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A hierarchical factor analysis of U.S. housing market dynamics

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  • Emanuel Moench
  • Serena Ng

Abstract

This paper studies the linkages between housing and consumption in the United States taking into account regional variation. We estimate national and regional housing factors from a comprehensive set of U.S. price and quantity data available at mixed frequencies and over different time spans. Our housing factors pick up the common components in the data and are less affected by the idiosyncratic noise in individual series. This allows us to get more reliable estimates of the consumption effects of housing market shocks. We find that shocks at the national level have large cumulative effects on retail sales in all regions. Though the effects of regional shocks are smaller, they are also significant. We analyse the driving forces of housing market activity by means of factor‐augmented vector autoregressions. Our results show that lowering mortgage rates has a larger effect than a similar reduction of the federal funds rate. Moreover, lower consumer confidence and stock prices can slow the recovery in the housing market.
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Suggested Citation

  • Emanuel Moench & Serena Ng, 2011. "A hierarchical factor analysis of U.S. housing market dynamics," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 1-24, February.
  • Handle: RePEc:ect:emjrnl:v:14:y:2011:i:1:p:c1-c24
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    File URL: http://hdl.handle.net/10.1111/j.1368-423X.2010.00319.x
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    Cited by:

    1. Hideaki Hirata & M. Ayhan Kose & Christopher Otrok & Marco E Terrones, 2013. "Global House Price Fluctuations: Synchronization and Determinants," NBER International Seminar on Macroeconomics, University of Chicago Press, vol. 9(1), pages 119-166.
    2. Matteo Luciani, 2015. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 199-218, March.
    3. Hernández-Murillo, Rubén & Owyang, Michael T. & Rubio, Margarita, 2017. "Clustered housing cycles," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 185-197.
    4. Valadkhani, Abbas, 2014. "Analysing interest rate mark-ups in the Australian mortgage market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 343-361.
    5. Forni, Mario & Giovannelli, Alessandro & Lippi, Marco & Soccorsi, Stefano, 2016. "Dynamic Factor model with infinite dimensional factor space: forecasting," CEPR Discussion Papers 11161, C.E.P.R. Discussion Papers.
    6. Frisancho Veronica, 2012. "Signaling Creditworthiness in Peruvian Microfinance Markets: The Role of Information Sharing," The B.E. Journal of Economic Analysis & Policy, De Gruyter, pages 1-43.
    7. Förster, Marcel & Jorra, Markus & Tillmann, Peter, 2014. "The dynamics of international capital flows: Results from a dynamic hierarchical factor model," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 101-124.
    8. Funke, Michael & Leiva-Leon, Danilo & Tsang, Andrew, 2017. "Mapping China’s time-varying house price landscape," BOFIT Discussion Papers 21/2017, Bank of Finland, Institute for Economies in Transition.
    9. Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," Discussion Papers of DIW Berlin 1351, DIW Berlin, German Institute for Economic Research.
    10. Michel van der Wel & Sait R. Ozturk & Dick van Dijk, 2016. "Dynamic Factor Models for the Volatility Surface," Advances in Econometrics,in: Dynamic Factor Models, volume 35, pages 127-174 Emerald Publishing Ltd.
    11. Luciani, Matteo, 2014. "Forecasting with approximate dynamic factor models: The role of non-pervasive shocks," International Journal of Forecasting, Elsevier, vol. 30(1), pages 20-29.
    12. repec:eee:reveco:v:55:y:2018:i:c:p:145-172 is not listed on IDEAS
    13. Cesa-Bianchi, Ambrogio, 2013. "Housing cycles and macroeconomic fluctuations: A global perspective," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 215-238.
    14. Sylvie Tchumtchoua & Dipak Dey, 2012. "Modeling Associations Among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach," Psychometrika, Springer;The Psychometric Society, vol. 77(4), pages 670-692, October.
    15. Leiva-Leon Danilo, 2014. "Real vs. nominal cycles: a multistate Markov-switching bi-factor approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(5), pages 1-24, December.
    16. Kirstin Hubrich, 2012. "Comment on "Global House Price Fluctuations: Synchronization and Determinants"," NBER Chapters,in: NBER International Seminar on Macroeconomics 2012, pages 167-173 National Bureau of Economic Research, Inc.
    17. repec:eee:reveco:v:53:y:2018:i:c:p:25-38 is not listed on IDEAS
    18. Heaton, Chris & Solo, Victor, 2012. "Estimation of high-dimensional linear factor models with grouped variables," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 348-367.
    19. Marcel Förster & Peter Tillmann, 2013. "Local Inflation: Reconsidering the International Comovement of Inflation," MAGKS Papers on Economics 201303, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    20. Olfa Kaabia & Ilyes Abid, 2012. "Theoretical Channels of International,Transmission During the Subprime Crisis to OCDE Countries : A FAVAR Model Under Bayesian Framework," EconomiX Working Papers 2012-40, University of Paris Nanterre, EconomiX.
    21. Marcel Förster & Peter Tillmann, 2014. "Reconsidering the International Comovement of Inflation," Open Economies Review, Springer, vol. 25(5), pages 841-863, November.
    22. MeiChi Huang, 2014. "Monetary policy implications of housing shift-contagion across regional markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(4), pages 589-608, October.

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