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House price synchronization across the US states: The role of structural oil shocks

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  • Sheng, Xin
  • Marfatia, Hardik A.
  • Gupta, Rangan
  • Ji, Qiang

Abstract

This paper analyzes the impact of disentangled oil shocks on the synchronization in housing price movements across all the US states plus DC. Using a Bayesian dynamic factor model, the house price movements are decomposed into national, regional, and state-specific factors. We then study the impact of oil-specific supply and demand, inventory accumulation, and global demand shocks on the national factor using linear and nonlinear local projection methods. The impulse response analyses suggest that oil-specific supply and consumption demand shocks are most important in driving the national factor. Moreover, as observed from the regime-specific local projection model, these two shocks are found to have a relatively stronger impact in a bearish rather than a bullish national housing market. Our results have important policy implications.

Suggested Citation

  • Sheng, Xin & Marfatia, Hardik A. & Gupta, Rangan & Ji, Qiang, 2021. "House price synchronization across the US states: The role of structural oil shocks," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    • Handle: RePEc:eee:ecofin:v:56:y:2021:i:c:s1062940821000127
    DOI: 10.1016/j.najef.2021.101372
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    Cited by:

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    3. Carolyn Chisadza & Matthew Clance & Xin Sheng & Rangan Gupta, 2023. "Climate Change and Inequality: Evidence from the United States," Sustainability, MDPI, vol. 15(6), pages 1-11, March.
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    5. Zheng Zheng Li & Chi-Wei Su, 2023. "How does real estate market react to the iron ore boom in Australian capital cities?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 71(2), pages 517-537, October.
    6. Oguzhan Cepni & Hardik A. Marfatia & Rangan Gupta, 2021. "The Time-Varying Impact of Uncertainty Shocks on the Comovement of Regional Housing Prices of the United Kingdom," Working Papers 202168, University of Pretoria, Department of Economics.
    7. Gabauer, David & Gupta, Rangan & Marfatia, Hardik A. & Miller, Stephen M., 2024. "Estimating U.S. housing price network connectedness: Evidence from dynamic Elastic Net, Lasso, and ridge vector autoregressive models," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 349-362.
    8. Gupta, Rangan & Sheng, Xin & van Eyden, Reneé & Wohar, Mark E., 2021. "The impact of disaggregated oil shocks on state-level real housing returns of the United States: The role of oil dependence," Finance Research Letters, Elsevier, vol. 43(C).
    9. Hanif, Waqas & Andraz, Jorge Miguel & Gubareva, Mariya & Teplova, Tamara, 2024. "Are REITS hedge or safe haven against oil price fall?," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1-16.
    10. Rangan Gupta & Hardik A. Marfatia & Christian Pierdzioch & Afees A. Salisu, 2022. "Machine Learning Predictions of Housing Market Synchronization across US States: The Role of Uncertainty," The Journal of Real Estate Finance and Economics, Springer, vol. 64(4), pages 523-545, May.
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    12. Nyakundi M. Michieka & Richard S. Gearhart & Noha A. Razek, 2024. "Oil Price Dynamics and Housing Demand in Oil Producing Counties in the U.S," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(2), pages 483-512, June.

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    More about this item

    Keywords

    Bayesian dynamic factor model; Housing market synchronization; Local projection method; Structural oil shocks;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

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