierve el agua que se bebe en su casa? Siempre 

A veces 
Solo bebidas calientes 



3 (.Que tipo de piso tiene su casa? Tierra 

Cemento 
Madera 
Otro 



4 iQue tipo de pared tiene su casa? Adobe 

Madera 
Bloque 
Ladrillo 

5 (.Que tipo de techo tiene su casa? Texas 

Asbestas 
Zinc 
Zacate 

6 (.Tiene huerto de hortalizas? Sf No 



i.Cuales son? papa chile repollo 

cebolla rabano tomate 

yuca remolacha otro: 

pepino zanahoria otro: 



7 ^Tiene usted arboles de frutas? 



i,Cuales son? 



guineos 

aguacate 

mango 



naranja 
toronja 
maranon 



otro: 



otro: 



otro: 



8 (,Como se guarda maiz en su casa? 

9 (,Como se guarda frijoles en su casa? 

10 ^Como se guarda arroz en su casa? 

1 1 i,Cuantos dlas de trabajo perdid usted este ano por enfermedades? 
(Esto incluye enfermedades de usted o de un pariente o amigo 

a quien usted tuvo que cuidar) 

13 ^,Cuantos animal es tiene? 

toros , vacas , bueyes , cerdos , burros , 

polios , caballos , pavos , perros , mulas 



14 ^Ademas de la siembra tiene otros ingresos? 



198 



VI. MATRICES DE COLORES: 

Vista %, + 

Hora: 



1_ 
2_ 
3_ 
4_ 
5_ 
6_ 
7_ 
8_ 
9_ 
10_ 
11_ 
12 



Ab 



B 



Hora: 



Altura cm 

Peso libras 

Brazo cm 



Pierna 



cm 



REFERENCES 



Abler, D.G. and J.S. Shortle (1995). "Technology as an agricultural pollution control policy." 
American Journal of Agricultural Economics, 77(1) pp. 20-32. 

Abrahamsen, M.A. (1976). Cooperative Business Enterprise, New York: McGraw-Hill. 

Aigner, D.J. and S.F. Chu (1968). "Estimating the industry production function." American 

Economic Review, 58, pp. 826-39. 

Aigner, D.J., C.A.K. Lovell and P.J. Schmidt (1977). "Formulation and Estimation of 

Stochastic Frontier Production Function Models." Journal of Econometrics, 6, pp. 21- 
37. 

Alchian, A. A. and H. Demsetz (1972). "Information Costs, and Economic Organization." 
American Economic Review, 62(5), pp. 777-95. 

Amemiya, T. (1981). "Qualitative Response Models: A Survey" Journal of Economic 
Literature, 19, pp. 1483-1536. 

Asian Productivity Organization (1991). Agricultural Cooperatives in Asia and the Pacific, 
Report of APO Multi-Country Study Mission, Tokyo. 

Banker, R.D., A. Charnes and W.W. Cooper (1984). "Some Models for Estimating Technical 
and Scale Inefficiencies in Data Envelopment Analysis." Management Science, 30(9), 
pp. 1078-1092. 

Banker, R.D. R.F. Conrad and R.P. Strauss (1986). "A Comparative Application of DEA and 
Translog Methods: An Illustrative Study of Hospital Production " Management 
Science, 32. pp. 30-44. 

Bardhan, P. (1989). "Alternative Approaches to the Theory of Institutions in Economic 

Development." in The Economic Theory of Agrarian Institutions, Ed. P. Bardhan, 
Oxford. England. Clarendon Press, pp. 3-17. 

Barham, B.L., and M. Childress (1992). "Membership Desertion as an Adjustment Process 
on Honduran Agrarian Reform Enterprises." Economic Development and Cultural 
Change, 40(3), pp.587-613. 

Barnadas, J.M. (1986). "The Catholic Church in Colonial Spanish America." The Cambridge 
History of Latin America ed. Leslie Bethell, Cambridge: Cambridge University Press. 



199 



200 



Barnard, C.I. (1938). The Functions of the Executive Cambridge, Mass., Harvard University 
Press. 

