Oracle Efficient Estimation of Heterogeneous Dynamic Panel Data Models with Interactive Fixed Effects

A-Tier
Journal: Journal of Business & Economic Statistics
Year: 2024
Volume: 42
Issue: 4
Pages: 1169-1184

Authors (4)

Yiqiu Cao (not in RePEc) Sainan Jin (Tsinghua University) Xun Lu (not in RePEc) Liangjun Su (Tsinghua University)

Score contribution per author:

1.005 = (α=2.01 / 4 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

We propose a two-step procedure to estimate a heterogeneous dynamic panel data model with interactive fixed effects. We establish the asymptotic properties of the estimators and show that the final estimator is oracle efficient. We also propose a specification test for the null hypothesis of homogeneous slopes and study the asymptotic properties of the test statistic under both local and global alternatives. Simulations demonstrate the fine performance of the estimator and test statistic. The new estimation and inference methods are applied to study the heterogeneous effects of minimum wage on employment across different counties in the United States. Our dynamic model suggests that the changes of employment range from about–1% to 1% when the minimum wage increases by 1%.

Technical Details

RePEc Handle
repec:taf:jnlbes:v:42:y:2024:i:4:p:1169-1184
Journal Field
Econometrics
Author Count
4
Added to Database
2026-01-25