{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2026-08-25","version":"1"},"project_desc":{"authoring_entity":[{"name":"A. Patrick Behrer","affiliation":"World Bank","email":"abehrer@worldbank.org"},{"name":"Saher Asad","affiliation":"World Bank","email":"sasad1@worldbank.org"},{"name":"Monica Yanez-Pagans","affiliation":"World Bank","email":"myanezpagans@worldbank.org"},{"name":"Martin Philipp Heger","affiliation":"World bank","email":"mheger1@worldbank.org"}],"title_statement":{"title":"Reproducibility package for Air Pollution And Student Learning In Pakistan","idno":"RR_PAK_2026_703"},"data_statement":"Some data is restricted and has not been included in the reproducibility package. For more details, please refer to the README file. \n\n","software":[{"name":"R","version":"4.5.2"},{"name":"Stata","version":"19.5 MP"}],"scripts":[{"title":"Reproducibility package for Air Pollution And Student Learning In Pakistan","date":"2026-08","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_PAK_2026_703","zip_package":"RR_PAK_2026_703.zip","dependencies":"R dependencies are listed in the file renv.lock. Stata dependencies are listed in the ado folder."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2026-08-25","abstract":"Ambient air pollution is a major health risk, but its implications for human capital formation are not well understood, particularly in low- and middle-income countries where exposure is high. This paper estimates the causal effect of sustained exposure to fine particulate matter (PM2.5) on primary-school learning in rural Punjab, Pakistan. We combine longitudinal student achievement data from the Learning and Educational Achievements in Punjab Schools (LEAPS) project with high-resolution satellite-based PM2.5 estimates. To address endogeneity of pollution to local economic activity, we exploit plausibly exogenous variation generated by open burning of agricultural residue interacted with wind direction, constructing school-year measures of upwind fire exposure as instruments for local PM2.5. Our instrumental variables estimates show that higher school-year PM2.5 significantly slows learning, with larger effects in mathematics than in language subjects. Results are consistent with impacts operating during instructional months: pollution exposure during the school year predicts lower achievement, while exposure during vacation months has little explanatory power. We find statistically imprecise heterogeneity by age and gender, opposite to patterns found in comparable settings. We organize the analysis around a simple framework in which learning depends on attendance, cognition, effort, and instructional quality, each a function of exposure to poor air quality. Pollution increases student absences, but this attendance channel explains only a small portion of the total effect, implying that most of the learning loss is non-attendance-related and likely operates through the framework\u2019s other channels\u2014direct effects on cognition, reduced effort, and degraded instructional quality.","geographic_units":[{"name":"Pakistan","code":"PAK"}],"keywords":[{"name":"Education"},{"name":"Air Pollution"},{"name":"Learning Outcomes"},{"name":"Pakistan"}],"topics":[{"id":"I21","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Analysis of Education","parent_id":"I2"},{"id":" I23","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Higher Education \u2022 Research Institutions","parent_id":"I2"},{"id":" O12","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Microeconomic Analyses of Economic Development","parent_id":"O1"},{"id":" Q5","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Environmental Economics","parent_id":"Q"}],"output":[{"type":"Working Paper","description":"Policy Research Working Papers (PRWP)","title":"Air Pollution And Student Learning In Pakistan"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"Run time ~ 40 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":"MIT License","uri":"https:\/\/opensource.org\/license\/mit"},{"name":"World Bank IGO Rider","uri":"https:\/\/github.com\/worldbank\/metadata-editor\/blob\/main\/WB-IGO-RIDER.md"}],"contacts":[{"name":"A. Patrick Behrer","affiliation":"World Bank","email":"abehrer@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"datasets":[{"name":"Learning and Educational Achievements in Punjab Schools (LEAPS) - Analysis Panel","note":"Data accessed in February 2025. Longitudinal survey of primary education in Punjab, Pakistan. Contains child-level test scores in Urdu, English, and Mathematics plus school, teacher, and household modules; rounds 2003-2006. Supplies the outcome variable (standardized test score all_theta_pdqc) and student\/household covariates for the school x test-year analysis panel (N approximately 55,862 students). Not included in the replication package, See the README for data access instructions. File location: data\/constructed\/analysis_panel_v1.dta \/constructed). \n\nWe used a restricted intermediate dataset `analysis_panel_v1` which was requested from A. Patrick Behrer  (abehrer@worldbank.org). The intermediate dataset was used because the data owners which were to provide the raw data did not respond to our email. Future replicators seeking access to the original raw dataset may contact the data owners at \"leaps@hks.harvard.edu.