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causal-powers

Causal Powers — a skills library for data analytics, causal inference, and reduced-form and structural econometrics.

2 · lancegui/causal-powers1 pluginMITupdated 9 days ago

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causal-powers

claudecodex

Superpowers for data analytics, causal inference, and econometrics: discipline skills that make the silent failures of data work loud — data contracts, data preparation, join-cardinality checks, wrong-number debugging, result verification, pre-analysis plans, descriptive evidence (stylized facts, trends, summary-stats tables, distributions, and maps done honestly — composition checks, real-vs-nominal, rate-not-count), causal identification, structural estimation (demand/BLP, dynamic discrete choice, games, auctions, consideration, search), predictive modeling (applied prediction — leakage-safe evaluation, deployment-matched splits, prediction-is-not-causation), analysis craft, code style (the author's flat-script voice for new R/Julia/Python files), figure craft (presentation-ready figures in any language — house style, Paul-Tol palette, B&W-legible, mandatory visual self-check), human-in-the-loop checkpoints, plan execution with parallel subagents, research-project organization, and a configurable R-first language profile. R, Julia, and Python.

19 skills · 2 agents · hooks

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