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Estimating spatial spillover in housing construction with nonstationary panel data

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  • Beenstock, Michael
  • Felsenstein, Daniel

Abstract

A model is proposed in which building contractors have regional preferences so that housing construction in different regions are imperfect substitutes. The model hypothesizes spatial and national spillovers in construction. Although the government does not engage directly in housing construction, it influences regional housing markets by auctioning land to contractors. Contractors are hypothesized to use housing-under-construction as a buffer between starts and completions. Spatial panel data for Israel are used to test the model and investigate the determinants of regional housing construction. Because the spatial panel data are nonstationary, we use spatial panel cointegration methods to estimate the model. The estimated model is used to calculate impulse responses which propagate over time and across space.

Suggested Citation

  • Beenstock, Michael & Felsenstein, Daniel, 2015. "Estimating spatial spillover in housing construction with nonstationary panel data," Journal of Housing Economics, Elsevier, vol. 28(C), pages 42-58.
    • Handle: RePEc:eee:jhouse:v:28:y:2015:i:c:p:42-58
    DOI: 10.1016/j.jhe.2014.10.002
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    2. Reinhold Kosfeld & Christian Dreger, 2018. "Local and spatial cointegration in the wage curve – a spatial panel analysis for german regions," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 38(1), pages 53-75, February.
    3. Yu Zhou & Caijiang Zhang & Zhangwen Li, 2023. "The impact of digital financial inclusion on household carbon emissions: evidence from China," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 12(1), pages 1-21, December.
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    5. Kosfeld, Reinhold & Dreger, Christian, 2019. "Towards an East German wage curve - NUTS boundaries, labour market regions and unemployment spillovers," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 115-124.
    6. 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.
    7. Badi H. Baltagi & Junjie Shu, 2024. "A Survey of Spatial Unit Roots," Mathematics, MDPI, vol. 12(7), pages 1-32, March.
    8. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    9. Chica-Olmo, Jorge & Sari-Hassoun, Salaheddine & Moya-Fernández, Pablo, 2020. "Spatial relationship between economic growth and renewable energy consumption in 26 European countries," Energy Economics, Elsevier, vol. 92(C).

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    More about this item

    Keywords

    Regional housing construction; Elasticity of housing supply; Spatial panel cointegration;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • R38 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Government Policy

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