In this paper we detail the entire Regression Discontinuity Design (RDD) history, including its origins in the 1960s, and its two main waves of formalization in the 1970s and 2000s, both of which are rarely acknowledged in the literature. Also, we dissect the empirical work into fuzzy and sharp designs and provide some intuition as to why some rule‐based criteria produce imperfect compliance. Finally, we break the literature down by economic field, highlighting the main outcomes, treatments, and running variables. Overall, we see some topics in economics gaining importance through time, like the cases of health, finance, crime, environment, and political economy. In particular, we highlight applications in finance as the most novel. Nonetheless, we recognize that the field of education stands out as the uncontested RDD champion through time, with the greatest number of empirical applications.

In this paper we detail the entire Regression Discontinuity Design (RDD) history, including its origins in the 1960's, and its two main waves of formalization in the 1970's and 2000's, both of which are rarely acknowledged in the literature. Also, we dissect the empirical work into fuzzy and sharp designs and provide some intuition as to why some rule-based criteria produce imperfect compliance. Finally, we break the literature down by economic field, highlighting the main outcomes, treatments, and running variables employed. Overall, we see some topics in economics gaining importance through time, like the cases of: health, finance, crime, environment, and political economy. In particular, we highlight applications in finance as the most novel. Nonetheless, we recognize that the field of education stands out as the uncontested RDD champion through time, with the greatest number of empirical applications.

This paper studies the impact of the Covid-19 pandemic on corporate credit in Colombia. We first exploit the geographic and temporal variation in the disease spread to estimate the effect of local exposure to the virus on credit. Our estimates indicate that neither local exposure to the virus, nor the sector-specific mobility restrictions had an impact on credit. We then assess the role of bank supply shocks. We create a measure of bank exposure, reflecting the geographic heterogeneity in pandemic vulnerability and deposits, and estimate its effect on credit. Results indicate that bank-supply shocks account for a credit contraction of approximately 5.2%. To further disentangle the role of bank supply shock, we control for the interaction between firm and time fixed-effects and restrict the sample to municipalities that were relatively spared from the pandemic, finding similar results. Most of the bank supply effects are driven by firms that are small, young, and have relatively low liquidity.

We investigate the impact of fiscal expansions on firm investment by exploiting firms that have multiple banking relationships. Further, we conduct a localized RDD approach and compare the lending behavior of banks that barely met and missed the criteria of being a primary dealer, as well as barely winners and losers at government auctions. Our results indicate that a 1 percentage point increase in banks’ bonds-to-assets ratio decreases loans by up to 0.4%, which leads to significant declines in firm investment, profits and wages. Our findings are grounded in a quantitative model with financial and real sectors with which we undertake a welfare analysis and compute the cost of government borrowing on the overall economy.

No abstract