Estimation of Higher-Order Spatial Autoregressive Panel Data Error Component Models

111 Pages Posted: 26 Feb 2009

See all articles by Harald Badinger

Harald Badinger

Vienna University of Economics and Business

Peter H. Egger

Ifo Institute for Economic Research - International Trade and Foreign Direct Investment; ETH Zürich; Ludwig-Maximilians University of Munich; CESifo (Center for Economic Studies and Ifo Institute for Economic Research)

Date Written: February 1, 2009

Abstract

This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM) estimation procedure of the spatial autoregressive parameters of the disturbance process and define a generalized two-stages least squares estimator for the regression parameters of the model. We prove consistency of the proposed estimators, derive their joint asymptotic distribution, and provide Monte Carlo evidence on their small sample performance.

Keywords: higher-order spatial dependence, generalized moments estimation, two-stages least squares, asymptotic statistics

JEL Classification: C13, C21, C23

Suggested Citation

Badinger, Harald and Egger, Peter H., Estimation of Higher-Order Spatial Autoregressive Panel Data Error Component Models (February 1, 2009). CESifo Working Paper Series No. 2556, Available at SSRN: https://ssrn.com/abstract=1349782 or http://dx.doi.org/10.2139/ssrn.1349782

Harald Badinger

Vienna University of Economics and Business ( email )

Department of Economics
Althanstrasse 39-45
Vienna, 1090
Austria

Peter H. Egger (Contact Author)

Ifo Institute for Economic Research - International Trade and Foreign Direct Investment ( email )

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Munich, DE-81679
Germany
+49 0 89 9224 1238 (Phone)
+49 0 89 985369 (Fax)

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ETH Zürich ( email )

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Switzerland

Ludwig-Maximilians University of Munich

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Munich, 80539
Germany

CESifo (Center for Economic Studies and Ifo Institute for Economic Research)

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Munich, DE-81679
Germany

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