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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 Local (LSTAR) approach in modelling transaction prices for the housing market in inner Paris. We use a data set from the Paris Region notary office (“Chambre des notaires d’Île-de-France”) which consists of approximately 250,000 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). This method incorporates a spatiotemporal filtering process into the conventional hedonic function and attempts to correct for spatial and temporal correlative effects. We find significant estimates of spatial dependence effects. Moreover, using an original methodology, we find evidence of a strong presence of both spatial and temporal heterogeneity in the model. It suggests that spatial and temporal drifts in households socio-economic profiles and local housing market structure effects are certainly major determinants of the price level for the Paris Housing Market.
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  • Ingrid Nappi‐Choulet & Tristan‐Pierre Maury, 2011. "A Spatial And Temporal Autoregressive Local Estimation For The Paris Housing Market," Journal of Regional Science, Wiley Blackwell, vol. 51(4), pages 732-750, October.
    • Handle: RePEc:bla:jregsc:v:51:y:2011:i:4:p:732-750
    DOI: j.1467-9787.2011.00713.x
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    1. Ingrid Nappi‐Choulet Pr. & Tristan‐Pierre Maury, 2009. "A Spatiotemporal Autoregressive Price Index for the Paris Office Property Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 37(2), pages 305-340, June.
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    8. Antonio Páez & Takashi Uchida & Kazuaki Miyamoto, 2002. "A General Framework for Estimation and Inference of Geographically Weighted Regression Models: 1. Location-Specific Kernel Bandwidths and a Test for Locational Heterogeneity," Environment and Planning A, , vol. 34(4), pages 733-754, April.
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    11. Bourassa, Steven C. & Hoesli, Martin & Peng, Vincent S., 2003. "Do housing submarkets really matter?," Journal of Housing Economics, Elsevier, vol. 12(1), pages 12-28, March.
    12. Basu, Sabyasachi & Thibodeau, Thomas G, 1998. "Analysis of Spatial Autocorrelation in House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 61-85, July.
    13. Pace, R Kelley & Barry, Ronald & Clapp, John M. & Rodriquez, Mauricio, 1998. "Spatiotemporal Autoregressive Models of Neighborhood Effects," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 15-33, July.
    14. Clapp, John M & Rodriguez, Mauricio, 1999. "Erratum: Spatiotemporal Autoregressive Models of Neighborhood Effects," The Journal of Real Estate Finance and Economics, Springer, vol. 19(1), pages 1-85, July.
    15. Alan E. Gelfand & Mark D. Ecker & John R. Knight & C. F. Sirmans, 2004. "The Dynamics of Location in Home Price," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 149-166, September.
    16. Can, Ayse & Megbolugbe, Isaac, 1997. "Spatial Dependence and House Price Index Construction," The Journal of Real Estate Finance and Economics, Springer, vol. 14(1-2), pages 203-222, Jan.-Marc.
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    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
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    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • R33 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Nonagricultural and Nonresidential Real Estate Markets

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