Barro, R.J., and Sala-i-Martin. X. (1992), 'Public finance in models of economic growth', 
Review of Economic Studies 59, pp. 645-61. 

Barry, T. and K. Norsworthy (1990). Honduras, A country Guide, Albuquerque, New 
Mexico: The Interhemispheric Education Resource Center. 

Bartlett, W., J. Cable, S. Estrin. D.C. Jones, and S.C. Smith (1992). "Labor-managed 
cooperatives and private firms in North Central Italy: an empirical comparison." 
Industrial and Labor Relations Review, 46(1) pp. 103-18. 

Battese, G.E.. and T.J. Coelli (1992). "Frontier Production Functions, Technical Efficiency 
and Panel Data: With Application to Paddy Farmers in India." J. Productivity Anal, 3 
pp. 153-69. 

Battese, G.E., T.J. Coelli, and T.C. Colby (1989). "Estimation of Frontier Production 

Functions and the Efficiencies of Indian Farms Using Panel Data from ICRISAT's 
Village Level Studies." Journal of Quantitative Economics, 5(2), pp. 327-48. 

Battese, G. and G. Corra (1977). "Estimation of a Production Frontier Model: With 
Application to the Pastoral Zone of Eastern Australia." Australian Journal of 
Agricultural Economics , 21(3), pp. 169-79. 

Bauer, P.W. (1990). "Recent Developments in the Econometric Estimation of Frontiers." 
Journal of Econometrics , 46, pp. 39-56. 

Becker, G.S. (1962). "Investment in Human Capital: A Theoretical Analysis." Journal of 
Political Economy, 70, pp. 9-49. 

Becker, G. and N. Tomes (1984). Human Capital and the Rise and Fall of Families 
Economics Research Center/NORC Discussion Paper. 

(1976). "Child Endowments and the Quantity and Quality of Children." The Journal of 

Political Economy, 84 pp. s 143-62. 

Becker, Gary S. and B.R. Chiswick, (1966). "Education and the Distribution of Earnings." 
American Economic Review, May. 

Behrman, J.R., B.L. Wolf and D.M. Blau (1985). "Human Capital and Earnings Distribution 
in a Developing Country: The Case of Prerevolutionary Nicaraj^ua." Economic 
Development and Cultural Change, 34, pp. 1-29 

Behrman, J. and B. Wolfe (1984). "More Evidence on Nutrition Demand: Income Seems 
Overrated and Women's Schooling Underemphasized." Journal of Development 
Economics, 14(1-2), pp. 105-28. 



201 



B.R. Albert and W.R. Cline (1979). Agrarian Structure and Productivity in Developing 
Countries, Baltimore: The Johns Hopkins Press. 

Birkhaeuser, D., R.E. Evenson and G. Feder (1991). "The Economic Impact of Agricultural 
Extension: A Review." Economic Development and Cultural Change, 39(3) pp. 607- 
50. 

Blaug, M. (1976). "The Empirical Status of Human Capital Theory: A Sightly Jaundiced 
View." Journal of Economic Literature, 14, pp. 827-55. 

Bliss, C. and N. Stern (1978). "Productivity, Wages and Nutrition." Journal of Development 
Economics, 5, pp. 331-98 

Bonin, L (1987). Economics of Cooperation and the Labor Managed Economy, Fundamentals 
of Pure and Applied Economics. Zurich: Harwood Economic Publishers. 

Bravo-Ureta, B.E., and L. Rieger. (1991). "Dairy Farm Efficiency Measurement Using 
Stochastic Frontiers and Neoclassical Duality." American Journal of Agricultural 
Economics. 73, pp. 421-28. 

Bravo-Ureta, B.E., and R. Evenson (1991). "Efficiency in Agricultural Production: The Case 
of Peasant Farmers in Eastern Paraguay." Agricultural Economics, 10, pp. 27-37. 

Brading, D.A. (1986). "Bourbon Spain and its American Empire." The Cambridge History of 
Latin America ed. Leslie Bethell, Cambridge: Cambridge University Press. 

Brenner, R. and N. Kiefer (1981). "The Economics of Diaspora: Discrimination and 

Occupational Structure." Economic Development and Cultural Change,29i3), pp. 517- 
34. 

