Find STATA code examples for empirical accounting research from published replication files. Adapt regression, matching, event study, and table export syntax to your variables, with citations to the papers behind each example.
STATA code pattern library for empirical archival accounting research. Provides tested syntax from 126 peer-reviewed JAR (Journal of Accounting Research) replication files (2017-2025). Use when the user asks procedural questions like "How do I implement [method]?" or "Show me code for [technique]" — including: entropy balancing, propensity score matching (PSM), difference-in-differences (DiD), regression discontinuity (RDD), instrumental variables (IV), event studies (CAR/BHAR), survival analysis, Fama-MacBeth regressions, bootstrap, quantile regression, reghdfe/xtreg/areg, clustering standard errors, fixed effects, esttab/outreg2 table formatting, winsorization, leads/lags. Users can specify their variables (e.g., treatment, outcomes, controls) and receive adapted syntax. NOTE: This skill provides code patterns from published papers, not research design advice.
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
This skill is a code pattern library, not a methodological advisor.
| Can Do | Cannot Do |
|---|---|
| Show how published papers implemented methods | Explain when to use one method over another |
| Provide tested STATA syntax | Advise on identification strategy |
| Indicate which robustness tests accompany analyses | Discuss research design trade-offs |
| Cite source papers for code patterns | Recommend optimal research design |
When users ask methodology questions (e.g., "Should I use entropy balancing or PSM?", "How do I address endogeneity?", "Is my identification strategy valid?"):
Use references/REFERENCES.md as the primary index, then read targeted .do files.
Search references/REFERENCES.md to identify relevant papers. The index contains structured metadata:
Example queries on REFERENCES.md:
Read only the identified .do files to extract actual syntax. This reduces context usage and improves accuracy.
For very specific syntax queries (e.g., "how does absorb() handle singletons?"), grep .do files directly:
| Task | Grep Pattern |
|---|---|
| Panel regressions | reghdfe|xtreg|areg |
| Fixed effects | absorb\(|i\.year|i\.firm |
| Clustering | cluster\(|vce\(cluster |
| Matching/PSM | psmatch2|teffects|cem|ebalance|pscore |
| IV regression | xtivreg|ivregress|ivreg2 |
| DiD | post.*treat|treat.*post|parallel.*trend |
| RDD | rdrobust|rddensity |
| Event studies | CAR|BHAR|abnormal.*return |
| Survival | stcox|streg|stset |
| Fama-MacBeth | fama.?macbeth|newey.*west |
| Bootstrap | bootstrap|bsample |
| Quantile regression | qreg|sqreg|bsqreg |
| Table output | esttab|outreg2|eststo |
| Winsorization | winsor|winsor2 |
126 STATA .do files from JAR Volumes 55-63 (2017-2025). See references/REFERENCES.md for complete catalog with paper titles and authors.
JAR_{volume}_{shortcode}.doJAR_{volume}_{issue}_{shortcode}_{authors}.do| Volume | Year | Papers |
|---|---|---|
| 55 | 2017 | 9 |
| 56 | 2018 | 12 |
| 57 | 2019 | 9 |
| 58 | 2020 | 13 |
| 59 | 2021 | 4 |
| 60 | 2022 | 22 |
| 61 | 2023 | 22 |
| 62 | 2024 | 25 |
| 63 | 2025 | 10 |
* Firm and year FE with firm-clustered SEs (most common)
reghdfe depvar indepvar controls, absorb(firm year) cluster(firm)
* Industry-year FE
reghdfe depvar indepvar controls, absorb(ind_year) cluster(firm)
eststo clear
eststo: reghdfe depvar indepvar controls, absorb(firm year) cluster(firm)
esttab using "table.tex", replace star(* 0.10 ** 0.05 *** 0.01) se
winsor2 varlist, cuts(1 99) replace
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