"Financial Development, Labor Markets, and Aggregate Productivity: Evidence from Brazil," with Bernardus Van Doornik
Revise and Resubmit, Journal of Financial Economics
We estimate the effect of an increase in the availability of bank credit on the employment and the wages of high- and low-skilled workers. To do so, we consider a bankruptcy reform that increased the legal protections of secured creditors, which led to an expansion of bank credit to Brazilian firms. We use detailed administrative data and an empirical strategy that exploits cross-sectional variation in the enforcement of the new legislation arising from differences in the congestion of civil courts. We find that the expansion in credit led to an increase in the skill intensity of firms and in within-firm returns to skill. To rationalize these findings, we design a model in which heterogeneous producers face constraints in their ability to borrow and have production functions featuring capital-skill complementarity. We use this framework to generate an industry-level measure of capital-skill complementarity, which we use to provide direct evidence that the effect of access to credit on skill utilization and the skill premium is driven by a relative complementarity between capital and labor.
Despite the prevalence of debt collection and the intense regulatory activity surrounding this industry, evidence on the causal impact of these practices on consumers is scarce. This paper conducts an empirical analysis of the effect of debt collection on traditional and alternative consumer credit and on indicators of financial health. I use individual credit record data and a research design that compares outcomes of consumers in states that restrict collection practices with those of consumers in counties that share a border but are located in a different state. I find that restricting collection activities leads to lower credit balances and limits, higher balances past due, and lower credit scores. Moreover, I find that payday borrowing increases once access to traditional credit declines, providing new evidence on the substitutability between traditional and alternative sources of credit.
Mentioned in: The Economist
"Modern Frameworks for Quantitative Economics," with Victor Duarte, Diogo Duarte, and Alexis Montecinos
Conditionally accepted, Journal of Economic Dynamics and Control
We investigate the performance of machine learning software and hardware for quantitative economics. We show that the use of modern numerical frameworks can significantly reduce computational time in compute-intensive tasks. Using the Least Squares Monte Carlo option pricing algorithm as a benchmark, we show that specialized hardware and software speeds the calculations by up to two orders of magnitude when compared to programs written in popular high-level programming languages, such as Julia and Matlab.
Works in Progress:
"Consumption and Portfolio Choice with Many Assets and Realistic Dynamics," with Victor Duarte, Aaron Goodman, and Jonathan Parker
"The Real Effects of Banking the Poor: Evidence from Brazil," joint with Adrien Matray
"Labor Misallocation Between the Private and Public Sectors: Evidence from Public Pension Reform in Brazil," joint with Adrien Matray