-------------------------------------------- 
WFP – IRP Cost-Effectiveness Analysis 

 
 

Methodology for calculating the Return of investment (ROI), 
the Benefit-Cost Ratio (BCR), and Cost Effectiveness Ratio 
(CER) of the integrated resilience programmes in the Sahel. 

 

June 2025 

Alliance Bioversity International and CIAT 

 

Femi E. Hounnou, Mathieu Ouedraogo 



 

 
 

Executive Abstract 

The Sahel faces persistent climate, food security, and livelihood challenges that require 
integrated approaches to resilience building. In response, the World Food Programme (WFP) and 
partners have implemented Integrated Resilience Programmes (IRPs) combining food 
assistance, asset creation, livelihood support, nutrition, education, and capacity strengthening. 
This report presents a standardized methodological framework to assess the Value for Money 
(VfM) of IRPs through the estimation of Return on Investment (ROI), Benefit–Cost Ratio (BCR), and 
Cost-Effectiveness Ratio (CER). The framework draws on international best practices from 
CGIAR, WFP, and development economics, integrating Cost-Benefit Analysis (CBA) and Cost-
Effectiveness Analysis (CEA). It applies a multi-level approach, combining detailed farm-level 
enterprise budgets with site-level analysis of programme costs and benefits. Both monetized and 
non-monetized outcomes are captured, including productivity gains, nutrition and health 
improvements, education outcomes, environmental services, and resilience to climate shocks. 
The methodology provides a robust, transparent tool to support accountability, learning, and 
evidence-based investment decisions for resilience programming in the Sahel. 

Key works: Cost-Benefit analysis, Cost-Effectiveness analysis, Resilience programmes, 
Sahel, Africa. 

 

 



 

 
 

About the Authors: 

Femi E. Hounnou & Mathieu Ouedraogo 

Suggested Citation: 

Hounnou E F., Mathieu Ouedraogo M.  Methodology for calculating the Return of investment (ROI), the 
Benefit-Cost Ratio (BCR), and Cost Effectiveness Ratio (CER) of the integrated resilience programmes 
in the Sahel. CGIAR Climate Security. 

Portrait Photo: WFP 

Graphic editing and editorial support: None 

Acknowledgments: 

This work was carried out with the support of the WFP. The ideas, opinions and comments therein are 

entirely the responsibility of its author(s) and do not necessarily represent or reflect WFP policy. This 

work has also benefited from the support of CGIAR’s science programs on: Climate Action, Gender 

Equality and Social Inclusion, and Food Security and Frontiers. We would like to thank all the funders 

who supported this research through their contributions to the CGIAR Trust Fund: 

https://www.cgiar.org/funders/. We also extend our gratitude to the WFP members of   who were 

instrumental for providing their comments to the document, especially Petra Bonometti and Cheikh 

SAMB 

Contacts: 
CGIAR Climate Security 
climatesecurity@cgiar.org 
https://climatesecurity.cgiar.org 
 

About Us: 

CGIAR Climate Security aims to address knowledge gaps on Climate Change and Food Security 
to inform peace and security policies and operations through a unique multidisciplinary 
approach. Our main objective is to align scientific Evidence on Food, Land, and Water Systems 
with Environmental Peacebuilding efforts that address conflicts through evidence-based 
environmental, policy, and socio-economic solutions. 

Creative Commons License 

CC BY-NC-ND 4.0 

© 2025 CGIAR Climate Security 

This is an open-access document distributed under the terms of the Creative Commons 
Attribution License, which permits unrestricted use, distribution, and reproduction in any 
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of any opinion whatsoever on the part of CGIAR concerning the legal status of any country, 
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of CGIAR or its donor organizations.

https://www.cgiar.org/funders/


 

 
 

Contents 

Acronym .................................................................................................................. 3 

1. Introduction ...................................................................................................... 1 

2. Background on Value for Money (VfM) analysis approach ..................................... 1 

2.1. CGIAR methodology ................................................................................... 1 

2.2. WFP methodology ...................................................................................... 2 

2.3. Global methodology ................................................................................... 2 

2.4. Choice of VfM analysis methodology ........................................................... 7 

3. Methodological framework  ................................................................................ 7 

3.1. Farm level .................................................................................................. 7 

3.2. Cost Benefit Analysis for IRP at site ........................................................... 12 

3.2.1. Cost of IRP ........................................................................................ 12 

3.2.2. Benefit of IRP .................................................................................... 14 

3.2.3. Indicators of CBA .............................................................................. 16 

3.3. Cost Effectiveness Analysis ...................................................................... 19 

4. Data collection approach ................................................................................ 19 

5. References ..................................................................................................... 23 

Annex : Data collection tools .................................................................................. 27 

 



 

 
 

List of tables 

Table 1. Farm budget structure for crop production including agroforestry ................... 9 
Table 2. Structure of farm fishing budget (data will be collected yearly per cycle) ........ 10 
Table 3: Structure of livestock budget ...................................................................... 11 
Table 4: Summary of IRP costs and Benefits ............................................................. 18 
Table 5: Different outcomes for each intervention used for CEA ................................. 21 
 

 

 

 



 

 
 

Acronym 
ABC : Activity-Based Costing 
ABC–I : Activity-Based Costing–Ingredients 
BCR : Benefit Cost Ratio 
BERA : Basic Efficiency Resource Analysis 
CBA : Cost-Benefit Analysis   
CEA : Cost–Effectiveness Analysis 
CGIAR : Consultative Group on International Agricultural Research 
CIAT : Centre International d'Agriculture Tropicale 
CUA : Cost Utility Analysis 
CUR : Cost Utility Ratio 
DALY : Disability Adjusted Life Year 
DFID : Department for International Development 
FFA : Food Assistance for Assets 
FFT : Food for Training 
FFW : Food for Work 
GASPA : Groupes d’Apprentissage et de Suivi des Pratiques d’ANJE 
GLV : Green Leafy Vegetables 
IDP : Integrated Development Program 
IRP : Integrated Resilience Program 
IRR : Internal Rate of Return 
LCS-EN : Livelihood Coping Strategies for Essential Needs 
LCS-FS : Livelihood Coping Strategies for Food Security 
LWM : Land and Water Management 
MAD : Minimum Acceptable Diet 
MAM : Moderate Acute Malnutrition 
MCA : Multi-Criteria Analysis 
MDD-W : Minimum Diet Diversity for Women 
NPV : Net Present Value 
PHL : Post-Harvest Losses 
PMTCT : Prevention of Mother-To-Child Transmission 
PROGRESA : Programa de Educación, Salud y Alimentación 
PV : Present Value 
QALY : Quality Adjusted Life Years 
rCSI : reduced Consumption-based coping Strategy Index,  
ROI : Return on Investment 
RUSF : Ready-to-Use Supplementary Food 
RUTF : Ready-to-Use Therapeutic Food 
SABER : Systems Approach for Better Education Results 
SAMs : Smallholder farmers Access to Market support 
SBCC : Social and Behavior Change Communication 
SDGs : Sustainable Development Goals 
SROI : Social return on investment 
TB-DOTS : Tuberculosis directly observed treatment 
TCTR : Total Cost per Transfer Ratio 
UNESCO : United Nations Educational, Scientific and Cultural Organization 
UNHCR : United Nations High Commissioner for Refugees 
UNICEF : United Nations Children's Fund 
VfM : Value for Money 
WFP : World Food Programme 

 



 

1 
 

1. Introduction  
The Sahel region faces persistent challenges including climate shocks, food insecurity, conflict, 
and poverty, all of which threaten the well-being of its populations and hinder long-term 
development. In response, integrated resilience programmes have been implemented by various 
actors to enhance the adaptive capacity of communities, reduce vulnerabilities, and improve 
livelihoods. Given the complexity and scale of these interventions, there is a growing need for 
robust, transparent, and standardized methods to evaluate their performance and justify 
investments. 

This document aims at developing a comprehensive methodology for assessing the economic 
and operational effectiveness of integrated resilience programmes in the Sahel, using three key 
financial and economic indicators: 

‒ Return on Investment (ROI): Measures the financial return generated for every unit of 
currency invested, providing an overall indication of programme efficiency. 

‒ Benefit-Cost Ratio (BCR): Compares the present value of benefits to the present value 
of costs, helping determine whether an intervention delivers net positive value. 

‒ Cost-Effectiveness Ratio (CER): Assesses the cost incurred per unit of desired outcome 
(e.g., improved food security, reduced livelihood losses), making it especially useful when 
benefits are not easily monetized. 

The methodology draws from international best practices, including guidance from development 
economics, impact evaluation, and resilience measurement frameworks, while adapting to the 
unique socio-economic and environmental context of the Sahel. It integrates both quantitative 
and qualitative data sources and accounts for multi-sectoral impacts across agriculture, health, 
education, and social protection. 

This framework is intended not only to support accountability and learning for programme 
implementers and donors, but also to inform future investment decisions by demonstrating the 
value and effectiveness of resilience programming. By applying this methodology consistently 
across projects, stakeholders can compare outcomes, scale successful models, and ultimately 
contribute to more sustainable and impactful resilience-building efforts in the region. 

2. Background on Value for Money (VfM) analysis approach  

2.1. CGIAR methodology 

In CGIAR institutes, several approaches have been mobilized to assess Value for Money. The main 
approaches applied by CGIAR encompass cost–benefit analysis (CBA) and cost–effectiveness 
analysis (CEA), particularly to evaluate agricultural technologies.  

Particularly, cost-benefit analysis (CBA) has emerged as a critical method for evaluating the 
economic viability of agroecological business models and innovations. Recent studies have 
applied CBA to assess upgraded agroecological business models (Narjes et al., 2024) and to 
analyze inclusive models within agroecology initiatives in Zimbabwe (Dawes and 
Mushongachiware, 2023). Additionally, CBA has been instrumental in quantifying the 
multifaceted benefits of resource recovery and reuse—capturing social, environmental, and 
economic dimensions to support broader value creation and human well-being (Lazurko, 2018). 

