econometrics

Plugin econometrics from marketplace great-econometrics in zhouziyue233/great-econometrics. Commands read from the repo's manifest — 1 month ago.

Skills (17)

• beamer-ppt

  Create Beamer-style academic PPTX presentations using python-pptx. Produces publication-quality .pptx files with navy-blue Metropolis theme (16:9, frame title bars, progress bar) for conference talks, job market presentations, and seminar slides. Called by /present command.

• data-pipeline

  End-to-end data pipeline for empirical research: fetch economic data from APIs (FRED, World Bank, IMF, BLS, OECD, Yahoo Finance), clean and transform raw data, construct strategy-specific variables, and validate panel structure. Use when asked to fetch data, download data, clean data, merge datasets

• did-analysis

  Econometrics skill for Difference-in-Differences (DID) analysis. Activates when the user asks about: "difference in differences", "DID", "DiD", "diff-in-diff", "parallel trends", "treatment group", "control group", "pre-treatment", "post-treatment", "policy evaluation", "natural experiment", "stagge

• figure

  Called by /plot to generate and upgrade econometric figures to top-journal standards.

• iv-estimation

  Econometrics skill for instrumental variables and treatment effect estimation. Activates when the user asks about: "instrumental variables", "IV estimation", "2SLS", "two-stage least squares", "endogeneity", "weak instruments", "first stage", "Sargan test", "overidentification", "propensity score ma

• literature-review

  Search, summarize, and synthesize economics literature. find research gaps, position your contribution.

• ml-causal

  Econometrics skill for machine learning methods in causal inference. Activates when the user asks about: "causal forest", "generalized random forest", "GRF", "double machine learning", "DML", "debiased machine learning", "LASSO for variable selection", "post-LASSO", "heterogeneous treatment effects"

• ols-regression

  Econometrics skill for OLS regression and linear models. Activates when the user asks about: "run OLS", "linear regression", "ordinary least squares", "interpret regression results", "heteroskedasticity", "multicollinearity", "regression assumptions", "robust standard errors", "GLS", "WLS", "fit a r

• panel-data

  Econometrics skill for panel data models. Activates when the user asks about: "panel data", "fixed effects", "random effects", "Hausman test", "within estimator", "between estimator", "two-way fixed effects", "clustered standard errors panel", "FE model", "RE model", "pooled OLS", "unobserved hetero

• paper-writing

  Draft economics papers with proper structure and academic style

• rdd-analysis

  Econometrics skill for Regression Discontinuity Design (RDD). Activates when the user asks about: "regression discontinuity", "RDD", "RD design", "sharp RDD", "fuzzy RDD", "running variable", "forcing variable", "cutoff", "bandwidth selection", "local linear regression", "McCrary test", "density tes

• results-analysis

  Comprehensive results analysis for empirical research: generate publication-quality descriptive statistics and balance tables, interpret regression coefficients with economic magnitude and effect sizes, assess identification assumption diagnostics, and produce structured results memos. Use when aske

• scrapling

  Scrape web pages using Scrapling with anti-bot bypass (like Cloudflare Turnstile), stealth headless browsing, spiders framework, adaptive scraping, and JavaScript rendering. Use when asked to scrape, crawl, or extract data from websites; web_fetch fails; the site has anti-bot protections; write Pyth

• stata

  Comprehensive Stata reference for writing correct .do files. Covers syntax, options, gotchas, and idiomatic patterns. Use this skill whenever the user asks you to write, debug, or explain Stata code. Generates ready-to-run .do files for the user to execute manually.

• synthetic-control

  Econometrics skill for Synthetic Control Method (SCM). Activates when the user asks about "synthetic control", "SCM", "placebo test", "synthetic DID", "合成控制", "安慰剂检验", "合成反事实", "合成DID".

• table

  Called by /plot to upgrade regression and summary tables to top-journal standards.

• time-series

  Econometrics skill for time series analysis. Activates when the user asks about: "time series", "stationarity", "unit root test", "ADF test", "KPSS test", "ARIMA", "ARMA", "autocorrelation", "ACF", "PACF", "VAR model", "VECM", "Granger causality", "cointegration", "impulse response function", "forec

Slash commands (9)

• /econometrics:analyze

  Identification Strategy Analysis. Synthesizes research question and literature review to diagnose endogeneity threats, evaluate feasible identification strategies, select the optimal one, and produce an Identification Strategy Memo.

• /econometrics:code

  Phase 6 Code Generation & Execution. Reads identification-memo.md, data-report.md, and model-spec.md, asks user to select software (Python / R / Stata), dispatches to the appropriate estimation skill, generates a reproducible analysis script with main regression, diagnostics, and output export, then

• /econometrics:data

  Phase 4 Data Preparation Pipeline. Data fetch, data clean and exploratory analysis. Produce a data report in the end.

• /econometrics:model

  Phase 5 Econometric Model Construction. Reads identification-memo.md and data-report.md, writes formal model specification with LaTeX equations, discusses identification assumptions and SE strategy, calls the appropriate estimation skill, and produces model-spec.md.

• /econometrics:plot

  Publication Polish. Runs after results-analysis (Phase 7). Audits all tables and figures produced in Phases 4–7, upgrades them to top-journal standards by calling the table and figure skills.

• /econometrics:present

  Phase 10 (optional) Beamer-Style PPTX Generation. Reads all upstream outputs and paper/sections/, maps research content to a presentation-type-specific slide outline, calls beamer-ppt skill to generate a Beamer-style .pptx file (navy-blue Metropolis theme, publication-quality), and produces slides/

• /econometrics:question

  Help user transform their idea into a clear research question through interactive dialogue.

• /econometrics:robustness

  Phase 8 Robustness, Heterogeneity & Mechanism Tests. Reads model-spec.md, diagnostic_report.md, and results-memo.md to build a personalised checklist, then runs method-specific robustness checks, heterogeneity analysis, and mechanism tests; generates code; and produces robustness-report.md.

• /econometrics:write

  Phase 9 Full Paper Writing. Reads all upstream outputs (model-spec.md, results-memo.md, robustness-report.md, literature-review-report.md) and drafts any section or the complete paper to Top-5 economics journal standards following a narrative-driven structure; assembles LaTeX, compiles to PDF, and e

Subagents (1)

• checker

  Phase 8 parallel checker. Launch three independent subagents simultaneously

Hooks (1)

• SessionStart

  printf '\n📊 Econometrics 可用技能或命令\n\n Phase 1 /question 确定研究问题\n Phase 2 literature-review skill 文献综述\n Phase 3 /analyze 识别策略分析\n Phase 4 /data 数据准备\n Phase 5 /model 计量模型构建\n P

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