IFPRI Datasets and Documentation

Permanent URI for this collectionhttps://hdl.handle.net/10568/129227

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Food Security Simulator – Papua New Guinea
(Dataset, 2025-06-04) International Food Policy Research Institute
The Food Security Simulator Papua New Guinea (FSS-PNG) is an innovative and easy-to-use, MS-Excel-based tool for assessing the potential short-term impacts of food price or household income shocks, along with changes in preferences, on food security and people’s diets. The Simulator is an ideal tool for first-cut forward-looking evaluations of direct, household-level outcomes of economic crises and policy responses in a timely manner. The tool allows users to enter positive and negative price or income changes in percentage terms and provides simulated changes for a diverse set of food-consumption- and diet-quality-related indicators. In addition to detailed tabular presentations of all simulation results by household income quintile and residential area, key indicator results are summarized in concise overview tables and visualized in graphs for easy export and use in reports. The underlying data include estimates from representative household survey data and rigorous, sophisticated food demand models to capture consumer behavior.
Social Accounting Matrix for Okara District, Pakistan: A Water Resources Accountability in Pakistan (WRAP) Project Analysis
(Data Paper, 2025-05-09) Davies, Stephen; Ali, Muhammad Tahir; Akram, Iqra; Hafeez, Mohsin
The aim of this paper is to develop a document to guide the methodology and data resources used to develop a local Social Accounting Matrix (SAM) for Okara district in Punjab, Pakistan, and to provide an overview of the SAM results. Regional SAMs at lower administrative levels can be used to understand the regional economic impact of geographically targeted policies and shocks. The common data standards, procedures, and classification systems for national SAMs are adapted and modified for these regional SAMs. This approach and paper closely follow the development of SAM construction outlined in IFPRI’s NEXUS Project, which emphasized the need for greater transparency and consistency in SAM construction to strengthen model-based research and policy analysis in developing countries. Utilizing much of that Project’s general structure, our results permit comparisons at regional administrative scales, especially in agriculture and food systems including water resources dimensions. Additionally, this paper develops a companion method to evaluate direct and indirect water use associated with the economic changes produced from SAM analyses. We hope this methodology can be used to develop SAMs for other districts in the future.
SELEVER study: Endline survey
(Dataset, 2025-03-21) International Food Policy Research Institute
The Soutenir l’Exploitation Familiale pour Lancer l’Élevage des Volailles et Valoriser l’Économie Rurale (SELEVER) study was a cluster randomized controlled trial conducted in rural Burkina Faso to evaluate the impact of an integrated agriculture-nutrition intervention on the diets, health, and nutritional status of women and children. The intervention package combined poultry value chain development, women’s empowerment initiatives, and a behavior change communication strategy to promote healthier diets and improved feeding, care, and hygiene practices. Data collection took place in rural communities across three regions—Boucle du Mouhoun, Centre-Ouest, and Haut-Bassins—over four rounds between March 2017 and August 2020. The baseline survey (Round 1) was conducted from March to June 2017, during the post-harvest season, and included a sample of 1,800 households. Follow-up 1 and Follow-up 2 (Rounds 2 and 3) were carried out during the lean season, with data collected in September–October 2017 and September–October 2019, respectively, from a subsample of 1,080 households. The endline survey (Round 4) took place from March to August 2020, with a temporary pause in data collection due to COVID-19 restrictions. The study aimed to assess the effectiveness of the intervention package in enhancing nutritional outcomes for women and children in the targeted communities. The data presented here are from the endline survey.
