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GeraSure / US Auto Cost Context / Methodology

Gera State Auto-Cost Context Index (GSACCI) — Methodology

Full reproducible formula for the GSACCI/100 index. Risk-context signals only — not a premium quote. All numbers trace to US Census ACS 2022 and BLS CPI public-domain data.

Important: what this index does and does not measure

The Gera State Auto-Cost Context Index (GSACCI) is a risk-context signal, not an insurance premium quote. Auto insurance premiums depend on dozens of property-specific factors (driver age, vehicle make/model, credit score, driving record, local insurer competition) that are not available in any key-free public dataset. GSACCI measures two structural risk-context signals that are publicly available and independently verifiable: how many vehicles per household a state has (exposure) and how long those vehicles are driven daily (time on road). Combined with the national BLS CPI trend for motor vehicle insurance, this gives a directional signal for relative cost context — not a premium prediction.

What is the GSACCI?

The Gera State Auto-Cost Context Index (GSACCI) ranks all 50 US states and DC on a 0–100 scale for auto-insurance cost context. Higher scores indicate states where structural risk signals (vehicle ownership density × typical commute time) are higher, which tends to correlate with higher insurance market costs — but the GSACCI does not quote, predict or estimate a specific dollar premium.

It is computed by Gera from two federal open datasets:

  • US Census ACS 2022 1-Year Summary File — vehicles available by household (B08201), aggregate travel time to work (B08013), and total commuting workers (B08303). One record per state, all 50 + DC.
  • BLS CPI Series CUUR0000SETD01 — Motor Vehicle Insurance, all urban consumers. National annual averages 2018–2025, used to establish a national trend rate.

The GSACCI formula

Step 1 — vehicles per household:
  veh_per_hh = (0×no_veh + 1×one_veh + 2×two_veh
              + 3×three_veh + 4.5×four_plus) ÷ total_hh

Step 2 — mean commute (minutes):
  mean_commute = B08013_E001 ÷ B08303_E001

Step 3 — raw index:
  raw = veh_per_hh × mean_commute

Step 4 — normalise 0–100:
  GSACCI = ((raw − min_raw) ÷ (max_raw − min_raw)) × 100

Why these inputs? Vehicle density (vehicles per household) captures how car-dependent a state is — more cars = more insured vehicles = more exposure. Mean commute time captures how long those vehicles are driven daily — longer trips mean more time at risk. The product of these two creates a single exposure signal. Min-max normalisation puts all 51 observations on a 0–100 scale for comparability.

CPI trend: The BLS CUUR0000SETD01 series shows motor vehicle insurance has risen from an index of 385.9 (2022) to 432.8 (2025) — a 3-year compound annual growth rate of 3.89% per year. This is cited as national context on every page. Per-state BLS CPI for motor insurance is not available in key-free form, so the national trend applies uniformly.

BLS CPI motor vehicle insurance trend

Series CUUR0000SETD01 — Motor Vehicle Insurance, all urban consumers (1982-84=100). Annual averages. Source: BLS public API, no key required.

YearCPI (1982-84=100)YoY change
2018302.730—
2019313.4653.5%
2020324.6873.6%
2021342.9615.6%
2022385.94112.5%
2023411.7426.7%
2024417.1861.3%
2025432.8103.7%

3-year CAGR 2022–2025: 3.89% per year. Source: BLS CUUR0000SETD01.

Worked example — Maryland

Maryland has the highest GSACCI (100/100) among the 51 entries.

InputValueSource
Total households2,459,019ACS B08201_E001
Vehicles per household1.8023ACS B08201 formula
Total workers2,832,476ACS B08303_E001
Aggregate commute (person-min)87,373,671ACS B08013_E001
Mean commute (min)30.8487,373,671 ÷ 2,832,476
Raw index55.581.8023 × 30.84
GSACCI (normalised)100.0 / 100highest state = 100

Data sources and licence

Census ACS 2022

Contains public sector information published by US Census Bureau and licensed under the US Government public domain. Source: US Census ACS 2022 1-Year Summary File — Tables B08201, B08013, B08303 (ACS 2022, published 2023).

American Community Survey 1-Year Estimates. Tables B08201 (Household Size by Vehicles Available), B08013 (Aggregate Travel Time to Work), and B08303 (Travel Time to Work). These are flat-file downloads — no API key required. US Government public-domain data; no copyright applies to federal works.

BLS CPI CUUR0000SETD01

Contains public sector information published by US Bureau of Labor Statistics and licensed under the US Government public domain. Source: BLS CPI Motor Vehicle Insurance (CUUR0000SETD01, all urban consumers) (2025, published 2026).

Motor Vehicle Insurance component of the Consumer Price Index for All Urban Consumers (CPI-U). Accessed via the BLS public REST API v1 (no registration key required for single-series, recent-years queries). Annual averages (period M13) used for trend computation. US Government public-domain data.

Reproducing the GSACCI

  1. Download acsdt1y2022-b08201.dat, acsdt1y2022-b08013.dat, and acsdt1y2022-b08303.dat from the ACS 2022 1-Year Data directory.
  2. Filter rows where GEO_ID starts with 0400000US (51 rows).
  3. For each state compute veh_per_hh (B08201 formula above) and mean_commute_min (B08013_E001 ÷ B08303_E001).
  4. Compute raw_index = veh_per_hh × mean_commute_min. Min-max normalise across all 51 rows → GSACCI.
  5. Fetch https://api.bls.gov/publicAPI/v1/timeseries/data/CUUR0000SETD01for the national CPI trend context. Use period M13 (annual average).
  6. Verify a sample: pick any state from the published pages, confirm its veh_per_hh, mean_commute_min, and gsaccimatch the formula applied to the downloaded ACS CSVs.

Exclusions and honesty note

  • No dollar premium figure is published anywhere in GS-US1. Actual auto insurance premiums are available only from insurer rate filings (PDF-only at state DOI offices, not machine-readable), NAIC reports (not bulk-licensed), or proprietary quote engines. None of these are available key-free; quoting a premium from them would require fabrication.
  • No per-state BLS CPI breakdown. The BLS series CUUR0000SETD01 is national (all-urban-consumers). State-level motor-insurance CPI breakdowns require a BLS API key and a regional series subscription not available in the public no-key v1 endpoint.
  • ACS 2022 is the most recent 1-Year file confirmed available key-free. Gera will update this index when the 2023 or 2024 1-Year files are confirmed accessible at the same URL pattern.
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