1
PROGRESA Caribe 
Mid-Term Evaluation Report 
Report prepared by the Nicaraguan Foundation for Economic and Social Development 
(FUNIDES)1 at the request of Catholic Relief Services (CRS) 
1 This document has been prepared by the Services Unit of FUNIDES (hereinafter evaluation team). The work team has been 
led by Camilo Pacheco, under the supervision of Juan Sebastián Chamorro. The research team is completed by Magaly 
Sáenz, Beverly Ruiz and Desireé Ferrey. Álvaro López and Lylliam Huelva, both Funides' economists, provided helpful 
comments for modeling of the impact and management of the database. Stephanie Huete provided assistance in the 
research. The preparation of the report has the support of CRS´s MEAL team and the Knowledge Management Division. 
Project Title: PROGRESA Caribbean
Donor UNITED STATES DEPARTMENT OF AGRICULTURE
Implementing Organization: CATHOLIC RELIEF SERVICES
Agreement Number: FCC-524-2014-056-00
Start Date: October 2014
End Date: September 2019
Reporting Period: 2016 - 2017
Contact: Jorge Brenes, Chief of Party 
Tel: (505)2278 3808 
E-mail: Jorge.brenes@crs.org
&zϮϬϭϰ&ŽŽĚĨŽƌWƌŽŐƌĞƐƐWZK'Z^ĂƌŝďĞ
DŝĚͲdĞƌŵǀĂůƵĂƚŝŽŶZĞƉŽƌƚ : Nicaragua
Program: &ŽŽĚĨŽƌWƌŽŐƌĞƐƐ
Agreement Number:&ͲϱϮϰͲϮϬϭϰͬϬϱϲͲϬϬ
Funding Year: Fiscal Year 201
Project Duration: 201ϰͲϮϬϮϮ
Implemented by: CRS 
DISCLAIMER: This publication was produced at the request of the United States Department of 
Agriculture. It was prepared by an independent third-party evaluation firm. The author’s views 
expressed in this publication do not necessarily reflect the views of the United States Department of 
Agriculture or the United States Government. 
Accessibility Note: An accessible version of this document can be made available by contacting 
fas.monitoring.evaluation@usda.gov
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Managua, November 2017
Acronyms and Abbreviations
ADDAC Asociación para la Diversificación y el Desarrollo Agrícola Comunal
ASIHERCA Asociación de Iniciativas de Hermanamiento de El Castillo
ATET Average Treatment Effect on the Treated 
BCIE Banco centroamericano de Integración Económica
BPP Buenas Prácticas Pecuarias
CIAT Centro Internacional Agricultura Tropical
COMPROMUB Cooperativa multisectorial de productores orgánicos de Muelle de los Bueyes
COODEPROSA Cooperativa Multisectorial de Desarrollo Productivo del San Juan
COOMUNSOL Cooperativa Multisectorial Nuevo Sol de Yaoya R.L
COOPROCAFUC Cooperativa de Productores de Cacao Familias Unidas de El Castillo
COOSEMUCRIM Cooperativa de Servicios Múltiples de Cacao en la Reserva de Indio Maíz
COOSEMUP Cooperativa de Servicios Múltiples “Unión de Paiwas”
COOSEMUVIS Cooperativa de Servicios Múltiples de Villa Siquia, R.L
CRS Catholic Relief Services 
EMNV Encuesta de Hogares sobre Medición del Nivel de Vida
FIDA Fondo internacional para el Desarrollo Agricola
FUNIDES Fundación Nicaragüense para el Desarrollo Económico y Social
HDDS Household Dietary Diversity Score
IFAD International Fund for Agricultural Development
IPM Integrated Pest Management 
LWR Lutheran World Relief 
MAHFP Months of Adequate Household Food Provisioning
MEAL Monitoring, Evaluation, Accountability and Learning 
MEFCCA Ministerio de Economía Familiar, Comunitaria, Cooperativa y Asociativa
NGO Non-governmental organization
OCSA Obras de Conservación de Suelo y Agua
PPI Progress out of Poverty Index 
PROGRESA Program for Rural Enterprise Management, Health and the Environment 
RAE Rural Associative Enterprises 
TNS TechnoServe 
UCA Ahmed Campos Union de Cooperativas Ahmed Campos
USDA United States Department of Agriculture
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Table of Contents
Executive Summary ......................................................................................................................... 5
1. Introduction .................................................................................................................................. 7
2. Description of the Intervention .................................................................................................. 8
2.1. Strategic Objectives ............................................................................................................... 8
2.2. Program Activities ................................................................................................................ 8
2.3. Eligibility Rules, Targeting and Selection of Beneficiaries by Chain........................... 10
3. Objectives of the Evaluation ..................................................................................................... 12
3.1. Development of the Hypothesis and Theory of Change ............................................... 12
3.2. Evaluation Questions.......................................................................................................... 15
3.3. Major Intermediate and Results Indicators ..................................................................... 17
4. Evaluation Design ...................................................................................................................... 20
4.1. Experimental design ........................................................................................................... 20
4.2. Participatory Evaluation of Impact................................................................................... 26
4.2.1. Evaluation of Producer Organizations: Facilitated Self-Assessment Tool for 
Management of the Rural Associative Enterprises (RAE)................................................ 26
4.2.2. Evaluation of Stakeholders in the Value Chain: Link Tool .................................... 27
4.2.3. Surveys on the Satisfaction and Perception of Beneficiaries.................................. 28
5. Sampling and Data..................................................................................................................... 28
5.1. Sampling Strategy ............................................................................................................... 28
5.2. Data Collection .................................................................................................................... 29
5.2.1. The Process.................................................................................................................... 29
5.2.2. Assessment of the Data Quality ................................................................................. 30
5.2.3. Data Collected............................................................................................................... 32
5.2.4. Attrition ......................................................................................................................... 35
6. Validation of the Evaluation Design........................................................................................ 40
7. Impact of the Program on the Beneficiaries and Key Stakeholders .................................... 41
4
7.1. Impact of the Program on the Producer Families........................................................... 41
7.1.1. Introduction .................................................................................................................. 41
7.1.2. Characteristics of the Producers................................................................................. 42
7.1.3. Productive Practices of the Early Treatment ........................................................... 44
7.1.4. Infrastructure and Equipment.................................................................................... 52
7.1.5. Social Capital and Assistance ..................................................................................... 53
7.1.6. Productive Yields and Its Association with Agricultural Practices ...................... 55
7.1.7. Commercialization of Production.............................................................................. 59
7.1.8. The Socio-economic Well-being of the PROGRESA Beneficiaries ........................ 63
7.1.9. Summary of Intermediate and Outcome Indicators................................................ 66
7.2. Farmers’ Perception Surveys ............................................................................................. 67
7.2.1. Beneficiary Satisfaction on the Program ................................................................... 67
7.2.2. Farmers’ Perception on Financial Education............................................................ 70
7.3. Producers Organizations Performance ............................................................................ 72
7.3.1. Introduction .................................................................................................................. 72
7.3.2. Methodology................................................................................................................. 73
7.3.3. Results for Management of Producers Organization.............................................. 75
7.4. Impact of the Participation and Practices of the Private Sector in Improving Market 
Links and Income of Smallholder Producers ......................................................................... 88
7.4.1. Introduction .................................................................................................................. 88
7.4.2. Methodology................................................................................................................. 89
7.4.3. Performance Assessment for the Cooperative Enterprises (sellers)...................... 90
7.4.4. Performance Assessment for Businesses (buyers)................................................... 94
8. Conclusions and Lessons Learned........................................................................................... 98
References...................................................................................................................................... 107
Annex............................................................................................................................................. 108
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Executive Summary
The Program for Rural Enterprise, Health and Environment – Caribbean Zone 
(PROGRESA Caribe) is a five-year (2014–2019) value chain strengthening project for the 
cacao and livestock (dual purpose) sectors in the Caribbean Coast Region of Nicaragua: 
RACCN, RACCS and Río San Juan. The Food for Progress Program, financed by the 
United States Department of Agriculture, has a total budget of US$9,511,675 and is under 
implementation by Catholic Relief Services (CRS) in consortium with TechnoServe (TNS) 
and Lutheran World Relief (LWR). The first stage of PROGRESA Caribe has been 
implemented for 18 months (October 2015-April 2017).
The program benefits more than 4,000 smallholder producers from 13 municipalities. The 
program also works on the strengthening of 17 producer organizations and associations, 
and in the promotion of 11 commercial relationships under inclusive business models. The 
project activities are aimed at fulfilling two strategic objectives: 1) increase agricultural and 
livestock productivity and 2) expand trade of cacao and cattle products. The long-term 
outcome of the program is to increase the income of the producer families and reduce 
poverty in the intervention areas.
PROGRESA Caribe considers the economic, political and cultural context of the Caribbean 
Coast and Río San Juan, which are areas with a high incidence of poverty and historically, 
they have received fewer resources for socio-productive projects. The program also fits 
within the Government of Nicaragua’s economic and agricultural development policies 
and programs.
PROGRESA Caribe mid-term evaluation followed a mixed approach, i.e., both 
quantitative and qualitative methods were incorporated. To measure the impact of the 
project on families’ welfare and farmers' performance, the evaluation team designed an 
experimental strategy called randomized order of phase-in. The intervention is 
implemented in two cohorts, making it possible to randomize beneficiaries for early and 
late treatment. More than 50% of the beneficiary producers were assisted from the 
beginning of the project (early treatment) and another part began to be assisted as of 
month 19 of activity implementation (late treatment). This strategy also allowed to 
randomize the length of time of participation in the program.
On the other hand, a participatory approach was implemented (ADA and Link tools) to 
measure the impact on producers’ organizations (cooperatives) and private companies 
and the satisfaction of services provided by the program.
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Key findings 
During its first stage, the program met the needs of the project beneficiaries. The results of 
the beneficiary satisfaction survey of the early treatment group reveals a positive 
assessment in all the types of interventions. Also, according to farmers' perception, the 
main factors that appear as key to facilitation of a better adoption in all types of 
interventions are training and provision of information. 
Farmers’ productivity for dairy/beef products increased for the early treatment group 
compared to the baseline, both in milk and in the weight of live cattle. Nevertheless, there 
is no effect yet in yields due to the intervention at the mid-term. This result is expected as 
productive yields do not change so rapidly in just 18 months of intervention. 
There is a reduction due to the intervention in livestock and cacao production costs and an 
increase in gross income for cacao. Also, in the cattle value chain there is an increase due 
to the intervention in the gross margin of the early treatment group. 
The proportion of farmers applying different types of practices evaluated in cacao and/or 
cattle has increased for most of the cases or at least remained or are relatively constant. In 
addition, there are substantial increases in the percentage of producers of early treatment 
compared to the late treatment, in both cacao and cattle, that have savings or investment 
budgets, who manage debt, record sales, keep track of livestock inventory, and keep 
records on costs and production. This important progress is due to the effort made by the 
program in its initiative to strengthen farm management. 
Moreover, for early treatment households’ poverty was reduced by 3 percentage points at 
the mid-term. The incidence of poverty was reduced in those households of the early 
treatment with greater economic vulnerability. However, at the mid-term no statistically 
significant changes in poverty are found due to the intervention. This result is expected 
since changes in welfare mostly take place in the long term. 
The overall score on the performance of producer's organizations increased compared to 
the baseline. It is likely that 9 cooperatives could reach the goal in performance at the end 
of the project. For the remaining cooperatives, whose baseline results were extremely low, 
it is also expected an increase in their performance at the end of the project. 
These results suggest that PROGRESA Caribe is on track to meet most of the development 
objectives at the end of the intervention. 
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1. Introduction 
The Program for Rural Enterprise, Health and Environment – Caribbean Zone (hereinafter 
PROGRESA Caribe) is a five-year (2014–2019) value chain strengthening project for the 
cacao and livestock sectors in the Caribbean Coast Region of Nicaragua: RACCN, RACCS 
and Río San Juan. The Food for Progress Program, financed by the United States 
Department of Agriculture, has a total budget of US$9,511,675 and is under 
implementation by Catholic Relief Services (CRS) in consortium with TechnoServe (TNS) 
and Lutheran World Relief (LWR). The first stage of PROGRESA Caribe has been 
implemented for 18 months (October 2015-April 2017). 
The program builds upon previous experiences of the consortium partners in the Northern 
Region and the Caribbean Coast of Nicaragua. It also continues working with producers 
that participated in previous programs. The idea is to build a critical mass of technical 
knowledge and commercial capacity that will transform the cacao and livestock value 
chains in Nicaragua and allow producers to capture greater shares of income and profit as 
their value chains become better articulated and their participation more proactive and 
organized. 
The project has as target population of more than 4,000 small cacao and/or livestock 
producers. The activities are focused on existing producers, instead of promoting new 
plantations. The beneficiaries of the project are from 13 municipalities. The project 
activities are aimed at fulfilling two strategic objectives: 1) increase agricultural and 
livestock productivity and 2) expand trade of cacao and cattle products. 
The consortium partners have collected quantitative and qualitative data at producer and 
organizational level for the baseline and mid-term rounds, to evaluate the evolution of 
intermediate and outcome indicators and to estimate the impact of the intervention in the 
first stage. The aim is to recommend strategic actions to improve project performance 
during the second stage. 
This report presents the results of the mid-term evaluation of PROGRESA in the 
Caribbean Coast of Nicaragua. The document is comprised of eight sections. The second 
section describes the background of the intervention. The third section presents the 
objectives of the evaluation. The fourth section addresses the quantitative and qualitative 
evaluation design. Section five addresses the sampling strategy and the data collected. The 
sixth section presents the validation of the evaluation design. Section seven focuses on the 
impact of the program on the beneficiaries and key stakeholders. Lastly, section eight 
discusses the lessons for learning and recommendations. 
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2. Description of the Intervention
PROGRESA Caribe works to strengthen the value chain of cacao and (dual purpose) 
livestock in the Caribbean Region of Nicaragua. The program benefits more than 4,000
smallholder producers from 13 municipalities: Waslala, Siuna, Bonanza and Rosita in 
RACCN; El Ayote, La Cruz de Río Grande, Muelle de los Bueyes, Bocana de Paiwas, 
El Rama, Bluefields, and Nueva Guinea in RACCS; and San Carlos and El Castillo in Río 
San Juan.
Furthermore, the program is working to strengthen 17 producer organizations and 
associations, and in the promotion of 11 commercial relationships under inclusive business 
models. The duration of the activities with the beneficiaries is approximately of three and 
a half years.
2.1. Strategic Objectives
The project activities are aimed at fulfilling two strategic objectives: 
1) Increase agricultural and livestock productivity.
2) Expand trade of cacao and cattle products.
Improvement in productivity will be addressed by providing inputs and facilitating 
genetic material, credit to the productive activity, technical assistance and training. This 
will enable improved production techniques and enhance the administration capacity of 
the farms. The expansion of cacao trade, dairy products and meat will be sought through 
training in business management to producers and cooperatives; facilitating construction 
and improvement of the post-harvest processing infrastructure; increasing access to 
markets, the activities will promote the participation in national tasting contests and the 
establishment of public-private and private-private alliances, as well as the leveraging of 
resources from the private sector and investments from the public sector.
2.2. Program Activities
The consortium partners implement a cohesive set of activities that aim to mitigate value 
chain weaknesses in four key areas of the cacao and livestock value chains: production, 
post-harvest handling, processing and marketing.
Activities to increase agricultural productivity in the target value chains are focused on 
training to improve agricultural production techniques and farm management, as well as 
fomenting farm-level financial and non-financial services that producers need to 
implement the best practices. 
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Activities to expand trade are focused on increasing market access for smallholder 
producers through improving post-harvest handing and processing, training on 
certifications and standards, and facilitating private and/or public partnerships for buying 
and selling, co-investment in infrastructure, and the exchange of market information. 
Complementary foundational activities include increasing the capacity of cooperatives 
and trade associations to serve their smallholder members.
The consortium partners explained to the evaluation team that there are ten types of 
interventions being implemented to varying degrees. These interventions are: 1) technical 
assistance, 2) trainings, 3) field schools, 4) workshops, 5) informative talks, 6) provision of 
goods and services, 7) dissemination through ICT, 8) participation in fairs, 9) field days 
and 10) exchange tours. Each consortium partner works with a different combination of 
interventions. This implies that some interventions are not implemented by all consortium 
partners.
TNS works mainly through monthly trainings and does not provide technical assistance in 
the way that LWR and CRS does. TNS does not conduct exchange tours and does not 
provide inputs to farmers, except for on the demonstrations plots. TNS supports the 
provision of goods and services indirectly through facilitation of microcredits by 
microfinance institutions or producer organizations (cooperatives).
LWR does not provide goods and services and does not implement informative talks and 
fairs. CRS implements nine types of interventions. CRS and LWR do not implement 
training in the way TNS does; instead, CRS and LWR apply the methodology of field 
schools. The intervention approach is diverse due to the territorial extension of the 
program (13 municipalities).
Figure 1: Types of interventions being implemented in Progresa Caribe
Technical assistance X X
Training X
Field schools X X
Workshops X X X
Informative talks X X
Goods and services X
Dissemination X X X
Fairs X X
Field days X X X
Exchange tours X X
Source: Consortium partners.
Activity CRS LWR TNS
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On the other hand, the evaluation team has reviewed the document of the agreement and 
the results of the mid-term evaluation for the first 18 months of the program and 
according to our observation the consortium is operating in line with the scope of the 
objectives of the program: 1) increase agricultural productivity: increase productivity of 
the cacao and dual-purpose livestock value chains, and 2) Expand trade of agricultural 
products: expand trade of cacao, dairy products, and beef. The modifications proposed by 
the consortia are related to sub-activities, allowing the consortium partners to focus on 
their combined strengths in addressing the actual needs of the producers and their 
organizations and respond to the realities on the ground. The modifications are detailed in 
annex.
Box 1. Monetization
During the first stage of PROGRESA Caribe, the leader of the consortium (CRS) has continued monetizing 
CDSO. Since the country is not self-sufficient in oil for human consumption, CRS identified in 2013 this 
commodity as a viable one to be monetized in Nicaragua. At that time, three companies, with relatively small 
capacity each, were identified as possible buyers. These companies have together imported this product for 
decades from Pasternak Baum; a U.S. company based in New York that has been willing to buy the product 
from CRS and to sell to the traditional buyers in the country, assuming the cost of insurance for shipping. 
Using a commercialization channel already established in Nicaragua, allows the companies involved (seller & 
buyers) to program a CRS sale in their normal calendar and at the same time maintaining a steady supply of 
the commodity for the country. For these reasons, PROGRESA Caribe has continued using CDSO to ensure 
enough funds for the execution of the project. 
During the last sale (early April 2017) a small impasse occurred due to an inappropriate handling of the 
product during the loading process at the US Port. As a consequence, 51 metric tons of CDSO (1.46% of the 
total amount) had to be destroyed in Nicaragua for having been deposited in a tank of the vessel that did not 
pass certificate of cleanliness during the loading process. That represented a total loss of US$ 40,000. CRS 
expects to recover this loss during the final sale. As a lesson learned, CRS is planning to include additional 
clauses into their sales and freight contracts in order to protect themselves against this type of issues.
Despite this impasse, CRS considers that CDSO continues to be a very good option for monetization in 
Nicaragua. The evaluation team does not have any objection that this continue to be the first option for the 
next and final sale.
2.3. Eligibility Rules, Targeting and Selection of Beneficiaries by Chain
The program targets RACCN, RACCS and Río San Juan because they are areas with a high 
incidence of poverty (50.5% in 2014)2 and historically, they have received fewer resources 
for socio-productive projects. In addition, they are areas of interest for the assistance 
 
2
INIDE (2015).
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provided by USDA in Nicaragua, where the members of the consortium and the 
implementing partners have extensive experience.
The selection of beneficiaries was based on the following criteria: a) cacao growers, dual 
purpose cattle ranchers, and producers that work in both chains, whose production is 
fundamental to their livelihood strategy; b) producers that have between 5 and 100 cattle 
in production (and less than 20 hectares allocated to livestock production) and/or with less 
than 5 hectares for agriculture; c) families that are willing to actively participate in the 
program; and d) identification of women farmers who work in these chains in order to 
achieve 20% participation by women in the program. According to the program 
beneficiary selection rules, beneficiaries can be supported in one or two chains, as long as 
they fulfill the selection criteria.
The program also decided to continue strengthening producers who have participated in 
prior interventions by the consortium members in the area and who meet the selection 
criteria. The remaining producers were identified by the members of the consortium and 
by the implementing partners. In practice, the selection of the communities was based on 
the geographic location of the producers that meet the eligibility criteria and who accepted 
being part of the program. 
The consortium partners selected a total of 4,247 producers to participate in PROGRESA 
Caribe. At the end of the baseline, a total of 4,134 producers were registered. According to 
CRS administrative data through April 20173
, there are a total of 4,401 active producers in 
the program. The distribution of beneficiaries by chain, department and consortium 
partner is the following:
Table 1. PROGRESA Caribe. Distribution of beneficiaries
At the end of the baseline, the consortium partners expressed interest in including more 
beneficiaries in the program. In this context, the evaluation team recommended that the 
new beneficiaries should come exclusively from the early treatment communities in order 
to avoid contamination in late treatment. A total of 275 new beneficiaries were added 
during the first phase of the program. A quick review of the database of new beneficiaries 
suggests that this recommendation was followed. 
 
3 This information is prior to the mid-term evaluation.
Both Cacao Cattle Total Both Cacao Cattle Total Both Cacao Cattle Total Both Cacao Cattle Total Both Cacao Cattle Total
CRS 321 295 140 756 194 179 42 415 29 84 28 141 - - - - 544 558 210 1312
LWR - 795 - 795 - 428 - 428 - - - - - 78 - 78 - 1301 - 1301
TNS 190 254 757 1,201 128 25 300 453 21 16 97 134 - - - - 339 295 1154 1788
Total 511 1344 897 2,752 322 632 342 1,296 50 100 125 275 - 78 - 78 883 2154 1364 4401
Source: CRS data
Total
Partner Early treatment Late treatment New beneficiaries Members of cooperatives
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31.0% of the beneficiary producers are supported in the dual-purpose cattle chain, 48.9% 
in the cacao chain, and 20.1% in both chains. TNS is more focused on cattle producers 
while LWR works only with cacao producers. CRS has a balance of beneficiaries working 
in cattle, cacao and both chains. Geographically, most of the selected cacao producers are 
concentrated in Waslala and El Castillo, while most of the livestock farmers are in RACCS 
(mainly in Nueva Guinea and Bocana de Paiwas).
3. Objectives of the Evaluation
3.1. Development of the Hypothesis and Theory of Change4
The construction of the PROGRESA Caribe theory of change has been based on the results 
framework, the detailed budgetary lines in the program implementation plan, and the 
indicators established in the association agreement with the USDA. 
The theory of change has been designed in a results chain scheme, where the causal logic 
is defined from the beginning of the program to its conclusion, taking the following 
elements into consideration: activities (the how), products (the why), the results (the if), 
the final results (the then)5
. Figures 2 and 3 present the results chain for the two strategic 
objectives: 1) improve agricultural and livestock productivity and 2) expand commerce of 
agricultural and livestock products.
Based on the results chain, the impact evaluation seeks to confirm the following 
hypothesis:
 If the program activities as a whole improve agricultural and livestock productivity and 
if the trade of cacao, dairy products and meat expands, this will increase the income of 
the farmer families and will contribute to poverty reduction in the areas of intervention.
In this sense, the hypothesis to be confirmed should identify – to the extent possible – the 
specific effect of the intervention as a whole relative to what the result would be in terms 
of family income and poverty levels if the beneficiaries were not attended by the program. 
 
