Audit Restrictions

Build a complete registry: restriction_number | restriction_name | variables_needed | variable_type

Phase 2: Check Data Availability

For each variable identified in Phase 1:

1. Check the panel: Read code/utils/data_loader.py for _MACRO_COLS and load a sample of data/processed/panel_monthly.parquet column names to verify the variable exists
2. Check raw sources: If not in panel, check data/raw/ for source files and code/data_pipeline/build_panel.py for construction logic
3. Check proxies: Some restrictions use proxies (e.g., BidAskSpread for search intensity). Flag these as "proxy" not "exact match"

Classify each variable as:

• AVAILABLE: exists in the panel (exact or close match)
• PROXY: available but using a proxy variable (note what the proxy is)
• CONSTRUCTIBLE: raw data exists, needs to be added to build_panel.py
• MISSING: no data source identified

Phase 3: Check Paper Documentation

For each restriction, verify the paper explains how the data is obtained. Check these files:

• paper/sections/estimation.tex or paper/sections/empirical.tex — should have a "Data" subsection
• paper/sections/framework.tex — may document variable construction
• paper/sections/introduction.tex — may reference data sources

For each variable, check:

1. Is the data source mentioned? (e.g., "from CRSP", "from Compustat", "from FRED")
2. Is the construction explained if it's derived? (e.g., "I/K = capx / ppent")
3. Is the availability period noted if limited? (e.g., "VIX available from 1990")

Classify each as:

• DOCUMENTED: source and construction explained
• PARTIAL: mentioned but construction not explained
• UNDOCUMENTED: not mentioned in the paper

Phase 4: Check Summary Statistics

Read the Table 1 generator (code/tables/summary_stats.py) and the generated paper/tables/table_1.tex. For each variable used in restrictions:

1. Does it appear in Panel A (firm characteristics) or Panel B (macro variables)?
2. If it's a key variable used in multiple restrictions, it SHOULD be in the summary stats
3. Flag variables used in 3+ restrictions that are missing from summary statistics

Classify as:

• IN TABLE: appears in summary statistics
• SHOULD ADD: used in 3+ restrictions, missing from table
• OK TO OMIT: used in 1-2 restrictions, omission is acceptable

Phase 5: Generate Report

Write the audit report to quality_reports/restriction_audit.md with:

# Restriction Data Audit — [date]

## Summary
- Total restrictions: X
- Variables covered: Y / Z
- Documentation gaps: N
- Summary stats gaps: M

## Restriction-by-Variable Matrix

| # | Restriction | Variable | Data Status | Paper Doc | Summary Stats |
|---|------------|----------|-------------|-----------|---------------|
| 1 | Power utility | cons_growth | AVAILABLE | DOCUMENTED | IN TABLE |
| ... | ... | ... | ... | ... | ... |

## Issues Found

### Data Gaps
[List variables with MISSING or CONSTRUCTIBLE status]

### Documentation Gaps
[List variables with UNDOCUMENTED or PARTIAL status]

### Summary Statistics Gaps
[List variables with SHOULD ADD status]

## Recommended Fixes
[Specific actions: add to summary stats, add documentation paragraph, etc.]

Phase 6: Apply Fixes (if mode = fix)

Only if $ARGUMENTS = fix:

1. Summary stats: Update code/tables/summary_stats.py to add missing variables to Panel A or Panel B
2. Paper documentation: Add/update the data description paragraph in paper/sections/estimation.tex to cover undocumented variables
3. Do NOT modify restriction tables (Tables 2–9) — those are authoritative
4. After edits, regenerate Table 1: python -m code.generate_tables --table 1
5. Compile paper: latexmk -pdf -cd paper/main.tex

Output

• Report always saved to quality_reports/restriction_audit.md
• If fix mode: edited files listed at end of report
• Return summary to user with issue counts and top-priority fixes