OECD Analytical House Prices: real house price index
Quarterly real (inflation-adjusted) house price indices, 2015=100, from the OECD Analytical House Prices database (OECD measure RHP: "Real house price indices"): 50 OECD members, partner economies and aggregates (euro area, OECD total), 1960-Q1 to the present (2026-Q2 as of 2026-09-23). Method: the OECD compiles national house-price sources and deflates the nominal indices to remove general price inflation; every series is seasonally adjusted. Unit: index points, 2015=100. Caveats: national sources and dwelling coverage differ across countries (documented per country by the OECD), so cross-country levels are less comparable than growth rates; emerging-economy histories start later (e.g. Saudi Arabia 2014-Q1, China 2010-Q1). Coverage: 50 areas including Brazil, China, India, Indonesia, Russia, Saudi Arabia and South Africa. Provenance: OECD SDMX-REST v2, keyless - please cite the OECD. Primary key: (quarter, country_code). Join keys: country_code (ISO 3166-1 alpha-3 for countries; EA, EA17 and OECD aggregates kept verbatim as published), quarter (first day of quarter). Cadence: refreshed quarterly; the OECD publishes with about one quarter's lag. Sample use: join with 'eurostat-house-price-index-quarterly' on (quarter, country_code) to compare OECD and Eurostat house-price dynamics.
- Source
- OECD
- Rows
- 7,554
- Columns
- 4
- Source cadence
- Quarterly
- Last refreshed
- Sep 23, 2026
- Theme
- housing
| Column | Type | Description |
|---|---|---|
| quarter | string | Reference quarter (the TIME_PERIOD column of the OECD SDMX-CSV response), stored as the first day of the quarter. |
| country_code | string | OECD REF_AREA code: ISO 3166-1 alpha-3 for countries (e.g. 'USA'); the EA (euro area), EA17 and OECD aggregates are kept verbatim as published. |
| country_name | string | Economy name from the OECD CL_AREA codelist, e.g. 'United States'. |
| index_2015_100 | float | Real house price index (OECD measure RHP: "Real house price indices"): inflation-adjusted house price index, seasonally adjusted. Unit: index points, 2015=100. (unit: index points, 2015=100) |
First 10 sample rows — a preview, not the complete dataset.
| quarter | country_code | country_name | index_2015_100 |
|---|---|---|---|
| 1970-01-01 | AUS | Australia | 25.572 |
| 1970-04-01 | AUS | Australia | 25.939 |
| 1970-07-01 | AUS | Australia | 26.455 |
| 1970-10-01 | AUS | Australia | 26.505 |
| 1971-01-01 | AUS | Australia | 26.7 |
| 1971-04-01 | AUS | Australia | 26.986 |
| 1971-07-01 | AUS | Australia | 27.464 |
| 1971-10-01 | AUS | Australia | 27.746 |
| 1972-01-01 | AUS | Australia | 27.958 |
| 1972-04-01 | AUS | Australia | 28.258 |
Profiled Sep 23, 2026 from snapshot 20260923T222804Z-08541430eb70
Measured- Completeness
- 100%
- Rows
- 7,554
- Columns
- 4
- Columns with gaps
- 0
| Column | Missing | Distinct | Range | Distribution |
|---|---|---|---|---|
| quartervarchar | 0% | 296 | — |
|
| country_codevarchar | 0% | 50 | — |
|
| country_namevarchar | 0% | 46 | — |
|
| index_2015_100double | 0% | 6,768 | 22.34 → 225.4median 94.77 | 152 outside 1st–99th percentile |
- Current
20260923T222804Z-08541430eb70 · sha256 08541430eb70…
7,554 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/oecd/real_house_price_index_quarterly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/oecd/real_house_price_index_quarterly").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/oecd/real_house_price_index_quarterly
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 20260923T222804Z-08541430eb70 and its content hash, so readers get exactly the data you used.
OECD. (2026). OECD Analytical House Prices: real house price index [Data set, snapshot 20260923T222804Z-08541430eb70, sha256 08541430eb70]. Datazimuts. Retrieved 2026-09-24, from https://datazimuts.com/en/datasets/oecd/real_house_price_index_quarterly?snapshot=20260923T222804Z-08541430eb70
@misc{dz_oecd_real_house_price_index_quarterly_08541430,
title = {{OECD Analytical House Prices: real house price index}},
author = {{OECD}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/oecd/real_house_price_index_quarterly?snapshot=20260923T222804Z-08541430eb70}},
note = {Snapshot 20260923T222804Z-08541430eb70, sha256 08541430eb7054a7015566250e04ca7285377cb105450795d70ffe733d65ef31; accessed 2026-09-24}
}Embed a table or a chart
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<iframe src="https://datazimuts.com/embed/chart?dataset=oecd%2Freal_house_price_index_quarterly&lang=en&theme=auto&snapshot=20260923T222804Z-08541430eb70&x=quarter&y=index_2015_100&agg=avg" title="OECD Analytical House Prices: real house price index" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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