SELEVER study: Second follow-up survey
(Dataset, 2025-03-21) International Food Policy Research Institute
The Soutenir l’Exploitation Familiale pour Lancer l’Élevage des Volailles et Valoriser l’Économie Rurale (SELEVER) study was a cluster randomized controlled trial conducted in rural Burkina Faso to evaluate the impact of an integrated agriculture-nutrition intervention on the diets, health, and nutritional status of women and children. The intervention package combined poultry value chain development, women’s empowerment initiatives, and a behavior change communication strategy to promote healthier diets and improved feeding, care, and hygiene practices. Data collection took place in rural communities across three regions—Boucle du Mouhoun, Centre-Ouest, and Haut-Bassins—over four rounds between March 2017 and August 2020. The baseline survey (Round 1) was conducted from March to June 2017, during the post-harvest season, and included a sample of 1,800 households. Follow-up 1 and Follow-up 2 (Rounds 2 and 3) were carried out during the lean season, with data collected in September–October 2017 and September–October 2019, respectively, from a subsample of 1,080 households. The endline survey (Round 4) took place from March to August 2020, with a temporary pause in data collection due to COVID-19 restrictions. The study aimed to assess the effectiveness of the intervention package in enhancing nutritional outcomes for women and children in the targeted communities. The data presented here are from the second follow-up survey.
SELEVER study: First follow-up survey
(Dataset, 2025-03-21) International Food Policy Research Institute
The Soutenir l’Exploitation Familiale pour Lancer l’Élevage des Volailles et Valoriser l’Économie Rurale (SELEVER) study was a cluster randomized controlled trial conducted in rural Burkina Faso to evaluate the impact of an integrated agriculture-nutrition intervention on the diets, health, and nutritional status of women and children. The intervention package combined poultry value chain development, women’s empowerment initiatives, and a behavior change communication strategy to promote healthier diets and improved feeding, care, and hygiene practices. Data collection took place in rural communities across three regions—Boucle du Mouhoun, Centre-Ouest, and Haut-Bassins—over four rounds between March 2017 and August 2020. The baseline survey (Round 1) was conducted from March to June 2017, during the post-harvest season, and included a sample of 1,800 households. Follow-up 1 and Follow-up 2 (Rounds 2 and 3) were carried out during the lean season, with data collected in September–October 2017 and September–October 2019, respectively, from a subsample of 1,080 households. The endline survey (Round 4) took place from March to August 2020, with a temporary pause in data collection due to COVID-19 restrictions. The study aimed to assess the effectiveness of the intervention package in enhancing nutritional outcomes for women and children in the targeted communities. The data presented here are from the first follow-up survey.
SELEVER study: Baseline survey
(Dataset, 2025-03-21) International Food Policy Research Institute
The Soutenir l’Exploitation Familiale pour Lancer l’Élevage des Volailles et Valoriser l’Économie Rurale (SELEVER) study was a cluster randomized controlled trial conducted in rural Burkina Faso to evaluate the impact of an integrated agriculture-nutrition intervention on the diets, health, and nutritional status of women and children. The intervention package combined poultry value chain development, women’s empowerment initiatives, and a behavior change communication strategy to promote healthier diets and improved feeding, care, and hygiene practices. Data collection took place in rural communities across three regions—Boucle du Mouhoun, Centre-Ouest, and Haut-Bassins—over four rounds between March 2017 and August 2020. The baseline survey (Round 1) was conducted from March to June 2017, during the post-harvest season, and included a sample of 1,800 households. Follow-up 1 and Follow-up 2 (Rounds 2 and 3) were carried out during the lean season, with data collected in September–October 2017 and September–October 2019, respectively, from a subsample of 1,080 households. The endline survey (Round 4) took place from March to August 2020, with a temporary pause in data collection due to COVID-19 restrictions. The study aimed to assess the effectiveness of the intervention package in enhancing nutritional outcomes for women and children in the targeted communities. The data presented here are from the baseline survey.