\" A variables list for the restricted intermediate dataset is provided in the package: \"variable_inventory.csv\"","access_type":"Data access was granted directly to the study authors by the data owners\/managers. It was obtained with a custom data license that does not allow for redistribution and it is not included in the reproducibility package.","license":"Custom License","citation":"Andrabi, Tahir, Jishnu Das, Asim Ijaz Khwaja, Tara Vishwanath, and Tristan Zajonc. 2007. \"Learning and Educational Achievements in Punjab Schools (LEAPS): Insights to Inform the Education Policy Debate\" [dataset]. Washington, DC: World Bank. https:\/\/www.leaps.hks.harvard.edu\/data. Accessed February 2025."},{"name":"SatPM (Satellite-Derived Particulate Matter) V5 GL 02 Surface PM2.5","note":"Gridded satellite-derived ground-level PM2.5 (\u00b5g\/m\u00b3, ~0.01\u00b0) from the  Atmospheric Composition Analysis Group (ACAG); \"Hybrid\"\/GWR product combining satellite AOD, GEOS-Chem, and geographically weighted regression against ground monitors.  Area-averaged over LEAPS school buffers \u2192 school \u00d7 month exposure \u2192 the endogenous  regressor in the IV analysis. Years extracted: 1999\u20132020. See the README for data access instructions. File location: data\/raw. Data accessed in February 2025. ","access_type":"Data is publicly available but not included in the reproducibility package ","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","uri":"https:\/\/www.satpm.org\/v5-gl-02","citation":"van Donkelaar, A., M. S. Hammer, L. Bindle, M. Brauer, J. R. Brook, M. J. Garay, N. C. Hsu, O. V. Kalashnikova, R. A. Kahn, C. Lee, R. C. Levy, A. Lyapustin, A. M. Sayer, and R. V. Martin. 2021. \"Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty\" [dataset]. Environmental Science and Technology 55 (22): 15287-15300. Dataset version: ACAG SatPM2.5 V5 GL 02. https:\/\/doi.org\/10.1021\/acs.est.1c05309. Accessed February 2025. ","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/?ref=chooser-v1"},{"name":"NASA FIRMS (Fire Information for Resource Management Systems) - Active Fire Detections","note":"Data accessed in June 2019. Moderate Resolution Imaging Spectroradiometer (MODIS) Terra\/Aqua thermal-anomaly (active-fire) detections, pre-joined to school locations by buffer distance (5\/10\/20\/50 km) and classified upwind\/downwind\/orthogonal relative to ERA5-derived wind direction to construct the excluded instrument (upwind fire counts). Bundled as author-processed school-buffer extracts. See the README for data access instructions. File location: data\/raw\/","access_type":"Data is publicly available but not included in the reproducibility package ","license":"Open License","uri":"https:\/\/firms.modaps.eosdis.nasa.gov","citation":"NASA FIRMS. 2019. \"MODIS Collection 6.1 Hotspot \/ Active Fire Detections MCD14ML\" [dataset]. NASA FIRMS. https:\/\/firms.modaps.eosdis.nasa.gov. DOI: 10.5067\/FIRMS\/MODIS\/MCD14ML. Accessed June 2019.","license_uri":"https:\/\/www.earthdata.nasa.gov\/data\/projects\/lance#ed-lance-disclaimer"},{"name":"ERA5-Land Hourly Reanalysis (Copernicus Climate Data Store)","note":"Data accessed 2020-2025. ERA5-Land hourly reanalysis, used two ways: (1) surface-weather controls  (t2m; d2m \u2192 relative humidity via the Magnus formula; precipitation; surface pressure),  area-averaged over school buffers and collapsed to school \u00d7 test-year means (temperature  binned in 2 \u00b0C intervals); (2) 10 m wind (via Google Earth Engine, `ECMWF\/ERA5_LAND\/\u2026`) to  set wind direction for the directional fire instrument. Years ~2002\u20132016.. See the README for data access instructions.  File location: data\/raw","access_type":"Data is publicly available but not included in the reproducibility package ","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","uri":"https:\/\/cds.climate.copernicus.eu\/datasets\/reanalysis-era5-land","citation":"Munoz Sabater, J. 2019. \"ERA5-Land Hourly Data from 1950 to Present\" [dataset]. