This paper estimates a hedonic housing model based on flats sold in the city of Paris over the period 1990-2003. This is done using maximum likelihood estimation taking into account the nested structure of the data. Paris is historically divided into 20 arrondissements, each divided into four quartiers (quarters), which in turn contain between 15 and 169 blocks (îlot, in French) per quartier. This is an unbalanced pseudo-panel data containing 156,896 transactions. Despite the richness of the data, many neighborhood characteristics are not observed, and we attempt to capture these neighborhood spill-over effects using a spatial lag model. Using Likelihood Ratio tests, we find significant spatial lag effects as well as significant nested random error effects. The empirical results show that the hedonic housing estimates and the corresponding marginal effects are affected by taking into account the nested aspects of the Paris housing data as well as the spatial neighborhood effects.

Document Type

Working Paper




Spatial Lag, Nested Effects, Hedonic Housing, Unbalanced Panel Data, Random Effects




Working Papers Series


Economic Policy | Economics | Public Affairs, Public Policy and Public Administration



Additional Information

Working paper no.163


Local input

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.



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