4 The CRS team has prepared an extensive version of the PROGRESA Caribe theory of change, 
which addresses the results chain for each strategic result, product, input and foundational result.
5 The sequence of the results chain may also begin with the inputs; in other words, the results that 
the project makes available (budget, personnel, etc.). PROGRESA Caribe´s theory of change takes 
this element into account.
13
Figure 2: Results Chain – Strategic Objective 1
14
Figure 3: Results Chain – Strategic Objective 2
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3.2. Evaluation Questions
The impact evaluation provides responses to key questions about the relevance, 
effectiveness, efficiency, impact and sustainability of the program, as well as specific 
questions about learning in the value chains that are important to USDA, the local 
partners, the donor community and other key stakeholders. For the mid-term evaluation, 
the questions to be answered are listed below:
Key evaluation questions
Relevance:
 To what extent did the project meet the needs of the project beneficiaries and take into 
account the economic, cultural and political context?
 To what extent did the project fit within the Government of Nicaragua’s economic and 
agricultural development policies and programs?
Effectiveness:
 To what extent has the project achieved its stated objectives?
 Did the project increase farmers’ productivity in cacao and dairy/beef products?
 Did the project enhance the quality and safety of the food produced by participating 
farmers?
 Did the project increase participating farmers’ sale of products?
 Did the project ensure food security of participating farmers’ family?
 Did the project increase participating farmers’ family income?
 Did the project reduce the incidence of poverty in the intervention areas?
Efficiency:
 To what degree have the project resources caused the results achieved and whether the 
same results could have been achieved with fewer resources or alternative approaches?
 Were the project strategies efficient in terms of financial and human resources, as 
compared to the outputs? What alternatives are there?
 Monetization: Evaluation of the efficiency and effectiveness of the monetization 
process, capturing lessons learned. 
 Was the monitoring system designed efficiently to meet the needs and requirements of 
the project?
 Coordination: The effectiveness and efficiency of coordination with project partners 
and other programs and activities carried out by other area stakeholders.
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Impact: 
Evaluation of the intentional or unintentional medium-term effects of the project and, to 
the extent possible, evaluation of the degree to which the effects are attributable to the 
project and not to other factors.
Sustainability of outcomes and impacts:
 To what extent are the project’s activities foreseen as sustainable?
 Will project activities continue in the absence of support from both USDA and 
consortium partners? If so, how? If not, why not?
 Will the effects of the project on producers, producer organizations, partner 
organization sustain overtime after the project ends?
 To what extent are the outcomes and impacts of the program resilient to risk over time?
Key value chain learning questions
 What is the return on investment (technology, infrastructure, etc.) that the participating 
families (and their organizations) achieved as a result of their participation in the value 
chains?
 What is the relationship between infrastructure investment and changes in sales and 
income at both the household and cooperative level?
 How do the different enterprise models established for value chain development, affect 
impacts at the producer and cooperative levels?
o In what measure do the enterprise models generate incentives for private sector 
businesses to invest in productive infrastructure and provision of services (technical 
and financial) for smallholder producers?
o What is the household-level impact of affiliation with cooperatives that are 
connected with value chains?
 What is the relationship between compliance with Good Livestock Practices (BPP, 
acronym in Spanish) norms (cattle) and organic or other certifications (cacao), changes 
in productivity, and income?
o What are the most effective incentives to promote compliance with sanitary and 
phytosanitary norms?
o What are the key success factors for leveraging sanitary and phytosanitary practices 
into access to higher value markets?
o Do certified producers have higher net income than non-certified producers?
17
3.3. Major Intermediate and Results Indicators
The indicators to be evaluated include those (intermediate) results that are achieved when 
the population served benefits from the program products as well as from the final 
outcomes of the intervention, which correspond to the strategic objectives. In addition, the 
implementation indicators agreed upon with the USDA will be evaluated. These have 
been monitored since the program’s baseline study. This ensures evaluation through the 
chain and better identification of the causes for the program results at mid-term. Figures 4 
and 5 present the matrix of intermediate and results indicators to be evaluated, 
respectively.
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Figure 4: Matrix of Intermediate Indicators
Description Calculation Formula Measuring Frequency Means of Verification
Liters of milk per cow per day
This indicator measures the productive
efficiency of cattle herd
Baseline survey, mid-term
survey, final survey
Module: Livestock
production
Yields in the cacao production
The total cacao production volume in
(Metric Tons) by producers divided by the
total number of production hectares 
Baseline survey, mid-term
survey, final survey Module: Agriculture
Average cattle weight per hectare 
This indicator will measure the total kilos of
live animals that the producer has in the
herd inventory, and are supported by
USDA
Baseline survey, mid-term
survey, final survey
Module: Livestock
production
Cocoa Production Costs
Total production cost per hectare measured
in dollars for the cacao category. All sales
related with cacao (dry and baba)
production are included, as well as genetic
material
Baseline survey, mid-term
survey, final survey Module: Agriculture
Production Cattle Costs
Total cost of milk sales, derived from milk
and cattle, by hectare of pasture and
measured in dollars
Baseline survey, mid-term
survey, final survey
Module: Livestock
production
Gross Margin per Hectare (cocoa)
Increase in income attributable to
investments made in improving production
techniques and technology implementation
Baseline survey, mid-term
survey, final survey Module: Agriculture
Gross Margin per hectare
(livestock)
Increase in income attributable to
investments made in improving production
techniques and technology implementation
Baseline survey, mid-term
survey, final survey
Modules: 1) Livestock
Production and 
2) Cattle Sales
Number of hectares managed
under sustainable agricultural
practices
Number of hectares of cocoa and livestock
managed under sustainable practices, such
as using eco-friendly fertilizers and
pesticides, erosion control, agroforestry, etc.
Baseline survey, mid-term
survey, final survey
Modules: 1) Livestock
Production and 
2) Cattle Sales
Indicator
Intermediate 
Indicators
 
 
 
 
 
 
 
 
 
 
*100
 
 
*100
 
 
 
 
 
19
Figure 5: Matrix of Outcome Indicators
Description Calculation Formula Measuring Frequency Means of Verification
Progress out of Poverty Index
The PPI is a simple index rating of poverty
that estimates the probability that a home
has costs less than a certain poverty line.
The index uses ten simple indicators for
collection on-site.
Baseline survey, mid-term
survey, final survey
Modules: 
Poverty Index PPI
Family Income
Family income received by the sale of
production and other income from some
family member(s)
Baseline survey, mid-term
survey, final survey
Modules: 1)
Agriculture 2) Sale of
Livestock and 3) Food
Security (socio￾demographic 
characteristics
** HDDS: Total number of food groups
consumed by families 
Months of adequate supply of
food in the household (MAHFP)
Capture changes in the home ability to
approach the vulnerability so as to
guarantee the procurement above a
minimum level throughout the year.
Measuring the MAHFP has the advantage of
obtaining the combined effects of a series of
interventions and strategies, for a better
agricultural production, storage and
activities that increase the families’
purchasing power.
Baseline survey, mid-term
survey, final survey
Modules:
Food Security 
Return of the producer’s
investment and processing of
cooperatives activities
It measures the reduction in production
costs and the increase of income as a result
of the quality achieved through the
efficiency of processing activities. Evaluates
the performance of the investment made by
the producer or cooperative in operation
(efficiency of spending to maximize sales)
Annual
Administrative 
Records 
Number of individuals receiving
financial services as a result of
USDA´s assistance
Number of producers who have access to
financial services, as a result of USDA´s
support. Financial services include those
that help identify and access funds through
formal and alternative channels.
Bi-annual
Administrative 
Records 
Indicator
Outcome 
indicators
Household dietary diversity scores
It collects information about the families´
food safety. Focuses on the composition of
the regular family diet, if they suffer some
kind of food shortage and in which months
this scarcity predominates.
Baseline survey, mid-term 
survey, final survey
Modules:
Food Security 
 
 
 
 
 100
 
 
 
*100
 
 
 
 
 
20
4. Evaluation Design
PROGRESA Caribe mid-term evaluation followed a mixed approach; in other words, both 
quantitative and qualitative methods were incorporated. This approach made it possible 
to a) triangulate the results of the evaluation, which strengthens the validity and 
credibility of the results; b) utilize information from one method to develop the instrument 
for another; c) have complementarity in the results; d) have diversity in the value 
dimensions of the evaluation; and e) generate new knowledge about the evaluation 
results. 
Furthermore, the evaluation followed an Evaluative Thinking approach, which implied 
close interaction with the Monitoring, Evaluation, Accountability and Learning (MEAL) 
team from each consortium partner and the CRS Knowledge Management Division. In this 
regard, the evaluation team conducted several sessions to exchange information about the 
program, and based on the quantitative and qualitative databases that were generated 
over the course of the evaluation, they developed a process for critical (and respectful) 
reflection and discussion from the process of cleaning the data to the identification of 
results. This made it possible to more deeply understand the assumptions of the program 
set forth in the theory of change and in the mechanisms for the implementation of 
activities, to respond to the evaluation questions, and to recommend future actions.
This section is divided in two parts. The first part discusses the experimental methodology 
to measure the impact of the project on families’ welfare and producer´s performance 
(quantitative approach). The second part addresses the participatory approach to 
evaluation (qualitative approach) that will measure the impact on producers’ 
organizations (cooperatives) and private companies and the satisfaction of services 
provided by the program.
4.1. Experimental design6
Selection bias
The selection of the beneficiaries of PROGRESA Caribe generated two types of selection 
bias, due to: a) administrative rule (based on observable characteristics) and b) self-selection.
The first was related to the fact that 14% of the targeted beneficiaries came from previous 
interventions of the consortium partners. These producers may differ in characteristics 
compared to those working for the first time with the consortium partners, as they would 
 
6 This section is a summary of PROGRESA Caribe´s baseline report, section 4.1. Experimental Design.
21
have better results due to the capacities built in previous interventions similar to the 
current one. However, there is no reason to believe that both groups have differences in 
their motivations to participate in the program. In addition, another slight bias was 
identified due to observable characteristics, given that 16% of the beneficiaries selected 
were women, who were encouraged to participate in the program.
Another source of bias came from the selection – under the consortium´s partner criteria –
of participants that were apparently willing to actively participate in the program 
(program placement bias). Finally, a potential self-selection bias might appear if some 
families with motivation to receive a benefit approached more actively local partners in 
order to get selected into the program.
Identification of impact
The selection of beneficiaries of PROGRESA Caribe did not follow an experimental design. 
However, as the activities were not going to start with all producers immediately, the 
evaluation team proposed an intervention strategy that made possible to randomly 
identify a temporary control group and also to randomize the duration of time in the 
program. This strategy is called randomized order of phase-in.
The evaluation team and the consortium partners agreed the intervention had to be 
implemented in two cohorts, making it possible to randomize the beneficiaries in early 
and late treatment. For the late treatment cohort, services initiated from the 19th month of 
the execution of activities (May 2017).
In order to diminish the contamination risk in the program, it was decided to randomize 
the treatment allocation at the level of 65 groups (clusters) of adjacent communities 
(cluster randomization). Also, it was decided a (cluster) random selection of 65% for early 
treatment and 35% for late treatment, which generated an early and late assignment of 42 
and 23 clusters, respectively. At beneficiary level, this implied 2,676 beneficiaries for early 
treatment (63%) and 1,571 for late treatment (37%).
Since all clusters had a similar opportunity to be early treatment, we had a treatment 
group (early treatment) and a temporary conventional control group (late treatment) with 
similar characteristics. For the mid-term evaluation, the first cohort becomes the treatment 
group and the second one corresponds to their comparison group.
A successful experiment requires a clear identification strategy. In this regard, the 
evaluation team has explained the experimental design and its challenges to the 
consortium partners, implementing partners and their technicians, so that they inform all 
beneficiaries and producer organizations about the treatment allocation process.
22
The diagram below presents the treatment selection process.
Figure 6. Treatment selection process
The cluster random assignment generated the following beneficiaries’ distribution by 
treatment status, partner, value chain, region, sex and repeating producers:
23
Table 2. Distribution of beneficiaries by treatment assignment
Econometric methodology
Difference-in-differences estimator
For the mid-term evaluation, we aim at estimating the Average Treatment Effect on the 
Treated (ATET). Under a standard evaluation of a binary treatment the ATET would be:
𝐴 𝐸 = 𝐸[∆ 
| = ] = 𝐸[𝑌1 𝑌0 
| = ] = 𝐸[𝑌1 
| = ] 𝐸[𝑌0 
| = ]
The key is to identify the counterfactual𝐸[𝑌0 
| = ], i.e., the potential outcome as 
untreated, for the treated ones.
Given that randomization solves the selection problem because it ensures that the 
treatment assignment be statistically independent of potential outcomes, then:
𝐴 𝐸 = 𝐸[𝑌1 
| = ] 𝐸[𝑌0 
| = ]
𝐴 𝐸 = 𝐸[𝑌1 
| = ] 𝐸[𝑌0 
| = 0]
Randomization causes that the potential outcome as untreated for those who were actually 
not treated (𝐸[𝑌0 
| = 0]) is a valid counterfactual.
Alternatively, the difference-in-means estimator could be specified through the following 
regression:
𝑌 = 𝛽0 𝛽1 𝜀 
Where i corresponds to the unit of analysis (the producer). Randomization ensures that 
is independently distributed from the unobservable characteristics (𝜀 
), so it accomplishes 
F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M F M
Both chains 25 194 15 87 28 139 12 21 127 3 43 84 476 4 1258
Cacao 32 171 11 81 38 242 75 296 17 127 65 175 3 5 17 94 7 61 36 161 43 124 21 43 10 1955
Livestock 9 99 5 27 108 571 3 16 4 35 3 13 140 1 1034
Total 66 464 31 195 38 242 0 0 75 296 17 127 201 885 6 33 42 256 10 107 36 161 0 0 43 124 21 43 97 626 0 5 4247
Source: Evalution team calculation based on PROGRESA Caribe adminsitrative records
Value Chain Total 
New Repeaters
Early treatment Late treatment
CRS LWR TNS CRS LWR TNS
Río San Juan RACS
New Repeaters New Repeaters New Repeaters New Repeaters
RACNS RACNS Río San Juan RACS RACNS RACNS
New Repeaters New Repeaters New Repeaters
24
with the zero-conditional mean assumption (𝐸[𝜀 
| = 0]). 𝛽1 measures the causal effect 
(or average treatment effect):
𝐴 𝐸 = 𝛽1 = 𝐸[𝑌 
| = ] 𝐸[𝑌 
| = 0]
Given that the data has been collected for two periods (baseline and follow-up), we can 
exploit the panel data structure by computing the ATET in the mid-term evaluation using 
the difference-in-differences methodology. This method consists of the double difference 
calculation:
∆̂ = (𝑌̅
 , 𝑓 𝑌̅
 , 𝑓 ) (𝑌̅
 , 𝑓 𝑌̅
 , 𝑓 )
The first difference corresponds to the difference in the after-and-before outcomes for the 
treatment group (early treatment), which controls for time-invariant characteristics. The 
second difference relates to the difference in the after-and-before outcomes for the 
comparison group (late treatment). Subtracting the first difference from the second, it has 
isolated the effect of time-varying factors, under the assumption that both treatment and 
comparison groups were exposed to the same environmental conditions (parallel trend 
assumption); this assumption is plausible in the context of PROGRESA Caribe, given the 
targeting in the Caribbean Coast and Rio San Juan, which are locations where the 
producers tend to face the same environmental conditions.
This method provides a more precise estimate of the impact and allows the treatment and 
comparison group to differ in characteristics, provided that the parallel assumption trend 
is accomplished and that the unobservable characteristics of the beneficiaries are time￾invariant. This is a very important feature, as later we will see that the balance in 
observable characteristics between early and late treatment was affected by attrition 
(nonresponse) of the evaluation sample. The evaluation team found a bias in the 
evaluation sample, as the attrition is correlated with treatment status. More detailed on 
this issue will be discussed in the following sections.
In the potential outcome framework, the difference-in-differences parameter can be 
expressed as follows:
𝛿𝐴 𝐸 = 𝐸[𝑌 ,2 𝑌 ,1 | = ] 𝐸[𝑌 ,2 𝑌 ,1 | = 0]
Where 𝑌 ,2 is the outcome of producer at the mid-term survey and 𝑌 ,1 is the potential 
outcome of the producer at the baseline survey. The potential outcome depends on 
whether the producer was assigned to be treated early ( = ), i.e. in the first 18 months of 
the program implementation, or while he was assigned to be treated late ( = 0), that is, 
from the 19th month.
25
The double difference can also be specified in the following regression, 
𝑌 = 𝛽0 𝛽1 𝛽2 𝛿 × 𝜇 𝜀 
Where 𝑌 represents the outcome of producer in cluster at time . 𝛿 corresponds to 
the impact coefficient, i.e. the mid-term program impact would be given by the interaction 
between the variable that captures the time of data collection ( ) and the binary variable 
that captures the early or late treatment assignment ( ). 𝜇 corresponds to time-invariant 
observable and unobservable characteristics of producer families, for example education 
and producer skills, sex, soil quality, etc. 𝜀 is a time-varying idiosyncratic error. The 
parameters 𝛽 and 𝛿 are unknown.
For the proposed experimental design, the difference-in-differences technique will allow 
the isolation of the self-selection bias (previously discussed), as it can be assumed that the 
motivation to participate in the program is a time-invariant unobservable characteristic.
In order to ensure robust results and reduce the residual variance of the estimate, 
additional regressors will be included to test the validity of the random sample7
. 
Therefore, the above equation can be rewritten as follows:
𝑌 = 𝛽0 𝛽1 𝛽2 𝛿 × 𝛾
′𝑋
′
 𝜇 𝜀 
Where 𝑋
′
corresponds to a vector of time-varying observable producer characteristics that 
may affect the potential outcome.
Matching estimators combined with difference-in-differences
As mentioned previously, the evaluation team found a bias in the evaluation sample, as 
the attrition is correlated with treatment status. In this case, the combination of two 
techniques may be used to isolate the bias: matching estimators (which mitigates the bias 
by observable characteristics) with difference-in-differences (which isolates the self￾selection bias)8
.
The idea behind matching estimators is to statistically identify (based on observable 
characteristics) two “identical” individuals in the data, with the exception that one is 
treated and the other individual is untreated, so that any difference in the result between 
the two may be attributed to the program.
 
7
If the program effect changes significantly by including additional regressions, then it is probable 
that the randomization has failed in some way.
8 The insight behind the application of this method has been explained in the previous section. 
26
Matching requires the assumption that the selection in the program is only based on 
observable characteristics, which also affect the expected results (conditional
independence assumption). If this assumption is fulfilled, conditional on a set of 
covariates, the allocation of treatment is random. Therefore, it is assumed that two 
individuals with the same characteristics, one treated and the other not, have the same
counterfactual (Caliendo and Kopeing, 2008). The key in this method lies on the careful 
identification of the “clone” for the treated individual.
Nonetheless, is difficult to identify for each treated individual an untreated one (curse of 
dimensionality); therefore, the propensity score technique should be applied. This method 
is one of the most popular in the impact evaluation literature when the experimental 
design is affected by attrition. It estimates the probability of participation in the program 
for the sample of treated and controlled individuals, using observable characteristics as 
covariates, which jointly affect the probability of participation and the potential outcome. 
Using the estimated probabilities for each individual, the sample is restricted to a region of 
common support; in other words, to individuals in both groups (treatment and control) 
that have similar probability of being treated. For this task, different matching algorithms 
(e.g. nearest neighbor, caliper and radius) are used. Once the matching is successful, we 
can compute the impact of the program, i.e. the difference in the mean outcome between 
the treated (early treatment) and control group (late treatment) for the region of common 
support.
4.2. Participatory Evaluation of Impact9
Participatory methods were applied to evaluate the impact on producer organizations and 
private enterprises, to identify lessons learned and to evaluate the degree of satisfaction 
with the services provided by the program. Two types of participatory evaluations were 
used: 1) participatory methods to assign scores (based on opinions and/or perceptions) 
and 2) survey of perceptions and satisfaction of the beneficiaries.
4.2.1. Evaluation of Producer Organizations: Facilitated Self-Assessment Tool for 
Management of the Rural Associative Enterprises (RAE) 
The mid-term performance evaluation of the producer organizations was based on the 
application of the tool for “facilitated self-assessment of the management of rural 
associative enterprises (RAE)”. This tool enables the producer organizations to conduct a 
quick analysis of their business management and organizational process. Gottret, Junkin 
and Ugarte (2011) state that this methodology aims at a participatory self-assessment 
 
9 The section on results discusses the methodological aspects of each of these tools in greater detail. 
27
process by the leadership bodies, members, and the management, administrative and 
technical teams of the cooperatives. 
The instrument includes different criteria that are summarized in indicators. Each criterion 
is assigned a score, from one to five, where five is the optimal status for the organization. 
The self-assessment scores were entered into an Excel file to estimate the average values 
for each thematic area and for the overall score.
Figure 7: Qualitative Indicators for the Facilitated Self-Assessment Tool
4.2.2. Evaluation of Stakeholders in the Value Chain: Link Tool
The stakeholders in the value chain are linked by commercial relationships in which each 
act as a buyer and seller for its neighboring links. The Link methodology is used to 
evaluate the degree of connection (inclusion) in the chain. This methodology is mainly 
aimed at those stakeholders that play the role of facilitators for the processes between 
sellers and buyers, the role played by the consortium and implementing partners.
The Link methodology includes the use of four tools: 1) the value chain map, which helps 
identify the key stakeholders, processes and services within a value chain and how each 
interacts with the rest; 2) the business model canvas, which enables the organizations 
and/or enterprises to rapidly sketch their current situation as an entity and to identify 
1) Strategic 
Orientation
Market Skills
Strategic 
Management 
Skills
Strategic 
Planning
Business Plan
Business 
Alliances
Access and Use 
of Information
2) Business 
Management
Economic 
Analysis
Economic and 
Financial 
Management
Administrative 
Management
Commercial 
Management
Human 
Resource 
Management 
and Gender
3) Technical 
Services
Access and 
Coverage
Partnerships 
for Innovatin 
in Service 
Delivery
Investment for 
the Provision 
of Services
Management 
for the 
provision of 
Services
Satisfaction 
with Technical 
Services
Skills 
development 
for Sustainable 
Production
Provisions of 
Operational 
Services
4) Financial 
Services
Financial 
Skills for 
Saving
Planning for the 
Provision of 
Financial Services
Partnerships for 
Financial Access
Management of 
Financial Services
Access and 
Coverage
Satisfaction with 
Service
5) Structure and 
Functionality
Legal Status
Organizatiional 
Chart and 
Functions
Rules and 
Regulations
Transparency 
and 
Accountability
Communicatio
n
Influence on 
Policies and 
Practices
6) Governance in 
Partnership 
Processes
Organizational 
Skills
Membership 
and 
Commitment
Organizational 
Practices
Resolution of 
Conflicts
28
areas for improvement and/or intervention; 3) business model principles for inclusive 
businesses, to determine whether each business that links rural producers with buyers is 
truly inclusive; and 4) the prototype cycle, which unites the three previous tools to 
undertake concrete strategies to expand what is already effective or to apply new 
innovations to promote the participation of smallholder farmers in the chain. These tools 
facilitate better understanding of the significant stakeholders, the processes and the 
relationships within a value chain. 
For the mid-term evaluation, as in the baseline, the evaluation team and CRS agreed to 
apply Tool #3. This exercise also will take place in the final evaluation. The idea is to get 
different perceptions and opinions, as well as, a better understanding of the context of the 
value chain for the mid-term. The rest of the tools are applied by each consortium partner 
throughout the life of the project.
4.2.3. Surveys on the Satisfaction and Perception of Beneficiaries 
The success of the program greatly depends upon the efficient and high-quality provision 
of technical, business and financial services to the producer families and the producer 
organizations. In this regard, the beneficiaries' perception on the quality of the services 
provided during the first stage by the consortium and implementing partners is addressed 
through a survey on satisfaction and perception of the program. This instrument has been 
developed by the evaluation team and constitutes a module of the mid-term survey. It 
covers the most-and least-liked aspects of the program and rating each of the major 
activities developed.
It is important to remark that results based on perception should be interpreted with 
caution. Although it may provide relevant information on the quality of the services, it can 
also show the degree of producers' understanding on the type and quality of services 
provided by the program. Also, we cannot rule out the possibility of measurement errors 
in data collection.
5. Sampling and Data
5.1. Sampling Strategy10
The information for the mid-term evaluation comes from a panel data that compiles the 
characteristics of producers and their families for two evaluation rounds (baseline and 
mid-term). The idea is to compare the outcomes of interest before and after the first stage 
 
10 This section is a reformulation of PROGRESA Caribe´s baseline report, section 5.1. Sampling
Strategy.
29
of the intervention. The sampling strategy has been designed to allow the collection of the 
necessary data to answer key evaluation questions and to analyze the effects of the 
intervention on intermediate and final outcomes.
For the baseline, it was calculated a representative sample of beneficiaries from the early 
and late treatment. The sampling strategy was designed to identify minimum impacts on 
cacao (metric tons per hectare) and milk (liters of milk per day) yields. It considered a 
confidence level of 95%, a statistical power of 80%, and the intra-cluster correlation of the 
adjacent communities. The sample size and power was computed using the noncentral t￾distribution.
The results suggested a representative sample of 980 observations (490 for each treatment 
status). Assuming a rate of non-response (attrition) of slightly more than 20% the total 
planned sample was of 1,210 producers (605 for each treatment status). The sample design 
used as a framework the list of project participants. The selection of the sample took place 
at one stage and was based on simple random sampling. Also, a random sample of a 14% 
of replacements was estimated, which was distributed proportionally to each 
implementing partner.
5.2. Data Collection
5.2.1. The Process
The data collection for the mid-term evaluation was shared responsibility of the 
consortium and implementing partners (through the zone supervisors and the 
enumerators11). The process was supervised by the CRS MEAL team.
CRS developed the instruments to be used in collection of the information from the 
producer families. The evaluation team and CRS MEAL team jointly revised this 
instrument to ensure that the questions would include all the elements necessary to 
conduct the evaluation, both those related to the key indicators (intermediate and outcome 
indicators), as well as the impact mechanisms. The CRS MEAL team suggested
adjustments be made to the survey. The evaluation team revised the adjustments in order 
to guarantee compatibility with the baseline study.
The preparation for the field work included training workshops, preparation of a users’ 
guide, pilot trials, and the creation of route sheets for collection of the information. In 
addition, the CRS team prepared a protocol for systemic review in order to filter data. This 
 
11 The enumerators are the same people who work as field technicians in the framework of the 
program.
30
makes it possible to reduce measurement errors and to assure quality in the management 
of the information. 
The following databases were obtained from the household survey:
1. Progress out of Poverty Index (PPI)
2. Food security
3. Agriculture: production of cacao
4. Agriculture: sales of cacao
5. Cattle production
6. Cattle inventory
7. Vaccination
8. Cattle sales
9. Infrastructure
10. Credit
11. Employment
12. Socio-demographic information
13. Financial education
14. Perception about the program
5.2.2. Assessment of the Data Quality12
The evaluation team and the CRS MEAL team agree that, during the process of field data 
collection, the same procedures were applied for both the early treatment and late 
treatment groups. The digital survey system makes the standardized application of the 
survey possible. This, together with the protocol for systematic review for data cleansing 
(prepared by CRS), minimized measurement errors.
The quality of the data for the mid-term evaluation is much better than the baseline data. 
This suggests that the consortium partners put into practice the recommendations and 
lessons learned from the baseline. Specifically, it improved the information gathering 
process in the sections on sociodemographic characteristics, infrastructure and livestock 
inventory, italso, improved the use of filters in the marketing section13. As expected, the 
quantity of information in the different sections of the survey is slightly different for all 
full interviews.
 
