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Local House Price Diffusion

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  • Jeffrey P. Cohen
  • Jeffrey Zabel

Abstract

We contribute to the literature on house price diffusion by carrying out our analysis at three levels: CBSA (nationwide), town and census tract (Greater Boston Area). We estimate fixed‐effect models of house price growth on lagged growth (“Persistence”), nearby lagged growth (“Spillovers”) and Fundamentals growth. CBSA‐level Persistence and Spillover Effects are positive and significant. These large ripple/contagion effects likely contributed to the recent national‐level housing downturn. We find evidence of smaller town‐level Persistence and Spillover Effects. Hence, diffusion appears stronger across than within housing markets. Fundamentals and price expectations drive price diffusion, leaving room for bubbles from future price overoptimism.

Suggested Citation

  • Jeffrey P. Cohen & Jeffrey Zabel, 2020. "Local House Price Diffusion," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 48(3), pages 710-743, September.
    • Handle: RePEc:bla:reesec:v:48:y:2020:i:3:p:710-743
    DOI: 10.1111/1540-6229.12241
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    2. Jacob Dearmon & Tony E. Smith, 2021. "A hierarchical approach to scalable Gaussian process regression for spatial data," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-33, December.
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    5. Cheng-Wen Lee & Shu-Hen Chiang & Zhong-Qin Wen, 2023. "Pursuing the Sustainability of Real Estate Market: The Case of Chinese Land Resources Diversification," Sustainability, MDPI, vol. 15(7), pages 1-19, March.

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