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

1. Hedonic regressions — Cross-sectional:

   log(price)

   on spill count/hours (continuous + bins), LSOA FE, heteroskedasticity-robust SE
2. Repeat sales — Within-property variation (Palmquist 1982), house fixed effects
3. Long difference — 250m grid-level changes, weighted/unweighted, all/exposed grids
4. News/media DiD — Google Trends and LexisNexis media coverage as treatment
5. Upstream/downstream — Directional spillover via PostGIS river network topology
6. 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_sites

  within 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/

  through

  scripts/R/06_analysis_datasets/

---

Workflow

Step 1: Parse Input

Determine target from

$ARGUMENTS

:

• .tex

  file: Review manuscript section for identification claims, assumption statements, estimation descriptions

• .R

  file: 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

  : Review

  docs/overleaf/*.tex

  and

  scripts/R/09_analysis/

• No argument: Review all manuscript sections and analysis scripts

Step 2: Context Gathering

Before auditing:

1. Read the target file(s)
2. Read

   docs/overleaf/refs.bib

   for citation availability
3. If reviewing scripts: read corresponding manuscript section for code-theory alignment
4. If reviewing manuscript: read corresponding analysis scripts for accuracy
5. Read

   scripts/R/utils/spill_aggregation_utils.R

   for 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.