12 The evaluation team did not provide direct supervision of the field work; therefore, it only 
addresses those details regarding data quality that could be seen from the desk, in the visits to CRS 
in Estelí, and in the discussions with the consortium and implementing partners.
13 In the baseline, the questions on marketing were applied to all producers irrespective of whether 
they were selling or not.
31
A very important aspect of data quality is the process of building and harmonizing the 
data base. Once the field data had been collected and prior to the delivery of the data base 
to the evaluation team, the CRS MEAL team conducted two exhaustive reviews of the 
information collected and requested clarifications and revisions from the consortium 
partners’ and the implementing partners’ monitoring teams. After this process, the 
evaluation team received the data set in Excel and proceeded as follows:
- The evaluation team reviewed the initial database. 
- The evaluation team prepared a log of doubts to send to the CRS MEAL team.
- The doubts were reviewed jointly with the CRS MEAL team, which then requested the 
partners to clarify and revise the indicators under discussion.
- CRS harmonized the clarifications and revisions and presented details of each 
modification to the evaluation team.
- The evaluation team reviewed the harmonization and expressed it agreement or 
disagreement with each instance.
- In cases of disagreement, joint decisions were made regarding the changes to be made 
(or not).
- The process was repeated as new doubts arose.
This process was exhaustive and time-consuming during the evaluation period, but it was
conducted this way to ensure the lowest possible data loss, to reduce measurement errors 
and atypical values in the information, and to ensure transparency in the database￾building process.
Although the available information is of very good quality, there are considerable 
differences among the consortium partners, the implementing partners and even the field 
technicians themselves in the ability to conduct the survey. In this regard, it could be 
thought that the training process for conducting the survey did not have the same impact 
upon all the field technicians. However, the evaluation team considers that the differences 
in capacity are due to two factors: 1) the field technicians’ educational attainment, given 
that many of them have empirical knowledge and have had limited previous exposure to 
the use of digital tools; and 2) the turnover of field technicians among some partners has 
led to a loss of the knowledge that had been gained in the baseline study.
This led to twice as many revisions being made in this evaluation, as compared to the 
baseline, to ensure the quality of the final data that would be analyzed. The evaluation 
team suggests improving the hiring process of the field technicians. For example, CRS 
should prepare an exam for each applicant; the exam can be divided in three parts: 
technical skills, soft skills and critical thinking. Also, training for data collection should 
also focuson on the field technicians exercising greater “critical thinking” during the 
survey.
32
There are other constraints that should be addressed in the future, which are mentioned 
below:
- Information was collected for – a few – producers whose identifiers did not match the 
master for the evaluation sample. These were eliminated from the final sample. 
- The database modules imported from the system contained duplicate information from 
the producers, which implied case-by-case review to ensure that the information was 
correct.
- The consortium partners decided to conduct the mid-term survey using an evaluation 
period (6 months) that was different from that of the baseline (1 year). CRS explained 
that they did not have sufficient technical staff to carry out two simultaneous or near￾term surveys. However, this measure required statistical adjustments, which could lead 
to bias in the information collected (e.g., annualized sales, the reconciliation of 
agricultural practices).
- The indicator of value of production in dollars (cattle or cacao) by hectare at mid-term 
can be constructed based on an annualized variable (income) without a statistical 
adjustment (hectares). However, this would lead to a bias in the comparative results 
between baseline and mid-term, as the baseline data is constructed using an evaluation 
period of 1 year and the mid-term data using a period of 6 months. A potential solution 
is to anualized the hectares, but there is no confident criterion to apply this adjustment. 
Therefore, the evaluation team will not analyze this indicator in this evaluation, and 
suggest resuming the analysis of this indicator at the final evaluation.
- The consortium partners made a modification to the format of data collection of the 
pasture areas for livestock. Basically, instead of raising information for 4 types of 
pasture areas, they extended the disaggregation to 6 types. The evaluation team 
considers that this caused some misunderstanding among those producers surveyed, 
which led to harmonizations from the desktop that could have some degree of bias.
- The variable of average cattle weight is measured based on the producer's perception. 
The evaluation team considers that this variable may have a bias, although uncertain in 
wether the producer´s perception in estimating the weight of cattle would be higher or 
lower than the true weight. Nevertheless, the data on number of animals and their 
mean weight in kilograms is collected by sex, age class and predominant breed. This 
disaggregation might reduce to some extent the potential measurement error.
5.2.3. Data Collected
In the baseline, the sample was planned for 1,210 producers; information was collected for 
945 producers (78% of the planned sample). These 945 producers constituted the planned 
mid-term evaluation sample to be used for building panel data from both time periods. 
33
The section from Progress Out of Poverty (PPI)14
 was used as the basis for determining the 
final sample. Information was collected for 740 producer families (78% of the planned 
sample). CRS reported that the 205 producers who were not interviewed had left the 
program. The next section will discuss the causes for attrition from the evaluation sample.
To estimate the number of complete interviews, it was determined that survey should 
have information on PPI and the inventory of livestock or the area of cacao in 
development or production15
. Taking this into account, a total of 735 complete interviews 
were obtained, and when the mid-term data was harmonized with the baseline, 36 
observations were lost16
. A total of 699 complete interviews were obtained (74% of the 
planned sample), of which 414 (59%) correspond to early treatment and 285 (41%) to late 
treatment.
The non-response rate, which corresponds to the percentage of non-responses17 in 
comparison with the programmed sample, is 26% (246 observations). This is 4 percentage 
points greater than the baseline. The construction process for the final sample is shown in 
the following table.
 
14 This criterion was established in the baseline because PPI is the program’s most important long￾term indicator, and because it is the section with the greatest number of interviewees.
15 When the producer works in only one value chain, the information required comes from the PPI 
and the production and sales in the respective chain.
16 This occurs because for some of the previously described indicators, there are no baseline 
observations for some of the producers and vice-versa (no mid-term observations), which causes a 
slight loss of information.
17 The nonresponse is the sum of the non-interviewed plus the incomplete interviews plus the loss 
due to baseline harmonization.
34
Table 3. Evaluation survey: final sample and nonresponse
Furthermore, during the process of constructing the panel data, the evaluation team 
identified that the information predicted for each value chain changed because the value 
chains were updated for 105 producers. A similar situation arose with the baseline, which 
reconfirms that there were shortcomings in the program’s targeting process. More 
importantly, this affects the “power” to make the impact estimates and causes the 
extrapolations to become approximations with some degree of imprecision.
Table 4. Change of value chain
Baseline Mid-Term
(1) Target Sample 1210 945
(2) Initial target sample 1040 945
(3) Efective Sample 922 740
(4) Replacements 165 -
(5) Use of replacement 104 -
(6) Sample identified by TNS 172 -
(7) Not interviewed 12 205
(8) = (3) + (5) + (6) Final Sample 1198 740
(9) Incomplete Interviews 253 5
(10) Lost due to harmonization with baseline - 36
(11) = (7) + (9) + (10) Nonresponse 265 246
Nonresponse rate 22% 26%
(12) = (8) - (9) - (10) Completed Interviews 945 699
(13) Early treatment 534 414
Percent intervention 57% 59%
(14) Late treatment 411 285
Percent intervention 43% 41%
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe.
Both Cocoa Catlle Total
Both 64 1 4 69
Cocoa 14 312 0 326
Cattle 83 3 218 304
Total 161 316 222 699
Source: Evaluation team calculations based on mid-term survey - PROGRESA Caribe.
Baseline
Mid-Term
35
5.2.4. Attrition
One advantage of the randomized order of phase-in is that makes it possible for the 
researchers and those responsible for program monitoring and evaluation to have greater 
contact with the beneficiaries, which helps reduce potential attrition of the evaluation 
sample. A potential disadvantage is that the late treatment may be affected by future 
treatment expectation (Winters et al., 2010). For example, farmers may delay some 
activities that they normally would have undertaken if they were not part of the project 
(e.g., seeking technical assistance and access to external markets). In addition, it is possible 
that producers for late treatment become beneficiaries from other projects, which would 
seriously affect the comparison in the mid-term evaluation.
That said, as mentioned earlier, CRS reported that the 205 producers who were not 
interviewed had abandoned the program. All partners in the consortium had dropouts 
from the evaluation sample for both early and late treatment. However, the most affected 
was CRS, specifically for late treatment, where it collected only 44.5% of the planned 
sample.
Table 5. Mid-term´s evaluation survey response
The evaluation team asked the CRS MEAL team to document the causes for attrition in the 
evaluation sample. The causes of desertion were documented for 167 producers. The 
reasons were varied, but the main causes were: a) loss of interest, b) migration to other 
areas of the country or abroad, c) change of economic activity18, d) distance and insecurity, 
e) deaths, or f) initiation of work by the NICADAPTA project. The following table presents 
the causes for attrition in the evaluation sample.
 
18 These farmers decided to not grow cacao or raise livestock and instead focus on growing other 
agricultural products or work outside the farm.
Early 
Treatment
Late 
Treatment
Total
Early 
Treatment
Late 
Treatment
Total
Early 
Treatment
Late 
Treatment
Total
CRS 166 128 294 112 57 169 67.5% 44.5% 57.5%
56.5% 43.5% 100.0% 66.3% 33.7% 100.0%
LWR 135 152 287 109 123 232 80.7% 80.9% 80.8%
47.0% 53.0% 100.0% 47.0% 53.0% 100.0%
TNS 233 131 364 193 105 298 82.8% 80.2% 81.9%
64.0% 36.0% 100.0% 64.8% 35.2% 100.0%
Total 534 411 945 414 285 699 77.5% 69.3% 74.0%
56.5% 43.5% 100.0% 59.2% 40.8% 100.0%
Source: Evaluation team calculations based on baseline and mid-term (panel data) household survey - PROGRESA Caribe.
Scheduled Sample Complete Interview Fullfillment 
Partner
36
Table 6. Causes of evaluation sample´s attrition (number of producers)
Box 2. NICADAPTA
“Adapting to Markets and Climate Change Project in Nicaragua - NICADAPTA” is executed by the 
Ministry of Family, Community, Cooperative and Associative Economy (MEFCCA, by its spanish 
acronym), with financing from the International Fund for Agricultural Development (FIDA) and 
the Central American Bank for Economic Integration (BCIE, by its spanish acronyms).
This project is being implemented in areas such as Nueva Segovia, Madriz, Estelí, Jinotega, 
Matagalpa, Boaco, Río San Juan, RACCS and RACCN. The project targets approximately 40,000 
small-scale producers who own coffee or cacao plantations. The duration of the project is from 
2014-2020.
NICADAPTA aims to contribute to the improvement of rural families´ living conditions by 
assisting them in their production process and making it more complex (value added). The specific 
objectives of the project are: 1) strengthen the capacity of organizations to improve productivity and 
quality of coffee and cacao through improved business and productive management; 2) incorporate 
investments and management practices that allow to improve the quality of raw material produced 
by reducing the impact on the environment, 3) increase the production of coffee and cacao
plantations managed by the small producers and the community, and 4) incorporate good 
management practices and investment decisions that improve adaptation to climate change, 
including improved water management efficiency and reduced soil loss.
The project works to accomplish these objectives through the following main activities. Firstly, 
facilitating access to markets for value added coffee and cacao, introducing crop diversification. 
Second, by communicating to the participant of the program agro-climatic information. Third, 
improving the capacity of producer organizations through their training. Lastly, collaborating with 
the government, cooperation agencies, and private sector to promote and strengthen the coffee and 
cacao industries.
Source: IFAD (2013). “Adapting to markets and climate change project in Nicaragua (NICADAPTA)”, International Fund for 
Agricultural Development; MEFCCA (2016). “TDR, Proyecto NICADAPTA”, Ministerio de Economía Familiar Comunitaria, 
Cooperativa y Asociativa.
CRS LWR TNS Total
Change of economic activity 7 16 9 32
Distance and insecurity 21 0 0 21
MEFCCA 30 0 0 30
Passed away 2 1 6 9
Migration 15 0 14 29
Not interest ed in the project 35 10 1 46
Total 110 27 30 167
Source: CRS Data
Partner Attrition cause
37
Regarding the distribution of the attrition by intervention area, for both early and late 
treatment, Siuna, Rosita and Waslala are the municipalities with the highest number of 
producers who left the evaluation sample.
Figure 8. Distribution of the attrition by intervention area
When high attrition rates are identified, it is important to examine the potential differences 
in observable characteristics between producers who left the program and those who 
stayed. Next, univariate tests are presented for different baseline indicators between the 
deserter group and those remaining in the evaluation sample, separating the results by 
chain and by assignment to treatment (early and late). Subsequently, there is a discussion 
of the results of probabilistic models of baseline characteristics, which are also separated 
by chain and the allocation to treatment.
The following tables present the results of the mean differences between the group of 
producers who left and those who remained in the evaluation sample. As for the 
socioeconomic well-being indicators, those producers who remain in the program turn out 
to be less poor and to have greater diversity in their diet. 
Table 7. Two-sample mean-comparison tests (univariate analysis) - General
Change of the value chain
Distance and insecurity
MEFCCA
Passed away
Migration
Not interested in the 
project
Attrition Complier Difference Attrition Complier Difference Attrition Complier Difference
PPI (%) 56.424 61.718 5.2941** 49.279 59.666 10.3865*** 62.558 64.728 2.171
HDDS 6.472 6.979 0.5080*** 7.103 7.073 -0.031 5.953 6.848 0.8952***
MAHFP (months) 11.228 11.133 -0.095 11.230 11.175 -0.054 11.226 11.074 -0.152
Source: Evaluation team calculations based on baseline - PROGRESA Caribe.
Total Early treatment Late treatment
Notes: 
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
* Significant at the 10 percent level.
38
For livestock producers, the only difference between those who stayed compared to those 
who left were among those assigned to late treatment. Those who remain have, on 
average, higher gross income and more pasture areas, improved pasture, livestock and 
cows in production.
Table 8. Two-sample mean-comparison tests (univariate analysis) - Cattle
For cacao producers, just as with livestock, the main differences are observed among those 
assigned to late treatment. Those who remain in the program have on average better 
baseline results than those who left. 
Table 9. Two-sample mean-comparison tests (univariate analysis) - Cacao
On the other hand, in the livestock chain, when controlled by a set of socioeconomic and 
productive variables19
, it can be observed that for late treatment producers there are 
differences between those who remained and those who abandoned the program. 
Specifically, the probabilities of remaining in the program are reduced for those producers 
with a higher proportion of pasture out of the total farm area, a larger farm size, and a 
 
19 Probabilistic models of the baseline characteristics.
Attrition Complier Difference Attrition Complier Difference Attrition Complier Difference
Gross income - cattle ($) 5121.61 9562.85 0.3525*** 6559.24 8349.94 0.02 3846.73 11751.77 0.7116***
Milk yields (liters of milk per cow per day) 2.80 2.61 -0.05 2.83 2.50 -0.07 2.78 2.80 -0.01
Total farm area (mzn) 63.94 77.10 0.15 65.89 75.16 0.12 62.38 80.58 0.20
Pasture area (mzn) 45.58 62.56 0.2803*** 52.81 60.52 0.10 39.83 66.18 0.4321***
Total livestock (number of heads) 43.20 52.92 0.2929** 55.26 48.90 -0.05 33.59 60.07 0.6052***
Cows in production (number of heads) 17.81 20.83 0.1952* 22.36 19.22 -0.02 13.80 23.68 0.4127***
Average cattle weight per hectare (kg/ ha) 364.13 378.22 0.03 395.39 373.00 -0.14 339.23 387.53 0.18
Improved pasture (% of producers) 0.52 0.60 0.0821** 0.62 0.64 0.02 0.44 0.53 0.0944*
Gross margin - Cattle (%) -51.13 -38.28 12.86 -39.13 -37.31 1.82 -61.78 -40.02 21.7579*
Source: Evaluation team calculations based on baseline - PROGRESA Caribe.
Total Early treatment Late treatment
Notes: 
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
* Significant at the 10 percent level.
Attrition Complier Difference Attrition Complier Difference Attrition Complier Difference
Gross income - cacao ($) 508.43 855.45 0.2703* 524.89 774.38 0.27 496.22 960.09 0.3263*
Amount harvested (qq) 15.04 21.80 0.1961* 14.88 20.15 0.18 15.16 23.94 0.2505*
Cacao in pulp yields per hectare (tm/ ha) 0.59 0.77 0.0830*** 0.62 0.78 0.07 0.56 0.77 0.0881**
Dry cacao yields per hectare (tm/ ha) 0.20 0.26 0.0428*** 0.21 0.26 0.0369* 0.19 0.26 0.0464***
Total area of cacao (mzn) 2.17 2.57 0.0897* 2.11 2.33 0.07 2.21 2.88 0.1412**
Amount of sales in dry cacao (qq) 14.72 21.48 0.1936* 14.57 19.78 0.18 14.84 23.67 0.2536*
Value of production per hectare ($/ ha) 444.52 621.58 0.2248* 503.29 627.97 0.23 400.92 613.33 0.22
Application of sustainable agricultural practices (%) 0.00 0.04 0.0355*** 0.00 0.05 0.0495*** 0.00 0.02 0.0174*
Proportion of area in production (%) 0.86 0.80 -0.0581** 0.85 0.80 -0.05 0.86 0.79 -0.0690**
Gross margin (%) -177.86 -249.25 -71.39 -172.63 -297.35 -124.73 -181.65 -187.36 -5.70
Source: Evaluation team calculations based on baseline - PROGRESA Caribe.
Total Early treatment Late treatment
Notes: 
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
* Significant at the 10 percent level.
39
greater average weight of cattle per hectare. By contrast, greater dietary diversity and a 
larger herd increase the probabilities of remaining in the program. In turn, belonging to a 
cooperative reduces the probabilities of remaining in the program.
Table 10. Probability of attrition (marginal effects) - Cattle
In contrast, in cacao differences can be observed in both early and late treatment. Greater 
dietary diversity, greater area of cacao planted, and higher production yields increase the 
probabilities of remaining in the program.
Table 11. Probability of attrition (marginal effects) - Cacao
From all the above discussion, the evaluation team concludes that the observed attrition 
correlates with treatment allocation. In the late treatment "the best ones remained", that is 
Early 
Treatment
Late 
Treatment
General
Water supply all year round (yes=1) 0.052 -0.061 0.031
Area of pasture as proportion of farm (%) -0.039 -1.030*** -0.278
Improved pasture area as a proportion of total 
pasture area (%)
0.026 -0.130 0.034
PPI (%) 0.044* 0.008 0.041*
Total area of the farm (mzn) 0.028 -0.562*** -0.146
Non-agricultural income ($) -0.002 -0.043 -0.013
HDDS 0.021 0.500*** 0.248***
Total livestock (number of heads) -0.017 0.709*** 0.186*
Average cattle weight per hectare (kg/ ha) -0.040 -0.520*** -0.166*
Milk yields (liters of milk per cow per day) -0.110 0.183 -0.018
Belongs to a cooperative (%) -0.021 -0.376*** -0.136**
Source: Evaluation team calculations based on baseline - PROGRESA Caribe.
Notes: 
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
* Significant at the 10 percent level.
Early 
Treatment
Late 
Treatment
General
Proportion of area in production (%) 0.099 0.099 0.018
PPI (%) 0.000 0.000 0.028
HDDS 0.302*** 0.302*** 0.209***
Amount harvested (qq) -0.193 -0.192* -0.113*
Total area of cacao (mzn) 0.341* 0.341** 0.175**
Cacao in pulp yields per hectare (tm/ ha) 0.711** 0.711** 0.437***
Belongs to a cooperative (%) 0.030 0.030 0.043
Source: Evaluation team calculations based on baseline - PROGRESA Caribe.
Notes: 
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
* Significant at the 10 percent level.
40
to say, those producers with the best productive performances and lower probability of 
poverty. The implications of this issue are addressed in the next section.
6. Validation of the Evaluation Design
In the previous section it was verified that although the causes of attrition were mostly 
exogenous to the management of PROGRESA Caribe, there is a degree of correlation 
between attrition and treatment allocation. In the late treatment group, the producers with 
the best productive performances remained in the evaluation sample.
In this regard, when recalculating the baseline indicators with the sample of producers for 
the mid-term panel data, it is found that the indicators differ considerably. Thus, to avoid 
bias in time comparisons, the evaluation team recommends that the new baseline data be 
used for analysis.
The table below reports the average of the indicators for the late treatment sample, as well 
as the difference between early and late treatment.
Table 12. Re-estimation of baseline differences between early treatment and late treatment at program level
Late 
treatment mean
Early 
treatment - 
Late 
treatment 
difference
p￾value Observation
Late 
treatment mean
Early 
treatment￾Late 
treatment 
difference
p - 
value Observations
Progress out of Poverty Index (PPI) - general 64.13 -6.35 0.145 945 64.42 -5.27 0.305 699
Progress out of Poverty Index (PPI) - extreme 25.26 -5.40 0.130 945 25.73 -5.19 0.180 699
MAHFP (months) 11.13 0.02 0.985 923 11.07 0.10 0.735 680
HDDS 6.57 0.46 0.115 923 6.85 0.23 0.470 680
Percentage of families with insufficient food 0.31 0.04 0.670 923 0.34 0.00 1.000 680
Total sales (dollars) 4,714.77 -64.45 0.995 900 5,765.91 -767.52 0.735 670
Cocoa sales (dollars) 850.62 -79.90 0.655 527 959.07 -185.48 0.450 391
Livestock sales (dollars) 9,668.53 -1800.00 0.705 442 12,300.00 -3820.00 0.460 328
Milk yields (lts of milk per cow per day) 2.76 -0.17 0.475 468 2.80 -0.30 0.305 349
Average cattle weight per hectare (kg / ha) 365.76 7.73 0.870 503 387.53 -14.53 0.825 370
Gross Income - cattle (dollars) 9,232.88 -1470.00 0.635 485 11,800.00 -3400.00 0.485 359
Value of production per hectare - cattle 174.56 21.74 0.395 440 213.12 1.72 1.000 359
Gross margin per unit of land - cattle (%) -44.44 5.87 0.605 485 -40.02 2.71 0.855 359
Dry cocoa yields (tm/ ha) 0.23 0.02 0.610 532 0.26 0.00 0.910 394
Hectares of cocoa in production (ha) 1.45 -0.21 0.135 533 1.52 -0.27 0.065 394
Hectares of cocoa in develpment (ha) 0.93 -0.11 0.270 241 0.96 -0.10 0.435 192
Gross income - cocoa (dólares) 858.15 -84.12 0.605 532 965.71 -184.29 0.450 391
Value of production per hectare- cocoa (dollars / ha) 565.04 71.50 0.670 527 616.91 16.77 0.810 391
Gross margin per unit of land - cocoa (%) -208.45 -52.86 0.650 532 -187.36 -110.00 0.510 391
Source: Evaluation team calculations based on baseline- PROGRESA Caribe.
Indicator
Baseline 2015 New baseline (Producers that remained in the 
project)
Notes: The table reports the difference in each variable between the early treatment and late treatment groups. Inference is adjusted by wild 
cluster bootstrap standard errors. Penultimate column reports the p-value of tests of differences for each variable.
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
* Significant at the 10 percent level.
41
The results suggest that there are no statistically significant differences between the 
characteristics of the early and late treatment group. This apparent "balance" in most 
sociodemographic and production indicators does not imply that there have been no
exogenous flaws in randomization. Rather, it may be revealing an issue with the statistical
power required to identify statistical differences between groups. In the baseline report, 
the evaluation team explained the potential presence of this problem, should a large 
amount of evaluation sample be lost.
Although the level of attrition affected the randomization and the statistical power, having 
a baseline and a follow-up survey (panel data) gives greater statistical power compared to 
a cross-section data, which mitigates power losses to some extent, even though the final 
sample is smaller.
Therefore, in order not to affect the internal validity of the evaluation, as explained in 
previous sections, two types of statistical analysis will be carried out: 1) Difference-in￾differences and 2) Matching estimators combined with difference-in-differences. The 
inference will control by baseline covariables that are associated with outcome indicators, 
either as regressors in the difference-in-differences estimator or as variables to determine 
the probability of selection in the program for the case of the difference-in-difference 
estimator combined with matching methods.
7. Impact of the Program on the Beneficiaries and Key Stakeholders
7.1. Impact of the Program on the Producer Families
7.1.1. Introduction
PROGRESA Caribe was designed under an experimental scheme in which more than 50% 
of the beneficiary producers were assisted from the beginning of the project (once the 
baseline was conducted, October 2015) and another part began to be assisted as of month 
19 of activity implementation (randomized order of phase-in).
This section discusses the comparison before (baseline) - after (mid-term) to analyze the 
evolution of key indicators at the end of the first stage of the program and the impact of 
the program on outcome indicators at mid-term. The idea is to obtain inputs on the 
services provided by the program and to infer the association between the program and 
the producers’ results.
As mentioned in sections 5 and 6, all consortium partners had dropouts from the 
evaluation sample for both early and late treatment. This implied the loss of statistical 
42
power to analyze the results separated by consortium partner. For example, CRS does not 
have enough statistical power to analyze separately its results for cacao and cattle, while 
TNS does not have enough statistical power to analyze its results for the cacao chain, but it 
has enough statistical power for the cattle chain. LWR has enough statistical power to 
analyze its results for the cacao chain. Therefore, the analysis addresses the intermediate 
and outcome indicators at project level, rather than on a partner level.
7.1.2. Characteristics of the Producers
At mid-term, information is available for 699 producers, of whom 414 (59.2%) correspond 
to early treatment and 285 to late treatment (40.8%). Women make up 14.5% of the sample; 
this proportion is quite similar for both treatment groups.
In terms of geographical distribution, 42.6% of the surveyed producers reside in RACCS, 
42.2% in RACCN, and 15.6% in Río San Juan. There is a relatively greater participation of 
RACCS producers in early treatment, whereas in late treatment the largest proportion of 
producers is located in RACCN.
TNS assists 42.6% of the evaluation sample, followed by LWR (33.2%) and CRS (24.2%). 
TNS and CRS have a higher proportion of early treatment producers (64%-66%); in the 
case of CRS, as was explained in previous sections, this is due to a greater attrition of 
producers in its late treatment sample.
39
47
15
47
37
16
42 43
15
0
5
10
15
20
25
30
35
40
45
50
RACCN RACCS Río San Juan
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe. 
Early Treatment Late Treatment Total
Graph 1. Geographical distribution of the evaluation sample 
Percentage of producers
43
By chain, 45.2% of the producers surveyed work only with cacao under the program, 
followed by those working with the livestock chain (31.8%) and those served in both 
chains (23.0%).
The 12.9% of the evaluation sample corresponds to producers who have previously 
participated in other projects carried out by the consortium partners. CRS is the partner 
that assists the highest proportion (31.4%) of “repeaters” among surveyed producers.
Table 13. Distribution of the evaluation sample by 
repeaters and new beneficiaries (%)
The average household size is 4.71 persons, and 19.2% of the respondents live in 
households of 7 or more persons. More persons per household are associated with a 
greater likelihood of poverty, suggesting that the program targeting is relatively good.
27 26
47
20
43
37
24
33
43
0
5
10
15
20
25
30
35
40
45
50
CRS LWR TNS
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe. 
Early Treatment Late Treatment Total
Graph 2. Distribution of the evaluation sample by consortium partner
Percentage of producers Partners Beneficiaries for the 
first time
Repeaters
CRS 68.6 31.4
LWR 87.9 12.1
TNS 97.0 3.0
Total 87.12 12.88
Source: Evaluation team calculations based on 
baseline and mid-term survey (panel data) - 
PROGRESA Caribe.
44
The average age of the heads of households surveyed is 46.4 years, and little more than a 
third of the sampled producers are under 40 years old (12.2% are under 30). Their average 
schooling level is 3.6 years. In spite of this, the heads of household have almost 20 years of 
experience working in agricultural production. On average, 2.2 family members are 
working on the farm.
7.1.3. Productive Practices of the Early Treatment20 21
The application of agricultural practices reflects the knowledge, skills and abilities that the 
farm families acquire either on their own or by the effect of the intervention. The 
 
