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# Data audit (P1)

file SHA-256 rows (excl. header) cols
data/cpi_quarterly.csv c8652dec1567ec35e3b84ee8fa55545e9bf0ae4990a4d6d05b89a6d22f6801ea 127 3 (quarter, cpi_avg, infl_annualised)
data/cpi_monthly.csv 855d069176369d30d02cbbe0cc6456b76d2f3967cdaabc1b362c2461ef9015a2 381 2 (month, cpi)
data/README.md 8ddc03b23fc4efce8ce697879fbb2ddca04c40ae54eb772a04e9777444098d0a — —

All hashes match README.md and bundle.json.

  • Units: cpi index (2002=100, NSA); infl_annualised in percent at annual rate.
  • Date ranges: quarterly 1995-01-01 … 2026-07-01 (127 consecutive quarters, all start months in {1,4,7,10}); monthly 1995-01 … 2026-09 (381 consecutive months).
  • Missing: only infl_annualised for 1995Q1 (by construction, no lag). No duplicates in either file.
  • Derivation check: quarterly mean of monthly values reproduces cpi_avg (max abs diff 3.3e-7, every quarter has 3 months); 400·Δln cpi_avg reproduces infl_annualised (max abs diff 3.3e-6, rounding).
  • Distribution: mean 2.13, sd 2.39, min −6.04, max 12.15 (2022Q2 — genuine inflation surge, not an error; kept). Strong seasonality: mean by quarter Q1 2.32, Q2 4.18, Q3 1.66, Q4 0.30.
  • Availability: last target needed is 2026-07-01 (origin 2025-07-01, h=4) — present. No input violates the availability rules; the analysis code truncates the series at each origin before any estimation.
  • Exclusions: 1995Q1 dropped (no inflation value). See out/exclusions.csv.
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