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Globalization & Monetary Policy Institute

International House Price Database

  • About the Database
  • Release Dates
  • Data
  • Charts
  • Related Reading
  • Partners
  • External Data Sources

About the International House Price Database

Access to international house price data with ample geographic and temporal coverage facilitates the work of researchers, scholars and policymakers interested in the study of housing through cross-country comparison and time series analysis. To promote this research further and enhance our understanding of the international dimensions of housing, the Globalization and Monetary Policy Institute of the Federal Reserve Bank of Dallas makes available its own international house price database.

The dataset uses publicly available, national sources and includes quarterly data on nominal and real house prices—complemented with household personal disposable income (PDI)—starting in the first quarter 1975. Currently, the dataset incorporates complete house price and PDI series covering 22 (mostly advanced) countries. We select a representative house price index for each country that is most consistent—in terms of units measured and methods applied—with the Federal Housing Finance Agency (FHFA) quarterly nationwide house price index for existing single-family houses in the U.S., which we take as our series of reference. However, given the heterogeneity of the existing sources across countries, some departures in measurement or methodological concepts are unavoidable.

On a case-by-case basis, we extend the preferred series for each country back to first quarter 1975—matching the FHFA house price index sample coverage—with available historical data or secondary sources of similar characteristics. Each country’s house price index is seasonally adjusted with our own unobserved components time series model for seasonal adjustment method over the entire sample period and then rebased to 2005 = 100. Each house price index is expressed in nominal terms, but it is also presented in real terms, taking the ratio of the nominal price index with the personal consumption expenditure (PCE) deflator of the corresponding country at the same base year. PDIs are always quoted in per capita terms using working-age population and are similarly expressed in real terms with the PCE deflator. We aggregate all countries in the database, weighted by their purchasing power parity-adjusted GDP shares in 2005, to compute an average (nominal and real) house price series and an average (nominal and real) per capita PDI series.

A brief overview of the sources and the methodology applied for selecting and homogenizing the data for comparability purposes can be found in Mack, Adrienne, and Enrique Martínez-García (2011), “A Cross-Country Quarterly Database of Real House Prices: A Methodological Note.”PDF Globalization and Monetary Policy Institute Working Paper no. 99 (Federal Reserve Bank of Dallas, December). The country sources and any relevant disclaimers are documented and regularly updated in Mack and Martínez-García (2011). We would appreciate that anyone wishing to use this dataset, modified or otherwise, in published work acknowledges the source of the data with a citation of the working paper and this webpage: for example, including a statement such as: “The authors acknowledge use of the dataset described in Mack and Martínez-García (2011).”

Announcements

  • In partnership with researchers from Lancaster University, we are now disseminating novel statistical indicators implemented with the international house price database in order to detect non-fundamental (or explosive) behavior in real house prices and house-price-to-income data. These indicators are currently available in our webpage starting with the second quarter of 2013 release for the three major economies affected by the last boom-bust episode in housing markets: the United States, the United Kingdom and Spain. The following slideshow presentation recorded in Dallas on November 15, 2013, provides some illustration, summarizes the technical details of the procedure and discusses the interpretation of the statistics.
  • Presentation of Monitoring Housing Markets for Episodes of Exuberance - An Application of the Phillips et al. (2013) GSADF Test on the Dallas Fed International House Price DatabasePowerpoint by Efthymios Pavlidis, Lancaster University and Enrique Martínez-García, Federal Reserve Bank of Dallas on November 15, 2013

Release Dates

The international house price dataset is updated on a quarterly basis. As a practical compromise between the timeliness of the release and the extent of country coverage, we schedule the posting of the international house price dataset during four fixed periods with a three-month lag to ensure that there will be a "sufficient" number of new country observations in each new quarterly release. Whenever observations are missing for these countries and series, we complete them with our own forecasts. Those forecasts would be replaced in subsequent revisions as the corresponding quarterly observations become available.

2013–14 Release Dates

Last Quarter Included

Release Date

Fourth quarter 2012

First week of April 2013

First quarter 2013

First week of July 2013

Second quarter 2013

First week of October 2013

Third quarter 2013

First week of January 2014

Fourth quarter 2013

First week of April 2014

First quarter 2014

First week of July 2014

Second quarter 2014

First week of October 2014

Third quarter 2014

First week of January 2015

We will apply the same schedule for data releases every year, unless a change in the lag with which country data becomes available requires us to adjust the timing of our quarterly releases accordingly to preserve the wide geographic coverage of the panel.

Download the Data

2013

  • Third Quarter 2013Excel | Exuberance IndicatorsExcel
    NOTE: The HPI index for Ireland has been revised. This will affect the nominal and real HPI series for the 2013Q3 release and all subsequent data releases. Starting in 2005 the series incorporates the hedonic price index produced by the National Statistics office, which better reflects underlying changes in house prices.
  • Second Quarter 2013Excel | Exuberance IndicatorsExcel
    NOTE:
    Several changes have occurred with the 2013Q2 release. Croatia is now included in the database and has been incorporated in the aggregate indexes. The PDI series for Croatia is proxied with available household income produced by the Croatian Bureau of Statistics, which measures household earnings plus benefits less taxes. This series is extended using monthly earnings—also produced by the Croatian Bureau of Statistics. The HPI series is constructed using current data from the Croatian Central Bank. The index is constructed using the Hedonic method and includes prices for all types of dwellings. This is extended using a price series from the Croatian Bureau of Statistics, which includes only new dwellings. PDI data for Luxembourg is now available from 2006-2011, so it resulted in a substantial revision of our previous estimates of the series since 2007.
    The RHPI and RPDI series for Croatia were revised on 10/15/2013 to correct an error in the PCE deflator data. This modification also affects the corresponding aggregate series.
  • First Quarter 2013Excel
    NOTE:
    Several changes have occurred with the 2013Q1 release, which will affect all subsequent releases: The Canadian house price index has been changed. An alternative source is used to obtain house prices from 2010 Q1 onwards due to a lapse in current data from the previous source. Also, the national index is now calculated as a weighted average of the 10 metropolitan areas of Canada, over the entire period using fixed population shares from the 2011 Census. The historical house price series for Italy between 1975 and 1987 has been revised. The national aggregate now represents a weighted average of the 13 metropolitan areas, pre-1987, using fixed population shares from the 1982 Census. Also, interpolation to a quarterly frequency is done by steps as series are spliced together at the higher frequency. The PDI series for New Zealand has been revised given that now we have personal disposable income data reported at quarterly frequency starting in 1998Q4. The PDI series for South Africa has been revised given that now we have working age population reported at quarterly frequency starting in 2008Q1. The PDI series for Luxembourg has been revised as well. An upward revision for Luxembourg’s Net National Disposable Income has produced a significant shift in the PDI per capita series starting in 2010.

