Front Cover
 Front Matter
 Title Page
 Table of Contents
 List of Tables
 List of Illustrations
 The research issues and approa...
 Commercialization of Guatemala's...
 Initiators and operators of export...
 Effects of the new export crops...
 Effects of the new export crops...
 Policy conclusions and general...
 Appendix: Programming model
 Back Cover

Title: Nontraditional export crops in Guatemala
Full Citation
Permanent Link: http://ufdc.ufl.edu/UF00085371/00001
 Material Information
Title: Nontraditional export crops in Guatemala
Physical Description: Book
Creator: Von Braun, Joachim,
Publisher: International Food Policy Research Institute,
Copyright Date: 1989
 Record Information
Bibliographic ID: UF00085371
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: 19518932 - OCLC

Table of Contents
    Front Cover
        Front Cover
    Front Matter
        Page 1
    Title Page
        Page 2
        Page 3
    Table of Contents
        Page 4
    List of Tables
        Page 5
        Page 6
    List of Illustrations
        Page 7
        List of Illustrations 2
        List of Illustrations 3
        Page 10
        Page 11
        Page 12
        Page 13
    The research issues and approach
        Page 14
        Page 15
        Page 16
        Page 17
        Page 18
        Page 19
    Commercialization of Guatemala's agriculture
        Page 20
        Page 21
        Page 22
        Page 23
        Page 24
        Page 25
    Initiators and operators of export cropping in small holder agriculture: The cuatro pinos cooperative
        Page 26
        Page 27
        Page 28
        Page 29
        Page 30
        Page 31
        Page 32
        Page 33
    Effects of the new export crops on agricultural production, income, and employment
        Page 36
        Page 37
        Page 38
        Page 39
        Page 40
        Page 41
        Page 42
        Page 43
        Page 44
        Page 45
        Page 46
        Page 47
        Page 48
        Page 49
        Page 50
        Page 51
        Page 52
        Page 53
        Page 54
        Page 55
        Page 56
        Page 57
        Page 58
        Page 59
        Page 60
        Page 61
        Page 62
        Page 63
        Page 64
        Page 65
        Page 66
    Effects of the new export crops on expenditures, consumption, and nutrition
        Page 67
        Page 68
        Page 69
        Page 70
        Page 71
        Page 72
        Page 73
        Page 74
        Page 75
        Page 76
        Page 77
        Page 78
        Page 79
        Page 80
        Page 81
        Page 82
        Page 83
        Page 84
        Page 85
        Page 86
        Page 87
        Page 88
        Page 89
    Policy conclusions and generalizations
        Page 90
        Page 91
        Page 92
    Appendix: Programming model
        Page 93
        Page 94
        Page 95
        Page 96
        Page 97
        Page 98
        Page 99
    Back Cover
        Page 100
        Page 101
Full Text


Joachim von Braun
David Hotchkiss
Maarten Immink



The International Food Policy Research
Institute was established in 1975 to identify
and analyze alternative national and inter-
national strategies and policies for meeting
food needs in the world, with particular em-
phasis on low-income countries and on the
poorer groups in those countries. While the
research effort is geared to the precise ob-
jective of contributing to the reduction of
hunger and malnutrition, the factors involved
are many and wide-ranging, requiring analy-
sis of underlying processes and extending
beyond a narrowly defined food sector. The
Institute's research program reflects world-
wide interaction with policymakers, adminis-
trators, and others concerned with increasing
food production and with improving the
equity of its distribution. Research results
are published and distributed to officials and
others concerned with national and inter-
national food and agricultural policy.
The Institute receives support as a consti-
tuent of the Consultative Group on Interna-
tional Agricultural Research from a number
of donors including Australia, Belgium,
Canada, the People's Republic of China, the
Ford Foundation, France, the Federal Re-
public of Germany, India, Italy, Japan, the
Netherlands, Norway, the Philippines, the
Rockefeller Foundation, Switzerland, the
United Kingdom, the United States, and the
World Bank. In addition, a number of other
governments and institutions contribute
funding to special research projects.

Board of Trustees

Dick de Zeeuw
Chairman, Netherlands
Eliseu Roberto de Andrade Alves
Vice Chairman, Brazil
Yahia Bakour
Anna Ferro-Luzzi
Yujiro Hayami
Gerald Karl Helleiner
Dharma Kumar
Anne de Lattre
James R. McWilliam
Harris Mutio Mule
Sukadji Ranuwihardjo
Theodore W. Schultz
Leopoldo Solis
M. Syeduzzaman
Charles Valy Tuho
C6te d'Ivoire
John W. Mellor, Director
Ex Officio, U.S.A.


Joachim von Braun
David Hotchkiss
Maarten Immink

Research Report 73
International Food Policy Research Institute
in collaboration with the
Institute of Nutrition of Central America and Panama
May 1989

Copyright 1989 International Food Policy
Research Institute.
All rights reserved. Sections of this report may
be reproduced without the express permission
of but with acknowledgment to the International
Food Policy Research Institute.

Library of Congress Cataloging
in Publication Data

Von Braun, Joachim, 1950-
Nontraditional export crops in Guatemala:
effects on production, income, and nutrition /
byJoachim von Braun, David Hotchkiss, Maarten
p. cm. (Research report / International
Food Policy Research Institute ; 73)
"In collaboration with the Institute of Nu-
trition of Central America and Panama."
Bibliography: pp. 97-99.
ISBN 0-89629-075-1
1. Vegetable trade-Guatemala. 2. Exports-
Guatemala. 3. Farms, Small-Guatemala.
4. Food supply-Guatemala. 5. Agricultural
laborers-Guatemala. 6. Household surveys-
Guatemala. I. Hotchkiss, David, 1959-
II. Immink, Maarten D. C. (Maarten Dirk Cornelis)
III. International Food Policy Research Institute.
IV. Institute of Nutrition of Central America and
Panama. V. Title. VI. Series: Research report
(International Food Policy Research Institute) ; 73.

HD9225.G92V66 1989



1. Summary 11
2. The Research Issues and Approach 14
3. Commercialization of Guatemala's
Agriculture 20
4. Initiators and Operators of Export
Cropping in Smallholder Agricul-
ture: The Cuatro Pinos Coopera-
tive 26
5. Effects of the New Export Crops
on Agricultural Production, In-
come, and Employment 36
6. Effects of the New Export Crops
on Expenditures, Consumption,
and Nutrition 67
7. Policy Conclusions and General-
izations 90
Appendix: Programming Model 93
Bibliography 97


1. Village-level information: sam-
pling in 1983 and 1985
2. Value of agricultural exports from
Guatemala, 1975-84
3. Farm-size distribution in Guate-
mala, 1950, 1964, and 1979
4. Specialization in crop produc-
tion, by farm size, 1950, 1964,
and 1979
5. Average farm size, population,
and land use pattern in Santa
Maria Cauqu6, 1963-85
6. Area under export vegetable
crops marketed by the Cuatro
Pinos cooperative, 1980-85
7. Effect of exchange-rate policy on
export vegetable producer price:
an example from a snow pea sale
by Guatemala to the United
States, July 1985
8. Marketing costs of a fresh export
vegetable (snow peas) from
Guatemala to the United States,
9. Farm size and cropping patterns
of members and nonmembers of
the Cuatro Pinos cooperative,
10. Probit estimate of export crop
11. Farm-size distribution of cooper-
ative members and nonmembers
12. Cost of production and gross
margins of export vegetables and
subsistence crops, 1984/85

13. Gross margins of export and tra-
18 ditional crops per hectare and
per person-day of family labor,
2 by farm size, 1984/85
14. Cropping patterns of cooperative
members and nonmembers, by
22 farm size, 1985
15. Relative quality of land of cooper-
ative members and nonmembers
and of land used for the new ex-
port crops
27 16. Landownership of parcels and
use for new cash crops
17. Shares of men, women, and chil-
30 dren in total family labor of
cooperative members, by crop
18. Average family labor used per
hectare by cooperative members
and nonmembers, by farm size
32 and crop
19. Wages paid for hired farm labor
by cooperative members and non-
members, by farm size and crop
34 20. Direct employment effects of the
new export vegetables, by farm
21. Consumption of own production
36 and net purchases of maize in
cooperative member and non-
39 member households, 1985
22. Farmers' attitudes toward grow-
41 ing maize
23. Reasons for growing maize stated
by farmers, by duration of co-
43 operative membership

24. Production of subsistence maize
and use for consumption in farm
households, 1985
25. Yields of subsistence food crops
on cooperative member and non-
member farms, 1985
26. Area allocation to maize and the
effects of export vegetable pro-
duction: regression model
27. Maize yields and effects of ex-
port vegetable production: re-
gression models
28. Effects of new export vegetables
on shadow cost of subsistence
food production and selected
other variables
29. Percentage of households receiv-
ing income from off-farm activi-
ties, by farm size and cooperative
30. Determinants of off-farm in-
come: regression model
31. Expenditures on foods (pur-
chased and own-produced) and
nonfoods, by farm size and dura-
tion of cooperative membership,
32. Food (including own-produced)
and nonfood expenditures of
cooperative members, 1985
33. Food (including own-produced)
and nonfood expenditures of non-
members of cooperative, 1985
34. Food (excluding own-produced)
and nonfood expenditures of
cooperative members and non-
members, 1983

35. Food and nonfood per capital ex-
penditures of cooperative mem-
56 bers and nonmembers, 1983 and
36. Change in per capital expendi-
57 tures, by cooperative member-
ship and duration of member-
ship, 1983-85
58 37. Determinants of budget shares
to food in cooperative member
and nonmember households,
59 1985: regression model
38. Incremental expenditures on
food by cooperative member and
nonmember households, by ex-
62 penditure quartile, 1985
39. Food availability and composition
of food consumption by expendi-
ture quartiles (mean values) in
64 the sample, 1985
40. Food availability and composi-
6tion of food consumption in co-
operative member and nonmem-
ber households, 1985
41. Availability of calories in house-
70 holds and export vegetable pro-
duction: regression model
42. Purchasers of food items in house-
71 hold transactions
43. Selected social indicators for co-
operative members and non-
72 members
44. Nutritional status of children
under 60 months in the study
area and other locations in Guate-
73 mala


45. Prevalence of malnutrition in the
Western Highlands of Guatemala
46. Prevalence of malnutrition among
children of cooperative mem-
bers and nonmembers, aged 6-
60 months, 1983 and 1985
47. Income levels and prevalence of
malnutrition among children of
cooperative members and non-
members, 1983 and 1985
48. Effects of income and income
source and composition on nutri-
tional status: multivariate analy-
sis for children aged 6-120
49. Determinants of change in nu-
tritional status and the role of
export crop production: multi-
variate analyses for cohort of

1. Flow of analysis for evaluation of
83 household-level effects of the com-
mercialization process
2. Snow pea prices paid to farmers
by cooperative, 1984-87
8 3. Marketing channels for fresh ex-
port vegetables from Guatemala
4. Cropping calendar of subsistence
84 crops, traditional vegetables, and
export vegetables in the Western
Highlands, 1984/85
5. Labor inputs for traditional crops
and new export vegetables on co-
85 operative members' farms, 1985
6. Transition of cooperative mem-
ber and nonmember households
between expenditure terciles from
1983 to 1985


Modernization of traditional agriculture entails increased participation of the small-
holder sector in the exchange economy. The achievement of this participation requires
an open trade regime, domestic policies that ensure against market failures, and public
policy that effectively permits use of new production technology for sustained growth.
To open up these opportunities to small farmers, investment in rural infrastructure is
essential, as is investment in education that will enable these farmers to participate as
entrepreneurs in the growth process. In order to reach out to the landless and land-scarce
households, the growth process must stimulate employment and increased returns to
land. Nontraditional vegetables for export have a high labor content and therefore
promise to help foster rural modernization.
In this study of nontraditional export crops and traditional smallholder agriculture
in Guatemala, Joachim von Braun, David Hotchkiss, and Maarten Immink highlight
the potentials and risks of export orientation in smallholder agriculture for food security.
The policy implications of the report reach far beyond the study area in Central America.
The multidisciplinary team of IFPRI and the Institute of Nutrition of Central America
and Panama (INCAP) has gone far toward tracing the critical linkages between economic
development and nutritional improvement. Two lessons of the study are of critical
importance for policy. First, growth in staple food production, stimulated jointly with
diversification into nontraditional crops, is necessary to actually capture the gains from
specialization in typically risky market environments. Second, joint operation and devel-
opment of the health and sanitation infrastructure in rural areas is required in order
to translate the growth effects into nutritional welfare effects for the poor.
This study, which is a component of IFPRI's ongoing research effort in the field of
commercialization of agriculture for food security and poverty alleviation, provides
evidence that the income and employment effects of cash cropping can be considerable
and, if accompanied by appropriate public policy, can make a major contribution to
eliminating hunger and malnutrition.

John W. Mellor
Washington, D.C.
May 1989


This research project was jointly designed and its first phase jointly directed with
Victor Valverde of INCAP, whose unexpected death in June 1986 came as a shock to
his friends and colleagues. This project is one of many research activities stimulated
by Victor to improve the understanding of poor people's living conditions and especially
of their nutritional situation.


This research project is based on complex sample surveys whose successful execu-
tion was made possible by the patient respondents in six Guatemalan villages and
careful enumerators under the experienced supervision of INCAP. Mireya Palmieri was
instrumental in the design and execution of the survey work. Local support of the
research by the Cuatro Pinos cooperative, and in particular by its executive manager,
Tulio Garcia, was essential for appropriate implementation of the research and interpre-
tation of results.
Earlier drafts have been constructively reviewed by Nancy Pielemeyer, Judith
McGuire, Allen Rosenfeld, Shubh Kumar, Rafael Cells, Shlomo Reutlinger, Per Pinstrup-
Andersen, Eileen Kennedy, Harold Alderman, and Graciela Wiegand, as well as anony-
mous reviewers. Research assistance at INCAP was provided by Jorge Alarc6n. We are
grateful for the funding of the research by the U.S. Agency for International Development
under Grant No. OTR-0096-6-55-4355-00.



Increasing foreign exchange problems and deteriorating prices of traditional export
commodities are leading agricultural policymakers to seek diversification in export crop
production. Export vegetables, which are nontraditional crops, appear to be a promising
option because of their high labor intensity and expanding demand in industrialized
countries. This study deals with a case of export vegetable production and its effects
on food production, employment, consumption, and nutrition in Guatemala.
Guatemala's agriculture has shifted away from food production to agroindustrial
crops. Food crops covered 58 percent of the country's crop area in 1950 compared
with 37 percent in 1979. Small farms decreased their basic food crop area from 97
percent to 87 percent in this period.
The focus of this study is the recent introduction of labor-intensive production of
vegetables for export in the traditional small-farm sector in the Western Highlands-an
area well known for its problems of poverty and malnutrition. Besides considerable
research on the "cash cropping-nutrition" issue, the study provides both cross-sectional
and longitudinal analyses of effects. The research is based upon two detailed rural
household surveys (400 families) that were undertaken in 1983 and 1985. The sample
is divided into two groups of households-those who produce the new export vegetables
(snow peas, broccoli, cauliflower, and parsley) under a cooperative scheme and those
who do not. Differences in duration of participation (one to seven years) in the export
crop scheme-the Cuatro Pinos cooperative-characterize the subsample of the export
crop growers.
The new export vegetables were rapidly adopted by the smallest farmers (average
0.7 hectare). The model analysis in the study shows that in the early phase of adoption,
small farmers with somewhat larger holdings (1-2 hectares) and households that had
no reasonably well secured off-farm income source showed a significantly higher prob-
ability of adoption. Access to good roads and infrastructure also increased adoption rates.
The new vegetables have certain risks for the small farmers due to possible crop
failures, price collapses on the export market, or a breakdown of the marketing institu-
tions. Relative production variability of the new crops is not higher than in the traditional
crops, but because the new crops are much more input-intensive the potential loss
relative to household income is higher than for the traditional crops. The price variability
of the new crops-especially of snow peas, the most important one of them-is extreme.
In 1985, prices fluctuated between 0.10 and 2.00 quetzals per pound, but farmers can
partially cope with this variability by spreading the growing seasons and having a long
harvest period (12 weeks). Recently, in addition to a multinational company and the
cooperative, other traders have handled the export channel. Also, local processing and
freezing of fresh produce have been initiated. These developments reduce the risk of
a sudden collapse of the marketing channel.
Nontraditional export crops are substantially more profitable to farmers than tradi-
tional crops. Net returns (gross margins) per unit of land of snow peas are on average
15 times those of maize-the most important traditional crop. Returns of the new
crops per unit of family labor were about twice as high as for maize and 60 percent
higher than for traditional vegetables produced for local markets in 1985. The input
costs per hectare for snow peas, however, are on average about 4 times higher than

for traditional vegetables and 13 times higher than for maize. Short-term financing of
inputs poses a problem to small farmers and indicates the importance of rural credit.
Farm households outside the cooperative grow traditional subsistence crops (maize
and beans) on 78 percent of their land, whereas participants in the scheme grow those
crops on 52 percent of their land. The smallest cooperative farms allocate the highest
shares of land to the new export crops.
Nevertheless, most export crop producers tend to have higher amounts of maize
available (per capital) for consumption from own produce than other farmers of the
same farm size, because cooperative members' maize and bean yields are 30 percent
higher on average than nonmembers' yields. A combination of factors is responsible
for this increase in yields; fertilizer inputs are increased and cropping practices are
more labor-intensive (more weeding labor). Farmers with the most school education
were found to have even higher yields at given input levels.
Analysis with the help of a consistent farm household model based on the survey
data shows that with new export crops the shadow cost of maize produced for own
consumption increased drastically. The difference between the shadow cost and the
actual market price (0.29 quetzal in 1985) maybe interpreted as an "insurance premium"
that farmers are willing to pay for the degree of self-sufficiency they actually maintain.
Nontraditional export crops created local employment directly on farms and indirectly
through forward and backward linkages and multiplier effects resulting from increased
income spent locally. Combining farm-level employment with the roughly estimated
employment created through the input supply and output marketing yields an overall
21 percent increase in agricultural employment in the six communities where the
cooperative functions. Labor input in agriculture increased by 45 percent on the farms
producing export vegetables. About half of this increase is due to family labor and half
to hired labor. A substantial share of the incremental increase in family labor is from
women and children. As a consequence of increased on-farm employment, off-farm
work and interregional migration of members of export vegetable producers' households
are found to be reduced.
The export crop production scheme led to increased income in the participants'
households. This increase between the two surveys (1983-1985) was most pronounced in
the group of new adopters, in which expenditures-used as an income proxy-increased
by 33 percent. The income gains were highest among the adopters on the smallest
farms, thus the new export crops had a favorable effect of moving the poorest upward
on the income scale.
At same-income levels, export crop-producing farm households spend less of their
additional income on food than traditional-crop households. While nonmembers in the
lowest quartile on the income scale spend 61 percent of additional income on food,
cooperative members in the same income class spend 53 percent. Additional income
increases calorie acquisition significantly but at decreasing rates at the margin. Member
households in the lowest half of the income scale increase their calorie consumption
by 2.8 percent with a 10 percent increase in income, while nonmember households
increase theirs by 4.4 percent.
The production- and income-related analysis concluded with favorable effects of
the nontraditional crops for food crop productivity, employment, income growth, and
income distribution. The expenditure and food consumption analysis found that incre-
mental income earned from the nontraditional crops tends-at same-income levels-to
be spent relatively less on food than other income; this is also reflected, although to
a lesser extent, in calorie availability. Thus, food expenditures and consumption in-
creased relatively less than expected. Improvement in the nutritional status of children,

most significantly in decreased wasting, is associated with increased income and food
consumption in export crop-producing households. The nutritional benefits of economic
growth, as shown in this study, are substantial but can be further enhanced by appro-
priate health- and nutrition-oriented social infrastructure. The effects of health programs
conducted by the export crop cooperative in participating communities support this
Especially in the late 1970s and early 1980s, steps to alleviate poverty and improve
living conditions in Guatemala were constrained by the economic and political environ-
ment. The case study shows, however, that with appropriate access to resources and
markets and effective assistance in institution-building at the community level, the
poor in the Western Highlands can substantially improve their income and welfare.



Commercialization of Traditional Agriculture
An increasing number of low-income countries are facing crucial strategic decisions
on how to cope with short- and long-run food security problems. At the core of these
strategic decisions is the appropriate choice of policies to promote production of export
crops, cash crops for the domestic market (food and nonfood), and subsistence food crops.
Many developing countries are encouraging the increased production of export
crops as a way to generate foreign-exchange earnings and fiscal revenues, to increase
the income of small landholders, and to provide employment for the rural poor. However,
critics of policies that advocate cash crop production argue that the potential benefits
have never materialized and, more important, that in areas where cash crop production
has increased, food consumption and the nutritional status of the poorest households
have deteriorated. A comprehensive review of the existing literature and earlier research
on the issue shows mixed results (Braun and Kennedy 1986). This is not surprising,
given the great variety of cash crops and production conditions in general.
In developing countries, increased market integration of semisubsistence agriculture
appears unavoidable. Rapid urbanization, growth of the rural nonagricultural sector,
and technological change in agricultural production are the major driving forces of this
commercialization process. Urbanization without increased rural-urban market integra-
tion would lead to volatile dualistic structures and import dependence.
On the basis of existing research, it is evident that critical relationships that deter-
mine food consumption and nutrition are affected by increased commercialization.
These effects may be positive or negative. At the macroeconomic level, an issue of
concern is whether foreign exchange generated through export cropping is actually
used for imports of goods and services that improve the food consumption and nutritional
situation of the poor. Foreign-exchange regulations and taxation of export crops, along
with import controls by governments, may lead to distortions that prevent the poor,
including small farmers in the export sector and other rural households, from having
access to the direct and indirect benefits of the specialization.
This study concentrates mainly on the household-level effects of cash cropping in
rural areas. At this micro level the outcome depends on changes in real income, income
distribution, income composition, and income control (by men or women). How do
these factors translate into household food consumption? What are the effects on time
allocation (especially for mothers), and on health and sanitary factors? At this point,
no clear ranking of factors is possible on the basis of existing research. A number of
studies show, however, that the positive effect of increased cash income on calorie
consumption may be quite small, even among the poor.' This may be a result of changes
in income composition and income control within the household.
A crucial question for policy and program design is whether potential adverse effects
of increased cash cropping on nutrition are actually observed and, if so, whether they
are of a short- or long-term nature. This is not to say that short-term effects for one to

' See the review in von Braun and Kennedy 1986, 55-59.

two years should not be an issue of concern. But appropriate and efficient policy
measures to balance potential adverse effects are dependent on the time frame of the
problem. Whereas short-term problems may be dealt with mainly by adjustments in
the timing of project implementation and a combination of measures such as temporary
income support, price subsidies, and nutrition education, long-term adverse effects
require very different policy instruments that have the potential to improve and stabilize
living conditions for the losers in the commercialization process. Employment genera-
tion in rural areas would be a major element of these policies.
The uneasiness about the above-mentioned critical relationships between agricul-
tural production and nutrition in the commercialization process suggested a series of
detailed studies that are being executed at IFPRI in collaboration with other institutions.

Theoretical Approach and Concept
This study on the commercialization of smallholder agriculture in Guatemala looks
into the introduction of nontraditional vegetables for export. It was clear at the outset
that this change had substantial effects on agricultural production and employment in
the study area. The order of magnitude of these effects and the effects on income,
consumption, and nutrition, however, were not clear at all. The precise concern was
that expansion of a crop for export in an area with a well-known nutrition problem
might have adverse effects on the availability and security of food and might further
aggravate the nutrition problem. If the export crop scheme increased employment and
income of the poor, a related issue that stimulated the research was the provision of
background understanding needed to ensure rapid translation of income growth into
improved physical welfare, especially nutrition, in the households.
The theoretical concept of the household-level analysis of commercialization effects
takes a disaggregated approach to tracing the consequences for different types of house-
holds and different groups inside the households. It is not a priori assumed here that
incremental employment and income from the new crops leaves household utility
functions unchanged. It is now widely recognized that farm households are not neces-
sarily homogeneous units of decisionmaking.2 Profound changes in the opportunities
for income earning on the farm-be it through new technology or new market outlets-
may have profound implications for division of labor and for relative control of income
shares, which may change budget allocations within the household beyond the pure
income effect. This study attempts to trace such effects and to quantify their impact
on the consumption and nutrition effects of increased commercialization of traditional
agriculture. Understanding these relationships is crucial to identifying policy options
that avoid adverse effects of commercialization on consumption and nutrition in poor
households and enhance positive ones.
The research focuses on the effects of the commercialization process on household-
level food security. Food security, in this context, is understood in the broad sense as
the ability of households and their members to acquire sufficient quantities of food
over time, whether from own produce or from the market. Related to this, the effects
of change in commercialization on the actual nutritional situation of children is assessed.
The main relationships studied in this evaluation of increased commercialization are
its effects on agricultural production (especially food) and on employment and income
(on-farm, off-farm), and the extent to which these translate into effects on food and

2 See Folbre 1986 and the literature quoted therein.

nonfood expenditures, food consumption, and nutrition. Clearly, these issues are related
to each other. A simplified overview of the relationships as affected by commercialization
at the household level is provided in Figure 1. This figure also provides an overview
of the steps of analysis but does not depict the complex dynamics involved.
Figure 1-Flow of analysis for evaluation of household-level effects of the
commercialization process

Adoption of new
crops by farmers

Introduction of new cash
crops (export vegetables)

Effects on
agricultural income
and employment

Effects on total income
(including level, by source and


Overview of the Report
The commercialization process at the micro farm-household level should be under-
stood in the context of the macroeconomic environment and its political economy. A
review of commercialization of Guatemala's agriculture is provided at the outset. The
introduction of new cash crops is evaluated in its institutional context. This requires
a focus on the actual making and operating of the commercialization process; success or
failure of a program is largely determined in this sphere, which is much underresearched.
Therefore, those who play a role in commercialization are examined before the house-
hold-level effects are evaluated.
At the farm-household level, the process and determinants of adoption of the new
crops are evaluated. The main questions addressed are who are the (early) adopters
and what are their characteristics? In the context of this case study, this leads directly
into the issue of competition and complementarity between nontraditional and tradi-
tional crops, on-farm and off-farm labor supply, and division of labor in the households.
How is food availability from own production affected? Where does the increased labor
input on the farm stem from? Who in the household controls the incremental farm income?
From the income effects, the effects for household resource allocation to food and
nonfood expenditures are traced. Special focus is on food expenditures and food (calorie)
availability. What share of incremental expenditure in export crop-producing households
versus other households at same-income levels is spent on food and what types of food?
To what extent is food availability in terms of calories improved?
Finally, these effects are traced to the nutritional status of children in the households.
How is nutritional status-measured in anthropometric terms (weight, height-for-age)-
affected by changes in food availability and the health and sanitation environment of
the households?
The study concludes with lessons for policy from this particular case and an attempt
to identify generalizable findings.