Bromley, Daniel, (1989). Economic Interests and Institutions, New York, New York: Basil 
Blackwell. 

Bueso, J. A. (1987). El Subdesarollo Hondureflo, Tegucigalpa, Hondures: Editorial 
Universitaria. 

Burrows, T.M. (1983). "Pesticide Demand and Integrated Pest Management: A Limited 

Dependent Variable Analysis." American Journal of Agricultural Economics, 65, pp. 
806-810. 

CEDOH (Centro de Documentaci(5n de Honduras) (1992). Puntos de Vista: Temas Agrarios, 
Tegucigalpa: Linea Grdfica S. de R.L.. 

Chandler, A.D. (1990). Scale and Scope : the Dynamics of Industrial Capitalism Cambridge, 
Mass.: Belknap Press. 



202 

Charnes, A,. W.W. Cooper and E. Rhoades (1978). "Measuring the Efficiency of Decision 
Making Units, European Journal of Operational Research, 2, pp. 429-444. 

Charnes, A,. W.W. Cooper and E. Rhoades (1981). "Evaluating Program and Managerial 
Efficiency: An Application to Data Envelopment Analysis to Program Follow- 
Through." Management Science, 27, pp. 668-697. 

Chiswick, B.R. (1983). "The Earnings and Human Capital of American Jews." The Journal 
of Human Resources. 18(3), pp. 313-36. 

Coase, R.H. (1937). "The Nature of the Firm." Economica, 4, pp. 386-405. 

Coase, R.H. (1991). "The Institutional Structure of Production." Nobel Lecture, December 9. 



Cobia, D. (1989). Cooperatives in Agriculture. Englewood Cliffs, NJ: Prentice Hall. 

Comes, R. (1992). Duality and Modern Economics, New York and Melbourne: Cambridge 
University Press. 

Davis, L.E. and D. North, (1971). Institutional Change and American Economic Growth, 
Cambridge, England: Cambridge University Press 

de Janvry A. (1981). The Agrarian Question and Reformism in Latin America, Baltimore: The 
Johns Hopkins University Press. 

Domenich, T.A. and D. McFadden (1975). Urban Travel Demand-A Behavioral Analysis, 
Amsterdam: North-Holland Publishing Co. 

Dorner, P. and D. Kanel (1971). "The Economic Case for Land Reform." In Land Reform in 
Latin America: Issues and Cases, ed. by Peter Dorner, pp. 41-56, Land Economics 
Monograph Series, no. 3 Madison: Published by Land Economics for the Land Tenure 
Center at the University of Wisconsin. 

Dublin, L. and Lotka, A. (1930). The Monetary Value of Man, New York: Ronald Press. 

Europa Yearbook (1991). London: Europa Publications. 

Fare, R., S. Grosskopf. and C.A.K. Lovell (1985). The Measurement of Efficiency of 
Production, Boston: Kluwer-Nijhoff Publishing. 

Fare. R.S., S. Grosskopf and C.A.K. Lovell, 1987, "Nonparametric Disposability Tests." 
Journal of Economics 47(1), pp. 77-85. 

Farrel, M. (1957). "The Measurement of Production Efficiency." Journal of the Royal 
Statistical Society (120) 253-81. 



203 



Friedman, M.S.. and S. Kuznets (1945). Income from Professional Practice, New York: 
National Bureau of Economic Research. 



Furubotn, E.G., and S. Pejovich. (1970). "Property Rights and the Behavior of the Firm in a 
Socialist State: The Example of Yugoslavia." Zeitschrift fur Nationalokonomie, 30, 
pp. 431-54. 

(1972). "Property Rights and Economic Theory: A Survey of Recent Literature." 

Journal of Economic Literature, 4, pp. 1137-162. 

Furubotn, E.G., and R. Richter. (1991). "The New Institutional Economics: New Views on 
Antitrust." Journal of Institutional and Theoretical Economics, 147, pp. 1-6. 

Fersund, F.R., C.A. Knox Lovell and P. Schmidt (1980). "A Survey of Frontier Production 
Functions and of their relationship to Efficiency Measurement. " Journal of 
Econometrics, 13(1) pp. 5-25. 