Papua New Guinea Rural Household Survey, 2023
(Dataset, 2025-03-16) International Food Policy Research Institute
The Papua New Guinea Rural Household Survey (2023) collected detailed household-level data on agricultural production, food and non-food consumption and expenditure, and livelihood strategies across 14 provinces, covering communities in the highlands, lowlands, and islands of Papua New Guinea (PNG). The survey was designed using a purposive sampling strategy based on defined agro-ecological zones, which allows for the analysis of key factors influencing rural households and communities. It is important to note that the survey is not nationally representative; however, given the careful random selection of survey areas, we expect that generalizable relationships between variables affecting socio-economic and other development outcomes in rural PNG communities will be consistently observed across representative samples and in this survey. These factors include those that contribute to more resilient local food systems, diversified employment opportunities, and improved household wellbeing. The survey encompasses 2,699 households in 270 communities, spanning five agroecological zones. It features detailed modules on a wide range of topics relevant to rural livelihoods, agricultural production, and household wellbeing.
SELEVER study data
(Data Paper, 2025-02-24) Gelli, Aulo; Becquey, Elodie; Ganaba, Rasmané; Leight, Jessica; Heckert, Jessica; Huybregts, Lieven; Toé, Laetica; Awonon, Josué; Diatta, Ampa Dogui; Diop, Loty; Santacroce, Marco; Pedehombga, Abdoulaye; Hein, Alain; Somé, Henri
The SELEVER study was a cluster randomized controlled trial aiming to evaluate the effects of an inte-grated agriculture–nutrition intervention package (including poultry value chain development, women’s empowerment activities, and a behavior change communications strategy to promote improved diets and feeding, care, and hygiene practices) on the diets, health, and nutritional status of women and chil-dren in rural Burkina Faso (1). Four rounds of data collection were carried out in rural communities of three regions of Burkina Faso: Boucle du Mouhoun, Centre-Ouest and Haut-Bassins between March 2017 and August 2020. The first round (Baseline) took place between March and June 2017 during the post-harvest season in a sam-ple of 1800 households. The second (Follow-up) and third (Follow-up 2) rounds took place during the lean season in 2017 (September-October) and 2019 (September-October) in a subsample of 1080 households. The last survey round (Endline) took place between March and August 2020 (including a break due to covid-19 restrictions).
Clustering for global market access in Bangladesh: Endline survey
(Dataset, 2024-12-31) International Food Policy Research Institute
The "Clustering for Global Market Access Survey" was conducted to assess the impacts of shrimp farm clustering interventions implemented by the Department of Fisheries (DoF), the Bangladesh Shrimp and Fish Foundation (BSFF), and a private sector actor. The survey was carried out in two rounds: a baseline in 2023 and an endline in 2024, to evaluate the effectiveness of these interventions. The data presented here are from the endline survey conducted between May 7 and May 31, 2024. Data were collected at the household, cluster, and community levels using a two-stage simple random sampling design and analyzed through a difference-in-differences approach. The household datasets include 1,222 shrimp farms across three districts in southern Bangladesh—Bagerhat, Khulna, and Satkhira. Among these, 622 are cluster farmers, and 600 are non-cluster comparison farmers situated in either the same or adjacent villages to cluster farmers. The data encompass cluster participation, pond characteristics, inputs received from cluster operators, stocking and harvesting, feed and non-feed input use, sales revenue, integrated farming, labor use, credit access, dietary diversity, and food security. The cluster datasets cover 68 shrimp farm clusters, providing insights into cluster composition and training delivered to cluster members. The community datasets provide contextual information on the 136 villages where both cluster and non-cluster farmers reside.
Clustering for global market access in Bangladesh: Baseline survey
(Dataset, 2024-12-31) International Food Policy Research Institute
The "Clustering for Global Market Access Survey" was conducted to assess the impacts of shrimp farm clustering interventions implemented by the Department of Fisheries (DoF), the Bangladesh Shrimp and Fish Foundation (BSFF), and a private sector actor. The survey was carried out in two rounds: a baseline in 2023 and an endline in 2024, to evaluate the effectiveness of these interventions. The data presented here are from the baseline survey conducted between November 14 and December 14, 2023. Data were collected at the household, cluster, and community levels using a two-stage simple random sampling design and analyzed through a difference-in-differences approach. The household datasets include 1,222 shrimp farms across three districts in southern Bangladesh—Bagerhat, Khulna, and Satkhira. Among these, 622 are cluster farmers, and 600 are non-cluster comparison farmers situated in either the same or adjacent villages to cluster farmers. The data encompass cluster participation, pond characteristics, inputs received from cluster operators, stocking and harvesting, feed and non-feed input use, sales revenue, integrated farming, labor use, credit access, dietary diversity, and food security. The cluster datasets cover 68 shrimp farm clusters, providing insights into cluster composition and training delivered to cluster members. The community datasets provide contextual information on the 136 villages where both cluster and non-cluster farmers reside.
