Hi All. Perhaps something useful from me. I'd like to announce that drlate, a Stata module for doubly robust estimation of the local average treatment effect (LATE) and the local average treatment effect on the treated (LATT), is now available in SSC.
Doubly Robust Estimation of Local Average Treatment Effects Using Inverse Probability Weighted Regression Adjustment
We revisit the problem of estimating the local average treatment effect (LATE) and the local average treatment effect on the treated (LATT) when control variables are available, either to render the i...
arxiv.org
![A screenshot of an R console showing code and output for an extended two-way fixed effects analysis. The code loads the `fetwfe` and `did` packages, loads the `mpdta` dataset, and transforms it into `pdata` with `attgtToFetwfeDf`, specifying outcome `lemp`, time variable `year`, unit identifier `countyreal`, treatment onset `first.treat`, and covariate `lpop`. Then it runs `etwfe(pdata, time_var="time_var", unit_var="unit_var", treatment="treatment", response="response", covs="lpop")`.
Below is the “Extended Two-Way Fixed Effects Results”:
* **Overall Average Treatment Effect (ATT):**
– Estimate: –0.0452
– Std. Error: 0.0145
– 95 % CI: \[–0.0736, –0.0167]
* **Cohort Average Treatment Effects (CATT):**
| Cohort | Estimated TE | SE | 95 % CI low | 95 % CI high |
| ------ | ------------ | ---------- | ----------- | ------------ |
| 2004 | –0.08762696 | 0.03555885 | –0.15732102 | –0.01793290 |
| 2006 | –0.02127833 | 0.02128938 | –0.06300475 | 0.02044809 |
| 2007 | –0.04595453 | 0.01633327 | –0.07796715 | –0.01394190 |
* **Model Details:**
– Units (N): 500
– Time periods (T): 5
– Treated cohorts (R): 3
– Covariates (d): 1
– Features (p): 29](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:v5yhsvcygebhudec4rhb35wx/bafkreihi2xmgx3rse6inv2nh3pe74s7d5ir4ypwnlgchqcnpo7muv7cq3y)
