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| Duration: | 1 hour |
|---|---|
| Where: | Join us from anywhere! |
| Cost: | Free—but registrations are limited |
The last years have seen an explosion in the difference-in-differences (DID) literature. We have moved from assuming treatment effects did not change over group or time to assuming treatment effects change over group and time. We have embraced heterogeneity.
Stata 18 introduced two commands (each with four estimators) to fit heterogeneous (DID) models: hdidregress for repeated cross-sectional data and xthdidregress for panel/longitudinal data. In this webinar, we briefly introduce the theory behind both estimators and then show how to fit heterogeneous DID models using the new commands. We also demonstrate postestimation tools to aggregate and visualize heterogeneous treatment effects and perform diagnostic tests.
The webinar is free, but you must register to attend. Registrations are limited so register soon.
We will send you an email prior to the start with instructions on how to access the webinar.
Di Liu is a Principal Econometrician in the econometric development team at StataCorp LLC. Di is fascinated by writing statistical software for researchers and doing research in both theoretical and applied econometrics. He is the primary developer of some Stata features, including heterogeneous DID, instrumental variable quantile regression, treatment effects estimation using lasso, lasso for prediction, lasso for inference, spatial autoregressive models, heckpoisson, and betareg. He also published research articles in Canadian Journal of Economics, Econometrics Reviews, Empirical Economics, Econometrics and Statistics, and the Stata journal. Di has a PhD degree in economics from Concordia University in Montreal, Canada; an engineer's degree in software engineering and statistics from Polytech'Lille in Lille, France; and master's and bachelor's degrees in computer science from Hohai University in Nanjing, China.
