Following Bruhn, Demirguc-Kunt, and Singer (forthcoming), Table A.6 uses the 2020 Bertelsmann Stiftung Transformation Index (BTI) as a measure of competition. As in the earlier paper, we interact this measure with labor productivity (the main effect is subsumed in the country fixed effect). Importantly, we also add interaction terms of the BTI with our measures of government support. These interaction terms are not statistically significant in Table A.6. Thus, we do not find evidence that the relationship between government support and firm performance depends on the competition environment.

With respect to reallocation from less productive to more productive firms, the results in Table A.6 suggest that the effect of competition persists in the medium run. The interaction terms between the BTI and labor productivity are of a similar magnitude as in Bruhn, Demirguc-Kunt, and Singer (forthcoming), although the coefficient for “Anticipate falling into arrears” in Table A.6 is not statistically significant at conventional levels. The exception is that the coefficient for “Percentage change in sales” is much smaller than in Bruhn, Demirguc-Kunt, and Singer (forthcoming), which may be because the reference period here is different. In the short run, change in sales was relative to 2019, while change in sales here is relative to the previous year. That is, competition influenced the initial reallocation in sales from low to high productivity firms but did not determine additional reallocation. It is worth nothing that this additional reallocation was also much smaller in magnitude, with the average percentage change in sales being -1.98 in the medium run (Table A.1), compared to -23.98 in Bruhn, Demirguc-Kunt, and Singer (forthcoming).

# **5.3 Using country-sector fixed effects**

The analysis in Section 4 controls for country and sector fixed effects. Here, we do a robustness check with country-sector fixed effects since governments may have directed support to those sectors that were hit harder in their country.

Table A.7 replicates the results in Tables 5 and 6 but replacing country and sector fixed effects with country-sector fixed effects. The results are similar, showing that our findings are robust to controlling for country-sector fixed effects.

# **5.4 Controlling for management quality**

Although the analysis in Table 5 and 6 controls for many firm characteristics, the findings could be subject to omitted variable bias. Most notably, an unobserved measure of firm quality could drive both the probability of receiving government support and subsequent firm performance. For example, firms with better managers may be more likely to apply for government support and may also perform better during a crisis. The ES include a measure of management quality, based on 11 questions that are aggregated following Grover and Karplus (2021) and Bloom et al. (2019). Unfortunately, the management quality measure is only available for firms with 20 or more employees. Table A.8 Panel A1 replicates the results from Table 5 in this smaller sample. As in Table 5, we find no statistically significant relationship between receiving government support in Round 1 or 2 and firm performance in Round 3. We then control for management quality in Panel A2 of Table A.8, which leaves the coefficients on Round 1 or 2 support basically unchanged.

9