brycewang-stanford/econometrics-check
skills/41-sticerd-eee-sewage-econometrics-check/skills/econometrics-check/SKILL.md
Causal inference design audit for the sewage-house-prices project. Runs a 4-phase review (claim identification, design validity, inference, polish) covering hedonic pricing, repeat sales, long difference, DiD/event studies, upstream/downstream, and dry spill strategies. This skill should be used when asked to "check the econometrics", "audit the identification", "review the strategy", or when verifying that code matches the stated design.
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skillsauthnpx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research econometrics-checkInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- econometrics-check
- description:
- Causal inference design audit for the sewage-house-prices project. Runs a 4-phase review (claim identification, design validity, inference, polish) covering hedonic pricing, repeat sales, long difference, DiD/event studies, upstream/downstream, and dry spill strategies. This skill should be used when asked to "check the econometrics", "audit the identification", "review the strategy", or when verifying that code matches the stated design.
- argument-hint:
- [.tex section, .R script, directory path, or 'all']
- allowed-tools:
- ["Read", "Grep", "Glob", "Write", "Agent"]
Econometrics Check
Run a 4-phase causal inference audit on the target file(s) for the sewage-house-prices project.
Input: $ARGUMENTS — a .tex file, .R script, directory path, or all.
Project-Specific Context
Identification Strategies in This Paper
- Hedonic regressions — Cross-sectional:
log(price)on spill count/hours (continuous + bins), LSOA FE, heteroskedasticity-robust SE - Repeat sales — Within-property variation (Palmquist 1982), house fixed effects
- Long difference — 250m grid-level changes, weighted/unweighted, all/exposed grids
- News/media DiD — Google Trends and LexisNexis media coverage as treatment
- Upstream/downstream — Directional spillover via PostGIS river network topology
- Dry spills — Spills occurring without rainfall as identification variation (rainfall threshold-based)
Key Variables
- Outcome:
log(price)for sales,log(rent)for rentals - Treatment:
spill_count,spill_hrs,spill_count_daily_avg,spill_hrs_daily_avg - Geography:
n_spill_siteswithin radius,min_dist/mean_dist - Radii: 250m, 500m, 1000m, 2000m, 5000m, 10000m
- Fixed effects: LSOA (
lsoa), MSOA (msoa), year-quarter - SE: heteroskedasticity-robust via
fixest::feols(vcov = "hetero") - Counting: 12/24-hour methodology in
spill_aggregation_utils.R
File Locations
- Manuscript:
docs/overleaf/*.tex - Analysis scripts:
scripts/R/09_analysis/ - Utility functions:
scripts/R/utils/ - Pipeline scripts:
scripts/R/01_data_ingestion/throughscripts/R/06_analysis_datasets/
Workflow
Step 1: Parse Input
Determine target from $ARGUMENTS:
.texfile: Review manuscript section for identification claims, assumption statements, estimation descriptions.Rfile: Review analysis script for code-theory alignment, package usage, SE computation- Directory (e.g.
scripts/R/09_analysis/02_hedonic/): Review all scripts in that approach all: Reviewdocs/overleaf/*.texandscripts/R/09_analysis/- No argument: Review all manuscript sections and analysis scripts
Step 2: Context Gathering
Before auditing:
- Read the target file(s)
- Read
docs/overleaf/refs.bibfor citation availability - If reviewing scripts: read corresponding manuscript section for code-theory alignment
- If reviewing manuscript: read corresponding analysis scripts for accuracy
- Read
scripts/R/utils/spill_aggregation_utils.Rfor counting methodology
Step 3: Run 4-Phase Review
Phase 1: Claim Identification
- What design is being used? (hedonic / repeat sales / long diff / DiD / upstream-downstream / dry spill)
- What is the estimand? (ATT / ATE / LATE)
- What is the treatment? (spill count, spill hours, distance, media coverage)
- What is the comparison group?
Phase 2: Core Design Validity
Design-specific assumption checks:
Hedonic:
- Selection on observables assumption — are LSOA FE sufficient?
- Omitted variable bias from neighbourhood sorting
- Measurement error in spill count/hours
Repeat sales:
- Within-property variation correctly specified
- Time-varying confounders addressed
- Property-level fixed effects properly implemented
Long difference:
- Grid construction and assignment correct
- Weighted vs unweighted justified
- Pre-period balance
DiD / Event studies:
- Parallel trends assumption stated and tested
- Treatment timing correctly identified
- Staggered adoption issues addressed (if applicable)
Upstream/downstream:
- River network topology correctly implemented
- Directionality assumption valid
- Spillover definitions consistent
Dry spills:
- Rainfall threshold justified
- Dry vs wet spill definition consistent with data pipeline
- Selection into dry spills addressed
Phase 3: Inference
- SE computation: heteroskedasticity-robust applied correctly
- Multiple testing: across radii, specifications, outcomes
- Code-theory alignment: does the R code implement what the paper claims?
Phase 4: Polish & Completeness
- Robustness checks: radius sensitivity, time period variation, specification changes
- Sensitivity analysis: how sensitive are results to key assumptions?
- Citation fidelity: are methodological references accurate?
Early stopping: If Phase 2 finds CRITICAL issues, focus there.
Step 4: Present Summary
## Econometrics Audit: [target]
**Date:** YYYY-MM-DD
### Design(s) Reviewed
- [List designs audited]
### Overall Assessment: [SOUND / MINOR ISSUES / MAJOR ISSUES / CRITICAL ERRORS]
### Blocking Issues (CRITICAL)
1. ...
### Priority Action List
1. ...
2. ...
3. ...
### Positive Findings
- ...
Save report to output/log/econometrics_check_[target].md.
Principles
- Design-opinionated, package-flexible. Validate the econometric logic, not just the R packages.
- Cross-reference code and paper. Flag any mismatch between what the manuscript says and what the script does.
- Actionable output. Every issue must have a concrete fix.
- Proportional. Not every approach needs every robustness check.
- Sequential phases. Never skip to robustness before verifying the core design holds.
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