{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DIME","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2025-07-28","version":"1"},"project_desc":{"authoring_entity":[{"name":"Robin Middelanis","affiliation":"World Bank","email":"rmiddelanis@worldbank.org"},{"name":"Bramka Arga Jafino","affiliation":"World Bank","email":"bjafino@worldbank.org"},{"name":"Ruth Hill","affiliation":"World Bank","email":"rhill@worldbank.org"},{"name":"Minh Cong Nguyen","affiliation":"World Bank","email":"mnguyen3@worldbank.org"},{"name":"St\u00e9phane Hallegatte","affiliation":"World Bank","email":"shallegatte@worldbank.org"}],"title_statement":{"title":"Reproducibility package for Global Socio-Economic Resilience To Natural Disasters","idno":"RR_WLD_2025_376"},"software":[{"name":"Python","version":"3.12"}],"scripts":[{"title":"Reproducibility package for Global Socio-Economic Resilience To Natural Disasters","date":"2025-07","notes":"Computational reproducibility verified by Development Impact (DIME) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_WLD_2025_376","zip_package":"RR_WLD_2025_376.zip","dependencies":"All dependencies are stored in the `environment.yml' file"}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2025-07-28","abstract":"Most disaster risk assessments use damages to physical assets as their central metric, often neglecting distributional impacts and the coping and recovery capacity of affected people. To address this shortcoming, the concepts of well-being losses and socio-economic resilience\u2014the ability to experience asset losses without a decline in well-being\u2014have been proposed. This paper uses microsimulations to produce a global estimate of well-being losses from, and socio-economic resilience to, natural disasters, covering 132 countries. On average, each $1 in disaster-related asset losses results in well-being losses equivalent to a $2 uniform national drop in consumption, with significant variation within and across countries. The poorest income quintile within each country incurs only 9% of national asset losses but accounts for 33% of well-being losses. Compared to high-income countries, low-income countries experience 67% greater well-being losses per dollar of asset losses and require 56% more time to recover. Socio-economic resilience is uncorrelated with exposure or vulnerability to natural hazards. However, a 10 percent increase in GDP per capita is associated with a 0.9 percentage point gain in resilience, but this benefit arises indirectly\u2014such as through higher rate of formal employment, better financial inclusion, and broader social protection coverage\u2014rather than from higher income itself. This paper assess ten policy options and finds that socio-economic and financial interventions (such as insurance and social protection) can effectively complement asset-focused measures (e.g., construction standards) and that interventions targeting low-income populations usually have higher returns in terms of avoided well-being losses per dollar invested.","geographic_units":[{"name":"World","code":"WLD"}],"keywords":[{"name":"Natural Disasters"},{"name":"Risk Reduction"},{"name":"Well-Being"},{"name":"Resilience"},{"name":"Recovery"}],"topics":[{"id":"Q50","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"General","parent_id":"Q5"},{"id":" Q54","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Climate \u2022 Natural Disasters and Their Management \u2022 Global Warming","parent_id":"Q5"},{"id":" I30","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"General","parent_id":"I3"},{"id":" I32","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Measurement and Analysis of Poverty","parent_id":"I3"},{"id":" D63","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Equity, Justice, Inequality, and Other Normative Criteria and Measurement","parent_id":"D6"}],"output":[{"type":"Working Paper","description":"Policy Research Working Papers (PRWP) WPS11129","title":"Global Socio-Economic Resilience To Natural Disasters","uri":"http:\/\/documents.worldbank.org\/curated\/en\/099542505212567521","doi":"https:\/\/www.doi.org\/10.1596\/1813-9450-11129"}],"language":[{"name":"English","code":"EN"}],"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":"Robin Middelanis","affiliation":"World Bank","email":"rmiddelanis@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"datasets":[{"uri":"https:\/\/microdata.worldbank.org\/index.php\/catalog\/global-findex\/?page=1&ps=15&repo=global-findex","license_uri":"https:\/\/microdata.worldbank.org\/index.php\/terms-of-use","license":"Public Use Files (PUFs)","name":"Global Financial Inclusion (Global Findex) Database","note":"Source: World Bank\nFile names: `WLD_2011_FINDEX_v02_M.csv`, `WLD_2014_FINDEX_v01_M.csv`, `WLD_2017_FINDEX_v02_M.csv`, `WLD_2021_FINDEX_v03_M.csv'\n","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package."