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A Spatial and Temporal Autoregressive Local Estimation for the Paris Housing Market

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  • Ingrid Nappi-Choulet
  • Tristan-Pierre Maury

Abstract

This original study examines the potential of a spatiotemporal autoregressive (STAR) approach in modelling transaction prices for the housing market in Paris and its inner suburbs. We use a data set from the Paris Region notary office (ìChambre des notaires díŒle-de-Franceî) which consists of more than 1,000,000 transactions units between the first quarter of 1990 and the end of 2005. We use the exact X -- Y coordinates and transaction date to spatially and temporally sort each transaction. We first choose to use the spatiotemporal autoregressive (STAR) approach proposed by Pace, Barry, Clapp and Rodriguez (1998). We do not find a global significant improvement from the STAR method for the modelling of the Paris Region housing market compared to a standard hedonic estimate. Nevertheless, we find evidence of a strong presence of both spatial and temporal heterogeneity in the model. Hence, we decide to develop a spatial and temporal autoregressive local estimation method. With this approach introduced by Pace and Lesage (1999) in a spatially autoregressive setup, we do no longer need to exogenously specify geographical submarket, nor to impose specified parameter variation function to take spatial heterogeneity in hedonic coefficients into account. It appears that spatial autoregressive effects seem to be much more pronounced in the historical centre of Paris than in its surrounding area. Moreover, these effects which were sizeable and significant for some geographical areas in 1991 have been deeply reduced between 1997 and 2005.

Suggested Citation

  • Ingrid Nappi-Choulet & Tristan-Pierre Maury, 2007. "A Spatial and Temporal Autoregressive Local Estimation for the Paris Housing Market," ERES eres2007_404, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2007_404
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    1. is not listed on IDEAS
    2. Jean Dubé & Diègo Legros, 2013. "Dealing with spatial data pooled over time in statistical models," Letters in Spatial and Resource Sciences, Springer, vol. 6(1), pages 1-18, March.
    3. Thanos, Sotirios & Dubé, Jean & Legros, Diègo, 2016. "Putting time into space: the temporal coherence of spatial applications in the housing market," Regional Science and Urban Economics, Elsevier, vol. 58(C), pages 78-88.
    4. Aaron Swoboda & Tsegaye Nega & Maxwell Timm, 2015. "Hedonic Analysis Over Time And Space: The Case Of House Prices And Traffic Noise," Journal of Regional Science, Wiley Blackwell, vol. 55(4), pages 644-670, September.
    5. repec:ers:journl:v:xxiv:y:2021:i:2b:p:810-834 is not listed on IDEAS
    6. Sören Gröbel, 2018. "Regional heterogeneity in age-related housing depreciation rates [Regionale Heterogenität altersbedingter Wertminderungen von Wohnimmobilien]," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 38(2), pages 219-254, October.
    7. Richard T. Baillie & Kun Ho Kim, 2015. "Local Deviations from Uncovered Interest Parity: The Role of Macroeconomic Fundamentals," Working Paper series 15-43, Rimini Centre for Economic Analysis.
    8. Mark J. Holmes & Jesús Otero & Theodore Panagiotidis, 2017. "A Pair-wise Analysis of Intra-city Price Convergence Within the Paris Housing Market," The Journal of Real Estate Finance and Economics, Springer, vol. 54(1), pages 1-16, January.
    9. Monica Palma & Claudia Cappello & Sandra De Iaco & Daniela Pellegrino, 2019. "The residential real estate market in Italy: a spatio-temporal analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2451-2472, September.
    10. Benchimol, Jonathan & Fourçans, André, 2009. "Money in a DSGE framework with an application to the Euro Zone," ESSEC Working Papers DR 09005, ESSEC Research Center, ESSEC Business School.
    11. Sotirios Thanos & Abigail L. Bristow & Mark R. Wardman, 2015. "Residential Sorting And Environmental Externalities: The Case Of Nonlinearities And Stigma In Aviation Noise Values," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 468-490, June.

    More about this item

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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