The framework has also been extended to evaluate social welfare impacts in large-scale poverty 
alleviation strategies. For example, the PROGRESA program utilized a social CBA to balance the 
costs and impacts of its interventions, highlighting how such analyses can inform the 



 

2 
 

effectiveness of policy instruments (Coady, 2000). Further applications of CBA have included 
studies assessing the integration of agroecological innovations in green leafy vegetable (GLV) 
value chains in Kiambu County, Kenya (Onyango et al., 2024) and the implementation of 
agroecological packages in the dairy value chain in Bobo-Dioulasso (Vall et al., 2024). 

Moreover, recent research has quantified the economic repercussions of agricultural challenges, 
such as the impact of Fusarium oxysporum f. sp. cubense Tropical Race 4 on value chain actors 
and their environments, providing essential insights into the disease’s far-reaching 
consequences (Ritter et al., 2024; Mockshell et al., 2024). Complementary studies have 
employed CBA to assess investment cases for agroecological business enterprises in Kenya 
(Chege et al., 2024) and to analyze the economic impacts of seed system interventions in Uganda 
implemented by the International Potato Center (Feukeng et al., 2024). 

CGIAR researchers have applied CEA in evaluating interventions ranging from improved crop 
technologies to gender-transformative programs. For example, studies on interventions such as 
intimate partner violence prevention have measured cost per case averted, providing evidence 
on which strategies deliver the best outcomes for the lowest cost (Leight et al., 2021). Although 
less frequently applied in agricultural research compared to public health, Cost Utility Analysis 
(CUA) has been used by CGIAR researchers to account for non-monetary benefits—such as 
improvements in nutritional status and overall well-being—which are crucial in evaluating 
interventions aimed at enhancing food security and reducing malnutrition. In adaptation area, de 
Brauw (2025) supported Norwegian Government to conduct Cost-effectiveness of anticipatory 
action including cash transfers, agricultural inputs, early warning information in Lesotho, 
Madagascar, and Mozambique. 

Collectively, these studies illustrate the robust and diverse applications of VfM and CBA 
methodologies in agricultural and rural development. They not only provide critical insights into 
the financial and social returns of various interventions but also guide policy decisions and 
strategic investments in sustainable agriculture and community development. 

2.2. WFP methodology 

During its interventions, the World Food Programme (WFP) has utilized various approaches to 
assess Value for Money (VfM) across single projects, broader programs, and multi-sectoral 
interventions. These include economy analyses (Venton et al., 2015), efficiency studies (WFP and 
UNHCR, 2014), and Cost-Effectiveness Analysis (CEA). For instance, Jenkins (2012) applied CEA 
to evaluate the Integrated Management of Acute Malnutrition program in southwestern Uganda.  
Similarly, the CEA approach was used in the Unlock Literacy program, where the equivalent years 
of schooling gained were found to be cost-effective, especially in Eswatini compared to Ethiopia 
(World Vision, 2022). In Afghanistan, Hall (2013) conducted a comparative CEA of four WFP 
hunger reduction activities—Food for Assets (FFA), Food for Training (FFT), and Food for Work 
(FFW)—focused solely on transfer modalities. 

Many WFP assessments have also applied Cost-Benefit Analysis (CBA), particularly in evaluating 
school feeding programs (WFP, 2018; 2019; Dunaev and Corona, 2019) and integrated resilience 
programs (Sissoko and Traore, 2019; WFP, 2024). 

2.3. Global methodology 

VfM assessments seek to measure the extent to which a particular investment or project 
represented the best possible use of the funds in the pursuit of a particular goal. Several 



 

3 
 

definitions have been elaborated since DFID (2011) defines VfM as “the optimal use of resources 
to achieve outcomes”. “New Zealand’s aid programme defines it as the best possible way to meet 
objectives during the lifetime of an activity regarding the total cost of managing and financing the 
activity, while ensuring the resources are used effectively, with no waste” (Adou, 2016). A range of 
VfM approaches can be applied depending on the theoretical and practical context-specific 
questions (Fleming, 2013). Theoretically, the way to measure value (consideration of economy, 
efficiency, effectiveness or equity) and which stakeholder value considered are the key issues. In 
practical terms, method choices depend on: (i) if the evaluation concerns a single project or 
comparing multiple projects; (ii) possibility to monetize or use of proxy measure of value; (iii) the 
way to participatory and transparently evaluate costs and benefits; and (iv) deciding whether the 
method promotes/enables participation and accountability to community or partners. There is 
also concern about the availability of data relating to the costs and benefits of the project, as well 
as the availability of comparators. In each case, the costs of a project are weighed up against the 
benefits that these costs generate. Various approaches include cost-minimization analysis 
(including Activity-based costing, Activity-based costing-ingredients, cost driver, follow the 
money, and efficiency analysis), cost effectiveness analysis, cost utility analysis, cost-benefit 
analysis, social return on investment, rank correlation of cost vs impact, basic efficiency 
resource analysis, multi-criteria analysis. 

Activity-based costing (ABC) has been trialed as an alternative approach in some contexts. 
While there is no standard approach to activity-based costing in humanitarian appeals, Stoddard 
et al., 2017) define ABC generically as average cost per beneficiary per sectoral activity. These are 
estimates based on the average previous costs of implementing these sectoral activities per 
number of people served, which indicate to donors the overall probable costs of a response 
(Puett et al., 2013).  

Activity-based costing–ingredients (ABC–I): This method merges activity-based accounting 
methods with the ‘ingredients’ method, which calculates programme costs from inputs, input 
quantities and input unit costs (Margolis and Hoddinett, 2015). The precise ‘ingredients’ for the 
study should be established based on discussions with staff, to determine the costs that were 
specific to the different transfer modalities (Margolis and Hoddinett, 2015). This approach, cost 
apportionment, spreads the total programme costs across multiple activities that produce 
specific outcomes, and then determines the unit costs of each outcome, which can be compared 
to unit costs for producing these outcomes through alternative means (as per CEA, below) (Abou-
Ali et al., 2010). Another approach is to assess whether the total cost of providing a range of  
benefits {𝑏1, 𝑏2 … , 𝑏𝑛} under a single Integrated Development Program (IDP) (𝑐𝑗𝑜𝑖𝑛𝑡) is lower than 
the summed costs of multiple separate projects delivering the same results at the unit costs of 
{𝑐1, 𝑐2 … , 𝑐𝑛}:  

𝑐𝑗𝑜𝑖𝑛𝑡  {𝑏1, 𝑏2 … , 𝑏𝑛} < ∑ 𝑐𝑖 × 𝑏𝑖         (1) 

The inequality shows costs savings or efficiency due to synergistic interventions within IDPs, as 
individual activities within an IDP share programme overheads and reinforce each other’s results 
(Acharya and Hilton, 2018). 



 

4 
 

Cost driver analysis: Cost driver refers to the cost categories that most influences the overall 
cost of a project / programme / portfolio (e.g. international staff, aid commodities or overheads) 
(Pongracz et al., 2016). It is a common practice for ex ante reviews of proposals and ex post audits 
to identify the types of costs that are the largest percentage of a budget and then establish if they 
are reasonable by referring to cost data from similar projects from other organizations, from 
previous responses and even global averages (Wheatley and Pongracz, 2014). Economy and cost 
driver analysis are highly relevant to humanitarian aid as both are about ensuring good 
stewardship of resources. However, aid agencies have expressed concerns that the focus on 
costs could lead to a ‘race to the bottom’ that privileges cheaper suppliers and a lack of 
consideration for quality (Stoddard et al., 2017). Also, projects or programs often seek to 
influence multiple aspects of wellbeing which cannot easily be summarized with a single benefit 
measure (food security, income, poverty, health). In such cases, it is advised to list the various 
single outcomes alongside the costs known as cost-consequence analysis (Ahmed et al. 2009; 
Hidrobo et al. 2014; Masset et al. 2018).  

Follow the money: This approach involves the detailed recording of all expenditures at each step 
in the implementation of an intervention (Pongracz et al., 2016). At each step the question is 
asked whether the results could have been obtained with less money, whether it was necessary 
to reach the next level (e.g. output) and what would have been the better alternative (Renard and 
Lister, 2013). It is applicable primarily at the project level. 

Efficiency approach: Conversion of inputs to outputs or ‘cost per beneficiary’, it refers to 
proportion of assistance directly reaching beneficiaries and ratio of programme costs to 
administrative costs (Wheatley and Pongracz, 2014). Cost per beneficiary is calculated by 
dividing the budget of a programme by the number of beneficiaries. The total cost per transfer 
ratio (TCTR) indicates the value of assistance that reaches beneficiaries compared to all other 
costs (often referred to as administrative costs) (White et al., 2013). A ratio of programme costs 
to overhead / administrative costs commonly appears in the public records of aid agencies to 
encourage private donations (e.g. 90 cents out of every dollar donated goes to programmes). 

Cost‑effectiveness analysis (CEA) is applied when benefits cannot be readily monetized. CEA 
provides an approximate unit cost for producing a particular desired output. Unlike CBA, its 
applicability requires comparator programmes that are aiming to produce the same outputs, 
allowing for comparisons of, for example, ‘cost per year of schooling’ under a range of different 
delivery models. CEA lacks the ability to provide an absolute analysis or a standardized metric for 
comparison. It also falls short in addressing uncertainty and equity considerations. Additionally, 
determining appropriate thresholds or target risk levels can be complex and subjective. 

Another study introduced the Omega Value (ratio of in-kind nutrient value per dollar and voucher, 
purchased food nutrient value per dollar) to assess vouchers and in-kind food assistance 
(Ryckembusch et al., 2013). While developed by WFP, this approach has limitations, including a 
lack of consideration for intra-household food distribution and an assumption that cash is 
always spent on food within households.  

To differentiate between vouchers and cash assistance, Hoddinott et al. (2018) conducted a 
randomised trial control. Their study found that in-kind transfers significantly improved 
consumption and dietary quality, while cash transfers were more effective in promoting 



 

5 
 

agricultural investment. This highlights a key trade-off between short-term and long-term 
economic resilience. Bailey (2014) identified several factors that influence the efficiency of 
intervention, including scale, size, frequency and duration of transfers, the delivery mechanism 
and whether cash replaces in-kind aid or supplements it. He also noted a major gap in VfM 
assessments due to the lack of practical tools for analyzing the efficiency and effectiveness of 
cash transfer programs. 