Frank, A.G. (1979). Mexican Agriculture, 1521-1630: Transformation of the Mode of 
Production, Cambridge: Cambridge University Press. 

Garcfa, M., R. Norton, M. Ponce and R. van Haeften (1988). Agricultural Development 

Policies in Honduras: A Consumption Perspective, Washington, D.C.: United States 
Department of Agriculture. 

GREAN (Global Research on the Environmental and Agricultural Nexui) (1996). Taskforce 

on Research Innovations for Productivity and Sustainability, Gainesville, University of 
Florida. 

Greene, W. (1980). Econometric Analysis, New York: Macmillan Publ shing Company. 

Griliches, Z. (1964). "Research Expenditures, Education, and the Aggregate Agricultural 
Production Function." American Economic Review, 54, pp. 961-74. 

Guevara-Escudero, J. (1983). Nineteenth Century Honduras: A Regional Approach to the 
Economic History of Central America, Dissertation, New York; New York 
University. 

Harper, J.K., M.E. Rister, J.W. Mjelde, B.M. Drees and M.O. Way (1990). "Factors 
Influencing the Adoption of Insect Management Technology." 
American-Journal-of-Agricultural-Economics, 72(4), pp. 997-1005. 

Hayes, M.D. (1988). "The U.S. and Latin America: A Lost Decade?" Foreign Affairs, 68, 
pp. 180-199. 

Helliwell, J.F. and R.D. Putnam (1995). "Economic growth and social capital in Italy." 
Eastern Economic Journal 21(3) pp. 295-307. 



204 



Huffman, W.E. (1977). "Allocative Efficiency: The Role of Human Capital." Quarterly 
Journal of Economics and Statistics, 91, pp. 59-79. 

Huffman, W.E. (1974). "Decision Making; The Role of Education." American Journal of 
Agricultural Economics, 54, pp. 86-97. 

Immink, M.D., F. Viteri and R. Helms (1982). "Energy Intake Over the Life Cycle and 
Human Capital Formation in Guatemalan Sugar Cane Cutters." Economic 
Development and Cultural Change, 30(2), pp. 351-72. 

Institute Hondureiio de Desarroiio Rural, 1980, 84 Meses de Reforma Agraria del Gobierno 
de las Fuerzas Armadas de Honduras, Tegucigalpa. 

IN A (Institute Nacional Agrario) (1985). Resumen Bdsico de Los Grupos Campesinos 
Beneficiarios de la Reforma Agraria, Tegucigalpa, Honduras, Departamento de 
Planificaci(3n, Seccidn de Estadfstica e Informacidn. 

Jamison, D.T. and L.J.Lau (1982). Farmer Education and Farmer Efficiency, Baltimore: The 
Johns Hopkins University Press. 

Jamison, D.T. and M.E. Lockheed (1987). "Participation in Schooling: Determinants and 
learning Outcomes in Nepal." Economic Development and Cultural Change, 35(2), 
pp. 279-306. 

Jamison, D.T. (1986). "Child Malnutrition and School Performance in China." Journal of 
Development Economics, 20(2), pp. 299-309. 

Jensen, M. C. and W. H. Meckling (1979). "Rights and Production Functions: An 

Application to Labor-Managed Firms and Codetermination. " Journal of Business, 
4, pp. 469-506. 

Jondrow, J., C.A.K. Lovell, I.S. Materov, and P. Schmidt. (1982). "On the Estimation of 

Technical Inefficiency in Stochastic Frontier Production Function Model." Journal of 
Econometrics 19, pp. 233-38. 

Kalirajan, K.P. (1990). "On Measuring Economic Efficiency, Journal of Applied 
Econometrics, 5(1), pp. 75-85. 

Kalirajan, K.P. (1984). "Farm Specific Technical Efficiencies and Development Policies." 
Journal of Economic Studies. 11, pp.3- 13. 

Kalirajan, K.P. and J.C. Finn (1983). "The Measurement of Farm-Specific Technical 
Efficiency." Pakistan Journal of Applied Economics, 2, pp. 167-80. 

