{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2026-02-25","version":"1"},"project_desc":{"authoring_entity":[{"name":"Qhelile Ndlovu","affiliation":"World Bank","email":"qndlovu@worldbank.org"},{"name":"Toshiaki Ono","affiliation":"World Bank","email":"tono@worldbank.org"},{"name":"Juan Buchenau","affiliation":"World Bank","email":"jbuchenau@worldbank.org"},{"name":"Qi Xue","affiliation":"World Bank","email":"qxue1@worldbank.org"}],"title_statement":{"title":"Reproducibility package for Managing Agricultural Credit Risk In The Face Of Natural Disasters: Lessons From Sub-Saharan Africa, Asia And The Americas","idno":"FR_WLD_2026_545"},"data_statement":"All data sources are publicly available and included in the reproducibility package.","software":[{"name":"R","version":"4.5.1"},{"name":"Excel"}],"scripts":[{"title":"Reproducibility package for Managing Agricultural Credit Risk In The Face Of Natural Disasters: Lessons From Sub-Saharan Africa, Asia And The Americas","date":"2026-02","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"FR_WLD_2026_545","zip_package":"FR_WLD_2026_545.zip","dependencies":"R dependencies are listed in the file renv.lock."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2026-02-25","abstract":"Natural disasters are driving sharp increases in credit risk for agricultural lenders in low\u2011income and climate\u2011vulnerable countries. Based on evidence from 36 financial institutions (FIs) in Burkina Faso, Kenya, Madagascar, and Rwanda, this study finds that disaster events routinely cause spikes in non\u2011repayment, with agricultural portfolios\u2011at\u2011risk peaking at 22 percent and average loan write\u2011offs reaching 10.7 percent. Smaller lenders\u2014especially MFIs and SACCOs\u2014face disproportionate losses due to high exposure to agriculture, limited liquidity, and weak risk assessment capacity.\nDespite these challenges, viable borrowers generally repay when supported through targeted forbearance and recovery lending. FIs that use tailored agricultural loan products, specialized loan officers, and proactive damage assessments experience significantly fewer losses, yet such practices remain limited. Regulatory frameworks also lag behind: most supervisors lack disaster\u2011responsive provisions that would allow restructuring without punitive classification or provisioning consequences.\nThe study calls for three priority actions: (i) strengthening FIs\u2019 technical capacity, assessment tools, and risk\u2011transfer mechanisms such as credit\u2011linked insurance and portfolio guarantees; (ii) integrating disaster risk into prudential regulation and supervision; and (iii) enhancing public\u2011sector support through climate data systems, disaster\u2011linked liquidity facilities, and coordinated financial, agricultural,and disaster\u2011risk policies.","geographic_units":[{"name":"World","code":"WLD"}],"output":[{"title":"Managing Agricultural Credit Risk In The Face Of Natural Disasters: Lessons From Sub-Saharan Africa, Asia And The Americas","type":"Flagship or other report"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"Run time: 2 minutes","disclaimer":"The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development\/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.","license":[{"name":"Modified BSD3","uri":"https:\/\/opensource.org\/license\/bsd-3-clause\/"}],"contacts":[{"name":"Qhelile Ndlovu","affiliation":"World Bank","email":"qndlovu@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"datasets":[{"name":"World Development Indicators","note":"Files location: Share of GDP in agriculture.xls; Share of employment in agriculture.xls. Indicators: SL.AGR.EMPL.ZS;  NV.AGR.TOTL.ZS.","access_type":"Data is publicly available and included in the reproducibility package","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/www.worldbank.org\/en\/about\/legal\/terms-of-use-for-datasets","uri":"https:\/\/databank.worldbank.org\/source\/world-development-indicators","citation":"World Bank. 2025. \"World Development Indicators\" [dataset]. https:\/\/databank.worldbank.org\/source\/world-development-indicators. Accessed September 2025."},{"access_type":"Data is publicly available and included in the reproducibility package","note":"File location: Table 3_Summary of disaster events per country.xlsx","citation":"Centre for Research on the Epidemiology of Disasters (CRED). 2025. \"EM-DAT The International Disaster Database\" [dataset]. https:\/\/doc.emdat.be\/docs\/data-structure-and-content\/emdat-public-table\/.  Accessed September 2025.","uri":"https:\/\/doc.emdat.be\/docs\/data-structure-and-content\/emdat-public-table\/","license_uri":"https:\/\/www.emdat.be\/terms-and-conditions\/","license":"EM-DAT Terms & Conditions","name":"EM-DAT The International Disaster Database"},{"note":"Compiled by the authors from interviews with the country teams. \nFile location: ACRM Study Charts-Reproducibility.xlsx","name":"Financial Institutions and Agricultural Lending Data","access_type":"Data is included in the reproducibility package","citation":"World Bank. (2025). \"Financial Institutions and Agricultural Lending Data\" [dataset]. Unpublished data"}],"reproduction_instructions":"To reproduce the findings in this paper, a new user should follow these steps:\n1. Most exhibits are produced in Excel. \n   Follow the instructions provided in the README file and in the included Excel file:  \n   `ACRM Study Charts Reproducibility.xlsx`.\n2. Figure 3 is produced in R.\n   Open the R project, then open `Figure 3_Reproducibility.Rmd` and run the code to generate the figure.","technology_environment":"Paper exhibits were reproduced on a computer with the following specifications:\n- OS: Windows 11 Enterprise\n- Intel(R) Core(TM) i5-1145G7 CPU @ 2.60GHz  \n- Memory available: 15.7 GB\n- Software version: R 4.5.1"},"tags":[{"tag":"DOI"},{"tag":"Open Code"},{"tag":"Open Data"},{"tag":"Restricted Data"}],"schematype":"script"}