# **Appendix E. Political Economy and COVID-19-Related School Closure Policies**

Political, financial, and healthcare factors may have influenced the way countries around the world handled the initial outbreak of the COVID-19 pandemic and the policies put in place to limit the spread of the virus. In this section, we examine how certain macroeconomic factors, measured before the pandemic, could have influenced a government's decision whether or how long to mandate a school closure policy due to COVID19. In this section we use this analysis to support the claim that school closures related to COVID-19 can be considered an exogenous shock.

In Table E1 we present country level regression analysis to estimate how a set of macroeconomic indicators in a country may be correlated with the likelihood that a school closure policy due to COVID-19 was put in place at any point during the survey period. First, we examine female labor force participation<sup>6</sup> prior to the pandemic as one might be concerned that countries that value women’s work more highly may be more likely to keep schools open or reopen schools early despite the ongoing COVID-19 pandemic. Second, we examine the correlation of the Freedom House Index (modified) and the likelihood of a school closure policy<sup>7</sup> since if women can vote and exert political power in their country, they may have a greater influence on political leaders to keep schools open. A third macro indicator we examine is the percentage of individuals using the internet within a country<sup>8</sup> as one might expect that those countries with greater internet penetration have more opportunities to shift toward home-based learning during the pandemic and therefore are more likely to keep schools closed. In Table E1 we also include the relationship between the gender norms constructs from the FoB survey as described in Appendix D and the likelihood of a school closure policy related to COVID-19 as countries with more liberal attitudes towards gender equality before the pandemic may have been influenced to open schools. Finally, we examine the correlation between a country’s wealth as measured by GDP per capita<sup>9</sup> and the likelihood of a school closure policy. Richer countries may face different pressures to relatively poorer countries to keep schools open/closed.

The results in Table E1 show that overall school closure policies related to COVID-19 are independent of the macro indicators for female labor force participation, Freedom House Index and the beliefs towards gender equality.<sup>10</sup> We find that a greater internet penetration within a country means a school closure policy related to COVID-19 was less likely to be mandated. In addition, we find that GDP per capita of a country is also negatively associated with a school closure policy related to COVID-19. Countries with greater wealth are expected to have higher internet penetration and once we control for GDP, we find that the correlation is no longer statistically significant.

In graphs E1-E3 below we show the relationship between GDP and our main outcomes of interest. In graph E1 we can see there is a negative relationship between GDP and business closure rates. We show a positive correlation between GDP and the progressiveness of the society. Throughout the analysis of the school closure shock on business outcomes our preferred specification includes a control for log of GDP per capita.

> 6 Measured as the rate (% of female population ages 15+. Source: https://data.worldbank.org/indicator/SL.TLF.CACT.FE.ZS

> 7 This is estimated using the Freedom House Index which measures how unrestricted a country is in terms of its electoral process. It is modified because we restrict to use 3 components: electoral process, political pluralism and participation, and function of government. Source:  https://freedomhouse.org/report/freedom-world

> 8 Percentage of population with access to internet. Source: https://data.worldbank.org/indicator/IT.NET.USER.ZS

> 9 Transformed to natural logarithm and in US dollars. https://data.worldbank.org/indicator/NY.GDP.PCAP.CD.

> 10 Only the perceived community norm by women entrepreneurs shows a negative relationship with school closure (significant at the 10% level) that is no longer statistically significant once we control for GDP per capita.

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