FABLE Scenathon database 2023
(Dataset, 2024-06-24) Douzal, Clara; Chemarin, Charlotte; Mosnier, Aline; Orduña-Cabrera, Fernando; Jones, Sarah; Adenäuer, Lucie; Vittis, Yiorgos; Cozza, Davide; Diaz, Maria; Javalera Rincón, Valeria; Rios, Alejandro; Sandoval, Marcial; Obersteiner, Michael; Navarrete Frias, Carolina; Declerck, Fabrice; Frank, Federico; Monjeau, Adrian; Bertranou, Camila; Navarro Garcia, Javier; Marcos-Martinez, Raymundo; Costa, Wanderson; Ramos, Fernando; Reyes, René; Zerriffi, Hisham; Paradis, Gregory; Maloney, Avery; Chavarro, John; Peña, Andres; Arguello, Ricardo; Escobar, Jorge; Marimon Bolivar, Wilfredo; Højte, Simone; Skou Fertin, Regitze; Fraas, Emil; Nyord, Tavs; Getaneh, Yonas; Nigussie, Yirgalem; Bekele, Mekonnen; Mulatu, Kalkidan; Abera, Wuletawu; Balcha, Yodit; Anshiso, Desalegn; Mohammed, Jemal; Assefa, Beneberu; Kebede, Kaleab; Eshetae, Meron; Hamza, Tagay; Tesfaye, Getachew; Tamene, Lulseged; Lehtonen, Heikki; Rämö, Janne; Rasche, Livia; Schneider, Uwe; Steinhauser, Jan; Landis, Conrad; Dellis, Konstantinos; Ioannou, Alexandra; Chatzigiannakou, Maria Angeliki; Laspidou, Chrysi; Koundouri, Phoebe; Saha, Ankit; Singh, Vartika; Das, Prantika; Joshi, Aditi; Jha, Chandan Kumar; Ghosh, Ranjan Kumar; Lotze-Campen, Hermann; Stevanović, Miodrag; Fuad, habiburrachman; Gonzalez-Abraham, Charlotte; Olguín, Marcela; Rodriguez Ramirez, Sonia; McCord, Gordon; Torres-Rojo, Juan Manuel; Flores-Martinez, Arturo; Cardenas Hernandez, Oscar; Avila Ortega, Daniel; Basnet, Shyam; Pradhan, Prajal; Acharya, Sushant; Uprety, Rajendra; Pokhrel, Pashupati; Khatri, Dil; Basnet, Ram; Van Oort, Bob; Daloz, Anne-Sophie; Strokov, Anton; Imanirareba, Dative; Hall, Marianne; Fetzer, Ingo; Tacer Caba, Zeynep; Kesici, Müge; Özuyar, Pinar; Smith, Alison; Lynch, John; Harrison, Paula; Whittaker, Freya; Wu, Grace C.; Baker, Justin; Wade, Christopher
This database contains key parameters and variables from the 2023 Scenathon which has been run by the Food, Agriculture, Biodiversity, Land-Use, and Energy (FABLE) Consortium. A scenathon - a scenario marathon - is a multi-objective challenge that allows a decentralized global modelling approach with multiple models developed by different teams in the world at national and regional scales, and a methodology to link them ensuring international trade consistency and tracking collective progress towards the achievement of global sustainability targets. A description and analysis of the Scenathon 2023 pathways has been published in Sachs et al. (2024). The Scenathon 2023 database includes results at the global, country and rest of the world regions levels, for indicators related to food and nutrition security, land and biodiversity, GHG emissions from agriculture and land use change, and input use in agriculture. It also includes key parameters that can be used to explain the results, such as the evolution of productivity and all supply and use balance items at the commodity level. It is possible to visualise some of the key results on the Scenathon dashboard.
