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The Role of Real Estate Uncertainty in Predicting US Home Sales Growth: Evidence from a Quantiles-Based Bayesian Model Averaging Approach

Author

Listed:
  • Oguzhan Cepni

    (Central Bank of the Republic of Turkey, Haci Bayram Mah. Istiklal Cad. No: 10, 06050, Ankara, Turkey)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, South Africa)

  • Mark E. Wohar

    (College of Business Administration, University of Nebraska at Omaha, 6708 Pine Street, Omaha, NE 68182, USA, and School of Business and Economics, Loughborough University, Leicestershire, LE11 3TU, UK.)

Abstract
This paper investigates the role of real estate-specific uncertainty in predicting the conditional distribution of US home sales growth over the monthly period of 1970:07 to 2017:12, based on Bayesian Model Averaging (BMA) to account for model uncertainty. After controlling for standard predictors of home sales (housing price, mortgage rate, personal disposable income, unemployment rate, building permits, and housing starts), and macroeconomic and financial uncertainties, our results from the quantile BMA (QBMA) model show that real estate uncertainty has predictive content for the lower and upper quantiles of the conditional distribution of home sales growth.

Suggested Citation

  • Oguzhan Cepni & Rangan Gupta & Mark E. Wohar, 2019. "The Role of Real Estate Uncertainty in Predicting US Home Sales Growth: Evidence from a Quantiles-Based Bayesian Model Averaging Approach," Working Papers 201936, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201936
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    References listed on IDEAS

    as
    1. Edward E. Leamer, 2007. "Housing is the business cycle," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 149-233.
    2. Dua, Pami & Miller, Stephen M & Smyth, David J, 1999. "Using Leading Indicators to Forecast U.S. Home Sales in a Bayesian Vector Autoregressive Framework," The Journal of Real Estate Finance and Economics, Springer, vol. 18(2), pages 191-205, March.
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    6. Edward E. Leamer, 2015. "Housing Really Is the Business Cycle: What Survives the Lessons of 2008–09?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(S1), pages 43-50, March.
    7. Han, Heejoon & Linton, Oliver & Oka, Tatsushi & Whang, Yoon-Jae, 2016. "The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series," Journal of Econometrics, Elsevier, vol. 193(1), pages 251-270.
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    10. Korobilis, Dimitris, 2017. "Quantile regression forecasts of inflation under model uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 11-20.
    11. Hossein Hassani & Zara Ghodsi & Rangan Gupta & Mawuli Segnon, 2017. "Forecasting Home Sales in the Four Census Regions and the Aggregate US Economy Using Singular Spectrum Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 83-97, January.
    12. Chuliá, Helena & Gupta, Rangan & Uribe, Jorge M. & Wohar, Mark E., 2017. "Impact of US uncertainties on emerging and mature markets: Evidence from a quantile-vector autoregressive approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 178-191.
    13. Johannes Strobel & Binh Nguyen Thanh & Gabriel Lee, 2020. "Effects of Macroeconomic Uncertainty and Labor Demand Shocks on the Housing Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 48(2), pages 345-372, June.
    14. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    15. Hamid Baghestani & Ilker Kaya, 2016. "Do financial indicators have directional predictability for US home sales?," Applied Economics, Taylor & Francis Journals, vol. 48(15), pages 1349-1360, March.
    16. Binh Nguyen Thanh & Johannes Strobel & Gabriel Lee, 2020. "A New Measure of Real Estate Uncertainty Shocks," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 48(3), pages 744-771, September.
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    18. Valencia, Fabián, 2017. "Aggregate uncertainty and the supply of credit," Journal of Banking & Finance, Elsevier, vol. 81(C), pages 150-165.
    19. Dua, Pami & Miller, Stephen M, 1996. "Forecasting Connecticut Home Sales in a BVAR Framework Using Coincident and Leading Indexes," The Journal of Real Estate Finance and Economics, Springer, vol. 13(3), pages 219-235, November.
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    Cited by:

    1. Stolbov, Mikhail & Shchepeleva, Maria, 2022. "Modeling global real economic activity: Evidence from variable selection across quantiles," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    2. Baek, Ingul & Liu, Jia & Noh, Sanha, 2024. "Real estate uncertainty and financial conditions over the business cycle," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 656-675.

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    More about this item

    Keywords

    Home Sales; Real Estate Uncertainty; Quantile Regression; Bayesian Model Averaging;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • 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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