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Time-varying spillovers between housing sentiment and housing market in the United States☆

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  • André, Christophe
  • Gabauer, David
  • Gupta, Rangan

Abstract

This paper investigates spillovers between the housing sentiment index of Bork et al.(2020), common factors in US real housing returns and their volatility, GDP growth and real interest rates. We find that in contrast to spillovers from the common factor of housing returns to housing sentiment and GDP, reverse spillovers are relatively weak. This suggests that, while a shock to housing prices is likely to have a significant impact on housing sentiment and the economy, a purely exogenous shock to housing sentiment may in itself have little impact on housing returns and volatility.

Suggested Citation

  • André, Christophe & Gabauer, David & Gupta, Rangan, 2021. "Time-varying spillovers between housing sentiment and housing market in the United States☆," Finance Research Letters, Elsevier, vol. 42(C).
  • Handle: RePEc:eee:finlet:v:42:y:2021:i:c:s1544612321000064
    DOI: 10.1016/j.frl.2021.101925
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    1. 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.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Charles P. Kindleberger & Robert Z. Aliber, 2005. "Manias, Panics and Crashes," Palgrave Macmillan Books, Palgrave Macmillan, edition 0, number 978-0-230-62804-5, October.
    4. Antonakakis, Nikolaos & Floros, Christos, 2016. "Dynamic interdependencies among the housing market, stock market, policy uncertainty and the macroeconomy in the United Kingdom," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 111-122.
    5. Robert J Shiller, 2008. "Historic Turning Points in Real Estate," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 34(1), pages 1-13, Winter.
    6. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan & Plakandaras, Vasilios, 2018. "Dynamic connectedness of uncertainty across developed economies: A time-varying approach," Economics Letters, Elsevier, vol. 166(C), pages 63-75.
    7. Jing Cynthia Wu & Fan Dora Xia, 2016. "Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(2-3), pages 253-291, March.
    8. Lambertini, Luisa & Mendicino, Caterina & Punzi, Maria Teresa, 2013. "Expectation-driven cycles in the housing market: Evidence from survey data," Journal of Financial Stability, Elsevier, vol. 9(4), pages 518-529.
    9. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    10. Gupta, Rangan & Ma, Jun & Theodoridis, Konstantinos & Wohar, Mark E., 2023. "Is there a national housing market bubble brewing in the United States?," Macroeconomic Dynamics, Cambridge University Press, vol. 27(8), pages 2191-2228, December.
    11. repec:wly:soecon:v:83:2:y:2016:p:609-624 is not listed on IDEAS
    12. Lasse Bork & Stig V. Møller & Thomas Q. Pedersen, 2020. "A New Index of Housing Sentiment," Management Science, INFORMS, vol. 66(4), pages 1563-1583, April.
    13. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    14. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    15. Marco Del Negro & Christopher Otrok, 2008. "Dynamic factor models with time-varying parameters: measuring changes in international business cycles," Staff Reports 326, Federal Reserve Bank of New York.
    16. David C. Ling & Joseph T.L. Ooi & Thao T.T. Le, 2015. "Explaining House Price Dynamics: Isolating the Role of Nonfundamentals," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(S1), pages 87-125, March.
    17. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    18. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    19. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    20. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    21. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    22. Gabauer, David & Gupta, Rangan, 2018. "On the transmission mechanism of country-specific and international economic uncertainty spillovers: Evidence from a TVP-VAR connectedness decomposition approach," Economics Letters, Elsevier, vol. 171(C), pages 63-71.
    23. Tihana Škrinjarić & Zrinka Lovretin Golubić & Zrinka Orlović, 2020. "Empirical analysis of dynamic spillovers between exchange rate return, return volatility and investor sentiment," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 38(1), pages 86-113, December.
    24. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    25. Marco Del Negro & Giorgio E. Primiceri, 2015. "Time Varying Structural Vector Autoregressions and Monetary Policy: A Corrigendum," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1342-1345.
    26. 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.
    27. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    28. Neely, Christopher J. & Rapach, David E., 2011. "International comovements in inflation rates and country characteristics," Journal of International Money and Finance, Elsevier, vol. 30(7), pages 1471-1490.
    29. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    30. Bhatt, Vipul & Kishor, N Kundan & Ma, Jun, 2017. "The impact of EMU on bond yield convergence: Evidence from a time-varying dynamic factor model," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 206-222.
    31. Thomas J. Fisher & Colin M. Gallagher, 2012. "New Weighted Portmanteau Statistics for Time Series Goodness of Fit Testing," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 777-787, June.
    32. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
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    More about this item

    Keywords

    Common housing market movements; Sentiment; Time-varying spillovers;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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