Most existing literature on the cost-effectiveness of cash, voucher, and in-kind food assistance 
points challenges in making direct comparisons. For instance, Gentilini (2007) emphasized the 
influence of context, management, and project objectives on comparison process. Additionally, 
hidden costs, inconsistent accounting methods, and varying budgeting practices can distort cost 
effectiveness calculations (Meyer, 2007). Given these challenges, robust comparison 
frameworks are essential for effective CEA (CRS, 2015). 

A cost-effectiveness analysis (CEA) cannot be conducted without reliable effectiveness data. It 
is essential to ensure that high-quality effectiveness data are available, either through monitoring 
and evaluation systems or from formal program evaluations (ACF-IN, 2013). In practice, it is often 
difficult to obtain data on program effectiveness at the impact level. However, impact data are 
not strictly required to perform a CEA. While decision-makers generally prefer final outcomes, 
intermediate outcomes may be used under certain conditions: (1) The intermediate outcome is 
more directly linked to the intervention than the final outcome (e.g. Example: Using the number 
of fully vaccinated children when the link between vaccination and disease reduction is not yet 
established); (2) The intermediate outcome is directly measurable within the study's time frame, 
whereas the final outcome would occur much later (e.g. Measuring the number of individuals 
who quit smoking in a cessation campaign, since the reduction in lung cancer cases would 
manifest too far in the future); (3) There is no well-established relationship between the 
intermediate and final outcome (e.g. In an HIV risk-reduction program, the number of people 
counseled may be used as the outcome if there is limited evidence linking counseling to actual 
prevention of HIV infections); (4) Cost data for the final outcome are not available or incomplete 
(e g. In a community-based pneumonia treatment program, using the number of households 
reached may be more feasible if the total treatment cost is unknown). In such cases, using 
intermediate outcomes allows the CEA to proceed, provided the limitations are clearly stated 
and the outcomes are meaningfully linked to the intervention. 

Cost Utility Analysis: QALY or DALY 

The cost–utility approach explicitly addresses multiple outcomes by aggregating utilities 
produced by the outcomes. This method can be used where monetizing outcomes is not possible 
or appropriate and appropriate with health projects applying Quality Adjusted Life Years (QALY) 
and Disability Adjusted Life Years (DALY). These indicators allow the comparison of medical 
interventions by the number of years that they extend life. The estimation of an overall utility of 
the intervention assumes knowledge of the utilities associated to each outcome and of the 
functional form used for their aggregation. QALYs and DALYs used by health economists are 
applications of this approach. QALYs and DALYs aggregate all outcomes in terms of life years 
gained weighted by the quality of living under different levels of morbidity and disability. Miller et 
al. (2017) considered non-health benefits to perform CUA. 



 

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The approach is based on the estimation of utility (𝑈) through a utility function specified for 𝑏 
outcomes (𝑏1, 𝑏2 … . . 𝑏𝑛): 𝑈 = 𝑓(𝑢𝑖(𝑏𝑖)). 

The utility so obtained is then used to calculate a Cost Utility Ratio: 𝐶𝑈𝑅 = 𝐶 𝑈⁄             (2). 

Cost–Benefit Analysis (CBA) monetizes all costs and benefits to give an overall benefit‑to‑cost 
ratio – a headline figure that clearly expresses whether benefits have outweighed costs on a 
particular project, and which allows for comparison with other potential investments and their 
respective benefit‑to‑cost ratio. CBA requires all benefits to be monetized, and as such, is often 
limited to projects where targeted returns are largely financial in nature. CBA compares the 
streams of all project benefits 𝐵 =  𝑏1 + 𝑏2 + ⋯ + 𝑏𝑛 and all project costs (𝐶 =  𝑐1 + 𝑐2 + ⋯ + 𝑐𝑛 
), all expressed in monetary terms and discounted over time t at the rate r. (Baird et al. 2011; 
Bernal and Fernández 2013). While CBA offers significant advantages, it primarily focuses on 
efficiency, sometimes overlooking other important criteria such as uncertainty and equity. 
Additionally, it faces challenges in accounting for non-monetized costs and benefits and often 
requires subjective judgment when selecting and appropriate discount rate. 

Social return on investment (SROI) is an innovative framework for measuring and accounting for 
the value generated by interventions or policies. It quantifies the social impact (benefits) of an 
activity in monetary terms and compares this value to the costs required to achieve it. While like 
traditional cost-benefit analysis, SROI is uniquely designed to evaluate socially driven initiatives. 
As James and Faivel (2012) explain, “SROI is specifically tailored to the analysis of social purpose 
activities.” Rooted in principles of social accounting and cost-benefit analysis (Weston and Hong, 
2013), SROI translates significant project outcomes into monetary equivalents, enabling direct 
comparison with input costs (both financial and in-kind). By calculating a benefit-to-cost ratio, 
SROI helps organizations communicate the value added by their projects to external 
stakeholders. 

Rank correlation of cost vs impact: This approach enables the relative measurement of value-
for-money across a portfolio of initiatives. It facilitates comparisons between alternatives with 
differing objectives and is particularly useful for multi-unit programs. Additionally, it supports 
participatory decision-making by engaging stakeholders in identifying and valuing program 
outcomes (Fleming, 2013). 

Basic efficiency resource analysis: It evaluates complex programs by comparing impact 
against resource allocation, offering a relative perspective on performance. Units are 
benchmarked against peer units, simplifying complex data into actionable insights. However, 
BER Analysis should not be used in isolation. It must be combined with complementary data 
sources and analytical methods to ensure robust decision-making (Cugelman and Otero, 2010; 
Fleming, 2013). 

Multi-criteria analysis (MCA): This is a structured approach for evaluating different intervention 
options based on multiple criteria. Each criterion is assigned a weight, and these weights are 
used to calculate an overall score for each option. The intervention with high score, the best it is. 
MCA is particularly useful when only partial data is available, when cultural and ecological factors 
are difficult to quantify, or when monetary benefits and effectiveness are just two among several 
important criteria. It provides a framework to integrate diverse decision factors into a quantitative 



 

7 
 

analysis without requiring monetary values to all factors. The reliability of MCA result depends on 
the certainty of the information used for the selected criteria, the relative importance assigned to 
each criterion (the weights or scores) and the level of stakeholder agreement on these weights. 
Sensitivity analysis can be applied to assess how changes in scores or weights affect the 
robustness of the results (UNFCCC, 2011). MCA is limited by the subjective nature of scoring and 
ranking interventions, making comparisons challenging.  

Several donor agencies have preference for applying specific VfM approach. The World Bank uses 
CBA in developing and managing programmes and is mandated to use this type of analysis to 
determine the economic rate of return (World Bank, 2010). The Network International uses SROI 
for discussing VfM (Fleming, 2013). ADB uses financial analysis and an assessment of the 
financial policies and the capacity of the financial management systems of the borrower or 
executing agency in developing and managing programmes (ADB, 2003). USAID uses results-
based management in addressing Congressional questions on value for money. 

From previous works and particularly based on White et al. (2013) and Tappis and Doocy (2017), 
the Value for Money could be conceptualized as follows: 

Cost Analysis: VfM Involves a descriptive assessment of program costs, including, where 
applicable, additional transaction, opportunity, social, political, or economic costs. 
Cost Efficiency Analysis: VfM Examines the relationship between administrative/program costs 
and outputs, assessing how efficiently resources are converted into deliverables. 
Cost Effectiveness Analysis: VfM evaluates the relationship between program costs and 
outcomes or impacts, comparing alternative approaches to achieving the same results without 
necessarily monetizing outcomes. 
Cost–Benefit Analysis: VfM assesses the relationship between program costs and 
outcomes/impacts expressed in monetary terms, requiring credible valuation of those outcomes 
to determine net economic gain. 

2.4. Choice of VfM analysis methodology 

Economic evaluation provides valuable tools for assessing the costs and consequences of 
resource allocation decisions. These methods systematically identify, measure, value, and 
compare the costs and outcomes of different options (Drummond et al., 2005). While economic 
evaluation methods aim to analyze efficiency, they vary in scope and measurement units. Three 
key approaches include cost-effectiveness analysis (CEA), cost-utility analysis (CUA), and CBA. 
Each has its strengths and limitations. However, based on the TOR objectives and the WFP’s 
previous approach to evaluate projects and programs, this study selects CBA and CEA to assess 
return on investment, the benefit-cost ratio, and Cost-Effectiveness Ratio.  

3. Methodological framework  
Considering the scope of the terms of reference, a multi-levels methodological framework will 
be applied. 

3.1. Farm level  

At the farm level, we will first evaluate the implementation of Food Assistance For Asset (FFA) 
activities and then assess the overall contribution of the IRP at site level. In this study, a site refers 
to villages where one or more interventions have been implemented. Depending on the nature 



 

8 
 

and type of interventions, data will primarily be collected at the household (including farms) and 
village levels.  

For each site, the process will begin by collecting data on: 

➢ the number of beneficiary households within each site 
➢ demographic details including the average of people per household by sex, 
➢ the extent of rehabilitated degraded land (in hectares), 
➢ the area of lowland developed for rice and vegetable production,  
➢ the number of water reservoir built,  
➢ the number of ponds realized, 
➢ the number of micro dams built and number of fertilizer application,   
➢ the area of horticulture, 
➢ the area of moringa reforestation 
➢ the area of reforestation in degraded land, 
➢ the area of irrigated gardens,  
➢ the area of school gardens established, 
➢ the number of fuel-efficient stoves installed, among others. 
➢ Number of innovations or improved agro-practices.  

The rehabilitated land will be disaggregated by crop type according to the standard use, such as 
maize, sorghum, millet, cowpea, groundnut, Bambara groundnut, cotton, sesame, forage etc., 
and the yield or production per hectare will be collected. Different land management practices 
(e.g. zai, half-moon, stone bunds), will also be considered for a more nuanced analysis. 

Additionally, yield data from rice and various vegetables (onions, tomatoes, okra, hibiscus, chili 
peppers, amaranth and vegetable leaf, etc.) produced in both irrigated and school gardens will 
be collected. 