Baseline data for Yemen School Milk Initiative Study
(Dataset, 2024-12-30) International Food Policy Research Institute
IFPRI, in collaboration with implementation partners HSA Group and World Food Programme, evaluated the impact of adding a milk intervention to a micronutrient fortified school feeding program. The study is a cluster randomized control trial (cRCT) that took place in 42 schools in Al Mukha district, Yemen. The evaluation includes baseline surveys with households and schools conducted before implementing the milk intervention (November-December 2023), and endline surveys conducted with the same households and schools after the interventions (April-May 2024). These datasets are with respect to the baseline surveys and contains baseline household and school data. The first part comprises household-level modules such as household roster, housing, assets, food security, and occurrence of shocking events. The second part comprises individual-level modules administered to children receiving the program, which include nutritional status, diet, health, cognition, and learning. The last part includes the school level modules such as infrastructure and food environment, administered to school staff.
The impact of site-specific soil fertility recommendations: Experimental evidence from Malawi
(Other, 2024-09-12) Van Campenhout, Bjorn; De Weerdt, Joachim; Assefa, Thomas; Spielman, David J.; Siyame, Edwin W. P.; Ariong, Richard M.; Atkinson, Jonathan
Raising agricultural productivity among smallholder farmers in Sub-Saharan Africa is widely recognized as an important component of inclusive wealth creation and structural transformation. Central to this endeavor will be the adoption of sustainable soil and land management to improve the sustainability, resilience and productivity of agriculture. As such, government advise farmers to increase soil productivity by embracing the use of fertilizers and implement proper soil health management practices. However, these recommendations mostly come in the form of blanket one-size-fits-all recommendations that ignore heterogeneity in soil characteristics that individual farmers face. Using a cluster randomize control trial, we evaluate the impact of a bundled intervention that involves offering farmers a soil test on a plot they select and, using the results of this soil test, provide them with tailored advise on soil management to attain a desired yield for a particular crop the farmer chooses to plant on the plot. Furthermore, we also explore resources constraints as a potential barrier to the adoption of site specific fertilizer blends by adding a subsidy. JEL codes: O33, Q12, Q16
Simulated Future Climates for Ethiopia Using MIT-IGSM HFDs Based on CMIP5
(Dataset, 2024-12-30) International Food Policy Research Institute; Massachusetts Institute of Technology
The dataset consists of high-resolution climate projections spanning 50 years, capturing spatial and temporal variations in temperature, precipitation, and extreme weather events. These climate inputs were combined with agricultural models to simulate the frequency, intensity, and impact of weather events on the yields of key crops, such as maize, in Ethiopia. It integrates hybrid frequency distributions (HFDs) from the Massachusetts Institute of Technology Integrated Global Systems Model (MIT-IGSM) with detrended gridded historical climates from Princeton Global Forcings. Using a Gaussian quadrature routine, 455 representative climate scenarios were selected for Ethiopia under each emissions scenario (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). This comprehensive dataset provides critical insights into the risks posed by climate change to food security and serves as a valuable resource for researchers and policymakers aiming to develop adaptive strategies for sustainable agriculture.
