diff: Simplifying the estimation of difference-in-differences treatment effects
Juan M. Villa
Global Development Institute
University of Manchester
Manchester, UK
[email protected]
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Abstract. In this article, I present the features of the user-written command
diff, which estimates difference-in-differences (DID) treatment
effects. diff simplifies the DID analysis by allowing the conventional
DID setting to be combined with other nonexperimental evaluation methods. The
command is equipped with an attractive set of options: the single DID with
covariates, the kernel propensity-score matching DID, and the quantile DID.
Specific options are included to obtain DID estimation on a repeated
cross-section setting and to test the general balancing properties of the
model. I illustrate the features of diff using a sample of the dataset
from the pioneering implementation of DID by Card and Krueger (1994,
American Economic Review 84: 772–793).
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Juan M. Villa
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diff, difference-in-differences, causal inference, kernel propensity score, quantile treatment effects, nonexperimental methods, DID, QDID
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