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381\/cds.e2161bac. https:\/\/cds.climate.copernicus.eu\/datasets\/reanalysis-era5-land. Accessed 2020-2025.","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"name":"MERRA-2 (Modern-Era Retrospective analysis for Research and Applications version 2) - temperature inversions","note":"Data accessed in March 2023. NASA MERRA-2 collection M2I3NPASM (inst3_3d_asm_Np): 3-hourly,  instantaneous, pressure-level assimilated meteorological fields (0.625\u00b0 \u00d7 0.5\u00b0), V5.12.4.  Air temperature (T) on pressure levels 1\u201319 is extracted over school buffers to identify  temperature inversions (which trap PM2.5 near the surface), feeding the pollution-exposure  construction (`07_import_MERRA.do`). Years 2003\u20132016 consumed. See the README for data access instructions.  File location: data\/raw","access_type":"Data is publicly available but not included in the reproducibility package ","license":"Open License","uri":"https:\/\/disc.gsfc.nasa.gov\/datasets\/M2I3NPASM_5.12.4\/summary","citation":"Global Modeling and Assimilation Office (GMAO). 2015. \"MERRA-2 inst3_3d_asm_Np: 3d, 3-Hourly, Instantaneous, Pressure-Level, Assimilation, Assimilated Meteorological Fields V5.12.4\" [dataset]. Greenbelt, MD: Goddard Earth Sciences Data and Information Services Center (GES DISC). DOI: 10.5067\/QBZ6MG944HW0. https:\/\/doi.org\/10.5067\/QBZ6MG944HW0. Accessed March 2023.","license_uri":"https:\/\/www.nasa.gov\/privacy\/"},{"name":"District-Level Annual and Summer PM2.5 Levels - Figure 1 Derived Data","note":"Author-generated district-level annual and summer PM2.5 levels and deviations (2000-2020), derived from the Van Donkelaar V5 GL 02 product and bundled so Figure 1 renders offline without the raw NetCDFs. Generated for this replication package by Asad, Behrer, Heger, and Yanez Pagans (2026). Upstream source: van Donkelaar et al. (2021) ACAG SatPM2.5 V5 GL 02 (see separate entry). No external access needed; file is bundled and read directly by the Figure 1 script. File location: output\/figdat\/fig1_data.csv.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Custom License","citation":"Asad, Behrer, Heger, and Yanez Pagans. 2026. \"District-Level Annual and Summer PM2.5 Levels - Figure 1 Derived Data\" [dataset]. Author-generated for this replication package. Upstream source: van Donkelaar et al. (2021), ACAG SatPM2.5 V5 GL 02, https:\/\/doi.org\/10.1021\/acs.est.1c05309."}],"reproduction_instructions":"The package uses intermediate data. The code used to process the raw data into intermediate data is included in the code folder for transparency. However, we did not verify the code that generates the intermediate data, as one of the raw datasets was not accessed. Instead, reviewers verified the outputs generated from the intermediate data which is also requested from the author and not included in the package.\n\nTo reproduce the findings in this paper, a replicator must:\n1. Secure Access to Data: Access the datasets not included in the package. See the Datasets section for more details\n1. Open the do file `run_all`, update the directory, install the required directories and run the script\n2. Open the R script `03_make_figures` install the required directories and run the script\n\nFuture replicators seeking access to the original raw dataset may contact the data owners at \"leaps@hks.harvard.edu.\" A variables list for the restricted intermediate dataset is provided in the package: \"variable_inventory.csv\"\n\nSince some of the data is restricted, the package includes the outputs produced by the replicators, which can be used to review the results presented in the paper\n","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) Gold 5218 CPU @ 2.30GHz (2.30 GHz) (2 processors)\n\u2022 Memory available: 16 GB"},"datacite":{"creators":[{"givenName":"A. Patrick","familyName":"Behrer","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Saher","familyName":"Asad","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Monica","familyName":"Yanez-Pagans","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Martin Philipp","familyName":"Heger","nameType":"Personal","affiliation":[{"name":"World bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]}],"titles":[{"lang":"en","title":"Reproducibility package for Air Pollution And Student Learning In Pakistan"},{"title":"RR_PAK_2026_703","titleType":"Other"}],"publisher":"World Bank","publicationYear":"2026","types":{"resourceType":"Reproducibility package","resourceTypeGeneral":"Other"},"url":"https:\/\/reproducibility.worldbank.org\/index.php\/catalog\/study\/RR_PAK_2026_703","language":"en"},"tags":[{"tag":"DOI"},{"tag":"Open Code"},{"tag":"Restricted Data"}],"schematype":"script"}