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Spatio-Temporal Diffusion of Housing Prices in Iran (in Persian)

Author

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  • Tavassoli, Solaleh

    (Faculty of Economics, Allameh Tabataba’i University, Tehran, Iran)

  • Khiabani, Nasser

    (Department of Economics, Faculty of Economics, Allameh Tabataba’i University, Tehran, Iran.)

Abstract

To understand the behavior of housing prices in the country it is necessary to investigate the spatial interactions of interconnected regional markets. The discussion on housing prices highlights the potential spatial heterogeneity and cross-sectional dependence in different regions. It is important to pay attention to the source of cross-sectional dependencies to better understand the dynamics of housing prices in different regions. Cross-sectional dependence can be caused either by the role of space in economic processes or by common shocks that affect the entire economy, such as the oil shock. Using a spatio-temporal housing price diffusion model, the study found that the Tehran region, as the center of economic development and oil revenues, was a dominant region, and that shocks to Tehran were propagated contemporaneously and spatially to other regions. The results show that in modeling the spatial diffusion of housing prices, financial proximity is more important than geographic proximity, and regions with stronger financial links with Tehran will be most affected by shocks to this region in the long run.

Suggested Citation

  • Tavassoli, Solaleh & Khiabani, Nasser, 2023. "Spatio-Temporal Diffusion of Housing Prices in Iran (in Persian)," The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی Ùˆ بودجه), Institute for Management and Planning studies, vol. 28(3), pages 3-42, December.
    • Handle: RePEc:auv:jipbud:v:28:y:2023:i:3:p:3-42
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    References listed on IDEAS

    as
    1. 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.
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    4. Alexander Chudik & M. Hashem Pesaran, 2013. "Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 592-649, August.
    5. William D. Larson & Weihua Zhao, 2020. "Oil Prices and Urban Housing Demand," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 48(3), pages 808-849, September.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Spatio-temporal Diffusion; Housing Prices; Dominant Unit; Regional Housing Markets; Dynamic Structural Vector Error Correction Models.;
    All these keywords.

    JEL classification:

    • 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
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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