Webinar Conditional Average Treatment Effects Estimation Using Stata
Di Liu – StataCorp LLC.
Date
Thursday, 04. September 2025
16:00 (UTC+01:00)
Free
Language of the webinar: English
Abstract
Treatment effects estimate the causal effects of a treatment on an outcome. These effects may be heterogeneous. Average treatment effects conditional on a set of variables (CATEs) help us understand such heterogeneous treatment effects and, by construction, are useful for evaluating how different treatment-assignment policies impact various groups within a population.
In this talk, Di Liu will demonstrate how to use Stata 19’s new cate command to answer key questions such as:
- Are the treatment effects heterogeneous?
- How do the treatment effects vary with some variables?
- Do the treatment effects vary across prespecified groups?
- Are there unknown groups in the data for which treatment effects differ?
- Which is best among possible treatment-assignment rules?
A must-attend for anyone working with causal inference, policy evaluation, or Stata-based data analysis.
Register now to secure your spot!