Survey Methods and Data
The household-level data of this research are based on representative surveys under-
taken in 1983 and 1985 in the six villages where the Cuatro Pinos cooperative was
active. The sample is based on a census in the villages done in 1983 (INCAP 1985).
A roughly equal number of members of the cooperative (n = 195)-that is, growers of
the new export crops-and nonmembers (n = 204) were drawn at random by village
from the census information. To ensure a reasonable coverage in the smaller villages,
the sample was biased toward the four smallest communities among the six villages.
This brings the sample closer to the prevailing village pattern in the Western Highlands.
The proportional adjustments of the sample by village size led to a coverage of 38-75
percent of the cooperative members in each community (average, 47 percent) and
8-17 percent of nonmember households (average, 11 percent) in these communities
(Table 1).
The same households were surveyed in 1983 and 1985. They were visited between
November and January of 1983/84 and 1985/86. Conducting both surveys during the
same time of the year avoids the seasonality effects that might disturb comparisons
between the two rounds.3

SSeasonality in food consumption, however, does not appear to be very pronounced in Guatemala. See /
Valverde et al. 1985b.

Table 1-Village-level information: sampling in 1983 and 1985
San El Santa Maria
Category Matho Rej6n Cauqu& Pacul Pachall Santiago Total
Size of village (number of house-
holds, 1983) 195 180 445 95 141 1,250 2,306
Cooperative member households, 1983 21 15 65 32 38 248 419
Nonmember households, 1983 174 165 380 63 103 1,002 1,887
1983 sample
Cooperative members 13 10 36 24 18 94 195
Sample population as percent
oftotala (62) (67) (55) (75) (47) (38) (47)
Nonmembers 29 27 32 11 18 87 204
Sample population as percent
oftotala (17) (16) (8) (17) (17) (9) (11)
1985 sample
Cooperative members 12 15 31 20 17 84 179
Nonmembers (farmers and non-
farmers) 28 23 37 14 20 100 222
Nonmembers (farmers) 24 23 34 12 16 70 179
Years of cooperative membership in 1985
Lessthan3 5 15 3 7 1 19 50
3-4 7 ... 14 4 9 19 53
5-7 ... ... 14 9 7 46 76

Sources: Institute of Nutrition of Central America and Panama survey, 1983; and Institute of Nutrition of Central
America and Panama/International Food Policy Research Institute survey, 1985.
a The percent figures in parentheses represent the percentage of total population covered in the communities by the
sample survey.

The composition of the 1985 sample is affected by changes in household characteris-
tics since the 1983 survey. Some households split when the younger generation started
its own households, some cooperative members dropped out of the cooperative, and
some nonmembers became members. Also, some households could no longer be inter-
viewed because of long-term absence. Between 1983 and 1985, 9 percent of the
member sample left the cooperative and 6 percent of the nonmember sample became
members. Taking the stratification of the sample into account, these numbers suggest
a net increase of members by 19 percent since 1983. This roughly corresponds to the
actual change in the membership statistics of the cooperative between 1983 and 1985.
The sample is spread over early and late adopters. Forty-two percent of the sampled
households of the cooperative members have been in the scheme for as long as five
to seven years. Newcomers are spread over all six communities, while the early adopters
are all in the four founding villages of the cooperative (see Table 1).
The field data collection for the 1983 and 1985 surveys was done by the experienced
survey staff of the Institute of Nutrition of Central America and Panama (INCAP).
The household-level information collected includes
1. demographics of the household (employment, schooling);
2. health, anthropometrics of children under 10 years of age, and child-feeding
3. housing conditions;
4. access to services;
5. nonfarm income (by individual, by source);
6. agricultural production (inputs, outputs, labor at field level by crop, size of fields,
produce sales, input purchases, animal production, land quality);
7. food expenditures and consumption of own-produced food; and
8. nonfood expenditures.

The various types of information are covered over recall periods specific to the
nature of the data. Agricultural production covers the crop years 1982/83 and 1984/85
(May-April), and off-farm income covers the 12 months preceding the surveys
(November-October 1982-83 and 1984-85). Food and nonfood expenditures are
monthly (October 1983, October 1985), with an annual recall for lump sum nonfood
expenditures (especially durable goods) added to the 1985 survey that covers November
1984 to October 1985.
In a subsample of the 1985 survey consisting of 40 households in two communities
(El Rej6n and Santiago de Sacatep6quez), a detailed assessment of intrahousehold
decisionmaking and of sexual division of labor and time allocation of household members
was undertaken parallel to the large survey (Nieves 1987).



Guatemala is the third largest in area of the Central American republics, after
Nicaragua and Honduras, but its population of about 8.4 million (1984 figure) exceeds
that of the latter two countries combined. About two-thirds of the population lives in
rural areas; around 60 percent of them are indigenous people who are descendants of
the Maya. The indigenous population is mainly concentrated in the Western Highlands
of Guatemala where this study was conducted.
The agricultural sector provides about 50 percent of the country's employment and
accounts for 25 percent of the gross domestic product (GDP) in the mid-1980s. Agri-
cultural exports hold a share of about 65 percent in total merchandise exports, thus
making agriculture the primary foreign-exchange earner of the economy.
Guatemala's highly dualistic agricultural structure is well documented.4 A modern,
export-oriented, large-scale farm sector and a traditional, subsistence-oriented, small-
scale sector have long coexisted. The two sectors are not independent but rather are
closely linked through the rural labor market. Labor from the traditional sector in the
Western Highlands (a sector operating on an agricultural-resource base per household
that in most cases cannot support the bare survival requirements of the family) seeks
employment through interregional migration either to the areas of the large-scale export
crop sector-mainly in the lower altitude regions-or, in recent decades, to the urban
services sector.
This pattern of export crop production and its interaction with the subsistence farm
sector has been in existence for decades. Its effects on the subsistence farm sector are
substantial (Schmid 1968, 33-45). Yet the focus of this research is not to study these
indirect effects but the recent changes in the subsistence sector itself, namely, those
resulting from the shift into export crop production by small farmers in the Western
Highlands. The traditional dualistic pattern of subsistence and export crop sectors,
however, must be kept in perspective to assess the implications of the change in
commercialization in the small-farm sector. Clearly, this subsector-though mainly
subsistence-oriented in crop production-was already "commercialized" by selling a
high share of its labor rather than its crops.

Exports from a Dualistic Agricultural Sector
Agricultural exports from Guatemala may be grouped into traditional and nontrad-
itional exports. The traditional ones in their order of share in total agricultural exports
are coffee, cotton, sugar, bananas, and beef. These crops account for 76 percent of
agricultural exports in the mid-1980s (Table 2). Among the important nontraditional
agricultural exports that account for the remaining 24 percent are cardamom, vegetables,
flowers and plants, fruits, and sesame seed. Since the mid-1970s the share of agricultural
exports in total merchandise exports has remained stable, but the composition of

4 See Nyrop 1983 and the extensive bibliography in this source; also World Bank 1978.

Table 2-Value of agricultural exports from Guatemala, 1975-84
ExportItem 1975 1980 1984
(US$ million)
Traditional agricultural exports
Coffee 164 464 361
Cotton 74 166 72
Sugar 116 69 71
Bananas 35 45 55
Beef 17 29 13
Subtotal 406 773 572
(Percent of total agricultural exports) (92) (79) (76)
Nontraditional agricultural exports
Cardamom 10 56 100
Vegetables, flowers and plants, fruits 9 68 43
Other 15 75 39
Subtotal 34 199 182
(Percent of total agricultural exports) (8) (20) (24)
Total agricultural exports 440 972 754
Total exports 651 1,520 1,132
(Agricultural exports as percent of
total exports) (67) (64) (67)

Source: Based on data from Bank of Guatemala, "Economic Data, 1985" (Bank of Guatemala, Guatemala City,
a Includes essential oils, fish, gum, honey, cocoa, cotton seed, sesame seed, cotton lint.

agricultural exports has become more diverse. The share of traditional agricultural
exports dropped from 92 percent in 1975 to 76 percent in 1984, although traditional
exports grew in absolute dollar terms. Increased diversification of the agricultural export
sector is a stated policy objective to reduce instability in foreign-exchange earnings
due to price fluctuations-for example, of coffee-in international markets (Banco
Interamericano de Desarrollo 1986, 74).
Landownership in Guatemala is extremely skewed. The Gini coefficient, which
ranges from zero in a situation of perfect equality to 100 in a situation of maximum
inequality, was 85.1 for land distribution in Guatemala in 1979-higher than for all
other Latin American countries (Hough et al. 1982, 1). The Gini coefficient increased
from 82.4 to 85.1 between 1964 and 1979, indicating further inequality (Hough et
al. 1982, 2). Two percent of farmers held 67 percent of the agricultural land-land
that is generally of better quality than the land cultivated by small farmers.
For those at the bottom of the land distribution, population growth leads to rapid
reduction of average farm size. From 1964 to 1979, the average farm size of those
under 1.4 hectares (2 manzanas) decreased from 1.0 to 0.7 hectare. Sixty percent of
Guatemalan farms fall in this group that cultivates 4 percent of the land (Table 3).
Most of the subsistence farm households in the Western Highlands also fall in this
group; thus, not surprisingly, more than 90 percent of the sample survey households
are part of this farm-size class.
Total agricultural land in use increased by 0.8 percent per year between 1950 and
1979. Expansion into new lands did not provide any significant relief for the land
constraint burdening the small-farm sector, nor does it provide a potential solution for
this problem (Hough et al. 1982). The obvious solution-agrarian reform with redistribu-
tion of land from large-scale farms to small farmers-was attempted by governments
in the late 1940s and early 1950s, but the attempts were finally blocked when the
government was toppled in a coup in 1954 (Kinzer and Schlesinger 1983).

Table 3-Farm-size distribution in Guatemala, 1950, 1964, and 1979
Share of Farms Share of Area
FarmSize 1950 1964 1979 1950 1964 1979
(hectares) (percent)
Less than 1.4 47a 44 60 3a 3 4
1.4-3.5 29 31 21 6 7 6
3.5-44.5 22 23 17 19 23 23
44.5 or more 2 2 2 72 67 67
Total 100 100 100 100 100 100

Source: Based on data from SEGEPLAN, Agricultura, Poblacidn, y Empleo en Guatemala (Guatemala City: SEGE-
PLAN, 1984).
a In the 1950 census, farms with less than 0.04 hectare were excluded.

Guatemala's agriculture has continuously and substantially shifted away from staple
food production (which includes a large share of subsistence production) to cash crops
and production for exports. Basic food crops covered 58.0 percent of agricultural area
in 1950 compared with only 37.4 percent in 1979 (Table 4). Cash crops and export
crops increased their share in land use from 20.0 to 29.8 percent during the same
period. Although this change in cropping patterns mainly took place in the medium-sized
farms (3.5-44.5 hectares), the smallest farms are following the same pattern of change.
They decreased their basic food crop area from 96.7 to 87.4 percent in this period
and increased their area devoted to cash crops.
Since 1979 the area allocated to the major staple foods (maize and beans) has
increased somewhat, but yields show a downward trend that has made total staple
food production stagnant and reduced the per capital staple food production by a rate
of -0.3 percent per year between 1968 and 1982 (FIDA 1985, 57-58).

Table 4-Specialization in crop production, by farm size, 1950,1964, and 1979
Land Use in Share of Farm-Size Class
FarmSize Type of Crops' 1950 1964 1979
(hectares) (percent)
Less than 1.4 Basic food crops 96.7 91.1 87.4
Cash and export crops 3.3 8.5 12.2
Pasture ... 0.4 0.4
1.4-3.5 Basic food crops 93.5 90.1 84.6
Cash and export crops 6.2 8.4 14.0
Pasture 0.3 1.5 1.4
3.5-44.5 Basic food crops 84.8 68.0 64.4
Cash and export crops 10.8 12.6 19.1
Pasture 4.4 19.4 16.5
44.5 or more Basic food crops 18.8 14.4 13.7
Cash and export crops 35.1 32.1 38.4
Pasture 46.1 53.5 47.9
Total Basic food crops 58.0 41.3 37.4
Cash and export crops 20.0 23.1 29.8
Pasture 22.0 35.6 32.8

Source: Based on data from SEGEPLAN, Agricultura, Poblacidn, y Empleo en Guatemala (Guatemala City: SEGE-
PLAN, 1984).
a Basic food crops include maize, beans, rice, wheat, potatoes, and traditional vegetables. Cash and export crops
include sorghum, cotton, coffee, sugarcane, cardamom, sesame, groundnut, tobacco, rubber, and fruits. Pasture
includes permanent pasture and land for fodder crops.

How did overall food availability develop over time against this background of
change in production patterns toward exports and the slow growth in domestic food
production? Overall per capital staple food availability was stable in the 1960s but
declined in the 1970s-from an average of 134 kilograms per capital per year (in wheat
equivalent) in 1961-63 to 128 kilograms in 1981-83. In the same period, calories per
capital per day increased from 1,937 to 2,080 (FAO, various years). Obviously, relatively
more calories come now from nonstaple foods. It should be stressed that such country
averages do not really address the food situation properly, especially in countries with
such large spreads in income distribution as Guatemala.
Generally, developing countries tend to manage joint growth in the basic food crop
and cash crop subsectors or fail to achieve growth in either (von Braun and Kennedy
1986, 27-36). Guatemala, however, appears as an exception to this tendency. Its cash
crop sector was growing over the long term while its basic food crop sector stagnated
(von Braun and Kennedy 1986, 35). This may be explained by the highly dualistic
structure of Guatemala's agricultural sector. This structure does not accommodate
positive spillover effects from promotion of traditional export crops through credit,
inputs, market infrastructure, and so forth, to the basic food crops, as the two are
mainly grown on two very distinct types of farms-large scale versus small scale-as
well as in different locations.
The effects of increased commercialization through the introduction of new cash
crops for food crop production in the small-farm sector may, however, turn out to be
very different from the development path of the isolated expansion of agroindustrial
crops in the large-scale farm sector. In principle, positive linkages between new cash
crops and the promotion of traditional food crops could be established in this case.

Recent Variations in Agricultural Policy

In the early 1980s Guatemala's substantial export-led economic growth, with low
levels of general inflation and an impressively strong currency, experienced a crisis.
Between 1982 and 1985, per capital gross national product (GNP) was down by 20.5
percent in real terms (Banco Interamericano de Desarrollo 1986, 5). The Guatemalan
quetzal, which was valued at a fixed 1-to-1 rate against the U.S. dollar for more than
40 years, was devalued in 1984 and further devalued in 1985 to about Q3.00-US$1.00
in the parallel market. A product-specific system that allowed differential access to the
parallel-market exchange rate and imposed different shares of the export revenue to
be converted at the old 1-to-1 rate has led to numerous variable exchange rates-and
implicitly to a host of different export tax levels through exchange-rate regulation. For
instance, in early 1986, 25 percent of coffee dollars were to be exchanged at the
parallel rate and 75 percent at the official rate. Export vegetable dollars got better
treatment by an imposed share of 50 percent at the official rate.
This exchange-rate policy induced equivalent distortions on the import side. A
policy of using the foreign exchange acquired through the implicit taxation of exports
for importation of so-called essential agricultural imports (such as fertilizer and food)
at the old exchange rate was largely ineffective. Fertilizer prices roughly doubled from
1985 to 1986. Thus the input-intensive export crops came under pressure from both
sides-export taxation through partly maintained overvalued exchange rates, and the
full effect of the devaluation of domestic currency on the input price side. During
1980-84, export values declined faster among traditional export crops (-7.3 percent)

than nontraditional crops (-2.2 percent). On the basis of this experience, the govern-
ment policy for agriculture, as laid out in the 1984-86 National Development Plan,
emphasizes both diversification of export-oriented agricultural production and increased
production of food commodities.
The causes of the recent economic crisis must be seen in the context of both the
country's violent internal conflicts and the external economic factors, especially the
deterioration of terms of trade and substantially higher interest rates for capital invest-
ments. In a country with a very small public sector and extremely limited public services
for the poor, the economic crisis is assumed to have hit particularly hard the low-income
stratum of the population, which in Guatemala is a large proportion of the population.
Poverty in Guatemala is predominantly a rural problem and is particularly concen-
trated in the Western Highlands. A survey in 1980 classified 36.2 percent of the rural
population as absolute poor, as their income was too low to purchase an adequate diet.
These rural poor constituted 73.5 percent of all poor. Agricultural income per household
in the Western Highlands was about 40 percent below the average of other rural areas
in the country (Guatemala 1982).

Evolution of Commercial Agriculture
in the Large- and Small-Farm Sectors

The dualistic structure of Guatemala's agriculture, with large-scale farms versus
minifundas (mainly in the hands of indigenous farmers), is largely an inheritance of
the structural change introduced by the Spanish during the colonization of the country
(Nyrop 1983). With the introduction of coffee cultivation after the 1840s, much of the
best land in the highland departments was absorbed into expanding coffee haciendas.
The indigenous population who had been farming these lands for generations'were
forced to move to higher, less fertile lands in order to continue growing their subsistence
crops-maize and beans (Hough et al. 1982, 21-24). This change took place mainly
between 1870 and 1920.
Another major export-oriented change with long-term consequences, not only for
agriculture but also for the political stability of the country, emerged in the 1920s and
1930s when the United Fruit Company acquired large landholdings-mainly for banana
plantations in the fertile lowlands. Concessions to the company by the government
totaled about 190,000 hectares (Kinzer and Schlesinger 1983).
The basic effect of the traditional export orientation in Guatemala's agriculture was
an increased concentration of land in large farms and of the indigenous population in
the remaining high-altitude areas with unfavorable land quality. At times, forced labor
obligations were imposed on this population to fill the labor demand in the export crop
sector (Nyrop 1983). Through reduction of the land-resource base for the indigenous
population, the opportunity cost of labor on their own small holdings was reduced,
thus assuring a cheap labor supply to the large-scale farmers.
Technological change in the food crop sector was not exceedingly successful in
Guatemala (CGIAR 1984). Growth in yields of maize was 1.6 percent per year between
1971-73 and 1981-83. Only a small surplus of the traditional food crops in the small-farm
sector is produced for marketing, so these crops have not become a source of cash
income. In the typical Western Highlands situation, about 90 percent of the maize
grown is retained for own consumption. It is only recently that maize production has
increased on large-scale farms.

Export vegetables, the focus of this study, were introduced to Guatemala in the
mid- 970s with substantial foreign investment.5 Originally, the scheme operated with
an integrated production-processing (screening, packing, cooling) exportation system
in the hands of one company. Soon the economic advantage of contract growing in
the smallholdings in the Western Highlands became apparent. Company crop production
was phased out and farmers in selected villages were awarded contracts. The main
commodities were cauliflower, broccoli, snow peas, and brussels sprouts.
This system continues to operate and the farmers of the Cuatro Pinos cooperative,
the focus of this research, were part of this contract system in the early 1980s. Kusterer,
Estrada, and Cuxil (1981, 6-9) point out the rather different effects of the contract-growing
scheme in different locations of its operation. The access to inputs and to restricted
delivery for the contracted amounts of outputs was, at various locations, a problem to
farmers. In general, farmers were very eager to join the scheme. In fact, a major
short-term problem was that farmers had moved unexpectedly fast into production of
some of the vegetables and the marketing and export channel did not keep up with
this rapid adoption, thus leading to critical frictions between the contract partners in
the cooperative (Kusterer, Estrada, and Cuxil 1981, 17-24).
Export vegetable production is done at the individual farm level in the context of
contract growing or independently relying on market middlemen, called coyotes. A
substantial part of the export vegetable production stems from farmers who have formed
cooperatives. The positive attitude of Guatemalan peasants toward cooperation in pro-
duction with households from the same ethnic group is a good basis for agricultural
cooperatives (Bossen 1984). In 1984, 812 cooperatives with more than 143,000 mem-
bers were registered, of which 382 cooperatives were agricultural ones.6 More than
half of all cooperatives are located in the Western Highlands, the area of this study.
Agricultural cooperatives had on average 167 members in 1983-less than half as
many as the Cuatro Pinos cooperative had at that time.

5 A very comprehensive description and evaluation of the early operation is given in Kusterer, Estrada, and
Cuxil 1981.
6 Of the 812 cooperatives, 731 were considered actually active at the end of 1983 according to El Instituto
Nacional de Cooperativas (INACOP), as stated in FIDA 1985, 137.



Food and agricultural policy plays a key role in shaping the commercialization of
traditional agriculture. Commercialization of subsistence agriculture does not simply
develop as a result of changes in economic incentives or new technology at the farm
level, the processing level, or in marketing. To a large extent, the commercialization
process is also influenced and designed by actors at the local level and, especially in
case of export crops, by actors who are quite removed from the local farm-production
scene. The Cuatro Pinos cooperative is an interesting case in point.

Socioeconomic Environment of
Cuatro Pinos at the Outset
Cuatro Pinos is active in six villages in and around the municipio (county) Santiago
Sacatepdquez, which is located about 35 kilometers west of Guatemala City.7 Storage
and processing facilities for the export vegetables are in Santiago, which is the base of
the cooperative. The community is connected to the paved road of the Pan-American
Highway, which is 5 kilometers away. The altitude is around 1,900-2,000 meters.
According to a survey carried out in 1977, 10 percent of the cultivated area of the
municipio was devoted to the production of different vegetables. The remaining 90
percent was for maize and beans (Hintermeister 1986, 10). Between 10 and 15 percent
of family heads living in Santiago were working in Guatemala City. In general, they
were relatively young and had access to small parcels of land below subsistence levels.
In one of the main villages in which Cuatro Pinos is operating, Santa Maria Cauqu6,
a comprehensive longitudinal study on population, agriculture, nutrition, and health
depicts the situation before implementation of the cooperative (Mata 1978). Between
1963 and 1971, the population increased at a rate of 3.1 percent per year, while farm
size decreased at a rate of 3.5 percent. Since then, population growth has increased
at a rate of 3.5 percent per year. This particular village, however, is a rather untypical
case. The trend toward cash crops was established even before the establishment of
the cooperative, but the cooperative reinforced the trend. This village was more com-
mercialized at the outset than the other five villages of the cooperative, mainly because
of its favorable access to transport and communication infrastructure by virtue of its
proximity to the Pan-American Highway. In the 1960s the cropping pattern changed
gradually, showing a reduced share of subsistence crops. From the early 1970s to 1985,
the share dropped from 70 to 50 percent, corresponding to the increased share of new
export crops and traditional vegetables (Table 5).
The incidence of severe protein calorie malnutrition (PCM) was found to be consid-
erable in Santa Maria Cauque. In a cohort analysis between 1964 and 1969, 13 percent

7 Since 1987, the cooperative has operated in eight villages.

Table 5-Average farm size, population, and land use pattern in Santa Maria
Cauque, 1963-85
Item 1963 1967 1971 1985
Farm size (hectares) 1.2 1.1 0.9 0.8
Population 1,071 1,254 1,370 2,225
Land use (percent)
Maize and beans 78.7 73.2 70.5 49.5
Vegetables and other crops
(including export crops) 21.3 26.8 29.5 50.5
Sources: Based on data from L. J. Mata, The Children of Santa Maria Cauqud: A Prospective Field Study of Health
and Growth (Cambridge: Massachusetts Institute of Technology Press, 1978), p. 18; and Institute of
Nutrition of Central America and Panama/International Food Policy Research Institute survey, 1985.
a Estimated on the basis of a 1983 census done by the Institute of Nutrition of Central America and Panama.

of 1-year-old children, 27 percent of 2-year-old children, and 9 percent of 3-year-old
children were found to be affected by PCM (Mata 1978, 298). Most cases of severe PCM
occurred in the rainy season (June-September), when infectious diseases-particularly
measles, diarrhea, and respiratory infections-are most frequent. In explaining this
pattern of the prevalence of PCM, Mata (1978, 302) concludes that "the relationship
of food availability, marketing, and cash to malnutrition deserves serious investigation."
At the outset, the general socioeconomic environment and health and nutrition
situation in the area of the Cuatro Pinos communities appeared to be not particularly
different from the general situation in the Western Highlands. Some special features
of the economic environment are, however, noteworthy. Closeness to the capital city
and the good infrastructure facilitated market integration with fresh vegetables. Average
farm size is below the average in the Western Highlands. Also, there are no big farms
in the area. This has two implications: there were no serious conflicts over land-at
least in the 1970s-and the influence of nonindigenous farmers on the social organi-
zation and economic activities in the municipio was small. Thus there was neither an
important social force to oppose the local development of the cooperative nor landow-
ners who considered the promotion of the profitable labor-intensive crops as a threat
to their control over the labor market (Hintermeister 1986, 11-12).

