firms represent a smaller share of aggregate activity: high-risk firms represent only 7.1% of countrywide sales compared to the low-risk firms that represent 41.2% of aggregate sales (Column 2). As a result, the contribution of high-risk firms as a group to overall indebtedness is smaller, 0.11 percentage points, than the contribution of low-risk firms, 0.53 percentage points (Column 3). The small weight of riskier firms in the aggregate therefore mitigates the micro adverse selection documented in the previous sections. Summing across all risk groups shows that the indebtedness of firms that use the credit program increases by 1.35 percentage points. This change in debt corresponds to 2.9% of the GDP reported by macro statistics. Those formal firms experience an increase of 3.6% of GDP in guaranteed credit (Table 11) and a decline in non-guaranteed credit.

Next, we extend the analysis to include the non-program users.<sup>24</sup> The leverage of program users increases by 9.71 percentage points during 2020, while the leverage of nonusers actually falls by 1.06 percentage points (Panel B). However, given that program users have a low weight in the aggregate economy (13.9% compared to 86.1% of non-users), total indebtedness across all firms increases by only 0.44 percentage points. Last, partitioning all active firms (users and non-users) by risk confirms that the higher the risk, the larger the within-change in debt (Panel C). But the higher the risk, the smaller their weight in the economy, thereby attenuating the increase in aggregate risk.<sup>25</sup> This analysis shows why the micro results presented in previous sections can have a relatively small impact at the macro level.

# **7.2 Risk Sharing between Banks and the Government**

Banks and the government share, absorb, and mitigate the risks that the credit program entails by dealing with the expected default risk from the loans granted, unexpected credit risk, and funding needs for the banks. To understand the risks involved, it helps to measure the magnitude of the program allocation across groups of firms. We focus here on firms by risk category.<sup>26</sup> Micro data indicate that by the end of 2020, banks provide guaranteed loans worth US$11,467 million, or 4.6% of 2019 GDP, including loans to formal firms and natural persons

> 24 We use Equations (5) and (6) to partition firms into credit program users and non-users and measure the contribution of these groups to overall indebtedness.

> 25In unreported results, we decompose indebtedness into two additional margins: banking status and size. Across the different partitions of firms, large increases in firm leverage within groups happen for firms with a relatively small weight at the aggregate level.

> 26As an alternative, Appendix Table 6 reports the results of partitioning firms by size. This is useful because the public guarantee varies by size (from 85% for small firms to 60% for large firms, as explained in Section 4), effectively determining how firms and the government share risk. Furthermore, the size categorization allows us to cover all firms in our sample, permitting a better mapping between the debt levels computed from micro and macro data.

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