{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DIME","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2025-07-11","version":"1"},"project_desc":{"title_statement":{"idno":"FR_SSA_2024_251","title":"Reproducibility package for Forward-Looking Household Climate Vulnerability Curves to Inform Poverty Reduction Policy"},"authoring_entity":[{"name":"Evie Calcutt","affiliation":"World Bank","email":"ecalcutt@worldbank.org"},{"name":"Ruth Hill ","email":"rhill@worldbank.org","affiliation":"World Bank"},{"name":"Katja Vinha ","email":"kvinha@worldbank.org","affiliation":"World Bank"}],"production_date":"2025-07","abstract":"Climate shocks increase poverty and reduce development gains and productive investments, in part because vulnerable households have poor financial resilience, are often not covered by public safety nets, and therefore have little ability to cushion the impacts of shocks. Globally, nearly one in five people (18 percent) are at risk of climate hazards and are likely to experience a severe climate shock in their lifetime that they will struggle to recover from. Among those at risk, 44 percent have no access to a bank or mobile money account, and 49 percent neither receive benefits nor are eligible to receive benefits from social protection schemes (World Bank Corporate Scorecard, 2024). Improving households\u2019 post-shock access to financing\u2014by strengthening public safety nets and encouraging people to increase their own financial resources to meet unanticipated expenses (for example, through savings and insurance)\u2014is thus an urgent policy priority.\n\nThis note presents an analytical approach to developing forward-looking household climate vulnerability curves to understand both the size of the financing problem and the ways that different policies can address it. The approach is illustrated with an application to drought risk in Sub-Saharan Africa. It provides valuable inputs for policymakers prioritizing investments in climate adaptation and resilience, can add technical value to key flagships such as Country Climate and Development Reports (CCDRs) and Poverty and Equity Assessments, and can support the use of instruments from the World Bank\u2019s Crisis Preparedness and Response Toolkit.","geographic_units":[{"code":"SSA","name":"Sub-Saharan Africa (excluding high income)"}],"output":[{"title":"Forward-Looking Household Climate Vulnerability Curves to Inform Poverty Reduction Policy","description":"World Bank Reports & Flagships","type":"Flagship or other report"}],"language":[{"name":"English","code":"EN"}],"software":[{"name":"Stata","version":"18 MP"}],"scripts":[{"title":"Forward-Looking Household Climate Vulnerability Curves to Inform Poverty Reduction Policy","date":"2025-07","file_name":"FR_SSA_2024_251","zip_package":"FR_SSA_2024_251.zip","dependencies":"Stata dependencies are listed in the ado folder.","instructions":"See README in reproducibility package.","notes":"Computational reproducibility verified by Development Impact (DIME) Analytics team, World Bank."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"reproduction_instructions":"1. **Secure Access to Data:** Access the datasets not included in the package. See subsection Datasets and the README for more details.\n2. **Download and Place Data:** Once the data is downloaded, users should place it in the appropriate folder.\n3. **Run the Package:** After placing the data in the folder:\n      - Open the do-file \"Policy_extensions\"\n      - Update the globals in line 11 to your folder's location and run the do-file\n \nSince all the data is not included, the package includes the results produced by replicators in the Results folder. These files can be used to review the results presented in the paper.","technology_requirements":"~ 10 minutes","technology_environment":"Paper exhibits were reproduced in a computer with the following specifications:\n\u2013 OS: Windows 11 Enterprise\n\u2013 Processor: INTEL(R) XEON(R) PLATINUM 8562Y+ 2.80 GHz (2 processors)\n\u2013 Memory available: 32.0 GB\n\u2013 Software version: Stata 18.0 MP","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":"Katja Vinha ","affiliation":"World Bank","email":"kvinha@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"data_statement":"Some data is restricted and has not been included in the reproducibility package. For more details, please refer to the README file.","datasets":[{"name":"Gridded Global Administrative Areas (GADM) for Africa","note":"Source: Global Administrative Areas. 2012. GADM database of Global Administrative Areas, version 2.0.\nLocated at: Input_data\/Remote_Sensed\/SSA\/gadm_admin_urg005_mapping","access_type":"Publicly available at the link provided and included in the package.","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0066860\/Gridded-Global-Administrative-Areas--GADM--for-Africa"},{"name":"Gridded Global Administrative Unit Layers (GAUL) for Africa","note":"Source: Gridded GAUL designations at uniform grid resolution of 0.05\u00b0 by 0.05\u00b0 used in Gascoigne et al. (2024).\nLocated at: Input_data\/Remote_Sensed\/SSA\/country_mapping","access_type":"Publicly available at the link provided and included in the package.","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0066859\/Gridded-Global-Administrative-Unit-Layers--GAUL--for-Africa"},{"name":"Gridded Crop Coverage for Africa","note":"Source: Buchhorn, M., B. Smets, L. Bertels, B. De Roo, M. Lesiv, N.