{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2025-08-08","version":"2"},"project_desc":{"production_date":"2026-03-30","technology_environment":"Paper exhibits were reproduced on a computer with the following specifications:\n\u2022 OS: Windows 11 Enterprise\n\u2022 Processor: INTEL(R) XEON(R) PLATINUM 8562Y+ 2.80 GHz (4 processors)\n\u2022 Memory available: 32.0 GB\n\u2022 Software version: Stata 18.0 MP","software":[{"name":"Stata","version":"18 MP"},{"name":"R","version":"4.4.0"}],"abstract":"This paper aims to answer two main questions. First, what is the number of people exposed to climate hazards in LAC, and whether the exposure rate is higher for the poor  than the non-poor. Second, whether there are hotspots, namely areas in the region where the incidence of climate hazard exposure and poverty rate are so high that they merit special policy attention. To answer these questions, we use an overlay of poverty maps and georeferenced information about climate hazards in the region as per methods by Doan, et al. (2023) but using five -rather than four- climate hazards (droughts, hurricanes, heatwaves, floods and landslides) and poverty maps at the administrative level 2 (ADM2, referring to county, district or municipality) rather than only provincial or departmental level (ADM1). Our estimates indicate that 36.9 percent of the population is exposed to at least one of the five climate hazards under consideration. If looking at the population in poverty only, the percentage is higher, 44.6 percent, whereas the exposure rate for the non-poor is 34.0 percent. Some areas in the territory of the continent experience high exposure to climate hazards and high poverty rates. These hotspots include about 10 percent of the population of the region. These areas are located in the Brazilian north-east, the upper-Amazon region of Colombia, Ecuador, Peru and Brazil, the Chaco region of Argentina, Brazil and Paraguay, the islands of the Caribbean, the western coast of the Gulf of California and the Yucatan Peninsula. ","topics":[{"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":"I32"},{"name":"Climate \u2022 Natural Disasters and Their Management \u2022 Global Warming","parent_id":"Q5","id":"Q54","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)"},{"id":"Q56","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Environment and Development \u2022 Environment and Trade \u2022 Sustainability \u2022 Environmental Accounts and Accounting \u2022 Environmental Equity \u2022 Population Growth","parent_id":"Q5"},{"id":"O54","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Latin America \u2022 Caribbean","parent_id":"O5"}],"license":[{"name":"Modified BSD3","uri":"https:\/\/opensource.org\/license\/bsd-3-clause\/"}],"authoring_entity":[{"name":"Samuel Freije-Rodr\u00edguez","affiliation":"World Bank","email":"sfreijerodriguez@worldbank.org"},{"name":"Ben J. Brunckhorst","affiliation":"World Bank","email":"bbrunckhorst@worldbank.org"},{"affiliation":"World Bank","email":"mkdoan@worldbank.org","name":"Miki Khanh Doan"},{"name":"Minh Cong Nguyen","affiliation":"World Bank","email":"mnguyen3@worldbank.org"},{"name":"Alejandro de la Fuente","affiliation":"World Bank","email":"adelafuente@worldbank.org"},{"email":"cgarciagarcia@worldbank.org","name":"Catalina Garcia Garcia","affiliation":"World Bank"}],"data_statement":"Some data is restricted and has not been included in the reproducibility package. For more details, please refer to the README file. ","scripts":[{"instructions":"See README in reproducibility package.","file_name":"RR_LAC_2025_402","zip_package":"RR_LAC_2025_402.zip","dependencies":"R dependencies are listed in the file renv.lock. Stata dependencies are listed in the ado folder.","title":"Reproducibility package for Are The Poor More Exposed To Climate Hazards In Latin America?","date":"2025-08","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank."}],"repository_uri":[{"uri":"https:\/\/reproducibility.worldbank.org","name":"Reproducible Research Repository (World Bank)"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"~ 25 minutes run time","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.","reproduction_instructions":"The package uses the Stata package datalibweb, which is accessible only to World Bank staff. The following instructions apply to World Bank staff.\n1. **Secure Access to Data:** Access the datasets not included in the package. The package relies on the Stata command datalibweb to get access to some datasets, which is only accessible to World Bank staff.  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      - Run the R code to prepare the intermediate files\n      - Open the do-file \"master\"\n      - Update the globals in line 5 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.","title_statement":{"title":"Reproducibility package for Are The Poor More Exposed To Climate Hazards In Latin America?","idno":"RR_LAC_2025_402"},"datasets":[{"license":"Creative Commons Attribution 4.0 International License (CC BY 4.0) ","name":"LAC subnational exposure estimates","note":"Source: : World Bank (2025). Compiled by the authors using spatial analysis. Instructions for accessing the raw hazard data files and the code to calculate subnational exposure estimates are available in the Reproducibility Package for Climate Risk Scorecard Vision Indicator 2021. For more details, please refer to that package: https:\/\/doi.org\/10.60572\/9j17-9n52.