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Spatial effects and house price dynamics in the USA

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  • Cohen, Jeffrey P.
  • Ioannides, Yannis M.
  • (Wirathip) Thanapisitikul, Win

Abstract

While an understanding of spatial spillovers and feedbacks in housing markets could provide valuable information for location decisions, little known research has examined this issue for the US Metropolitan Statistical Areas (MSAs). Also, it is unknown whether there can be differences in the spatial effects before and after a major housing “bust”. In this paper we examine spatial effects in house price dynamics. Using panel data from 363 US MSAs for 1996 to 2013, we find that there are significant spatial diffusion patterns in the growth rates of urban house prices. Lagged price changes of neighboring areas show greater effects after the 2007–08 housing crash than over the entire sample period of 1996–2013. In general, the findings are robust to controlling for potential endogeneity, and for various spatial weights specifications (including contiguity weights and migration flows). These results underscore the importance of considering spatial spillovers in MSA-level studies of housing price growth.

Suggested Citation

  • Cohen, Jeffrey P. & Ioannides, Yannis M. & (Wirathip) Thanapisitikul, Win, 2016. "Spatial effects and house price dynamics in the USA," Journal of Housing Economics, Elsevier, vol. 31(C), pages 1-13.
    • Handle: RePEc:eee:jhouse:v:31:y:2016:i:c:p:1-13
    DOI: 10.1016/j.jhe.2015.10.006
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    6. Gabriel S. Lee & Stefanie Braun, 2021. "Agglomeration Spillover Effects in German Land and House Prices at the City and County Levels," Working Papers 207, Bavarian Graduate Program in Economics (BGPE).
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    8. Huang, Naqun & Yang, Zhenlin, 2021. "Spatial dynamic models with short panels: Evaluating the impact of purchase restrictions on housing prices," Economic Modelling, Elsevier, vol. 103(C).
    9. Tsai, I-Chun, 2022. "Changes in social behavior and impacts of the COVID-19 pandemic on regional housing markets: Independence and risk," Journal of Behavioral and Experimental Finance, Elsevier, vol. 35(C).
    10. Balcilar, Mehmet & Gupta, Rangan & Sousa, Ricardo M. & Wohar, Mark E., 2021. "Linking U.S. State-level housing market returns, and the consumption-(Dis)Aggregate wealth ratio," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 779-810.
    11. Feng Lan & Chengcai Jiao & Guoying Deng & Huili Da, 2021. "Urban agglomeration, housing price, and space–time spillover effect—Empirical evidences based on data from hundreds of cities in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(4), pages 898-919, June.
    12. Pontines, Victor, 2020. "A provincial view of consumption risk sharing in Korea:Asset classes as shock absorbers," Journal of the Japanese and International Economies, Elsevier, vol. 55(C).
    13. Cynthia Fan Yang, 2021. "Common factors and spatial dependence: an application to US house prices," Econometric Reviews, Taylor & Francis Journals, vol. 40(1), pages 14-50, January.
    14. I-Chun Tsai, 2019. "Interregional correlations in the US housing market at three price tiers," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 63(1), pages 1-24, August.
    15. Qing Yao & Yingen Hu, 2023. "Spatial–Temporal Variation and Influencing Factors on Housing Prices of Resource-Based City: A Case Study of Xuzhou, China," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    16. Yunlong Gong & Jan de Haan & Peter Boelhouwer, 2020. "Cross‐city spillovers in Chinese housing markets: From a city network perspective," Papers in Regional Science, Wiley Blackwell, vol. 99(4), pages 1065-1085, August.
    17. Shengfu Yang & Shougeng Hu & Weidong Li & Chuanrong Zhang & José A. Torres, 2017. "Spatiotemporal Effects of Main Impact Factors on Residential Land Price in Major Cities of China," Sustainability, MDPI, vol. 9(11), pages 1-16, November.
    18. Jeffrey P. Cohen & Cletus C. Coughlin & Daniel Soques, 2019. "House Price Growth Interdependencies and Comovement," Working Papers 2019-028, Federal Reserve Bank of St. Louis, revised 11 Jan 2021.
    19. Wenjing Li & John E. Anderson & James R. Schmidt, 2020. "The effect of deed taxes on real estate prices in China," Asia-Pacific Journal of Regional Science, Springer, vol. 4(2), pages 317-341, June.
    20. Yang, Xiaozhong & Zhang, Cheng, 2022. "Spatial investments in the real estate industry: Based on the population flow within the city," Journal of Business Research, Elsevier, vol. 140(C), pages 593-603.

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    More about this item

    Keywords

    Housing price dynamics; Spatial effects; Great Recession of 2007–2009; House price interactions across US MSAs; Geographical proximity effects; Migration flows;
    All these keywords.

    JEL classification:

    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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