Econometrics Journal· 2026Q1
What Do We Get from Two-Way Fixed Effects Regressions? Implications from Numerical Equivalence
- 1citations
- Q1SCImago
- 2026year
Short summary
Two-way fixed effects (TWFE) regression coefficients can be interpreted as a weighted average of first-difference (FD) coefficients across all time horizons, with causal interpretation requiring common trends at all horizons simultaneously.
AI-generated from the title and abstract; the full text is not read.
Key points
- TWFE coefficients are equivalent to a weighted average of FD coefficients across all time horizons.
- Causal interpretation of TWFE requires common trends assumptions to hold simultaneously across all horizons.
- Each FD coefficient's causal interpretation relies only on the common trends assumption at its specific horizon.
- Diagnostic procedures are proposed to empirically assess common trends assumptions horizon by horizon.
AI-generated from the title and abstract; the full text is not read.
Abstract
Abstract This paper develops numerical and causal interpretations of two-way fixed effects (TWFE) regressions in settings with nonbinary, nonstaggered treatments and time-varying covariates. Using the equivalence between TWFE and pooled first-difference (FD) regressions, I express the TWFE coefficient as a weighted average of FD coefficients across all horizons, clarifying how short- and long-run changes contribute to the estimate. Causal interpretation of the TWFE coefficient relies on common trends assumptions at all horizons simultaneously, whereas each FD coefficient relies on the assumption only at its own horizon. This structure opens the identifying assumptions to empirical scrutiny: I propose diagnostic procedures that assess common trends horizon by horizon, and illustrate them by reexamining TWFE estimates of minimum-wage effects on employment.
The authors' abstract, as published at the source. Econometrics Journal, 2026 · DOI ↗
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Field: Economics and Econometrics
Economics and EconometricsEconomics, Econometrics and Finance