Each crop will be analyzed through farm budget building where all charges (labor, seeds, fertilizer, 
small farming tools, and other farming cost) and related incomes (crop sale, estimation own 
consumption, donation and crop residues) for one hectare exploited will be established. Beyond 
agricultural outputs, we will estimate or record quantities of agroforestry products such as 
firewood and tree pole per hectare. Tables 1, 2 and 3 represent the farm budget structure that will 
be employed during the field data collection, respectively for cropping, fishing, and livestock 
(poultry, small ruminants). See Annex 1, 2 and 3 for details about data collection tools. 

  



 

9 
 

Table 1. Farm budget structure for crop production including agroforestry. 

Intervention 1=Rehabilitation, 2=Lowland developed, 
3=Irrigated land, 4=School Garden 

Crop  
Practices 1=Zai, 2=Half-moon, 3=Stone bunds 
Revenue/income Quantity/unit Unit price Total revenue 

‒ Crop sales    
‒ Fruit trees (Mangoes, Papayas, 

Baobab fruit) 
   

‒ Nuts and seeds (Moringa, 
Shea, Nere) 

   

‒ Firewood from agroforestry    
‒ Tree poles from agroforestry    
‒ Other crop related income 

(residues, medicinal plants) 
non-timber forest product, 
herbaceous and forest seed, 
forestry production. 

   

Costs Description/units Unit cost Total cost 
Variables costs    

‒ Vegetable seeds    
‒ Tree seedlings (Moringa, 

Baobab, Fruit trees) 
   

‒ Inorganic Fertilizers    
‒ Organic fertilizers (Composts 

and manure) 
   

‒ Pesticides    
‒ Nursery establishment    
‒ Labor (land preparation, 

planting, weeding, harvesting, 
application of fertilizer or 
herbicide) 

   

‒ Transport and logistics    
‒ Other variable costs (food)    

Fixed costs    
‒ Land rent or lease    
‒ Drip irrigation system    
‒ Equipment and tool 

depreciation (tractors, hoes, 
watering can, pruning shears) 

   

‒ Repairs and maintenance    
‒ Other fixed expenses    

 

  



 

10 
 

Farm fishing budget/per cycle / year 

Table 2. Structure of farm fishing budget (data will be collected yearly per cycle) 

Costs Description/unit Unit cost Total cost 
Fixed cost    

‒ Pond construction    
‒ Borehole     
‒ Pompe     
‒ Irrigation canals    
‒ Nets    
‒ Aerators     
‒ Feeders    
‒ Testing kits    
‒ Fish storage    
‒ Smoking/drying equipment     

Variable costs    
‒ Fingerlings (juvenile fish: Tilapia, 

Catfish) 
   

‒ Fish feed    
‒ Labor (workers’ salaries)    
‒ Pond maintenance (repairs, water 

quality management) 
   

‒ Medicine and disease control    
‒ Transportation and marketing    

Revenue  Description or unit Unit price Total 
revenue 

‒ Fish sales     
‒ By-products (fish waste like organic 

fertilizer, animal feed) 
   

 

Contribution of forage availability for livestock in each site will be estimated through triangulation 
among pastoralists and small-scale breeders comparing the additional net profit that they could 
be attributed to IRP interventions.  

 

  



 

11 
 

Table 3: Structure of livestock budget 

Cows, Goats, sheep Description/unit Unit cost Total cost 
Total initial investment Depreciation    
Purchase price per animal    
Housing/Shelter    
Equipment (feeders, waterers)    
Operating costs Description/unit Unit cost Total cost 
Feed & supplements (seasonal feeding, 
dry season support) 

   

Veterinary/ health care (vaccines, 
deworming, basic treatment) 

   

Labor (daily care, herding, feeding, 
watering) 

   

Family labor    
Water access    
Breeding/AI services    
Transport    
Miscellaneous (admin fees)    
Revenue Description or unit Unit price Total 

revenue 
Offspring sold (calves, kids, lambs)    
Conservative estimates     
Milk sales (if applicable)    
Manure/Soil fertility/compost    

 

Finally, the evaluation will consider the intangible benefits of FFA, including positive 
environmental impacts (carbon sequestration, soil fertility improvement, etc.) and improvement 
in beneficiary wellbeing (cost of malnutrition and health averted).  

The financial analysis will be converted to economic one by using the standard conversion factor. 
The analysis of FFA will be used as inputs for CBA, particularly the gross revenue will represent a 
component of benefits in IRP analysis.  

To accurately assess the livelihood improvements associated with Asset creation and land 
rehabilitation (land and water management, LWM), it is essential to consider the flow of costs 
and benefits over the evaluation period (T) assuming to be 151 years. This will be done by 
calculating the net present value (NPV) for both non-LWM and the LWM systems, as outlined in 
Equations 1 and 2. The overall net benefits of using the LWM farming system will then be 
determined by the difference between the two (Equation 3). 

𝐵𝑒𝑛𝑒𝑓𝑖𝑡𝑡 = 

𝑁𝑃𝑉𝑛𝑜𝑛−𝐿𝑊𝑀 = ∑ 𝑛𝑒𝑡 𝑐𝑟𝑜𝑝 𝑟𝑒𝑣𝑒𝑛𝑢𝑒𝑡/(1 + 𝑟)𝑡

𝑡
+ ∑ 𝑛𝑒𝑡 𝑜𝑡ℎ𝑒𝑟 𝑟𝑒𝑣𝑒𝑛𝑢𝑒𝑡/(1 + 𝑟)𝑡

𝑡
     (3) 

 
1 As applied for several interventions due practical and theoretical way (FAO et al., 2021) 



 

12 
 

𝑁𝑃𝑉𝐿𝑊𝑀 = ∑
𝑛𝑒𝑡 𝑐𝑟𝑜𝑝 𝑟𝑒𝑣𝑒𝑛𝑢𝑒𝑖𝑡

(1 + 𝑟)𝑡
𝑡

+ ∑
𝑛𝑒𝑡 𝑜𝑡ℎ𝑒𝑟 𝑟𝑒𝑣𝑒𝑛𝑢𝑒𝑖𝑡

(1 + 𝑟)𝑡
𝑡

− ∑
𝐿𝑊𝑀 𝑖𝑚𝑝𝑙𝑒𝑚𝑒𝑛𝑡𝑎𝑡𝑖𝑜𝑛 & 𝑚𝑎𝑛𝑎𝑔𝑒𝑚𝑒𝑛𝑡 𝑐𝑜𝑠𝑡𝑡

(1 + 𝑟)𝑡
𝑡

   (4) 

 

∆𝑁𝑃𝑉 = 𝑁𝑃𝑉𝐿𝑊𝑀 − 𝑁𝑃𝑉𝑛𝑜𝑛−𝐿𝑊𝑀 (5) 

The return on investment will be calculated using the following formulas 

𝑅𝑂𝐼𝐹𝐹𝐴 =
𝐵𝑒𝑛𝑒𝑓𝑖𝑡 𝑜𝑟 𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝐹𝐹𝐴  − 𝐶𝑜𝑠𝑡𝐹𝐹𝐴

𝐶𝑜𝑠𝑡𝐹𝐹𝐴
      (6) 

 

3.2. Cost Benefit Analysis for IRP at site 

For IRP analysis at the site level, all costs and benefits will be first identified for each intervention. 
These interventions include asset creation for land restoration and natural resources 
conservation, Reducing Post-Harvest loss and development of value chains, Capacity 
strengthening, Nutrition, and School feeding. Most of the required data will be sourced from 
country offices through specific surveys, M&E reports and dataset. Additional information will 
also be collected through focus group discission to ensure data completeness, triangulation, and 
validation. 

The “with and without” scenario will be used in identifying the costs and benefits. Only costs and 
benefits resulting from the interventions will be identified and those that would have still taken 
place even without the interventions will be ignored. Thus, only incremental costs and benefits 
arising from the interventions will be considered.  

3.2.1. Cost of IRP 

Beyond administrative and management cost, which will be integrated at the overall intervention 
level, site-specific investments will be assessed across the five IRP components. These costs 
will generally fall into three categories: fixed costs, operational costs and social2 and 
environmental costs. Fixed costs will include expenses related to beneficiary training, equipment 
and installation, initial inputs (such as fertilizers, seedlings, cash capital, etc.), project planning, 
implementation and monitoring. Operation costs will cover ongoing expenses such as 
maintenance, raw materials and supplies, monitoring, security, and replacement of short-life 
equipment. Even if they are not considered for this study, social costs generally account for 
potential losses in social benefits resulting from intervention, while environmental costs will 
consider potential negative impacts, including water quality deterioration, soil and land 
degradation, and pollution. These costs will be allocated to each component or intervention at 
site level. In cases where is not feasible, a weighted approach will be applied based on 
stakeholder feedback triangulation. 

 
2 A social cost is a net loss of social benefit incurred due to the introduction of a particular project or 
intervention, such as failure by a community to access a natural resource (e.g. firewood) previously enjoyed by 
the community without the project. 



 

13 
 

2.2.1.1. Asset creation for land restoration and natural resources conservation 

The cost associated with this component will include expenses for sustainable land and water 
management, community gardens, boreholes installation with solar pumps, and rehabilitation 
of feeder roads, traits, and dikes. A key cost consideration will be households’ transfers, 
factoring in the number of beneficiary households, the duration of transfers per year, and the 
total number of years the transfers are made. Cost Adjustments will be accounted for increased 
inputs such as seeds, labor, and machinery costs while factoring in the overall productivity 
boost. 

2.2.1.2. Smallholder Farmers Access to Market support 

Costs under this component will include expenses for farmer training, warehouse rehabilitation, 
investment in solar equipment, and maintenance. Relevant data will cover the number of farmers 
trained, the number of warehouses rehabilitated, and the percentage and value of post-harvest 
losses prevented. Agricultural and livestock inputs (improved seeds, fertilizers, etc.) distributed 
or subsidized, shared tools and machine support for groups will be accounted for cost of 
Smallholder Farmers Access to Market support (SAMs) interventions.  

2.2.1.3. Capacity strengthening 

This component will focus on vocational capacity building, sustainable management practices, 
leadership development, income-generating activities, and land restoration capacity building. 
Associated costs will include trainer fees, venue rentals, material purchases, participants 
transportation, allowance, and other relevant expenditures. Data collection will consider the 
number of participants and community size, training duration, and the year of implementation 
for each sub-component. 

