US metro price-level intelligence (BEA RPP, annual)
US metro price-level intelligence from the BEA Regional Price Parities (RPP, 2008–2024 vintage, keyless FRED redistribution, U.S. public domain): ~384 metropolitan statistical areas (OMB 2023 delineations), annual, US = 100. Method: the closed RPPALL<CBSA> 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 metro-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), 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 cbsa_code + year for territory-level demand models, site selection, regional pricing, and real (price-level-adjusted) market sizing — the state panel's coarser sibling for metro granularity. Caveats: RPPs compare price levels across places, not inflation over time; the latest 1–2 vintages are routinely revised.
Les titres et les descriptions proviennent des sources de données, en anglais.
- Lignes
- 6 271
- Colonnes
- 16
- Cadence de la source
- Annuelle
- Dernière actualisation
- 2 oct. 2026
- Thème
- economy
| Colonne | 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). |
| cbsa_code | string | 5-digit CBSA code (OMB 2023 delineations). |
| metro_name | string | Metropolitan statistical area title. |
| metro_states | string | State codes spanned by the metro, hyphen-joined. |
| 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. |
10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.
| year | country | country_code | cbsa_code | metro_name | metro_states | 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 | 10180 | Abilene, TX | TX | 92,197 | -7,803 | low | 270 | — | — | 108,46 | d23189953e3831f6 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=RPPALL10180 | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2 008 | United States | USA | 10420 | Akron, OH | OH | 92,502 | -7,498 | low | 256 | — | — | 108,11 | 7912d1460f953499 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=RPPALL10420 | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2 008 | United States | USA | 10500 | Albany, GA | GA | 86,48 | -13,52 | very_low | 351 | — | — | 115,63 | a7c854cf3ef164a6 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=RPPALL10500 | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2 008 | United States | USA | 10540 | Albany, OR | OR | 99,323 | -0,677 | average | 82 | — | — | 100,68 | 913d6c644e3d5d58 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=RPPALL10540 | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2 008 | United States | USA | 10580 | Albany-Schenectady-Troy, NY | NY | 102,446 | 2,446 | average | 51 | — | — | 97,61 | 62a9f796003f9c71 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=RPPALL10580 | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2 008 | United States | USA | 10740 | Albuquerque, NM | NM | 96,974 | -3,026 | average | 133 | — | — | 103,12 | baea54f3cf0d1632 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=RPPALL10740 | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2 008 | United States | USA | 10780 | Alexandria, LA | LA | 89,683 | -10,317 | very_low | 319 | — | — | 111,5 | 8a64d0f7acb23079 | https://fred.stlouisfed.org/graph/fredgraph.csv?id=RPPALL10780 | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2 008 | United States | USA | 10900 | Allentown-Bethlehem-Easton, PA-NJ | PA-NJ | 101,062 | 1,062 | average | 60 | — | — | 98,95 | 645dd868d4e3437e | https://fred.stlouisfed.org/graph/fredgraph.csv?id=RPPALL10900 | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2 008 | United States | USA | 11020 | Altoona, PA | PA | 93,889 | -6,111 | low | 221 | — | — | 106,51 | 0935593cd5894b2e | https://fred.stlouisfed.org/graph/fredgraph.csv?id=RPPALL11020 | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
| 2 008 | United States | USA | 11100 | Amarillo, TX | TX | 95,81 | -4,19 | average | 162 | — | — | 104,37 | 42156dcb3150da3d | https://fred.stlouisfed.org/graph/fredgraph.csv?id=RPPALL11100 | https://www.bea.gov/data/prices-inflation/regional-price-parities-state-and-metro-area |
Profilé le 2 oct. 2026 à partir de l’instantané 20261002T024141Z-144011bec841
Mesuré- Complétude
- 97,8 %
- Lignes
- 6 271
- Colonnes
- 16
- Colonnes incomplètes
- 2
| Colonne | Manquant | Distinctes | Plage | Distribution |
|---|---|---|---|---|
| yearbigint | 0 % | 20 | 2 008 → 2 024médiane 2 016 | |
| countryvarchar | 0 % | 1 | — |
|
| country_codevarchar | 0 % | 1 | — |
|
| cbsa_codevarchar | 0 % | 351 | — |
|
| metro_namevarchar | 0 % | 412 | — |
|
| metro_statesvarchar | 0 % | 83 | — |
|
| price_level_indexdouble | 0 % | 5 048 | 78,28 → 122,87médiane 94,32 | 126 hors du 1er–99e centile |
| cost_premium_pctdouble | 0 % | 4 795 | -21,72 → 22,87médiane -5,68 | 126 hors du 1er–99e centile |
| price_tiervarchar | 0 % | 5 | — |
|
| national_rankbigint | 0 % | 403 | 1 → 369médiane 185 | 100 hors du 1er–99e centile |
| rpp_yoy_ppdouble | 5,9 % | 3 791 | -9,56 → 8,47médiane -0,0875 | 120 hors du 1er–99e centile |
| rpp_5y_ppdouble | 29,4 % | 2 842 | -10,45 → 12,03médiane -0,6285 | 90 hors du 1er–99e centile |
| local_purchasing_power_100double | 0 % | 2 281 | 81,39 → 127,75médiane 106,03 | 126 hors du 1er–99e centile |
| row_hashvarchar | 0 % | 5 642 | — |
|
| provenance_urlvarchar | 0 % | 400 | — |
|
| source_urlvarchar | 0 % | 1 | — |
|
- Actuelle
20261002T024141Z-144011bec841 · sha256 144011bec841…
6 271 lignes · premier instantané
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/bea_rpp_intel/bea_metro_rpp_annual" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/bea_rpp_intel/bea_metro_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)Point d’accès API : https://datazimuts.com/v1/datasets/bea_rpp_intel/bea_metro_rpp_annual
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.
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Épinglé à l’instantané 20261002T024141Z-144011bec841 et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.
U.S. Bureau of Economic Analysis. (2026). US metro price-level intelligence (BEA RPP, annual) [Data set, snapshot 20261002T024141Z-144011bec841, sha256 144011bec841]. Datazimuts. Retrieved 2026-10-02, from https://datazimuts.com/fr/datasets/bea_rpp_intel/bea_metro_rpp_annual?snapshot=20261002T024141Z-144011bec841
@misc{dz_bea_rpp_intel_bea_metro_rpp_annual_144011be,
title = {{US metro price-level intelligence (BEA RPP, annual)}},
author = {{U.S. Bureau of Economic Analysis}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/fr/datasets/bea_rpp_intel/bea_metro_rpp_annual?snapshot=20261002T024141Z-144011bec841}},
note = {Snapshot 20261002T024141Z-144011bec841, sha256 144011bec841a7e3a24fa47f1628d3782b7b4979464383eb22e2d35fd7c8ea41; accessed 2026-10-02}
}Intégrer un tableau ou un graphique
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<iframe src="https://datazimuts.com/embed/chart?dataset=bea_rpp_intel%2Fbea_metro_rpp_annual&lang=fr&theme=auto&snapshot=20261002T024141Z-144011bec841&x=year&y=year&agg=avg" title="US metro price-level intelligence (BEA RPP, annual)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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