{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2025-11-18","version":"1"},"project_desc":{"authoring_entity":[{"name":"Pierre Mandon","affiliation":"World Bank Group","email":"pmandon@worldbank.org"},{"name":"Vincent Nossek","affiliation":"World Bank Group","email":"vnossek@worldbank.org"},{"name":"Jared Greathouse","affiliation":"Georgia State University","email":"jgreathouse3@student.gsu.edu"}],"title_statement":{"title":"Reproducibility package for Economic Impact Of Cameroon\u2019s Anglophone Crisis: A Forward Difference-In-Differences Approach","idno":"RR_CMR_2025_456"},"data_statement":"Data is publicly available and included in the reproducibility package.","software":[{"name":"Python","version":"3.12.10"}],"scripts":[{"title":"Reproducibility package for Economic Impact Of Cameroon\u2019s Anglophone Crisis: A Forward Difference-In-Differences Approach","date":"2025-11","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_CMR_2025_456","zip_package":"RR_CMR_2025_456.zip","dependencies":"Python dependencies are stored in poetry.lock file."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2025-11-18","abstract":"The economic consequences of violent conflict pose significant challenges for development policy, yet measuring these impacts remains methodologically difficult in data-scarce environments. This paper employs the novel Forward Difference-in-Differences estimator with satellite-based nighttime light intensity data to analyze the economic impact of Cameroon\u2019s Anglophone Crisis and associated recovery efforts. Using quarterly data from 2013-2024 across 105 subnational regions, we find that the conflict reduced mean nighttime light intensity by 25 percent and total output by 28 percent in the Northwest region over seven years. Conversely, targeted economic recovery investments in the Southwest region likely increased both measures by approximately 32 percent over five years following intervention. Our methodology addresses key limitations of traditional difference-in-differences and synthetic control methods when applied to heterogeneous donor pools by selecting optimal subsets of control units whose pre-treatment trajectories most closely match treated units. The results demonstrate that modern causal inference methods combined with satellite remote sensing data provide credible estimates of conflict\u2019s economic costs and recovery potential in fragile and conflict-affected states where conventional data sources are unreliable.","geographic_units":[{"name":"Cameroon","code":"CMR"}],"keywords":[{"name":"Cameroon"},{"name":"Causal Inference"},{"name":"Conflict"},{"name":"Forward Difference-In-Differences"},{"name":"Nighttime Lights"},{"name":"Recovery"},{"name":"Satellite Data"}],"topics":[{"id":"C21","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Cross-Sectional Models \u2022 Spatial Models \u2022 Treatment Effect Models \u2022 Quantile Regressions","parent_id":"C2"},{"id":" C23","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Panel Data Models \u2022 Spatio-temporal Models","parent_id":"C2"},{"id":" D74","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Conflict \u2022 Conflict Resolution \u2022 Alliances \u2022 Revolutions","parent_id":"D7"},{"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":" O55","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Africa","parent_id":"O5"}],"output":[{"type":"Working Paper","description":"Policy Research Working Papers (PRWP)","title":"Economic Impact Of Cameroon\u2019s Anglophone Crisis: A Forward Difference-In-Differences Approach"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"Runtime: 3 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":"Pierre Mandon","affiliation":"World Bank","email":"pmandon@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"datasets":[{"name":"NASA\u2013NOAA VIIRS Day\/Night Band Nighttime Lights","uri":"https:\/\/doi.org\/10.5067\/VIIRS\/VNP46A2.001","license_uri":"https:\/\/developers.google.com\/terms","note":"Source: Google Earth Engine","access_type":"Data is publicly available and included in the reproducibility package.","citation":"NASA LP DAAC. (2024). VIIRS\/NPP Gap-Filled Lunar BRDF-Adjusted Nighttime \nLights Daily L3 Global 500m Linear Lat Lon Grid, Version 1 [Data set]. \nNASA EOSDIS Land Processes DAAC. https:\/\/doi.org\/10.5067\/VIIRS\/VNP46A2.001","license":"Open access with citation requested"},{"name":"Global Administrative Unit Layers (GAUL) (2024)","note":"Source: Food and Agriculture Organization of the United Nations (FAO)","access_type":"Data is publicly available and included in the reproducibility package.","citation":"Franceschini, G., Khan, A., Moretti, L., Nyabuti, K., Asif, M., Bezuidenhoudt, E. and Morteo, K. 2025. The Global Administrative Unit Layers (GAUL) 2024. Technical guidelines. Rome, FAO. https:\/\/doi.org\/10.4060\/cd4262en","uri":"https:\/\/doi.org\/10.4060\/cd4262en","license":"Creative Commons Attribution-4.0 International licence (CC BY 4.0)","license_uri":"https:\/\/gee-community-catalog.org\/projects\/gaul\/#license"},{"uri":"https:\/\/doi.org\/10.1080\/17538947.2024.2390454","citation":"Pesaresi, M., Schiavina, M., Politis, P., Freire, S., Krasnod\u0119bska, K., Uhl, J. H., \u2026 Kemper, T. (2024). Advances on the Global Human Settlement Layer by joint assessment of Earth Observation and population survey data. International Journal of Digital Earth, 17(1). https:\/\/doi.org\/10.1080\/17538947.2024.2390454","name":"Global built-up surface 2025","note":"Source: Google Earth Engine","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution-4.0 International licence (CC BY 4.0)","license_uri":"https:\/\/ec.europa.eu\/info\/legal-notice_en"}],"reproduction_instructions":"This package uses intermediate processed data. The raw Earth Engine data requires API access and authenticated Google Earth Engine projects, so it is not included in this package. The package includes SCM_CameroonWork.ipynb, which processes the raw Earth Engine data to generate the intermediate datasets used in the analysis (you don't need to run this file as the intermediate data is already provided). To successfully reproduce the analysis, follow these steps:\n1. Install the provided Python environment called `poetry.lock` file\n2. Run `cameroon_results_vectorized.py`.\n4. The following outputs will be generated :\n`fdid_summary_output2.txt`\n `fig1.png`","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 6226R CPU @ 2.90GHz\n\u2022 Memory available: 16.0 GB"},"tags":[{"tag":"DOI"},{"tag":"Open Code"},{"tag":"Open Data"}],"schematype":"script"}