20 As was mentioned in previous sections, the mid-term survey applied an evaluation period of 6 
months. The consortium partners indicated that many of the practices evaluated could have a 
downward bias due to the periodicity, as some practices are carried out only once a year. 
Considering this issue, the evaluation team and the consortium member monitoring teams decided 
to evaluate the practices by unifying the data from the last monitoring campaign with the mid-term 
evaluation data. The evaluation team found that the application of this procedure revealed 
significant changes in the percentage of producers applying the different practices. However, this 
approach was only applied to the early treatment, as a constraint of this method is that it does not 
permit the reconstruction of the productive practices of late treatment, because the monitoring 
campaign does not cover this group.
21 The analysis of evolution in practice indicators is based on simple regressions of a given practice 
as a function of a binary variable that takes the value of 1 if the observation corresponds to the mid￾term round. Hence, the discussion of changes (increases, reductions) in the proportion of producers 
applying the different practices is based on "statistically significant" changes.
4.2
5.2 5.2
5.0
4.7
4.4
4.9
4.7
0.0
1.0
2.0
3.0
4.0
5.0
6.0
CRS LWR TNS Total
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe. 
Baseline Mid-Term
Graph 3. Average household size
Number of persons
45
application of these practices reflects the human capital of the producers. This is discussed 
below for each chain.
Cattle
The deworming and vaccination of cattle are the most relevant sanitary practices carried 
out by the farmers of the early treatment group. At mid-term, there are no relevant 
changes in this type of practice. In other words, the proportion of producers applying this 
type of practice has remained relatively constant.
As far as livestock management practices are concerned, the main ones are cattle 
dehorning and the rotation of pastures. There is a notable increase (10 percentage points or 
more) in the proportion of producers who perform these two practices. The percentage of 
producers who practice clean milking and cattle identification also increases. Along with 
pasture rotation, these two last practices are promoted under the program.
14
87
73
5
15
90
72
3
0
10
20
30
40
50
60
70
80
90
100
Mastitis Deworming Vaccination Tuberculosis
Source: Evaluation team calculations based on baseline, mid-term survey and CRS administrative records (monitoring 
campaign ) - PROGRESA Caribe 
Graph 4. Sanitary practices
Percentage of producers
Baseline Mid-Term
46
Livestock practices under improved management are determined by the application of 
three of the following practices: vitaminization, deworming, vaccination or rotation of 
pastures. In this respect, no statistically significant changes between mid-term and 
baseline are identified. At mid-term, the percentage of producers applying livestock 
practices under improved management is 81.2%. In the same way, the percentage of of 
producers applying sustainable agricultural practices did not change (in statistical terms) 
compared to the baseline. 90.8% of the producers were applying this practice at the mid￾term round.
The use of vitamins and mineral salts predominates in cattle feeding practices. Comparing 
with the baseline, there is a notable increase in the proportion of producers that use 
mineral salts (35.9 percentage points) and molasses (10 percentage points). At mid-term, 
the proportion of producers using molasses is 20%.
70
81
31
1
24
60
68
19
1
15
0 10 20 30 40 50 60 70 80 90
Dehorning
Rotation of pastures
Cattle identification
Artificial
insemination
Clean Milking
Source: Evaluation team calculations based on baseline, mid-term survey and CRS administrative records (monitoring 
campaign ) - PROGRESA Caribe 
Graph 5. Practices for livestock management 
Percentage of producers
Baseline Mid-Term
91
81
87
79
70 75 80 85 90 95
Sustainable agricultural practices
Improved Management
Source: Evaluation team calculations based on baseline, mid-term survey and CRS administrative records (monitoring 
campaign ) - PROGRESA Caribe 
Graph 6. Improved and sustainable practices Percentage of producers
Baseline Mid-Term
47
Farm management practices are one of the activities that the program emphasizes the 
most. As compared with baseline, there are substantial increases in the percentage of 
producers that make expenditure, savings or investment budgets, who manage debt, 
record sales, keep track of livestock inventory, and keep records of costs and the 
production. In fact, at the baseline, the proportion of producers who carried out these 
practices was lower than 5% in almost all indicators and for mid-term almost all the 
proportions analyzed had doubled. This important progress is due to the effort made by 
the program in its initiative to develop farm plans. The comparison of farm management 
practices between early treatment and the late treatment producers who remained in the 
program shows that at baseline both groups had very similar adoption levels, and that the 
relative mid-term increase for early treatment is much greater (more than double) than 
that of late treatment.
52
3
20
0
2
10
0
0
97
16
3
10
1
4
13
0
2
98
0 10 20 30 40 50 60 70 80 90 100
Mineral Salts
Concentrate
Molasses
Multinutritional blocks
Prepared food on the farm
Cut and grass
Fodder
Silage
Vitaminization
Source: Evaluation team calculations based on baseline, mid-term survey and CRS administrative records 
(monitoring campaign ) - PROGRESA Caribe 
Graph 7. Feeding practices for cattle
Percentage of producers
Baseline Mid-Term
48
The evaluation team considers this result to be highly positive considering that only 18 
months of activities have passed and that the program is carried out in a context of low 
educational level among its beneficiaries. In fact, there is no statistically significant 
association between the educational attainment of the head of the household and the 
adoption of farm plans. However, it is noteworthy that there is a negative (statistically 
significant) association between the head of household’s years of experience and some of 
the farm management indicators.
The adoption of the plans depends more on the producer’s will or motivation for change 
(of culture) than directly on his/her previous knowledge. This does not rule out that this 
has been quite difficult for several producers with low educational levels. In this sense, the 
evaluation team suggests that the consortium partners make a qualitative evaluation of the 
difficulties faced by the producers in the implementation of the farm plans and 
alternatives to overcome them. One option might be to integrate the children - who are 
likely to have a higher educational level - into farm management activities. For example, in 
the financial education section, it was noticed (discussed below) that some producers keep 
records with the support of children.
This does not imply that there is no room for improvement in the adoption of farm 
management practices, but rather the opposite, since the indicator with the highest 
proportion of producers performing the practice (control of livestock inventory) is below
30%.
2.5
15.0
2.3 2.8
0.0
3.9
0.8
3.5
1.3
8.2
1.5
2.8
5.4
13.3
3.0
4.3
2.5
19.7
0.8
7.1
4.6
23.2
0.8
5.7
0.8
2.6
0.0 0.7
2.1
10.7
2.3
0.0
1.3 1.3
5.3
3.5
0.0
5.0
10.0
15.0
20.0
25.0
Baseline Mid-Term Baseline Mid-Term
Early treatment Late treatment
Source: Evaluation team calculations based on baseline, mid-term survey and CRS administrative records (monitoring 
campaign ) - PROGRESA Caribe.
Graph 8. Farm management practices - cattle 
Percentage of producers
Expenditure Savings Investment budgets
Debt Record sales Livestock inventory
BPP registration Record of cost and production BPA registration
49
Cacao
For cacao production, the program worked on: 1) crop genetics, 2) pest management, 
3) disease management, and 4) soil-related fertilization and conservation.
In terms of crop genetics, the elimination of buds is the most common practice among 
early treatment producers (93.9% at mid-term). Compared to baseline, there are positive 
and statistically significant changes in the proportion of producers practicing rehabilitative 
pruning and eliminating buds.
Pest management activities focused on maintenance pruning and integrated pest 
management (IPM). Consistent with the above, this last indicator experienced progress (in 
statistical terms) at mid-term (8.5 percentage points). Around 85% of producers continue 
to apply maintenance pruning. It is interesting to note that the percentage of producers 
that carried out weed control increased (96.8% in the medium term).
35
13
84
40
23
94
0
10
20
30
40
50
60
70
80
90
100
Crop genetic Pruning rehabilitation Elimination of buds
Graph 9. Crop genetic Percentage of producers Baseline Mid-Term
Source: Evaluation team calculations based on baseline, mid-term survey and CRS administrative records (monitoring campaign ) -PROGRESA Caribe.
50
For disease management, the application of broths (bordeaux mixture or bordo mix, which 
are IPM controls) and disease control was promoted. The former did not show relevant 
changes in the medium term, but there was a substantial increase in the proportion of 
producers who carry out disease control (almost 70% in the medium term).
The fertilization and soil conservation activities promoted under the program were: 
a) fertilization, b) soil and water conservation practices (OCSA, by its spanish acronym), 
c) incorporation of green manure, d) ground cover management, and e) organic foliar 
fertilization. At baseline, the proportion of producers applying these practices did not 
reach 30% in any indicator. At mid-term, there are no relevant changes in the producers 
who carry out this type of practice. The most common practices performed by the early 
treatment producers are fertilization (25.5%) and cover management (20.2%). These results 
16
81
88
25
86
97
0
10
20
30
40
50
60
70
80
90
100
Integrated pest management Maintance pruning Weed control
Graph 10. Pest management activities
Percentage of producers
Baseline Mid-Term
Source: Evaluation team calculations based on baseline, mid-term survey and CRS administrative records (monitoring campaign ) - PROGRESA Caribe.
5
69
4
47
0 20 40 60 80
Aplication of
broths
Disease control
Graph 11. Disease management
Percentage of producers
Baseline Mid-Term
Source: Evaluation team calculations based on baseline, mid-term survey and CRS administrative records (monitoring campaign ) - PROGRESA Caribe.
51
suggest that the consortium partners should make greater efforts to encourage the 
implementation of these practices among the beneficiaries of both the early and the late 
treatment.
As mentioned earlier, farm management practices are one of the most important activities 
promoted by the program. For cacao production, a substantial improvement is also 
identified in the proportion of producers that carry out different farm management 
practices. The most notable progress is in the management of expenditure budget, sales 
record, farm plan, and records of costs and production. As in the case of livestock, there is 
still ample room for improvement in the adoption of these practices. Also, as in the case of 
livestock, a comparison of farm management practices between early treatment and late 
treatment producers that remained in the program shows that the mid-term increase for 
the former is much greater.
26
5 5
27
9
11
1
26
4
6
20
7
11
4
0
5
10
15
20
25
30
Fertilization OCSA Incorporation
of green manures
Ground cover management
Organic foliar
fertilization
Foliar fertilizer Validation Plots
Graph 12. Fertilization and soil conservation activities
Percentage of producers
Baseline Mid-Term
Source: Evaluation team calculations based on baseline, mid-term survey and CRS administrative records (monitoring campaign ) - PROGRESA Caribe.
52
7.1.4. Infrastructure and Equipment22
The infrastructure, tools and equipment represent the physical assets held by the producer 
families. Regarding the infrastructure of the producers assisted in the cacao chain, there 
are no significant changes in the proportion of producers who have chainsaws and toolkits 
for cacao cultivation. In contrast, there is a striking reduction in the percentage of 
producers who possess fumigation pumps and agricultural tools. The late treatment group 
follows a similar trend, except in the possession of toolkits for cacao cultivation.
 
22 The infrastructure and equipment data base is broad. In this section, the analysis focuses on 
indicators selected by the evaluation team.
12
1
5 5
17
0
14
7
2
25
5
11
7
38
0
32
21
2
0
5
10
15
20
25
30
35
40
Expanditure Savings Investment
Budgets
Debt Record Sales Cash Flow Farm
Management
Record of
cost and
production
BPA Registration
Graph 13. Farm management practices - cacao
Percentage of producers
Baseline Mid-Term
Source: Evaluation team calculations based on baseline, mid-term survey and CRS administrative records (monitoring campaign ) - PROGRESA Caribe.
76
61
79
63
16
19
15 16
29
33
25
13
92
70
85
78
0
10
20
30
40
50
60
70
80
90
100
Baseline Mid-Term Baseline Mid-Term
Early Treatment Late Treatment
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe
Graph 14. Infrastructure and equipment - cacao Percentage of producers
Fumigation pumps Chainsaws Toolkits Agricultural tools
53
For the livestock chain producers, there are more notable increases in the percentage of 
producers who have milk jugs, water tanks, water troughs for livestock, corrals and 
milking parlors. No statistically significant changes in the possession of grass grinders 
were identified. In several of these indicators the growth trend in the early treatment 
group is relatively higher than that of the late treatment producers who remained in the 
program.
7.1.5. Social Capital and Assistance
The social capital of producer families is partly due to their link with local organizations 
and other development projects. A little over a third of the early treatment producers are 
enrolled in a cooperative. This proportion is higher for the late treatment group that 
remained in the program (45.6%). LWR is the partner with the highest proportion of 
producers belonging to cooperatives.
43
51
42
46
12
23
13 15
8
13
5
11 11 14
9
15
92
79
96
88
57
65
59
70
1
7
0
7
0
10
20
30
40
50
60
70
80
90
100
Baseline Mid-Term Baseline Mid-Term
Early Treatment Late Treatment
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe
Graph 15. Infrastructure and equipment - cattle 
Percentage of producers
Milk jugs Water tank Water troughs Pasture grinder
Agricultural tools Corrals Milking parlors
54
On the other hand, at mid-term it was found that nearly a third of the producers of early 
treatment report receiving some type of assistance from other organizations. This 
percentage is 21.9%. for the late treatment group that remained in the program. There is no 
single organization that serves all these producers.
Upon detailed examination of the type of technical assistance that beneficiaries report 
receiving, it was found that a good proportion benefited from government programs such 
as Zero Usury, Productive Bonus, Roof Plan, and School Shoes and Supplies. Others are 
served by the programs of local NGOs (e.g. IPADE, ADDAC) and international NGOs and 
by the MEFCCA program called NICADAPTA.
35
61
15
32
23
85
12
46
0
10
20
30
40
50
60
70
80
90
CRS LWR TNS Total
Graph 16. Enroll to a cooperative
Percentage of producers
Early Treatment Late Treatment
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe. 
45
36
13
28 29 28
11
22
0
5
10
15
20
25
30
35
40
45
50
CRS LWR TNS Total
Graph 17. Producers that received assistance from others 
organizations Percentage of producers Early Treatment Late Treatment
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe. 
55
In order to explore the potential contamination by the presence of these programs23
, the 
evaluation team made a brief documentary study and discussed the nature of these 
programs with the consortium partners. It was concluded that, by their nature and degree 
of coverage, most of these programs would not have a significant effect on the 
productivity of the beneficiaries compared to the effect that PROGRESA Caribe could have 
generated. In addition, there is no evidence that these organizations work on 
commercialization issues.
7.1.6. Productive Yields and Its Association with Agricultural Practices
Strategic Objective 1 of PROGRESA Caribe is to increase agricultural productivity. 
Activities to increase agricultural productivity are focused on training to improve 
agricultural production techniques and farm management, as well as fomenting farm-level 
financial and non-financial services that producers need to implement the best practices. 
The combination of practices discussed above, including those for which there was a 
higher degree of adoption and those for which there was not, allowed the following mid￾term average yields per producer24 to be achieved:
Table 14. Average yields per producer
The average milk yields for the early treatment group increased by 0.8 liters compared to 
the baseline, reaching an average of 3.2 liters per cow per day. This positive change is 
statistically significant. The average weight of live cattle also experienced major increases 
compared to the baseline, as the average weight in kilograms almost doubled.
In contrast, for the case of dry cacao production the average yield per producer for the 
early treatment group fell by 0.09 metric tons per hectare. The drop in yield is widespread 
in both the North Caribbean Coast and Río San Juan and for CRS and LWR. Detailed 
examination of the variations in cacao yields reveals that the areas in production remain 
constant (in statistical terms), while the amount harvested in metric tons dropped.
 
23 This potential effect is isolated in the impact estimates.
24 The indicators are calculated for producers who present performance data for both the baseline 
and the mid-term.
Baseline Mid-Term
Milk yields (lts of milk per cow per day) 2.39 3.20
Average cattle weight per hectare (kg/ ha) 382.10 615.11
Dry cacao yields (tm/ ha) 0.27 0.17
Source: Evaluation team calculations based on baseline and mid-term 
survey (panel data) - PROGRESA Caribe. 
56
Upon documenting the possible explanations for this drop, the evaluation team considers 
that it is due to low yields of newly planted and old cacao trees that have been replaced 
but that have yet reached their production potential; in addition, and in part to the 
negative effects of Hurricane Otto, which occurred in late November 2016. This hurricane 
affected parts of the Caribbean Coast and the entire area of Río San Juan.
This hypothesis acquires greater validity because, as discussed above, the proportion of 
producers who applied the different practices of cacao production promoted by the 
program increased or remained constant (in statistical terms).
In addition, the fact that cacao plantations in production are very young (10 years on 
average, and less for CRS and TNS) causes them to be more vulnerable to exogenous 
factors and also require more attention from producers.
By applying the difference-in-differences and the matching estimators combined with 
difference-in-differences, no statistically significant changes are found due to the 
intervention in any of the above discussed yields. The evaluation team considers that this 
result is expected as productive yields do not change so rapidly in just 18 months of 
intervention. In this regard, it is positive that livestock yields have grown over time. Also, 
for the cacao yields, the reduction was observed in both early treatment and (weighted) 
late treatment; this implies that negative exogenous factors played an important role 
during the first stage of the intervention.
For the three performance indicators discussed above, at the project level25 the results are 
qualitatively similar to the average per producer.26
Based on the mid-term yield levels and their change from the baseline, a cluster analysis27
was used to construct ranges of yields of the early treatment group for the three indicators 
discussed above.
 
