Facebook
TwitterAttribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
This dataset provides comprehensive insights into U.S. residential house prices through the S&P Case-Shiller Home Price Index, which includes both the national index and indices for 20 metropolitan regions. The data is derived from the S&P Case-Shiller Index, a widely recognized and reliable measure of U.S. housing price movements. It is updated monthly and utilizes the "repeat sales method" to track the price changes of the same properties over time, making it an accurate reflection of housing appreciation.
The dataset includes: - S&P/Case-Shiller U.S. National Home Price Index: A composite index of single-family home prices across nine U.S. Census divisions. - Indices for 20 Metropolitan Regions: Regional indices that highlight housing price trends in major U.S. cities.
The index uses a "repeat sales" approach, which tracks properties that have been sold at least twice to capture changes in their value over time. This method minimizes biases from changes in housing stock or individual property characteristics. The index originated in the 1980s through the work of Karl E. Case and Robert J. Shiller, pioneers in developing the repeat sales technique. It remains one of the most trusted tools for measuring U.S. housing market trends.
The indices are used widely by policymakers, economists, and analysts to gauge housing market conditions and make informed decisions.
This dataset can be used for: - Housing Market Analysis: Track trends in national and metropolitan housing prices. - Econometric Modeling: Analyze the relationship between housing prices and macroeconomic factors. - Forecasting: Build models to predict future housing market movements.
Data sourced from: https://github.com/datasets/house-prices-us Original source: https://datahub.io/core/house-prices-us
Facebook
Twitterhttps://fred.stlouisfed.org/legal/#copyright-pre-approvalhttps://fred.stlouisfed.org/legal/#copyright-pre-approval
Graph and download economic data for S&P CoreLogic Case-Shiller NY-New York Home Price Index (NYXRSA) from Jan 1987 to Sep 2025 about New York, NY, HPI, housing, price index, indexes, price, and USA.
Not seeing a result you expected?
Learn how you can add new datasets to our index.
Facebook
TwitterAttribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
This dataset provides comprehensive insights into U.S. residential house prices through the S&P Case-Shiller Home Price Index, which includes both the national index and indices for 20 metropolitan regions. The data is derived from the S&P Case-Shiller Index, a widely recognized and reliable measure of U.S. housing price movements. It is updated monthly and utilizes the "repeat sales method" to track the price changes of the same properties over time, making it an accurate reflection of housing appreciation.
The dataset includes: - S&P/Case-Shiller U.S. National Home Price Index: A composite index of single-family home prices across nine U.S. Census divisions. - Indices for 20 Metropolitan Regions: Regional indices that highlight housing price trends in major U.S. cities.
The index uses a "repeat sales" approach, which tracks properties that have been sold at least twice to capture changes in their value over time. This method minimizes biases from changes in housing stock or individual property characteristics. The index originated in the 1980s through the work of Karl E. Case and Robert J. Shiller, pioneers in developing the repeat sales technique. It remains one of the most trusted tools for measuring U.S. housing market trends.
The indices are used widely by policymakers, economists, and analysts to gauge housing market conditions and make informed decisions.
This dataset can be used for: - Housing Market Analysis: Track trends in national and metropolitan housing prices. - Econometric Modeling: Analyze the relationship between housing prices and macroeconomic factors. - Forecasting: Build models to predict future housing market movements.
Data sourced from: https://github.com/datasets/house-prices-us Original source: https://datahub.io/core/house-prices-us