Myanmar Agricultural Performance Survey Round Three: Note on Sample Characteristics and Weighting
(Data Paper, 2024-12-11) Myanmar Agriculture Policy Support Activity
The Myanmar Agricultural Performance Survey (MAPS) Round 3 provides nationally and sub-nationally representative data on agricultural performance, integrating insights from 4,892 farming households. Conducted between January and March 2023, this survey leverages phone-based data collection to address logistical challenges posed by Myanmar's remote and conflict-affected regions. MAPS modules encompass critical agricultural indicators, including crop production, marketing, input usage, farm assets, and services. The survey design integrates rigorous sampling and weighting strategies to ensure representation across demographic and geographical strata. Findings highlight variations in agricultural practices between seasons and years, alongside challenges in household retention due to conflict and infrastructure limitations. Despite attrition and inherent limitations of phone surveys, MAPS successfully enumerated 271 out of 324 townships, contributing vital data for understanding agricultural dynamics in Myanmar.
Migration Propensity Index Validation Survey, Honduras
(Dataset, 2024-12-29) International Food Policy Research Institute
This dataset documents migration and empowerment indicators from a two-round survey conducted in Western Honduras as part of a study validating the Migration Propensity Index (MPI). The baseline survey (May–June 2023) reached 1,209 households across six departments, using a multi-stage cluster sampling strategy prioritizing municipalities with high migration prevalence. Data included MPI questions and potential migration factors. A follow-up survey (May–June 2024) re-interviewed 1,094 households, with additional tracking efforts yielding data on migration for 1,176 households (97% of the baseline). Migration was categorized as internal (to a different department) or external (outside Honduras). The follow-up survey also collected empowerment data on a theoretically-informed subset of indicators from the Women’s Empowerment Metric for National Statistical Systems (WEMNS) from one household respondent, focusing on intrinsic, instrumental, and collective agency, as well as agency-enabling resources, aggregated into a single empowerment index.
Unpacking Joint Decision-making
(Dataset, 2024-04-15) Measures for Advancing Gender Equality (MAGNET) Initiative
The Measures for Advancing Gender Equality (MAGNET) initiative aims to broaden and deepen the measurement of women’s agency, based on the development of new tools and rigorous testing and comparison of both new and existing methods for measuring agency, and promoting the adoption of these measures at scale. By increasing the availability of innovative meaningful measures of agency for a broad range of contexts, we hope our work will lead to an improved understanding of what women’s agency is, how it manifests and how it can best be measured across contexts given the research question at hand. Improving women’s decision-making power is crucial for advancing gender equality. But evidence shows that wives and husbands have systematically different perceptions of who makes these decisions across contexts and intra-household disagreement is often not random; women “taking power” correlates with other women’s empowerment variables. This could be because the standard decision-making answer options “wife, husband, joint” is too categorical and it does not allow us to capture the strength in decision-making power (thinking it as a continuum), or because men and women have a different understanding of what sole/joint decision-making is. This tool, Unpacking Joint Decision-making, allows us to elicit responses regarding subjective assessments of a hypothetical married couple under different scenarios that involve the wife and the husband making household decisions around large household purchases. This tool is suited for nationally representative individual- or household-level surveys, and for targeted thematic or impact evaluation surveys designed to understand individuals' agency and decision-making. This data study includes following files. 1. A survey document (including implementation guidelines) 2. Two files, CAPI_Choices and CAPI_Survey, along with the accompanying files, can be used to construct a CAPI program ready for survey implementation. Alternatively, users can use an Excel workbook "CAPI_.xlsx" that includes worksheets for survey and choices, along with others, for constructing a CAPI program ready for survey implementation.
