This dissertation combines micro-level data and partial equilibrium models to understand how financial policies affect non-financial firms, with a particular focus on the role played by banks in such transmission. In the first chapter we study a large-scale intervention in the Brazilian banking sector characterized by a sudden increase in the supply of credit provided by commercial government banks. Theoretically, the effect of this type of policy is ambiguous: while it can increase the total amount of credit in the economy, it can also increase misallocation if government banks finance riskier firms with unproductive projects. We leverage credit registry data to document a series of empirical facts and test if the intervention alleviated inefficient underprovision of credit. We find that while the intervention led to a reduction in interest rates and to an increase in total credit from both government and private banks, government banks faced a significant increase in defaults. Loans to ex-ante indebted firms explain this increase in default for government banks. Moreover, neither the increase in total credit nor the reduction in interest rates had any observable effects on output or employment. Our results suggest that the intervention increased credit misallocation, and that adverse selection did not play a significant role in the allocation of credit in Brazil.
In the second chapter, we assess the role of banks in the Paycheck Protection Program (PPP), a large and unprecedented small-business support program instituted as a response to the COVID-19 crisis in the United States. In 2020, the PPP administered more than $525 billion in loans and grants to small businesses through the banking system. First, we provide empirical evidence of heterogeneity in the allocation of PPP loans. Firms that were larger and less affected by the COVID-19 crisis received loans earlier, even in a within-bank analysis. Second, we develop a model of PPP allocation through banks that is consistent with the data. We show that research designs based on bank or regional shocks in PPP disbursement, common in the empirical literature, cannot directly identify the overall effect of the program. Bank targeting implies that these designs can, at best, recover the effect of the PPP on a set of firms that is endogenous, changes over time, and is systematically different from the overall set of firms that ultimately receive PPP loans. We propose and implement a model-based method to estimate the overall effect of the program and find that the PPP saved 7.5 million jobs.
In the third chapter we further explore the Paycheck Protection Program (PPP) by asking what is the optimal allocation of funds across firms and the distortions caused by allocating these funds through banks. We show that it can be optimal to allocate funds to the least or most affected firms depending on the underlying distribution of the shock that firms face, the firms' financial position, and the total budget available for the program. In the model, as in the data, banks distort the allocation toward firms with more pre-pandemic debt and those less affected by the COVID-19 crisis. We characterize how this misallocation depends on the degree of asymmetric information between banks and the government. In an empirical application of our model, we estimate the PPP's effectiveness and compare it with alternative policies. A policy targeted at the smallest firms could have increased the program's effectiveness significantly.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/yvps-2327 |
| Date | January 2022 |
| Creators | De Souza Netto, Felipe Anderson |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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