lower-skilled labor. Third, we provide novel evidence on how country-level characteristics shape the impact of conflict on firms. We document that economic, social, and political conditions can either amplify or attenuate the effects of conflict exposure. Furthermore, we show that the specific mechanisms through which conflict affects firm activity vary systematically with these characteristics, suggesting that policy interventions to address the effects of conflict need to be context-specific and tailored to the conditions in which firms operate.

The paper proceeds as follows. Section 2 describes the data. Section 3 outlines the empirical strategy. Section 4 presents the results. Section 5 concludes.

# **2 Data**

## **2.1 Firm data**

Our main data source is the World Bank Enterprise Survey (WBES), a global dataset providing firm-level information for the manufacturing, retail, and other service sectors across 148 countries.<sup>4</sup> Data are collected through face-to-face interviews using a standardized questionnaire and are designed to be representative at the country level. The survey targets privately owned firms with at least five employees operating in the formal (non-agricultural) sector.<sup>5</sup> Our data cover the years 2006-2019 (to exclude the COVID-19 pandemic period).

We use a confidential version of the WBES global dataset, which also provides firms’ geo-localization. This information allows us to match each firm with conflict and political violence events occurring in its geographical neighborhood and is therefore essential for constructing the firm-specific measure of conflict exposure used in our analysis.<sup>6</sup> Another important feature of the WBES is that—although designed as a repeated cross-section—it includes a sizable panel component for a subset of countries, with some firms interviewed in multiple waves. As discussed in Section 3, our estimation strategy relies on firms for which geo-localized data are available and that belong to this panel component. Restricting further to firms with non-missing sales data, our main estimating sample consists of 36,087 firm-year observations across 89 countries.<sup>7</sup> Table A1 provides a detailed list

> 4The WBES dataset is the most comprehensive resource for conducting firm-level studies worldwide, as discussed in Besley and Mueller (2018), Fisman et al. (2024) and Armangu ́e-Jubert et al. (2024).

> 5Firms are selected using random sampling techniques with three stratification levels to ensure national representativeness across firm size (5–19 employees; 20–99 employees; and 100+ employees) and sector (manufacturing, retail, and other services). For details on the WBES sampling methodology, see `https://www.worldbank.org/content/dam/enterprisesurveys/documents/methodology/ Enterprise%20Surveys_Manual%20and%20Guide.pdf` .

> 6The WBES collected information on firm geo-localization in 120 countries. This information is missing for 5% of firm-year observations. For firms with geo-localization available for at least one survey wave, we impute the same location across other waves to increase the sample size. Results are virtually identical when excluding firms with imputed geo-localization.

> 7Of the 120 countries for which there is information on firm geo-localization, 89 have at least two survey

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