2.2.1.4. Nutrition 

Nutrition-related costs will include expenses for malnutrition prevention, treatment of moderate 
malnutrition, provision of locally fortified/improved food for vulnerable groups, SBCC initiatives, 
and support for nutrition education sessions in GASPA. Apart from logistics and food transport 
cost, key cost elements will include RUTF, medical supplies, health facilities, therapeutic 
feeding centres: Personnel devoted to food assistance-related activities (or % staff time); Staple 
rations + storage & Transport; Value of beneficiary time spent traveling to, waiting for and 
attending distributions; Value of beneficiary time traveling to and waiting at health centres for 
malnutrition treatment; Value of distribution sites; Value of time spent by community leaders in 
beneficiary selection; Equipment & Supplies, including materials for distributing rations and 
building distribution sites; Personnel devoted to additional activities related to RUSF (or % staff 
time), and its management and logistics; RUSF sachets used in program + storage & transport; 
medical & anthropometric equipment; Program support costs (Puett et al., 2013). Data will be 
collected from country offices on the number of beneficiary households, per capita food supply, 
and other relevant metrics. 

2.2.1.5. School feeding 

Costs in this component will cover school meals provision, installation of school gardens 
(including various inputs and materials), rehabilitation of school kitchen, and canteen equipment 
such as fuel-efficient stoves. Data will focus on the numbers of students affected, quantity and 
cost of food supplied per student, training and capacity building expenses for school gardens, 



 

14 
 

infrastructure investments, etc. They also include value of commodities (food given or 
purchased), transport (international and landside transportation, storage and handling), 
operational costs (staff, vehicles and facilities), and overhead costs. 

3.2.2. Benefit of IRP 

Both tangible and intangibles benefits that enhance the resilience of communities will be 
assessed. Tangible benefits include measurable financial gains such as increased revenues 
from improved agricultural production, while intangible benefits encompass social and 
environmental gains, such as knowledge acquisition, and gains from environmental and natural 
resources conservation, that are more challenging to quantify.  

2.2.2.1. Asset creation for land restoration and natural resources conservation 

This component focuses on the establishment of soil and water management practices and 
conservation initiatives. The first Benefits consideration will be about the net profit of 
agricultural, fishing, agroforestry and livestock practices. They will be calculated per household 
based on the number of beneficiaries and average gains per household. 

Productivity Gains: This benefit will be drawn from farm budgets established for FFA (see farm 
budgets for different sectors). 

Time Savings: Quantifying and valuing reductions in transport time for goods, access to fields, 
and services such as health, education, and communication due FFA implementation. 

Environmental Benefits: quantifying and estimating value of increases in soil fertility, reductions 
in topsoil loss and nutrient depletion, enhanced water storage, reduced runoff, carbon 
sequestration (Gordon et al., 2020), and biodiversity improvements. 

𝐵𝑒𝑛𝑒𝑓𝑖𝑡𝑡
𝐶𝑜𝑢𝑛𝑡𝑟𝑦

= 𝐻𝑐𝑟𝑜𝑝[𝐶𝑂2𝑈𝑟𝑒𝑎(𝑈𝐶𝑟𝑜𝑝,𝑔𝑎𝑝
𝑤𝑖𝑡ℎ − 𝑈𝑐𝑟𝑜𝑝) +  𝐶𝑂2𝐷𝐴𝑃(𝐷𝐶𝑟𝑜𝑝,𝑔𝑎𝑝

𝑤𝑖𝑡ℎ − 𝐷𝑐𝑟𝑜𝑝)] ∗

𝑆𝐶𝐶𝑐𝑜𝑢𝑛𝑡𝑟𝑦 ∗ 𝐸                                   (7)                                                                                      

𝐻𝑐𝑟𝑜𝑝 Land area 
𝐶𝑂2𝑈𝑟𝑒𝑎  CO2 per kg of Urea fertilizer 
𝐶𝑂2𝐷𝐴𝑃 CO2 per kg of DAP fertilizer 
𝑈𝑐𝑟𝑜𝑝  Kg of Urea used at Baseline 
𝐷𝑐𝑟𝑜𝑝  Kg of DAP used at Baseline 

𝑈𝐶𝑟𝑜𝑝,𝑔𝑎𝑝
𝑤𝑖𝑡ℎ  Kg of Urea used under FFA 

𝐷𝐶𝑟𝑜𝑝,𝑔𝑎𝑝
𝑤𝑖𝑡ℎ  Kg of DAP used under FFA 

𝑆𝐶𝐶𝑐𝑜𝑢𝑛𝑡𝑟𝑦 Country level Social cost of Carbon 
𝐸 Real Exchange Rate 

 

Due to land rehabilitation, the conflict about land and reducing outflow of able-bodied workers 
will be reduced and it will be valued as benefit for IRP.  

2.2.2.2. Reducing Post-Harvest loss and development of value chains: SAMs 

This segment evaluates the efficiency improvements achieved through: 

Productivity Enhancements: quantifying and valuing yield improvements and the reduction in 
post-harvest losses (PHL) due to advanced conservation/storage practices and technologies. 



 

15 
 

Market Integration: Assess additional profits from shifts toward higher-value cropping systems, 
increased access to agricultural market, and the stimulation of private investments driven by the 
implementation (see annex 4 and 5). 

2.2.2.3. Capacity strengthening 

The IRP arm aims to empower local communities by reinforcing other components, achieving 
their potential. Benefits from this component will be captured as follows: 

- Training and Skill Development: Measuring and valuing its contribution to the improvement 
in agricultural practices, natural resource management, and technical skills, as well as 
income opportunity generating. Knowledge acquired will be valued using Abelson (2007) 
approach where he attributed percentages to the training cost to obtain the training benefit 
for different beneficiary levels. Thus, benefit represents 10%, 20% and 30% respectively for 
individual, individual and households, individual, households and communities (FAO et al., 
2021). 

- Institutional Strengthening: Evaluating and valuing its support to the increased capacity of 
local institutions to manage and sustain agricultural innovations and resilience strategies. 

2.2.2.4. Nutrition  

The nutrition intervention within the IRP could generate a wide range of measurable benefits, 
contributing to both immediate and long-term improvements in health, productivity, and 
economic outcomes. These benefits will be quantified based on the number of beneficiaries and 
the estimated value per beneficiary across several key dimensions: 

− Improved Hygiene and Time Savings: Enhanced hygiene practices and reduced time 
spent collecting water lower the incidence of waterborne diseases and free up time, 
resulting in increased productive labor days. 

− Prevention of Malnutrition in Vulnerable Groups: Targeting children under five and 
pregnant or lactating women, the intervention aims to prevent malnutrition. Benefits will 
be calculated based on healthcare cost savings and enhanced well-being. (Total 
admission, recovery, defaulters, non-response, death with treatment, defaulters’ death, 
non-response death; number of deaths without treatment; deaths averted yearly);  

− Reduction in Disease Incidence and Healthcare Costs: fewer and less severe illnesses 
among beneficiaries will lead to direct savings in healthcare expenditures. 

− Treatment of Acute Malnutrition: The number of individuals treated for acute malnutrition 
and the economic value of lives saved and health will be quantified. 

− Lowering Mortality Rates: A decrease in mortality among vulnerable groups will be 
assessed by the economic value of lives saved.  

− Strengthening Local Health Systems: Improvements in system capacity and service 
delivery will enhance community health outcomes and contribute to long-term 
resilience, with benefits valued accordingly. 

2.2.2.5. School feeding 

This component of IRP could yield several benefits including: Value Transfer to the Household 
(the value of the food received, and the healthcare expenditures avoided due to the children’s 
better health); Return on Investment on Saved Assets; Increased Productivity of the Beneficiary 



 

16 
 

(increased school attendance); Healthier and Longer Life; and Externalities (lower costs for 
government or community benefits), gender equity. In monetary terms, the study will adopt the 
benefit framework developed by WFP and MasterCard (2016), which allocates the total benefits 
as follows: 12% for value transfers or access to food and healthcare services, 8% for improved 
health and increased life expectancy, 4% for return on investment, and 67% (6-25% of variation) 
for gains in productivity. 

2.2.2.6. Global benefit 

Transversally, the benefit of IRP will consider reduction of debt burden, increased solidarity, jobs 
creation, floods protection, recharge of water table, and other tangible and intangible benefits 
will be considered. 

 

3.2.3. Indicators of CBA  

Three indicators for a time span of 15 years (2018-2032) including NPV, BCR and IRR using # 
social discount rate (see Excel file : IRP_CBA).  

𝑁𝑃𝑉𝐼𝑅𝑃 = ∑
𝐵𝑒𝑛𝑒𝑓𝑖𝑡𝐼𝑅𝑃𝑡

− 𝐶𝑜𝑠𝑡𝐼𝑅𝑃𝑡

(1 + 𝑟)𝑡

𝑁

𝑡=0

     (8) 

𝑩𝑪𝑹 = 𝐵𝑒𝑛𝑒𝑓𝑖𝑡𝐼𝑅𝑃 𝑃𝑉 𝐶𝑜𝑠𝑡𝐼𝑅𝑃𝑃𝑉 ⁄      (9) 

 

𝑁𝑃𝑉𝐼𝑅𝑃 = ∑
𝐵𝑒𝑛𝑒𝑓𝑖𝑡𝐼𝑅𝑃𝑡

− 𝐶𝑜𝑠𝑡𝐼𝑅𝑃𝑡

(1 + 𝑰𝑹𝑹)𝑡

𝑁

𝑡=0

= 0                  (10) 

Where:  

• NPV (Net Present Value): The difference between the present value of benefits and the 
present value of costs over the analysis period. 

• PV (Present Value): The current worth of a future stream of benefits or costs, discounted at 
a specified rate. 

• BCR (Benefit-Cost Ratio): The ratio of the present value of benefits to the present value of 
costs, used to assess economic efficiency. 

• IRR (Internal Rate of Return): The discount rate at which the net present value of an 
investment becomes zero, reflecting the project's rate of return. 

• t (Time): The time period or horizon over which the analysis is conducted. 
• IRP (Integrated Resilience Program): The program under assessment, comprising multiple 

interventions aimed at strengthening resilience. 
• r (Discount Rate): The rate used to discount future costs and benefits to their present values. 