-E. Tsendbazar, M. Herold, and S. Fritz. Copernicus Global Land Service: Land Cover 100m: Collection 3: epoch 2019: Globe 2020. (https:\/\/land.copernicus.eu\/global\/products\/lc).\nLocated at: Input_data\/Remote_Sensed\/SSA\/crop_coverage\/country_mapping.\n","access_type":"Publicly available at the link provided and included in the package.","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0066869\/Gridded-Crop-Coverage-for-Africa"},{"name":"Crop calendar for Africa","note":"Source1 : Dimou, Maria (2018): Crop calendar dataset compatible with satellite-derived land surface phenology. European Commission, Joint Research Centre (JRC) [Dataset] PID: http:\/\/data.europa.eu\/89h\/jrc-10112-10003.\nSource2: https:\/\/geodata.ucdavis.edu\/gadm\/gadm3.6\/\nLocated at: \/Input_data\/Remote_Sensed\/SSA\/merge_variable_data; Input_data\/Data_Integration\/SSA\/crop_calendar_gaul_asap1.","access_type":"Publicly available at the link provided and included in the package.","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0066842\/Crop-calendar-for-Africa"},{"name":"Gridded Travel Time to Market for Africa","access_type":"Publicly available at the link provided and included in the package.","note":"Source: Gridded Travel Time to Market at uniform grid resolution of 0.05\u00b0 by 0.05\u00b0 used in Gascoigne et al. (2024).\nLocated at: Input_data\/Remote_Sensed\/SSA\/time_to_market\/country_mapping","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0066865\/Gridded-Travel-Time-to-Market-for-Africa"},{"name":"Gridded Global Agro-ecological Zones (GAEZ) for Africa","note":"Source: Gridded Global Agro-ecological Zones at uniform grid resolution of 0.05\u00b0 by 0.05\u00b0 used in Gascoigne et al. (2024). \nLocated at: Input_data\/Remote_Sensed\/SSA\/agro_ecological_zone\/country_mapping.","access_type":"Publicly available at the link provided and included in the package.","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0066857\/Gridded-Global-Agro-ecological-Zones--GAEZ--for-Africa"},{"name":"Gridded Livelihood Zones for Africa","note":"Source:  Dixon, John, Dennis P. Garrity, Jean-Marc Boffa, Timothy O. Williams, Tilahun Amede, Christopher Auricht, Rosemary Lott, and George Mburathi, eds. 2019. Farming Systems and Food Security in Africa: Priorities for Science and Policy Under Global Change. Routledge. (See figure 2.2b.).\nLocated at: Input_data\/Remote_Sensed\/SSA\/livelihood_zone\/country_mapping","access_type":"Data is restricted and not included in the package. World Bank internal users can access the data at the link provided. Users outside the Bank can contact the authors to access the dataset. ","uri":"https:\/\/datacatalog.worldbank.org\/int\/search\/dataset\/0066861\/Gridded-Livelihood-Zones-for-Africa"},{"name":"Gridded Dekadal Soil Water Index (SWI) for Africa","note":"Source:  Copernicus Service information 2018. (https:\/\/land.copernicus.eu\/global\/products\/swi).\nLocated at:  Input_data\/Remote_Sensed\/SSA\/SWI","access_type":"Publicly available at the link provided and included in the package.","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0066864\/Gridded-Dekadal-Soil-Water-Index--SWI--for-Africa"},{"name":"Gridded Monthly Normalized Difference Vegetation Index (NDVI) for Africa","note":"Source: Didan, K. 2021. MODIS\/Terra Vegetation Indices Monthly L3 Global 0.05Deg CMG V061 [data set]. NASA EOSDIS Land Processes DAAC. Accessed 2021-06-24 from https:\/\/doi.org\/10.5067\/MODIS\/MOD13C2.061. (https:\/\/lpdaac.usgs.gov\/products\/mod13c2v061\/).\nLocated at: Input_data\/Remote_Sensed\/SSA\/NDVI","access_type":"Publicly available at the link provided and included in the package.","uri":"https:\/\/datacatalog.worldbank.org\/search\/dataset\/0066862\/Gridded-Monthly-Normalized-Difference-Vegetation-Index--NDVI--for-Africa"},{"name":"Household Consumption and Expenditure Surveys","access_type":"Data is restricted and not included in the package. Ruth Hill (rhill@worldbank.org) can be contacted for details.","note":"Source: Household consumption surveys provided by country poverty economists in the World Bank\u2019s Poverty and Equity Global Practice. \nLocation: Input_Data\/Data_Integration\/Country\/Ethiopia; Input_Data\/Household_Survey\/Malawi\/Dataprep.\n\nA detailed list of datasets is available in the data_hash_report file included in the package."},{"name":"Simulated poverty rates and poverty gaps","note":"Source: These outputs are from the reproducibility package for Gascoigne et al. (2024) https:\/\/reproducibility.worldbank.org\/index.php\/catalog\/301\nLocation: Results\/'country_name' folders for the seven countries: Ethiopia, Lesotho, Malawi, Mozambique, Nigeria, Zambia, and Zimbabwe.","access_type":"Included in the package"},{"name":"Payout schedules for the Ethiopia simulation ","note":"Source: Assembled by the authors. The NDVI values are generated by the scripts included in the reproducibility package. The data used in the Excel file are extracted from the file:\nProcessed_Data\/Country\/Pooled\/Ethiopia_rs_ndvi0.dta","access_type":"Included in the package."}]},"tags":[{"tag":"DOI"},{"tag":"Open Code"},{"tag":"Restricted Data"}],"schematype":"script"}