The Evolution of Export Cropping
by Cuatro Pinos Farmers
The adoption of export vegetable production by small farmers in the Western
Highlands is determined by long-term changes in economic variables, especially the
increased demand for these crops in U.S. and European markets and the growing
labor-land ratio on small farms. Both these factors increase the comparative advantage
of labor-intensive crops in rural environments where there is increasing (seasonal)
underemployment. International development assistance organizations played a catalytic
role in the beginning for the rapid use of potential economic benefits from nontraditional
export crop production in the Western Highlands. The interaction of four groups of
actors finally led to the rapid expansion of export vegetable production.
1. External development assistance organizations were instrumental at two different
levels. First, they provided the seed money (loans) to a private company, Alimentos
Congelados S.A. (ALCOSA), to open up the export channel (Latin American Agribusiness
Corporation S.A. [LAAD] and the U.S. Agency for International Development [AID]


played a role in this). Second, they stimulated the formation of the cooperative, im-
plemented its programs, and assisted in securing access to the export channel through
private exporters (Swiss Group, a Swiss nongovernmental organization).
2. An external private company (ALCOSA, a subsidiary of U.S.-based Hanover
Brands, Inc.) provided the know-how and the export channel to the U.S. market,
including such related infrastructure facilities as cold storage.
3. Guatemalan public institutions provided the know-how on agricultural technology
(Instituto de Ciencias y Tecnologias Agricolas [ICTA]) and farm-level credit (Banco
Nacional de Desarrollo Agricola [BANDESA]). INCAP developed vegetable-processing
4. Local farmers formed the Cuatro Pinos cooperative, which organizes export
vegetable production and provides field-level extension, input supply, produce collec-
tion, selection, and storage. Lately the cooperative has organized its own exports
independently from the ALCOSA outlet, both to the United States and to Europe.
The interaction of these players in the process of increased commercialization was
quite different in the various phases of the process. The following calendar of events
that led to the expansion of vegetable production for exports at Cuatro Pinos sheds
light on this:

Export Vegetables in
Year Guatemala

Cuatro Pinos Cooperative

1970 LAAD founded (LAAD's Central
American subsidiary mainly funded
through USAID loans)
1971 ALCOSA began operations in Guate-
mala with a LAAD loan (freezing
fruits and vegetables)
1975 ALCOSA purchased by Hanover
Brands, Inc., and expanded with
new loans from LAAD to export veg-
etables to United States (okra, broc-
coli, cauliflower, brussels sprouts)
1976 Main production of vegetables for
export by ALCOSA started on com-
pany lands leased by ALCOSA; small
experiments with small farmers
1977 Buying stations set up to buy cauli-
flower from small farmers in high-

Earthquake in the Western High-
lands; death toll about 30,000; Swiss
Group comes to rebuild Santiago

Swiss Group's development pro-
grams-food aid, literacy courses,
along with reconstruction work in
villages; formation of groups that
later formed the cooperative

1978 Rapid expansion of cauliflower pro-

1980 Production on ALCOSA's own farm-
land closed; all cold-weather vege-
tables now from small highland
farmers (about 2,000 farmers in
purchasing program, delivering to
17 stations); crisis of ALCOSA-
contracts were signed for much
more broccoli and cauliflower than
plant's processing capacity; break-
down of field organization; suspen-
sion of purchases; losses to farmers
1981 Expansion of processing capacities
of ALCOSA; change in contractual
arrangements with farmers

1987 Five companies (Guatemalan) in
addition to ALCOSA started frozen-
vegetable business

Implementation of agricultural pro-
grams-maize improvement, tra-
ditional vegetables; contract with
ALCOSA through Swiss Group for
broccoli and cauliflower production
in Santiago Sacatepequez
Construction of buildings for cold
storage and packing at cooperative
headquarters at Santiago Sacatepb-
quez; contractual arrangements
with fresh snow pea exporters

Rapid expansion of cauliflower,
broccoli, and snow pea production
and direct exports by cooperative to
United States
Further expansion of cooperative;
construction of own freezing, pro-
cessing facilities; 20 percent of ex-
ports to Europe

Production technology, management, and on-field supervision requirements for
export vegetables are well suited to small farms. The early experience of ALCOSA with
crop production and procurement clearly indicates that the production of export vege-
tables (broccoli, cauliflower, snow peas) has rapidly decreasing returns to scale. The
production initially started on land leased by ALCOSA where up to 400 people were
directly employed by the company. Then ALCOSA contracted middle-sized farms of
20-40 hectares operated by agricultural entrepreneurs and, finally, shifted to small
farmers. Although ALCOSA initially intended to depend on its own farming for raw
material, it soon began to rely more on its outgrowers (Kusterer, Estrada, and Cuxil
1981, 13). The experience showed that nontraditional commercial farming entrepreneurs
on the middle-sized farms were not a satisfactory source of supply.
The small farms' comparative advantage in vegetable production is due not only to
the high labor intensity of the work tasks but also to careful on-field management and
supervision requirements to meet quality standards that are better fulfilled by the small
farmers experienced in traditional vegetable production. These production characteris-
tics are important features for the sustainability of export vegetable production in the
hands of small farmers. Along its development path, Cuatro Pinos has benefited from
institutional support and soft loans for its investments but not from subsidies for on-farm
production. The institutional support and know-how transfer was probably the most
important ingredient for the growth of the cooperative.

By 1987, Cuatro Pinos had expanded to 1,150 members, compared with 177
members in 1979. The cooperative farmers were growing nearly 300 hectares of export
vegetables in 1985. More than half of this area was devoted to snow peas. The area
under these crops has quadrupled since 1980/81 (Table 6). At the cooperative head-
quarters, about 150 persons-more than half of them women-found employment in
screening and packing work.

Sustainability of Export Crop
Production by Small Farmers
Export vegetable production is frequently considered risky for small farmers. Various
types of risks are distinguished: risk of crop failures (pests, weather), risk of price
collapses, and risk of a breakdown of the marketing institutions (the domestic or
external part of the channel or both).
The production risk at the farm level will be discussed later on the basis of farm
survey data. The two "institutional" risks are addressed in the following sections.
Price Risk and Exchange-Rate Policy
Prices of export vegetables, and those of snow peas in particular, are extremely
unstable compared with, say, staple food prices. Highest and lowest prices paid to
Cuatro Pinos farmers in 1985 for snow peas of similar quality ranged from Q0.10 to
02.00 with a median of about 00.80 per pound (see Figure 2). These fluctuations
reflect directly the actual price movements in the export markets (especially the spot
markets in Miami, Los Angeles, and London). The fluctuations are the result of short-
term supply-and-demand changes. Various regions enter the markets of these products
at different times (for example, Mexico, California, and the Dominican Republic). Other
types of fresh vegetables probably induce substitution effects on the demand side in
various seasons, but little is known about these. However, it is important to note that
the high degree of price instability of snow peas from week to week does not translate
into a similar instability of returns from the crop. Harvesting of the crop starts 9 weeks
after planting and extends over 10 to 12 weeks with three pickings of the crop per
week. The grower is thus facing an average price over the whole harvesting period of
a field. A farmer who, for example, planted his crop in the beginning of June 1985
and was harvesting in August, September, and October delivered his crop at prices
ranging from 00.10 to 01.50 per pound with an average-depending on volume at
the specific points in time-of about 00.55 per pound. The price fluctuations listed

Table 6-Area under export vegetable crops marketed by the Cuatro Pinos
cooperative, 1980-85
Crop 1980/81' 1984/85 1985/86
Snowpeas 6 90 170
Cauliflower 61 67 67
Broccoli 0 10 45
Parsley 0 2 7
Total 67 169 289
Source: Records of Cuatro Pinos cooperative.
a Rough estimate.

Figure 2-Snow pea prices paid to farmers by cooperative, 1984-87

4.0 r







----- Monthlyprices
12-week moving average


I.I t

Z F x5
It J

1984 1985

1986 1987

Source: Records of Cuatro Pinos cooperative.

in Figure 2 are thus smoothed out in 12-week moving averages with which they actually
translate into gross revenues from the crop. Farmers also can-and actually do-grow
the crops in phases on different plots at different points in a year, thus further reducing
the price risk.
Such price variability is not necessarily a problem for farmers if it represents a
seasonal pattern with predictable ups and downs in prices. For some time it was
assumed that snow pea export prices were at a seasonal high during September-December
and farmers were accordingly advised to plant for harvest at that time. In recent years,
however, no clear seasonal price pattern has occurred, so farmers have been confronted
with a high degree of uncertainty. Developments on the supply-and-demand side of
the international market for snow peas-for example, increased demand from Western
Europe and increased supply in various seasons from other producing regions such as
the Dominican Republic, other Central American countries, and California-appear as
important factors. Also, little is known about substitution effects of changes in prices
of competing types of vegetables on the formation of prices for such luxury vegetables
as snow peas. Predicting future crop prices, which is crucial for the sustainability of
the export operation, is hardly possible with any acceptable margin of error. Demand
in the rich countries of the North appears to be rising. However, as long as new
technologies are not developed that would permit the cultivation of the crop with
substantially lower labor input in comparable climatic zones, small farmers in the


Guatemalan highlands have a sustained comparative advantage due to the local labor
supply situation. Deflated average prices for snow peas paid to cooperative farmers
have shown neither a decreasing nor an increasing tendency since 1984: first-quarter
averages (January-April in 1984 prices) were Q0.50 per pound in 1984, Q0.36 in
1985, Q0.76 in 1986, and Q0.61 in 1987. The variability of prices also shows no
particular tendency in these years.
Comparative advantage of export vegetables at the farm level is directly affected
by the exchange-rate policy, which determines changes in the price ratio between
traded and nontraded agricultural products and inputs. Recently, exchange-rate policy
changes in Guatemala have introduced an additional uncertainty element into the price
environment. These policy changes are not predictable for farmers; thus the erratic
exchange-rate policy discussed in Chapter 3 establishes one component of the price
risk facing the farmer.
The overvalued exchange rate in the early 1980s and the multiple exchange-rate
system in place in 1985/86 translate into a changing taxation of the export vegetables.
In mid-1985, the exchange-rate system for vegetable exports required 50 percent of
the sales value to be exchanged at the official rate (Q1.00 = US$1.00) and permitted
the other 50 percent to be exchanged at the parallel rate (about Q1.00 = US$0.27).
Even taking into account a common practice of underreporting the sales value, this
exchange-rate policy resulted in an export tax of about 25 percent for snow peas (see
Table 7). This tax favors production of domestically consumed traditional vegetables
and, to some extent, the subsistence crops (maize and beans). It also suggests that
returns to farm labor in the small enterprises in the Western Highlands are cut. The
export tax for the labor-intensive new vegetables in the Western Highlands had adverse
effects on employment and real income of the rural poor.

Table 7-Effect of exchange-rate policy on export vegetable producer price:
an example from a snow pea sale by Guatemala to the United States,
July 1985
Affected Item Price and Tax Effects

(1) Actual "return price" of a shipment US$0.35/pound
(2) Declared "return price" of shipment (lowest price
noted on market in reference period of shipping) US$0.25/pound
(3) 50 percent of declared "return price" at official
exchange rate (Q1.00 = US$1.00) Q0.125/pound
(4) 50 percent of declared "return price" at parallel
exchange rate (Q1.00 = US$0.27) Q0.463/pound
(5) Difference between actual and declared "return
price" at parallel exchange rate (Q1.00 = US$0.27) Q0.407/pound
(6) Actual "return price" in domestic currency (posi-
tion [3] + [4] + [5]) Q0.995/pound
(7) Tax due to official exchange rate applied to 50
percent of declared "return price" (in position [3]) Q0.338/pound
Tax in percentage of actual "return price"
position (1) at parallel exchange rate 25.4 percent
Source: Information from traders in Guatemala.
Note: "Return price" is the net price c.i.f. U.S. market (Miami) after transport and handling costs are deducted.
It is "returned" to the exporting cooperative, which passes it on to farmers after deducting local marketing

Risks in the Marketing Institutions
It is obvious that the sustainability of the export operation of a perishable commodity
largely depends upon the proper functioning of the marketing channel of inputs and
outputs (Figure 3). Input markets of fertilizers and pesticides appear to be well integrated
in Guatemala. Domestic prices of inputs are largely determined by international price
changes and by the exchange-rate policy.
The output marketing in the study area is largely via the Cuatro Pinos cooperative.
The sustainability of this institution is crucial for the profitability of export crop produc-
tion. Cooperatives in the Western Highlands have a mixed record of success. It has
not been uncommon for cooperatives to collapse because of dishonest management
practices or political reasons, especially during the period of violent conflicts in the

Figure 3-Marketing channels for fresh export vegetables from Guatemala

Vegetable Producers
(small farmers)

Input Suppliers
* fertilizers
* pesticides

via cooperative via traders

Village Col

election by


Transfer to Middleman
(cool storage, screening,

Transfer to airport and
air-transport to export markets
(United States) by companies,

Village Collection by
(cool storage,
screening, packing at

Transfer to airport
and air-transport to
export markets
(United States,
Europe) by
contractors/agents of





Adoption of Export Crops by Subsistence Farmers
Agriculture in the survey area was formerly dominated by production of maize and
beans, with 10 percent of the land devoted to vegetables for the local market. Those
farm households who are not members of the export crop cooperative and who live
in the more remote sample villages still show this cropping pattern in 1985. In villages
such as El Rej6n, Pacul, and Pachali, maize and beans cover 84-96 percent of the crop
area of nonmember farms (Table 9).
The important relationship of access to infrastructure and degree of market integra-
tion is revealed by the case of Santa Maria Cauqu6, which is located at the highway
to Guatemala City. There, even nonmember households plant only 51 percent of their
land with subsistence crops.
Cooperative members farm on average 0.94 hectare, while nonmembers farm 0.66
hectare. Comparisons of the two groups, therefore, must take the farm-size difference
into account. Accordingly, most agriculture-related information is presented by farm-size
classes in this chapter. It is interesting to note that with these holdings and the allocation
of 52 percent of land to subsistence crops by members and 78 percent by nonmembers,
households in both groups allocate on average about the same land area to subsistence
V crops (members, 0.49 hectare, versus nonmembers, 0.51 hectare).

Table 9-Farm size and cropping patterns of members and nonmembers of
the Cuatro Pinos cooperative, 1985
San El SantaMaria Total
Farm Size/Crops Mateo Rej6n Cauque Pacul Pachali Santiago Average
Average farm size
Members 0.82 1.15 0.86 0.61 1.06 0.85 0.94
Nonmembers 0.64 0.95 0.83 0.80 0.58 0.54 0.66
(percent of area)
Maize, beans
Members 48.8 62.6 41.3 45.3 42.4 57.7 51.8
Nonmembers 81.6 83.9 51.0 87.2 95.5 81.9 77.8
New cash crops
Members 45.9 35.4 38.8 41.8 53.3 35.9 39.3
Nonmembers 4.0 8.0 22.1 3.3 1.5 7.3 8.9
Traditional cash crops
Members 5.3 2.1 19.9 12.9 4.4 6.4 9.1
Nonmembers 14.5 8.1 26.9 9.5 3.0 10.9 12.8
Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
Note: Parts may not add to totals because of rounding.

Export crop production is open to every farmer in the six communities where the
Cuatro Pinos cooperative is active. Because merchants outside the cooperative have
recently begun operation of another marketing channel for the new export crops, the
option to grow export vegetables is not entirely tied to membership. However, with
the exception of Santa Maria Cauqud, a centrally located village where many merchants
base their operations, only a very small group of nonmember farmers grows the new
crops. This means that becoming an export crop farmer is in most villages synonymous
with becoming a cooperative member. This decision is a matter of free choice.8
The major decisions made in commercial and subsistence agriculture are decisions
that are mostly made either exclusively by the male head of household or jointly by
men and women but dominated by men. Nieves (1987) finds that the presence of the
cooperative seems not to have altered this relation, at least not in the short term. In
her case study on 21 households that are a subsample of the INCAP/IFPRI survey in
1985, Nieves found that the decision to become a member was, in all 21 cases,
prompted by the male head of the household. In 16 of these cases, the male head
asked the wife's opinion before taking any action. There are no legal or statutory
barriers to female participation in the cooperative as members in their own right, yet
very few women have membership status (5 out of more than 1,000 members in 1987).
Nieves states that women in the study area will assume only public, visible roles that
are culturally sanctioned. Applying to the local committee for membership would be
an example of a public action traditionally not open to women. Cooperative membership
is not a status that women feel they can attain, so they do not apply.
Membership in the cooperative is open to crop growers (but not necessarily to
landowners) and small farmers by local standards (no member has more than 3 hectares).
Members are obliged to participate in scheduled meetings of the organization and to
pay a one-time membership fee of Q38. This enrollment fee is not negligible, as it roughly
corresponds to 12 days' wages for a farm worker.
To test the determinants of adoption of export cropping, a probit model is estimated
in which the dependent variable equals 1 if the household is an export crop grower,
and zero otherwise:

Y = p'X + ui, (1)
Y = 1 if Y >0, otherwise
Y = 0, and
Probability (Yi = 1) = Probability (u,> p'Xi) = 1 F(-p'X,),

where F is the cumulative distribution function for u.9 The W' are maximum likelihood
estimates. The bias toward a higher (nonrepresentative) members' share in the sample
is taken into account in estimating the probit model. The true proportion of members
versus nonmembers, known from the 1983 census information and the cooperative

8 For the first time, the cooperative was closed to new members in the fall of 1986, as the rapid expansion
of members was considered unmanageable by the cooperative leadership. More members were admitted
later, but the cooperative was closed to new members again in 1988.
9 For a description and discussion of the probit model, see, for example, Maddala 1983, 22-27.

records, is used to weigh the observations.'0 The theoretical concept of the model
application is the following: Income potentially earned off-farm determines the oppor-
tunity cost of working on-farm. In the long run, earning off-farm income versus increased
on-farm work growing the labor-intensive export vegetables is a choice facing farm
households. This choice is determined by the off-farm versus on-farm opportunity costs
of family labor. Endowment of human capital and established off-farm employment
opportunities determine these relationships for a specific household.
It is hypothesized that the choice to become an export crop grower was determined
by the expected income increase, which can be assumed to be determined by the
resource endowments of the farm (farm size, land quality) on the one hand, and the
access to alternative, relatively secure off-farm employment on the other. It should be
noted that only a secure (formal) off-farm income source enters here as an exogenous
factor, since high substitution of daily wage earnings and occasional trading income
versus on-farm work in the new export crop prevails, as is shown later.
It is further hypothesized that household labor force size and composition (women's
share) may be a factor for adoption. A larger household labor force may enhance
adoption of the labor-intensive crop, and a higher share of women's labor may induce
a different balance of preferences and bargaining positions in the household. Since the
decision is mainly that of the male head of household, his age, education level, and
attitude toward traditional agriculture are other factors of hypothetical impact for the
adoption decision.
The access of villages to infrastructure affects adoption of the new crops. This and
the stepwise expansion of the cooperative into some of the villages suggest the inclusion
of village-specific variables in the model. Based on these hypotheses, the adoption
model is specified as follows:

EXG = export crop grower (= 1 if more than 10 percent
of area in nontraditional export crops, else = 0),
FSZHA = farm size (hectares),
WLQ = land quality index (1 = best, ... 4 = worst),
FOFFY = household income from formal off-farm employ-
ment (quetzals per year),
LAB = total labor available in the household (that is,
persons of working age), not disabled and not
long-term absentees (in man equivalents),
RWOMLAB = share of female labor in total labor of household,
HHAGE = age of head of household (years),
HHEDUC = household head's education (years of schooling),

10 The approach is described in Manski and McFadden 1982.

HHTRAD = household head's attitude toward maize produc-
tion being "traditional" (= 1 if stated that most
important reason for growing maize was for food
and that second most important reason was that
he grew maize to this extent because he always
did so; else = 0), and
VILLAGE 1-5 = dummy variables for villages 1... 5 = 1 each
(else = 0); villages as listed in Table 1 from left
to right.

The probit estimates are listed in Table 10 and can be used to derive linear prob-
abilities pu,, which can be approximated (see Amemiya 1981) by

Table 10--Probit estimate of export crop adoption

Probabilty of
Independent JoiningExport MeanValue Standard
Variable Coeffident t-Value Crop Production" of Variable Deviation

FSZHA 0.65970 5.105 0.2630000 0.689 0.644
WLQ -0.19191 -1.109 ... 2.120 0.456
FOFFY -0.00021 -2.540 0.0000848 406.600 932.900
LAB -0.08476 -1.544 ... 3.780 2.360
RWOMLAB -1.00440 -2.016 0.4020000 0.466 0.179
HHAGE -0.00822 -0.833 ... 38.700 12.400
HHEDUC 0.32280 0.692 ... 2.930 1.730
HHTRAD -0.36682 -2.263 -0.1470000 0.545 0.489
VILLAGE 1 -0.54760 -1.953 -0.2190000 0.119 0.324
VILLAGE2 0.17560 0.692 ... 0.113 0.317
VILLAGE3 0.78250 3.632 0.3130000 0.186 0.389
VILLAGE4 -0.23840 -0.811 ... 0.076 0.265
VILLAGE 5 -0.16220 -0.558 ... 0.095 0.287
INTERCEPT 0.72380 1.258

Notes: Dependent variable: Export crop grower (= 1, else = 0). Number of observations: 357. Chi-squared:
FSZHA = farm size (hectares),
WLQ = land quality index (1 = best,..., 4 = worst),
FOFFY = household income from formal off-farm employment (quetzals
per year),
LAB = total labor available in the household (that is, persons of
working age) not disabled and not long-term absentees (in man
RWOMLAB = share of female labor in total labor of households,
HHAGE = age of head of household (years),
HHEDUC = household head's education (years of schooling),
HHTRAD = household head's attitude toward maize production being
"traditional" (= 1 if stated that most important reason for
growing maize was for food and that second most important
reason was that he grew maize to this extent because he always
did so; else = 0), and
VILLAGE 1-5 = dummy variables for villages 1 ... 5 = 1 each (else = 0);
villages as listed in Table I from left to right.
a The values in this column are the (3 for the parameters estimated with a reasonable degree of statistical
significance (above 95 percent level).

uLP = 0.4 1'. (3)
The estimation results indicate that the decision of households to adopt the new
export crops is not independent of household and farm characteristics:
1. Although all farms in the sample are small by almost any standard, an increase
in size of farm significantly increases the probability of becoming an export cropper.
Applying the above-mentioned conversion factor of 0.4 to the parameter estimate
(FSZHA in Table 10) suggests that one additional hectare of farm size increases the
probability of growing export vegetables by 26 percent. The adoption-farm size relation-
ship is complex. This finding of increased probability of adoption within the small-farm
sector with rising farm size is not contradictory to the earlier finding that the new
export crops moved in a trial-and-error path from production on large-scale exporter
enterprises to contract growing on medium-sized farms of 20-30 hectares to the small-
farm sector. As the probability of adopting within the small-farm sector increases with
farm size up to a certain level, economies of scale are apparently not linear at the tail
end. It is found, however, that those smallest farms that did adopt actually allocated a
higher share of their land to the new crop. Adoption and extent of adoption are thus
not synonymous.
2. Increased income from formal off-farm employment-that is, relatively secure
Income from sources other than day labor--decreases the likelihood that households
will grow export crops. The estimation result suggests that if this type of relatively
secure income increases by Q500 (which is approximately the difference between the
mean and standard deviation of FOFFY), the probability of joining the scheme decreases
by 4 percent.
3. An increased share of women's labor in total labor significantly reduces the
probability of growing export vegetables (RWOMLAB) after controlling for total labor
force of the household (LAB). As noted earlier, adoption of the new crop is primarily
a male decision, and the model results suggest that households with a female-dominated
labor force stay away from the new crop.
4. Traditional motivation to grow maize (HHTRAD) significantly decreases the prob-
ability of becoming an export crop grower.
5. For households located in a remote village that has recently been included in
the scheme (village 1, San Mateo), the probability of becoming a member appears
lower, while it is significantly higher in village 3 (Santa Maria Cauqud), which is located
at the highway.
The statistically nonsignificant results in the probit model are also interesting to note:
1. Differences in land quality of the farm (WLQ) have not significantly affected the
choice of becoming an export crop farmer.
2. Availability of household labor does not significantly affect the choice of becoming
an export crop grower. The market for hired labor is highly integrated in the region,
which suggests this model outcome.
3. The age and level of education of household head, which were assumed in order
to indicate human capital endowment of the household, do not significantly affect the
adoption probability.
In summary, it may be concluded from these results that the less traditional farmers
on the somewhat larger (small) farms and those who do not have access to relatively
secure (formal) off-farm employment were most likely to adopt the export crops."

The probit model of the same specification was also estimated for the dependent variable defined as
membership/nonmembership in the cooperative (= 1,0). While the results for the farm size and off-farm
income variables were similar, the other variables were not statistically significant in that model.

That comparatively larger farms were joining the cooperative becomes clear from
the distribution by farm-size class among the member and nonmember groups. Table
11 reveals a tendency often observed in patterns of adoption of "green revolution"
technologies in peasant agriculture; more of the early adopters have somewhat larger
farms (more than 1 hectare) than adopters who join later.

