1. (StataNow) Local average treatment effects (LATE). New command lateffects estimates a local average treatment effect (LATE), also known as a complier average treatment effect. When individuals do not comply with their assigned treatment, it may not be possible to estimate a treatment effect for the entire population. But with lateffects, we can exploit information regarding the assigned treatment by using an instrumental variable. This allows us to estimate the treatment effect for those who comply with the assigned treatment, the LATE.

lateffects estimates LATE for a continuous, binary, count, or fractional outcome with a binary treatment. Three estimators are available:

 

• Normalized kappa weighted
• Normalized covariate-balancing propensity scores
• Inverse-probability-weighted regression adjustment

Postestimation command latebalance provides two balancing diagnostics and an overidentification test.

 

• latebalance summarize compares the means and variances of the raw data and the weighted data over the treatment-assignment groups.
• latebalance density plots the density of the raw data and the weighted data over the treatment-assignment groups.
• latebalance overid performs a test for covariate balance.

Postestimation command lateoverlap provides a diagnostic plot for the overlap assumption.

 

2. (StataNow) More VCE options for linear models. Stata’s most commonly used linear regression commands now come with a richer set of VCE specifications.

If you have autocorrelated errors in your time-series or panel-data model, you can use regress or areg, which now allow for heteroskedasticity- and autocorrelation-consistent (HAC) standard errors with option vce(hac), or use xtreg, fe, which now allows users to specify Driscoll–Kraay standard errors with new option vce(dkraay).

 

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Commands regress, areg, xtreg, fe, didregress, and xtdidregress each now allow for both HC2 and HC3 standard errors with clustering. The inference adjustment of Hansen (2025) is available with HC3 standard errors using new suboption hansen.

 

You can also account for multiple nonnested clusters when fitting an instrumental-variables regression with ivregress. And you can allow for arbitrary correlation within panels by specifying new option corr(unstructured) in xtgls.

 

3. (StataNow) The Do-file Editor can now indicate that changes have been made to a line by using colored markers in the change history ribbon located in the margin. Two different markers indicate changes to a line: modified and reverted-to-original. A modified marker indicates that a change was made to a line. A reverted-to-original marker indicates that a change was made to a line, saved, and then reverted to its original state. To update the visibility of the change history ribbon, right-click in the Do-file Editor, select Preferences…, and check or uncheck Change history in the General tab for Windows and Unix and the Display tab for Mac. Note that changes to the visibility of the change history ribbon will only take effect on new editors.
4. (StataNow) In the Data Editor grid, variable names can now be truncated using several different methods, including at the end (the default), in the middle, or by selecting 1, 2, 3, or 4 characters before the end. The behavior can be changed in the Data Editor’s preference dialog.
5. (StataNow) xtgls with option panels(iid) or panels(heteroskedastic) is now faster.