},{"uri":"https:\/\/www.social-protection.org\/gimi\/ShowWiki.action?id=52","note":"Source: International Labor Organization\nFilename: ILO_WSPR_SP_exp.csv","name":"World Social Protection Report data","access_type":"Data is publicly available and included in the reproducibility package.","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","license":"CC BY 4.0"},{"name":"Penn World Table","uri":"https:\/\/www.rug.nl\/ggdc\/productivity\/pwt\/","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","license":"CC BY 4.0","access_type":"Data is publicly available and included in the reproducibility package","note":"Source: Feenstra, R. C., Inklaar, R., & Timmer, M. P. (2015). The Next Generation of the Penn World Table. American Economic Review, 105(10), 3150\u20133182. \nFilename: pwt1001.xlsx"},{"name":"Global Infrastructure Risk Model and Resilience Index (GIRI) ","note":"Source: Coalition for Disaster Resilient Infrastructure (CDRI)\nFilename: export_all_metrics.csv.zip","access_type":"Data is publicly available and included in the reproducibility package.","license":"CC BY 3.0 IGO","license_uri":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/igo","uri":"https:\/\/giri.unepgrid.ch"},{"name":"Flood protection levels data","note":"Source: Natural Hazards and Earth System Sciences (NHESS) \nFilename: Scussolini_et_al_FLOPROS_shp_V1\/","access_type":"Data is publicly available and included in the reproducibility package.","license":"CC BY 3.0","uri":"https:\/\/nhess.copernicus.org\/articles\/16\/1049\/2016\/nhess-16-1049-2016-supplement.zip","license_uri":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"},{"name":"Modeled coastal flood protection layer","note":"Source: Tiggeloven, T. (2020). Benefit-cost analysis of adaptation objectives to coastal flooding at the global scale V2\nFilename:Results_adaptation_objectives.zip","access_type":"Data is publicly available and included in the reproducibility package.","license":"CC BY 4.0","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","uri":"https:\/\/doi.org\/10.5281\/zenodo.4275517"},{"name":"Global Map shape file","note":"Source: GADM\nFilename: gadm_410-levels.gpkg","access_type":"Data is publicly available and included in the reproducibility package.","license":"CC BY-SA 2.0","license_uri":"https:\/\/creativecommons.org\/licenses\/by-sa\/2.0\/","uri":"https:\/\/gadm.org\/"},{"name":"Gridded population density data","note":"Source: NASA Socioeconomic Data and Applications Center (SEDAC)\nFilename: gpw_v4_population_density_adjusted_rev11_2pt5_min.nc","access_type":"Data is publicly available and included in the reproducibility package.","license":"CC BY 4.0","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","uri":"https:\/\/doi.org\/10.7927\/H4F47M65"},{"name":"Global Exposure Model data","note":"Source: Global Earthquake Model (GEM)","access_type":"Data is publicly available and included in the reproducibility package.","license":"CC BY-NC-SA 4.0","license_uri":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/","uri":"https:\/\/github.com\/gem\/global_exposure_model"},{"name":"Global Monitoring Database (GMD)","note":"Source: World Bank The Global Monitoring Database (GMD) contains micro-level survey data, with access restricted to World Bank staff using Bank-managed computers. External access is not available.\nFilename: Dwelling quintile vul ratio.xlsx","access_type":"Restricted and not included in the package."},{"name":"Hyogo Framework for Action performance indicators","note":"Source: United Nations Office for Disaster Risk Reduction (UNDRR)\nFilename: `HFA_all_2009_2011.csv`, `HFA_all_2011_2013.csv`, `HFA_all_2013_2015.csv`","access_type":"Data is publicly available but does not allow redistribution.","license_uri":"https:\/\/www.undrr.org\/terms-and-conditions","uri":"https:\/\/www.unisdr.org\/we\/inform\/publications\/43291"},{"name":"World Risk Poll","note":"Source: The Lloyd's Register Foundation\nFilename: lrf_wrp_2021_full_data.csv.zip","access_type":"Data is publicly available but does not allow redistribution.","license_uri":"https:\/\/www.lrfoundation.org.uk\/terms-of-use","uri":"https:\/\/www.lrfoundation.org.uk\/wrp"},{"name":"Estimated exposure by poverty line and hazard","note":"Source: World Bank\nFilename: exposure bias.dta\nData was obtained from the World Bank's Poverty team.  Individuals interested in accessing the data for replication purposes can contact Ben James Brunckhorst at bbrunckhorst@worldbank.org.