Dear list members,

I was wondering if someone could help me out. Estimating a general spatial model (gstslshet) our model is likely to suffer from endogeneity not only introduced by the spatial lag but also from other explanatory variables. Is there any possibility to explicitly account for this endogeneity (by using specific instruments)? Is it covered/dealt with in some kind? Obviously I do not understand equation 4 in Piras (2010).
I read Anselin, Amaral and Arribas-Bel (2012) where they compare different GMM implementations among others also with an endogenous explanatory variable, but cannot reproduce the results in R sphet (problem is knitr, sweave,... I never use that), which is the only spatial econometrics software I use as I am a beginner. I would be really glad I someone could explain me this issue.

Best regards,

Paul
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Technische Universität München - TUM
Paul Feichtinger
Lehrstuhl für Volkswirtschaftslehre, Umweltökonomie und Agrarpolitik

Alte Akademie 14
85354 Freising
Tel: +49.8161.71.3574
Fax: +49.8161.71.3408
e-mail: Paul.Feichtinger@tum.de


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