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Temporal Causality between House Prices and Output in the U. S.: A Bootstrap Rolling-Window Approach


  • Wendy Nyakabawo

    () (Department of Economics, University of Pretoria)

  • Stephen M. Miller

    () (College of Business, University of Las Vegas, Nevada)

  • Mehmet Balcilar

    () (Department of Economics, Eastern Mediterranean University, Famagusta, North Cyprus,via Mersin 10, Turkey)

  • Sonali Das

    () (CSIR, Pretoria, South Africa)

  • Rangan Gupta

    () (Department of Economics, University of Pretoria)


This paper examines the causal relationships between the real house price index and real GDP per capita in the U.S., using the bootstrap Granger (temporal) non-causality test and a fixed-size rolling-window estimation approach. We use quarterly time-series data on the real house price index and real GDP per capita, covering the period 1963:Q1 to 2012:Q2. The full-sample bootstrap non-Granger causality test result suggests the existence of a unidirectional causality running from the real house price index to real GDP per capita. A wide variety of tests of parameter constancy used to examine the stability of the estimated vector autoregressive (VAR) models indicate short- and long-run instability. This suggests that we cannot rely on the full-sample causality tests and, hence, this warrants a time-varying (bootstrap) rolling-window approach to examine the causal relationship between these two variables. Using a rolling window size of 28 quarters, we find that while causality from the real house price to real GDP per capita occurs frequently, significant, but less frequent, evidence of real GDP per capita causing the real house price also occurs. These results imply that while the real house price leads real GDP per capita, in general (both during expansions and recessions), significant feedbacks also exist from real GDP per capita to the real house price.

Suggested Citation

  • Wendy Nyakabawo & Stephen M. Miller & Mehmet Balcilar & Sonali Das & Rangan Gupta, 2013. "Temporal Causality between House Prices and Output in the U. S.: A Bootstrap Rolling-Window Approach," Working Papers 201329, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201329

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    Cited by:

    1. Christina Christou & Rangan Gupta & Wendy Nyakabawo & Mark E. Wohar, 2017. "Do House Prices Hedge Inflation in the US? A Quantile Cointegration Approach," Working Papers 201707, University of Pretoria, Department of Economics.
    2. Martin Kalthaus, 2016. "Knowledge recombination along the technology life cycle," Jena Economic Research Papers 2016-012, Friedrich-Schiller-University Jena.
    3. Kirsten Thompson & Renee Van Eyden & Rangan Gupta, 2015. "Identifying an index of financial conditions for South Africa," Studies in Economics and Finance, Emerald Group Publishing, vol. 32(2), pages 256-274, June.
    4. Huseyin Karamelikli, 2016. "Linear and nonlinear dynamics of housing price in Turkey," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 46.
    5. repec:ipg:wpaper:2014-466 is not listed on IDEAS
    6. repec:eee:finlet:v:22:y:2017:i:c:p:227-232 is not listed on IDEAS
    7. repec:rjr:romjef:v::y:2017:i:4:p:152-165 is not listed on IDEAS
    8. Nicholas Apergis & Beatrice D. Simo-Kengne & Rangan Gupta & Tsangyao Chang, 2013. "The Dynamic Relationship between House Prices and Output: Evidence from US Metropolitan Statistical Areas," Working Papers 201349, University of Pretoria, Department of Economics.
    9. Chi-Wei SU & Zong-Liang YAO & Hsu-Ling CHANG, 2016. "The relationship between output and asset prices: A time – and frequency – varying approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(606), S), pages 57-76, Spring.
    10. Christou, Christina & Gupta, Rangan & Hassapis, Christis, 2017. "Does economic policy uncertainty forecast real housing returns in a panel of OECD countries? A Bayesian approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 50-60.
    11. Nikolaos Antonakakis & Rangan Gupta & John W. Muteba Mwamba, 2016. "Dynamic Comovements Between Housing and Oil Markets in the US over 1859 to 2013: a Note," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 44(3), pages 377-386, September.
    12. Sheung-Chi Chow & Juncal Cunado & Rangan Gupta & Wing-Keung Wong, 2016. "Causal Relationships between Economic Policy Uncertainty and Housing Market Returns in China and India: Evidence from Linear and Nonlinear Panel and Time Series Models," Working Papers 201674, University of Pretoria, Department of Economics.
    13. Furkan Emirmahmutoglu & Mehmet Balcilar & Nicholas Apergis & Beatrice D. Simo-Kengne & Tsangyao Chang & Rangan Gupta, 2014. "Causal relationship between asset prices and output in the US: Evidence from state-level panel Granger causality test," Working Papers 201411, University of Pretoria, Department of Economics.
    14. Nikolaos Antonakakis & Mehmet Balcilar & Rangan Gupta & Clement Kyei, 2016. "Components of Economic Policy Uncertainty and Predictability of US Stock Returns and Volatility: Evidence from a Nonparametric Causality-in-Quantile Approach," Working Papers 201639, University of Pretoria, Department of Economics.
    15. repec:ipg:wpaper:2014-476 is not listed on IDEAS
    16. Rangan Gupta & Xiaojin Sun, 2016. "Housing Market Spillovers in South Africa: Evidence from an Estimated Small Open Economy DSGE Model," Working Papers 201641, University of Pretoria, Department of Economics.
    17. 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.
    18. repec:eee:jrpoli:v:53:y:2017:i:c:p:88-102 is not listed on IDEAS
    19. repec:rfe:zbefri:v:34:y:2016:i:2:p:529-554 is not listed on IDEAS

    More about this item


    Real house price; Real GDP per capita; Bootstrap; Time-Varying Causality;

    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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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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