\n","access_type":"Restricted and not included in the package"},{"name":"Investment and Capital Stock Data","note":"Source: International Monetary Fund (IMF)\nFilename: IMFInvestmentandCapitalStockDataset2021.xlsx","access_type":"Data is publicly available but does not allow redistribution.","license_uri":"https:\/\/www.imf.org\/en\/About\/copyright-and-terms","uri":"https:\/\/infrastructuregovern.imf.org\/content\/dam\/PIMA\/Knowledge-Hub\/dataset\/IMFInvestmentandCapitalStockDataset2021.xlsx"},{"name":"Household tenure data","note":"Source: United Nations Statistics Division\nFilename: 2025-02_13_value_added_by_industry.csv, 2025-02-18_household_tenure.csv","access_type":"Data is publicly available and included in the reproducibility package.","license_uri":"https:\/\/data.un.org\/Host.aspx?Content=UNdataUse","uri":"https:\/\/data.un.org\/"},{"name":"Eurostat database","note":"Source: Eurostat\nFilenameS: eurostat__nama_10_nfa_st__capital_stock.csv, eurostat__nama_10_a64__value_added.csv, home_ownership_rates.xlsx","access_type":"Data is publicly available and included in the reproducibility package.","license":"CC BY 4.0","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","uri":"https:\/\/ec.europa.eu\/eurostat\/web\/main\/data\/database"},{"name":"Affordable Housing Data","note":"Source: The Organisation for Economic Co-operation and Development (OECD)\nFilename: HM1-3-Housing-tenures.xlsx","access_type":"Data is publicly available and included in the reproducibility package.","license":"CC BY 4.0","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","uri":"https:\/\/webfs.oecd.org\/Els-com\/Affordable_Housing_Database\/HM1-3-Housing-tenures.xlsx"},{"name":"Home Ownership Rates","note":"Source: Centre for Affordable Housing Finance in Africa\nFilename: Home_ownership_rates\/home_ownership_rates.xlsx","access_type":"Data is publicly available and included in the reproducibility package.","license":"CC BY 4.0","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","uri":"https:\/\/housingfinanceafrica.org\/"},{"name":"World Bank Country and Lending Groups data","note":"Source: World Bank\nFilename: CLASS.xlsx","access_type":"Data is publicly available and included in the reproducibility package.","license_uri":"https:\/\/www.worldbank.org\/en\/about\/legal\/terms-and-conditions","uri":"https:\/\/datacatalogfiles.worldbank.org\/ddh-published\/0037712\/DR0090755\/CLASS.xlsx"},{"name":"Poverty and Inequality Platform data","note":"Source: World Bank\nFilename: Files in \"poverty_data\" folder","access_type":"Data is publicly available and included in the reproducibility package.","license":"CC BY 4.0","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","uri":"https:\/\/pip.worldbank.org"},{"name":"Mapping of the GEM Building Taxonomy","note":"Source: Global Earthquake Model (GEM)\nFilename: data from Table D-2 stored as `hazus-gem_mapping.csv`","access_type":"Data is publicly available and included in the reproducibility package.","uri":"https:\/\/cloud-storage.globalquakemodel.org\/public\/wix-new-website\/pdf-collections-wix\/publications\/GEM%20Building%20Taxonomy%20Version%202.0.pdf","license_uri":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/","license":"CC BY-NC-SA 4.0"},{"name":"World Bank Databank ","note":"Source: World Bank\nData is downloaded via the API; please see the README for details on the indicators","uri":"https:\/\/databank.worldbank.org\/","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","access_type":"Data is publicly available but not included in the reproducibility package."}],"reproduction_instructions":"To successfully reproduce the analysis, follow these steps:\n- Install the provided Python environment using the `environment.yml` file.\n- Open the `reproduce_results.py` file located in the `code` folder.\n- Ensure that the `force_recompute` flag is set to `False` so that the code uses intermediate data instead of downloading raw data from the API.\n- Run the script `reproduce_results.py`.\n\nAll outputs\u2014except Appendix Tables 6 and 7\u2014will be saved in the `figures` folder. Appendix Tables 6 and 7 will be displayed in the command line.\nPlease note that since some of the raw data is restricted, users will only be able to replicate the analysis using the intermediate data included in the `data\/processed` folder of the reproducibility package.","data_statement":"Some data is restricted and has not been included in the reproducibility package. For more details, please refer to the README file.","technology_requirements":"~1 hour runtime"},"tags":[{"tag":"DOI"},{"tag":"Open Code"}],"schematype":"script"}