25 The project-level indicator uses in its division the sum of the formula components of all of the 
producers under study. 
26 The comparison between these formulas does not necessarily produce similar results. 
27 The methodology used is based on the method of hierarchical conglomerates proposed by Ward 
(1963) and uses as an approximation measure the Euclidean distance squared.
57
Table 15. Categories of yields and agricultural practices – milk 
Table 16. Categories of yields and agricultural practices – average cattle weight
1 2 3 Average
Milk yields (lts of milk per cow per day) 3.2 8.9 1.5 3.2
Changes in Milk yields (lts of milk per cow per day) 1.2 6.3 -1.2 0.8
Mineral Salts 65.9% 43.8% 55.7% 59.5%
Concentrate 3.5% 6.3% 4.1% 4.0%
Molasses 20.0% 31.3% 22.7% 22.5%
Multinutritional blocks 1.2% 0.0% 0.0% 0.5%
Prepared food on the farm 1.2% 0.0% 4.1% 2.5%
Cut and grass 7.1% 12.5% 13.4% 10.5%
Fodder 0.0% 0.0% 0.0% 0.0%
Silage 0.0% 6.3% 0.0% 0.5%
Vitaminization 98.8% 100.0% 99.0% 99.0%
Deworming 89.4% 81.3% 95.9% 92.0%
Vaccination 72.9% 75.0% 79.6% 76.6%
Cattle identification 29.4% 43.8% 31.6% 32.3%
Rotation of pastures 91.8% 68.8% 85.7% 87.1%
Tuberculosis 4.7% 0.0% 4.1% 4.0%
Clean milking 29.4% 12.5% 20.4% 23.4%
Mastitis 14.1% 25.0% 14.3% 15.9%
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - 
PROGRESA Caribe.
58
Table 17. Categories of yields and agricultural practices – dry cacao
As the previous results show, there is no clear association between the categories of yields 
analyzed and the practices carried out by producers - which are promoted by the program.
1 2 3 Average
Average cattle weight (kg/ ha) 282.8 1432.5 4479.2 615.1
Changes in average cattle weight (kg/ ha) -82.3 909.7 4164.8 233.0
Mineral salts 48.9% 72.4% 71.4% 52.4%
Concentrate 3.7% 0.0% 14.3% 3.5%
Molasses 17.4% 34.5% 42.9% 20.3%
Multinutritional blocks 0.5% 0.0% 0.0% 0.4%
Prepared food on the farm 2.1% 3.4% 0.0% 2.2%
Cut and grass 9.5% 10.3% 14.3% 10.1%
Fodder 0.0% 0.0% 0.0% 0.0%
Silage 0.5% 0.0% 0.0% 0.4%
Vitaminization 98.4% 96.6% 85.7% 97.8%
Deworming 88.9% 100.0% 85.7% 90.3%
Vaccination 72.1% 86.2% 71.4% 73.6%
Cattle identification 31.1% 34.5% 42.9% 31.7%
Rotation of pastures 82.6% 86.2% 85.7% 82.8%
Tuberculosis 3.7% 3.4% 0.0% 3.5%
Clean milking 25.3% 20.7% 14.3% 24.2%
Mastitis 15.8% 13.8% 14.3% 15.4%
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - 
PROGRESA Caribe.
1 2 3 4 Average
Dry cacao yield (tm/ ha) 0.06 0.16 0.13 0.33 0.17
Changes in dry cacao yields (tm/ ha) -0.04 -0.19 -0.64 0.12 -0.10
Crop genetic 34.9% 54.1% 41.2% 54.0% 46.6%
Pruning rehabilitation 28.6% 23.0% 17.6% 26.0% 25.1%
Elimination of buds 98.4% 100.0% 94.1% 96.0% 97.9%
Integrated pest management 31.7% 36.1% 5.9% 16.0% 26.7%
Maintance pruning 90.5% 96.7% 88.2% 90.0% 92.1%
Aplication of broths 6.3% 6.6% 5.9% 4.0% 5.8%
Disease control 74.6% 86.9% 76.5% 78.0% 79.6%
Fertilization 41.3% 26.2% 5.9% 20.0% 27.7%
Incorporation of green manures 9.5% 6.6% 11.8% 6.0% 7.9%
OCSA 7.9% 4.9% 5.9% 0.0% 4.7%
Ground cover management 31.7% 23.0% 11.8% 20.0% 24.1%
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - 
PROGRESA Caribe.
59
The evaluation team considers that this result could be due to a weakness in the 
measurement of the performance indicator of practices. At the moment, this indicator only 
counts the practices that the producer considers to carrying out, without checking if it does 
or does not. In addition, it is important to incorporate two additional indicators: 1) the 
intensity on the application of the practice, measured as the number of months that the 
producer has applied the practice; and 2) an indicator of performance quality of the 
practice.
7.1.7. Commercialization of Production
Strategic Objective 2 of PROGRESA Caribe is the expansion of trade in agricultural 
products. Activities to expand trade are focus on increasing market access for smallholder 
producers through improving post-harvest handing and processing, training on
certifications and standards, and facilitating private and/or public partnerships for buying 
and selling, co-investment in infrastructure, and the exchange of market information. 
Complementary foundational activities include increasing the capacity of cooperatives 
and trade associations to serve their smallholder members. Furthermore, through the 
promotion of good agricultural practices, marketing is affected by the positive effects on 
yields and the improvement in production quality.
The average income from the sale of cacao28 in the case of early treatment grew by mid￾term due to a higher volume of average production. The average price per producer for 
dry cacao remained practically constant (from the statistical point of view).
In the case of livestock and milk sales, there are no statistically significant changes, even 
though the average prices of the liter of milk and of live cattle showed increases during the 
evaluation period. It should be noted that a reduction was identified in the average 
amount sold (kilograms) of standing cattle.
Table 18. Average sales, quantity sell and prices
On the other hand, at the project level29
, there is a 12.0% growth in the total value 
(income30) of cacao and livestock production of the early treatment group. This suggests 
 
28 The quantity sold is taken into account. Sales are multiplied by the unit price to obtain the value 
of sales, which corresponds to sales revenue.
Sales ($)
Quantity 
sell (lts)
Price ($) Sales ($)
Quantity 
sell (kg)
Price ($) Sales ($)
Quantity 
sell (tm)
Price ($) 
Baseline 4,251.5 15,130.6 0.26 8,135.9 4,341.1 1.80 773.6 0.30 2,379.2
Mid-term 4,801.9 16,952.2 0.28 6,315.4 2,246.2 2.80 1,098.9 0.50 2,374.9
Milk Cattle Dry cacao
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe. 
60
that low performances are offset by high performers, mainly of larger producers and in 
live cattle production. These results were determined by revenue growth in both value 
chains. In relative terms, the increase in income was greater for cacao (66.4%).
The increase in income at the project level was due to a positive (relative) change in the 
production volumes of all items (mainly cacao) and increases in the prices of liter of milk 
and livestock. 
By applying the matching estimators combined with difference-in-differences, no 
statistically significant changes are found, at the mid-term, due to the intervention, in total 
income (value of production) and total cost. However, by chain, there is an increase in 
cacao income due to the intervention compared with the evolution of the late treatment in 
around 40 percentages points. This positive change in cacao income is accompanied with 
an increase in cacao cost (more than 40 percentages points). The evaluation team considers 
that this increase in the production costs is reasonable because: 1) cacao producers are 
relatively new in the value chain and therefore are learning from the project to improve 
their production cost records, which makes the information more truthful; and 2) the 
producers have invested in new productive technologies that naturally push up the 
production costs.
 
29 In its formula, the project-level indicator uses the sum of the income of all the producers under 
study. This indicator is extrapolated to the universe of early treatment. 
30 The entire production is taken into account – that which is sold, that which is used as seed, and 
that which is consumed by the household.
2
13
16
1
12
14
0 2 4 6 8 10 12 14 16 18
Cacao
Cattle
Project
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe. 
Graph 18. Production´s value Millions of dollars 
Baseline Mid-Term
61
In contrast, there is no effect of the intervention at the mid-term in the livestock income, 
but the evolution of livestock production costs has reduced by more than 50 percentage 
points for the early treatment as compared to the evolution of the late treatment group.
A direct result of the growth in marketing is the average gross margin, which is defined as 
the ratio of net income (gross income minus production costs) to gross income. The 
average margin per farmer for the early treatment group in cattle changed from negative (-
37.3%) to positive (30.7%). For cacao, no statistically significant changes are identified in 
the gross margin. Given the strong dispersion in the margins estimated for each producer, 
this indicator is best analyzed using the median and also at the project level31
. In this way, 
margins in cacao change from negatives in baseline to mid-term positives, which is in line 
with the increase in income discussed earlier. At the project level, the margins for both 
chains have grown considerably compared to the baseline, mainly due to the good 
dynamism in livestock.
Table 19. Average gross margin and median per farmer and by project level
At mid-term, 80% of the producers assisted in livestock in the early treatment group have
positive margins. In contrast, only 45.6% of the cacao farmers present positive margins. 
This suggests that there is still much room for improvement for the second stage of the 
program in the cacao chain. It is should be noted that for the case of cacao, the fact that the 
margin is positive at project level compared to the average and the median (which are 
negative) implies that the increase in net income was higher for the relatively larger cacao 
growers.
By applying the matching estimators combined with difference-in-differences, no 
statistically significant changes are found, at the mid-term, due to the intervention, in the 
evolution of the gross margin of cacao, as both income and production costs show a 
positive trend during the period of analysis. For cattle, there is an increase in the gross 
margin due to the intervention compared with the evolution of the late treatment in more 
than 30 percentages points. This effect is due to a considerable reduction in production 
costs for the early treatment.
 
31 In its formula, the project-level indicator uses the sum of the income and costs of all the producers 
under study.
Average Median Project Average Median Project
Cattle -37.3 -40.6 19.5 30.7 52.7 57.1
Cacao -297.4 -34.3 -15.0 -480.0 -18.1 13.5
Baseline Mid-term
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - 
PROGRESA Caribe. 
Value chain
62
The program promotes the marketing of production through producer organizations. 
Despite this, most livestock production is marketed in the local market or with local 
traders. At mid-term, only 10% of early treatment producers sell their production to 
producer organizations. No relevant changes are identified in livestock marketing 
mechanisms at mid-term. In contrast, most cacao production is marketed in the local 
market or through cooperatives. As in livestock, at mid-term no significant changes in the 
marketing mechanisms of cacao are identified.
0.5 0.9 0 0 0.8 1.9 0.9 0.8
13.7
10.4
1.7 3.3 0.9 1.4 0 0.8
42.5 42
69
62.8
43.4 42.5
28.5
37.2
2.8
6.6
11.2
5.8 7.1 6.6
3.5
6.6
1.4 0.5 0 0
2.4 5.2
0
1.7
9.4 7.6 6.9 6.6
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
Baseline Mid-Term Baseline Mid-Term
Early treatment Late treatment
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe. 
Graph 19. Marketing mechanisms for livestock 
Percentage of producers 
Auction Commodity market Cooperative Farmer groups
Local market Local trader Processing market Retail
Roadside Rural assembly Wholesale
0.6 0.5 0.6 1.5 0.6
2.4
44.1 42.2
50.9
28.9
0.5 1.0 1.2
0.9 0.5 8.2
0.6
5.0
1.0 1.8
0.6
0.9 0.6 0.6
46.8
50.5
35.1
62.1
0.9 2.0 1.0 0.6 1.8
2.4
0.6
0
10
20
30
40
50
60
70
Baseline Mid-Term Baseline Mid-Term
Early treatment Late treatment
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe. 
Graph 20. Marketing mechanisms for cacao 
Percentage of producers
Wholesale Roadside Cooperative Exportations
Farmer groups Local intermediary Processing market Commodity market
Local market Retail Local operator Auction
63
In this regard, the evaluation team suggests that the consortium partners examine in 
greater detail why the marketing mechanisms under the program are so rigid. A relevant 
point is to analyze if the program has supported the marketing of all the beneficiaries 
equally.
7.1.8. The Socio-economic Well-being of the PROGRESA Beneficiaries
The PROGRESA Caribbean theory of change states that if program activities as a whole 
improve agricultural productivity and if trade in dairy products and/or beef and cacao is 
increased, the income of farmers’ families will be increased and a contribution will be 
made to poverty reduction in the areas of intervention.
The transmission channel of agricultural programs with poverty reduction and food 
security are not so obvious. First, poverty is a structural problem and its dynamics of 
change are slow in the short term. Second, food security depends not only on producers' 
incomes but also on their consumption patterns, which in rural areas are usually 
determined by cultural factors and the availability of food in the area.
Taking this into account, this section discusses the evolution of the final outcomes of the 
program, poverty, and food security, and address to what extent their behavior could 
reflect the impact of the mid-term intervention. The following table presents the evolution 
of these outcomes.
Table 20. Evolution of the program outcomes
The measurement of poverty is based upon the 2015 version of the PPI (Progress Out of 
Poverty Index)
32
. The results indicate that early treatment households, poverty was 
 
32 The PPI methodology for Nicaragua was updated by Mark Schreiner in 2013 using the 2009 
EMNV [standard-of-living survey] as a reference for estimating the probability of being poor.
Baseline Mid-Term
PPI general (%) 59.15 56.01
HDDS 7.06 5.84
MAHFP (months) 11.17 11.52
% of families with insufficient food 34.51 17.39
Early treatment
Source: Evaluation team calculations based on baseline and mid-term 
survey (panel data) - PROGRESA Caribe. 
64
reduced by 3 percentage points at the mid-term. This change is statistically significant at 
10% level.
The PPI reflects that the incidence of poverty is (statistically) higher in the producers 
assisted in the cacao chain as compared to those who work only with livestock. The 
greatest statistical reduction of poverty between the baseline and mid-term is observed in 
the producers who are assisted in both value chains.
The panel data allows the estimation of transition matrices33 of poverty levels for the early 
treatment between the baseline and mid-term, using poverty quintiles. The calculations 
show a greater mobility towards more favorable poverty ranges34
. In other words, the 
greatest number of deprivations were reduced in those households with greater economic 
vulnerability.
Table 21. PPI (%) - Transition matrix
Examination of PPI components found that the incidence of poverty in the early treatment 
group was reduced by the reduction of household size and the increase in household 
assets. As for the household size, this could be due to migratory flows and changes in the 
family composition (e.g. marriage or unions of children) during the 18 months of 
intervention. This indicator contributes with little more than 30% in the effective score of 
the general index. On the other hand, the greater asset holdings could be influenced by the 
intervention and the income from other activities.
Exploring income from other activities shows that at the mid-term, almost one-third of 
beneficiary households had family members who earned income from other sources. This 
 
33 The transition matrix is a Markov process that estimates the conditional probability of finding a 
household in a specific range of poverty at midterm, conditioned on the fact that this household 
was in another range at the baseline.
34 The transition matrix is a Markov process that estimates the conditional probability of finding a 
household in a specific range of poverty at the midterm, conditioned on the fact that this household 
was in another range at the baseline.
0-20 21-40 41-60 61-80 81-100
0-20 57.0 15.2 17.7 6.3 3.8 100
21-40 29.3 17.2 31.0 15.5 6.9 100
41-60 15.0 14.3 43.6 25.7 1.4 100
61-80 7.4 5.5 18.0 59.0 10.1 100
81-100 2.0 2.0 10.7 32.2 53.2 100
Total 14.7 8.3 22.0 34.9 20.0 100
Baseline
Mid-term
Total
Source: Evaluation team calculations based on baseline and mid-term 
survey (panel data) - PROGRESA Caribe.
65
income represents just over a third of total family income35
. There are no statistically 
significant changes compared to baseline in the proportion of households generating
income from other activities or in the levels of this income. Revenue from other activities
came mainly from both agricultural and non-agricultural temporary and self-employment. 
In contrast, net income (value of production minus production costs) more than doubled 
in comparison to the baseline. This reflects that, although poverty changes are effectively a 
combination of several factors, the effects of the intervention might have a significant 
weight because of the importance of the chains in which they work vis-à-vis the average 
income of the beneficiary households. It is worth noting that livestock producers or those 
who are assisted in both chains depend to a greater extent on income from agricultural 
activities, as compared to those working with cacao.
To complement the analysis, food security indicators such as the number of Months of 
Adequate Household Food Provisioning (MAHFP) are also discussed. In this regard, at 
mid-term the MAHFP reached an average of 11.5 months for the early treatment group 
(0.35 months longer than baseline). The changes were statistically positive for all chains
under analysis and are relatively higher for producers who work exclusively with 
livestock.
Another indicator on food security is the Household Dietary Diversity Score (HDDS), 
which is constructed with a group of 12 foods associated with balanced nutrition. HDDS 
results show that producers consume an average of 5.8 food groups per day at mid-term
(7.1 food groups at baseline). This reduction over time is statistically significant. An 
analysis by chain showed no statistically significant differences in dietary diversity among
producer families. The drop in the indicator (in statistical terms) was generalized for all 
the chains analyzed and is relatively higher for producers who work exclusively with 
livestock.
The previous result should be treated with caution, given that in the baseline the 
evaluation team warned of a potential bias in HDDS results. This is because women tend 
to have a better knowledge of the household food situation but when the survey was 
conducted, the majority of respondents to this section were men. Since there was no field 
supervision in the mid-term round, the evaluation team was not able to verify whether the 
recommendation made in the baseline to request the presence of a person familiar with the 
household food situation while filling out this section was fulfilled.
On the other hand, the food shortage indicator is measured by the proportion of 
households that faced food shortages in some month during the last year. At the mid-term, 
 
35 The diagonal highlighted in yellow corresponds to the probability of remaining in the initial 
poverty range.
66
only 17.4% of early treatment farmers underwent food shortages at some point during the 
year, representing a reduction of 17.1 percentage points over baseline.
By applying the difference-in-differences and the matching estimators combined with 
difference-in-differences, no statistically significant changes are found due to the 
intervention in any of the above discussed outcomes (poverty and food security). As in the 
case of yields, this result is also expected as changes in welfare mostly take place in the 
long term. Moreover, as mentioned before, poverty changes are a combination of several 
factors. As mentioned before this channel of transmission is difficult to prove directly, as 
the PPI methodology does not allow to prove this link easily. The evaluation team 
considers that positive changes in welfare due to the intervention will be found at the final 
evaluation of PROGRESA Caribe.
7.1.9. Summary of Intermediate and Outcome Indicators
The following is a summary of the intermediate and outcome indicators discussed above 
for the case of early treatment between baseline and mid-term, and the impact estimation.
Table 22. Matrix of Intermediate and Outcome Indicators
Baseline Mid-Term
Difference 
(MT vs BL)
Impact 
(ET vs LT)
Milk yields (liters of milk per cow per day) 2.4 3.2 0.8** No
Dry cocoa yields (tm/ ha) 0.27 0.17 -0.10** No
Average cattle weight per hectare (kg / ha) 382.1 615.1 233.0** No
Gross income - cacao ($) 781.4 1,277.9 496.5*** 40%
Gross income - cattle ($) 8,349.9 8,753.3 403.4 No
Cacao production Costs ($) 892.2 1,124.2 232.0* < 40%
Cattle production Costs ($) 6,931.5 3,970.4 -2961.1*** < 50%
Gross Margin per Hectare (cocoa) (%) -297.4 -480.0 -182.6 No
Gross Margin per Hectare (livestock) (%) -37.3 30.7 68.0*** > 30%
Progress Out of Poverty Index (%) 59.2 56.0 -3.1* No
Household dietary diversity scores (HDDS) 7.1 5.8 -1.2*** No
Months of adequate supply of food in the 
household (MAHFP)
11.2 11.5 0.3*** No
Notes: The table reports the difference in each variable between the baseline and mid-term for the early treatment group. Inference is 
adjusted by wild cluster bootstrap standard errors. Last column reports the difference for each variable between the two periods. Impact 
indicators are estimated by applying the difference-in-differences and the matching estimators combined with difference-in-differences. 
BL: baseline, MT: mid-term, ET: early treatment, LT: late treatment.
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
* Significant at the 10 percent level.
Source: Evaluation team calculations based on baseline and mid-term survey (panel data) - PROGRESA Caribe.
Intermediate 
Indicators
Outcome 
Indicators
Indicator 
67
Also, it is important to remark that farm management practices are one of the activities 
that the program emphasizes the most. As compared with baseline and the late treatment, 
there are substantial increases in the percentage of producers of early treatment, in both 
cacao and cattle, that contribute to costs, have savings or investment budgets, who manage 
debt, record sales, keep track of livestock inventory, and keep records on costs and 
production. This important progress is due to the effort made by the program in its 
initiative to strengthen farm management. 
7.2. Farmers’ Perception Surveys
This section discusses the results of the beneficiary satisfaction survey and farmers’ 
perception on financial education. Both modules were included in the mid-term survey. 
The results are valid only for those producers surveyed and do not necessarily reflect the 
perception of all farmers assisted by the project, as the sample was designed to capture 
objective indicators (e.g. yields, income) and not for subjective indicators. Also, the results 
are only informative and should be treated with caution, since as explained in section 
5.2.2, the data for both modules was collected with a certain degree of error; the 
measurement errors were isolated to some extent from the desktop. Nevertheless, despite
the measurement errors, the evaluation team considers that the results could be useful for
the consortium partners.
7.2.1. Beneficiary Satisfaction on the Program
This section discusses the results of the beneficiary satisfaction survey of the early 
treatment group surveyed with reference to each of the types of interventions being 
implemented. The interventions that have a higher level of adoption are identified, along 
those issues that are constraining and leave room for improvement.
As mentioned in section 2.2, each consortium partner works with a different combination 
of interventions. Therefore, some interventions are not implemented by all consortium 
partners. However, in the process of data collection the information was recorded without 
taking this aspect into account. The consortium partners explained that this happened 
because the perception survey was sent to them after the general training process of the 
entire survey.
Efectively, due to time constraints, the consortium partners received the survey tool one 
week after the evaluation had already begun and this limited the consortium partners to 
implement the tool as expected. Firstly, the language of the questions was not adjusted to 
the language used by each consortium partner in their activities with farmers. Secondly, 
68
the main type of intervention that TNS does (monthly trainings) was left out of the survey; 
although we cannot rule out that the respondents could have confused this type of 
intervention with other ones (e.g. workshops). Third, there was no extensive training on 
the way of collecting this type of data.
Due to these issues, it is likely that enumerators and respondents had several confusions 
on how to fill and respond to this module. Nevertheless, the evaluation team isolated the 
measurement error to some extent by filtering the information considering only the types 
of interventions carried out by each partner.
For the final evaluation, it is important to redesign this questionnaire considering all the 
aforementioned aspects and make an extensive training in methods to collect data on 
farmers' perception.
On the other hand, it is important to mention that in some interventions the percentage of 
farmers who recall not receiving this activity is high, e.g. exchange tours (73.2%) and fairs 
(63.5%). However, this is normal since some type of activities do not involve the 
participation of many beneficiaries.
Table 23. Farmers who recall not receiving the activity…
(percentages)
The information is presented as follows: positive evaluation (excellent or good) and 
negative evaluation (regular or bad). For each indicator, the calculation excludes the 
number of producers who recall not receiving the activity.
In general, the early treatment group surveyed gives a positive assessment in all types of 
interventions, as technical assistance, field schools, workshops and informative talks.
%
Technical assistance 5.2
Field schools 26.3
Workshops 16.5
Informative talks 28.0
Goods and services 14.2
Dissemination 49.3
Fairs 63.5
Field days 31.8
Exchange tours 73.2
Source: Evaluation team calculations based on 
benefeciaries perception survey.
69
Regarding the dissemination of information through ICT and the exchange tours, there is a 
positive assesment for each consortium partner, although there is room for improvement. 
For the fairs, the satisfaction is highly positive for CRS and TNS (more than 90%). Field 
days in general earned a positive appraisal for the three consortium partners. The table 
below shows the detail of the respondents' assessment to each type of intervention.
Table 24. Perception of beneficiaries - valuation by 
Component and consortium partners (percentages)
The main factors that appear as key to facilitation of a better adoption in all the project 
components are training (83.7%) and provision of information (83.6%). This may suggest 
that more consistent and timely communication channels contribute to more optimal 
performance of the producers. In this sense, the visualization of benefits also contributes to 
Technical assistance
Positive evaluation 90.6 87.7 -
Negative evaluation 9.4 12.3 -
Field shools
Positive evaluation 93.8 86.8 -
Negative evaluation 6.2 13.2 -
Workshops
Positive evaluation 96.8 93.0 93.5
Negative evaluation 3.2 7.1 6.5
Informative talks
Positive evaluation 97.3 - 70.1
Negative evaluation 2.7 - 29.9
Goods and services
Positive evaluation 92.3 - -
Negative evaluation 7.7 - -
Dissemination
Positive evaluation 92.9 63.2 70.3
Negative evaluation 7.1 36.8 29.7
Fairs
Positive evaluation 100.0 - 90.8
Negative evaluation 0.0 - 9.2
Field days
Positive evaluation 100.0 88.6 89.2
Negative evaluation 0.0 11.4 10.8
Exchange tours 
Positive evaluation 100.0 77.2 -
Negative evaluation 0.0 22.9 -
Source: Evaluation team calculations based on benefeciaries perception survey.
CRS LWR TNS
70
the adoption of components. The behavior is homogeneous among the consortium 
partners.
The main factors that appear as impediments or constraints to the adoption of the 
components are lack of resources (65.4%) and lack of time (58.1%). To a lesser extent, 
climatic conditions are reported as affecting component compliance by 20.7%, while 17.0% 
of the producers surveyed report feeling discouraged to participate in the focus areas of 
the program.
7.2.2. Farmers’ Perception on Financial Education
This section discusses the basic knowledge of financial management that the producers 
report to understand and to apply in their farm management. The module is constructed 
based on 10 questions, developed by the consortium partners, to which a rating is assigned 
according to the indicated answers. The analysis is aimed at evaluating farmers' 
perception on: the obtaining and investment of profits, the control of expenditures and 
investments, the formulation of a family budget, savings, and the frequency of and access 
to credit.
Regarding surveyed farmers perception of having positive profits, less than 60% of the 
producers consider having positive profits from their economic activity in the 2016-2017 
cycle. It is important to remark that this figure is influenced by the fact that a great share of 
farmers (more than 40%) were not able to answer this question in the module of financial 
education, for both early and late treatment. Therefore, this result does not provide 
information on the real financial gains of the producers. Instead, it highlights the 
importance of providing greater tools of financial education to producers, so that they 
have a better understanding of the financial gains or losses in their economic activity. 
Excluding the number of producers that did not answer this module, for all consortium 
partners, the percentage of producers consider having positive profits from their economic 
activity in the 2016-2017 cycle is greater than 70%, for both, early and late treatment.
71
The financial module shows a non-response rate greater than 40% for all the consortium 
partners and for both, early and late treatment. Thus, the results for the rest of the section 
exclude the number of producers that did not answer to the module on financial 
education.
The perception on the investment of profits reveals that for the early treatment producers, 
the three main destinations are health (60.8%), education (46.0%) and debt payment 
(40.0%). Investment components related to farm management, such as the purchase of 
animals, land or equipment, are low.
On the other hand, when analyzing how many of the early treatment producers surveyed 
consider keeping some type of account of the activities on their farm, it was found that 
only 3 out of 10 consider keeping any type of record. When specifically asked whether a 
family budget was prepared, the responses did not differ from the aforementioned.
With reference to savings, slightly more than half (52.0%) of early treatment beneficiaries 
mentioned having ever saved. The most common frequency is monthly, and the two main 
ways of saving are by buying animals and keeping cash at home. 
Regarding access to credit, less than 20.0% of the early treatment producers surveyed 
reported having accessed to some type of credit in the last year (compared to the date of 
the survey). This result must be interpreted with caution as it might reflect farmers' 
understanding on their credit situation rather than the real status of their access to finance.
35
21
54 51
33
68
58
57
36 49
44
28
7
22
10
0
23
5
0
10
20
30
40
50
60
70
80
90
100
CRS LWR TNS CRS LWR TNS
Early treatment Late treatment
Graphic 21. Farmer´s perception on profits 
Percentage
Do not respond Positive profits Negative profits
Source: Evaluation team calculations based on mid-term survey , financial education module- PROGRESA Caribe.
72
It should be mentioned that the association between the perception on access to credit and 
financial knowledge score was analyzed. The results are not significant, which is to say, 
there is no relation between these two variables.
Finally, the general score of the financial knowledge assessment shows that the early 
treatment beneficiaries had a stronger performance in financial practices in comparison 
with the late treatment group. The difference was nearly 8 percentage points.
The evaluation team considers this result is in line with the growth in the management 
practices discussed in previous sections, which is highly positive considering that only 18 
months of activities have passed.
7.3. Producers Organizations Performance
7.3.1. Introduction
The performance evaluation of the producer organizations is based on the application of 
the tool for “facilitated self-assessment of the management of rural associative enterprises 
(ADA)”. This tool enables the producer organizations to carry out a quick analysis of their 
business management and organizational process. The methodology is based on a 
participatory self-assessment process by the leadership bodies, partners, and the 
management, administrative and technical teams of the cooperatives. 
The importance of the application of this tool relies in the fact that the different 
stakeholders (partners, leadership, contracted personnel or collaborators) that comprise 
71
63
58
60
62
64
66
68
70
72
Early treatment Late treatment
Graphic 23. Financial education score
Average score
Source: Evaluation team calculations based on mid-term survey , financial education module- PROGRESA Caribe.
73
these rural cooperative enterprises, understand the status of their organization and the 
progress that it experiences over time. 
7.3.2. Methodology
The Learning Alliance tool is based on six areas: 1) Strategic orientation, 2) Business
management, 3) Technical services, 4) Financial services, 5) Structure and functionality, 
and 6) Governance in partnership processes.
Each area, in turn, is disaggregated into five, six or seven sub-areas with questions for 
each. Each sub-area is evaluated through Likert items from one to five, with one being 
when the cooperative enterprise does not fulfill the optimal description of the indicator 
and five when it fulfills it in its entirety.
The baseline assessment applied the original version of the ADA (Learning Alliance) tool 
developed by Gottret, Junkin and Ugarte (2011). This assessment reported low producer 
organizations performance levels in all the “Financial Services” sub-areas, particularly 
among the organizations assisted by CRS and TNS. For example, most of the producer 
organizations analyzed in the baseline did not carry out financial planning training 
processes, lacked financial savings skills, showed weaknesses in terms of access and 
coverage due to the few (if any) services provided, or had failed to introduce client 
satisfaction feedback mechanisms. 
The baseline self-assessment findings informed the design of the organization￾strengthening plans for the organization assisted by the project. However, because most of 
these organizations do not include the provision of financial services within their work 
focus, activities to strengthen this area were not included in the project framework. For 
this reason, the evaluation team and consortium partners agreed to exclude the “Financial 
Services” area from the mid-term evaluation36
, as its inclusion would have misrepresented 
the actual performance levels achieved by the organizations with the project’s support. 
This measure required the recalculation of the ADA baseline indicators.
For the interpretation of the results and trend analysis, a standard normalization index 
was constructed for the sub-areas that comprise each area, obtaining percentage values 
from zero to 100.
 