Kalirajan, K.P. and R.T. Shand (1985). "Types of Education and Agricultural Productivity: A 
Quantitative Analysis of Tamil Nadu Rice Farming." The Journal of Development 
Studies, 21(2), pp. 232-43. 



205 



Khaldi, N. (1975). "Education and Allocative Efficiency in U.S. Agriculture" American 
Journal of Agricultural Economics, 57(4), pp. 650-657. 

Koopmans, T.C. (1951). Activity Analysis of Production and Allocation , Cowles Commission 
for Research in Economics Monograph No. 13, New York, John Wiley and Sons. 

Kopp, R.J., and W.E. Diewert (1982). "The Decomposition of Frontier Cost Function 
Deviations into Measures of Technical and Allocative Efficiency," Journal of 
Econometrics, 19, pp. 319-331. 

Kopp, R.J. and V.K. Smith (1980). "Frontier Production Function Estimates for Steam 

Electric Generation: a Comparative Analysis." Southern Economic Journal, 47, pp. 
1049-1059. 

Kurian, G.T. (1987). Encyclopedia of the Third World, New York: Facts on File Inc. 

Lele, U. (1981). "Co-operatives and the Poor: A Comparative Perspective" 
World-Development 9, pp. 55-72. 

Lele, U. (1974). "Role of Credit and Marketing in Agricultural Development." in Nurul 
Islam (ed.) Agricultural Policy in Developing Countries, London: Macmillan. 

Liebenstein, H. (1957). Economic Backwardness and Economic Growth, New York: Wiley. 

MacLeod, M.J. (1983). "Ethnic Relations and Indian Society in the Province of Guatemala, 
ca. 1620-ca. 1800" in Spaniards and Indians in Southeastern Mesoamerica : Essays 
on History of Ethnic Relations edited by Murdo J. MacLeod and Robert Wasserstrom. 
Lincoln: University of Nebraska Press. 

Macneil, I.R. (1974). "The Many Futures of Contracts." Southern California Law Review, 47 
pp. 691-816. 

Maddala, G.S. (1983). Limited Dependent and Qualitative Variables in Econometrics, 
Englewood, N.J. Cambridge University Press. 

Marshall, A. (1920). Principles of Economics, London: Macmillan. 

Martin, M.J. and T.G. Taylor (1995). "Evaluation of a Multimedia Extension Program in 
Honduras." Economic Development and Cultural Change 43, pp. 821-834. 

Martin^z-Peldez, S. (1975). La patria del Criollo, San Jos6: Editorial Lniversitaria 
Centroamericana. 

Mccommon, C.N. Rueschhoff. L.T. and J. Wilkowski (1985). Guanchias Limitada: a Case 
Study of an Agrarian Reform Cooperative and its Long-term Relationship with a 
Multinational Firm in Honduras, Washington, D.C.: U.S. Agency for International 
Development. 



206 



Meeusen, W. and J. van den Broeck (1977). "Efficiency estimation from Cobb- Douglas 

Production Functions with Composed Error." International Economic Review, 18, pp. 
435-444. 

Meister, R.T. (1980). "Pest Management Coops- The Small Grower's Answer to the IPM 
Puzzle?" Agricultural Consultant and Fieldman, 36, pp. 8-11. 

Meng, R. and J. Sentance (1984). "Religion and the Determination of Earnings: Further 
Results." Canadian Journal of Economics, 17(3), pp. 481-88. 

Milon, W. (1987). "The Science and Art of Efficiency Analysis: The Role of Other 

Performance Criteria," in Economic Efficiency in Agricultural and Food Marketing, 
Kilmer and Armbruster eds. . Ames, Iowa: Iowa State University Press for the Farm 
Foundation and the Institute of Food and Agricultural Sciences of the University of 
Florida, pp. 67-87. 

Mincer, J. (1989). Job Training: Costs, Returns, and Wage Profiles National Bureau of 
Economic Research Working Paper: 3208. 

Mincer, J. (1962). "On the Job Training: Costs, Returns and Some Implications." Journal of 
Political Economy, 70, pp. 50-79. 

