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US housing-vacancy signals (market tightness)

Quarterly US housing-vacancy signals from the Census Bureau (FRED RRVRUSQ156N rental vacancy and RHVRUSQ156N homeowner vacancy, 1956-Q1 ->): 1-year momentum, year-on-year change, 4-quarter volatility, 3-sigma anomaly flags, naive-drift forecasts, 5-year z-scores, a tight-rental-market (<7%) flag, and an elevated-homeowner-vacancy (>=2.5%) flag. The tightness lens on US housing — the direct gauge of supply/demand balance — complementing housing-signals (construction, prices, mortgage rates). All rows normalized to country_code USA. Raw series: U.S. Census Bureau (Housing Vacancy Survey) via FRED.

Source: US Housing-Vacancy Signals (derived)564 lignesMis à jour: 22/09/2026
housingvacancyrentaltightnesssupply-demandrentscensusmomentumanomaly-detectionforecastingsignalsfred

Qualité

95.8

Attribution

U.S. Census Bureau via FRED; signals by Frontier Data Hub

Schéma

ColonneTypeDescription
datestringObservation date (FRED API field date; YYYY-MM-DD, quarterly).
countrystring
country_codestring
series_idstringRRVRUSQ156N: Rental Vacancy Rate for the United States (percent); RHVRUSQ156N: Homeowner Vacancy Rate for the United States (percent). Both from the U.S. Census Bureau, Housing Vacancy Survey, not seasonally adjusted.
series_labelstringThe rental vacancy rate is the share of the rental housing inventory that is vacant and available for rent; the homeowner vacancy rate is the share of the homeowner inventory that is vacant and for sale. Together they measure the supply/demand balance of the US housing stock.
valuefloatVacancy rate in percent. Low rental vacancy signals a landlord's market and coming rent pressure; elevated homeowner vacancy signals for-sale slack and potential price pressure.
momentum_1y_ppfloat
yoy_change_ppfloat
volatility_4qfloat
anomaly_flaginteger
forecast_1qfloat
z_5yfloat
tight_rental_flagfloat
high_homeowner_vacancy_flagfloat
rental_z_5yfloat
homeowner_z_5yfloat

Exemple de lignes

datecountrycountry_codeseries_idseries_labelvaluemomentum_1y_ppyoy_change_ppvolatility_4qanomaly_flagforecast_1qz_5ytight_rental_flaghigh_homeowner_vacancy_flagrental_z_5yhomeowner_z_5y
1956-01-01United StatesUSARHVRUSQ156NHomeowner Vacancy Rate for the United States (percent, Census Bureau via FRED)100
1956-04-01United StatesUSARHVRUSQ156NHomeowner Vacancy Rate for the United States (percent, Census Bureau via FRED)100
1956-07-01United StatesUSARHVRUSQ156NHomeowner Vacancy Rate for the United States (percent, Census Bureau via FRED)1.100
1956-10-01United StatesUSARHVRUSQ156NHomeowner Vacancy Rate for the United States (percent, Census Bureau via FRED)0.900
1957-01-01United StatesUSARHVRUSQ156NHomeowner Vacancy Rate for the United States (percent, Census Bureau via FRED)0.9-0.09999999999999998-0.099999999999999980.1258305739211792200

Télécharger un échantillon

Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).

Utiliser avec un LLM

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

curl "https://datazimuts.com/v1/datasets/housing_vacancy_signals/us_housing_vacancy_signals" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/housing_vacancy_signals/us_housing_vacancy_signals").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/housing_vacancy_signals/us_housing_vacancy_signals

Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.

US housing-vacancy signals (market tightness)