Uncovering Financial Constraints

Abstract

We classify firms’ financial constraints using a random forest model trained on the Hoberg and Maksimovic (2015) text-based constraint measures. Our model uses only financial variables to predict constraints, allowing us to significantly expand the cross-section and time-series of classified firms compared to the text-based measures. We conduct tests to validate the informativeness of our measures. Using the measures, we show the equity issuance, investment, and institutional ownership of equity-focused, constrained firms is especially sensitive to investor sentiment. In the cross-section, institutional ownership is negatively associated with equity-related constraints. Among 1990s discount brokerage investors and Robinhood investors, the stock of equity-focused constrained firms is preferred relative to unconstrained firms.

Keywords: financial constraints, machine learning, random forests, institutional investors, retail investors

JEL Classification: G00, G30, G35, G1, G3