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Forecasting house price inflation: a model combination approach

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In this paper we use a range of statistical models to forecast New Zealand house price in ation. We address the issue of model uncertainty by combining forecasts using weights based on out-of-sample forecast performance. We consider how the combined forecast for house prices performs relative to both the individual model forecasts and the Reserve Bank of New Zealand's house price forecasts. We find that the combination forecast is on par with the best of the models for most forecast horizons, and has produced lower root mean squared forecast errors than the Reserve Bank's forecasts.

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  • Sarah Drought & Chris McDonald, 2011. "Forecasting house price inflation: a model combination approach," Reserve Bank of New Zealand Discussion Paper Series DP2011/07, Reserve Bank of New Zealand.
  • Handle: RePEc:nzb:nzbdps:2011/07
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    1. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    2. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2012. "Does Forecast Combination Improve Norges Bank Inflation Forecasts?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 163-179, April.
    3. Chris McDonald & Leif Anders Thorsrud, 2011. "Evaluating density forecasts: model combination strategies versus the RBNZ," Reserve Bank of New Zealand Discussion Paper Series DP2011/03, Reserve Bank of New Zealand.
    4. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    5. Das, Sonali & Gupta, Rangan & Kabundi, Alain, 2009. "Could we have predicted the recent downturn in the South African housing market?," Journal of Housing Economics, Elsevier, vol. 18(4), pages 325-335, December.
    6. Nikola Dvornak & Marion Kohler, 2007. "Housing Wealth, Stock Market Wealth and Consumption: A Panel Analysis for Australia," The Economic Record, The Economic Society of Australia, vol. 83(261), pages 117-130, June.
    7. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    8. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    9. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    10. Chris McDonald & Mark Smith, 2009. "Developing stratified housing price measures for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2009/07, Reserve Bank of New Zealand.
    11. John N. Muellbauer, 2007. "Housing, credit and consumer expenditure," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 267-334.
    12. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    13. Emmanuel De Veirman & Ashley Dunstan, 2008. "How do Housing Wealth, Financial Wealth and Consumption Interact? Evidence from New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2008/05, Reserve Bank of New Zealand.
    14. Leslie Hull, 2003. "Financial deregulation and household indebtedness," Reserve Bank of New Zealand Discussion Paper Series DP2003/01, Reserve Bank of New Zealand.
    15. Brendan O'Donovan & David Rae, 1997. "The determinants of house prices in New Zealand: An aggregate and regional analysis," New Zealand Economic Papers, Taylor & Francis Journals, vol. 31(2), pages 175-198.
    16. Chris Bloor & Troy Matheson, 2010. "Analysing shock transmission in a data-rich environment: a large BVAR for New Zealand," Empirical Economics, Springer, vol. 39(2), pages 537-558, October.
    17. Matteo Iacoviello & Stefano Neri, 2010. "Housing Market Spillovers: Evidence from an Estimated DSGE Model," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(2), pages 125-164, April.
    18. Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Using Large Data Sets to Forecast Housing Prices: A Case Study of Twenty US States," Working Papers 200912, University of Pretoria, Department of Economics.
    19. Andrew Coleman & John Landon-Lane, 2007. "Housing Markets and Migration in New Zealand, 1962-2006," Reserve Bank of New Zealand Discussion Paper Series DP2007/12, Reserve Bank of New Zealand.
    20. Patricia Fraser & Martin Hoesli & Lynn McAlevey, 2008. "House Prices and Bubbles in New Zealand," The Journal of Real Estate Finance and Economics, Springer, vol. 37(1), pages 71-91, July.
    21. International Monetary Fund, 2003. "United Kingdom: Selected Issues," IMF Staff Country Reports 2003/047, International Monetary Fund.
    22. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    23. Peter Abelson & Roselyne Joyeux & George Milunovich & Demi Chung, 2005. "Explaining House Prices in Australia: 1970–2003," The Economic Record, The Economic Society of Australia, vol. 81(s1), pages 96-103, August.
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    2. Maryam Akbari Nasiri, 2020. "How Long Do Housing Cycles Last? A Duration Analysis For Emerging Economies," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 23(2), pages 179-200, July.
    3. Laurynas Narusevicius & Tomas Ramanauskas & Laura Gudauskaitė & Tomas Reichenbachas, 2019. "Lithuanian house price index: modelling and forecasting," Bank of Lithuania Occasional Paper Series 28, Bank of Lithuania.
    4. Jose Torres-Pruñonosa & Pablo García-Estévez & Josep Maria Raya & Camilo Prado-Román, 2022. "How on Earth Did Spanish Banking Sell the Housing Stock?," SAGE Open, , vol. 12(1), pages 21582440221, March.
    5. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
    6. Arvydas Jadevicius & Brian Sloan & Andrew Brown, 2012. "Examination of property forecasting models - accuracy and its improvement through combination forecasting," ERES eres2012_082, European Real Estate Society (ERES).

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    More about this item

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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