US state price-level intelligence (BEA RPP, annual)
US state price-level intelligence from the BEA Regional Price Parities (RPP, 2008–2024 vintage, keyless FRED redistribution, U.S. public domain): 50 states plus DC, annual, US = 100. Method: the closed 51-series <ST>RPPALL universe is pulled via fredgraph.csv; every series must span 2008 to the latest vintage with zero gaps and plausible values or the ingest fails loudly. Derived signals per state-year: cost_premium_pct (RPP − 100), a documented 5-band price_tier (very_low <90 … very_high ≥110), within-year national_rank (1 = most expensive), 1-year and 5-year index-point drift (rpp_yoy_pp / rpp_5y_pp — relative price convergence or divergence), and local_purchasing_power_100 (10000/RPP: the national-dollar value of $100 spent locally). Use as prediction features: join to customers/orders/leads by state_code + year to deflate nominal amounts into real terms, set regional price lists and sales quotas, and score market affordability — a $29 subscription feels like $26 in California but $33 in Mississippi. Caveats: RPPs compare price levels across places, not inflation over time; the latest 1–2 vintages are routinely revised.
- Rows
- 867
- Columns
- 16
- Source cadence
- Yearly
- Last refreshed
- Oct 2, 2026
- Theme
- economy
| Column | Type | Description |
|---|---|---|
| year | integer | Reference year of the RPP vintage. |
| country | string | Country name (United States). |
| country_code | string | ISO alpha-3 country code (USA). |
| state_code | string | USPS 2-letter state / district code. |
| state_fips | string | 2-digit state FIPS code. |
| state_name | string | State / district name. |
| price_level_index | float | BEA Regional Price Parity: price level as a percentage of the overall national price level (US = 100). |
| cost_premium_pct | float | Signed premium (+) or discount (−) vs the national average: price_level_index − 100. |
| price_tier | string | Documented 5-band cut: very_low (<90), low (90–95), average (95–105), high (105–110), very_high (>=110). |
| national_rank | integer | Within-year rank of price_level_index across the universe (1 = most expensive; ties share the rank). |
| rpp_yoy_pp | float | 1-year change of the index in percentage points (relative price drift). |
| rpp_5y_pp | float | 5-year change of the index in percentage points (structural drift). |
| local_purchasing_power_100 | float | 10000 / price_level_index: the national-dollar value of $100 spent locally — deflate nominal amounts by this / 100. |
| row_hash | string | Content hash (sha256, 16 hex) over geography, year, and index. |
| provenance_url | string | Exact fredgraph.csv URL behind this row's series. |
| source_url | string | Canonical BEA Regional Price Parities page. |
First 10 sample rows — a preview, not the complete dataset.
| year | country | country_code | state_code | state_fips | state_name | price_level_index | cost_premium_pct | price_tier | national_rank | rpp_yoy_pp | rpp_5y_pp | local_purchasing_power_100 | row_hash | provenance_url | source_url |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2,008 | United States | USA | AK | 02 | Alaska | 103.878 | 3.878 | average | 11 | — | — | 96.27 | 644a0429a9afce57 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=AKRPPALL | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2,008 | United States | USA | AL | 01 | Alabama | 88.901 | -11.099 | very_low | 44 | — | — | 112.48 | 137f8225ede9b7ca | https://fred.stlouisfed.org/graph/fredgraph.csv?id=ALRPPALL | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2,008 | United States | USA | AR | 05 | Arkansas | 88.096 | -11.904 | very_low | 46 | — | — | 113.51 | 0ea190dc2ed52d8c | https://fred.stlouisfed.org/graph/fredgraph.csv?id=ARRPPALL | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2,008 | United States | USA | AZ | 04 | Arizona | 102.504 | 2.504 | average | 15 | — | — | 97.56 | 6f20599ce064c569 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=AZRPPALL | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2,008 | United States | USA | CA | 06 | California | 111.22 | 11.22 | very_high | 3 | — | — | 89.91 | 627afc3a2bf2d8d6 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=CARPPALL | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2,008 | United States | USA | CO | 08 | Colorado | 103.315 | 3.315 | average | 13 | — | — | 96.79 | 9d2dc4898cf9c179 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=CORPPALL | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2,008 | United States | USA | CT | 09 | Connecticut | 110.451 | 10.451 | very_high | 4 | — | — | 90.54 | 1ea070b5b7a70985 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=CTRPPALL | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2,008 | United States | USA | DC | 11 | District of Columbia | 112.368 | 12.368 | very_high | 1 | — | — | 88.99 | 43c0f7d2a1832c1e | https://fred.stlouisfed.org/graph/fredgraph.csv?id=DCRPPALL | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2,008 | United States | USA | DE | 10 | Delaware | 100.753 | 0.753 | average | 18 | — | — | 99.25 | 27eeae0a18f0aef9 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=DERPPALL | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2,008 | United States | USA | FL | 12 | Florida | 101.668 | 1.668 | average | 16 | — | — | 98.36 | c1b627c34ab49e81 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=FLRPPALL | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
Profiled Oct 2, 2026 from snapshot 20261002T023303Z-5f0cc10e6281
Measured- Completeness
- 97.8%
- Rows
- 867
- Columns
- 16
- Columns with gaps
- 2
| Column | Missing | Distinct | Range | Distribution |
|---|---|---|---|---|
| yearbigint | 0% | 20 | 2,008 → 2,024median 2,016 | |
| countryvarchar | 0% | 1 | — |
|
| country_codevarchar | 0% | 1 | — |
|
| state_codevarchar | 0% | 55 | — |
|
| state_fipsvarchar | 0% | 52 | — |
|
| state_namevarchar | 0% | 59 | — |
|
| price_level_indexdouble | 0% | 880 | 85.02 → 114.24median 96.72 | 18 outside 1st–99th percentile |
| cost_premium_pctdouble | 0% | 725 | -14.98 → 14.24median -3.28 | 18 outside 1st–99th percentile |
| price_tiervarchar | 0% | 5 | — |
|
| national_rankbigint | 0% | 45 | 1 → 51median 26 | |
| rpp_yoy_ppdouble | 5.9% | 905 | -5.81 → 5.28median -0.048 | 18 outside 1st–99th percentile |
| rpp_5y_ppdouble | 29.4% | 532 | -6.31 → 6.33median -0.2305 | 14 outside 1st–99th percentile |
| local_purchasing_power_100double | 0% | 732 | 87.53 → 117.62median 103.39 | 18 outside 1st–99th percentile |
| row_hashvarchar | 0% | 810 | — |
|
| provenance_urlvarchar | 0% | 48 | — |
|
| source_urlvarchar | 0% | 1 | — |
|
- Current
20261002T023303Z-5f0cc10e6281 · sha256 5f0cc10e6281…
867 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/bea_rpp_intel/bea_state_rpp_annual" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/bea_rpp_intel/bea_state_rpp_annual").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/bea_rpp_intel/bea_state_rpp_annual
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20261002T023303Z-5f0cc10e6281 and its content hash, so readers get exactly the data you used.
U.S. Bureau of Economic Analysis. (2026). US state price-level intelligence (BEA RPP, annual) [Data set, snapshot 20261002T023303Z-5f0cc10e6281, sha256 5f0cc10e6281]. Datazimuts. Retrieved 2026-10-02, from https://datazimuts.com/en/datasets/bea_rpp_intel/bea_state_rpp_annual?snapshot=20261002T023303Z-5f0cc10e6281
@misc{dz_bea_rpp_intel_bea_state_rpp_annual_5f0cc10e,
title = {{US state price-level intelligence (BEA RPP, annual)}},
author = {{U.S. Bureau of Economic Analysis}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/bea_rpp_intel/bea_state_rpp_annual?snapshot=20261002T023303Z-5f0cc10e6281}},
note = {Snapshot 20261002T023303Z-5f0cc10e6281, sha256 5f0cc10e6281ea45a98400f9aa97e0859bb71012d03dcc445d03903f4df2df45; accessed 2026-10-02}
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