\nFile location: : 02.input\/lac_5haz_exp100_any.dta, 02.input\/lac_5haz_exp100_mun.dta, 03.intermediate\/Annex 1 and 2.xlsx","access_type":"Included in the package."},{"access_type":"Included in the package.","license":"Creative Commons Attribution 4.0 International License (CC BY 4.0) ","note":"Source: Data produced by the project team using an R script (01.code\/R\/lac_combined_shapefile.R) that combines multiple administrative boundary datasets, detailed in the README. Input shapefiles (listed in 02.input\/LAC boundaries.xlsx) are not included in the package but are available from their respective source. Poverty map shapefiles for seven countries (Brazil, Chile, Colombia, Honduras, Mexico, Panama, Peru) is made available on the World Bank Development Data Hub at the links below (except Honduras). The combined LAC shapefile  is in 03.intermediate\/shapefiles\/.\nCHL: https:\/\/datacatalog.worldbank.org\/int\/search\/dataset\/0066885\/chile_communal_estimates_of_income_and_multidimensional_poverty_2022; \nCOL: https:\/\/datacatalog.worldbank.org\/int\/search\/dataset\/0066886\/monetary_poverty_mapping_in_colombia; \nMEX: https:\/\/datacatalog.worldbank.org\/int\/search\/dataset\/0066887\/measuring_poverty_in_mexican_municipalities_2020; \nBRA: https:\/\/datacatalog.worldbank.org\/int\/search\/dataset\/0066884\/vulnerability_levels_of_brazilian_municipalities; \nPAN: https:\/\/datacatalog.worldbank.org\/int\/search\/dataset\/0066888\/poverty_and_inequality_in_panama_district_and_township_maps_2015; \nPER: https:\/\/datacatalog.worldbank.org\/int\/search\/dataset\/0066889\/peru_poverty_map__district_2018; \nECU: https:\/\/datacatalog.worldbank.org\/int\/search\/dataset\/0066890\/poverty_map_ecuador_2022.\n\n","name":"LAC boundaries"},{"access_type":"Included in the package.","name":"World Bank Country and Income Groups","note":"Source: : World Bank (2024).\nFile location: 02.input\/ctrn_names.dta","uri":"https:\/\/data.worldbank.org\/country"},{"access_type":"Restricted and not included in the package.","name":"Global Monitoring Database (GMD)","note":"Source: World Bank (2025). Data were obtained from the World Bank Datalibweb platform (datalibweb2.worldbank.org\/home) using the Stata package datalibweb. Access to survey data in the Global Monitoring Database (GMD) is restricted to World Bank staff using Bank-managed computers and is not available to external users. While most GMD surveys are available internally, some require users to request access through the Datalibweb platform.\nFile location: 02.input folder, in country subfolders for Brazil, Chile, Colombia, Ecuador, Honduras, Mexico, Panama, and Peru.\n\n"},{"name":"LAC subnational survey estimates ","access_type":"Restricted and not included in the package. Please contact the authors to request access to the dataset.","note":"Source: World Bank. Compiled by the authors. The file was created manually using $6.85 (2017 PPP) poverty rates from the Subnational Poverty and Inequality Database (SPID) (https:\/\/datacatalog.worldbank.org\/int\/search\/dataset\/0064796\/subnational_poverty_and_inequality_database_spid) for ARG, BOL, CRI, GTM, HTI, NIC, PRY, SLV, and URY; GMD data via datalibweb for DOM; and national poverty rates from PIP (AM24 version) for BLZ, GRD, GUY, JAM, LCA, SUR, TTO, and VEN.\nFile location: 02.input\/LAC subnational survey estimates 685.xlsx"},{"note":"Source: Data were extracted from papers and\/or files obtained from National Statistical Offices (NSOs), as described in the README, through country Poverty Economists. \n\nFile location: 02.input in country subfolders: BRA\/BRA_mun_SPrate1.dta, CHL\/LVL3_Income2022_cod_comuna.csv, COL\/COL_pop2020.xlsx, COL\/LVL3_Municipalities_ADM2_PCODE.csv, ECU\/LVL1_Provinces_2022_DPA_DESPRO.csv, PAN\/LVL3_Corregimientos2015_PROV_ID-DIST_ID.csv, PAN\/pan2022sae.dta, MEX\/LVL1_Municipalities_CVEGEO_short.dta, MEX\/LVL2_Municipalities_CVEGEO_short.dta, PER\/LVL1_District_2018_UBIGEO.dta, PER\/per2018_dist.dta, HND\/LVL1_Municipalities_Poverty_MUNICIPIO.csv, HND\/HND2019_pop.dta.\n\n","access_type":"All datasets except for Honduras are included in the package; access to the Honduras data can be requested from the authors.","name":"Poverty map database"}],"output":[{"type":"Working Paper","description":"Policy Research Working Papers (PRWP)","title":"Are The Poor More Exposed To Climate Hazards In Latin America?"}],"contacts":[{"name":"Samuel Freije-Rodr\u00edguez","affiliation":"World Bank","email":"sfreijerodriguez@worldbank.org"},{"email":"reproducibility@worldbank.org","name":"Reproducibility WBG","affiliation":"World Bank"}],"geographic_units":[{"name":"Latin America","code":"LAC"}]},"tags":[{"tag":"DOI"},{"tag":"Open Code"},{"tag":"Restricted Data"}],"schematype":"script"}