arbiter
JournalsPricingAccount

A Complete Framework for Model-Free Difference-in-Differences Estimation

Daniel J. Henderson & Stefan Sperlich

Foundations and Trends in Econometrics2023https://doi.org/10.1561/0800000046article
AJG 1ABDC C
Weight
0.40

What the paper says

We propose a complete framework for data-driven difference-in-differences analysis with covariates, in particular nonparametric estimation and testing. We start with simultaneously choosing confounders and a scale of the outcome along identification conditions. We estimate first heterogeneous treatment effects stratified along the covariates, then the average effect(s) for the treated. We provide the asymptotic and finite sample behavior of our estimators and tests, bootstrap procedures for their standard errors and p-values, and an automatic bandwidth choice. The pertinence of our methods is shown with a study of the impact of the Deferred Action for Childhood Arrivals program on educational outcomes for non-citizen immigrants in the US.

2 citations

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1561/0800000046

Or copy a formatted citation

@article{daniel2023,
  title        = {{A Complete Framework for Model-Free Difference-in-Differences Estimation}},
  author       = {Daniel J. Henderson & Stefan Sperlich},
  journal      = {Foundations and Trends in Econometrics},
  year         = {2023},
  doi          = {https://doi.org/https://doi.org/10.1561/0800000046},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

A Complete Framework for Model-Free Difference-in-Differences Estimation

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.40

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.13 × 0.4 = 0.05
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.