brycewang-stanford

by Bryce Wang

Agent skill stack for the American Economic Review, AER: Insights, and AEJ family. Covers topic selection, literature positioning with citation verification, modern causal identification (DiD / IV / RDD / SCM / Bartik), experimental pre-registration with power/MDE sizing, referee-anticipating robustness, body-section drafting with magnitude discipline, Keith-Head-style introductions, AER booktabs tables, full-manuscript consistency audits, adversarial referee simulation, AEA Data and Code Availability deposits, submission preflight, and R&R rebuttal letters. Includes Stata / R / Python templates, an optional StatsPAI agent-native implementation engine, and classic-AER-paper exemplars.

by Bryce Wang

Explicit 8-step empirical-analysis pipeline in the traditional Python econometrics stack (pandas + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml). Data cleaning → variable construction → Table 1 → diagnostics → estimation (OLS / IV / DID / RDD / PSM / SCM / DML / Causal Forest) → robustness battery → mechanism / heterogeneity / mediation → publication-ready tables & figures. Also covers epidemiology (TMLE / IPTW / Mendelian randomization / survival) and ML-causal (DML / meta-learners / Dragonnet) modes. Every line is explicit and swappable — built for teaching, referee-level audit, and strict replication.

by Bryce Wang

Explicit 8-step empirical-analysis pipeline in the modern tidyverse + econometrics R stack (dplyr + haven + fixest + did + synthdid + rdrobust + MatchIt + WeightIt + grf + DoubleML + mediation + marginaleffects + modelsummary). All eight steps fit in a single .qmd; `quarto render` produces a unified PDF / HTML / Word reproducibility report. Also covers epidemiology (tmle / ltmle / MendelianRandomization / survival) and ML-causal (DoubleML / grf / policytree) modes. The Quarto-rendered reproducibility report is unique to R.

by Bryce Wang

Explicit 8-step empirical-analysis pipeline in the traditional Stata ecosystem (reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + synth + psmatch2 + teffects + esttab + coefplot). From use / import all the way to .tex / .rtf tables and .pdf figures, with the full modern DID toolkit (bacondecomp + honestdid + rwolf + ritest). Also covers epidemiology and ML-causal (ddml / crforest) modes. The first choice when a referee or co-author insists on a Stata replication pack.

by Bryce Wang

Study p-hacking in econometric designs: map researcher degrees of freedom, audit a specification search with a complete ledger and null-calibrated honest p-values, replay realistic search procedures, detect p-hacking in a literature, immunise an analysis, and benchmark whether an AI agent p-hacks. Research and teaching use only.

by Dylan Moore

Comprehensive Stata reference — syntax, data management, econometrics, causal inference, graphics, Mata, and 20 community packages.

by Dylan Moore

Develop high-performance C/C++ plugins for Stata — SDK setup, .ado wrappers, cross-platform compilation, performance optimization, and Python/R package translation.

by Dylan Moore

Development and testing tools for contributing to the stata-skill project. Run evals, analyze results, improve docs.

by 一泽 Eze

Complete web browsing and automation skill for Claude Code - intelligent tool selection, CDP browser automation, and site experience accumulation