Generalized spatial autocorrelation in a panel-probit model with an application to exporting in China
Badi Baltagi (),
Peter Egger () and
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Michaela Kesina: ETH Zurich
Empirical Economics, 2018, vol. 55, issue 1, 193-211
Abstract This paper proposes a generalized spatial panel-data probit model with spatial autocorrelation of the dependent variable, the time-invariant individual shocks, and the remainder disturbances. It proposes its estimation with a Bayesian Markov chain Monte Carlo procedure. Simulation results show that the proposed estimation method performs well in small- to medium-sized samples. This method is then applied to the analysis of export-market participation of 1451 Chinese firms between 2002 and 2006 in the prefecture-level city of Wenzhou in the province of Zhejiang. Empirical results show that two of the three forms of the hypothesized spatial autocorrelation are significant, namely the spatial lag for the dependent variable and the time-invariant firm-specific shocks, but not the time-variant shocks. Ignoring any of these significant spatial effects would lead to misspecification.
Keywords: Spatial econometrics; Spillovers; Panel-data econometrics; Panel-probit; Firm-level exporting; Chinese firms (search for similar items in EconPapers)
JEL-codes: C23 C31 D24 L65 (search for similar items in EconPapers)
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