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House Price Synchronization across the US States: The Role of Structural Oil Shocks

Author

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  • Xin Sheng

    (Lord Ashcroft International Business School, Anglia Ruskin University, Chelmsford, CM1 1SQ, United Kingdom)

  • Hardik A. Marfatia

    (Department of Economics, Northeastern Illinois University, 5500 N St Louis Ave, BBH 344G, Chicago, IL 60625, USA)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Qiang Ji

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing, China; School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing, China)

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

  • Xin Sheng & Hardik A. Marfatia & Rangan Gupta & Qiang Ji, 2020. "House Price Synchronization across the US States: The Role of Structural Oil Shocks," Working Papers 202076, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202076
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    2. 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.
    3. Mohsen Bahmani-Oskooee & Hesam Ghodsi & Muris Hadzic, 2021. "On the Link between House Prices and House Permits: Asymmetric Evidence from 51 States of the United States of America," International Real Estate Review, Global Social Science Institute, vol. 24(3), pages 323-361.
    4. Sheng, Xin & Kim, Won Joong & Gupta, Rangan & Ji, Qiang, 2023. "The impacts of oil price volatility on financial stress: Is the COVID-19 period different?," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 520-532.
    5. 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.
    6. 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.
    7. 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).
    8. Sheng, Xin & Marfatia, Hardik A. & Gupta, Rangan & Ji, Qiang, 2023. "The non-linear response of US state-level tradable and non-tradable inflation to oil shocks: The role of oil-dependence," Research in International Business and Finance, Elsevier, vol. 64(C).
    9. 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.
    10. 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.
    11. 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.
    12. Stenvall, David & Hedström, Axel & Yoshino, Naoyuki & Uddin, Gazi Salah & Taghizadeh-Hesary, Farhad, 2022. "Nonlinear tail dependence between the housing and energy markets," Energy Economics, Elsevier, vol. 106(C).

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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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