AgentSkillsCN

stata-accounting-research

面向实证型会计档案研究的 STATA 代码范例库。本库收录了来自 126 篇经同行评议的 JAR(Journal of Accounting Research)复现论文的成熟语法(2017–2025 年)。当用户提出诸如“如何实现 [方法]?”或“请提供 [技术] 的代码示例”之类的操作性问题时,可选用此技能——涵盖熵平衡、倾向得分匹配(PSM)、双重差分法(DiD)、断点回归(RDD)、工具变量法(IV)、事件研究(CAR/BHAR)、生存分析、Fama-MacBeth 回归、自助法(Bootstrap)、分位数回归、reghdfe/xtreg/areg 回归、聚类标准误、固定效应模型、esttab/outreg2 表格格式化、Winsorization 处理、前导/滞后变量等常用方法。用户可自行指定变量(如处理变量、结果变量、控制变量),系统将据此提供适配的代码语法。注意:本技能仅提供已发表论文中的代码范例,不提供研究设计方面的建议。

SKILL.md
--- frontmatter
name: stata-accounting-research
description: |
  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.

Scope and Limitations

This skill is a code pattern library, not a methodological advisor.

Can DoCannot Do
Show how published papers implemented methodsExplain when to use one method over another
Provide tested STATA syntaxAdvise on identification strategy
Indicate which robustness tests accompany analysesDiscuss research design trade-offs
Cite source papers for code patternsRecommend 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?"):

  1. Acknowledge the limitation: "This skill provides code patterns from published papers, not research design guidance."
  2. Show how different papers approached similar problems (code examples)
  3. Suggest consulting methodology references: Breuer & deHaan (2024) for fixed effects, Angrist & Pischke for causal inference, or the user's methodologist/advisor
  4. 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

  1. Adapt patterns to the user's variable names and research context
  2. 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:

TaskGrep Pattern
Panel regressionsreghdfe|xtreg|areg
Fixed effectsabsorb\(|i\.year|i\.firm
Clusteringcluster\(|vce\(cluster
Matching/PSMpsmatch2|teffects|cem|ebalance|pscore
IV regressionxtivreg|ivregress|ivreg2
DiDpost.*treat|treat.*post|parallel.*trend
RDDrdrobust|rddensity
Event studiesCAR|BHAR|abnormal.*return
Survivalstcox|streg|stset
Fama-MacBethfama.?macbeth|newey.*west
Bootstrapbootstrap|bsample
Quantile regressionqreg|sqreg|bsqreg
Table outputesttab|outreg2|eststo
Winsorizationwinsor|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

VolumeYearPapers
5520179
56201812
5720199
58202013
5920214
60202222
61202322
62202425
63202510

Standard Patterns

Clustering and Fixed Effects

stata
* 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

stata
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

stata
winsor2 varlist, cuts(1 99) replace