Profitability and Risks of New Export Crops
and Subsistence Crops
For those farmers willing to adopt new export crops, the returns of those crops to
factors of production (that is, land and labor) is central. In addition to the average
profitability, the stability of returns from these crops is an important factor, as risk may
be an issue of concern. Gross margins are used as measures of profitability. The gross
margins calculated are based upon the 1985 survey covering the 1984/85 cropping
season as expressed in the cropping calendar (Figure 4). Gross margins are the value
of output minus the direct costs. Rent for land is not included. To assess the competi-
tiveness of various crops at the farm level, gross margins are expressed per unit of land
and per family-labor day.
Since snow peas stand out as the main new crop in the following comparisons, its
agronomic characteristics will be mentioned here. The peas are sown in rows. When
they are about 20 centimeters high, the plants are tied to ropes that are stretched
between sticks along the rows of plants. The plants grow up to about 1-1.3 meters on
the continuously added ropes. The main work tasks are weeding, spraying for pest
control, and picking the peas. Picking starts after an 8-week growing period and extends
over 10-12 weeks. The crop is thus on the field from 18 to 20 weeks. Snow peas are
sprayed two times per week over the growing period. The cost of recommended spraying
in 1984/85 was Q596 per hectare. Because the devaluation of the quetzal on the
parallel market sharply increased this cost (see Chapter 4), the 1986 spraying bill was
310 percent of the 1984/85 bill. The wage bill for snow peas is also considerably
higher than for any of the competing crops. The related employment issues will be
addressed later.
Being a legume (a variety of p. sativum), the snow pea enriches the nitrogen content
of the soil, which benefits crops that follow in the rotation.
Snow peas yield a gross margin per unit of land 15 times higher than that of the J
principal subsistence crop, maize, on cooperative member farms (Table 12). Per unit
of fami labor, the gross margin of snow peas is about twice the margin reported for

Table 11 -Farm-size distribution of cooperative members and nonmembers

Length of Membership
2Years 3-4 5Years
Farm Size Nonmembers or Less Years or More
(hectares) (percent) (percent)
Less than 0.25 25.8 5.0 6.1 2.8
0.25-0.50 36.0 20.0 24.5 20.8
0.50-1.00 21.3 47.5 40.8 41.7
1.00 or more 16.9 27.5 28.6 34.7
Total 100.0 100.0 100.0 100.0
Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,

Figure 4-Cropping calendar of subsistence crops, traditional vegetables,
and export vegetables in the Western Highlands, 1984/85
1984 1985
Crop J F M A M J J A S O N D J F M A M J J

Maize ---------------
Beans ----

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
Note: The double lines show the main periods of planting, growing, and harvesting; the single lines show
extended periods during which a minority of farmers engage in these activities.
a Cabbage, carrots, radishes, and others.
b Main planting season, May-August; main harvest season, June-September.
c Main growing period, August-April; main harvest period, October-June.

maize, as snow peas absorb 7 times more family labor per hectare, or 5 times more
total labor input in terms of days, than maize. Traditional vegetables are roughly as
profitable as broccoli and cauliflower per unit of family labor. Beans are between maize
and the above vegetables. The per hectare input costs of snow peas are about 13 times
as high as those of maize. These high input costs of snow peas stem from high use of
pesticides and from the costs of special production inputs (sticks to bind the plants
and ropes to tie the climbing snow pea plants to the sticks).
Cooperative members finance the considerable input costs partly through agricul-
tural credit. Forty-two percent of members had received credit during the previous
year. On average the sum borrowed amounted to Q480, which covered the variable
input cost for 0.3 hectare of snow peas. Only 3 percent of the nonmembers reported
having had access to credit during 1984/85. It is interesting to note that those farmers
who grow the new export vegetables under the cooperative scheme have higher returns
and lower unit costs of production in the maize crop than other farmers (columns I
and 2 of Table 12). The input cost and wage bill are higher for members, yet their
output per unit of land is further increased, thus leading to this outcome. The relationship
of this pattern to the export vegetables is analyzed in detail below.
The ranking of crops by their profitability shows a similar pattern if the sample is
disaggregated by farm-size class (Table 13). There is a tendency for maize gross margins
per hectare to decrease with increasing farm size, both for export crop producers and
other farms, but returns to family labor do not differ a great deal between farm-size
classes. Constant returns to family labor and decreased returns to land with increased
farm size indicate that larger farms operate at higher cost levels per unit of land or at
lower yield levels or both. No general tendency is visible from the tabulations of gross
margins of the new export vegetables per unit of land and labor. The apparently negative
scale effects for these crops, discussed above in the context of ALCOSA's experience
(Chapter 4), may become effective only outside the range of small farm sizes observed
in the sample.

Table 12--Cost of production and gross margins of export vegetables and
subsistence crops, 1984/85

Cooperative Member Farms
member Traditional Crops NewExportCrops
Farms, Traditional Broccoli,
Item Maize Maize Beans' Vegetables Cauliflower SnowPeas
(quetzals/hectare, mean values of sample)
Seeds, plants 0.20 0.21 26.55 106.30 85.76 54.87
Fertilizer 100.12 105.60 85.28 158.61 243.82 216.16
Other inputs 13.66 14.85 55.10 167.95 103.88 1,296.13
Total inputs 113.98 120.66 166.93 432.86 433.46 1,567.16
Wages paid 96.22 167.71 133.69 306.06 283.58 552.71
Value of output 353.75 457.80 681.00 1,804.53 1,339.17 4,416.20
Gross margin per
hectare 120.43 143.87 362.79 1,065.61 593.37 2,204.15
6,^/,-/'4, e.-^ 4 8' -41 17 3 --" IF
(days/hectare, mean values of sample)
Days of family labor
per hectares 63 54 121 299 168 400
Days of total labor
perhectared 101 119 172 416 277 613

(quetzals/day, mean values of sample)
Gross margin per day
offamilylabor 1.91 2.66 2.99 3.47 3.53 5.51

Source: Computed from data from Institute of Nutrition of Central America and Panama/International Food Policy
Research Institute survey, 1985.
Note: The mean values are based on 173 observations on nonmember farms and 160 observations on member
a Beans in sole stand.
b To compute the gross margin from value of output, wages, and total inputs, interest on the sum of purchased
inputs and on the part of the wage bill for nonharvest labor is deducted. The interest rate used is 15 percent
adjusted to the duration of the crop's growing period.
c Men's, women's, and children's labor days are weighted by 1.0, 1.0, and 0.6, respectively.
d This includes hired labor.

Cooperative members on average have higher returns than nonmembers to both
land and family labor for the three comparable crops (maize, beans, and traditional
vegetables; see totals in Table 13). In general, this pattern is also revealed within the
farm-size classes.12 Thus it appears that the more efficient farmers joined the export
crop scheme, as there is no indication of basic differences in land-resource quality
between the two groups. Yet, joining the cooperative may also have improved farmers'
access to yield-improving technologies-for example, inputs and information. These
aspects will be evaluated in more detail below. At this point it is worthwhile to note
that export crop producers achieve higher returns to land and family labor from subsis-
tence crops (maize and beans) than do other farmers, although the export crop farmers
devote more resources to the new export vegetables.
The gross margin (net return) per day of family labor indicates the level of opportunity
cost of family labor in agriculture. The gross margins per family labor day fall in the
range of local wage rates, which were Q2.00-2.50 in 1984 and Q3.00-3.50 in 1985

12 It should be noted that many different crops are aggregated into the group of traditional vegetables. The
related gross margin figures vary considerably between farms due to this aggregation.

Table 13-Gross margins of export and traditional crops per hectare and
per person-day of family labor, by farm size, 1984/85
Export Crop Producers Traditional Crop Producers
Traditional Broccoli, Traditional
Farm Size/Unit Maize Beans Vegetables Cauliflower SnowPeas Maize Beans Vegetables
(hectares) (quetzals)
Less than 0.25
Perhectare (188.00) ... (407.00) ... (2,198.00) 127.00 181.00 852.00
Per daya (2.61) ... (1.00) ... (3.74) 1.98 3.18 1.64
Perhectare 175.00 (254.00) (2,654.00) (365.00) 2,791.00 149.00 191.00 609.00
Per daya 3.13 (7.70) (7.97) (2.81) 6.10 2.10 3.19 2.14
Perhectare 146.00 187.00 375.00 645.00 1,785.00 85.00 (25.00) 397.00
Perdaya 2.43 2.25 1.24 3.41 4.52 1.42 (0.32) 1.15
1.00 or more
Per hectare 117.00 648.00 860.00 624.00 2,398.00 84.00 83.00 935.00
Perdaya 2.72 5.36 3.54 4.22 6.97 1.83 3.19 4.16
Per hectare 144.00 363.00 1,066.00 593.00 2,204.00 120.00 130.00 659.00
Perdaya 2.66 2.99 3.47 3.53 5.51 1.91 1.76 1.96

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
Notes: Values computed from 10 observations or fewer are in parentheses. The export crop producers are
members of the cooperative; the traditional crop producers are not members.
a Children's labor days are weighted with a factor of 0.6; men's and women's labor days are weighted with 1.0 each.

for a man's person-day in the field. Women's wage rates are reported to range from
Q0.50 to 01.00 lower than men's. Returns to family labor on export crop farms exceed
these male and female wage rates by a substantial margin. As a result, the labor supply
into the local labor market from these farm households has substantially decreased.
Inseparable from the assessment of profitability of new export crops versus tradi-
tional crops is their comparative risk. There is a great deal of uncertainty about the
new crops' output and input price fluctuations. A long-term longitudinal study would
be required to properly address the issue. Moreover, it should be reiterated that new
export crops particularly impinge on the off-farm labor supply of small farm households
in the Western Highlands. The comparison of risks in reallocating household labor
away from the uncertain off-farm labor market into their own uncertain new crop
enterprise is as important as the between-crop comparisons, which is the focus of most
literature on farm production risk. While this study is not designed to assess this aspect,
it should be kept in mind that the between-crop comparisons are of limited relevance
for an agricultural system that is as closely integrated into the nonagricultural labor
market as is the case with farmers in the Guatemalan highlands.13
A first indication of differences in degrees of price risk for crops is given by the
variance of prices within a cropping year across the survey area. Clearly, average prices
received by farmers for the new export crops vary much more than the maize price
but not more than the price of beans and traditional vegetables grown for the local

13 Increasing labor market participation in case of crop loss is a common risk-adjustment strategy of small
farmers in Central America. In a survey in El Salvador, it was found to be the most frequently used strategy.
See Walker and Jodha 1985, 17-34.

markets. As shown below, the coefficients of variation of snow pea, broccoli, and
cauliflower prices in 1985 tended to be even lower than those for beans and selected
traditional vegetables.
Crop of Variation

Maize 0.23
Beans 0.83
Traditional vegetables
Beets 0.77
Radishes 2.27
Lettuce 0.63
Spinach 1.00
New export crop
Snow peas 0.58
Cauliflower 0.52
Broccoli 0.24

It should be noted, however, that the intrayear price differences of beans and traditional
vegetables may be of a seasonal nature that could be predicted by farmers with a certain
probability. Thus the level of uncertainty related to price variability of traditional crops
may be less than, say, for snow pea prices, which do not follow a clear seasonal pattern
(see discussion in Chapter 4).
A second indication of the risk of new export crops versus traditional crops is given
by a comparison of the variation of their respective gross margins per hectare. We find
that gross margins of the new export vegetables tend to be less variable across the
sample than those of traditional crops.
Relative variability crop-by-crop does matter, but levels of potential losses as a
proportion of the asset base (land) are also important for the determination of household
risk. Given the high input levels for new export crops, the potential loss from crop
failure, output-price depression, or input-price increases may constitute a much higher
probability of substantial income loss. To assess this aspect, the frequencies and levels
of losses from traditional crops and new export crops are evaluated. Losses are rep-
resented in this assessment by negative gross margins, that is, net returns to land and
unpaid family labor were negative, as variable costs exceeded the gross value of produc-
tion. A combination of factors may lead to this outcome; for example, unfavorable
input-output ratios, high input or low producer prices, or both. From this comparison,
it becomes evident that farmers produced the new export crops at a loss as frequently
as the traditional crops in 1985.14 However, to take the two extreme cases-maize
and snow peas-in 24.5 percent of the sample fields, gross returns of maize do not
cover the variable costs and, similarly, in 25.1 percent of the fields, gross returns of
snow peas do not cover these costs. The absolute loss per unit of land is about 10
times as much in the case of snow peas as it is for maize (Q130 versus Q1,309 per

14 It should be noted that the percentage levels of negative gross margins might be somewhat overstated
due to the usual noisiness of such recall surveys that leads to extended tails of the distribution function of
variables. For this analysis, only the relative comparison across crops is relevant, and that should not be
affected too much by this problem.

hectare). Clearly, this new export vegetable appears quite risky if viewed in isolation
on the farm, but most farmers tend to minimize loss by devoting only a fraction of
their land to the new crop.
Losses and gains from crops within the farm enterprise may compensate for each
other. A comparison between cooperative members and nonmembers shows that the
percentage of farms that reported an overall income loss was similar in both groups in
1984/85 (17.8 percent of members and 16.8 percent of nonmembers). The income
losses in percentage of total expenditures averaged 7.7 percent in the member house-
holds and 5.7 percent in the nonmember households. This suggests that overall income
risk does not appear significantly greater among members than nonmembers.

Effects of New Export Crops
on Land Use and Land Market
Despite the small absolute differences in farm size, cropping patterns change sub-
stantially by farm size. It is particularly interesting to note the case of maize. With
increasing farm size, the share of maize in land use increases in member farms but
decreases in nonmember farms (Table 14). Snow peas-the principal new export
crop-have a relatively higher share in smaller farm-size classes of cooperative members.
While the probit model (Table 10) indicated that the choice to become an export
cropper is biased toward the somewhat larger farms within the small-farm sector, the
relative scale at which new export crops are adopted (once the decision to grow them
has been made) appears larger in the smaller farms (or at least the same as in the
bigger farms if snow peas and broccoli-cauliflower are viewed together). It is noteworthy
that some nonmembers of the cooperative also grow the new crops. They are mainly
located in one village close to the Inter-American Highway, where traders have started
to pick up export vegetables.
An effort is made in the survey to assess differences in land quality between member
and nonmember farms. Farmers were asked to evaluate each of their fields according
to a scale of 1 to 4 ("very good," "good," "not so good," "poor") in comparison with

Table 14-Cropping patterns of cooperative members and nonmembers, by
farm size, 1985
Broccoli, Traditional
Farm Size Maize Beans SnowPeas Cauliflower Vegetables Other
(hectares) (percent of cropland)
Less than 0.25 35.3 3.2 44.9 ... 14.5 2.1
0.25-0.50 41.4 5.0 28.9 8.4 13.5 2.6
0.50-1.00 45.3 6.6 27.7 13.0 5.2 2.3
1.00 or more 48.4 5.7 25.6 12.5 5.3 2.5
Total 46.7 5.2 28.0 11.1 6.7 2.4
Less than 0.25 67.7 13.1 5.8 ... 12.4 0.5
0.25-0.50 60.0 19.0 4.8 1.8 11.0 3.4
0.50-1.00 60.7 14.2 7.0 4.1 12.7 1.3
1.00 or more 54.0 12.8 15.8 7.0 9.1 1.3
Total 66.1 11.7 6.3 2.5 11.4 1.9

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,

the land quality in their community. A variable derived from this subjective evaluation,
included in the probit model in Chapter 4, was insignificant for adoption. Although
the distribution pattern of the surveyed fields by members and nonmembers (Table
15) underscores that there are no indications of substantial difference in land quality
between member and nonmember farms, there is a clear indication that cooperative
members grow the new export crops on their better pieces of land. The members
planted new export crops on 69.2 percent of their land identified as "very good," but
on only 31.6 percent of the land classified as "not so good."
The much higher returns of new export vegetables per unit of land, compared with
traditional local vegetables or subsistence food crops, can be expected to impinge on
the local land market. Demand for the quality land should increase, thus increasing
land prices in the prevailing situation of extreme land scarcity. Given the shortage of
cash and limitations of collateral for borrowing substantial amounts of money, the
increased demand for land is hypothesized to be largely realized on the land-rental
market rather than through land purchases. Yet, as the survey indicates, both the
land-rental market and the land-purchase market appear to be stimulated by increased
land demand from export crop growers. Cooperative members use a significant share
of their rented land (20 percent) for the new cash crops (Table 16). Also, members
pay higher rents per hectare of land used for new cash crops than for land rented and
used for subsistence crops (rents per hectare are 42 percent higher for export vegetable
fields). This may be due to the better land quality demanded for these crops.

Table 15-Relative quality of land of cooperative members and nonmembers
and of land used for the new export crops
Share of
Parcels Used
Share of Parcels in Each Quality Group byMembers for
Land Quality Members Nonmembers NewExportCrops
Verygood 10.2 7.2 69.2
Good 74.3 74.4 55.9
Not so good 14.9 17.6 31.6
Poor 0.6 0.8 0.0

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,

Table 16-Landownership of parcels and use for new cash crops
Cooperative Members
Share of Nonmembers
Share of Parcels Used for Share of
Land Status All Parcels New Cash Crops All Parcels
Owned 76 73 77
Rented 17 20 15
Other' 7 7 8

Source: Institu e of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
a Other forms f land acquisition, that is, temporary reallocations of land among members of a family.


Cooperative members expanded their own total land area during 1984 and 1985.
Nonmembers had only a small increase. The reported net increase of members' land
is 12.2 percent of the 1985 area compared with a 1.4 percent increase in the nonmember
group. Land purchases are more frequent among the members, as 23 percent of the
members reported a land purchase during the two years compared with only 8 percent
for nonmember households. Usually very small amounts of land are purchased. Coopera-
tive members were paying much higher prices for new land than nonmembers (Q6,272
versus Q3,150 per hectare). As in the case of rented land this may be due to the
members' demand for more quality land for expansion of new export crop production
versus the nonmembers' acquisition of more land for maize and beans.
Two conclusions are highlighted from this assessment of the effects of new export
vegetables on the land market. First, the effective demand for land is increased as
export crop producers expand their landholdings through rentals as well as land pur-
chases. This expansion tends to further widen the existing gap in land size within the
small-farm sector between export crop producers and other farmers. In the long run,
it should be expected that a concentration of quality land will evolve in the sector of
new export crop farmers, although currently there is no evidence of such a distinction.
Second, increased land values may be realized by land sales, renting out land, or
making use of the increased collateral value of owned land on the capital market.
Landowners in the area thus benefit from the increased land values induced by export
crop production, regardless of whether they actually are export crop producers. Ad-
versely affected through this effect are farm households that rent in land, especially if
they have not taken up export cropping. Maintaining subsistence food levels from own
production on rented land has become more expensive. The pressure to either give
up rented land or join the export cropping scheme is increased due to the increased
cost of land rental.

Effects of New Export Crops
on Labor Demand and Employment
The new export crops create employment directly on the field and through forward
and backward linkages, and indirectly through multiplier effects of the related income
and employment. Their backward linkages are substantial. These crops have much
higher input demands-not only for pesticides and fertilizers, which are not very labor
intensive-but also, in the case of snow peas, for the locally manufactured sticks and
ropes required for tying plants. Also, forward linkages are significant for employment,
as the operation of the first stage of marketing is quite labor-intensive (selection,
screening, and packing of produce). There are indirect employment effects from poten-
tially higher income spent on goods and services with a high employment content.
The following discussion focuses on the direct employment effects.
The new cash crops require much more labor input per unit of land than maize,
the main subsistence crop (Figure 5). Snow peas also require more labor than traditional
vegetables. Hired labor input is substantial, not only in the cash crops but also in
subsistence maize, as more than half of the total labor input in maize is hired.
Most labor in all crops is provided by men, but this varies by crop type and by
farm-size class. Women are responsible for 9 percent of family labor in maize, 25
percent in traditional vegetables, and 31 percent in snow peas (Table 17).
Family labor input per hectare decreases with increasing farm size for maize and
traditional vegetables as well as for new export crops (Table 18). This family labor
input is combined with increased hired labor inputs. Even in the smallest farm-size

Figure 5-Labor inputs for traditional crops and new export vegetables on
cooperative members' farms, 1985
700 -
a Family labor, men

SFamily labor, women
Family labor, children

Hired labor


300 -


100 -

0 -


Maize Traditional Broccoli, Snow Peas
Vegetables Cauliflower
Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,

Table 17-Shares of men, women, and children in total family labor of
cooperative members, by crop
Broccoli, Traditional
Labor Maize SnowPeas Cauliflower Vegetables
Men 85 59 70 61
Women 9 31 20 25
Children 6 10 10 14
Source: Computed from Table 18.

classes substantial wage bills per hectare are incurred from new cash crop production
(Table 19).
Division of family labor among men, women, and children in the production of
new export crops is not uniform across farm size. As shown below, men's share of
total family labor remains quite stable across farm-size classes, while women's share
declines and children's share increases.

Farm Size Men Women Children
(hectares) (percent of family labor)

Less than 0.25 59 39 2
0.25-0.50 59 33 7
0.50-1.00 58 32 10
1.00 or more 58 26 15

With increasing farm size women's labor is relatively replaced by hired labor and child
labor. This is not true for men's labor. The high substitution between women's labor
and hired labor is a phenomenon observed widely across countries of the Third World
(see, for instance, Boserup 1970, 30). It is probably related to the increasing opportunity
cost of women's labor in the field when the combined household and farm enterprise
expands. Returns to female household labor, including such activities as meal prepara-
tion for hired labor, increase and lead to higher degrees of specialization within the
farm-household. This still means that absolute levels of family labor input by both men
and women may increase with increasing farm size.
The pattern of hired labor use changes with the introduction of new export vege-
tables. Cooperative members demand more hired labor for the subsistence crop (maize)
on a per hectare basis than do nonmembers in the same farm-size class (Table 19).
This demand for hired labor is a result of the inability of family labor to meet the
increased demand of producing cash crops. The production level of traditional crops
is maintained to a certain extent by hiring outside labor for their cultivation.
The direct employment effects of new export crops on farms can be approximately
accounted for by tracing the partial effects due to (1) switching land between traditional
crops and new crops, (2) the change in labor input per unit of land, and (3) related
substitutions between types of labor input, that is, family labor (men, women, children)
and hired labor. These changes of allocation of crops and labor differ by farm size. In
a given farm-size class (i) the net employment effect (E) is then

Table 18-Average family labor used per hectare by cooperative members
and nonmembers, by farm size and crop
Members Nonmembers
Snow Broccoli, Traditional Traditional
Family Labor Farm Size Maize Peas Cauliflower Vegetables Maize Vegetables
(hectares) (person-days/hectare)
Men Less than 0.25 64 350 ... 271 53 399
Women 8 228 ... 141 7 68
Childrena ... 10 ... 0 4 53
Total 72 588 ... 412 64 520
Men 0.25-0.50 49 272 105 176 60 180
Women 6 152 25 100 6 69
Children' 1 34 0 57 5 36
Total 56 458 130 333 71 285
Men 0.50-1.00 50 231 133 181 52 249
Women 6 126 41 61 7 90
Children' 4 39 15 61 1 6
Total 60 396 189 303 60 345
Men 1.00 or more 37 200 104 167 42 169
Women 2 91 25 64 2 44
Children' 5 53 26 12 2 12
Total 44 344 155 243 46 225
Men Allsizes 45 234 117 181 54 239
Women 5 125 33 76 6 69
Children' 3 41 18 42 3 28
Total 53 400 168 299 63 336

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
a Children's labor input is weighted with 0.6.

E = [ (as, *L- a,* Li,)+ wi*. L*- wil L1], (4)
ais, aijs = per hectare labor input (days) of family labor types
s(s= 1,..., 3)incropj(j= 1,..., 6)andfarm-
size class i(i = 1, ..., 4) with (a*) and without (a)
the new export crops in the production program,
w*, wi = per hectare wage labor input (days) with (w*)
and without (w) the new export crops, and
L*, Lij = land used (hectares) for each crop (j) in farm-size
class (i) with (L*) and without (L) the new export
While the situation of new export crops is represented by the situation of land and
labor allocation in the cooperative member farms, the "without" situation is represented
by nonmember farms of the respective farm-size class that do not grow the new crops.
Participation in the scheme was found to be influenced by farm size and secure off-farm
employment (see the probit model above). While the farm-size effect is accounted for
by the disaggregation into farm-size classes, the effect of off-farm employment is not.
One might suspect that cooperative member farmers were growing some of the more
labor-intensive traditional vegetables before they switched to export vegetables. This
hypothesis, which can be assessed by the small number of farmers who became members
between the two surveys, is not supported. Therefore, the cross-sectional evaluation

Table 19-Wages paid for hired farm labor by cooperative members and
nonmembers, by farm size and crop
Members Nonmembers
Snow Broccoli, Traditional Traditional
Farm Size Maize Peas Cauliflower Vegetables Maize Vegetables
(hectares) (quetzals/hectare)
Lessthan0.25 135 158 ... ... 95 141
0.25-0.50 159 469 149 128 65 73
0.50-1.00 143 618 249 350 122 438
1.00 or more 209 570 368 340 136 358
Average 168 553 284 306 96 165
Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,

of the employment effects appears reasonable. Table 20 presents the results of the
above computations. The main findings are as follows:
1. Labor input in agriculture increases in the export crop-producing farms by 45
percent (81 days per crop season).
2. This increase is equally shared by family labor and hired labor.
3. The increased labor demand results primarily from snow pea production. On
average, labor is cut back in maize by 7 days (13 percent), beans by 6 days (43 percent),
and traditional vegetables by 12 days (29 percent), but total hired labor input into
maize increases somewhat.
4. In the smallest farm-size class virtually all the net increase in labor input comes
from family labor. Total labor input on these farms of less than 0.25 hectare more than
5. With increased farm size more hired labor is covering the increased work load,
but in all four farm-size classes family labor input increases by a roughly similar absolute
6. A substantial share of the increased family labor is from women-44 percent in
the two smallest farm-size classes and 32 percent in the largest farm-size class.
The farm-level data can be used to extrapolate the employment effects to the six
communities where the cooperative is operating. For 1985, the increased labor demand
in crop production corresponds to about 15 percent of agricultural employment. When
added to the employment in input supply (special input shops in the villages and special
production inputs for snow peas) and output marketing (cooperative staff), it yields an
increase in agricultural employment of 21 percent.
Clearly, the employment effects are significant and impinge on off-farm employment
and interregional migration in the location. Among export crop producers an average
of 0.72 persons per household work away, compared with 0.92 family members among
the other sample farmers. Also, nonmembers of the cooperative spend more time away
over the year (4.2 versus 2.3 months on average).
The increased demand for hired labor in the region spreads the employment effect.
Much of the hired labor comes from neighboring communities where export crop
production has not been introduced.