(1958). "Investment in Human Capital and Personal Income Distribution." The Journal 

of Political Economy, 60, pp. 281-302 

Morris, J. A. (1984). Honduras : Caudillo Politics and Military Rulers, Boulder: Westview 
Press. 

North, D. (1992). "Institutions and economic theory" American Economist, 36(1), pp. 3-6. 

(1991). "Institutions." Journal of Economic Perspectives, 5, pp. 97-112 

Pinheiro, A. (1992). An Econometric Analysis of Farm Level Efficiency of Small Farms in the 
Dominican Republic, M.S. Thesis, University of Connecticut. 

Pudasaini, S.P. (1983). "The Effects of Education in Agriculture: Evidence fi-om Nepal." 
American Journal of Agricultural Economics, 65(3), pp. 509-15. 

Monthly Review, December (1985). p. 25. 

Morley, S.G. and G. Brainerd (1983). The Ancient Maya, 4th ed. / revised by Robert J. 
Sharer, Stanford, Calif.: Stanford University Press. 

Moock, P.R. and J. Leslie (1986). "Childhood Malnutrition and Schooling in the Terai 
Region of Nepal." Journal of Development Economics, 20(1), pp. 33-52. 



207 



Miiller, J. (1974). "On Sources of Measured Technical Efficiency: The Impact of 
Information." American Journal of Agricultural Economics, 55, pp. 730-38. 

Newson, Linda A. (1986). The Cost of Conquest : Indian Decline in Honduras Under Spanish 
Rule, Boulder: Westview Press. 

Nguyen, D.T. and M.L. Martinez-Saldivar (1979). "The Effects of Land Reform on 

Agricultural Production, Employment and Income Distribution: A Statistical Study of 
Mexican States, 1959-69" Economic Journal, 89, pp. 624-35. 

Palanigounder, D. (1989). Human Capital and Adoption of Innovations in Agricultural 

Production: Indian Evidence Yale Economic Growth Center Discussion Paper: 577. 

Paus. Eva, ed. (1988). Struggle against dependence: Nontraditional export growth in Central 
America and the Caribbean. Series in Political Economy and Economic Development 
in Latin America, Boulder, Colo, and London: Westview Press. 

Piesse, J., C. Thirtle and J. Turk (1996). "Efficiency and Ownership in Slovene Dairying: A 
Comparison of Econometric and Programming Techniques." Journal of Comparative 
Economics, 22, pp. 1-22. 

Posas, M. (1981). Conflictos Agrariosy Organizacion Campesina: Sobre los Origenes de las 
Primeras Organizaciones Campesinas en Honduras, Tegucigalpa, Honduras: Editorial 
Universitaria. 

Posas, M. (1987). El Subdesarrollo Hondureflo, Tegucigalpa, Hondura;.: Editorial 
Universitaria. 

Prychitko, D. and J. Vanek (1996). Producer Cooperatives and Labor Managed Systems, 
England; Edgar Elgar Publishing Limited. 

Putnam, R. D. (1993). Making Democracy Work: Civic Traditions in Modern Italy, 
Princeton: Princeton University Press. 

Putterman, L. (1986). Peasants, Collectives and Choice: Economic Theory and Tanzania's 
Villages, Greenwich, Conn: JAI Press. 

(1989). "Agricultural Producer Co-operatives," in The Economic Theory of Agrarian 

Institutions, Ed. Pranab Bardhan, Oxford, England: Clarendon Press, pp. 319-39. 

Quiiiones, E. and M. Argueta (1978). Historiade Honduras, Tegucigalpa, Honduras: Escuela 
Superior del Profesorado "Francisco Morazan." 

Romer, P. (1990). "Endogenous Technological Change' Journal of PoMcal Economy, 98, 
pp. S71-102. 



208 

Rook, S.P. and G.A. Carlson (1985). "Participation Pest Management Groups" American 
Journal of Agricultural Economics, 67(3), pp. 563-66. 

Roy, K. and C. Clark, eds. (1994). Technological change and rural development in poor 
countries: Neglected issues, Oxford and New York: Oxford University Press. 

