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asheshrambachan
HonestDiD:Robust Inference in Difference-in-Differences and Event Study Designs
Provides functions to conduct robust inference in difference-in-differences and event study designs by implementing the methods developed in Rambachan & Roth (2023) <doi:10.1093/restud/rdad018>, "A More Credible Approach to Parallel Trends" [Previously titled "An Honest Approach..."]. Inference is conducted under a weaker version of the parallel trends assumption. Uniformly valid confidence sets are constructed based upon conditional confidence sets, fixed-length confidence sets and hybridized confidence sets.
Maintained by Ashesh Rambachan. Last updated 1 months ago.
difference-in-differencesevent-studiesrobust-inference
197 stars 7.05 score 63 scripts
s3alfisc
summclust:Module to Compute Influence and Leverage Statistics for Regression Models with Clustered Errors
Module to compute cluster specific information for regression models with clustered errors, including leverage and influence statistics. Models of type 'lm' and 'fixest'(from the 'stats' and 'fixest' packages) are supported. 'summclust' implements similar features as the user-written 'summclust.ado' Stata module (MacKinnon, Nielsen & Webb, 2022; <arXiv:2205.03288v1>).
Maintained by Alexander Fischer. Last updated 2 years ago.
clustered-standard-errorsfixestlinear-regressionrobust-inference
6 stars 6.16 score 53 scripts 3 dependents