Estimation of spatial panel data models with time varying spatial weights matrices

This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models where spatial weights matrices can be time varying. We show that QML estimate is consistent and asymptotically normal. We also derive the asymptotic distribution of average impact coefficients (direct, indirect, total). Monte Carlo results are reported to investigate the finite sample properties of QML estimates and impact coefficients.

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Year of publication:	2015
Authors:	Wang, Wei ; Yu, Jihai
Published in:	Economics Letters. - Elsevier, ISSN 0165-1765. - Vol. 128.2015, C, p. 95-99
Publisher:	Elsevier
Subject:	Spatial autoregression \| Panel data \| Time varying spatial weights matrices \| Fixed effects \| Maximum likelihood \| Impact analysis

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Type of publication:	Article
Classification:	C13 - Estimation ; C23 - Models with Panel Data ; R15 - Econometric and Input-Output Models; Other Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011208460