Multiple Structural Breaks in Interactive Effects Panel Data Models

Abstract

This paper develops new econometric methods for multiple structural break detection in panel data models with interactive fixed effects. The new methods include tests for the presence of structural breaks, estimators for the number of breaks and their location, and a method for constructing asymptotically valid break date confidence intervals. The new methodology is applied to a large panel of US banks for a period characterized by massive quantitative easing programs aimed at lessening the impact of the global financial crisis and the COVID-19 pandemic. The question we ask is as follows: Have these programs been successful in spurring bank lending in the US economy? The short answer turns out to be: “No”.