36 CRS is an active member of the Learning Alliance, which created the methodology and tools for 
the facilitated self-assessment. CRS explained to the evaluation team that the ADA member 
organizations’ directors and partners have the authority to determine which areas should be 
included in the ADA tool, as defined by the context of interventions and the thematic focus of each 
project. 
74
 𝑧 =
 
 𝑥 𝑥 00
The score for the areas was constructed through a simple average of the sub-areas that 
comprise them. Likewise, the overall score, henceforth called the Learning Alliance score, 
was obtained through a simple average of the five standardized areas considered in this 
analysis. 
 𝑦 𝐴 =
 
 
𝐿 𝐴 =
 𝐴 𝐴 
 𝐴 𝐴 
Thus, the tool makes it possible to compare the results of the self-assessments with the 
results obtained by other rural associative enterprises and among themselves over time. 
For the evaluation of the tool, the methodology suggests that a score greater than or equal 
to 70 points places the cooperative in a positive situation.
The consortium partners and the implementing partners, with support from their business 
technical advisors, acted as facilitators of the process for the baseline and mid-term 
evaluation but not as evaluators or verifiers. Following the methodology, they formed 
groups with the boards of directors and the technical, management and administrative 
teams. Once this phase concluded, a meeting was held where the different groups shared 
and came to a consensus on the final score for each assessment area.
Information37 was collected for 17 producer organizations (cooperative businesses) in both 
baseline and mid-term rounds. Ten producer organizations left the project. Two of them 
were supported by TNS and LWR. The remaining 8 cooperatives were supported by CRS.
A process of verification of the status of the producers was made for the mid-term. CRS 
found that there were producers that, although were part of the cooperative businesses 
selected to be part of the program, were inactive or did not meet all the requirements. 
Some of the reasons are: 1) they did not live in the community assisted by the program 
anymore; 2) their value chain was not cattle or cacao; 3) they did not have an interest in 
participating in the program. For these reasons, CRS decide to exclude these 8 
organizations from the Learning Alliance.
 
37 The tool also compiles quantitative performance indicators. However, this data is not available 
for most of the producer organizations. Therefore, these indicators are not evaluated in this report.
75
The evaluation team reviewed and validated the database and constructed a panel data to 
analyze the trend in the performance of the producer organizations toward fulfillment of 
the proposed goals. This identified pending challenges and future actions for 
improvement in the second part of the project.
7.3.3. Results for Management of Producers Organization
This section analyzes the major results obtained from the application of the Learning 
Alliance self-assessment tool. It compares the information for the mid-term with the 
baseline study to identify progress and areas of improvement in the organizational 
development of the cooperatives.
7.3.3.1. Producers Organization Aggregate Performance
At mid-term, the cooperative businesses assisted by the project had increased their
aggregate average ADA score by 5.7 points, bringing it to 47.6 points. The cooperative 
businesses with the highest scores are Cooperativa La Pradera with 71.6 points, Cooperativa 
de Servicios Múltiples de Cacao en la Reserva de Indio Maíz (COOSEMUCRIM) with 66.8 
points, and Unión de Cooperatives (UCA) Ahmed Campos with 66.5 points. COMPROMUB is 
the cooperative with the lowest score (18.8 points). This same cooperative had one of the 
lowest scores in the baseline, and its performance level actually dropped at mid-term. 
Table 25. General Score AdA
Normalized Indicator
Cooperatives Baseline Mid-term Growth 
La Pradera 66.45 71.60 5.14
COOSEMUCRIM 65.57 66.80 1.23
UCA Ahmed Campos 71.27 66.53 -4.74
Nueva Waslala 54.40 64.25 9.86
COODEPROSA 41.54 61.87 20.33
CACAONICA 64.06 59.47 -4.59
COOSEMUP 44.26 54.10 9.84
COOPROCAFUC 59.06 52.32 -6.73
ASIHERCA 32.38 51.73 19.35
COOPROCAR 38.00 45.11 7.11
COOSAGRO 41.58 38.03 -3.55
COOMUNSOL 19.33 37.18 17.84
COOSEMUVIS 32.12 37.01 4.88
COOMUSALWI 18.13 29.34 11.22
COOPELACTME 15.46 29.31 13.85
COMULVAN 14.18 25.89 11.71
COMPROMUB 34.34 18.83 -15.51
Overall Score 41.89 47.61
Source: Elaboration based on participatory tool ADA, FUNIDES
76
The only cooperative that obtained a mid-term score higher than the goal of 70 points was 
Cooperativa La Pradera, which had nearly reached this score in the baseline. Although UCA
Ahmed Campos was the only cooperative with more than 70 points in the baseline report, its 
mid-term score dropped 4.5 points, due to deterioration in most areas with the exception 
of “Strategic Orientation.”
The cooperatives that showed the greatest growth in comparison with their baselines were 
COODEPROSA, ASIHERCA, and COOMUNSOL. Although these cooperatives do not yet 
surpass 70 points, they have improved their positions significantly. COODEPROSA and
COOMUNSOL improved in all the areas. In contrast, ASIHERCA deteriorated in 
“Strategic Orientation” and “Structure and Functionality” while growing considerably in 
the other areas.
Five cooperatives scored lowered at mid-term when compared to baseline (UCA, 
CACAONICA, COOPROCAFUC, COOSAGRO, COMPROMUB). One possible external 
factor identified by the consortium partners that can explains this performance is the fall in 
the price of cacao, which caused the closure of the central of producers. These factors 
discouraged producers' partners and organizations. 
Looking into the different areas, all the cooperatives that scored lower at mid-term, 
dropped their score in the area of “Governance in Partnership Processes”, and 80% of 
these five cooperatives also dropped their score in “Structure and Functionality”.
7.3.3.2. Producers Organization Performance by Area
At the mid-term, none of the aggregate ADA thematic area scores managed to exceed 70 
points. “Structure and Functionality” obtained the highest rating with 60 points, while 
“Technical Services” received the lowest score at 33.8 points.
In terms of comparative growth between baseline and mid-term, “Business Management” 
stands out with 24.9% improvement. The areas that had the lowest growth are “Structure 
and Functionality” and “Governance in Partnership Processes,” with 7.7% and 7.4%, 
respectively. In spite of this, these two areas have the highest scores for both assessment 
periods.
Table 26. Evolution of score per area
All the cooperatives
77
The following web graph also presents the aggregate performance by area38: 
The following table presents each cooperative’s performance by area.
 
38 The area of "financial services" was included by CRS' suggestion only for visual representation. 
However, as explained before, this area is not part of the analysis.
Baseline Mid-term Growth
Strategic Orientation 38.30 45.11 17.76%
Business Management 39.27 49.07 24.94%
Technical Services 29.61 33.85 14.33%
Structure and Functionality 55.70 60.00 7.71%
Governance in Partnership Processes 46.56 50.02 7.44%
Source: Elaboration based on participatory tool ADA, FUNIDES
0
20
40
60
80
100
Strategic Orientation
Business Management
Structure and Functionality Technical Services
Governance in Partnership
Processes
Graph 24. Score per evaluation area- ADA
Comparison between base line and mid-term evaluation
Baseline Mid-term
Source: Elaboration based on participatory tool ADA, FUNIDES
78
Table 27. Overall Score per area and chain value 
All organizations – Mid-term
 Strategic Orientation: Only three cooperatives earned a score higher than 70 points. 
This is the strongest area for the La Pradera and COOPROCAFUC cooperatives and the 
weakest area for the CACAONICA and ASIHERCA cooperatives.
 Business Management: Only four cooperatives earned a score higher than 70 points. 
This is the strongest area for the COOSEMUP and COODEPROSA cooperatives and 
the weakest area for the COOPROCAR and COOMULVAN cooperatives. 
Strategic 
Orientation
Business 
Management
Technical 
Services
Structure and 
Functionality
Governance 
in Partnership 
Processes 
Overall 
Score
La Pradera 84.4 73.3 61.0 76.9 62.5 71.6
COOSEMUP 50.0 70.5 41.7 54.2 54.2 54.1
COOSAGRO 41.7 51.8 2.4 56.3 38.0 38.0
COOMUNSOL 28.1 30.3 20.3 59.8 47.4 37.2
COOSEMUVIS 39.6 48.8 0.0 58.7 38.0 37.0
COOMUSALWI 29.2 29.3 0.0 55.5 32.8 29.3
COOPELACTME 25.0 34.5 8.5 37.9 40.6 29.3
COOSEMUCRIM 70.8 70.0 54.5 75.1 63.5 66.8
UCA Ahmed Campos 74.0 65.0 50.5 80.6 62.5 66.5
Nueva Waslala 65.5 68.6 58.1 71.8 57.3 64.3
COODEPROSA 58.4 69.6 67.7 60.6 53.0 61.9
CACAONICA 41.7 58.8 73.1 59.2 64.6 59.5
COOPROCAFUC 64.3 62.9 29.8 58.6 46.1 52.3
ASIHERCA 34.9 59.4 45.0 58.3 61.1 51.7
COOPROCAR 35.4 29.0 38.1 64.2 58.9 45.1
COMULVAN 17.7 6.3 21.6 51.6 32.3 25.9
COMPROMUB 6.3 6.5 3.3 40.6 37.5 18.8
Source: Elaboration based on participatory tool ADA, FUNIDES Cattle Cacao
79
 Technical Services: As previously mentioned, this is the weakest area; 60% assign their 
lowest score to this area (10 of the 17 cooperatives) Only CACAONICA reports a score 
higher than 70 points.
 Structure and Functionality: Approximately 60% of the cooperatives recognize this as 
their strongest area (10 of the 17 cooperatives earned their highest score in this area.) 
None of the cooperatives identified this as its weakest area.
 Governance in Partnership Processes: None of the cooperatives earned a score higher 
than 70 points in this area. This is the strongest area for the ASIHERCA, COOPROCAR, 
COOPELACTME and COMPROMUB cooperatives.
7.3.3.3. Producers Organization Performance by Consortium Partner
The cooperatives with the highest scores were assisted by TNS and LWR. The cooperative 
with the lowest overall score is COMPROMUB, which was assisted by TNS. The 
cooperatives assisted by TNS have a heterogeneous score distribution, and no specific 
pattern can be found between the highest and lowest performance. Similarly, the score 
distribution of the few cooperatives assisted by CRS does not present a pattern; they have 
high, intermediate and low performance ratings. The cooperatives assisted by LWR all 
have scores higher than 45 points. This result reflects the project’s focus, which is to work 
with cooperatives with heterogeneous performance levels.
Partner’s performance in the different areas as well as the factors that have contributed to 
their change is addressed as follows: as previously stated, the partners assist cooperatives 
19
26
29
29
37
37
38
45
52
52
54
59
62
64
67
67
72
0 10 20 30 40 50 60 70 80
COMPROMUB
COMULVAN
COOPELACTME
COOMUSALWI
COOSEMUVIS
COOMUNSOL
COOSAGRO
COOPROCAR
ASIHERCA
COOPROCAFUC
COOSEMUP
CACAONICA
COODEPROSA
Nueva Waslala
UCA Ahmed…
COOSEMUCRIM
La Pradera
TNS LWR CRS
Graph 25. Overall Score by Partner
Normalized Indicator
Source: Elaboration based on participatory tool ADA, FUNIDES
80
with widely heterogeneous characteristics. For this reason, while it would be misguided to 
compare the partners, it is relevant to assess the development of the cooperatives they 
assist. In the first place, each of the partners strengthened its mid-term ADA score, as 
compared to the baseline.
Table 28. Comparison among the score per area
Score per area
By evaluating the partner’s scores over time, it can be concluded that CRS represents the 
partner with the highest overall growth (13.1 points) compared to the baseline. This 
increase in their score is due to a significant improvement in all areas of the evaluation. 
The second partner with the highest growth compared to baseline is LWR, with an 
increase of 5.9 points; it should be taken into consideration that the score declines in the 
areas of Strategic Orientation and Structure and Functionality (-1.1 and -0.2 points, 
respectively). TNS is the partner that has the lowest growth in its score (3.1 points); the 
areas of Technical Services and Governance, decrease -5.0 and -0.2 points, respectively.
Table 29. Score’s evolution in time according to partner and area
Performance of the Producers Organizations Assisted by CRS
Partner
Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term
CRS 18.9 37.1 23.4 35.0 17.5 33.4 47.4 61.0 39.3 45.7 29.3 42.4
LW R 55.1 54.0 55.3 64.1 40.1 54.0 62.6 62.4 49.4 57.7 52.5 58.4
TNS 35.4 42.8 35.6 45.4 27.8 22.8 54.6 58.3 47.4 47.2 40.2 43.3
Source: Elaboration based on participatory tool ADA, FUNIDES
Strategic 
Orientation
Business 
Management
Technical Services Structure and 
Functionality 
Governance in 
Partnership 
Processes
Overall Score
Partner
Strategic 
Orientation
Business 
Management
Technical 
Services
Structure and 
Functionality 
Governance in 
Partnership 
Processes 
Overall 
Score
CRS 18.2 11.6 15.9 13.6 6.4 13.1
LW R -1.1 8.8 13.9 -0.2 8.3 5.9
TNS 7.4 9.8 -5.0 3.7 -0.2 3.1
Source: Elaboration based on participatory tool ADA, FUNIDES
81
The business cooperatives supported by CRS grew in all the areas. “Cooperativa de Servicios 
Múltiples Nueva Waslala” obtained the highest overall performance score, although it has
not yet reached 70 points.
Table 30. Comparison among the scores per area, according to partner (CRS) 
Score per area
At mid-term, the area with the highest rating is “Structure and Functionality,” which can 
be attributed to improved performance in the “Organizational Chart and Functions” and 
“Legal Status” areas. The area with the lowest score is “Technical Services”, although it 
does show progress in comparison with the baseline. The importance of CRS’s 
emphasizing this area is indicated by the fact that the lowest scores are found in its sub￾areas (“Provision of Operational Services” and “Investment for the Provision of Services.”)
Table 31. Sub-area with highest score – CRS
Mid- term
Partner Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term
Nueva Waslala 43.2 65.5 56.5 68.6 50.9 58.1 67.1 71.8 54.3 57.3 54.4 64.3
COOMUNSOL 11.5 28.1 10.0 30.3 0.0 20.3 42.9 59.8 32.3 47.4 19.3 37.2
COMULVAN 2.1 17.7 3.8 6.3 1.5 21.6 32.3 51.6 31.3 32.3 14.2 25.9
Promedio Total 18.9 37.1 23.4 35.0 17.5 33.4 47.4 61.0 39.3 45.7 29.3 42.4
Source: Elaboration based on participatory tool ADA, FUNIDES
Overall Score
Strategic 
Orientation
Business 
Management
Technical 
Services
Structure and 
Functionality
Governance in 
Partnership Processes 
82
Table 32. Sub-area with the lowest score – CRS 
Mid-term
Performance of the Producers Organizations Assisted by LWR
Area
Strategic 
Orientation
Business 
Management
Technical 
Services
Structure and 
Functionality
Governance in 
Partnership 
Processes 
Subareas 
with 1st 
Best Score
Market 
Competencies
Commercial 
Management
Access and 
Coverage
Organizational 
Chart and 
Functions
Organizational 
Practices
78.7
Subareas 
with 2nd 
Best Score
Strategic 
Planification
Economic 
Analysis
Satisfaction 
with 
Technical 
Services
Legal Status
Membership 
and 
Commitment
72.7
Source: Elaboration based on participatory tool ADA, FUNIDES
Area
Strategic 
Orientation
Business 
Management
Technical 
Services
Structure and 
Functionality
Governance in 
Partnership 
Processes 
Subareas 
with 1st 
Worst 
Score
Business Plan Administrative 
Management
Provision of 
operational 
services
Influence on 
practices and 
policies
Organizational 
Competencies
16.1
Subareas 
with 2nd 
Worst 
Score
Access and use 
of information 
Management of 
human 
Resources and 
Gender
Investment for 
the provision 
of services
Communication Conflict 
Resolution
17.5
Source: Elaboration based on participatory tool ADA, FUNIDES
83
The business cooperatives assisted by LWR show growth in all the areas except “Strategic 
Orientation” and “Structure and Functionality.” The cooperative with the highest overall 
score is COOSEMUCRIM with a score of 66.8.
Table 33. Comparison among the scores per area, according to partner (LWR)
Score per area
The highest average score earned by the cooperatives assisted by LWR is in the area of 
“Business Management,” which assesses administrative, financial, environmental, 
commercial, technical and communication management. The sub-areas with the highest 
performance are “Economic and Financial Management” and “Economic Analysis.” The 
areas with the lowest scores are “Strategic Orientation” and “Technical Services,” although 
the latter is the area with greatest growth.
The “Strategic Orientation” sub-areas that reflect the greatest weakness and require 
further reinforcement are “Strategic Administration Competence” and “Strategic 
Planning.” The weakest “Technical Services” sub-areas are “Investment for the Provision 
of Services” and “Management for the Provision of Services.” 
Table 34. Sub-area with the highest score – LWR
Mid-term
Partner Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term
COOSEMUCRIM 69.3 70.8 72.4 70.0 49.7 54.5 73.9 75.1 62.5 63.5 65.6 66.8
COODEPROSA 47.6 58.4 43.0 69.6 32.0 67.7 47.3 60.6 37.8 53.0 41.5 61.9
CACAONICA 58.3 41.7 58.8 58.8 69.3 73.1 67.2 59.2 66.7 64.6 64.1 59.5
COOPROCAFUC 64.7 64.3 62.9 62.9 45.0 29.8 64.8 58.6 57.9 46.1 59.1 52.3
ASIHERCA 35.6 34.9 39.7 59.4 4.8 45.0 59.8 58.3 22.0 61.1 32.4 51.7
Overall Score 55.1 54.0 55.3 64.1 40.1 54.0 62.6 62.4 49.4 57.7 52.5 58.4
Source: Elaboration based on participatory tool ADA, FUNIDES
Governance in 
Partnership 
Processes 
Overall Score
Strategic 
Orientation
Business 
Management
Technical 
Services
Structure and 
Functionality
84
Table 35. Sub-area with the lowest score - LWR
Mid-term
Performance of the Producers Organizations Assisted by TNS
La Pradera is the only cooperative assisted by TNS that obtained a score higher than 70 
points. The cooperatives assisted by TNS reported an average growth in every area except 
“Technical Services” and “Governance in Partnership Processes”.
Table 36. Comparison among the scores per area according to partner (TNS)
Area
Strategic 
Orientation
Business 
Management
Technical 
Services
Structure and 
Functionality
Governance in 
Partnership 
Processes 
Subareas with 
1st Best Score
Access and 
use of 
information 
Financial and 
Accounting 
Management
Partnerships 
for innovation 
in service 
delivery
Rules and 
regulation
Organizational 
Practices
76.26
Subareas with 
2nd Best 
Score
Business 
Aiances
Economic 
Analysis
Access and 
Coverage
Transparency 
and 
accountability
Membership 
and 
Commitment
76.2
Source: Elaboration based on participatory tool ADA, FUNIDES
Area
Strategic 
Orientation
Business 
Management
Technical 
Services
Structure and 
Functionality
Governance in 
Partnership 
Processes 
Subareas with 
1st Worst 
Score
Strategic 
management's 
Competencies
Management 
of human 
Resources and 
Gender
Investment for 
the provision of 
services
Influence on 
practicies and 
policies
Organizational 
Competencies
37.12 25
Subareas with 
2nd Worst 
Score
Strategic 
Planification
Commercial 
Management
Management 
for the 
provision of 
services
Communication
Conflict 
Resolution
44.75 30
Source: Elaboration based on participatory tool ADA, FUNIDES
85
Score per area
The cooperatives assisted by TNS are strongest in the area of “Structure and 
Functionality.” Their highest performance is in the “Rules and Regulations” and 
“Organizational Chart and Functions” sub-areas. They are weakest in the area of 
“Technical Services” and particularly in the “Investment for the Provision of Services” and 
“Management for the Provision of Services” sub-areas, which are important spaces for 
improvement.
Table 37. Sub- area with the highest score - TNS 
Mid - term
Partner Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term Baseline Mid-term
La Pradera 74.0 84.4 65.8 73.3 50.0 61.0 74.1 76.9 68.4 62.5 66.5 71.6
UCA Ahmed 74.0 74.0 68.5 65.0 54.3 50.5 83.1 80.6 76.6 62.5 71.3 66.5
COOSEMUP 33.3 50.0 52.3 70.5 45.1 41.7 50.6 54.2 40.1 54.2 44.3 54.1
COOPROCAR 28.1 35.4 15.3 29.0 39.1 38.1 58.1 64.2 49.4 58.9 38.0 45.1
COOSEMUVIS 33.3 39.6 39.8 48.8 0.0 0.0 49.5 58.7 38.0 38.0 32.1 37.0
COOSAGRO 29.2 41.7 33.0 51.8 54.2 2.4 46.3 56.3 45.3 38.0 41.6 38.0
COOMUSALWI 12.5 29.2 15.0 29.3 0.0 0.0 38.1 55.5 25.0 32.8 18.1 29.3
COOPELACTME 12.5 25.0 15.3 34.5 4.0 8.5 25.7 37.9 19.8 40.6 15.5 29.3
COMPROMUB 21.9 6.3 16.0 6.5 3.6 3.3 66.2 40.6 64.1 37.5 34.3 18.8
Overall Score 35.4 42.8 35.6 45.4 27.8 22.8 54.6 58.3 47.4 47.2 40.2 43.3
Source: Elaboration based on participatory tool ADA, FUNIDES
Overall Score
Strategic 
Orientation
Business 
Management
Technical 
Services
Structure and 
Functionality
Governance in 
Partnership 
Processes 
86
Table 38. Sub- area with the lowest score - TNS 
Mid – term
7.3.3.4. Comparison of ADA’s Score with Operational Start-up Date
Most of the lowest-scoring cooperatives, such as COMPROMUB, COOMULSALWI, 
COOPROCAR, COOPELACTME, COMULVAN, COOSEMUVIS and COOMUNSOL, have 
been in operation for less time than the others or are still in the process of starting up. This 
suggests that years of experience is a factor in the variation of strengths among the 
cooperatives.
Area
Strategic 
Orientation
Business 
Management
Technical 
Services
Structure and 
Functionality
Governance in 
Partnership 
Processes 
Subareas 
with 1st Best 
Score
Strategic 
Planification
Economic 
Analysis
Partnerships 
for innovation 
in service 
delivery
Rules and 
regulation
Organizational 
Practices
76.3
Subareas 
with 2nd 
Best Score
Business 
Aiances
Administrative 
Management
Provision of 
operational 
services
Organizational 
Chart and 
Functions
Membership 
and 
Commitment
74
Source: Elaboration based on participatory tool ADA, FUNIDES
Area
Strategic 
Orientation
Business 
Management
Technical 
Services
Structure and 
Functionality
Governance in 
Partnership 
Processes 
Subareas 
with 1st 
Worst 
Score
Business Plan
Management 
of human 
Resources and 
Gender
Investment for 
the provision 
of services
Communication Organizational 
Competencies
14.8
Subareas 
with 2nd 
Worst 
Score
Strategic 
management's 
Competencies
Financial and 
Accounting 
Management
Management 
for the 
provision of 
services
Influence on 
practicies and 
policies
Conflict 
Resolution
19.4
Source: Elaboration based on participatory tool ADA, FUNIDES
87
Table 39. Start date of operation39 and overall score
An examination of the correlation between the ADA score and the start-up date of the 
cooperative reveals a coefficient of determination of 42.5%, which indicates that the 
cooperative’s higher performance has a positive correlation with the greater number of 
years of operation. The following graph better illustrates this affirmation.
 
