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

Badi Baltagi, Bernard Fingleton () and Alain Pirotte
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Alain Pirotte: CRED-TEPP (CNRS), University of Pantheon-Assas Paris II and IFSTTARDEST, French Institute of Science and Technology for Transport, Development and Networks

No 161, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

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.

Keywords: House Prices; Panel Data; Spatial Lag; Nested Random Effects; In-strumental Variables; Spatial Dependence (search for similar items in EconPapers)
JEL-codes: C33 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2013-11
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https://surface.syr.edu/cpr/382/ (application/pdf)

Related works:
Journal Article: Spatial lag models with nested random effects: An instrumental variable procedure with an application to English house prices (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:max:cprwps:161

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