2012

  • Fourth Quarter 2012Excel
  • Third Quarter 2012Excel
    NOTE: Two changes have occurred with the 2012:Q3 release, which will affect all subsequent releases: First, to control for seasonality and excess volatility in some of the PDI series, we now estimate the series with a structural time series model in state-space form. This model allows us to identify and systematically extract the seasonal and excessively volatile components of the data. Second, in cases where national data is not available at the scheduled time of our release, we now provided forecast estimates.
  • Second Quarter 2012Excel
  • First Quarter 2012Excel
    NOTE:
    Several changes have occurred with the 2012:Q1 data release and will affect all subsequent releases. We no longer rely on the OECD Outlook database for current personal disposable income data, but have reconstructed most series using data from national sources and Eurostat. Luxembourg and South Africa are now included in the database. Both countries are included in all four aggregate series. The time coverage of Luxembourg’s disposable income data is limited. Therefore, the personal disposable income series for Luxembourg is inferred through Belgian data. 2012 Q1 and Q2 data have been released concurrently due to the lagged release caused by these data revisions.

2011

  • Fourth Quarter 2011Excel
  • Third Quarter 2011Excel
  • Second Quarter 2011Excel
    NOTE: The second quarter 2011 data has been revised. The nominal personal disposable income data for Canada was not indexed to 2005 = 100 in the original release of the data, which affects both the Canadian series and the OECD-19 aggregate series. Therefore, we offer a revised version, with the Canadian series indexed to 2005 = 100, using the same vintage of data as the original release.

Charts

The following charts provide a snapshot and overview of the real (inflation-adjusted) house price and personal disposable income data from first quarter 1975 to second quarter 2012 for all countries included in the database. The real house price data is the index of the relative price of residential housing over the private consumption expenditures (PCE) deflator. Personal disposable income data is the index of income available to households from all sources (participation in production, assets and current transfer receipts), net of the income taxes paid to the government. These charts include indicators of contraction to show periods of sustained decline in the data, as well as the indexes for real house prices and real personal disposable income in levels and growth rates. The corresponding interquartile range of the growth rates of all countries is added to illustrate the dispersion of the data across countries.

Charts 1A and 1B compare contraction periods of real house prices with downturns in real household disposable income.

NOTE: Colored-bars indicate contraction (peak-to-trough), determined using the Bry and Boschan (1971) classical cycle dating approach implemented in Harding and Pagan (2002). Black indicates contractions of the all-country aggregate, red, the U.S. and blue, all other countries in the database. Restrictions are imposed to avoid spurious cycles, so each phase of expansion and contraction must last at least three quarters for real house prices and two quarters for real personal disposable income.

Charts 2A and 2B plot the index levels of real house prices and real personal disposable income for an aggregate of all countries included in the panel, an aggregate that excludes the U.S. and for the U.S. series itself.

NOTE: Shaded areas indicate contraction (peak-to-trough) of the aggregate real house price index, determined using the Bry and Boschan (1971) classical cycle dating method implemented in Harding and Pagan (2002). Each phase of expansion and contraction must last at least three quarters for real house prices, to avoid spurious cycles.

Charts 3A and 3B plot the year-over-year growth rates of real house prices and real personal disposable income for an aggregate of all countries included in the panel, an aggregate that excludes the U.S. and for the U.S. series itself.

NOTE: Shaded areas indicate contraction (peak-to-trough) of the aggregate real house price index, determined using the Bry and Boschan (1971) classical cycle dating method implemented in Harding and Pagan (2002). Phases of expansion and contraction must last at least three quarters for real house prices, to avoid spurious cycles. The interquartile range refers to the difference between the upper and lower quartiles (the highest and lowest 25 percent) of the growth rates across all countries.

References

Bry, Gerhard and Charlotte Boschan (1971): "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs." Technical Paper 20 (New York, N.Y., National Bureau of Economic Research); Harding, Don and Adrian Pagan (2002): "Dissecting the Cycle: A Methodological Investigation." Journal of Monetary Economics 49 (2): 365–81.

Related Reading

Partners

The Federal Reserve Bank of Dallas’ Globalization and Monetary Policy Institute through its international house price database initiative maintains contacts and close ties with a number of highly-respected scholars and foreign institutions with whom we have partnered to research specific country sources and datasets. Cooperation is important for the development and extension of the database, although every partner remains solely responsible for its work. We would like to acknowledge contributions by our international partners, listed below:

Contact Information

For any questions, comments or suggestions about the data or the webpage, please contact the authors at:

Enrique Martínez-García: enrique.martinez-garcia@dal.frb.org
Adrienne Mack: adrienne.mack@dal.frb.org
Valerie Grossman: valerie.grossman@dal.frb.org

 

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