Stat.ai

The main window works like a chat, but the answers lean toward syntax rather than prose. Paste a command block with an error and you get the suspected line, a corrected version, and a note on why the original failed. It handles the everyday grind: merging files, renaming variables, recoding missing values, and building loops over a varlist.

The Stata code generator side of the product is really a translator. Feed it a dplyr pipeline or a pandas block and it returns the Stata equivalent, usually with the matching commands for loading, reshaping, and labeling. The reverse direction works too, which helps when a co-author works in R and you work in Stata.

Describe a design in words and the tool proposes an estimator. A treated group with pre and post periods points to difference-in-differences. A cutoff on a running variable points to regression discontinuity. Each suggestion comes with the assumptions you'd need to defend, which is the part most econometrics AI tools skip.

Most of the time in a Stata project goes into data management, not the regression. The assistant writes reshape, merge, collapse, and egen blocks from a description of the shape you want, and it flags mismatches in key variables before you run the merge.

It generates graph code for common publication figures: coefficient plots, event-study charts, and twoway overlays. It also writes the export lines for esttab and outreg2, which saves a round of trial and error when a table has to match a journal's format.

The free plan includes a monthly credit allowance, which is enough to test both tools before paying. Paid plans raise the allowance or remove the cap, and the annual option is discounted. Credits are the only limit that matters in practice, so heavy users should watch the count during a big debugging session.