Type: preprint
Abstract: Treatment effects may be different for groups that are treated in different time periods or may change over time after a group has been treated. Think about, for example, the effect of job training programs on earnings or the effectiveness of COVID vaccines. To capture this heterogeneity, Stata 18 introduces two commands that estimate treatment effects specific to each cohort and time period. For repeated cross-sectional data, we have hdidregress. For panel data, we have xthdidregress. Both commands let you aggregate treatment effects by cohort and exposure to treatment and visualize these effects graphically. Tests of pretreatment parallel trends are also available. This presentation will illustrate how both commands work and briefly discuss the theory underlying them.
Author: Eduardo Garcia Echeverri
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7112719119