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A Spatial And Temporal Autoregressive Local Estimation For The Paris Housing Market

  • Ingrid Nappi‐Choulet
  • Tristan‐Pierre Maury

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.

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File URL: http://hdl.handle.net/10.1111/j.1467-9787.2011.00713.x
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Article provided by Wiley Blackwell in its journal Journal of Regional Science.

Volume (Year): 51 (2011)
Issue (Month): 4 (October)
Pages: 732-750

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Handle: RePEc:bla:jregsc:v:51:y:2011:i:4:p:732-750
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  1. 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.
  2. Bourassa, Steven C. & Hamelink, Foort & Hoesli, Martin & MacGregor, Bryan D., 1999. "Defining Housing Submarkets," Journal of Housing Economics, Elsevier, vol. 8(2), pages 160-183, June.
  3. Pace, R Kelley, et al, 1998. "Spatiotemporal Autoregressive Models of Neighborhood Effects," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 15-33, July.
  4. 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 203-22, Jan.-Marc.
  5. 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, 09.
  6. R. Kelley Pace & Otis W. Gilley, 1998. "Generalizing the OLS and Grid Estimators," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 26(2), pages 331-347.
  7. 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 85, July.
  8. Kelley Pace, R. & Barry, Ronald, 1997. "Sparse spatial autoregressions," Statistics & Probability Letters, Elsevier, vol. 33(3), pages 291-297, May.
  9. 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.
  10. 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.
  11. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
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