Research Lab

We investigate the impact of uneven transparency regulation across countries and industries on the location of economic activity. Using two distinct sources of regulatory variation—the varying extent of financial-reporting requirements and the staggered introduction of electronic business registers in Europe—, we consistently document that direct exposure to transparency regulation is negatively associated with the focal industry’s economic activity in terms of inputs (e.g., employment) and outputs (e.g., production).

The covid-19 crisis has led to a sharp deterioration in firm and bank balance sheets. The government has responded with a massive intervention in corporate credit markets. We study equilibrium dynamics of macroeconomic quantities and prices, and how they are affected by government intervention in the corporate debt markets. We find that the interventions should be highly effective at preventing a much deeper crisis by reducing corporate bankruptcies by about half, and short-circuiting the doom loop between corporate and financial sector fragility.

The composition of natural liquidity has been changing over time. An analysis of intraday volumes for the S&P500 constituent stocks illustrates that (i) volume surprises, i.e., deviations from their respective forecasts, are correlated across stocks, and (ii) this correlation increases during the last few hours of the trading session.

This article provides an applied introduction to Bartik instruments. The instruments attempt to reduce familiar endogeneity concerns in differential exposure designs (e.g., panel regressions with unit and time fixed effects). They isolate treatment variation due to the differential impact of common shocks on units with distinct pre-determined exposures. As a result, the instruments purge the treatment variation of possibly confounding factors varying across units over time.

We provide an applied introduction to Bayesian estimation methods for empirical accounting research. To showcase the methods, we compare and contrast the estimation of accruals models via a Bayesian approach with the literature’s standard approach. The standard approach takes a given model of normal accruals for granted and neglects any uncertainty about the model and its parameters. By contrast, our Bayesian approach allows incorporating parameter and model uncertainty into the estimation of normal accruals.

Are extreme price swings part of a longer-term trend in the transition towards a greener future?

The high-yield bond market has just experienced an extreme cycle of bust and boom in the debt of energy companies.

We study the performance of many traditional and novel, text-based variables for in-sample and out-of-sample forecasting of oil spot, futures, and energy company stock returns, and changes in oil volatility, production, and inventories. After controlling for small-sample biases, we find evidence of in-sample predictability. Our text measures, derived using energy news articles, hold their own against traditional variables.

We follow a representative panel of millions of consumers in the U.S. from 2007 to 2017 and document several facts on the long-term effects of the Great Recession. There were about six million foreclosures in the ten-year period after Lehman's collapse. Owners of multiple homes accounted for 25% of these foreclosures, while comprising only 13% of the market. Foreclosures displaced homeowners, with most of them moving at least once. Only a quarter of foreclosed households regained homeownership, taking an average four years to do so.