Full Citation
Title: A general proposal for model-free difference-in-differences
Citation Type: Miscellaneous
Publication Year: 2021
ISBN:
ISSN:
DOI:
NSFID:
PMCID:
PMID:
Abstract: We propose a general framework for model-free difference-in-differences analysis with confounders. Following the natural steps in practice, we start by searching for the preferred data setup, namely thesimultaneous selection of confounders and potential data (outcome) transformations. We then offer a test for the credibility of identification assumptions. The treatment effects themselves are estimated in two steps: first, the heterogeneous effects stratified along the confounders, then second, the average treatment effect(s) for the population(s) of interest. We suggest bootstrap procedures to calculate the standard errors of these estimates, as well as for significance tests. We study the asymptotic statistics as well as the finite sample behavior (via simulations) of our tests and estimators. We address practical issues that arise such as bandwidth selection, incorporating sample weights and dealing with discrete data in both the outcome variable and set of confounders. These are addressed in a setting whereby we look at the impact of the Deferred Action for Childhood Arrivals (DACA) program on human capital responses of non-citizen immigrants. We find that past (linear parametric) estimates are similar regarding (albeit underestimating) the positive impact of DACA on school attendance (for individuals aged 14-18) and the positive impact on high school completion, but at the same time, fail to identify the negative impact of DACA on school attendance for college aged individuals.
Url: https://economics.ucr.edu/wp-content/uploads/2021/10/02-03-2022-Henderson.pdf
User Submitted?: No
Authors: Henderson, Daniel J.; Sperlich, Stefan
Publisher:
Data Collections: IPUMS USA
Topics: Methodology and Data Collection
Countries: