講者:Prof. Shoya Ishimaru (Department of Economics, Hitotsubashi University)
演講主題: Estimating Treatment Effects in Panel Data Without Parallel Trends
講題摘要:
This paper proposes a novel approach for estimating treatment effects in panel data settings, addressing key limitations of the standard difference-in-differences (DID) approach. The standard approach relies on the parallel trends assumption, implicitly requiring unobservable factors correlated with treatment assignment to be unidimensional, time-invariant, and affect untreated potential outcomes in an additively separable manner. This paper introduces a more flexible framework that allows for multidimensional unobservables and non-additive separability, and offers sufficient conditions for identifying the average treatment effect on treated. An empirical application to job displacement reveals smaller long-run earnings losses compared to the standard DID approach, reflecting the framework’s ability to account for heterogeneity in earnings growths between treated and control groups. For example, nine years after displacement, the alternative estimate suggests a reduction in earnings less than half of that estimated by the DID approach. While the method requires substantial pre-treatment and post-treatment data and specific conditions on serial correlation, it expands the econometric toolkit by enabling more robust causal inference in the presence of complex unobserved heterogeneity.