TAFSSA District Agrifood Systems Assessment in Nepal 2023: Retail Survey
(Dataset, 2024-12-09) International Rice Research Institute; International Food Policy Research Institute
TAFSSA (Transforming Agrifood Systems in South Asia) is a CGIAR Regional Integrated Initiative aimed at advancing equitable access to sustainable healthy diets, enhancing farmers' livelihoods and resilience, and conserving natural resources such as land, air, and water across South Asia. The TAFSSA district agrifood systems assessment seeks to establish a robust, accessible, and integrated evidence base that connects farm production, market access, dietary patterns, climate risk responses, and natural resource management, with gender considerations integrated throughout. The assessment focuses on rural areas in Bangladesh, India, and Nepal, utilizing a district-level, multi-year approach. Data was collected between February and June 2023 in the Banke and Surkhet districts of Nepal. The survey covered 25 wards in each district, focusing on formal and informal retail shops operating in the sampled villages. The types of retail shops included local grocery stores and specialized shops selling meat, fish, eggs, or dairy products. The survey employed pretested, structured questionnaires organized into three modules: 1. Interview-Based Module: Captured vendor information, assortments of essential goods, availability, resilience, food sourcing, food wastage, and dimensions of access and protection. 2. Observation + Photo-Based Module: Documented market infrastructure, food quality, safety, and hygiene aspects. 3. Food List Module: Recorded the availability and prices of an exhaustive list of food items found in the location.
Understanding the Meanings of Ownership
(Dataset, 2024-04-15) Measures for Advancing Gender Equality (MAGNET) Initiative
The Measures for Advancing Gender Equality (MAGNET) initiative aims to broaden and deepen the measurement of women’s agency, based on the development of new tools and rigorous testing and comparison of both new and existing methods for measuring agency, and promoting the adoption of these measures at scale. By increasing the availability of innovative meaningful measures of agency for a broad range of contexts, we hope our work will lead to an improved understanding of what women’s agency is, how it manifests and how it can best be measured across contexts given the research question at hand. Expanding women’s asset ownership is key for improving gender equality and promoting economic development and well-being. A widespread challenge in data collection is that ownership can have different meanings across contexts, particularly regarding which components of the bundle of rights comprise ownership. Yet, surveys often implicitly assume that all rights are held by the same person. This tool, Understanding the Meanings of Ownership, allows us to elicit responses regarding subjective assessments of what ownership entails by presenting different scenarios in which the main premise is a woman owning a particular asset, but scenarios differ on the rights that women have over the asset. The multiple questions aim to assess how the answers may vary by type of asset and women’s status in the household (living with a partner, living with in-laws, living with her parents). To fully understand individuals’ understanding of ownership, it is useful to have this tool alongside modules that solicit information on individual’s ownership of the asset. This data study includes following files. 1. A survey document (including implementation guidelines) 2.Two files, CAPI_Choices and CAPI_Survey, along with the accompanying help files, can be used to construct a CAPI program ready for survey implementation. Alternatively, users can use an Excel workbook "CAPI_.xlsx" that includes worksheets for survey and choices, along with others, for constructing a CAPI program ready for survey implementation.
TAFSSA District Agrifood Systems Assessment in Nepal 2023: Market Survey
(Dataset, 2024-12-09) International Rice Research Institute; International Food Policy Research Institute
TAFSSA (Transforming Agrifood Systems in South Asia) is a CGIAR Regional Integrated Initiative aimed at advancing equitable access to sustainable healthy diets, enhancing farmers' livelihoods and resilience, and conserving natural resources such as land, air, and water across South Asia. The TAFSSA district agrifood systems assessment seeks to establish a robust, accessible, and integrated evidence base that connects farm production, market access, dietary patterns, climate risk responses, and natural resource management, with gender considerations integrated throughout. The assessment focuses on rural areas in Bangladesh, India, and Nepal, utilizing a district-level, multi-year approach. Data was collected between February and June 2023 in the Banke and Surkhet districts of Nepal. The survey covered 25 wards in each district, focusing on formal and informal multi-vendor markets offering a variety of food products. The survey utilized pretested, structured questionnaires divided into three distinct modules: 1. Interview-Based Module: Gathered information on vendors, assortments of essential goods, availability, resilience, food sourcing, food wastage, and dimensions of access and protection. 2. Observation + Photo-Based Module: Documented market details, infrastructure, and aspects related to food quality, safety, and hygiene. 3. Food List Module: Recorded the availability and prices of an extensive list of food items found in the markets.

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