18 jusi aalto stata accounting research

Skill brycewang-stanford/Auto-Empirical-Research-Skills/skills/18-jusi-aalto-stata-accounting-research

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npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill 18-jusi-aalto-stata-accounting-research

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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.

SKILL.md

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Scope and Limitations

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?"):

Acknowledge the limitation: "This skill provides code patterns from published papers, not research design guidance."
Show how different papers approached similar problems (code examples)
Suggest consulting methodology references: Breuer & deHaan (2024) for fixed effects, Angrist & Pischke for causal inference, or the user's methodologist/advisor
Offer to show multiple implementations so the user can see variation in approaches

Workflow

Use references/REFERENCES.md as the primary index, then read targeted .do files.

Stage 1: Index Search

Search references/REFERENCES.md to identify relevant papers. The index contains structured metadata:

Primary Method: STATA commands used (reghdfe, psmatch2, stcox, etc.)
Identification Strategy: DiD, PSM, IV, RDD, Event Study, etc.
Robustness/Special Features: Winsorization levels, clustering specs, placebo tests, etc.

Example queries on REFERENCES.md:

"entropy balancing" → finds JAR_60_alv, JAR_60_bl, JAR_61_ds, JAR_62_5_llz, JAR_63_2_npstv
"stacked DiD" → finds JAR_61_ds, JAR_62_5_aov, JAR_62_5_gibbons
"Cox hazard" → finds JAR_59_ctv, JAR_62_2_xyz

Stage 2: Code Extraction

Read only the identified .do files to extract actual syntax. This reduces context usage and improves accuracy.

Stage 3: Adaptation and Citation

Adapt patterns to the user's variable names and research context
Cite source: "Based on [Authors] ([Year]), JAR Volume"

Fallback: Direct Grep Patterns

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`

Corpus Overview

126 STATA .do files from JAR Volumes 55-63 (2017-2025). See references/REFERENCES.md for complete catalog with paper titles and authors.

File Naming Convention

V55-61: JAR_{volume}_{shortcode}.do
V62-63: JAR_{volume}_{issue}_{shortcode}_{authors}.do

Volume Coverage

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

Standard Patterns

Clustering and Fixed Effects

* 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)

Output Conventions

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

Winsorization

winsor2 varlist, cuts(1 99) replace