Spatial Lag Models with Nested Random Effects: An Instrumental Variable Procedure with an Application to English House Prices

Author(s)/Creator(s)

Badi H. Baltagi, Syracuse UniversityFollow
Bernard Fingleton, University of Cambridge
Alain Pirotte, University of Pantheon-Assas Paris II and IFSTTAR-DEST,French Institute of Science and Technology for Transport, Development and Networks

Description/Abstract

This paper sets up a nested random effects spatial autoregressive panel data model to explain annual house price variation for 2000-2007 across 353 local authority districts in England. The estimation problem posed is how to allow for the endogeneity of the spatial lag variable producing the simultaneous spatial spillover of prices across districts together with the nested random effects in a panel data setting. To achieve this, the paper proposes new estimators based on the instrumental variable approaches of Kelejian and Prucha (1998) and Lee (2003) for the cross-sectional spatial autoregressive model. Monte Carlo results show that our estimators perform well relative to alternative approaches and produces estimates based on real data that are consistent with the theoretical house price model underpinning the reduced form.

Document Type

Working Paper

Date

11-2013

Keywords

House Prices, Panel Data, Spatial Lag, Nested Random Effects, In-strumental Variables, Spatial Dependence

Language

English

Series

Working Papers Series

Disciplines

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

ISSN

1525-3066

Additional Information

Working paper no. 161

Recommended Citation

Baltagi, Badi H.; Fingleton, Bernard; and Pirotte, Alain, "Spatial Lag Models with Nested Random Effects: An Instrumental Variable Procedure with an Application to English House Prices" (2013). Center for Policy Research. 382.
https://surface.syr.edu/cpr/382

Source

Local Input

Creative Commons License

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