Skills for running empirical economics analysis end to end in Python, Stata, or R, covering DID, RD, IV, synthetic control, and double machine learning. Each skill follows the conventions of applied economics papers and produces paper-style results.
@brycewang-stanfordHelps you prepare an academic paper for AAAI, from experiments and related work through author rebuttals, camera-ready files and artifact packaging. Each stage gets its own guidance, so you spend less time checking venue rules by hand.
@brycewang-stanfordUse when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics…
@brycewang-stanfordClassical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy +…
@brycewang-stanfordClassical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid +…
@brycewang-stanfordClassical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem — dplyr + tidyr + haven +…
@brycewang-stanfordUniversal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports…
@brycewang-stanfordThis skill should be used when the user asks to "implement a DiD regression", "write a causal inference pipeline", "set up an…
@brycewang-stanfordSTATA code pattern library for empirical archival accounting research. Provides tested syntax from 126 peer-reviewed JAR (Journal…
@brycewang-stanfordUse when writing Python code for DSGE models, HANK models, numerical economic computation, causal inference, or quantitative…
@brycewang-stanfordVS-Enhanced Research Question Refiner - Prevents Mode Collapse and derives differentiated research questions Enhanced VS 3-Phase…
@brycewang-stanfordVS-Enhanced Theoretical Framework Architect with Critique & Visualization Full VS 5-Phase process: Modal theory avoidance,…
@brycewang-stanfordAgent A5 - Paradigm & Worldview Advisor - Philosophical foundations for research design. Covers ontology, epistemology, axiology,…
@brycewang-stanfordUse when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance…
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