"Financial Development and Labor Market Outcomes: Evidence from Brazil," with Bernardus Van Doornik

Journal of Financial Economics, Vol. 143(1): 550-568, 2022

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.

"Modern Frameworks for Quantitative Economics," with Victor Duarte, Diogo Duarte, and Alexis Montecinos

Journal of Economic Dynamics and Control Vol. 111, Feb 2020

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.


"Access to Credit and Financial Health: Evaluating the Impact of Debt Collection" 

Conditionally Accepted, Journal of Finance

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.  

Media: The Economist

"The Real Effects of Banking the Poor: Evidence from Brazil," with Adrien Matray


We use a large expansion of government-owned banks in cities with extremely low bank branch coverage and data on the universe of formal-sector employees in Brazil over 2000-2014 to study how financial development affects economic development and wage inequality. We find that higher financial development fosters firm creation and firm expansion, which increases labor demand and leads to higher average wages, especially for cities initially located in banking deserts. The gains produced by higher financial development are not shared equally, but instead monotonically increase with workers’ productivity, which leads to a substantial increase in inequality. This increase is concentrated in cities where the initial supply of skilled workers is low, indicating that talent scarcity is an important driver of how financial development affects inequality.


"Simple Allocation Rules and Optimal Portfolio Choice Over the Lifecycle," with Victor Duarte, Aaron Goodman, and Jonathan Parker [NBER working paper version]

We develop a machine-learning solution algorithm to solve for optimal portfolio choice in a detailed and quantitatively-accurate lifecycle model that includes many features of reality modeled only separately in previous work. We use the quantitative model to evaluate the consumption-equivalent welfare losses from using simple rules for portfolio allocation across stocks, bonds, and liquid accounts instead of the optimal portfolio choices. We find that the consumption-equivalent losses from using an age-dependent rule as embedded in current target-date/lifecycle funds (TDFs) are substantial, around 2 to 3 percent of consumption, despite the fact that TDF rules mimic average optimal behavior by age closely until shortly before retirement. Our model recommends higher average equity shares in the second half of life than the portfolio of the typical TDF, so that the typical TDF portfolio does not improve on investing an age-independent 2/3 share in equity. Finally, optimal equity shares have substantial heterogeneity, particularly by wealth level, state of the business cycle, and dividend-price ratio, implying substantial gains to further customization of advice or TDFs in these dimensions.

Media: Wall Street Journal



"How Much do Small Businesses Rely on Personal Credit?", with Jialan Wang

We estimate that U.S. entrepreneurs were able to substitute about 51% of the supply contraction in small business credit caused by large banks after the 2008 financial crisis by increasing their use of personal credit.

Julia Fonseca

Assistant Professor of Finance

University of Illinois at Urbana-Champaign