There is currently no consensus on the appropriate social discount rate for evaluating social and 
environmental projects in the central Sahel. Reported rates vary widely—for example, 12% for the 
Sahel (IDG, 2018), 3.9–5% (WFP, 2024), 10% for Benin (WFP, 2019), 7% for Ghana (Dunaev and 
Corona, 2019), and 5–10% (Westerberg et al., 2019). Since a social discount rate reflects either 
society’s time preference for money or the social opportunity cost of capital, it is generally 
expected to be lower than market (private or commercial) rates (FAO et al., 2021). A rate of 6% 



 

17 
 

has been suggested as appropriate for social investments (Maradan, 2017). At USAID, the 
convention is to apply a 12% rate for economic analyses, while the financial analysis uses a rate 
aligned with the cost of capital, typically reflecting the prevailing interest rate in the intervention 
area (Schubert, 2020). For the purposes of this study, a 10% discount rate will be used for Food 
Assistance for Assets (FFA) analysis, and a 5% social discount rate will be applied to Integrated 
Resilience Programming (IRP) interventions at the site level. Sensitivity analysis will also be 
realized considering different levels of social discount rate (3%, 7% and 10%).  

 

  



 

18 
 

Table 4: Summary of IRP costs and Benefits 

Components  Cost  Benefit  
Food 
Assistance 
For Asset 

Transfer to households Revenue from agriculture  
Equipment  Revenue from livestock 
Machinery Revenue from fishing 
Farming tools Revenue from agroforestry  
Specialist for field work (agronomists, 
technicians) 

Valorization of time saving 
(transport goods, access to 
fields and services) Boreholes installation 

Solar pumps 
Additional cost for feed road rehabilitation Environment benefit  
Additional cost for trait rehabilitation Value of hardship reduction  
Additional cost for dike rehabilitation Reduction of land conflict 
Seed distributed Environmental service  
Seedling distributed Carbon sequestration 
Additional labor  

 
SAMs 

Training costs Value of PHL prevented 
Warehouse building  
Solar equipment  Benefit of market integration 
Maintenance of equipment Value of compost production 
Improved seed distributed  
Fertilizer distributed   
Subsidized farm inputs  

Capacity 
strengthening  

Trainer fees Training and skill 
development valuation Venue rentals 

Training materials Value of local institution 
Participant transports  
Allowance  
Other expenditures  

Nutrition  Logistics Hygiene and time saving 
value Management  

Food transports Healthcare cost averted 
Storage Welfare value 
RUTF (ready to use therapeutic food) Lived saved  
Medical Value of health restored 
Heath facilities  
Therapeutic feeding center  
Personal related cost  
Anthropometric equipment  

School 
feeding 

Meals/food supplies  Value 
transfer/food/healthcare Installation of school garden 

Rehabilitation/construction of kitchen Productivity increased 
Canteen equipment  Healthier and long life 
Stoves fees Externalities  
Training capacity building cost Saved assets 
Transport  
Storage  
Overhead   

 



 

19 
 

3.3. Cost Effectiveness Analysis 

Regarding the availability of project or intervention documents (e.g. endline survey reports, 
baseline survey reports, external evaluation reports, final project/program reports, annual 
results reports, indicator tracking reports, and narrative reports), the Cost Effectiveness Analysis 
will examine indicators related to food assistance, health, and resilience. For food assistance, 
the indicators include Food consumption score, Livelihood based Coping Strategy Index LCSI, 
Household dietary Diversity Score, Reduced coping Strategy Index, Household hunger scale, 
household economy approach, and poverty gap (USAID, 2020). Health indicators will focus on 
the number of individuals whose health improved, cases of death or sickness averted. Resilience 
will be assessed based on the improvement or reinforcement at the individual or household level.  

Following Cochran et al. (2024), the cost effectiveness ratio is expressed as follow:  

𝐶𝐸𝑅𝑖 =
𝑇𝑜𝑡𝑎𝑙 𝐼𝑅𝑃𝑐𝑜𝑚𝑝𝑜𝑛𝑒𝑛𝑡 𝑐𝑜𝑠𝑡𝑠𝑖

𝑂𝑢𝑡𝑐𝑜𝑚𝑒 𝑚𝑒𝑎𝑠𝑢𝑟𝑒𝑖
                  (11)  

with 𝑖 represents the single intervention to yield 𝑜𝑢𝑡𝑐𝑜𝑚𝑒 𝑚𝑒𝑎𝑠𝑢𝑟𝑒 

For each outcome indicator, the difference or gain attributable to the IRP will be calculated using 
baseline or midline values as a reference. Endline values will be scaled up to reflect changes over 
time in both the intervention and control areas. 

𝑂𝑢𝑡𝑐𝑜𝑚𝑒𝑡,𝑖,𝑗 = 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒_𝑂𝑢𝑡𝑐𝑜𝑚𝑒𝑡,𝑖,𝑗 − 𝑚𝑖𝑑𝑙𝑖𝑛𝑒 𝑜𝑟 𝑒𝑥𝑡𝑟𝑎𝑝𝑜𝑙𝑎𝑡𝑒_𝑂𝑢𝑡𝑐𝑜𝑚𝑒𝑡,𝑖,𝑗                (12)  

𝑂𝑢𝑡𝑐𝑜𝑚𝑒𝑐,𝑖,𝑗 = 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒_𝑂𝑢𝑡𝑐𝑜𝑚𝑒𝑐,𝑖,𝑗 − 𝑚𝑖𝑑𝑙𝑖𝑛𝑒 𝑜𝑟 𝑒𝑥𝑡𝑟𝑎𝑝𝑜𝑙𝑎𝑡𝑒_𝑂𝑢𝑡𝑐𝑜𝑚𝑒𝑐,𝑖,𝑗                (13)  

𝑂𝑢𝑡𝑐𝑜𝑚𝑒𝐼𝑅𝑃𝑖,𝑗
= 𝑂𝑢𝑡𝑐𝑜𝑚𝑒𝑡,𝑖,𝑗 − 𝑂𝑢𝑡𝑐𝑜𝑚𝑒𝑐,𝑖,𝑗                                          (14) 

Where t and c represent the situations with and without the IRP, respectively, and j denotes the 
outcome indicators (food security, health, school, malnutrition, capacity building, climate 
change indicators). 

Based on available monitoring and evaluation systems and existing evaluation reports, we will 
review and identify relevant outcomes indicators that can serve as the principal indicators for 
each intervention (Table 5; Annex 4 and 5). 

4. Data collection approach 
Given the nature of the study, most data will be sourced from existing project-level datasets and 
documentation. Secondary data will be obtained from available materials related to the project’s 
monitoring and evaluation (M&E) system. These include periodic progress reports, budget 
execution files, and impact evaluation documents such as baseline, midline, and endline 
studies. This existing documentation will provide foundational quantitative and qualitative 
information for conducting both cost-benefit analysis (CBA) and cost-effectiveness analysis 
(CEA). 

To complement this secondary data, national consultants will carry out targeted visits to relevant 
reference institutions, such as health centers, schools, and research institutes, to gather 
additional contextual or technical data required for accurate modeling. 



 

20 
 

Primary data collection will focus specifically on the development of representative farm 
budgets across various productive sectors, including crop farming, livestock, and fishing. Within 
crop production, attention will be given to major crops such as sorghum, millet, maize, cowpea, 
vegetables, and rice. The analysis will also consider different land management and restoration 
techniques (e.g., half-moons, zai pits, stone bunds) and types of land development (e.g., 
degraded land restoration, lowland rehabilitation, irrigated gardens, and school gardens). 

Rather than conducting household surveys or structured individual interviews, primary data will 
be collected through focus group discussions (FGDs) with key informants and beneficiary 
representatives. These discussions will be organized to co-develop detailed farm budgets for 
each sector, crop type, and land management practice. Depending on logistical feasibility and 
local conditions, two-day workshops may be organized at central locations to facilitate in-depth 
discussions and consensus-building among stakeholders. 

The data collection process will apply standardized units to ensure consistency and 
comparability across sites. This includes estimating costs and revenues per hectare of cultivated 
land, per head of livestock, or per standard fishing unit. These standardized farm budgets will 
serve as critical inputs for the CBA and CEA models. 

 



 

21 
 

Table 5: Different outcomes for each intervention used for CEA 

  Without IRP With IRP Outcom
es IRP 

Components Indicators 
Sta
rt 

Reference 
year 

Sta
rt 

Reference 
year 

Food 
Assistance 

For Asset 

Percentage of the population in targeted communities reporting benefits from an 
enhanced livelihood asset base       
Percentage of FFA supported assets that demonstrate improved vegetation and soil 
conditions      
Proportion of the population in targeted communities reporting environmental benefits      

Smallholder 
farmers 

Access To 
Market 
support 
(SAMs) 

Value and volume of smallholder sales through WFP-supported aggregation systems      
Average percentage of smallholder post-harvest losses at the storage stage      
Percentage of targeted smallholder farmers reporting increased production of nutritious 
crops      
Percentage of targeted smallholder farmers selling through WFP-supported farmer 
aggregation systems      

Capacity 
Strengtheni

ng 

Transition strategy for school health and nutrition and school feeding developed with 
WFP support       
Number of national policies, strategies, programmes and other system components 
contributing to zero hunger and other SDGs enhanced with WFP capacity strengthening 
support        
Number of national policies, strategies, programmes and other system components 
relating to school health and nutrition/including school feeding enhanced/developed 
with WFP capacity strengthening support      
Number of new or adapted policies and legislative instruments contributing to zero 
hunger and other SDGs endorsed with WFP capacity strengthening support      

Nutrition 

Proportion of eligible population reached by nutrition preventive programme (coverage)       
Proportion of target population who participate in an adequate number of distributions 
(adherence)      
Proportion of children 6–23 months of age who receive a minimum acceptable diet 
(MAD)      
Minimum diet diversity for women and girls of reproductive age (MDD-W)       



 

22 
 

Percentage of moderate acute malnutrition (MAM) cases reached by treatment services 
(coverage)       
Moderate acute malnutrition (MAM) treatment performance rate (recovery, mortality, 
default and non-response)        
Default rate of clients from anti-retroviral therapy, tuberculosis directly observed 
treatment (TB-DOTS) and prevention of mother-to-child transmission of HIV (PMTCT) 
programmes      