Effects of New Export Crops on Staple Food Production
The evaluation above shows that new export vegetables yield higher returns per
unit of land and labor than subsistence crops. Yet cooperative members still plant on

Table 20-Direct employment effects of the new export vegetables, by farm
Change in Labor Input Due to Shifts in Crop Area and Reallocation of Labor
Farm Size/ Traditional Other Broccoli, Snow
Labor Maize Beans Vegetables Crops" Cauliflower Peas Total
(hectares) (person-days ofwork/year/farm)
Less than 0.25
Family -4 -2 -2 +1 ... +57 +50
Hired 0 0 -5 0 ... +6 +1
Total -4 -2 -7 +1 ... +63 +51
Family -11 -6 +4 0 +2 +61 +50
Hired +5 -2 +2 +2 +2 +26 +35
Total -6 -8 +6 +2 +4 +87 +85
Family -9 -6 -15 +1 +7 +58 +36
Hired -4 -1 -1 -4 +1 +42 +33
Total -13 -7 -16 -3 +8 +100 +69
1.00 or more
Family -9 +2 -11 +3 0 +62 +47
Hired +9 -5 -10 +7 +15 +42 +58
Total 0 -3 -21 +10 +15 +104 +105
All sizesb
Family -9 -4 -9 +1 +3 +59 +41
Hired +2 -2 -3 +1 +5 +37 +40
Total -7 -6 -12 +2 +8 +96 +81

Source: Computed from data from Institute of Nutrition of Central America and Panama/International Food Policy
Research Institute survey, 1985.
a Includes tree crops and fruits.
b Weighted by the distribution of farm-size classes.

average half of their land with maize and beans. Although this is significantly less than
nonmember farmers, it is still a large proportion. No obvious technical reason exists
why farmers should not further expand their export vegetable area, as suitable land
remains in reserve (Table 15). Hired labor is available in the region to fill increased
labor demand. In the smallest farms, underemployed family labor or family labor seeking
off-farm employment could be drawn into the export crops, since average returns per
workday are much higher than the prevailing market wage rate (Table 13). This produc-
tion behavior can be hypothesized as driven by the concern of farmers about risk of
the new crops (the potentially high absolute losses per unit of land were discussed
above) and the household's desire for food security.
A household is in a secure food situation when it always-throughout the seasons
and over the years-has the ability to acquire the food needed to maintain the health
of all its members. In farm households, household-level food security may be achieved
by own food production and related stockholding, or by relying on open-market trading
of food and nonfood production to generate income (and savings), or partially by seeking
off-farm, income-earning possibilities. The level and mix of these alternatives depend
upon a household's resource endowments, including human capital; the type of market
integration for agricultural produce, food, and labor; and the extent to which public
institutions (intervention schemes) or community-level institutions (villages, extended
family) play a role in providing basic levels of food security in view of unforeseeable
circumstances. It is obvious that with decreased institutional provision of food security,
lower security of off-farm employment opportunities, and more instability of the agricul-

tural produce and food market, the food security burden shifts toward own production
and stockholding. The historical record of food security in the Western Highlands
suggests that these are the driving forces that lead farm households to maintain high
levels of staple food production for direct household consumption. The survey region
as a whole is, however, not self-sufficient. About 50 percent of maize consumed in the
six survey villages consists of net imports into the region (Table 21). Self-sufficiency in
maize is 67.7 percent among cooperative members and 53.4 percent among nonmembers.
Public institutions cannot ensure effective response to household or local crisis
situations. The food and agricultural produce markets are very unstable, as is the labor
market. It can thus be hypothesized that farm households operating below or at the
margin of food security provided from own food production put a risk premium on
nonfood income-earning alternatives. This risk premium-or food insurance premium-
that farm households are indirectly paying is represented by the difference between
the actual market price of staple food and the shadow cost of production of staple food
at the margin. Clearly, the shadow cost of staple food production increases when the
opportunity costs of land and labor increase as a consequence of introduction of a new
cash crop that yields higher returns to land and labor. To what extent this occurs in
the case studied here will be evaluated with a farm model later in the chapter. Before
this normative aspect is discussed, another question will be addressed: What actually
happened to food production when the new export vegetables were introduced?
Practically all export crop producers (94 percent) maintain some maize production.
Ninety-seven percent of the other sample farmers grow maize. Farm households were
asked in the 1985 survey what the three most important reasons are for them to grow
maize. By far the most important reason stated was "to always have food" (Table 22).
Differences between export crop producers and other farmers are small in this respect.
The second most important reason, tradition ("we always did it like that"), was followed
by the perception that "other crops are risky" and the statement that "maize is profit-
able." Much has been written about traditional and religious motivations of Western
Highlands farmers for growing maize.15 While most farmers do not give up their milpa
(cornfield) and plant it with something else altogether, their attitude toward maize and
its importance in the production program obviously undergoes change. The introduction

Table 21 -Consumption of own production and net purchases of maize in
cooperative member and nonmember households, 1985
Consumption of Own- Net Purchases
Households Produced Maize' ofMaize
(percent of maize consumption)
Cooperative members 67.7 32.3
Farmers 53.4 46.6
Nonfarm households ... 100.0
Weighted average for the
six cooperative villages 50.4 49.6

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
a Excluding use for animal feed.

15 A comprehensive piece is, for instance, Bossen 1984; insights are also provided by Gladwin 1983,

Table 22-Farmers' attitudes toward growing maize
Ranking of Reasons
Cooperative Members Nonmembers
Stated Reason for Most Most
GrowingMaize Important Second Third Important Second Third
(percent of responses)
To always have food 84 10 2 86 11
We always did it like that 3 57 15 1 57 19
Other crops are risky 1 7 16 ... 8 12
Maize is profitable ... 2 9 ... 5 6
Other 9 12 7 11 10 7
Not applicable 3 12 51 2 9 56

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,

of new export crops plays a role in this context, and at the same time, the adoption
of new crops is affected by these attitudes. This was already apparent in the adoption
model (Table 10) and is further revealed when the reasons stated for growing maize
are compared for early versus late adopters of new export crops. Long-term members
of the cooperative are more concerned about own-produced maize supply than are new
members (Table 23). Also, the early adopters have been or have become less traditional
in their decisionmaking on production; the importance of tradition decreases with
duration of membership in the cooperative. Long-term members also view other crops
as less risky than do new members.
This change in attitude patterns does not lead to a reduction in maize availability
from own production for consumption. In fact, when corrected for farm size, the
majority of export crop growers tend to have similar or higher amounts of maize
available for consumption from own produce than other farmers (Table 24). Despite
reductions in area and labor inputs to maize, household-level production is maintained
because of higher yields of the staple food per unit of land. Cooperative members'
maize yields are 30 percent higher on average than those of nonmembers (Table 25).
However, because of higher shares of land use for beans, the nonmembers have in the
aggregate a somewhat greater subsistence-food availability (maize and beans together)
than the members.

Table 23-Reasons for growing maize stated by farmers, by duration of
cooperative membership

Years of Membership in Cooperative
More than Less than
Reason 5 Years 3-5 Years 3Years
To always have food 92 89 82
We always did it like that 51 62 64
Other crops are risky 9 20 23

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
aOne, two, or three reasons could be stated; therefore, the percentages do not add up to 100 (see Table 22).

Table 24-Production of subsistence maize and use for consumption in farm
households, 1985
Cooperative Members Nonmembers
UsedforOwn Used forOwn
Farm Size Production Consumption Production Consumption
(hectares) (kilogram/adult equivalent)b
Less than 0.25 48 41 59 49
0.25-0.50 103 88 95 82
0.50-1.00 131 113 127 97
1.00 or more 182 137 180 138
Average 142 115 109 87
Source: Computed from data from Institute of Nutrition of Central America and Panama/International Food Policy
Research Institute survey, 1985.
a Calculated from a complete production and disappearance balance (production minus sales, losses, animal feed,
gifts, seed).
Adult equivalents are based on calorie requirements of persons in the household by age and sex.

The two surveys of the same farms permit a comparison of farmers' maize yields
once they had moved from nonmember to member status and from recent to long-term
members. Maize yields were substantially higher in 1985 than in 1983 in all groups.
Climatic conditions played a role in these yields. As shown below, the increase was
highest in the group consisting of cooperative members who had joined 3 to 4 years
earlier and above average in the group who had joined 5 to 6 years earlier.
1983-85 Change in
Status of Group Kilograms per Hectare

Nonmembers in 1983 and 1985 + 272
Members since 1984 or 1985 + 45
Members since 1982 or 1983 + 456
Members since 1980 or 1981 +314

By far the lowest yield increase is in the group of cooperative members who had joined
most recently. Their yield increase is even below that of nonmembers. This pattern
gives some insights into the dynamics of maize yields in the context of increased export
crop production: initially, yields per hectare stagnate or may even drop when the
farmer gives much of his attention and resources to the new crops, thus pushing maize
onto the more marginal land of his farm. A couple of seasons later, maize yields
apparently do catch up. Appropriate program and policy packages that help farmers to
speed up in catching potential positive spillover effects from new cash crops to subsistence
crops may have high returns and assist in ensuring against household-level food insecurity.
A combination of factors is responsible for the maize yield increases among coopera-
tive members. Fertilizer inputs increased by an average of 6 percent and cropping
practices are more labor-intensive among members. Total labor input to staple foods
decreases, but labor input per unit of land is increased by 18 percent (mostly for more
weeding). Much of the additional weeding labor is hired. Despite increased inputs
(fertilizer) and labor, cooperative members produce maize at lower average cost per
unit of output. When the cost of family labor is estimated with the prevailing wage
rate, members produce a ton of maize for Q189, while nonmembers produce a ton for
Q214. Thus, members appear to be more efficient-whether they were so before

Table 25-Yields of subsistence food crops on cooperative member and
nonmember farms, 1985
Cooperative Members Nonmembers
Farm Size Maize Beans Maize Beans
(metric tons/hectare)
Less than 0.25 (2.3) (1.1) 1.8 0.5
0.25-0.50 2.4 (0.7) 1.7 1.5
0.50-1.00 2.1 1.2 1.5 0.6
1.00 or more 2.2 1.8 1.7 0.8
Average 2.2 1.3 1.7 1.0

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
Note: Figures based on less than 10 observations are in parentheses.

joining the scheme or became more efficient through joining the scheme is an issue
addressed in more detail below. Both of the above cost figures come close to the
prevailing farmgate selling price of maize, which was Q210 on average in the 1985
sample period. Average costs are not much different from marginal cost in this produc-
tion system.
A closer look at the subsistence crops-export vegetable interaction is provided in
the following production function and a programming-model analysis. The objective of
this analysis is to assess competition and complementaritybetween the new crops and
the subsistence crop (maize) in particular. The approach will be briefly described at
the outset.
Crop production (q) is technically a result of area (a) times yield (y) of a crop (i):

qi = y,. (5)

Choices on the use of inputs, technology, and the amount and quality of land for a
certain crop are joint decisions. Acknowledging the problem of separating these deci-
sions, competition between crops can be built into an area allocation function, while
input-output relations may be assessed on a per unit of land basis in a yield function.

a,= biiX, and (6)

yi= bo+ biXm, (7)

where biN and bim are the parameters of the area allocation and yield function of the
respective exogenous variables Xi and Xm. While the X in the area allocation model
is mainly describing economic environment and depicts the related response of farmers,
the Xm in the yield model covers technical input-output relationships.
It is hypothesized that consumption needs (calorie requirements) determine, among
other things, that the traditional farm households plant a certain share of their total
area with maize. With increased farm size, this "subsistence needs-oriented" determin-
ation of the maize area is reduced. The worse the land quality of a farm, the higher
the share of land required for maize for subsistence needs, everything else being equal.
It is also hypothesized that a more traditional attitude toward maize would lead to an
increased share of maize land.

Maize is only to a minor extent a "cash crop," but its area share should be expected
to be affected by the relative returns to maize versus new export vegetables after
desired subsistence levels are fulfilled along the above-stated hypotheses. It is also
expected that membership in the cooperative leads to a decreased maize area share
beyond the above-mentioned factors, as the cooperative stimulates the growing of new
crops. Finally, village-specific dummy variables are included in the model, since the
land-quality variable is based on village-specific comparisons of farmers and not on a
generalizable measure.
The estimation results of the area model specified along these hypotheses are in
Table 26. The model explains a high share of the variance in maize area allocation (85
percent). The following findings will be highlighted:
1. Production is very much driven by staple food needs; this becomes evident from
the highly significant variable representing the calorie requirements of the household
(ACU). One additional adult-equivalent unit in the household leads, all else (including
farm size) being equal, to an expansion of the maize area share by 6 percentage points.
Clearly these semisubsistence households not only (partly) consume what they grow
but also base their maize production decisions on consumption requirements.
2. Households with a more traditional attitude toward maize (DMZREAS) have a
higher maize area share, but smaller farms plant relatively less area with maize (FSZHA).
Both determinants are statistically highly significant.

Table 26-Area allocation to maize and the effects of export vegetable
production: regression model

Variable Parameter t-Value

DCID5 0.03370 0.647
DCID4 0.09424 1.855
DCID3 -0.03591 -0.892
DCID2 0.12100 2.391
DCIDI 0.11986 2.454
RGM -0.04209 -1.075
MZLANDQ 0.18134 16.542
FSZHA -0.06416 -2.792
DMZREAS 0.06791 2.238
ACU 0.06005 10.189
MIEM -0.04272 -1.509
R2= 0.85, DF=337

Notes: Dependent variable: maize area over total farm size.
DCIDI ... 5 = dummy variables for villages 1 through 5 = 1, else = 0;
RGM = ratio of gross margin of new export crops over gross
margin of maize;
MZLANDQ = quality of area under maize (1,..., 4; 1 = best);
FSZHA = farm size in hectares;
DMZREAS = traditional attitude toward maize = 1, else = 0; 1 = "we
grow maize for own consumption because we always did
it like that";
ACU = calorie requirements of households (adult equivalents);
MIEM = membership in the cooperative = 1, else = 0.

3. The worse the land quality (MZLANDQ) the bigger the area share of maize. This
is to be expected, as alternative crops have less comparative advantage on such land
and households also have absolute targets of maize supply from own production.
4. Cooperative membership (MIEM) tends to decrease the area allocated to maize
as expected; the net effect is about 4 percentage points, thus, all else being the same,
maize area decreases from 60 to 56 percent. The respective parameter is not highly
5. The ratios between the gross margins of maize and the new export vegetables
do not turn out to be significant (RGM). It is probably only in the long run that their
obvious role comes into play significantly.
Maize yield models are estimated for the total sample (model 1) and separately for
the cooperative member farmers (model 2). Finally, yield model 2 is modified by
including the degree of participation in export crop production to assess its effects on
maize yields beyond the common production factors (model 3).
A heuristic approach is taken to specification of the yield models. From increased
fertilizer use, higher yields are expected though decreasing at the margin. Increased
labor input should have positive yield effects. With better education, farmers are ex-
pected to make more efficient use of resources and get higher yields. On smaller farms,
it is hypothesized, farmers pay more attention to yields beyond the factors mentioned.
Yields are expected to be lower on plots of lower land quality.
The estimation results of the yield models formulated along these hypotheses are
in Table 27. The main findings of this analysis are as follows:

Table 27-Maize yields and effects of export vegetable production: regression

Total Sample Cooperative Members Only
Model 1 Model 2 Model 3
Variable Parameter t-Value Parameter t-Value Parameter t-Value

DCID5 382.65000 1.729 621.41000 1.844 505.53500 1.512
DCID4 -65.68800 -0.298 23.72200 0.075 67.34400 0.217
DCID3 -6.77190 -0.039 -48.71030 -0.183 -56.24500 -0.215
DCID2 -824.29200 -3.886 23.72290 0.075 -877.94900 -2.527
DCIDI -40.26500 -0.195 513.74800 1.390 -58.24500 -0.215
MZLANDQ -136.25200 -2.196 -34.01890 -0.265 68.67100 0.518
HHEDUC 33.77700 0.933 155.39500 2.645 162.74200 2.815
LABDAYSI 2.20680 2.081 4.07790 2.517 3.69015 2.307
RAREA34 .. .. .. ... 811.23180 2.506
FSZHA -17.92300 -0.186 -70.33560 -0.482 35.65770 0.238
INPUTI 9.81776 4.021 9.48170 2.144 8.14740 2.095
SQINPUTI -0.02326 -2.973 -0.02451 -1.820 -0.02445 -1.848
(constant) 1,256.55000 4.449 834.56600 1.873 383.55100 0.810
R2 = 0.19 R2 = 0.20 R2 =0.23
F =7.02 F =3.40 F =3.75
DF= 326 DF= 148 DF = 147

Notes: Dependent variable: maize yields in kilogram per hectare, 1985.
DCID5 = dummy variables for villages 1 through 5 = else = 0;
MZLANDQ = quality of area under maize (1,..., 4; 1 = best);
FSZHA = farm size in hectares;
HHEDUC = years of schoolingof head of household;
LABDAYSI = total labor days in maize per hectare;
RAREA34 = area under new export vegetables over total area (ratio);
INPUTI = cost of fertilizer per hectare of maize; and
SQINPUTI = cost of fertilizer per hectare of maize (squared).

1. Input levels of fertilizer (INPUT1) increase yields as expected, and at decreasing
rates as the negative sign of the squared term indicates (SQINPUT1). Fertilizer cost
per hectare is used as a proxy for nutrients. Differences between the cooperative
members and the total sample are not significant in this respect. One additional quetzal
spent on fertilizer yields-calculated at sample means-4.9 kilograms of maize at the
margin, which sold for QO.98-1.23 on the market.16 This suggests that fertilizer use
is in the range of efficient levels.
2. Increased labor inputs (LABDAYS1) have a higher than average positive yield
effect on cooperative farms. Although marginal labor productivity in maize is higher
among members than for the total sample, marginal returns to labor of Q00.82-1.02
(model 2 with maize price of QO.20-0.25) in the subsistence crop are at the lowest
end of the prevailing wage rates, which were 02.00-2.50 per day in 1984 for men
and Q1.00-2.00 for women.
3. A striking result is that better education significantly shifts the yield function
upward in the group of cooperative members but does not do so in general (model 2).
Apparently literacy becomes increasingly more relevant for productivity when the farms
become more complex with the new export crops included in the production program
Than it does in general (model 1). This is fully in line with the finding of the specific
study on the effects of education on Guatemalan agriculture (Freire 1981, 107-145)
that illiterate and literate farmers operate on the same aggregate production function,
but literate farmers are technically more efficient than illiterate farmers on more diver-
sified farms.
4. Land quality (MZLANDQ) tends to affect yields as expected; here it becomes
clear that separating the area allocation effect from the yield effect of production is
useful, as the effect of land quality works in opposite directions in the two functions
of the model.
5. A striking effect results from the new export vegetables in the crop production
program (RAREA34): the higher the share of new crops in the land use, the higher
the maize yields even after accounting for different levels of inputs, labor use, and
human capital (model 3). Two explanations for this result come to mind. First, the
snow pea crop increases the soil-nitrogen levels, which benefits maize if maize follows
in the rotation on that land. Second (and more hypothetical), export crop producers
improve crop management, which leads to higher efficiency in input use in maize.
This effect is then not captured in the input and labor variables. It is plausible that
export vegetable producers, in their desire to increase yields of maize for the purpose
of maintaining household food security, eliminate Leibensteinian "x-inefficiencies"
tolerated before (Leibenstein 1966). The parameter estimated in the yield function
implies that joining the scheme with average allocation of land to the new crops
(RAREA34) results in a yield increase by 11 percent above the result from higher
fertilizer input and labor use per hectare. The higher yields among cooperative members
are to this extent a result of the complementary interaction with the new export crops
and not just a result of inherently higher efficiency of members.
To sum up, the analysis on the basis of area and yield functions for the subsistence
crop (maize) shows that new export vegetables play a complementary rather than a
competitive role in the system. Although maize area is reduced and partly squeezed
onto land of lower quality, increased input use (fertilizer and labor), favorable soil-fertility
effects of the main new crop (snow peas), and more efficient crop-production practices

16 Maize prices ranged between Q0.20 and Q0.25 per kilogram in the 1984/85 crop year.

overcompensate for the adverse effects and leave export crop producers with higher
yields and total supply levels of the subsistence crop. This finding is in line with findings
by Reyes-Hernandez, Garcia, and Campos (1985), who diagnose positive yield-increasing
spillover effects for the traditional food crop (maize) in more diversified farm-production
systems in the area of Chimaltenango (Western Highlands). In their small sample of
farms, maize yields in the diversified systems were about 40 percent higher than in
the traditional system.

A Premium for Own-Produced Maize: Model Results
The context in which this interaction between new export vegetables and subsis-
tence crops takes place is not only the field crop operation of the farm enterprise but
the farm production-consumption unit. To evaluate the effects of introduction of the
new crops on farm households' incentive to provide food security from own production,
a linear programming model is constructed.17 Applying a programming model with a
profit-maximizing objective function under constraints does not imply an assumption
that the farm households in the Western Highlands are single-minded, short-term profit
maximizers. It is recognized that a multitude of objectives exist for farmers that may
be only partly captured by the constraints introduced into the model. All evidence from
the evaluation of response to crop profitability, however, suggests that small highland
farmers are managing their agricultural resources and their own time very efficiently
and rationally in an economic sense. Still, opposite conclusions have sometimes been
drawn for the highland farmers. Gollas (1977), for instance, concludes (from a Cobb-
Douglas production function analysis with results that show a positive marginal produc-
tivity of farm labor in view of an assumed general surplus labor situation) that the
highland farmers are "poor and inefficient." More careful production function analyses
by Marsh, Jameson, and Phillips (1983) and Stein (1982) as well as the assessment of
households' flexible response to returns to time inside and outside agriculture by
Swetnam (1980) clearly refuted Gollas's "poor and inefficient" conclusion for the
traditional farmers of the highlands.
Although only a small proportion of farm households sell subsistence crops (13
percent of all maize producers in the sample sold maize during the year), almost all
farm households grow maize for own consumption. The cost of this maize to the farm
household is determined by the opportunity cost of the resources used for its production.
Obviously the opportunity cost of maize production increased when farmers had the
option of growing snow peas. It thus follows that consumption of own-produced maize
should have become more costly. To what extent is this actually the case? How did
farmers respond to this change in this key shadow price?
The model is based on average data of the 0.50-1.00 hectare farms in the sample.
Three versions of a farm model are used for comparative static analysis: model 1
represents the situation before new export crops were introduced; model 2 represents
the situation after export crops were introduced, but yield levels and technology in
subsistence crops are not changed; and model 3 represents the situation as in model
2, but with actual improved productivity in subsistence crops.
The three model versions are described in the Appendix. The main features of the
model are the usual constraints on land and family labor (by season). Inputs (fertilizer,
pesticides), hired labor, and input financing are available at exogenously fixed prices.

