riskier firms with access to the program.<sup>1</sup> At the macro level, risks appear to be small, in part because risky firms weigh little in the aggregate credit allocation. Although risky firms increase their indebtedness in percentage points the most, the overall amount of credit going to less risky firms is much larger (even when it represents a smaller increase in relative terms for them). Some of the features driving the micro and macro results are due to the program design, while others are due to how the demand and supply sides respond to incentives and to general market conditions.

The transaction-level data we gather are unique in their comprehensive nature and level of detail. We employ the universe of formal bank credit to all firms collected by Chile’s financial supervisory agency and high-frequency-matched administrative data for the universe of formal firms compiled by the tax authority and the central bank. The former include credit flows and balances, default history, firm loan applications, bank approvals and rejections, and terms of the individual transactions. The latter contain time-varying financial statements, input use, and sales collected monthly, plus industry and municipality of where firms are located. These micro data, especially loan applications and approvals, allow us to measure selection and to disentangle supply and demand factors determining the countrywide equilibrium allocation of credit. The micro data also enable us to estimate the macro risk by calculating risk at the firm level and then aggregating across types of firms.

In addition to offering novel data, the large and sudden quasi-natural experiment in Chile contains attractive features to study the drivers and effects of crisis credit. The size requirements of the credit program, dynamic lockdowns, and an alternative employment program, among other things, provide sources of exogenous variation and useful information to analyze the effects of the credit program implemented when the pandemic erupts. In exchange for banks granting loans at a predetermined low interest rate to most firms, the government offers to take most of the tail credit risk. The flat low interest rates alone would differentially increase demand from riskier borrowers who otherwise pay correspondingly higher risk premia under the status quo. However, to reduce this adverse selection while generating new financing, the program establishes that banks absorb the initial loss and a fraction of the remaining credit risk. New loans are not allowed to be used to repay existing loans, and firms with past due repayments are ineligible to participate in the program.<sup>2</sup>

> 1We use the term “adverse selection” in a loose sense to convey bank lending shifting toward riskier clients as our analysis lacks the standard presumption of asymmetric information. Our empirical estimations are based on observable information, and the model we present also has symmetric information.

> 2The policy in Chile has similarities with other public credit guarantee programs, such as those in Colombia, Italy, and the United Kingdom (OECD, 2017). It is also related to an array of credit programs implemented in more than 142 countries during the COVID-19 pandemic (Feyen et al., 2021).

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