# 2.2. What are the characteristics of disruptions-prone firms?

Country-level factors are important for the individual firm. The empirical analysis of our firm-level data thus introduces country-specific controls common to all firms in corresponding economy alongside general country-level fixed effects. Country-level data on economic and demographic variables is sourced from the WDI and WGI databases. Climate data to measure natural risks has been extracted from the ERA5 climate re-analysis model (Copernicus Climate Change Service, 2018).<sup>1</sup> While the impact of infrastructure disruptions is typically transmitted across wide networks, they are not felt by all firms in the same way. This section focuses on statistical properties of firm-level variables do identify correlates of disruptions to shed light on exposure and resilience factors. All firm-specific information is retrieved from the _Enterprise Surveys (ES)._ All specifications include two-digit ISIC (revision 3.1) sector fixed effects to capture production technology-induced exposure and other sector-specific factors. Standard errors are clustered at the regional level to account for regressor correlation with region fixed effects and uncertainty about regressors’ marginal effects being region-specific.

Table 2 summarizes the main empirical results. Specifically, it shows regressions of the full set of variables on i) the total annual duration of blackouts, ii) total annual duration of water supply disruptions or iii) a subjective index (1-4) of the severity of transport problems in overall business operation. Those three variables are directly or indirectly provided by the ES, while no similar information is given on telecommunication disruptions, unfortunately. Note that our global climate variables cover a selected set of geo coordinates, specifically up to three of the economically most important cities of each country. Thus, to reliably identify impacts of climate risks at the firm level (in particular extreme precipitation and storms), we restrict attention to firms in those cities, covering approximately a quarter of the full sample. Conclusions concerning non-climatic variables remain qualitatively unchanged in the full sample.

According to ISIC factor estimates, disruptions of **electricity** supply are significantly more prevalent within the mining sector, manufacturing of fabricated metal products as well as coke and petroleum refinement. By contrast, for air transport service providers, post and telecommunications as well as producers of telecommunication equipment, total annual blackout durations are significantly below average. This suggests that effective measures are taken to shield critical infrastructure to prevent outage-inflicted damage from spreading further. Moreover, larger and private firms tend to experience fewer outages while at the same time many outages cause firms to invest in own back-up generation. On the macro level, dynamism, high population density and growth is associated with more vulnerable electricity infrastructure while on the other hand outages and the business cycle are negatively related. Natural disasters do not seem to have a systematic impact on blackouts on the global level.

**Water** infrastructure disruptions tend to occur within the chemical industry, gastronomy and the production of food and beverages while wood and paper industries suffer significantly less water supply disruptions. As with electricity, larger firms experience less disruptions, while all other firm-level variables show no significance performance. On average, economies with higher urbanization are associated with fewer water supply irregularities. Concerning natural hazards, extreme precipitation and storms are

> 1 For a detailed description on how disaster risk variables have been constructed from hourly climate data, see appendix A.2.

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