School 
Feeding 

Retention rate/drop-out rate (by grade)      
Attendance rate (complementary with UNICEF, UNESCO, World Bank)      
Enrolment rate      
Graduation/completion rate (complementary with UNICEF, UNESCO and the World 
Bank)      
Systems Approach for Better Education Results (SABER) school feeding index      

Transversal outcomes 

Food 
Security and 

essential 
needs 

Food consumption score       
Consumption-based coping strategy index, reduced CSI (rCSI)       
Livelihood coping strategies for food security (LCS-FS)       
Economic capacity to meet essential needs       
Livelihood coping strategies for essential needs (LCS-EN)       
Food consumption score – nutrition      

Actions to 
protect 
against 
climate 
shocks 

Climate adaptation benefit score       
Climate resilience capacity score       
Climate services score      

Investment capacity index      
 

 



   
 

23 
 

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27 
 

Annex : Data collection tools 
Annex 1. BAU, Zai, Stone bunds, Half-moon, Lowland developed, Irrigated gardens and school 
gardens 
Annex 1.1. Land used for crop, vegetable, agroforestry and tree  
For each crop and land development technique, data will be collected during interview with CO 
representative farmers within each site 

Area developed and farmed (ha) Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 
Sorghum           
Millet           
Maize           
Cowpea           
Groundnut           
Bambara ground nut           
Sesame           
Cotton           
Rice           
Onions           
Tomatoes           
Okra           
Hibiscus           
 Chili peppers           
Amaranth           
Vegetable leaf           
Mango           
Papaya           
Baobab           
Moringa           
Nere           
Shea           
Agroforestry firewood           
Agroforestry tree poles           
Timber tree           
Crop1           
Crop2           
Crop3           
Crop4           
Crop5           
Vegetable1           
Vegetable2           
Vegetable3           
Tree planting1            
Tree planting2           
Tree planting3           

 
 
 
  



   
 

28 
 

Annex1.2. Crop, Vegetable, Agroforestry and Tree production per ha 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Product Subproduct 
Crop/vegetable/tree Unit Quantity  Farmgate 

price 
Unit  Quantity Farmgate 

price 
Sorghum       
Millet       
Maize       
Cowpea       
Groundnut       
Bambara ground nut       
Sesame       
Cotton       
Rice       
Onions       
Tomatoes       
Okra       
Hibiscus       
 Chili peppers       
Amaranth       
Vegetable leaf       
Mango       
Papaya       
Baobab       
Moringa       
Nere       
Shea       
Agroforestry firewood       
Agroforestry tree poles       
Timber tree       
Crop1       
Crop2       
Crop3       
Crop4       
Crop5       
Vegetable1       
Vegetable2       
Vegetable3       
Tree planting1        
Tree planting2       
Tree planting3       

 
 



   
 

29 
 

Annex 1.3. Input for Crop, Vegetable, Agroforestry and Tree production per ha 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Inorganic fertilizer Organic fertilizer 
Crop/vegetable/tree Unit Quantity  Price Unit  Quantity Price 
Sorghum       
Millet       
Maize       
Cowpea       
Groundnut       
Bambara ground nut       
Sesame       
Cotton       
Rice       
Onions       
Tomatoes       
Okra       
Hibiscus       
 Chili peppers       
Amaranth       
Vegetable leaf       
Mango       
Papaya       
Baobab       
Moringa       
Nere       
Shea       
Agroforestry firewood       
Agroforestry tree poles       
Timber tree       
Crop1       
Crop2       
Crop3       
Crop4       
Crop5       
Vegetable1       
Vegetable2       
Vegetable3       
Tree planting1        
Tree planting2       
Tree planting3       

 
 



   
 

30 
 

Annex 1.4. Input for Crop, Vegetable, Agroforestry and Tree production per ha 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Herbicide Pesticide 
Crop/vegetable/tree Unit Quantity  Price Unit  Quantity Price 
Sorghum       
Millet       
Maize       
Cowpea       
Groundnut       
Bambara ground nut       
Sesame       
Cotton       
Rice       
Onions       
Tomatoes       
Okra       
Hibiscus       
 Chili peppers       
Amaranth       
Vegetable leaf       
Mango       
Papaya       
Baobab       
Moringa       
Nere       
Shea       
Agroforestry firewood       
Agroforestry tree poles       
Timber tree       
Crop1       
Crop2       
Crop3       
Crop4       
Crop5       
Vegetable1       
Vegetable2       
Vegetable3       
Tree planting1        
Tree planting2       
Tree planting3       

 
 



   
 

31 
 

Annex 1.5. Input for Crop, Vegetable, Agroforestry and Tree production per ha 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Improved seed Local seed 
Crop/vegetable/tree Unit Quantity  Price Unit  Quantity Price 
Sorghum       
Millet       
Maize       
Cowpea       
Groundnut       
Bambara ground nut       
Sesame       
Cotton       
Rice       
Onions       
Tomatoes       
Okra       
Hibiscus       
 Chili peppers       
Amaranth       
Vegetable leaf       
Mango       
Papaya       
Baobab       
Moringa       
Nere       
Shea       
Agroforestry firewood       
Agroforestry tree poles       
Timber tree       
Crop1       
Crop2       
Crop3       
Crop4       
Crop5       
Vegetable1       
Vegetable2       
Vegetable3       
Tree planting1        
Tree planting2       
Tree planting3       

 



   
 

32 
 

Annex1.6. Labor for Crop, Vegetable, Agroforestry and Tree production per ha: Fertilizer 
application 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Inorganic fertilizer application Organic fertilizer application 
Crop/vegetable/tree Unit Quantity  Price Unit  Quantity Price 
Sorghum       
Millet       
Maize       
Cowpea       
Groundnut       
Bambara ground nut       
Sesame       
Cotton       
Rice       
Onions       
Tomatoes       
Okra       
Hibiscus       
 Chili peppers       
Amaranth       
Vegetable leaf       
Mango       
Papaya       
Baobab       
Moringa       
Nere       
Shea       
Agroforestry firewood       
Agroforestry tree poles       
Timber tree       
Crop1       
Crop2       
Crop3       
Crop4       
Crop5       
Vegetable1       
Vegetable2       
Vegetable3       
Tree planting1        
Tree planting2       
Tree planting3       

 
 



   
 

33 
 

Annex 1.7. Labor for Crop, Vegetable, Agroforestry and Tree production per ha: Herbicide and 
pesticide applications 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Herbicide application Pesticide application 
Crop/vegetable/tree Unit Quantity  Price Unit  Quantity Price 
Sorghum       
Millet       
Maize       
Cowpea       
Groundnut       
Bambara ground nut       
Sesame       
Cotton       
Rice       
Onions       
Tomatoes       
Okra       
Hibiscus       
 Chili peppers       
Amaranth       
Vegetable leaf       
Mango       
Papaya       
Baobab       
Moringa       
Nere       
Shea       
Agroforestry firewood       
Agroforestry tree poles       
Timber tree       
Crop1       
Crop2       
Crop3       
Crop4       
Crop5       
Vegetable1       
Vegetable2       
Vegetable3       
Tree planting1        
Tree planting2       
Tree planting3       

 



   
 

34 
 

Annex 1.8. Labor for Crop, Vegetable, Agroforestry and Tree production per ha: Sowing and land 
preparation 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Sowing Land preparation 
Crop/vegetable/tree Unit Quantity  Price Unit  Quantity Price 
Sorghum       
Millet       
Maize       
Cowpea       
Groundnut       
Bambara ground nut       
Sesame       
Cotton       
Rice       
Onions       
Tomatoes       
Okra       
Hibiscus       
 Chili peppers       
Amaranth       
Vegetable leaf       
Mango       
Papaya       
Baobab       
Moringa       
Nere       
Shea       
Agroforestry firewood       
Agroforestry tree poles       
Timber tree       
Crop1       
Crop2       
Crop3       
Crop4       
Crop5       
Vegetable1       
Vegetable2       
Vegetable3       
Tree planting1        
Tree planting2       
Tree planting3       

 
 



   
 

35 
 

Annex 1.9. Labor for Crop, Vegetable, Agroforestry and Tree production per ha: Weeding and 
harvesting 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Weeding  Harvesting 
Crop/vegetable/tree Unit Quantity  Price Unit  Quantity Price 
Sorghum       
Millet       
Maize       
Cowpea       
Groundnut       
Bambara ground nut       
Sesame       
Cotton       
Rice       
Onions       
Tomatoes       
Okra       
Hibiscus       
 Chili peppers       
Amaranth       
Vegetable leaf       
Mango       
Papaya       
Baobab       
Moringa       
Nere       
Shea       
Agroforestry firewood       
Agroforestry tree poles       
Timber tree       
Crop1       
Crop2       
Crop3       
Crop4       
Crop5       
Vegetable1       
Vegetable2       
Vegetable3       
Tree planting1        
Tree planting2       
Tree planting3       

 
 



   
 

36 
 

Annex 1.10. Transport and logistics, Vegetable, Agroforestry and Tree production per ha 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Transport  Logistic and other costs 
Crop/vegetable/tree Description  Unit  Unit cost  Description  Unit  Unit cost  
Sorghum       
Millet       
Maize       
Cowpea       
Groundnut       
Bambara ground nut       
Sesame       
Cotton       
Rice       
Onions       
Tomatoes       
Okra       
Hibiscus       
 Chili peppers       
Amaranth       
Vegetable leaf       
Mango       
Papaya       
Baobab       
Moringa       
Nere       
Shea       
Agroforestry firewood       
Agroforestry tree poles       
Timber tree       
Crop1       
Crop2       
Crop3       
Crop4       
Crop5       
Vegetable1       
Vegetable2       
Vegetable3       
Tree planting1        
Tree planting2       
Tree planting3       

 
 



   
 

37 
 

Annex 1.11. Fixed cost: Vegetable, Agroforestry and Tree production per ha 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site. 

