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A New Index of Housing Sentiment

Author

Listed:
  • Lasse Bork

    (Aalborg University)

  • Stig V. Møller

    (Aarhus University and CREATES)

  • Thomas Q. Pedersen

    (Aarhus University and CREATES)

Abstract

We propose a new measure for housing sentiment and show that it accurately tracks expectations about future house price growth rates. We construct the housing sentiment index using partial least squares on household survey responses to questions about buying conditions for houses. We ?find that housing sentiment explains a large share of the time-variation in house prices during both boom and bust cycles and it strongly outperforms several macroeconomic variables typically used to forecast house prices.

Suggested Citation

  • Lasse Bork & Stig V. Møller & Thomas Q. Pedersen, 2016. "A New Index of Housing Sentiment," CREATES Research Papers 2016-32, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2016-32
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    References listed on IDEAS

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    1. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    4. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    5. Luis Armona & Andreas Fuster & Basit Zafar, 2019. "Home Price Expectations and Behaviour: Evidence from a Randomized Information Experiment," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(4), pages 1371-1410.
    6. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    7. Yuliya Demyanyk & Otto Van Hemert, 2011. "Understanding the Subprime Mortgage Crisis," The Review of Financial Studies, Society for Financial Studies, vol. 24(6), pages 1848-1880.
    8. Cindy K Soo, 2018. "Quantifying Sentiment with News Media across Local Housing Markets," The Review of Financial Studies, Society for Financial Studies, vol. 31(10), pages 3689-3719.
    9. Hernández-Murillo, Rubén & Owyang, Michael T. & Rubio, Margarita, 2017. "Clustered housing cycles," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 185-197.
    10. Robert J. Shiller, 2007. "Understanding recent trends in house prices and homeownership," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 89-123.
    11. Markus K. Brunnermeier & Christian Julliard, 2008. "Money Illusion and Housing Frenzies," The Review of Financial Studies, Society for Financial Studies, vol. 21(1), pages 135-180, January.
    12. Sydney C. Ludvigson, 2004. "Consumer Confidence and Consumer Spending," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 29-50, Spring.
    13. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    14. Glaeser, Edward L. & Nathanson, Charles G., 2017. "An extrapolative model of house price dynamics," Journal of Financial Economics, Elsevier, vol. 126(1), pages 147-170.
    15. Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, vol. 146(2), pages 304-317, October.
    16. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    17. John B. Taylor, 2014. "Causes of the Financial Crisis and the Slow Recovery: A Ten-Year Perspective," Book Chapters, in: Martin Neil Baily & John B. Taylor (ed.), Across the Great Divide: New Perspectives on the Financial Crisis, chapter 3, Hoover Institution, Stanford University.
    18. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
    19. Shen, Junyan & Yu, Jianfeng & Zhao, Shen, 2017. "Investor sentiment and economic forces," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 1-21.
    20. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
    21. Carroll, Christopher D & Fuhrer, Jeffrey C & Wilcox, David W, 1994. "Does Consumer Sentiment Forecast Household Spending? If So, Why?," American Economic Review, American Economic Association, vol. 84(5), pages 1397-1408, December.
    22. Robert J. Shiller, 2007. "Understanding recent trends in house prices and homeownership," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 89-123.
    23. Monika Piazzesi & Martin Schneider, 2009. "Momentum Traders in the Housing Market: Survey Evidence and a Search Model," American Economic Review, American Economic Association, vol. 99(2), pages 406-411, May.
    24. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    25. Bauer, Gregory H., 2017. "International house price cycles, monetary policy and credit," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 88-114.
    26. Bryan Kelly & Seth Pruitt, 2013. "Market Expectations in the Cross-Section of Present Values," Journal of Finance, American Finance Association, vol. 68(5), pages 1721-1756, October.
    27. Bork, Lasse & Møller, Stig V., 2015. "Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection," International Journal of Forecasting, Elsevier, vol. 31(1), pages 63-78.
    28. Case, Karl E. & Quigley, John M. & Shiller, Robert J., 2013. "Wealth Effects Revisited 1975-2012," Critical Finance Review, now publishers, vol. 2(1), pages 101-128, July.
    29. Del Negro, Marco & Otrok, Christopher, 2007. "99 Luftballons: Monetary policy and the house price boom across U.S. states," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 1962-1985, October.
    30. Hai Lin & Chunchi Wu & Guofu Zhou, 2018. "Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach," Management Science, INFORMS, vol. 64(9), pages 4218-4238, September.
    31. Ghysels, Eric & Plazzi, Alberto & Valkanov, Rossen & Torous, Walter, 2013. "Forecasting Real Estate Prices," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 509-580, Elsevier.
    32. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    33. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 671-690.
    34. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    35. Tyler H. McCormick & Adrian E. Raftery & David Madigan & Randall S. Burd, 2012. "Dynamic Logistic Regression and Dynamic Model Averaging for Binary Classification," Biometrics, The International Biometric Society, vol. 68(1), pages 23-30, March.
    36. Baker, Malcolm & Wurgler, Jeffrey & Yuan, Yu, 2012. "Global, local, and contagious investor sentiment," Journal of Financial Economics, Elsevier, vol. 104(2), pages 272-287.
    37. Rapach, David E. & Strauss, Jack K., 2009. "Differences in housing price forecastability across US states," International Journal of Forecasting, Elsevier, vol. 25(2), pages 351-372.
    38. Atif Mian & Amir Sufi, 2009. "The Consequences of Mortgage Credit Expansion: Evidence from the U.S. Mortgage Default Crisis," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(4), pages 1449-1496.
    39. Kelly, Bryan & Pruitt, Seth, 2015. "The three-pass regression filter: A new approach to forecasting using many predictors," Journal of Econometrics, Elsevier, vol. 186(2), pages 294-316.
    40. Michael Lemmon & Evgenia Portniaguina, 2006. "Consumer Confidence and Asset Prices: Some Empirical Evidence," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1499-1529.
    41. Nelson, Charles R & Kim, Myung J, 1993. "Predictable Stock Returns: The Role of Small Sample Bias," Journal of Finance, American Finance Association, vol. 48(2), pages 641-661, June.
    42. Martin Neil Baily & John B. Taylor (ed.), 2014. "Across the Great Divide: New Perspectives on the Financial Crisis," Books, Hoover Institution, Stanford University, number 8, July.
    43. John Taylor, 2014. "Causes of the Financial Crisis and the Slow Recovery: A 10-Year Perspective," Discussion Papers 13-026, Stanford Institute for Economic Policy Research.
    44. Martin Schneider & Monika Piazzesi, 2009. "Momentum traders in a search model of the housing market," 2009 Meeting Papers 1266, Society for Economic Dynamics.
    45. Yu, Jianfeng & Yuan, Yu, 2011. "Investor sentiment and the mean-variance relation," Journal of Financial Economics, Elsevier, vol. 100(2), pages 367-381, May.
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    More about this item

    Keywords

    Housing sentiment; house price forecastability; partial least squares; dynamic model averaging;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • G1 - Financial Economics - - General Financial Markets

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