Ruhl, M. (1989). "The Honduran Agrarian Reform Under Suazo Cdrdova, 1982-85; An 
Assessment, Inter-American Economic Affairs, 39, pp. 63-80. 

Schaible, G.D., C.S. Kim, and N.K. Whittlesey (1991). "Water Conservation Potential from 
Irrigation Technology Transitions in the Pacific Northwest. " Western Journal of 
Agricultural Economics, 16 pp. 194-206. 

Schmid, A. (1972). "Analytical Institutional Economics." American Journal of Agricultural 

Economics. 54. pp. 893-901. 

Schmidt, P. (1976). "On the Statistical Estimation of Parametric Frontier Production 
Functions." Review of Economics and Statistics, 58, pp. 238-39. 

Schotter, A. (1981). The Economic Theory of Social Institutions, New York: Cambridge 
University Press. 

Schultz, T.W. (1975). "The Value of the Ability to Deal with Disequilibria." Journal of 
Economic Literature, 13(3), pp. 827-46. 

(1964). Transforming Traditional Agriculture, New Haven: Yale University Press, 1964. 

(1963). The Economic Value of Education, New York, New York: Columbia University 

Press. 

Seale, J.M. (1990). "Estimating Stochastic Frontier Systems with Unbalanced Panel Data: The 
Case of Floor Tile Manufactories in Egypt. " Journal of Applied Econometrics, 5 pp 
59-74. 

Seiford, L. and R.M. Thrall (1990). "Recent Developments in DEA" Journal of 
Econometrics, 46, pp. 7-38. 

Seligsan, M. and E. Nessman, (1989). Land Titling in Honduras: An Im.pact Study in the 
Comayagua Region, unpublished manuscript. 

Shapiro, K.H. and J. Muller (1977). "Sources of Technical Efficiency: The Roles of 

Modernization and Information." Economic Development and Cultural Change 25(2) 
pp. 293-310. 



Sheffield, J.R., (1975). Retention of Literacy and Basic Skills, (Paper prepared for Education 
Department of the World Bank. 



209 



Shephard, R. W. (1970). Tlieory of Cost and Production Functions, Princeton: Princeton 
University Press. 

(1953). Cost and Production Functions, Princeton: Princeton University Press. 

SITRAUNAH (Sindicato de Trabajadores de la Universidad Nacional Autonoma de Honduras) 
(1979). Conjura Antisindical Contra Honduras, Tegucigalpa, D.C., Honduras. 

Smith, A. (1892). An Inquiry into the Nature and Causes of the Wealth of Nations, London: 
Routledge. 

Spence, L.H. (1993). "Rethinking the Social Role of Public Housing" Housing Policy Debate 
4, pp. 355-68. 

Stokes, W.S. (1947). "The Land Laws of Honduras." Agricultural History , 21, pp. 148-54. 

Stringer, R. (1984). An Analysis of Credit Use in the Honduran Agrarian Reform Sector, 
University of Wisconsin, Ph.D. Thesis. 

(1989). "Honduras: Toward Conflict and Agrarian Reform" in Searching for Agrarian 

Reform in Latin America. Ed. William C. Thiesenhusen, BostO'i: Unwin Hyman Inc 
pp. 358-383.. 

Taylor, T.G., H.E. Drummond and A.T. Gomes (1986). "Agricultural Credit Programs and 
Production Efficiency: An Analysis of Traditional Farming in Southeastern Minas 
Gerais, Brazil." American Journal of Agricultural Economics, 58, pp. 110-19. 

Toman, M. A. (1994). "Resources for the Future" Land-Economics, 70, pp. 399-413. 

Tomes, N. (1985). "Human Capital and Culture: Analysis of Variation m Labor Market 
Performance." AEA Papers and Proceedings, May. 

Torquemada, Juan de, ca. 1557-1664, Monarquia Indiana, por fray Juan de Torquemada. 3. 
ed. Mexico, D. F.. S. Chavez Hayhoe. 1943. 

USAID (U.S. Agency for International Development) (1982). AID Policy Paper: Private 
Enterprise Development, Washington, D.C.. 

(1978). Honduran Agricultural Assessment Drafts, Washington, D.C. . 

