Economic Impact of the Socio-Political Crisis in the Northwest and Southwest Regions of Cameroon: A Forward Difference-in-Differences Approach

Jared Greathouse (), Vincent Nossek () and Pierre Mandon ()
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Jared Greathouse: Georgia State University - USG - University System of Georgia
Vincent Nossek: CERDI - Centre d'Études et de Recherches sur le Développement International - IRD - Institut de Recherche pour le Développement - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne, WBG = GBM - World Bank Group = Groupe Banque Mondiale
Pierre Mandon: WBG = GBM - World Bank Group = Groupe Banque Mondiale, CERDI - Centre d'Études et de Recherches sur le Développement International - IRD - Institut de Recherche pour le Développement - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne

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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 the socio-political crisis in Cameroon's Northwest and Southwest regions and associated recovery dynamics. Using quarterly data from 2013-2024 across 105 subnational regions, we find that the crisis reduced mean nighttime light intensity by 25 percent and total output by 28 percent in the Northwest region over seven years.Conversely, we observe that economic activity in the Southwest region increased by approximately 32 percent over five years, a divergence potentially attributable to multiple factors including greater connectivity, economic diversification, a more favorable business environment, and political economy considerations. 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 pretreatment 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's economic costs and recovery potential in fragile and conflict-affected states where conventional data sources are unreliable.

Keywords: Recovery; Satellite data; Nighttime lights; Forward difference-in-differences; Conflict; Causal inference; Cameroon (search for similar items in EconPapers)
Date: 2026-02-23
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