39 The cooperatives for which the start date of operations appears as "In process", refers to 
cooperatives that are performing some operations but are in the process of legalization before the 
regulator. These cooperatives were part of the baseline study, so they can also be part of the mid￾term evaluation.
Cooperatives
Start Date 
of 
Operation
Overall 
Score
COMPROMUB In Process 18.8
COOMUSALWI In Process 29.3
COOPROCAR In Process 45.1
COOPELACTME 2016 29.3
COMULVAN 2016 25.9
COOSEMUVIS 2014 37.0
COOMUNSOL 2013 37.2
La Pradera 2012 71.6
COOSEMUP 2012 54.1
COODEPROSA 2008 61.9
COOPROCAFUC 2008 52.3
Nueva Waslala 2006 64.3
COOSEMUCRIM 2004 66.8
COOSAGRO 2003 38.0
ASIHERCA 2001 51.7
CACAONICA 2000 59.5
UCA Ahmed Campos 1992 66.5
Source: Elaboration based on participatory 
tool ADA, FUNIDES
88
At least six cooperatives could have trouble advancing quickly in the organizational 
strengthening process due to their lack of experience. For these cooperatives, the
consortium partners should design specific plans that will facilitate greater assimilation of 
the project-provided services.
7.4. Impact of the Participation and Practices of the Private Sector in 
Improving Market Links and Income of Smallholder Producers
7.4.1. Introduction
Parties involved in a value chain are linked by an exchange relationship in which each act 
as a buyer and seller at different stages. For example, while producers are sellers and the 
cooperatives are buyers in the first link in the chain, the cooperatives are sellers and the 
companies are buyers in the next link.
The Link methodology has been used within the framework of PROGRESA Caribe. This 
methodology was developed by the International Center for Tropical Agriculture (CIAT) 
to evaluate the impact of the program over time on the participation and (inclusive) 
business practices of the private sector on the different links of the chain.
The Link methodology is based on an innovation process that involves the use of four 
tools:
R² = 0.425
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
0 5 10 15 20 25 30 Overall Score
Years Operation
Graph 26. Correlation between start date of 
operation and overall score
Source: Elaboration based on participatory tool ADA, FUNIDES
89
1) the value chain map, which helps identify the key stakeholders, processes and services 
within a value chain and how each interacts with the rest; 2) the business model canvas, 
which enables the organizations and/or enterprises to identify their current situation as an 
entity and to identify areas for improvement and/or intervention; 3) the principles for 
inclusive business models, to determine the level of inclusion in the business between 
producers and buyers; and 4) the prototype cycle, which unites the previous tools to 
determine strategies for expansion or to put new innovations into practice to promote the 
participation of smallholder farmers in the chain. These tools facilitate a better 
understanding of the major stakeholders, the processes and the relationships within a 
value chain during the process of innovation in the commercial relationship. This enables 
all the stakeholders involved to attain greater benefits. 
Tool #3 has been applied for the mid-term study to the companies that have worked with 
the cooperatives targeted by the project. The tool was applied to a total of 10 vendors 
(cooperative enterprises) and 4 buyers (companies). From the vendor´s side 11 commercial 
relationships were evaluated and 5 from the buyer’s side40 41
.
Compared to the baseline study, one seller (UCM) and three buyers (CARSA, 
COAGROPEK, QUEBAR) were not evaluated. UCM withdrew from the project, and the 
baseline had identified that these three buyers did not meet the criteria for inclusion (they 
showed no interest in carrying out such an inclusion process) in the Link process.
The consortium partners and the implementing partners, with support from their business 
technical advisors, acted as facilitators of the process for the mid-term evaluation but not 
as evaluators or verifiers; the evaluation team carried out the entire process for the 
baseline.
7.4.2. Methodology
Tool #3 of the Link methodology is a participatory instrument designed to analyze the 
principles for inclusive business models. The methodology serves a double purpose: 
 