17 Average data from the 0.50 hectare and 1.00 hectare farm-size classes are used for the model's coefficients.

Rotational restrictions follow the ones widely accepted by farmers. In all three model
versions, household demand for staple food (maize or beans or both) is maintained at
the same level as observed in the respective class of sample households. Family labor
of men and women-but not children-may also earn income from off-farm employment
at a constant wage rate.
In the initial situation (model 1) the shadow cost of maize produced for own
consumption is Q0.49 per kilogram (Table 28)-more than twice the average sales
price of maize in the respective survey year (Q0.21) and substantially higher than the
average purchase price (Q0.26). Clearly, farm households are willing to pay the price
in terms of income forgone to have maize from their own fields. The difference between
the shadow cost of maize production for own consumption and the actual purchase
price of maize can be interpreted as a "food-security insurance premium." In 1985
the premium was Q0.23 per kilogram in farm households that did not grow the new
export vegetables. When the new export crops become an option for the farm household,
this insurance premium increases drastically-nearly quadrupling, as demonstrated
with model 2 versus model 1 (from Q0.23 to Q0.90 per kilogram). Maintaining subsis-
tence production becomes more than twice as costly as before: the shadow cost of
maize production increases from Q0.49 to Q1.16 per kilogram. While there was an
incentive before, as indicated by the 1985 insurance premium, to bring down the unit
cost of production for subsistence, this incentive was much increased by the introduction
of competitive export vegetables.
Households have two options in responding to the increased cost of food security
provided from own production. They may simply cut back the staple food production
or increase its productivity (or a combination of the two). The yield function analysis
above demonstrated that they most often choose the latter. This option's effect on the

Table 28-Effects of new export vegetables on shadow cost of subsistence
food production and selected other variables
Model2 Model 3
Model I After Introduction of New Export Crop
Before Intro- Without Improved With Improved
duction of New Productivityin Productivityin
Variable Export Crop Subsistence Crops Subsistence Crops

Land use (hectares)
Subsistence crops 0.49 0.49 0.35
Traditional vegetables 0.26
Snowpeas ... 0.26 0.40
On-farml (days in model 100) 100.00 124.00 165.00
Off-farm d in model 1 = 100) 100.00 84.00 55.00
Share of family labor on farm (percent) 49.30 59.60 75.00
Working capital
Overyear (quetzals in model 1 = 100) 100.00 304.00 441.00
In percent of cash income 24.50 51.40 58.10
Shadow price of land (quetzals/hectare) 456.00 1,455.00 1,455.00
Shadow cost of maize produced for own
consumption (quetzals/kilogram) 0.49 1.16 0.84
Difference to average maize purchase
price (quetzals/hectare) ("insurance
premium") 0.23 0.90 0.58

Notes: These results of programming model scenarios are for an average 0.75-hectare farm based on 1985 survey
of farms from 0.50 to 1.00 hectare. See Appendix for descriptions of the three versions of the model.

insurance premium is traced in model 3. Clearly, the cost of maintaining desired
household food security through production of staple food for own consumption can
be substantially decreased this way (from 0.90 to 0.58, as shown in Table 26). Still,
the insurance premium remains higher than in the situation at the outset. The incentive
remains high to further increase productivity in staple food production.
The new crops lead to an increased labor and capital intensity in agricultural
production. The new export crops require not only more absolute working capital but
also more relative capital in percent of total household cash income. Without new
export crops, working capital invested in crop production was about one quarter of
total cash income (model 1). With the new crops, it amounts to more than half of cash
income (58.1 percent, model 3).
With increased productivity of staple food, overall income increases and land is
freed for the new export crop that can generate additional income. The income increase
made possible by increased productivity of subsistence crops (going from model 2 to
model 3) is about as high as the income effect from the pure introduction of the export
vegetables without improved productivity in the staple foods (going from model 1 to
model 2). This key role of technological improvement in staple food production of
farms that have the option of growing new export crops must be understood in order
to maximize both income and employment opportunities.
In summary, the following conclusions are stressed from this analysis of the agricul-
tural production effects:
1. Export crops and subsistence crops are complementary rather than competitive
in the case studied.
2. Household-level food security through a high level of subsistence food production
was maintained or even expanded when new export crops were introduced. While
this is understandable and explainable with market failures-that is, failures in the
food market and in the labor market on which many of the small farmers with an
excess supply of labor depend-this approach to food security does not appear to be
the "first-best" economic solution, as indicated by the high "insurance premiums" paid
by farm households for own-produced subsistence food. A policy environment that
ensures the functioning of food markets without major disruptions is a precondition
for farm households to develop confidence in the market and consequently to make
use of the advantages of the exchange economy. It is thus a precondition for first-best
economic solutions to food insecurity. Options other than food security based on
own-produced food exist for the cost-effective provision of food security; for instance,
food-related income transfers or employment-oriented measures targeted toward the
absolute poor. Such measures would impinge on the observed resource allocation in
agricultural production biased toward staple food only if they were perceived as reliable
by the poor.
3. The shadow cost of staple food production for own consumption increases dras-
tically as returns to land and labor of the new export crops increase. In view of the
prevailing high preference for having maize from the own field for food security reasons,
the increased shadow cost of subsistence production did lead to some reduced area
allocation to staple food production. However, variable inputs (labor, fertilizer) per unit
of land increased. This and positive yield-increasing effects of the new crops in the
rotation permit reduction of staple food crop area along with an increase in food output
combined with the favorable income and employment effects of the new crops.
4. The Western Highlands farmers were able to adopt this balanced strategy of crop
diversification plus intensification of staple food production because of the availability
of yield-increasing measures, related input supply channels (seed, fertilizer), and hired

labor. In the absence of these conditions, farmers with strong preferences for subsistence
Crops will not adopt the export crop. The policy conclusion is obvious: if gains from
diversification and export crop production are to be achieved through rapid adoption
by small farmers without diminishing their food security in an environment of market
failures, farmers must have access to technology to enhance food crop productivity per
unit of land.'8

Effects of New Export Crops on Off-Farm Income
The previous chapters concerned production and related income effects. As stated
earlier, agricultural income is very much complemented by income from other sources
in these communities of the Western Highlands. In fact, it is often the other way
around: off-farm income is complemented by farm income in many households.
Patterns concerning sources of income differ by cooperative status (Table 29). In
general, nonmembers earn more income as agricultural day laborers and nonagricultural
workers than do members. Member households are also active in such off-farm income-
earning activities during the year, but they work fewer days off-farm, which explains
their lower absolute income from these sources. In addition, income from transfers
and remittances is not only higher on average in member households but also more
widely distributed. Seventy-five percent of the households reported transfers.
The distribution pattern of income by source suggests that export crop producers
withdraw from the off-farm labor market and spend more of their time in agricultural
production on their own fields (see also employment effects in Table 20). This reduces

Table 29-Percentage of households receiving income from off-farm activities,
by farm size and cooperative membership
Source of Off-Farm Income
Farm Size/ Agricultural Nonagricultural Nonagricultural Income,
Membership Day Labor Wages Merchant Remittances
(hectares) (percent of households in farm-size group)
Less than 0.25
Members 25.0 50.0 12.5 62.5
Nonmembers 53.2 48.9 10.6 55.3
Members 25.0 33.3 13.9 75.0
Nonmembers 40.6 48.4 17.2 57.8
Members 17.8 27.5 19.2 76.7
Nonmembers 13.2 34.2 28.9 57.9
1.00 or more
Members 7.5 28.3 11.3 75.5
Nonmembers 30.0 20.0 6.7 36.7
All sizes
Members 16.5 30.0 15.3 75.3
Nonmembers 36.3 40.8 16.2 53.6
Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,

18 Similarly, in labor-scarce, land-rich environments, such as parts of Africa, productivity of labor in food
production must increase to achieve this desired development effect.

their off-farm earnings. Numerous intervening variables determine the extent to which
this actually happens. The following model sheds some light on this.
It is hypothesized that household earnings are determined by available labor; demo-
graphic structure; the farm's resource base in relation to household labor force, which
determines the opportunity cost of off-farm work; and human capital, which may
impinge on the off-farm income-earning possibilities. Local-level labor market condi-
tions, including location of village, may further differentiate the effect of the various
factors. An off-farm income-earning function (r) may thus be specified for i households as

r, = ao + biXi, + bkXk + ui (8)
a = intercept,
bj = the parameters of Xil variables describing the
off-farm income-earning potentials,
bk = the parameters of Xik variables depicting the
on-farm income-earning potential, and
ui = error term.

The results of the model specified along the above-stated hypotheses underscore
that off-farm income-earning by farm households is reduced with an increased resource
base for agricultural income-earning on the own farm (RFMLAB) (Table 30). The oppor-
tunity to grow the new export vegetables with rising returns per unit of family labor
can be interpreted as an expansion of the resource base per unit of family labor. Returns
to family labor more than doubled those of traditional crop producers and export crop
producers (for instance, maize, beans, and traditional vegetables of traditional farmers
versus snow peas, broccoli, and cauliflower of export crop producers shown in Table
13). A doubling of the resource base (land per family labor, RFMLAB) would reduce
off-farm income-earning by 11 percent at sample means.

Table 30-Determinants of off-farm income: regression model
Mean of
Variable Parameter t-Value Variable

RFMLAB -362.947 -1.71 0.231
HHEDUC 184.600 5.68 3.003
RWOMLAB -689.430 -2.04 0.463
DCID5 411.807 2.00 0.092
DCID4 100.564 0.48 0.089
DCID3 -327.380 -2.04 0.186
DCID2 -480.957 -2.43 0.102
DCID1 -288.961 -1.44 0.097
(Constant) 683.016 3.58 ...
2 = 0.12, F = 6.50, degrees of freedom = 3.62.

Notes: Dependent variable: total nonfarm income per capital peryear (quetzals).
RFMLAB = farm size per person of working age available for
farm work (in hectares per person),
HHEDUC = household education (years of school),
RWOMLAB = share of female labor in total household labor, and
DCID ... 5 = village dummy variables.

The model only implicitly addresses the complex issue of the value of human time
and its effect on substitution between off-farm versus on-farm work. People may derive
utility from spending less time searching and traveling for off-farm work. Also, the
search cost for off-farm employment reduces the net income from such sources. An
indication for this is that nonmembers of the cooperative spend relatively and absolutely
more on transportation. One quetzal of gross income from off-farm work may therefore
be worth less to the household than one quetzal of discounted present value earned
on the own farm.
Most important and significant is the influence of education levels on off-farm
earnings (HHEDUC). Thirty percent of the explained variance is a result of this variable.
In the simple model specification, the parameter estimate suggests that one additional
year of schooling of the household head raises off-farm income, all else being equal,
by 25 percent. It should be recalled that higher levels of human capital were also found
to raise labor productivity in agriculture once the production system becomes more
complex with new technologies and the new cash crops (see Table 27). Investment
in human capital is thus shown here to shift both the agricultural and the nonagricultural
income-earning capacities.
Although more available labor per unit of land increases a household's per capital
off-farm earnings, an increased share of female labor (RWOMLAB) decreases it. Off-farm
income-earning opportunities are less favorable for women in the area, and women's
wages tend to be lower than men's in agricultural work by 20 to 30 percent.
The village dummy variables test for the difference with Santiago, which is the
largest community and provides the most opportunities. As expected, most of the
village dummy variables for the other communities are significantly negative.
The result of this analysis suggests that the net increase in farm income from the
new export crops is not identical with the net increase in total income. The increase
in total income is diminished by reduced off-farm income, since households withdraw
partly from off-farm income earning once they adopt the new export vegetables, for
which they allocate more of their time to on-farm work.



Surveys on income-especially direct approaches to income assessment rather than
indirect ones via disaggregated accounting of costs and returns, as in this study for
agricultural income-suffer from both inaccuracy and high intertemporal fluctuations
that do not represent the long-term standard of living of households. This is particularly
true in the Western Highlands, where high shares of off-farm income may have signif-
icant fluctuations over time. Expenditures on food and nonfood, including the value
of home-produced food, represent a more stable indicator of households' permanent
income standard.
The following analysis of expenditures has two main purposes: first, to evaluate
the effects of the new export crop production on levels of expenditures (using total
expenditures as an income proxy); and second, to assess the effects of changes in
income levels and the nature of the income stream on the composition of expenditures.
Of special interest are questions such as, What happens to the composition of the diet
once households earn more income from the export crop? or, Do poor households
increase their spending on "luxury items" when they earn more cash income from
cash crops than in-kind income from increased subsistence food production?
This analysis is based on the complete expenditure surveys on all food and nonfood
items for September 1983 and September 1985. Only the 1985 survey includes foods
consumed from own production and an annual expenditure survey on durables and
less-frequent expenditures, such as for housing, education, health, feasts, and clothes.
The following comparative evaluation between 1983 and 1985 is based on the strictly
comparable monthly cash expenditure surveys. Analysis based only on the 1985 survey
draws on the full expenditure survey, including own-produced food consumed in the
household and items from the annual expenditure survey. This approach was taken to
use a maximum of information from the longitudinal comparisons, while presenting
the complete picture from the more detailed 1985 survey.19

Income Effects in Relation to
Farm Size and Income Distribution
As shown in the table below, the 1985 cross-sectional comparison suggests that
export crop production increases relative income the most in the smallest farm-size
classes and thus contributes to a more equal income distribution among the poor. Farm
households with more than 1 hectare and who depend more on hired labor for additional
labor input actually capture comparatively less benefit from new export vegetable

t9 This explains the difference between the 1985 figures in the comparative tables and the 1983 data
below versus the 1985 figures in the other tables.

Difference in per Capita
Expenditure of Members
Farm Size Versus Nonmembers
Less than 0.25 + 59.8
0.25-0.50 + 33.1
0.50-1.00 + 20.2
1.00 or more +3.4
During the two-year period between the surveys, the distribution pattern of expen-
ditures changed only slightly. This does not mean, however, that the situation of
households in poverty in the area is a static one. To what extent did the same households
remain static or move upward or downward in terms of real per capital income and
what is the role of new export vegetables in this respect? The per capital expenditures
from 1983 are, for the purpose of this comparison, expressed in 1985 prices.20
Household transitions from one expenditure class to another inside and outside
the export crop scheme provide interesting results (Figure 6). For cooperative members
among the poorest tercile in terms of per capital expenditures, only 38.0 percent
remained in this position from 1983 to 1985, compared with 55.0 percent for nonmem-
bers. A much higher percentage of members moved upward in the expenditure classes
and a much lower percentage moved downward. This holds true for the middle and
high income terciles. For instance, among members, 30.4 percent dropped from the
middle tercile to the lower and 37.5 percent moved to the higher tercile; among the
nonmembers in the middle tercile in 1983, 36.7 percent dropped to the lower and
25.0 percent moved to the higher tercile. The whole spectrum of households moved
relatively more upward among members than among nonmembers.

Effects on Expenditure Patterns
The total expenditures of cooperative members are 20 percent higher than those
of nonmembers. The cash expenditures of members on both food and nonfood items
and the value of their own-produced food for home consumption are higher. Members'
nonfood expenditures are 32 percent higher and the imputed value of the own-produced
food for home consumption is 8 percent higher. Even after controlling for farm size,
food purchases of members are higher than those of nonmembers. For example, member
households with farms of 0.5-1.0 hectare spend 15 percent more per capital on purchased
food than nonmembers in the same farm-size group.
Although the absolute food expenditures of cooperative members are greater than
those of nonmembers, the share of the budget that members devote to food items is
lower. Members spend on average 64 percent of total expenditures on food compared
with 67 percent among nonmembers (Table 31).
A more detailed breakdown of household expenditure patterns reveals that relative
differences between export crop producers and other farm households are not substan-
tial (Tables 32 and 33). For food items other than meat, eggs, and fish, cooperative
members spend relatively less than nonmembers. This implies that income elasticities

20 The reported general inflation rate in Guatemala was 4 percent in 1984, 19 percent in 1985, and 23
percent in 1986. The inflation rate measured in the noncooperative households, which are the majority
of households at the location, was used to derive the location-specific inflation rate (33.6 percent over the
two-year period).

Figure 6-Transition of cooperative member and nonmember households
between expenditure terciles from 1983 to 1985



- Lowest --


S--Middle -
Lowest Highest
37% Highest Lowest 38%
25% 30%

d37% Highest
Highest 4 Highest --- Middle

19% Low-

Sources: Institute of Nutrition of Central America and Panama survey, 1983; and Institute of Nutrition of Central
America and Panama/International Food Policy Research Institute survey, 1985.
Note: Expenditures are in constant 1985 prices.

for meat, eggs, and fish are above unity and for other food items are below unity. For
some of the main staple foods-for example, maize and beans-members also spend
absolutely less. It should be noted that this may partly reflect price differences rather
than quantity differences. This issue is further addressed later in the food consumption
analysis. Also, in 1983, the simple comparison of expenditure patterns of the two
groups does not reveal striking differences (Table 34). The direction and magnitude of
the differences between item-specific budget shares of members and nonmembers are
as expected.

Table 31-Expenditures on foods (purchased and own-produced) and
nonfoods, by farm size and duration of cooperative membership,
Group Food, Purchased Own-Produced Nonfood Total Expenditures
(quetzals) (percent) (quetzals) (percent) (quetzals) (percent) (quetzals) (percent)
By farm size (hectares)
Less than 0.25 267.76a 55.5 36.30a 7.5 178.92a 37.0 482.97a 100.0
0.25-0.50 239.86 59.7 37.71 9.4 124.12 30.9 401.69 100.0
0.50-1.00 240.30 49.8 57.08 11.9 184.85 38.3 482.24 100.0
1.00 or more 221.36 48.1 53.07 11.5 185.84 40.4 460.27 100.0
Totalaverage 233.77 52.7 50.06 11.3 159.59 36.0 443.42 100.0
Less than 0.25 185.64 61.4 22.77 7.5 93.87 31.1 302.27 100.0
0.25-0.50 182.08 60.2 31.90 10.5 88.53 29.3 302.51 100.0
0.50-1.00 208.83 52.0 52.92 13.2 139.64 34.8 401.39 100.0
1.00ormore 212.89 47.8 55.05 12.3 177.92 39.9 445.87 100.0
Totalaverage 204.82 57.0 35.05 9.8 119.45 33.2 359.32 100.0
By years of membership
Less than 2 years 237.97 51.4 44.07 9.5 181.36 39.1 463.41 100.0
2-4years 222.17 53.4 54.30 13.0 140.02 33.6 416.49 100.0
5-6years 244.99 50.4 52.11 10.7 188.94 38.9 486.05 100.0
Totalaverage 233.77 52.7 50.06 11.3 159.56 36.0 443.42 100.0

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
Note: Parts may not add to totals because of rounding.
a There are only 6 observations in this group; in all other groups, at least 25 observations are the basis of the
mean values listed.

Between 1983 and 1985, total expenditures at 1985 constant prices for all purchased
items (excluding own-produced food) increased by nearly the same rate in member
and nonmember households (5.1 and 5.0 percent, respectively). (See Tables 35 and
36.) However, cooperative members spend substantially more on housing and land
purchases, which cannot be included in this comparison, as the 1983 baseline does
not exist. The annual recall for 1985 showed 84 percent higher spending for land
purchases by member households, which may be indicative of a higher savings rate in
those households. This expenditure-savings pattern may also be a reason for the higher
increase in expenditures among the recent export crop producers versus households
that have been in the scheme longer. The introduction of new export vegetables leads
to increased consumption of food and nonfood expenditures, especially in the first
years of membership. Total expenditures of new members who entered the scheme
between the two surveys increased by 33.1 percent and food expenditures went up
by 13.8 percent. For members in the scheme longer, consumption expenditures either
increased less substantially, or in the case of medium-term members (3-4 years), even
dropped in real terms. This pattern is a function of the one-time reallocation of resources
to export vegetables and higher returns to land and labor. Once this specialization
effect is achieved, further growth is constrained by resource endowments and lack of
new technology.
It is noteworthy that landless households' total expenditures dropped in real terms
by 1.3 percent (Table 36). Contraction in overall employment in Guatemala and reduced
real wage rates during the economic crisis in the mid-1980s greatly affected this group.
The favorable employment effects from export vegetables in the cooperative area have

Table 32-Food (including own-produced) and nonfood expenditures of
cooperative members, 1985

Value of Consumed
Value of Purchases Own Produce Total per Capita
Commodities, Other Items per Capita per Year per Capita per Year per Year
(quetzals) (percent) (quetzals) (percent) (quetzals) (percent)
Maize 15.59 4.0 26.93 53.8 42.52 9.6
Other cereals, bread 39.76 10.1 .. .. 39.76 9.0
Pulses 15.72 4.0 6.80 13.6 22.52 5.1
Sugar 14.67 3.7 .. ... 14.67 3.3
Roots, tubers, bananas 10.73 2.7 1.11 2.2 11.85 2.7
Vegetables, fruits 27.45 7.0 9.86 19.7 37.31 8.4
Milkproducts 9.01 2.3 2.33 4.7 11.33 2.6
Meat,eggs,fish 73.23 18.6 2.91 5.8 76.13 17.2
Fat, oil 6.26 1.6 0.12 0.2 6.38 1.4
Otherfoods 3.34 0.8 ... ... 3.34 0.8
Nonnutritious foods, beverages 18.01 4.6 ... 18.01 4.1
Totalfood 233.77 59.4 50.06 100.0 283.83 64.0
Fuel, energy 26.30 6.7 ... ... 26.30 5.9
Clothing 22.76 5.8 ... ... 22.76 5.1
Home articles 11.62 2.9 .. ... 11.62 2.6
Hygiene, cosmetics 24.18 6.2 .. .. 24.18 5.5
Education 0.55 0.1 ... ... 0.55 0.1
Health 13.19 3.4 ... ... 13.19 3.0
Transportation 20.27 5.2 ... ... 20.27 4.6
Entertainment 3.15 0.8 ... ... 3.15 0.7
Loans, transfers, donations 11.16 2.8 ... ... 11.16 2.5
Other services 26.42 6.7 ... .. 26.42 6.0
Total nonfood 159.59 40.6 .. 159.59 36.0
Total expenditures 393.36 100.0 50.06 100.0 443.42 100.0

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
Notes: Data are based on one-month recall, September 1985. Parts may not add to totals because of rounding.

apparently not counterbalanced these effects for the landless in the sample but certainly
reduced the adverse effects of the economic crisis.
A number of factors determine how scarce resources are allocated by poor house-
holds to food consumption versus other consumer goods. To test the extent to which
the source of income along with other factors impinges on the budget share allocated
to food, a model is specified for estimation of Engel curves that includes relevant sources
of income (their relative shares) as explanatory variables together with the level of
income. Also, household size is controlled for to account for potential scale effects.
Three sources of income are distinguished-income earned from the new export crops,
male income earned off-farm, and female income earned off-farm. The hypotheses to
be tested are that income earned under men's control (off-farm and from the new
export vegetables) is relatively less spent on food than farm income in general, and
female-controlled income earned off-farm is relatively more spent on food than general
household income. Total expenditure is used as a proxy for expected permanent income
in this analysis. It is noted that this is not entirely satisfactory because of the simplistic
assumptions regarding savings.
Three different models are specified to evaluate the hypotheses. The first model
includes members and nonmembers and tests whether the cooperative has an institu-
tional effect after controlling for the relative income-share effect from the new crops.
Institutional arrangements such as cash payment schemes, savings opportunities, and

Table 33-Food (including own-produced) and nonfood expenditures of
nonmembers of cooperative, 1985
Value of Consumed
Value of Purchases Own Produce Total per Capita
Commodities, Other Items per Capita per Year per Capita per Year perYear
(quetzals) (percent) (quetzals) (percent) (quetzals) (percent)
Maize 22.90 7.1 21.18 60.4 44.08 12.3
Other cereals, bread 31.63 9.7 0.01 0.0 31.65 8.8
Pulses 18.13 5.6 3.72 10.6 21.85 6.1
Sugar 12.16 3.7 ... ... 12.16 3.4
Roots, tubers, bananas 9.25 2.9 0.60 1.7 9.85 2.8
Vegetables, fruits 23.43 7.2 7.06 20.2 30.49 8.5
Milk products 8.00 2.5 0.48 1.4 8.48 2.4
Meat, eggs, fish 56.68 17.5 1.95 5.6 58.63 16.3
Fat, oil 5.25 1.6 0.05 0.1 5.30 1.5
Other foods 1.92 0.6 ... ... 1.92 0.5
Nonnutritious foods, beverages 15.47 4.8 .. 15.47 4.3
Total food 204.82 63.2 35.05 100.0 239.87 66.8
Fuel, energy 22.36 6.9 ... ... 22.36 6.2
Clothing 15.29 4.7 .. ... 15.29 4.3
Home articles 5.01 1.5 .. ... 5.01 1.4
Hygiene, cosmetics 22.76 7.0 .. .. 22.76 6.3
Education 0.56 0.2 ... 0.56 0.2
Health 10.45 3.2 .. .. 10.45 2.9
Transportation 22.76 7.0 .. .. 22.76 6.3
Entertainment 3.77 1.2 .. .. 3.77 1.0
Loans, transfers, donations 0.98 0.3 .. .. 0.98 0.3
Other services 15.52 4.8 .. .. 15.52 4.3
Total nonfood 119.45 36.8 .. ... 119.45 33.2
Total expenditures 324.27 100.0 35.05 100.0 359.32 100.0

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
Notes: Data are based on one-month recall, September 1985. Parts may not add to totals because of rounding.

household extension activities may have an effect on the budget share allocated to
food. The same model is then estimated separately for members and nonmembers to
test for additional differences in spending behavior between the two groups. The results
of this analysis are in Table 37.
Food expenditures as a proportion of total expenditures decrease significantly, but
not rapidly, with increased income. At total sample mean, a 10 percent increase in
total expenditure decreases the budget share to food by only 0.21 percent (computed
from Table 37). The dummy variable for separating the cooperative members (MIEM),
which is included in the model for the total sample, is not statistically significant. Thus,
once income levels and sources are controlled for, membership does not seem to have
a distinct effect on shifting the budget share for food. At the margin at higher income
levels, however, the budget share to food decreases more rapidly with rising income
in member households than in nonmember households (see LTEXPCSQ in the three
models, Table 37).
There are indications from anthropological research in the study area that male-
controlled income is spent more according to men's preferences than women's and
more food may not rank high among men (Nieves 1987, 32). The variables related to
income source indicate in this analysis that an increased share of income from new
export vegetables (RCASH) decreases the budget share to food beyond the total income
effect in cooperative member households. The effect is, however, not highly statistically

Table 34-Food (excluding own-produced) and nonfood expenditures of
cooperative members and nonmembers, 1983
Annual per Capita Value of Purchases
Item Members Nonmembers
(quetzals) (percent) (quetzals) (percent)
Maize 13.71 4.9 14.76 6.4
Other cereals, bread 40.68 14.5 38.32 16.6
Pulses 10.11 3.9 7.95 3.4
Sugar 12.61 4.5 11.19 4.8
Roots, tubers, bananas 8.36 3.0 7.16 3.1
Vegetables, fruits 14.56 5.2 10.92 4.7
Milk products 6.05 2.2 5.76 2.5
Meat, eggs, fish 43.55 15.5 37.85 16.4
Fat, oil 4.35 1.6 3.71 1.6
Other foods 3.15 1.1 2.90 1.3
Nonnutritious foods, beverages 14.33 5.1 11.31 4.9
Total food 171.46 61.2 151.85 65.7
Fuel, energy 15.32 5.5 12.65 5.5
Clothing 33.09 11.8 13.37 5.8
Home articles 6.74 2.4 3.94 1.7
Hygiene, cosmetics 12.69 4.5 11.76 5.1
Education 0.42 0.1 0.00 0.0
Health 7.44 2.7 6.91 3.0
Transportation 7.79 2.8 14.24 6.1
Entertainment 1.08 0.4 1.24 0.5
Loans, transfers, donations 4.23 1.5 0.00 0.0
Other services 19.81 7.1 15.13 6.5
Total nonfood 108.61 38.8 79.24 34.3
Total expenditures 280.07 100.0 231.09 100.0

Source: Institute of Nutrition of Central America and Panama survey, 1983.
Notes: Data are based on one-month recall, September 1983. Parts may not add to totals because of rounding.

significant. If, for instance, the income share from new cash crops increases from 0 to
50 percent, the food budget share is reduced by 1.2 percentage points, holding income
This analysis also shows that the net effect for the food budget share of an increased
income share of new export crops is very similar to the net effect of an increased share
of male nonagricultural income (see the parameters for RCASH in the cooperative
member model and for RMNAGINC in the nonmember model in Table 37). On the
other hand, women's share in total off-farm income (RFNAGINC) does not appear to
have an effect on the budget share to food beyond total income.
Of Q100 of incremental income, cooperative members in the lowest income quartile
spend 052.7 on food, but nonmembers spend 061.0 on food (Table 38). The estimates
of the marginal food expenditures within expenditure quartiles by members and non-
members show generally lower values for the members within the same expenditure
groups. These estimates also point to an interesting relationship between income (total
expenditure) and marginal food expenditures. In the poorest quartiles, both members
and nonmembers spend less of incremental income on food than the second quartile
(in the case of members, even less than the third quartile). Apparently, the poorest
households have a high propensity to spend on goods and services other than food at
the margin. This expenditure pattern may originate from fixed expenditure obligations
for nonfood necessities. As shown in Chapter 7, this expenditure behavior may still
be consistent with a high income elasticity of calorie consumption among the poor.