(USITC) (United States International Trade Commission) (1992). Potential Effects of a North 
American Free Trade Agreement on Apparel Investment in CBERA Countries USITC 
Publication 2541. 

Varian, H.L., (1984). "The Nonparametric Approach to Production Aailysis" Ecnometrica 

52 pp. 579-97. 



210 

Vaughan, R. (1989). Education, Training and Labor Markets: Summary and Policy 

Implications of Recent Research by Jacob Mincer, Conference Paper Series, The 
Institute on Education and the Economy, Teachers College, Columbia University, 
New York. 

Veblen, T. (1899). The Tlieory of the Leisure Class; an Economic Study in the Evolution of 
Institutions. New York: The Macmillan company: London, Macmillan & co. 

Villanueva, B. (1968). Institutional Innovations and Economic Development. Honduras: A 
Case Study, University of Wisconsin, Ph.D. Thesis 

Walsh, J.R. (1935). "Capital Concept Applied to Man," Quarterly Journal of Economics, 49, 
pp. 255-85. 

Ward, B. (1958). "The Firm in Illyria." American Economic Review, 48, pp. 566-89. 

Williamson, O. (1991). "Comparative Economic Organization: The Analysis of Discreet 
Structural Alternatives." Administrative Science Quarterly, 36, pp. 269-296. 

(1985). The Economic Institutions of Capitalism: Firms, Markets and Relational 

Contracting, New York, New York: Free Press. 

Williamson, O. and S. Masten (1995). Transaction Cost Economics, England: Edgar Elgar 
Publishing Limited. 

World Bank (1993). World Development Report, Washington, DC. 

Wu, C. (1977). "Education in Farm Production: The Case of Taiwan." American Journal of 
Agricultural Economics, 59(4), pp. 699-709. 

Yankelvich, P. (1988). Honduras, Mexico, D.F.: Editorial Patria, S.Af.. de C.V. 

Zepeda, L. (1990). "Predicting Bovine Somatotropin Use by California Dairy Producers." 
Western Journal of Agricultural Economics, 15 pp. 55-62. 



BIOGRAPHICAL SKETCH 



Michael Martin was born and raised in Des Moines, Iowa. He graduated from the 
University of Iowa in August, 1977, with a bachelor's degree in economics. He worked as a 
coop advisor with the Peace Corps in El Salvador and Honduras from 1979 to 1982. 

He enrolled in the Agricultural Economics Department at the University of Wyoming 
in 1983. In 1985 he conducted tleldwork and research in Somalia to fulfill the requirements 
for a Master of Science degree. 

He enrolled in the Food and Resource Economics Department at the University of 
Florida in 1985. In 1988, he returned to Honduras to gather data for his Ph.D. thesis from 
the cooperatives with which he had worked as a Peace Corps volunteer. His doctorate was 
awarded in December, 1996. 



211 



I certify that I have read this study and that in ray opinion it conforms to acceptable 
standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation 
for the degree of Doctor of Philosophy. 




timothy G. Taylor, Chair 
Professor of Food and Resource 
Economics 



I certify that I have read diis study and that in my opinion it conforms to acceptable 
standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation 
for the degree of Doctor of Philosophy. 





UmaLele, Co-Chair 
Graduate Research Professor 
Professor of Food and Resource 
Economics 



I certify that I have read this study and that in my opinion it conforms to acceptable 
standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation 
for the degree of Doctor of Philosophy. 




Chris O. Andrew 
Professor of Food and Resource 
Economics 



I certify that I have read this study and that in my opinion it conforms to acceptable 
standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation 
for the degree of Doctor of Philosophy. 




^lies L. Scale, Jr. 
Professor of Food and Resource 
Economics 



I certify that I have read this study and that in my opinion it conforms to acceptable 
standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation 
for the degree of Doctor of Philosophy. 




rdi 

'of History 



This dissertation was submitted to the Graduate Faculty of the College of Agriculture and 
to the Graduate School and was accepted as partial fulfillment of the requirements for the degree 
of Doctor of Philosophy. f\ 

December, 1996 Dean, College of Agriculture 




Dean, Graduate School 



i 
it