econometrics-skills
10 econometrics skills. Trigger: causal analysis, regression models, treatment effects, panel data. Design: method-centric guides with R/Python code and diagnostic tests.
Best use case
econometrics-skills is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
10 econometrics skills. Trigger: causal analysis, regression models, treatment effects, panel data. Design: method-centric guides with R/Python code and diagnostic tests.
Teams using econometrics-skills should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/econometrics/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How econometrics-skills Compares
| Feature / Agent | econometrics-skills | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
10 econometrics skills. Trigger: causal analysis, regression models, treatment effects, panel data. Design: method-centric guides with R/Python code and diagnostic tests.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# Econometrics — 10 Skills Select the skill matching the user's need, then `read` its SKILL.md. | Skill | Description | |-------|-------------| | [causal-inference-guide](./causal-inference-guide/SKILL.md) | Causal inference methods including DiD, IV, RDD, and synthetic control | | [econml-causal-guide](./econml-causal-guide/SKILL.md) | Apply EconML for causal inference combining machine learning and econometrics | | [iv-regression-guide](./iv-regression-guide/SKILL.md) | Apply instrumental variables, 2SLS, and address endogeneity issues | | [mostly-harmless-guide](./mostly-harmless-guide/SKILL.md) | Replication code and guide for Mostly Harmless Econometrics methods | | [panel-data-guide](./panel-data-guide/SKILL.md) | Panel data analysis with fixed and random effects models | | [python-causality-guide](./python-causality-guide/SKILL.md) | Learn causal inference with Python using the Brave and True handbook | | [robustness-checks](./robustness-checks/SKILL.md) | Sequential robustness checks in Stata with confounder blocks | | [stata-analyst-guide](./stata-analyst-guide/SKILL.md) | Stata workflows for publication-ready sociology and social science research | | [stata-reference-guide](./stata-reference-guide/SKILL.md) | Comprehensive Stata reference covering syntax, econometrics, and 20+ packages | | [time-series-guide](./time-series-guide/SKILL.md) | Apply ARIMA, VAR, cointegration, and time series econometric methods |
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