Table 35-Food and nonfood per capital expenditures of cooperative members
and nonmembers, 1983 and 1985

Expenditures per Capita
Group Food Nonfood Total
(quetzals) (percent) (quetzals) (percent) (quetzals) (percent)
Landless 257.30 54.8 212.00 45.2 469.30 100.0
Members by years of membershipa
2orless 209.87 66.3 106.84 33.7 316.71 100.0
3-4 225.08 60.7 145.94 39.3 371.02 100.0
5-6 248.16 58.7 174.33 41.3 422.49 100.0
Total average for members 229.07 61.2 145.10 38.8 374.17 100.0
Total average for nonmembers 202.87 65.7 105.86 34.3 308.73 100.0


Members bvvears of membershipa


270.83 58.5

or less 238.76 56.6
-4 222.17 66.1
-6 246.29 57.1
Total average for members 233.77 59.4
Total average for nonmembers 204.82 63.2

192.15 41.5 462.93 100.0

182.86 43.4 421.63 100.0
113.77 33.9 335.94 100.0
184.96 42.9 431.25 100.0
159.59 40.6 393.36 100.0
119.45 36.8 324.27 100.0

Sources: Institute of Nutrition of Central America and Panama survey, 1983; and Institute of Nutrition of Central
America and Panama/International Food Policy Research Institute survey, 1985.
Notes: Data exclude own-produced food consumed in the household, as the 1983 survey does not include
related information. All data are in 1985 prices. Parts may not add to totals because of rounding.
SYears of membership in the cooperative as of 1985.

Table 36-Change in per capital expenditures, by cooperative membership
and duration of membership, 1983-85

Cooperative Members Nonmembers
Change in Total Change in Food Change in Total Change in Food
Category Expenditures Expenditures Expenditures Expenditures

Landless ... ... -1.3 +5.3
Cooperative members by
years of membership
2 orless' +33.1 + 13.8 ..
3-4 -9.5 -1.3 ..
5-6 +2.1 -0.8
Total average +5.1 +2.1 +5.0 +1.0

Sources: Institute of Nutrition of Central America and Panama survey, 1983; and Institute of Nutrition of Central
America and Panama/International Food Policy Research Institute survey, 1985.
Notes: Value of own-produced food is not included here, as the 1983 survey did not include these items. In
1985 the value of own-produced food was 13 percent.of total household expenditures for cooperative
members and 11 percent for nonmembers.
a This group became members in the cooperative two years or less before 1985; thus they entered the cooperative
after the 1983 survey.

Table 37-Determinants of budget shares to food in cooperative member and
nonmember households, 1985: regression model
TotalSample Nonmembers Members
Variable Parameter t-Value Parameter t-Value Parameter t-Value

HHSZ 0.003765 1.424 0.005195 1.462 0.002795 0.704
RCASH -0.023010 -1.691 -0.018140 -1.047 -0.038070 -1.655
RFNAGINC 0.009191 0.261 0.018070 -0.411 -0.007464 -0.104
RMNAGINC -0.023100 -1.706 -0.033500 -2.263 0.020290 0.578
MIEM 0.010550 0.797
LTEXPC 0.279710 1.861 0.156420 0.913 0.579280 1.821
LTEXPCSQ -0.035270 -2.809 -0.024610 -1.694 -0.060220 -2.314
(Constant) 0.248630 0.557 0.596770 1.193 -0.630700 -0.650
R2 = 0.34 R2 = 0.37 R2 = 0.33
DF = 342 DF =178 DF = 158
F =25.6 F =17.7 F =12.8

Notes: Dependent variable: budget share to food.
HHSZ = household size (number of persons);
RCASH = ratio of income from new export vegetables over total
income (total expenditure is used as proxy for expected
total income);
RMNAGINC = ratio of female (male) nonagricultural off-farm income
over total income (total expenditure is used as proxy for
expected total income);
MIEM = membership in cooperative (1 = members, else = 0);
LTEXPC = log of per capital total expenditures serving as a proxy
for expected (permanent) income; and

Effects on Calorie Consumption
The problem of protein-energy deficiency of the rural poor in Guatemala is well
researched (see, for example, Balderston et al. 1981; Mata 1978). It is, therefore, not
the objective of this research to comprehensively evaluate the nature and prevalence
of food deficiencies and malnutrition but to assess the direction and magnitude of
changes in consumption and nutrition due to increased export crop production in
smallholder households.
Differences in food availability in the Western Highlands households are closely
related to income. This is to be expected at such low levels of income. If the sample
is grouped into four equal groups by total expenditure per capital (including the value
of home-produced food consumed), the lowest quartile had less than two-thirds of
calories per adult equivalent unit as the highest quartile (Table 39). Within the Western
Highlands, the degree of poverty as reflected in levels of food availability in households
indicates a considerable degree of inequality among the poor. It should be noted that
calorie availability for this assessment is based on monthly purchases of food and food
from own production used for home consumption. This rough approach to food consump-
tion is likely to result in higher calorie per capital figures than an accounting of actual
food intake, since losses in storage and processing and losses due to waste are not
included. Ideally, actual food intake of individual family members would be preferred
in view of findings from earlier research in Guatemala that suggest the income-food
intake relationship (calories) is more pronounced among children (preschoolers) than

Table 38-Incremental expenditure on food by cooperative member and
nonmember households, by expenditure quartile, 1985

Expenditure Share ofIncremental Expenditure on Food
Quartile Members Nonmembers
Lowest 52.7 61.0
Second 70.4 76.6
Third 58.1 57.0
Highest 31.9 44.5

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
Notes: The estimates of the presented marginal shares of food expenditures are based upon the following
regression model estimated separately for each of the groups and quartiles: food expenditure per
HHSZ = household size (number of persons);
LTEXPC = log of per capital total expenditures serving as a proxy
for expected (permanent) income;
RCASH = ratio of income from new export vegetables over total
income (total expenditure is used as proxy for expected
total income); and
RMNAGINC = ratio of female (male) nonagricultural off-farm income
over total income (total expenditure is used as proxy
for expected total income).

Table 39-Food availability and composition of food consumption by
expenditure quartiles (mean values) in the sample, 1985

Lowest Second Third Highest
Category Quartile Quartle Quartile Quartile
(per capital)
Average of 1985
expenditures (quetzals)a 186 283 410 771
Calorie availability per adult
equivalent per day
Cooperative members 2,214 2,563 3,088 3,446
Nonmembers 2,122 2,680 3,101 3,401
Total average 2,153 2,628 3,094 3,429
Percent of total calories
Maize 57.2 57.0 54.6 49.4
Other cereals 6.1 7.4 5.7 6.8
Pulses 9.0 8.3 8.2 7.3
Sugar 13.7 11.7 10.7 11.8
Meat, eggs, fish 4.8 5.6 6.5 7.4
All other foods and beverages 9.2 10.0 14.3 17.3
Total (percent) 100.0 100.0 100.0 100.0

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
a Includes the value of own-produced food consumed by the household.
b Average of total sample.

for the household as a whole (Flores 1975, 10). To the extent that Flores's finding
based on survey data from the 1960s is still valid, the household income-calorie con-
sumption relationship for preschoolers is assumed to be even higher than the total
household averages presented here.
More than half of the available calories in households are from maize, but this
share decreases with increasing income (Table 39). Also, the calorie share of pulses
(mainly beans) decreases, while the share of meat, eggs, fish, and other food calories
increases with higher income. Accordingly, the price per calorie increases with rising
income as the diet becomes more diversified. Cooperative members spend an average
Q0.265 per 1,000 calories, while nonmembers spend Q0.240 per 1,000 calories, or
10 percent less.
Comparison of food availability between export vegetable-producing households
(cooperative members) and other households shows that the latter acquire, on average,
about 7 percent fewer calories per capital. Members acquire a lower share of maize
calories, but the absolute amount of calories per capital from maize is still 4.4 percent
higher than in nonmember households (Table 40).
The diet composition of cooperative members and nonmembers is not significantly
different. Members have a slightly larger share of calories from sugar, starchy roots,
vegetables, meat products, fats, and other processed foods (Table 40). These differences
between averages of members' and nonmembers' consumption appear to be largely
determined by the differences in income levels and distribution. As shown in Table
39, per capital calorie consumption of members within the same expenditure quartile
as nonmembers is sometimes slightly higher (for example, in the lowest and highest
quartiles) and sometimes slightly lower (for example, in the two middle quartiles).
More refined approaches are used below to test for the significance of these differences.
The basis for the concept of this analysis of the effects of increased export crop
production on food consumption is that the principal relationships between change in
prices and levels of income and food consumption are well established. Since real
income increased in households that adopted new export crops, the hypothesis is that
food consumption levels increased, too. Less clear are hypotheses related to the effects

Table 40-Food availability and composition of food consumption in
cooperative member and nonmember households, 1985
Category Members Nonmembers

Calorie availability per adult
equivalent per day 2,931 2,733
Percentage of total calories
Maize 53.8 55.3
Other cereals 6.2 6.8
Pulses 8.1 8.3
Sugar 12.1 11.8
Starchy roots, bananas 2.7 2.5
Vegetables, fruits 5.6 5.4
Milk 0.5 0.4
Meat, eggs, fish 6.4 5.8
Fats and oils 1.3 1.0
Other foods and beverages,
meals outside home 3.3 2.7
Total (percent) 100.0 100.0

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,

of income-source changes, control over household income, and the form and frequency
of income. (For a review of evidence on this issue, see Braun and Kennedy 1986,
55-59.) Export vegetable production impinges on all of these jointly with its favorable
effect on the overall real income. The net effect of export vegetable production on
household food consumption may thus be smaller or larger than the "pure" income
effect suggests. These factors will be evaluated in the following model, which attempts
to explain aggregate household-level food availability in the form of calories (c,):

c w= f(l, Iq Si, Dn, Pmi, Mql), (9)

Ii = per capital income of household i (total expen-
diture is used as income proxy),
S, = a set of j variables describing sources of income
(from new cash crops, off-farm women's income),
Dn = a set of n variables describing household size
and composition,
Pm = a set of m variables depicting food prices that
respective households face, and
Mq = a set of q variables describing the membership
and its duration in the cooperative for export
vegetable production.

The model is estimated both for the total sample and separately for the lowest 50
percent of income groups among members and nonmembers. The actual specifications
of the model along the above-formulated hypothesis and the estimation results are
presented in Table 41.
The estimated response of calorie availability to changes in levels of income is
highly significant. Additional income increases calorie consumption (LTEXPC), but at
decreasing rates at the margin (LTEXPCSQ). The elasticity of calorie consumption with
respect to income is 0.306 at the total sample mean. Since the new export crops
increased household per capital income, a positive effect for calorie consumption in
cooperative member households is to be expected according to these parameter estimates.
Since the food expenditure analysis in the previous section suggested that export
crop income is spent less than other income for food at the margin, the extent to which
this translates into calorie consumption is tested. It is hypothesized that membership
in the cooperative reduced women's off-farm income and increased shares of cash
income from new crops, which are controlled by men (see, for example, Tinker 1979).
Most purchased food items in Guatemalan households are actually acquired by
women. Maize is the only food that is purchased in a significant amount by men (Table
42). In this environment, women's income levels may have a particularly positive effect
on levels of food acquisition over and above total income of the household. This
hypothesis, tested by the variable RFNAGINC-share of (off-farm) income earned by
women in total income-in Table 41, does not find statistical support. Income earned
by women off-farm does not significantly change calorie acquisition after controlling
for total income, although it was found earlier in the expenditure analysis that an
increased share of female-controlled off-farm income increased the budget share to
food beyond the income effect. The explanation for this difference may be that the

Table 41-Availability of calories in households and export vegetable
production: regression model

Lowest Two Quartlles
Total Sample Cooperative Members Nonmembers
Variable Parameter t-Value Parameter t-Value Parameter t-Value

LTEXPC 20,446.410 2.663 3,928.210 1.218 6,289.810 3.794
LTEXPCSQ -1,328.330 -2.072
RFNAGINC -1,685.120 -0.971 -1,096.170 -0.437 -1,675.740 -0.606
RCASH 57.254 0.082 553.030 0.438 173.124 0.194
HHSZ 1,747.343 13.021 1,244.150 5.075 1,510.410 6.629
RCHILD -6,627.550 -3.106 -4,957.520 -1.088 -4,923.010 -1.230
MPRICE -82,424.880 -5,774 -46,732.990 -1.821 -54,545.190 -1.648
BFPRICE 505.477 1.020 949.183 0.826 1,139.320 1.168
MIEM -829.710 -1.218
(Constant) -47,623.400 -2.060 -6,841.310 -0.394 -18,424.900 -1.417
R2 = 0.41 R2 = 0.33 R2 = 0.64
F =26.6 F =4.20 F =9.60
DF = 340 DF = 60 DF = 98

Notes: Dependent variable: calories available for consumption per day in the household (from purchases and
consumed from own production, 1985).
LTEXPC = log of total expenditures per capital per year in quetzals
(as a proxy for permanent income);
RFNAGINC = ratio of female off-farm income over total income (total
expenditure is used as proxy for permanent income
in the ratio);
RCASH = ratio of income from new cash crops over total income
(total expenditure is used as proxy for permanent in-
come in the ratio);
HHSZ = number of persons in the household;
RCHILD = ratio of number of children under 5 over number of
persons in the household;
MPRICE, BFPRICE = price of maize, beef; and
MIEM = membership in the cooperative (1, else = 0).

Table 42-Purchasers of food items in household transactions

Food Item Husband Wife Other Person
Milk 8 87 5
Eggs 1 92 7
Pork 2 95 3
Sausage 2 90 8
Maize 24 76
Beans 2 93 5

Source: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
Note: Data are based on one-month recall.

usual off-farm work in trading and services takes women away from home from morning
till sunset even if temporary migration is not involved, and that more expensive time-saving
foods may enter the budget of such households. Obviously, generalizations of the
relationships between women's income and food acquisition are risky if the interactions
with mode of income earning are not taken into account. The issue of the actual value
of human time discussed above and the possibly different utility derived by households
from on-farm versus off-farm work at equal returns per unit of time is also relevant here.
An increased share of income from new export crops (RCASH) does not have a
significant effect on calorie acquisition beyond the income-level effect. The respective
parameters of this variable are not statistically significant in any of the three models
(Table 41). That is, income from the new export vegetables translates into calorie
availability no differently than income in general.
The model for the total sample tests whether membership in the cooperative (MIEM)
and the share of income from export crops (RCASH) affect calorie acquisition beyond
the absolute income effect. The respective parameter estimate of cooperative member-
ship suggests a marginally significant negative effect on calorie availability (the parameter
of MIEM is not statistically significant; see column 1, Table 41). Although this appears
as the general picture, the situation seems different at low-income levels, as shown by
the separate estimates of the calorie consumption functions for members and nonmem-
bers in the lowest income half of the joint income distribution (Table 41). Nonmembers
show a significant positive response in calorie acquisition with rising income but
members do not. Calculated at the identical income level at the mean of the joint
sample-not at the differing means of the two separate samples, which would distort
the picture-cooperative members increase their calorie acquisition by 2.8 percent
with 10 percent more income, but nonmembers increase theirs by 4.4 percent. (This
income elasticity of calorie acquisition among members is based on a parameter estimate
that is statistically not significant-see Table 41.) The households in the area are clearly
price-responsive in their calorie acquisition. Understandably, the maize price (MPRICE)
is most prominent in this respect, as about 50 percent of calories come from maize.21
The estimated (maize) price elasticity of calorie consumption is high; -1.15 among
the lowest income half of nonmembers and 0.95 among the members in that income
group, which means that a 10 percent increase in the maize price reduces calorie
availability by 9.5 percent at the household level. If increased export vegetable produc-
tion were to shift farm households from net sellers or self-sufficiency to net purchasers,
or shift whole village communities in the Western Highlands to net importers, the
related price effect could have a significant effect on calorie consumption.
In the final assessment, the effects of increased export crop production on food
acquisition are on average positive in terms of calorie availability to the households,
supporting further the conclusion drawn from the agricultural production and income
assessments that household-level food security seems to have improved. Yet the change
in the source of income-earning reduces the positive gross-income effect for calorie
acquisition from an expected increase of 7.2 percent to an overall net effect of 1.9
percent in a typical farm household that joined the cooperative (based on model in
column 1, Table 41). The following section traces these effects to the nutritional status
of children.

21 Price variability in the cross-sectional sample results from local price differences and the fact that
households face in varying degrees a c.i.f. price if they are purchasing or an f.o.b. price if they are selling.
To households that are only consuming their own-produced maize, the local f.o.b. price was assigned to
represent the shadow price of maize consumption.

Effects on Nutrition
The nutrition problem in the Western Highlands is a syndrome that stems from
poverty. The health and sanitation environment along with the ability to acquire food-
be it from own production or market-and employment, especially of mothers, are
important interrelated factors that determine the nutritional performance of children
(Balderston et al. 1981). The new export vegetable production scheme directly or
indirectly impinges on all of these variables.

Patterns of Malnutrition in the Region and Sample Population
In a number of social indicators, cooperative member households appear to have
a better standard of living than nonmembers. Many of these indicators may be directly
or indirectly linked to increased income of members, but other indicators may reflect
their desire and ability to change their living standards as compared with others in the
communities. In general, members have higher education levels, better housing and
water supply conditions, and higher-quality health services (clinics). Basic health ser-
vices, such as vaccination, are used similarly by the two groups. Although they are
generally less poor, the percentage of members obtaining food aid tends to be higher
than among nonmembers (see indicators, Table 43).
As found in the above analyses, both real household income and food from own
production increased due to export vegetables. Women's on-farm employment in-
creased, leading to less off-farm work. Employment in the six communities also increased
due to export cropping; this should be beneficial to the local landless and smallest
farmers, who depend more on off-farm work. However, the country went through a
period of general economic decline in the mid-1980s that adversely affected economic
opportunities of the poor. Thus it is an open question whether the nutritional situation
in the six communities generally improved. This question will be evaluated using
nutritional status indicators of children-weight-for-age, height-for-age, and weight-for-

Table 43-Selected social indicators for cooperative members and
Indicator Members Nonmembers
Household size (persons) 6.7 6.4
Literate heads of household (percent) 61.7 55.4
Electricity in the house (percent) 60.3 47.7
Housing conditions
Houses with mud floor (percent) 41.7 56.5
Houses with corrugated iron (percent) 69.7 49.8
Own water tap or own well (percent) 79.6 61.9
Use of health services (percent)
At clinics 45.6 33.4
At pharmacy or other services 50.1 60.6
Vaccination of children under 5 years (percent)
Measles 68.6 65.1
BCG 70.8 67.1
DPT (3 or 4 doses) 50.0 46.6
Polio (3 or 4 doses) 48.8 45.3
Food aid received in
1983 (percent of households) 53.2 45.8
1985 (percent of households) 45.0 42.8

Source: Institute of Nutrition of Central America and Panama survey, 1983; and Institute of Nutrition of Central
America and Panama/International Food Policy Research Institute survey, 1985.

height. In this analysis, the respective indicators are normalized for age differences by
expressing them in terms of their deviation from the age-specific standards over the
standard deviation (Z-scores).22
The general nutritional situation in the study area, as represented by children in
households not participating in the cooperative, is not very different from other parts
of the highlands despite the accessibility of the survey villages to Guatemala City and
to infrastructure (Table 44). Also, prevalence rates of malnutrition in these communities
(especially height-for-age) are at similar levels to, or even higher than, the rates found
in more remote parts of the Western Highlands (Table 45).
Comparing the Guatemalan data with comparable data from Africa, significant
differences are found. For instance, average Z-scores for growth retardation of about
-1.4 were found in a comparable survey in The Gambia (von Braun, Puetz, and Webb
1989). However, a straight comparison of average Z-scores of anthropometric indicators
across populations may not be fully justified because of ethnic differences between
populations. Therefore, the focus is mainly on relative changes rather than absolute
levels of anthropometric status as a nutritional indicator in this analysis.
A comparison of the 1983 and 1985 prevalence rates does not indicate a general
improvement in nutritional status (Table 45). However, this tendency should not be
generalized to local developments. During these years, Guatemala was going through
a severe economic crisis, which may be the reason for this general pattern of develop-
ment. Desired information on change over time in anthropometric indicators from
other Guatemalan locations in the early 1980s is not available. Comparison of cooperative
members with nonmembers shows that children of members tend to be better off in terms
of weight-for-age and height-for-age and about the same in terms of weight-for-height.
Table 46 presents an analysis of the prevalence of wasting and stunting among the
children of families who are members versus nonmembers. Two cutoff points are used
for both the weight-for-height and height-for-age standards. The commonly used cutoff
point to classify wasting is children below 80 percent weight-for-height, and for stunting,
below 90 percent height-for-age standards. Only children 6-60 months of age are
included. By the above standards, 66.7 percent of children of members and 75.7

Table 44-Nutritional status of children under 60 months in the study area
and other locations in Guatemala
Weight- Height- Weight-
Area for-Age for-Age for-Height
(average Z-scores)
Study area, 1985" -1.89 -3.27 0.11
A study area in four villages in Patuldl area, 1984 -1.98 -3.26 0.00
A study area of coffee plantations, 1984 -1.65 -2.61 -0.05

Sources: Institute of Nutrition of Central America and Panama/International Food Policy Research Institute survey,
1985; and data from Victor Valverde, Hernin Delgado, Rafael Flores, and Ricardo Sibridn, "Minimum
Wage Law and Nutritional Status in Guatemala," Institute of Nutrition of Central America and Panama,
Guatemala City, 1985, (mimeographed).
a Children aged 6-60 months of the nonmembers of the cooperative.

22 The National Center for Health Statistics standards were used for Z- scores. Z-scores are standard deviation
scores. For any value X, the Z-score is (X X)/S, where X is the median and S is the standard deviation
of the reference population. A negative (positive) Z-score means the specific value X, is "Z" standard
deviations below (above) the median of the reference population.

Table 45-Prevalence of malnutrition in the Western Highlands of Guatemala
Children Below -2Z-Scores
Weight- Height- Weight-
Area for-Age for-Age for-Height
Study area, 1983' 43.2 82.1 1.7
Studyarea, 1985a 42.4 89.2 1.3
Western Highlands (north) 36.8 67.6 1.7
1983b 36.8 67.6 1.7
1987c 58.3 66.2 8.2
1987d 51.7 81.8 4.2

Sources: Based on data from USPADA/INCAP/UCPRODA, Resultados del Andlisis de las Encuestas de Base
Agroecondmica, Dieta y Estado de Nutrici6n Infanti Project MAGA-AID 520-T-034/0255, 1983
(Guatemala City: INCAP, 1986); Cooperaci6n Guatemalteca-Alemana Alimentos, Informe Fina4 Baseline
Survey, Andlisis del Grupo Meta (Poblacidn Rural de los Departamentos El Quiche-Sury Totonicapan),
vol. 2 (Guatemala City: COOGAT, 1987); and Institute of Nutrition of Central America and Panama,
Informe de los Resultados de las Encuestas de Consumo de Alimentos y Estado Nutricional Project
MAGA-AID 520-T-034/0255, 1987 (Guatemala City: INCAP, 1988).
a Children aged 6-60 months of the nonmembers of the cooperative.
b Six departments: Huehuetenango, Quetzaltenango, San Marcos, Totonicapin, El Quiche, and Solold; children
aged 0-60 monthss.
c Two departments: Totonicapan and El Quiche; children aged 0-71 monthss.
d Six departments as in note (b): children aged 12-60 months.

percent of children of nonmembers were stunted in 1985. This reflects an increase in
both groups, although somewhat higher in the nonmember group. Severe stunting
(below 80 percent) hardly prevails among children of members (0.6 percent) but affects
children of nonmembers (5.8 percent). Severe wasting, which represents an indicator
of short-term nutrition problems, is practically nonexistent in both groups. In 1985,
0.6 percent of children of members and 1.0 percent of children of nonmembers were

Table 46-Prevalence of malnutrition among children of cooperative
members and nonmembers, aged 6-60 months, 1983 and 1985

Members' Nonmembers'
Weight- Height- Weight- Height-
Year for-Height for-Age for-Height for-Age
(percent of children below 90 percent of reference standard)b
(stunted) (stunted)
1983 15.1 59.3 10.2 65.1
1985 6.8 66.7 7.8 75.7

(percent of children below 80 percent of reference standard)b
(wasted) (wasted)
1983 2.3 0.6 0.9 4.2
1985 0.6 0.6 1.0 5.8

Source: Institute of Nutrition of Central America and Panama survey, 1983; and Institute of Nutrition of Central
America and Panama/International Food Policy Research Institute survey, 1985.
'Number of children: 1983 = 172 members, 215 nonmembers; 1985 = 177 members, 206 nonmembers.
b The standards used are the National Center for Health Services standards.

