Direct and Indirect Treatment Effects with Time-Varying Covariates
(2026) In Journal of Applied Econometrics- Abstract
- We propose a simple approach to treatment effect estimation in panel data that is valid when the number of time periods is small and the parallel trends condition is violated due to the presence of interactive fixed effects. The procedure allows the covariates to be affected by treatment and enables separation of the part of the estimated treatment effect that is due to the covariates from the part that is not. The asymptotic properties of the new approach are established, and their accuracy in small samples is investigated using Monte Carlo simulations. The procedure is illustrated using as an example the effect of increased trade competition on firm markups in China. We estimate that about half of the impact of China's entrance into the... (More)
- We propose a simple approach to treatment effect estimation in panel data that is valid when the number of time periods is small and the parallel trends condition is violated due to the presence of interactive fixed effects. The procedure allows the covariates to be affected by treatment and enables separation of the part of the estimated treatment effect that is due to the covariates from the part that is not. The asymptotic properties of the new approach are established, and their accuracy in small samples is investigated using Monte Carlo simulations. The procedure is illustrated using as an example the effect of increased trade competition on firm markups in China. We estimate that about half of the impact of China's entrance into the WTO on markup dispersion came from the changes in industry-level productivity. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/16d3008d-a719-4dfd-ba79-1c4ed77c7eb9
- author
- Brown, Nicholas ; Butts, Kyle and Westerlund, Joakim LU
- organization
- publishing date
- 2026
- type
- Contribution to journal
- publication status
- epub
- subject
- in
- Journal of Applied Econometrics
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- scopus:105036409886
- ISSN
- 0883-7252
- DOI
- 10.1002/jae.70055
- language
- English
- LU publication?
- yes
- id
- 16d3008d-a719-4dfd-ba79-1c4ed77c7eb9
- date added to LUP
- 2026-02-22 16:03:39
- date last changed
- 2026-06-23 14:48:18
@article{16d3008d-a719-4dfd-ba79-1c4ed77c7eb9,
abstract = {{We propose a simple approach to treatment effect estimation in panel data that is valid when the number of time periods is small and the parallel trends condition is violated due to the presence of interactive fixed effects. The procedure allows the covariates to be affected by treatment and enables separation of the part of the estimated treatment effect that is due to the covariates from the part that is not. The asymptotic properties of the new approach are established, and their accuracy in small samples is investigated using Monte Carlo simulations. The procedure is illustrated using as an example the effect of increased trade competition on firm markups in China. We estimate that about half of the impact of China's entrance into the WTO on markup dispersion came from the changes in industry-level productivity.}},
author = {{Brown, Nicholas and Butts, Kyle and Westerlund, Joakim}},
issn = {{0883-7252}},
language = {{eng}},
publisher = {{John Wiley & Sons Inc.}},
series = {{Journal of Applied Econometrics}},
title = {{Direct and Indirect Treatment Effects with Time-Varying Covariates}},
url = {{http://dx.doi.org/10.1002/jae.70055}},
doi = {{10.1002/jae.70055}},
year = {{2026}},
}