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Spatial Effects and House Price Dynamics in the U.S.A

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

Abstract

This paper examines spatial effects in house price dynamics. Using panel data from 363 US Metropolitan Statistical Areas for 1996 to 2013, we find that there are spatial diffusion patterns in the growth rates of urban house prices. Lagged price changes of neighboring areas show greater effects after the 2007-2008 housing crash than over the 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

  • Jeffrey Cohen & Yannis M. Ioannides & Win (Wirathip) Thanapisitikul, 2015. "Spatial Effects and House Price Dynamics in the U.S.A," Discussion Papers Series, Department of Economics, Tufts University 0809, Department of Economics, Tufts University.
    • Handle: RePEc:tuf:tuftec:0809
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    Cited by:

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    2. I-Chun Tsai & Che-Chun Lin, 2019. "Variations and Influences of Connectedness among US Housing Markets," International Real Estate Review, Global Social Science Institute, vol. 22(1), pages 27-58.
    3. Weida Kuang & Qilin Wang, 2018. "Cultural similarities and housing market linkage: evidence from OECD countries," Frontiers of Business Research in China, Springer, vol. 12(1), pages 1-25, December.
    4. Tan, Ronghui & He, Qingsong & Zhou, Kehao & Xie, Peng, 2019. "The effect of new metro stations on local land use and housing prices: The case of Wuhan, China," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    5. Kirchhain, Heiko & Mutl, Jan & Zietz, Joachim, 2021. "Spillover effects of company news across real estate markets and causal impact analysis," Journal of Housing Economics, Elsevier, vol. 54(C).
    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).
    7. repec:ire:issued:v:22:n:01:2019:p:27-59 is not listed on IDEAS
    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

    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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