40 The CACAONICA cooperative assessed its business relationship with the Ethiquetable and Ritter 
Sport companies. Ritter Sport evaluated its business relationship with the cooperative Nueva 
Waslala and the other cooperatives that trade cacao and are assisted by the project using this 
methodology. 
41 The ten sellers mention above are: ACAWAS, ASIHERCA, CACAONICA, COODEPROSA, 
COOPROCAFUC, COOSEMUCRIM, Nueva Waslala, UCA AHMED Campos, COOSEMUVIS, 
COOSEMUP. Eleven commercial relationship are established because CACAONICA has 
commercial relationships with: Ritter Sport and Ethiquetable. The four buyers are Gente del Cacao, 
Ritter Sport, La Perfecta and Nilac. Five relationship are evaluated, as Ritter Sport has two separate 
evaluation: 1) Ritter – Nueva Waslala and 2) Ritter – the rest of producers organizations.
90
helping the buyers as well as the sellers to assess their commercial relations under 
inclusive criteria and serving as a point of departure in the promotion of the inclusion of 
small-scale producers in the value chain in which they participate.
This tool assesses six principles:
1. Collaboration among Stakeholders: establishing the level of common goals that exists 
between buyers and sellers. 
2. Effective Market Linkage: evaluating the relations that form among the stakeholders to 
access market information and quality products.
3. Transparent and Consistent Governance: establishing the level of sharing of the rules of 
negotiation. 
4. Access to Services: measuring the impact of the buyer company in collaborating with 
the cooperative to access diverse services. 
5. Inclusive Innovation: evaluating the joint promotion of innovations in the products and 
in good practices. 
6. Measurement of Results: incorporating customized indicators and monitoring plans to 
assess the health status of the commercial relations of a for-profit company, as well as 
its effectiveness in promoting development.
Each principle is disaggregated in sub-indicators and the score for each of the principles in 
this case, is achieved through self-assessment based on the perceptions of the cooperative’s 
representatives (or the company´s representatives). The score ranges from zero to five, 
with zero signifying that the parties are in “strong disagreement” with the sub-indicator 
and five signifying that there is “strong agreement.” The scale is designed to not have a 
neutral score; in other words, each response will have a positive or negative inclination. 
There are some criteria that may not be applicable (N/A), which depends on the context in 
which the business model is developed. 
7.4.3. Performance Assessment for the Cooperative Enterprises (sellers)
The aggregate average Link score for the cooperative enterprises (sellers) rose slightly 
(0.4), increasing from 2.5 at baseline to 2.9 at mid-term.
The cacao chain cooperatives with the highest scores are COODEPROSA, 
COOPROCAFUC and CACAONICA (linked with Ritter Sport), with 3.50, 3.48 and 3.42 
points respectively. They are all assisted by LWR. There are only two livestock chain 
cooperatives, COOSEMUVIS and COOSEMUP, which earned 2.3 and 2.1 points, 
respectively, and are assisted by TNS.
91
The cooperatives with the greatest baseline-to-midterm growth are ASIHERCA (75.0%) 
and COODEPROSA (38.4%), both of which belong to the cacao chain, are linked with 
Ritter Sport, and are assisted by LWR. Two cooperatives reported a downward trend: 
COOSEMUP (-6.4%), which belongs to the cattle chain, is linked with La Perfecta and is 
assisted by TNS; and Nueva Waslala (-6.3%), which belongs to the cacao chain, is linked 
with Ritter Sport and is assisted by CRS. The performance of the remaining cooperatives is 
mixed; for example, COOSEMUVIS shows a slight increase (0.5%).
2.1
2.3
2.4
2.5
2.8
3.0
3.0
3.1
3.4
3.5
3.5
0.0 1.0 2.0 3.0 4.0
COOSEMUP
COOSEMUVIS
CACAONICA (ETHIQUETABLE)
UCA AHMED CAMPOS
ACAWAS
COOSEMUCRIM
ASIHERCA
NUEVA WASLALA
CACAONICA (RITTER)
COOPROCAFUC
COODEPROSA Cattle Cacao
Graph 27. Overall Score by cooperatives and partners
Sellers 
TNS LWR CRS
Source: Elaboration based on participatory tool Link, FUNIDES
2.8
1.7
2.1
3.1
2.5
3.1
2.6
3.3
2.2 2.3 2.2
2.8
3.0
2.4
3.4 3.5 3.5
3.0 3.1
2.5
2.3
2.1
0%
75%
11% 11%
38%
11%
15%
-6%
15%
0%
-6%
-20%
-10%
0%
10%
20%
30%
40%
50%
60%
70%
80%
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0 ACAWAS ASIHERCA CACAONICA (ETHIQUETABLE) CACAONICA (RITTER) COODEPROSA COOPROCAFUC COOSEMUCRIM NUEVA WASLALA UCA AHMED CAMPOS COOSEMUVIS COOSEMUP
Cacao Cattle
Graph 28. Overall Score - Link
Sellers
Baseline Mid-Term Growth
Source: Elaboration based on participatory tool Link, FUNIDES
92
The following heatmap provides further detail on the mid-term results per principle for 
each cooperative enterprise. The principle “Collaboration among Stakeholders” earned the 
highest aggregate average score (3.5). In contrast, the principle “Inclusive Innovation” 
holds the lowest aggregate average score (2.2).
Table 40. Disaggregation by principle, mid-term score Sellers
 Collaboration among Stakeholders: As was previously mentioned, this is the principle 
with the highest aggregate score and is the strongest principle for the COODEPROSA, 
COOPROCAFUC, ASIHERCA, ACAWAS, CACAONICA (linked with Ethiquetable) and 
COOSEMUVIS cooperatives. No cooperative identified this principle as its weakest. 
Although it is the principle with best score, there are still areas for improvement. 
Specifically, increase the agreement on the environmental objectives established 
between sellers and buyers, and to exchange information formally and more frequently.
 Effective Market Linkage: This is the principle with the second-highest aggregate score 
for sellers and is the strongest principle for the COOPROCAFUC and Nueva Waslala
cooperatives. It is not the weakest principle for any of the cooperatives. The areas for 
improvement in this principle are the joint (sellers and buyers) conservation of 
environmental resources. Likewise, the frequent review of the seller’s position in the 
market.
 Transparent and Consistent Governance: This principle has an aggregate average score 
of 2.7, and is not the strongest principle for any of the cooperatives. It is the weakest 
principle for the CACAONICA (linked with Ritter Sport) and ASIHERCA cooperatives.
The actions that should be taken to improve this principle is to increase the knowledge 
Value 
Chain 
Cooperative
Collaboration 
among 
Stakeholders
Market 
Linkage 
Transparent 
and 
Consistent 
Governance
Access to 
Services 
Inclusive 
Innovation 
Measurement 
of Results 
Overall 
Score
COODEPROSA 4.1 3.4 3.0 2.9 3.6 4.0 3.5
COOPROCAFUC 3.8 3.8 3.3 2.8 3.6 3.6 3.5
CACAONICA (RITTER) 3.8 3.8 2.4 2.6 4.3 3.6 3.4
NUEVA WASLALA 3.4 3.9 3.5 2.6 2.1 3.0 3.1
ASIHERCA 3.7 2.8 2.0 2.9 3.6 3.2 3.0
COOSEMUCRIM 3.2 3.6 3.0 2.1 3.6 2.8 3.0
ACAWAS 3.8 3.3 2.4 1.9 3.1 2.0 2.8
UCA AHMED CAMPOS 2.9 3.0 3.1 2.4 0.0 3.5 2.5
CACAONICA (ETHIQUETABLE) 4.2 2.9 2.9 1.9 0.0 2.3 2.4
COOSEMUVIS 3.0 2.8 2.5 2.5 0.0 2.9 2.3
COOSEMUP 2.7 2.7 2.3 1.9 0.0 2.9 2.1
Overall Score 3.5 3.3 2.7 2.4 2.2 3.1 2.9
Source: Elaboration based on participatory tool Link, FUNIDES
Cacao
Cattle
93
on the quality standards demanded by the customers, as well as to share the productive 
risks with the buyers.
 Access to Services: This principle has an average score of 2.4, which is the second￾lowest aggregate score. It was not reported to be the highest performing principle for 
any of the cooperatives. It was the weakest principle for COODEPROSA, 
COOPROCAFUC, COOSEMUCRIM and ACAWAS cooperatives. The areas for 
improvement suggested by the sellers are the supply of inputs for production and post￾harvest and to improve the access to suitable transportations.
 Inclusive Innovation: This principle has the lowest aggregate average score. The Nueva 
Waslala, UCA Ahmed Campos, CACAONICA (linked with Ethiquetable), COOSEMUVIS
and COOSEMUP cooperatives perceive it as their weakest principle. Since it is the 
principle with the lowest average score, it is necessary to pay special attention to 
improve in this area. Specifically, the joint innovation with the buyer, and to turn it into 
a continuous and recurring activity.
 Measurement of Results: This principle has an aggregate average score of 3.1, and is the 
strongest principle for the UCA Ahmed Campos. To improve the score of this principle, it 
is necessary to implement evaluation processes designed and jointly tested with the 
customer and to discuss the information generated by the buyer.
The principles “Access to Services” and “Inclusive Innovation” reflect the greatest relative 
progress in the baseline-to-midterm comparison. These results are very positive in that 
these principles encompassed the lowest scores in the baseline. The “Effective Market 
Linkage” principle, which has the second-highest performance level, also showed 
relatively modest growth. “Transparent and Consistent Governance” is the principle in 
which the greatest number of cooperatives’ performance level dropped.
Table 41. Collaboration between stakeholders – sellers
Growth between baseline and mid-term
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For the cacao chain, the principles showing greatest relative strengthening at midterm are 
“Collaboration among Stakeholders” (3.7) and “Effective Market Linkage” (3.4). The greatest 
weakness was identified in “Access to Services” (2.5). For the livestock chain, the strongest 
principle is also “Collaboration among Stakeholders” (2.8), while the weakest is “Inclusive 
Innovation” (0). The following graph shows each chain’s average score for each principle. 
7.4.4. Performance Assessment for Businesses (buyers)
The assessment of the general score from the buyers’ perspective reflects a downward or 
low-growth trend in all the businesses for both chains. The buyers who report slight 
increases are Gente del Cacao (0.4 points), Ritter Sport in its business relations with some of 
the cooperatives (0.1 points) and Nilac (0.2 points). For its part, Ritter Sport reported 
declines in its business relations with Nueva Waslala in the period under study. The lowest 
ASIHERCA 7.78% 56.25% 0.00% 123.08% * 75.00% 75.35%
COODEPROSA 0.00% 14.81% 0.00% 107.14% * 8.33% 38.39%
UCA AHMED CAMPOS 15.15% 8.00% 5.71% 71.43% * 6.98% 15.49%
COOSEMUCRIM 0.00% 14.29% -1.39% 16.67% 212.50% -22.12% 14.80%
CACAONICA (ETHIQUETABLE) 0.00% 4.00% -4.17% 144.29% * 15.38% 11.14%
COOPROCAFUC 0.00% 0.00% -3.51% 0.00% 108.33% 9.30% 10.86%
CACAONICA (RITTER) 16.28% 25.93% -12.92% 13.04% 15.38% 3.30% 10.52%
ACAWAS 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%
NUEVA WASLALA -16.98% 6.06% 27.27% -16.13% -40.00% 15.38% -6.32%
COOSEMUVIS 8.33% 0.00% -15.63% 13.64% * 0.00% 0.56%
COOSEMUP 2.94% -7.69% -3.85% -34.48% * 15.15% -6.40%
** Indicates that there are no variations in the percentage growth, since the cooperatives in baseline report a score of 0.
Source: Elaboration based on participatory tool Link, FUNIDES
Overall 
Score Cacao Cattle
Collaboration 
among 
Stakeholders
Market 
Linkage 
Transparent 
and Consistent 
Governance
Access to 
Services 
Inclusive 
Innovation 
Measurement 
of Results
Cooperative
3.7
3.4
2.8
2.5
2.7
3.1 3.0 2.8 2.7
2.4 2.2
0.0
2.9
2.2
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Collaboration
among
Stakeholders
Market Linkage Transparent
and Consistent Governance
Access to
Services
Inclusive
Innovation
Measurement
of Results
Overall Score
Graph 29. Disaggregation comparison by principle and value 
chain
Sellers
Cacao Cattle
Source: Elaboration based on participatory tool Link, FUNIDES
95
midterm scores were observed in La Perfecta (2.9), in Ritter Sport in its business relationship 
with Nueva Waslala (3.3), and in Nilac (3.4). This suggests there is much room for 
improvement in inclusive business relations.
Table 42. Disaggregation by principle, mid-term score Buyers
Within the cacao chain, the companies consider that their business relations have been 
most strengthened in the principles “Measurement of Results” (4.4), “Collaboration among 
Stakeholders” (4.1) and “Effective Market Linkage” (4.1). The lowest performance level is 
observed in “Inclusive Innovation” (2.4). Within the livestock chain, “Inclusive 
Innovation” (0.0) is the weakest performing principle as well. “Collaboration among 
Stakeholders” (4.0) shows the highest performance level. The aggregate average scores are 
shown by chain in the following table.
3.6
3.8 3.8
3.2 3.2
4.0
3.3
3.9
3.0
3.4
-15%
-10%
-5%
0%
5%
10%
15%
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
GENTE DEL CACAO RITTER (NUEVA WASLALA)
RITTER (VARIAS) LA PERFECTA NILAC
Cacao Cattle
Graph 30. Overall Score- LINK
Buyers 
Base Line Mid-Term Growth
Source: Elaboration based on participatory tool Link, FUNIDES
Cooperative
Collaboration 
among 
Stakeholders
Market 
Linkage 
Transparent 
and Consistent 
Governance
Access to 
Services 
Inclusive 
Innovation 
Measurement 
of Results 
Overall 
Score
GENTE DEL CACAO 4.23 4.78 4.00 4.40 1.43 5.00 3.97
RITTER (NUEVA WASLALA) 3.85 3.25 3.58 3.33 2.14 3.85 3.33
RITTER (VARIAS) 4.27 4.22 3.21 3.70 3.71 4.38 3.92
LA PERFECTA 3.69 3.33 3.73 3.40 0.00 3.62 2.96
NILAC 4.38 4.22 3.67 4.00 0.00 4.00 3.38
Source: Elaboration based on participatory tool Link, FUNIDES
Cacao
Cattle
96
The baseline-to-midterm comparison of chains by principle yields different results. For 
example, the performance levels of Nilac and Ritter Sport (in its business relations with 
Nueva Waslala) dropped in nearly all the principles, while Gente del Cacao and La Perfecta
experienced growth in almost all areas. No systematic growth patterns can be identified 
for a specific area, reflecting the heterogeneity among the business relationships analyzed 
from the buyers’ perspective.
Table 43. Collaboration between stakeholders – Buyers
Growth between baseline and mid-term
It is important to remark that Lala, a large mexican company, purchased La Perfecta
during the evaluation period. The company restructured its operations and changed key 
staff. This influenced the relationship with the cooperatives assisted in the program. For 
example, Lala/La Perfecta reduced the commercialization with different cooperatives, 
including those assisted in the program, afecting negatively the perception in the Link 
evaluation.
4.1 4.1
3.6 3.8
2.4
4.4
3.7
4.0 3.8 3.7 3.7
0.0
3.8
3.2
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Collaboration
among
Stakeholders
Market Linkage Transparent
and Consistent
Governance
Access to
Services
Inclusive
Innovation
Measurement
of Results
Overall Score
Graph 31. Disaggregation comparison by principle and value 
chain
Buyers
Cacao Cattle
Source: Elaboration based on participatory tool Link, FUNIDES
Buyers
Collaboration 
among 
Stakeholders
Market 
Linkage 
Transparent 
and Consistent 
Governance
Access to 
Services 
Inclusive 
Innovation 
Measurement 
of Results
Overall 
Score
GENTE DEL CACAO 17.02% 0.00% 2.33% 0.00% * 0.00% 9.84%
RITTER (VARIAS) 4.72% 5.56% -1.97% 0.00% 8.33% 1.79% 3.13%
RITTER (NUEVA WASLALA) -5.66% -18.75% 9.49% -9.91% -37.50% -10.71% -12.22%
LA PERFECTA 3.64% 5.56% 9.01% 5.26% * 4.00% 5.37%
NILAC -9.43% -6.25% -2.38% -17.07% * -6.00% -8.40%
** Indicates that there are no variations in the percentage growth, since the cooperatives in baseline report a score of 0.
Source: Elaboration based on participatory tool Link, FUNIDES
Cacao 
Cattle
97
98
8. Conclusions and Lessons Learned
PROGRESA Caribe is an agribusiness program that has thus far been implemented over 18 
months (October 2015-April 2017) in consortium by Catholic Relief Services (CRS), 
TechnoServe (TNS) and Lutheran World Relief (LWR). The program aims to strengthen 
the value chain of cacao and livestock (dual purpose) in the Caribbean Coast of Nicaragua 
and Río San Juan. The program benefits more than 4,000 smallholder producers from 13 
municipalities. The program also works on the strengthening of 17 producer organizations 
and associations, and in the promotion of 11 commercial relationships under inclusive 
business models.
The project activities are aimed at fulfilling two strategic objectives: 1) increase agricultural 
and livestock productivity and 2) expand trade of cacao and cattle products. The long￾term outcome of the program is to increase the income of the producer families and reduce 
poverty in the intervention areas.
Relevance of the Program
The program takes into account the economic and political context. It targets RACCN, 
RACCS and Río San Juan, which are areas with a high incidence of poverty and 
historically, they have received fewer resources for socio-productive projects. The 
beneficiaries are producers who work on dual-purpose cattle, cacao or both chains, and 
whose production is fundamental to their livelihood strategy. These value chains have 
high regional impact, not only because of their high presence in the area, but also because 
of their potential growth in demand for workers. According to data of the National 
agricultural census (2010), the Caribbean Coast accounts for 39% of the country's cattle and 
53% of the area planted with cacao.
The program also considers the cultural context. The specific activities stipulated in the 
original agreement between CRS and USDA changed slightly in part because, once on the 
ground, the consortium partners identified that minor adjustments should be made in 
some activities to better fit the context of the different areas of intervention. The evaluation 
team considers that the modifications made to the activities should not diminish the 
expected results. To the contrary, the adaptation to the context of the different areas of 
intervention should enhance the results.
During its first stage, the program met the needs of the project beneficiaries. The results of 
the beneficiary satisfaction survey of the early treatment group reveals a positive 
assessment in all the types of interventions. The intervention approach is diverse, 
involving approximately 10 major activities, ranging from technical assistance, training, 
field schools, exchange trips with farmers, to participation in trade fairs. However, as the 
99
beneficiary satisfaction survey demonstrates, each consortium partner works with 
different combination of interventions. This implies that some interventions are not 
implemented by all consortium partners. The consortium partners explained that the 
intervention approach is diverse due to the territorial extension of the program (more than 
200 communities in 13 municipalities). This approach creates a heterogeneity among the 
producers in terms of the impact of the assistance provided, which should be examined 
very closely when learning is assessed at the final evaluation.
The program fits within the Government of Nicaragua’s economic and agricultural 
development policies and programs. The Caribbean Coast is a region of high interest for 
the Government and PROGRESA's components are in accordance with other programs 
executed by the Government with funding from international cooperation agencies. For 
example, NICADAPTA, which is executed by MEFCCA.
Effectiveness and Impact of the Program
As for the effectiveness and impact of the program, the evaluation team considers that the 
project is on track to meet the development objectives. Farmers’ productivity for 
dairy/beef products increased compared to the baseline, both in milk and in the weight of 
live cattle. Cacao yields fell in both the North Caribbean Coast and Río San Juan, for both 
early and late treatment, in part to the negative effects of Hurricane Otto, which occurred 
in late November 2016. Cacao plantations currently in production are a combination of old 
producing trees and some very young replacements, and therefore are more vulnerable to 
exogenous factors and require more attention from farmers and will take longer than 18 
months to come into full production potential.
At the mid-term, there are no statistically significant changes in farmers’ productivity of 
the early treatment compared to the late treatment. Nevertheless, the evaluation team 
considers that this result is expected as productive yields do not change so rapidly in just 
18 months of intervention.
At the project level, there is an increase in the total value of cacao and livestock production 
of the early treatment group. This suggests that low performances are offset by high 
performers, mainly from larger producers and in live cattle production. These results were 
determined by revenue growth in both value chains. In relative terms, the increase in 
income was greater for cacao. The increase in income at the project level was due to a 
positive (relative) change in the production volumes of all items (mainly cacao) and 
increases in the price per of liter of milk and livestock.
At average producer level, even when there is no effect of the intervention at the mid-term 
in the livestock income, there is a reduction in livestock production costs due to the 
100
intervention. The incomes from sales only grew (in statistical terms) for the case of cacao 
due to a higher volume of average production. In fact, there is an increase in income for 
the early treatment due to the intervention compared with the evolution of the late 
treatment. This positive change in cacao income is accompanied with an increase in cacao 
cost (more than 40 percentages points). The evaluation team considers that this increase in 
the production costs is reasonable because: 1) cacao producers are relatively new in the 
value chain and therefore are learning from the project to improve their production cost 
records, which makes the information more truthful; and 2) the producers have invested 
in new productive technologies that naturally push up the production costs.
Consistent with these results, in the cattle value chain, there is an increase in the gross 
margin of the early treatment due to the intervention compared with the evolution of the 
late treatment. This is due to a considerable reduction in production costs for the early 
treatment. At the project level, the margins for both chains have grown considerably 
compared to the baseline. Nevertheless, at mid-term, 45.6% of the producers assisted in 
cacao in the early treatment group have positive margins. This suggests that there is still 
much room for improvement for the second stage of the program in the cacao chain, as the 
increase in net income was higher for the relatively larger cacao growers.
PROGRESA Caribe´s theory of change states that if program activities as a whole improve 
agricultural productivity and if trade in dairy products and/or beef and cacao is increased, 
the income of farmers’ families will be increased, and a contribution will be made to 
poverty reduction in the areas of intervention. Compared to the baseline, the results 
indicate that for early treatment households’ poverty was reduced by 3 percentage points 
at the mid-term. Also, the calculations show that the incidence of poverty was reduced in 
those households of the early treatment with greater economic vulnerability. There is an 
increase for the early treatment in the number of months of adequate household food 
provisioning. But, at the mid-term no statistically significant changes are found due to the 
intervention in poverty and food security.
These results are expected since changes in welfare mostly take place in the long term. 
Moreover, poverty changes are a combination of several factors. The evaluation team 
considers that positive changes in welfare due to the intervention will be found at the final 
evaluation of the program.
Sustainability
Sustainability of the actions might be affected by the context of low educational levels in 
the intervention area, the limited time to continue promoting the process for awareness 
and change in the behavior of the producers, and the heterogeneous attention to the 
producers. These latter two aspects are due to budgetary limitations. 
101
The evaluation team considers that there is room for the achievement of greater yields and 
income from production. An important element is the knowledge that will be transfered to 
the producers and producer organizations over the remaning course of the program.
Other similar experiences in Nicaragua (for example, PROGRESA Norte) suggest that 
PROGRESA-style programs should have a minimum duration of five years, and between 
six and seven years to achieve significant changes at producer and producer organizations 
levels.
As the mid-term evaluation did not include field work, the evaluation team was not able 
to explore if the implementing partners are developing a sustainability strategy. The 
evaluation team suggest that this should be addressed by the consortium partners during 
the second stage of the program.
Efficiency of the Program
The evaluation team considers that it is not possible to explore whether the same results 
could have been obtained with fewer resources or alternative approaches during the first 
stage, for several reasons: 1) the program made adjustments in the original activities to 
better fit the context of the different areas of intervention, 2) the activities delivered by the 
program are not the same for the all the producers served, given that the intervention 
approach was planned in this way, and 3) negative exogenous factors took place at the end 
of 2016 (Hurricane Otto), especially in Río San Juan. Furthermore, there was no 
comparison project with a design, context and situation similar to the one experienced in 
PROGRESA Caribe.
The first issue discussed above is a very important aspect of efficiency. The evaluation 
team considers that the modifications made to the activities should not diminish the 
expected results. To the contrary, the adaptation to the context of the different areas of 
intervention should enhance the results.
Efficient strategies were implemented in terms of financial and human resources. In 
financial terms, a cost-share system was designed for the provision of goods for 
production so that it was possible to double the goods delivered compared to the original 
plan. This system provided a subsidy of between 50% and 80%, depending on the type of 
asset, the value chain, and the stratum of the producer. Even more important, this 
strategy helped encourage the producers to value the investment and put more effort into 
the production activity.
102
In terms of human resources, the program strove to provide more coverage to the 
beneficiaries through workshops for groups of producers, farmer field schools and 
informational talks. Nevertheless, it cannot be stated whether this strategy had a 
differentiated impact (whether it diluted the effects or not), as there was no comparison 
group attended exclusively in an individual manner.
Regarding the monetization process, despite a recent problem with the freight company, 
the evaluation team does not have any objection that CDSO continue to be the first option 
for the next and final sale. CRS is planning to include additional clauses into their sales 
and freight contracts to protect themselves against future problems during the process of 
monetization.
Good Agricultural and Commercialization Practices
The application of agricultural practices reflects the knowledge, skills and abilities that the 
farm families acquire either on their own or by the effect of the intervention. The 
application of these practices reflects the human capital of the producers.
For most of the cases, the proportion of producers applying different types of practices 
evaluated in cacao and/or cattle has increased or at least remained or are relatively 
constant.
In cattle, there is notable increase in the following practices: dehorning, rotation of 
pastures, clean milking and cattle identification. These last three practices are promoted 
under the program. Other important practices in cattle are improved management and 
sustainable agricultural practices. Both remain constant at mid-term and the percentage of 
producers applying these practices is above 80%. In cattle feeding practices, the proportion 
of producers that use mineral salts and molasses show a significant increase.
In cacao, there are significant changes in the proportion of producers practicing: 
rehabilitative pruning, eliminating buds, integrated pest management (IPM), weed control 
and disease control. The fertilization and soil conservation activities, which are promoted 
under the program, show no relevant changes in the proportion of producers who carry 
out this type of practice. These results suggest that the consortium partners should make 
greater efforts to encourage the implementation of these practices among the beneficiaries 
of both the early and the late treatment.
Farm management practices are one of the activities that the program emphasizes the 
most. As compared with baseline and the late treatment, there are substantial increases in 
the percentage of producers of early treatment, in both cacao and cattle, that contribute to 
costs, have savings or investment budgets, who manage debt, record sales, keep track of 
103
livestock inventory, and keep records on costs and production. This important progress is 
due to the effort made by the program in its initiative to develop farm plans. The 
evaluation team considers this result to be highly positive and one of the most important,
considering that only 18 months of activities have passed and that the program is carried 
out in a context of low educational level among its beneficiaries. 
This does not imply that there is no room for improvement in the adoption of farm 
management practices, but rather the opposite, since the indicator with the highest 
proportion of producer performance (control of livestock inventory) is below 30%. In this 
context, the evaluation team suggest that the consortium partners make a qualitative 
evaluation of the difficulties faced by the producers in the implementation of the farm 
plans and alternatives to overcome them. One option might be to integrate youth - who 
are likely to have higher educational levels - into farm management activities.
On the other hand, it is important to mention that the evaluation team found that there is 
no clear association between the categories of yields analyzed and the practices carried out 
by producers - which are promoted by the program. The evaluation team considers that 
this result could be due to a weakness in the measurement of the performance indicator of 
practices. At the moment, this indicator only counts the practices that the producer is 
considering in carring out, without checking if farmers actually do or not. In addition, it is 
important to incorporate two additional indicators: 1) the intensity on the application of 
the practice, measured as the number of months that the producer has applied the 
practice; and 2) an indicator of performance quality of the practice.
Finally, the program promotes the marketing of production through producer 
organizations. Despite this, most livestock production is marketed in the local market or 
with local traders. For cacao, most of the production is marketed in the local market or 
through cooperatives. No relevant changes are identified in livestock and cacao marketing 
mechanisms at mid-term. The evaluation team suggests that the consortium partners 
examine in greater detail why the marketing mechanisms under the program are so rigid. 
A relevant point is to analyze if the program has supported the marketing of all the 
beneficiaries equally.
Business Models in Value Chains and their Impact at the Level of Producers and their 
Organizations
 ADA
- The average overall score of ADA increased by 13% compared to the average score 
recorded in the baseline. 
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- Overall, the strongest areas at the mid-term evaluation are “Structure and 
Functionality” and “Governance in Partnership Processes”. This indicates that, in 
general, the cooperatives are doing well in terms of legal composition, distribution of 
duties, and in their business relationship. 
- The area with the lowest score is “Technical Services”. In this specific area, the 
consortium partners need to improve, specifically in the investment and management 
for the provision of services. 
- The areas that experienced the biggest growth at the mid-term compared to the baseline 
are “Strategic Orientation” and “Business Management”. On the other hand, the areas 
that experienced the smallest growth are “Structure and Functionality” and 
“Governance in Partnership Processes”. 
- The cooperatives with lowest scores are the newest ones, with recent star-up entry into 
operations, this indicates that the cooperative’s higher performance has a positive 
correlation with the greater number of years in operation.
- Five cooperatives scored lower at mid-term when compared to baseline (UCA,
CACAONICA, COOPROCAFUC, COOSAGRO, COMPROMUB). One possible external 
factor identified by the consortium partners that can explain this performance is the 
reduction in the price of cacao and an unsustainable price-differential, which caused the 
closure of one of the umbrella association of producers (UCM). Additional efforts must 
be made for these cooperatives to regain the growth path.
The evaluation team considers that 9 out 17 cooperatives (those above 50 points) could 
reach the score of 70 points at the final evaluation. For the remaining cooperatives, whose 
baseline results were extremely low, a positive achievement reaching at least 50 points 
should be expected in the final evaluation.
LINK
- Overall, the principle with a better score was “Collaboration among Stakeholders” and 
the principle with the worst score was “Inclusive Innovation”.
- The principles with the biggest growth compared to the baseline were “Access to 
Services” and “Inclusive Innovation”. These were the principles with the lowest scores
in the baseline, which is an indicator of the impact of the results in good practices. 
- The value chain that had the biggest growth is cacao, this is partly because Ritter Sport 
has been an active player in the inclusive business processes.
- For the cacao value chain, the principles with the highest score were “Collaboration 
among Stakeholders” and “Market Linkage”. The greatest weakness was “Access to 
Services”. 
- For the cattle value chain, the highest strength is “Collaboration among Stakeholders” 
and the greatest weakness is “Inclusive Innovation”.
105
- The overall score from the buyer’s perspective shows a decreasing trend, or small 
growth in all organizations and in both value chains. This implies that the consortium 
partners must work more closely with the companies in order to achieve better future 
outcomes in terms of inclusiveness.
There is a lot of space for improvement, especially in cattle and in the areas of inclusive 
innovation and access to services.
Program Monitoring System
PROGRESA Caribe monitoring and evaluation system is a latest generation system and 
uses a series of complementary tools that provide better information management and 
ensure better quality while reducing measurement errors in the ongoing monitoring 
(campaigns) and the evaluation rounds. For data collection, the system includes user 
guides, pilot tests, and creation of roadmaps for information gathering. Also, systematic 
review protocols were prepared for data filters and consistency in the different data 
modules, which allowed measurement errors to be reduced and ensured the quality of 
information management.
The quality of the data for the mid-term evaluation is much better than the baseline data. 
This suggests that the consortium partners put into practice the recommendations and 
lessons learned from the baseline.
Although the available information is of very good quality, there are considerable 
differences among the consortium partners, the implementing partners and even the field 
technicians themselves in the ability to conduct the survey. In this regard, it could be 
thought that the training process for conducting the survey did not have the same impact 
upon all the field technicians. However, the evaluation team considers that the differences 
in capacity are due to two factors: 1) the field technicians’ training, given that many of 
them have empirical knowledge and have had limited previous exposure to the use of 
digital tools; and 2) the turnover of field technicians among some partners has led to a loss 
of the knowledge that had been gained during the baseline study.
This led to twice as many revisions being made in this evaluation, as compared to the 
baseline, to ensure the quality of the final data that would be analyzed. The evaluation 
team suggests improving the hiring process of the field technicians. For example, CRS 
should prepare an exam for each applicant; the exam can be divided in three parts: 
technical skills, soft skills and critical thinking. Also, training for the data collection should 
focus on the field technicians exercising greater “critical thinking” during the survey.
106
On the other hand, there are aspects of the system management that should be considered 
in the continuous improvement processes:
- Improvements in the digital data collection surveys should not be made at the cost of 
losing elements for comparison with previous rounds. It is important to maintain 
harmonization in the questionnaires and the evaluation period of the different 
evaluation rounds.
- Improve the identification of the value chains to which the producers belong.
- Create a change to the protocols in the digital surveys to improve the supervision of the 
surveyors.
- Identify why some information was collected for – a few – producers whose identifiers 
did not match the master of the evaluation sample.
- Although it was appreciated that the data quality control applied by the CRS MEAL 
team is based on expert judgement, it took more time than planned. It is recommended 
that part of the quality control be performed in specialized statistical programs to catch 
measurement errors more quickly (for example, Stata or R).
- Develop explicit rules for consistency in the analysis of the databases.
- The variable of average cattle weight is measured based on the producer's perception. 
The evaluation team considers that this variable may have a bias, although uncertain in 
wether the producer´s perception in estimating the weight of cattle would be higher or 
lower than the true weight. Nevertheless, the data on number of animals and their 
mean weight in kilograms is collected by sex, age class and predominant breed. This 
disaggregation might reduce to some extent the potential measurement error.
107
References
Caliendo M. and Kopeinig S. (2008). Some Practical Guidance for the Implementation of 
Propensity Score Matching, Journal of Economic Surveys, No. 22, pp. 31-72.
Gottret, Junkin and Ugarte (2011). Self-assessment provided for the Management of Rural 
Enterprises. CATIE.
Instituto Nacional de Información de Desarrollo (2015). Resultados de la “Encuesta 
Nacional de Hogares sobre Medición de Nivel de Vida - 2014”.
Schreiner, M. (2013). A Simple Poverty Scorecard for Nicaragua. Microfinance Risk 
Management, L.L.C.
Winters, P., Salazar, L. and Maffioli, A. (2010), Designing Impact Evaluations for 
Agricultural Projects, SPD Working Papers 1007, Inter-American Development Bank, 
Office of Strategic Planning and Development Effectiveness (SPD).
108
Annex
Change in the activities of PROGRESA Caribe
Original text from the 
cooperative agreement 
Attachment A
How the activity is developed or would be 
developed during the life of the program
Proposed adjustments pending 
USDA approval
Capacity Building: Trade 
Associations
CRS will assist with the formation of, 
and strengthen existing non-profit 
and for-profit national trade 
associations for both cacao and 
livestock products. CRS will 
integrate trade associations into 
existing value chains, facilitate value 
chain discussions and collaborations, 
provide training in value chain 
analysis, manage each link in the 
chain, and assist with forging 
relationships with business actors. 
CRS will assist trade association 
stakeholders to develop 
competitiveness plans and advocate 
for support of those plans from 
secondary actors such as the 
government, universities, 
investigative centers, and service 
providers. CRS will help trade 
associations to increase the quantity 
and timeliness of market information 
for their members, including pricing 
trends, sales volumes, buyer tenders, 
and quality requirements.
CRS will assist the strengthening of existing 
non-profit national trade associations that 
promote cacao and dairy products. CRS will 
integrate non-profit trade associations into 
the existing value chains. For example, it is 
working with FAGANIC and CONAGAN 
to strengthen their linkages and services to 
local cattle associations. It is also working 
with APEN and CANICACAO with cacao 
farmers and their cooperatives. CRS will 
also facilitate value chain discussions and 
collaboration between the actors linking the 
different levels in the chains through the 
participation in fairs, congresses, and 
commercial missions. Additionally, CRS 
will assist trade association and cooperative 
stakeholders to develop competitiveness 
plans and advocate for support of those 
plans from secondary actors such as the 
government, universities, investigative 
centers, and service providers. CRS will 
help trade associations and cooperatives to 
increase the quantity and timeliness of 
market information for their members 
including pricing trends, sales volumes and 
quality requirements.
CRS proposes not assisting with 
the formation of new non-profit 
and for-profit national trade 
associations since the program has 
found at mid-term that it is more 
efficient to strengthen those that 
already exist such as 
CANICACAO, APEN, 
CONAGAN, and FAGANIC. In 
addition, at mid-term, CRS 
proposes to not directly “manage 
each link of the value chain”, but to 
instead “facilitate linkages between 
the different levels of the chain”. 
Financial Services: Facilitate 
Agricultural Lending
CRS will establish a loan facilitation 
fund that helps buy-down financial 
institution risk, yielding more 
affordable interest rates. This fund 
may be used for partial loan 
guarantees, co-financing of collateral, 
buy-down of interest charges, and the 
co-investment in private-private 
partnerships. CRS will also train 
producer cooperatives in the basic 
business skills necessary to obtain 
formal credit, including improved 
CRS will promote the co-investment in 
private-private partnerships. CRS will also 
train producer cooperatives in the basic 
business skills necessary to obtain formal 
credit, including improved record keeping, 
basic production and business plans, and 
the preparation of bankable loan dockets. 
Additionally, CRS will coordinate with 
microfinance agencies to facilitate 
relationship building with producer 
cooperatives and help them to develop and 
offer appropriate loan products that will 
As discussed previously with 
USDA representatives, CRS 
proposes eliminating the activity 
related to the loan facilitation fund 
due to budget cuts at the beginning 
of the project. The original intent of 
the fund was to lower risk for 
financial institutions to invest in 
small-scale farmers. Even without 
the fund, we have found that 
presence of the program team in 
the field and the program´s 
109
record keeping, basic production and 
business plans, and the preparation of 
bankable loan 
dockets. Additionally, CRS will 
coordinate with microfinance agencies 
to facilitate relationship building with 
producer cooperatives and help them 
to develop and offer appropriate loan 
products that will meet the needs of 
the producer organizations.
meet the needs of the producer 
organizations.
support for the activities at the 
farm level has helped to lower the 
perception of risk that the financial 
institutions have regarding 
program participants.
Infrastructure: Post￾Harvest Processing
CRS will facilitate the construction 
and improvement of post-harvest 
cocao processing infrastructure 
including fermentation trays, drying 
tunnels, and ovens through direct 
investments, co-investments with 
private companies, assisting with 
obtaining credit for equipment 
purchases, and providing technical 
training. CRS will also develop dairy 
cold chains, chilling stations, 
producer-level milking rooms and 
handling equipment, smaller milk 
collection centers closer to target 
producers, and improved cheese 
processing equipment by co-investing 
with producer cooperatives and 
private investors.
CRS will facilitate the construction and 
improvement of post-harvest cacao
processing infrastructure including 
fermentation trays, drying tunnels, and 
ovens through direct investments, co￾investments with private companies, 
assisting with obtaining credit for 
equipment purchases, and providing 
technical training. CRS will also develop 
chilling stations at farm level, producer￾level milking rooms and handling 
equipment, smaller milk collection centers 
closer to target producers, and improved 
cheese processing equipment by co￾investing with producer cooperatives.
The effort will focus on investments in 
milking rooms at the farm level and 
developing collection centers through co￾investment between private companies and 
cattle farmers’ associations or cooperatives. 
The program will invest in small cheese 
processing equipment in order to provide 
the cooperative with the opportunity of 
utilizing raw milk when the companies 
(LALA or NILAC) are not able to get to the 
collection center due to extreme weather or 
other events.
At mid-term, CRS proposes to not 
develop dairy cold chains. Private 
companies are establishing this 
kind of facility with their own 
funds in the area where they buy 
raw milk. New investments in the 
dairy cold chain depend on the 
demand of raw milk and while 
prices are low there is not much 
incentive for farmers to co-invest in 
this particular intervention. 
Inputs: Develop Agrodealers 
and Other Input Suppliers
CRS will assist producer 
organizations and associations with 
obtaining working capital to develop 
supply infrastructure, purchase 
inputs, and build business 
CRS will assist producer organizations and 
associations with obtaining working capital 
to develop supply infrastructure, purchase 
inputs, and build business relationships 
with input suppliers to obtain inputs on 
CRS does not propose changes in 
this activity.
110
relationships with input suppliers to 
obtain inputs on credit. Additionally, 
CRS will identify individual producer 
input and service needs and negotiate 
for an entire group in order to 
increase bargaining power and reduce 
the cost of acquiring inputs.
credit. Additionally, CRS will identify 
individual producer input and service 
needs and negotiate for an entire group in 
order to increase bargaining power and 
reduce the cost of acquiring inputs.
Inputs: Increase Access to 
Improved Genetic Material
CRS will establish cacao nursery and 
plant propagation sites within 
producer cooperatives and small 
private enterprises in order to 
increase the availability of improved 
genetic material in target 
municipalities. CRS will provide 
technical assistance, facilitate access 
to finance for start¬ up costs, and 
train nursery enterprises in basic 
business management skills. For the 
cattle value chain, CRS will improve 
bull breeding, expand stud farms, and 
promote the use of artificial 
insemination services by training 
independent specialists in improved 
techniques, small business 
management skills, and for-fee 
services to cattle producers.
CRS will establish cacao nursery and plant 
propagation sites within producer 
cooperatives and small private enterprises 
in order to increase the availability of 
improved genetic material in target 
municipalities. CRS will provide technical 
assistance, facilitate access to finance for 
start-up costs, and train nursery enterprises 
in basic business management skills. For 
the cattle value chain, CRS will promote the 
use of artificial insemination services by 
training independent specialists in 
improved techniques, small business 
management skills, and for-fee services to 
cattle producers.
As discussed previously with 
USDA, CRS proposes eliminating 
the bull-breeding activities and 
expanding stud farms. Given the 
realities on the ground and time it 
takes to do bull breeding and 
expand stud farms, CRS believes 
that it is better to focus on training 
farmers to use better criteria for the 
selection of bulls on their farms or 
the purchase of new animals that 
are going to be used as studs.
Source: CRS.