Estimated with weighted OLS, normalised survey stratification weights applied. Standard errors in parenthesis, clustered on region. Significance levels: *** 0.01, ** 0.05, * 0.10.

First, these estimates suggest a robust and significant negative impact of infrastructure disruptions on firm utilization rate. Power outages, water outages, and transportation issues all contribute to reducing utilization, and therefore productivity and revenues.

Second, estimates indicate that for water and transport, indirect effects may be as or even more important than direct impacts, while the indirect impact of power outages seems to be smaller. However, indirect effects are imperfectly measured using regional disruption levels, as point estimates for regionlevel variables are sensitive to different controls and show large standard errors.<sup>3</sup> Nonetheless, one implication is that estimates looking only at direct impacts of infrastructure disruptions may be missing a large part of the economic cost.

Third, the interaction term (between direct and indirect impacts) is positive for all types of infrastructure. This means that direct impacts are less severe if the firm’s backward and forward linkages are disturbed anyways – and conversely: supply chain mediated indirect effects cause less harm when the firm already suffers from direct disruptions.

The estimated model suggests that infrastructure disruptions have a significant economic cost in the form of reduced business utilization rates. In the case of electricity outages, measured by the annual selfreported total blackout duration, this effect is robust significant across model specifications. Following this estimate, 100 additional hours of blackout decrease utilization by 0.13 to 0.32 percentage points on average (Table 4 model III).4 Note that this estimate is close to the results in section 4.1. based on selfreported losses, which suggest that 100 hours of blackout would decrease the annual utilization rate by about 0.29 percentage points in the model without interaction (Table 4 model I). This makes us confident that our identification strategy in the previous section is valid and thus also provides reliable estimates for water and transportation.

A similar result is obtained for water outages, measured by the annual total outage duration. In this case, 100 additional hours of water outages are estimated to decrease utilization by up to 0.19 percentage points on average.<sup>5</sup> From among the three infrastructure variables considered here, water has the weakest explanatory power according to standardized beta coefficients (not shown).

For transport, there is also a significant impact of transport problems on the utilization rate, but numerical results are difficult to interpret since the metric is qualitative. In fact, it does not allow to investigate marginal effects, and we can only compare the _proportion_ of direct to indirect effects.

For assessing the impact of marginal increases in transport reliability, we use an alternative measure of transport reliability, the Logistic Performance Index’ (LPI) “timeliness” sub-indicator (Jaramillo et al., 2018). LPI can be used to proxy reliability, resilience and steadiness of transport infrastructure, i.e. the absence

> 3 Note that for transport, various country-level characteristics correlate with transport quality, making it hard to pin down indirect effects.

> 4 The average firm in the sample experiences 253.5 hours of blackout annually, while 10% of all firms face 720 hours or more.

> 5 The majority of firms does not face any water supply disruptions while a few firms have to cope with long and frequent interruptions. The top 5% of most disrupted firms face at least 120 hours, the top 1% faces 2700 hours or more.

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