In both groups, children who have been moderately underweight substantially
improved, relatively more among cooperative members. Between 1983 and 1985, the
percentage of children below 90 percent of the weight-for-height standard decreased
from 15.1 to 6.8 percent among children of members, and from 10.2 to 7.8 percent
among children of nonmembers.

Income and Nutritional Improvement
The straightforward comparisons of mean values and prevalence rates of malnutri-
tion provide limited insights, since the earlier analysis showed that members of the
cooperative have higher incomes than nonmembers. The sample is therefore broken
into three income classes, using expenditure per capital as an income proxy. For children
6-120 months of age, there is a generally positive but weak relationship between
income and nutritional status (Table 47). While children in the middle and highest
terciles showed a slight improvement in their weight-for-age Z-scores, children from
households in the lowest group appear to have worsened between the two rounds.
The prevalence of stunting (height-for-age) increased among children from households
in the bottom and middle terciles, while it decreased among the highest income group.
The higher prevalence of stunting may be related to the worsening of the general
socioeconomic conditions during the first half of the 1980s, when real per capital GDP
decreased by 20.5 percent (1981-85) in Guatemala.
Because of increases in real income, available food from own production, and
women's on-farm employment, as well as overall employment in the six communities,
which is beneficial to the landless and the smallest farmers, it is hypothesized that the
nutritional situation improved for both members and nonmembers of the cooperative.
The following model is a reduced form of income-nutrition relationships. At higher

Table 47-Income levels and prevalence of malnutrition among children of
cooperative members and nonmembers, 1983 and 1985
Children Below -2 Z-Scores
Lowest Middle Highest
Number Income Income Income
Measure Year inSample Tercile Tercile Tercile
(percent of children 6-120 months)
Weight-for-age 1983 755 41.6 38.9 36.8
1985 824 43.0 36.5 32.2
Height-for-age 1983 755 77.4 75.0 77.7
1985 824 83.4 87.4 74.4
Weight-for-height 1983 755 1.9 0.8 2.1
1985 824 1.9 0.7 0.8

(percent of children 6-60 months)
Weight-for-age 1983 406 46.2 38.0 39.7
1985 394 48.3 38.2 34.1
Height-for-age 1983 406 78.7 78.5 83.6
1985 394 84.8 95.8 81.1
Weight-for-height 1983 406 2.4 1.7 0.9
1985 394 1.7 1.4 0.8

Source: Institute of Nutrition of Central America and Panama survey, 1983; and Institute of Nutrition of Central
America and Panama/International Food Policy Research Institute survey, 1985.
Note: Income levels refer to expenditures of respective year in per capital terms as income proxy (excluding
value of own-produced food consumed, which was not collected in 1983 survey).

income levels, reduced marginal effects of increased income for nutritional improvement
are expected. It is further hypothesized that an increased share of male nonagricultural
income or export crops has a negative effect on child welfare, holding household income
constant. If a disproportional share of income is spent on luxuries, children's nutritional
status would deteriorate at a given income level. On the other hand, it is hypothesized
that an increased share of female-controlled income leads to increased child welfare-
related spending and nutritional improvement. Subsistence food income is included in
the total household income variable in this reduced-form model, which has the following

where = f(DEM,,, INCOME,, INCOMP,), (10)
Sil = nutritional status of child (i) in household
(j) in 1985;
DEMiJ = demographic variables of child (sex, age in
months-level and squared-birth order);
INCOME1 = household (j) income per capital per year
(and the respective squared term); and
INCOMP- = composition and sources of income (shares
from new export crops, male- or female-
earned nonagricultural income).

The results indicate that the level of income is highly significant for the weight-for-
age, height-for-age, and weight-for-height indicators (Table 48). At higher levels of

Table 48-Effects of income and income source and composition on nutritional
status: multivariate analysis for children aged 6-120 months
Weght-for-Age Height-for-Age Weight-for-Height
Z-Scores Z-Scores Z-Scores
Estimated Estimated Estimated
ExplanatoryVarlable Parameter t-Value Parameter t-Value Parameter t-Value

Age in months -3.489E-03 -0.85 -0.0156 -3.03 -9.485E-03 -2.28
Age squared 3.497E-05 1.14 1.397E-04 3.64 1.053E-04 3.39
Birth ordera 1.706E-04 0.01 -0.0240 -1.37 0.0220 1.55
Sex (male = 1, female = 2) 7.083E-03 0.12 0.0379 0.52 -0.0562 -0.96
Duration of breastfeedingb 9.663E-05 2.03 1.894E-04 3.17 -3.063E-05 -0.63
Income per capital 8.231E-04 3.20 7.807E-04 2.41 5.162E-04 1.98
Income squared -3.930E-07 -2.74 -3.489E-07 -1.93 -2.625E-07 -1.80
Share of male nonagricul-
tural income 0.1613 2.00 0.3291 3.24 -0.0531 -0.67
Share of female nonagricul-
tural income 0.4953 2.20 0.4895 1.73 0.3140 1.37
Share of income from
exportcrops 0.1569 1.88 0.1958 1.81 0.0640 0.73
Constant -2.1165 -12.89 -3.110 -15.08 0.0549 0.33
R2 0.032 ... 0.073 ... 0.028
F-value 3.590 ... 7.280 ... 3.290
Degrees of freedom 785 ... 785 ... 785

a First-born child = 1, second = 2, and so forth.
b Variable only for children above 24 months of age (else = 0).
c Expenditure per capital per year is used as a proxy for income.

income, the marginal effect is reduced as hypothesized, indicated by the negative sign
for the squared income term. Thus the effect of marginal income on nutrition is greater
in poor households than the sample means indicate. At sample mean, a 10 percent
increase in income increases the weight-for-age Z-score by 1.5 percent, the height-for-
age Z-score by 0.9 percent, and the weight-for-height Z-score by 9.7 percent. The high
income elasticity of short-term nutritional improvement (weight-for-height) suggests
that even marginal income growth among the poor leads to significant short-term
weight gains of children. It thus can be inferred that increased real income due to the
export crops has a particularly significant effect in this respect. To reduce stunting
substantially, however, would require a major increase in income.
Higher shares of either male or female off-farm nonagricultural income improve
the nutritional status of children. Although this is contrary to the study hypothesis
concerning male-controlled income, the respective parameter values indicate different
levels of impact. In the weight-for-age model, women's income always had a greater
impact on nutritional status than men's income. In the height-for-age model, which
depicts long-term effects, the differential effect between male- and female-controlled
income is less pronounced; for short-term nutritional status (weight-for-height), income
control within the household does not appear to be an issue (the parameters are not
statistically significant).
A higher share of income from the new export crops has a low positive effect on
nutrition after controlling for income in the weight-for-age and height-for-age models
but is not significant in the weight-for-height model. The hypothesis that income from
new cash crops, which is largely male-controlled, would be disproportionately used for
nonfood and luxury items that would adversely affect nutrition of children in the
household does not find support in this analysis.
Social Programs
The commercialization process studied in this case is inseparable from the Cuatro
Pinos cooperative scheme. The cooperative has developed and implemented three types
of social programs: productive, educational, and medical. These programs may improve
the health status of children and have a long-term effect on nutritional improvement
beyond the income-consumption effect of the new export crops.
Productive programs include a rabbit project that was started in March 1986 for
women. This project consists of providing credit for acquisition of a rabbit pen and
three rabbits-credit that must be repaid in one year. Furthermore, participants are
trained in rabbit growing, maintenance, and slaughtering techniques. As of April 1987,
105 women had participated in the project. It is estimated that 50 percent of the rabbit
meat production is for own consumption, and the remainder is sold to supermarkets
in Guatemala City.
By statute, 10 percent of the cooperative's profits are earmarked for its educational
fund. The first program (initiated in Santiago in 1978) was an adult education program
for members and nonmembers, with primary education and literacy classes. In 1983
the program was expanded to three communities and was taught by three teachers
directly employed by the cooperative. In 1986, 132 adults (36 nonmembers) finished
the primary education subprogram and 66 (12 nonmembers) finished the literacy
In 1980, with funds from the Swiss Group, a nongovernmental development orga-
nization, several children began to receive study scholarships. The scholarship program
was formally organized in 1985, and scholarships are provided for secondary education
and vocational training and normally cover tuition and books. The education committee

of the cooperative reviews and approves scholarship applications. In 1987,47 scholarship
applications were approved.
An institution providing secondary education has been established in Santiago and
receives financial assistance from the cooperative, thus benefiting some members indi-
rectly. Additional educational programs for schoolchildren were started in 1985 in
production techniques related to vegetables and aspects of cooperativism, and in 1986
cooperative education courses were organized for members, their spouses, schoolchildren,
and cooperative officials. Technical training in such fields as administration and account-
ing was initiated in 1987 for personnel of the cooperative.
In 1984 the cooperative organized a food and nutrition program for spouses of
members. As of mid-1987, 225 women have participated in this program, whose
contents center on different ways of preparing vegetables (particularly broccoli, snow
peas, and cauliflower) and their nutritive values, in order to stimulate more own
consumption of these foods. The program is conducted by two home extension workers
who are employees of the cooperative and were partially trained by INCAP.
The medical services program consists of several subprograms: maternal-infant, pre-
and post-natal care, outpatient consultations, and deworming. The program is currently
carried out in all communities from which the cooperative draws members. The staff
consists of a full-time doctor (as of August 1986) who is an employee of the cooperative.
The doctor spends four afternoons a week in the health clinic in Santiago and divides
the remainder of the time among the other communities. This is in addition to a
full-time health promoter who, among other things, prescribes medicines. From 1982
to August 1986, a medical doctor provided services two mornings a week in Santiago
and Pacul. In January 1987 the cooperative established a pharmacy in Santiago that
also supplies medicines to the other communities.

Food Consumption and Health-Based Model
of Nutritional Improvement
To assess the effects of increased commercialization on the nutritional status of
children, it is hypothesized that the related income effects-identified in the reduced-
form model above-can be traced to nutrition through increased food consumption
and improved health and sanitary conditions. Such further separation of the elements
of the growth and development process traced to nutritional effects is desirable for
policy and program design.
The model, unlike the reduced-form, income-based model in the previous section,
is a cohort-specific analysis of determinants of change in nutritional status. The model
for the identical children aged 6-60 months in 1983 and 30-84 months in 1985 has
the following form:

dS1983 1985) = f(DEMii, CAL,

BRE i, SANp, EDUI, PERI, S 1983)), (11)
dC = 5(1985) (1983).
dSi = Si Oss- i
DEMij = demographic variables of child (sex, age in
months-level and squared-birth order);

CALJ = household-level calorie consumption per
adult equivalent (level and squared);
BREJ = breastfeeding duration (children over 24
SANJ = sanitary environment (latrine);
EDUI = education of head of household (years of
PERj = years of cooperative membership; and
Sj = nutritional status of child(i) in household1) in
1985 (weight- or height-for-age, or weight-
for-height Z-scores).

In this model of the determinants of change in nutritional status, household calorie
availability is included as a proxy variable for household food consumption. Household
food availability may not be a satisfactory indicator of child food consumption. The
hypothesis is that children capture a share of incremental household calories. Additional
indicators related specifically to breastfeeding duration are also introduced.
Poor latrine facility is used as a proxy for sanitation environment. It is further
hypothesized that households with better education have the ability to make better
use of available resources to improve the health and nutrition of their children. Finally,
the duration of membership in the cooperative is evaluated for its effect, beyond the
income-consumption effect, on children's health and nutritional status. Beneficial effects
from cooperative membership may come from participation in the social programs,
such as literacy classes, food and nutrition education of women, and improved informa-
tion exchange among communities. Adverse effects might result from changes in income
control not captured fully by the food consumption variables and women's time con-
straints for child-nurturing activities.
Inclusions of an individual child's nutritional status indicator (1983) before the
period during which change is measured (1983-85) take account of individual charac-
teristics. This increases the overall explanatory power of the models as compared with
the purely cross-sectional, income-based models. The lower the Z-score at the outset
(1983), the greater the reduction in weight deficiencies during the two years of observation.
For instance, children who were underweight at -2 Z-scores in 1983 tended to
catch up by one Z-score over the period (-0.5004 x -2, see Table 49). This points
out that a high proportion of malnutrition-reflected in weight deficiency-is of an
episodic nature. These serial episodes of weight loss then create the long-term nutritional
problem reflected in growth deficiency (see, for example, Balderston et al. 1981).
Although significantly increasing, too, catch-up growth from a stunted position at the
outset occurs much less often than catching up on weight. It should be noted that age
of the child is controlled for in this analysis and seasonality is eliminated, as the sample
surveys were done at the same time of the two years.
Other results of the regression models presented in Table 49 relate to the effects
of food consumption: household-level calorie availability does have a strong positive
effect-though decreasing at the margin--on the more short-term indicator of nutri-
tional status (weight-for-height). Current calorie consumption would be an unsatisfac-
tory indicator for the food availability history to which the children were exposed. For
this reason, in the long-term model of nutritional status (height-for-age), current calorie

Table 49-Determinants of change in nutritional status and the role of export
crop production: multivariate analyses for cohort of children

Change in Weight- Change in Height- Change in Weight-
for-Age Z-Scores for-Age Z-Scores for-Height Z-Scores
Estimated Estimated Estimated
ExplanatoryVariable Parameter t-Value Parameter t-Value Parameter t-Value

Age in months 0.0296 1.60 0.0140 0.74 0.0366 1.79
Age in months squared -2.548E-04 -1.62 -4.248E-05 -0.27 -3.132E-04 -1.81
Birthordera 0.0482 2.72 0.0144 0.82 0.0689 3.54
Sex(male= 1, female =2) -0.0226 -0.32 -0.1009 -1.39 0.04133 0.52
Calories per day per adult
equivalent, 1985 5.249E-05 0.73 ...b ... 2.2029E-04 2.78
Calories squared -5.586E-09 -0.69 ... ... -2.491E-08 -2.76
Breastfeedinge 0.2662 1.64 0.1351 0.82 0.3169 1.77
Unsuitable latrine (= 1,
else = 0) -1.212 -0.68 -0.3459 -1.91 0.0556 0.28
Education of household
head (years in school) 0.0261 1.28 0.0188 0.92 0.0217 0.97
Z-score of weight-for-age,
1983 -0.5004 -13.48 ...
Z-score of height-for-age,
1983 ... ... -0.2672 -7.90
Z-score ofweight-for-height,
1983 ... ... ... ... -0.6984 -17.34
Duration of membership in
cooperative (years) 7.694E-03 3.37 0.01237 5.36 1.774E-03 0.70
Constant -2.278 -3.88 -1.784 -3.10 -1.914 -2.95
R2 0.360 ... 0.229 ... 0.469
F-value 20.400 ... 13.500 ... 31.500
Degrees of freedom 369 ... 371 ... 369

Note: These analyses are based on a cohort of children who were aged 6-60 months in 1983 and 30-84 months
in 1985.
a First-born child = 1, second = 2, and so forth.
b The variable is not included in this model because it is not assumed to have an effect on the long-term measure
of nutritional status.
c If child was breastfed = 1 (else = 0).

availability was not included as a variable. To the extent that the new export vegetables
increased income, and thus increased household food availability, these results show
that the nutritional status of children is likely to be improved, at least in the short run.



This study of export crop production in smallholder agriculture is based on experi-
ence with a scheme that relies for success on particular conditions described earlier
in the report. Clearly the Cuatro Pinos cooperative is an exceptional case of agricultural
and rural development and is not typical in Guatemala. However, it is precisely because
the cooperative stands out favorably in an environment of numerous failures of agricul-
tural modernization with farmers' participation in Central America that it is possible
to arrive at important policy conclusions.
Mellor and Desai (1985, 209) stress that disparities in the distribution of assets
and power, which are often based on the social as well as the economic structure,
must be recognized. "The need for radical institutional changes may have been over-
stated in recent years vis-a-vis technological change in agriculture but the necessity for
such change must always be examined." Also, their emphasis that "state-sponsored
dualism must be guarded against" and that "a full attack must be made on all discrimina-
tory practices that restrain the poor" is of great relevance for this case study.
In studying the effects of increased commercialization of traditional smallholder
agriculture in Guatemala, the broader context of the "agrarian crisis" in Latin America,
which provides the political and economic environment of this study, should be kept
in mind. As de Janvry (1981, 3) puts it, the agrarian crisis in Latin America is charac-
terized by sharply uneven development among farms, crops, and regions, and by massive
rural poverty and political tensions. In contrast to the poverty issue in much of Africa,
poverty is not a separate phenomenon but is to be seen in terms of its functionality
(de Janvry 1981, 149). Low productivity in the traditional sector, unemployment, and
regressive income distribution patterns may be identified as direct causes of poverty
but are, at the same time, a function of the political-economic systems. As a consequence,
de Janvry (1981, 150) points out, policy recommendations regarding poverty run the
risk of assuming a reality separate from the functioning of the economic system when
they are only directed by idealistic and humanitarian concerns.
Clearly, political and economic structures should be kept in focus when policy
conclusions are derived from the case studied here. When the implications of the new
export crop production are evaluated here in the context of the existing political-economic
system, this is not intended to imply that the effects of this type of export crop scheme
are independent of the political system. In a drastic way, this was made clear by the
violent repressions that peasant organizations, such as cooperatives, suffered in some
parts of Central America in the early 1980s (Williams 1986).
Using Adelman's (1975) term, Guatemala may be a case for "redistribution before
growth." Taking a pragmatic evolutionary approach to the problem leads to the deriva-
tion of criteria for rural change that work in a desirable direction. Two issues are
essential in this respect. The first is the identification of policies that make use of the
opportunities for agricultural trade to sustain, not oppose, the relation between growth
and distribution. The second is the question classified by de Janvry (1981, 265) as
probably the most important one in this context, "whether growth itself is articulating."
Does growth through the creation of employment, and hence domestic demand for

wage goods, lead to gradual changes in the production structure that result in "social
articulation" of the poor, that is, expressed demand for services, infrastructure, educa-
tion, and participation in decisionmaking and priority-setting in the development process?
Concerning the first issue-trade opportunities and distribution-the production
of export vegetables has worked in the right direction in this study. Some peculiarities
of the new crops and the conditions at the location have produced this outcome.
Because of their diseconomies of scale in production, nontraditional crops ended up
on the smallest farms in the poorest area of the country, creating employment for the
small farmers and local landless, substantially increasing real income, and favorably
affecting food security and consumption. The favorable effect of the nontraditional
crops for small farmers largely depends upon the crops' characteristics, which are very
different from those of such traditional export products as cotton, coffee, and beef.
These products have apparently positive returns to scale in production and are produced
more efficiently on the other end of the dual spectrum of Guatemala's agriculture-the
large-scale farm enterprises.
As for the second issue-social articulation-the study finds that institutional
changes combined with the expansion of export crop production in a cooperative
scheme are forces leading toward social articulation. Noteworthy are the strengthening
of cooperation among farmers, increased interaction between village communities,
development of local trading and entrepreneurship due to the new crops, and related
buildup of economic power in the rural areas by the small-farmer-based economic
growth. An earlier discussion (Chapter 4) showed that development assistance can and
actually has played a catalytic role in this process. The economic costs of terminating
this process are now higher, especially in light of the country's severe foreign exchange
problem, which nontraditional export vegetable production plays an important role in
No general automation between growth and social articulation of the poor that
could lead to development can be postulated based on this study. The study demonstrates
the existence of niches in the system that provide this potential and also highlights
the specific conditions under which it may work. Central to these conditions are the
diseconomies to scale in producing the export vegetables and the ecological conditions
in the Western Highlands along with the labor market situation.
The sustainability and expansion potentials of the program depend on the function-
ing of the marketing channels, domestically and internationally, for both inputs and
outputs. The implicit taxation of small farmers through overvalued exchange rates for
outputs is a matter of concern. The riskiness of the new crops due to potential distur-
bances in the marketing chain needs to be a matter of constant attention.
For maximum gains from specialization, policies that ensure efficiently functioning
food, labor, and financial markets are the first-best solution. Market imperfections are
the worst enemies of sustainable market integration of the subsistence farm sector. As
long as market failures cannot be excluded and small farmers' perception of their
potential occurrence remains due to past experience (and this may change only slowly),
second-best options for policy must be considered. Therefore, the deep-rooted desire
for food security achieved by high levels of self-sufficiency at the household level in
the Western Highlands can best be accommodated by rapid technological improvements
in the traditional subsistence crops-maize and beans-along with expansion of the
new export vegetables. This is also a condition for adoption of the new crops and, as
observed in this study, small farmers manage to achieve complementarity between
growth in the subsistence crops and the new crops.

Accelerated growth in food production alone would have little effect on the general
poverty situation in the Western Highlands. Single-minded focus on nontraditional
export crops would be risky for small farmers' food security and would be constrained
by the adoption problem if food crops did not move jointly.
To cope with production risk and to finance the adoption of the input-intensive
new crops, a functioning rural capital market is essential. Rural credit and banking
schemes that open up outlets for rural savings are essential for long-term growth.
Otherwise, savings find their way into the form of assets-that is, land-with obvious
efficiency losses to the initiated development and potential adverse distributional effects
at the micro level.
Modest, though statistically highly significant, improvements in nutrition via the
favorable income and consumption effects of the program may be expected, as shown
by the analysis. This suggests that rapid employment and income growth will make a
difference that can be translated into nutritional improvement at the low levels of
poverty. The research further suggests that the income-growth effect needs to be
supported by appropriate health- and nutrition-oriented social infrastructure. This re-
quires sustained government commitment and community-based actions rather than
short-term charity. Development assistance can play an important role if the objective
is seen as building up the human capital of the poor.
Given the important role of nonagricultural rural employment in the Western
Highlands, the productivity of the growing landless population group depends upon
improved human capital, with education and training playing crucial roles. Increasing
the human capital stock is also a prerequisite for agricultural productivity to grow in
a sustainable way. It is hardly by chance that the early leadership of the export crop
cooperative-which the study mainly found to be a success story in the difficult political
and economic environment of Guatemala-emerged from intensive primary school
courses provided by a local project.

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World Bank. 1978. Guatemala: Economic and social position and prospects. World
Bank Country Study. Washington, D.C.: World Bank.


AFRICAN COUNTRIES, July 1986, by Ulrich Koester
Leonardo A. Paulino
COMMUNITY, November 1985, by Michel Petit
AMERICA, October 1985, by Victor J. Elias
AND 2000, April 1985, by J. S. Sarma and Patrick Yeung
1985, by Sudhir Wanmali
IMPLICATIONS, December 1984, by Nabil Khaldi
POLICIES IN THAILAND, November 1984, by Prasarn Trairatvorakul
BUTION AND CONSUMPTION, July 1984, by Harold Alderman and Joachim von Braun
43 CLOSING THE CEREALS GAP WITH TRADE AND FOOD AID, January 1984, by Barbara Huddleston
November 1983, by Joachim von Braun and Hartwig de Haen
NIGERIA, September 1983, by Peter B. R. Hazell and Ailsa Roell
1983, by Grant M. Scobie
Ammar Siamwalla and Stephen Haykin
1983, by Raj Krishna and Ajay Chhibber
TALUKA, February 1983, by Sudhir Wanmali
TINA, December 1982, by Domingo Cavallo and Yair Mundlak
TIONS FOR DEVELOPING COUNTRIES, November 1982, by Ulrich Koester
Harold Alderman, Joachim von Braun, and Sakr Ahmed Sakr

Joachim von Braun has been a research fellow at IFPRI since 1982.
David Hotchkiss is a research analyst at IFPRI. Maarten Immink,
formerly chief of the Division of Food Planning and Nutrition at
INCAP, is now a research fellow at IFPRI.


February 1989, by Raisuddin Ahmed and Andrew Bernard
KENYA, December 1988, by Thomas C. Pinckney
November 1988, by Joachim Zietz and Alberto Valdes
Kumar and David Hotchkiss
BIAN EXPERIENCE, August 1988, by Jorge Garcia Garcia and Gabriel Montes Llamas
TION, May 1988, by Geraldo M. Calegar and G. Edward Schuh
February 1988, by Mahabub Hossain
1987, by Harold Alderman
IN SOUTHWESTERN KENYA, November 1987, by Eileen T. Kennedy and Bruce Cogill
TIVES, September 1987, by Ram P. Yadav
FOOD CONSUMPTION, AND NUTRITIONAL STATUS, August 1987, by Marito Garcia and Per
1987, by Marc Nerlove, Assaf Razin, and Efraim Sadka
CHANGE RATE POLICIES, May 1987, by Romeo M. Bautista
CATION, March 1987, by Neville Edirisinghe
December 1986, by J. S. Sarma
November 1986, by Tshikala B. Tshibaka
October 1986, by T. Ademola Oyejide
(continued on inside back cover)

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