 Depreciation of irrigation 
system equipment 

Depreciation of other 
equipment and tools  

Crop/vegetable/tree Description  Unit cost  Description  Unit cost  
Sorghum     
Millet     
Maize     
Cowpea     
Groundnut     
Bambara ground nut     
Sesame     
Cotton     
Rice     
Onions     
Tomatoes     
Okra     
Hibiscus     
 Chili peppers     
Amaranth     
Vegetable leaf     
Mango     
Papaya     
Baobab     
Moringa     
Nere     
Shea     
Agroforestry firewood     
Agroforestry tree poles     
Timber tree     
Crop1     
Crop2     
Crop3     
Crop4     
Crop5     
Vegetable1     
Vegetable2     
Vegetable3     
Tree planting1      
Tree planting2     
Tree planting3     

 
 
 
 
 
 



   
 

38 
 

Annex 1.12. Fixed cost: Vegetable, Agroforestry and Tree production per ha 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Reparation and maintenance Other fixed cost 
Crop/vegetable/tree Description  Unit cost  Description  Unit cost  
Sorghum     
Millet     
Maize     
Cowpea     
Groundnut     
Bambara ground nut     
Sesame     
Cotton     
Rice     
Onions     
Tomatoes     
Okra     
Hibiscus     
 Chili peppers     
Amaranth     
Vegetable leaf     
Mango     
Papaya     
Baobab     
Moringa     
Nere     
Shea     
Agroforestry firewood     
Agroforestry tree poles     
Timber tree     
Crop1     
Crop2     
Crop3     
Crop4     
Crop5     
Vegetable1     
Vegetable2     
Vegetable3     
Tree planting1      
Tree planting2     
Tree planting3     

 
 



   
 

39 
 

Annex 1.13. Fixed cost: Vegetable, Agroforestry and Tree production per ha 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Land rent or lease  
Crop/vegetable/tree Description  Unit cost    
Sorghum     
Millet     
Maize     
Cowpea     
Groundnut     
Bambara ground nut     
Sesame     
Cotton     
Rice     
Onions     
Tomatoes     
Okra     
Hibiscus     
 Chili peppers     
Amaranth     
Vegetable leaf     
Mango     
Papaya     
Baobab     
Moringa     
Nere     
Shea     
Agroforestry firewood     
Agroforestry tree poles     
Timber tree     
Crop1     
Crop2     
Crop3     
Crop4     
Crop5     
Vegetable1     
Vegetable2     
Vegetable3     
Tree planting1      
Tree planting2     
Tree planting3     

 
 



   
 

40 
 

Annex 1.14. Yield change over year: Vegetable, Agroforestry and Tree production per ha 
For each crop and land development technique, data will be collected during interview with 
representative farmers within each site 

 Yield Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 
Crop/vegetable/tree Initial level per ha           
Sorghum           
Millet           
Maize           
Cowpea           
Groundnut           
Bambara ground nut           
Sesame           
Cotton           
Rice           
Onions           
Tomatoes           
Okra           
Hibiscus           
 Chili peppers           
Amaranth           
Vegetable leaf           
Mango           
Papaya           
Baobab           
Moringa           
Nere           
Shea           
Agroforestry firewood           
Agroforestry tree poles           
Timber tree           
Crop1           
Crop2           
Crop3           
Crop4           
Crop5           
Vegetable1           
Vegetable2           
Vegetable3           
Tree planting1            
Tree planting2           
Tree planting3           

 
 
 
 
 



   
 

41 
 

Annex 2. Livestock 
Annex 2.1. Evolution of livestock 

 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 
Bovine           
Goat           
Sheep           
Swine           
Poultry           
Livestock1           
Livestock2           
Livestock3           
Livestock4           
Livestock5           
           
           

 
Annex 2.2. Evolution of livestock and subproduct sale 

 Livestock numbers Unit  Price  
 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10   
Bovine             
Goat             
Sheep             
Swine             
Poultry             
Bovine milk             
Goat milk             
Sheep milk              
Livestock1             
Livestock2             
Livestock3             
Livestock4             
Livestock5             
Bovine byproduct             
Goat byproduct             
Sheep byproduct             
Swine byproduct             
Poultry byproduct             
Livestock1 byproduct             
Livestock2 byproduct             
Livestock3 byproduct             
Livestock4 byproduct             
Livestock5 byproduct             
             
             

 
 



   
 

42 
 

Annex 2.3. Evolution of livestock purchase 
 Livestock numbers Unit  Price  
 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10   
Bovine             
Goat             
Sheep             
Swine             
Poultry             
Livestock1             
Livestock2             
Livestock3             
Livestock4             
Livestock5             

 
Annex 2.4. Per capita feeding, supplements, and veterinary for livestock 

 Average feeding  Average Supplements  Veterinary  
 Quantity Unit cost Quantity Unit cost Quantity Unit cost 
Bovine       
Goat       
Sheep       
Swine       
Poultry       
Livestock1       
Livestock2       
Livestock3       
Livestock4       
Livestock5       
       

 
Annex 2.5. Per capita health care, labor, and water access for livestock 

 Average Health care  Average labor  Family labor  Water access 

 
Quantity Unit cost Number Unit cost Number Unit cost Number Unit 

cost 
Bovine         
Goat         
Sheep         
Swine         
Poultry         
Livestock1         
Livestock2         
Livestock3         
Livestock4         
Livestock5         
         



   
 

43 
 

Annex 2.6. Per capita transport, marketing and other variable costs for livestock 
 Transport  Marketing  Other variable cost  
 Number Unit cost Number Unit cost Number Unit cost 
Bovine       
Goat       
Sheep       
Swine       
Poultry       
Livestock1       
Livestock2       
Livestock3       
Livestock4       
Livestock5       
       

 
Annex 2.7. Per capita housing/shelter, feeder, waterer depreciation for livestock 

 
Housing/shelter Feeder   Waterer Other 

equipment 

 
Number Unit 

cost 
Number Unit 

cost 
Number Unit 

cost 
Number Cost  

Bovine         
Goat         
Sheep         
Swine         
Poultry         
Livestock1         
Livestock2         
Livestock3         
Livestock4         
Livestock5         
         

 



   
 

44 
 

Annex 3. Fishing 
Annex 3.1. Evolution of fishing area or infrastructure (fishing hole, floating boat, pond, etc.) 

 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 
Tilapia           
Catfish           
Fish1           
Fish2           
Fish3           
Fish4           
Fish5           
Fish6           
Fish7           
Fish8           

 
Annex 3.2. Evolution of fish and subproduct sale 

 Livestock numbers Unit  Price  
 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10   
Tilapia sale             
Catfish sale             
Fish1 sale             
Fish2 sale             
Fish3 sale             
Fish4 sale             
Fish5 sale             
Fish6 sale             
Fish7 sale             
Fish8 sale             
Tilapia byproduct             
Catfish byproduct             
Fish1 byproduct             
Fish2 byproduct             
Fish3 byproduct             
Fish4 byproduct             
Fish5 byproduct             
Fish6 byproduct             
Fish7 byproduct             
Fish8 byproduct             

 
 



   
 

45 
 

Annex 3.3. Evolution of fingerlings purchase 
 Livestock numbers Unit  Price  
 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10   
Tilapia fingerlings             
Catfish fingerlings             
Fish1 fingerlings             
Fish2 fingerlings             
Fish3 fingerlings             
Fish4 fingerlings             
Fish5 fingerlings             
Fish6 fingerlings             
Fish7 fingerlings             
Fish8 fingerlings             

 
Annex 3.4. Per capita feeding, labor, and veterinary for livestock 

 Average feeding  Average labor  Medicine & Disease control  
 Quantity Unit cost Number Unit cost Quantity Unit cost 
Tilapia        
Catfish        
Fish1        
Fish2        
Fish3        
Fish4        
Fish5        
Fish6        
Fish7        
Fish8        

 
Annex 3.5. Per capita transport, marketing and other variable costs for fishing 

 Transport  Marketing  Repair & maintenance  Other variables 
 Number Unit cost Number Unit cost Number Unit cost Cost 
Tilapia         
Catfish         
Fish1         
Fish2         
Fish3         
Fish4         
Fish5         
Fish6         
Fish7         
Fish8         
        

 
 
 
 



   
 

46 
 

 
Annex 3.6. Per capita pond, borehole, pump, irrigation canal depreciation for fishing 

 Pond Borehole  Pump Irrigation canal 
 Number Unit cost Number Unit cost Number Unit cost Number Cost  
Tilapia          
Catfish          
Fish1          
Fish2          
Fish3          
Fish4          
Fish5          
Fish6          
Fish7          
Fish8          
         

 
Annex 3.7. Per capita net, aerator, feeder, testing kit canal depreciation for fishing 

 Net Aerator  Feeder Testing kit 
 Number Unit cost Number Unit cost Number Unit cost Number Cost  
Tilapia          
Catfish          
Fish1          
Fish2          
Fish3          
Fish4          
Fish5          
Fish6          
Fish7          
Fish8          
         

 
Annex 3.8. Per capita stockage kit, smoking/drying kit, other equipment depreciation for 
fishing 

 Stockage kit Smoking/drying kit  Other equipment 
 Number Unit cost Number Unit cost Number Unit cost 
Tilapia        
Catfish        
Fish1        
Fish2        
Fish3        
Fish4        
Fish5        
Fish6        
Fish7        
Fish8        
       

 



   
 

47 
 

Annex 4. Outcome indicators with IRP 

  With IRP 
IRP 
Compone
nts Indicators 

St
art 

Referenc
e year 

Food 
Assistanc

e For 
Asset 

Percentage of the population in targeted communities reporting 
benefits from an enhanced livelihood asset base    
Percentage of FFA supported assets that demonstrate improved 
vegetation and soil conditions   
Proportion of the population in targeted communities reporting 
environmental benefits   

Smallhol
der 

farmers 
Access To 

Market 
support 
(SAMs) 

Value and volume of smallholder sales through WFP-supported 
aggregation systems   
Average percentage of smallholder post-harvest losses at the storage 
stage   
Percentage of targeted smallholder farmers reporting increased 
production of nutritious crops   
Percentage of targeted smallholder farmers selling through WFP-
supported farmer aggregation systems   

Capacity 
Strengthe

ning 

Transition strategy for school health and nutrition and school feeding 
developed with WFP support    
Number of national policies, strategies, programmes and other 
system components contributing to zero hunger and other SDGs 
enhanced with WFP capacity strengthening support     
Number of national policies, strategie