Topic:Estimation and Diagnostic Test of Dynamic Panel Spatial Vector Autoregression
Speaker:Yang Kai, School of the Economics of SUFE
Time: 15:00–16:30
Date: April 28, 2019
Venue:106B, Zhonghui Building
Abstract:
This paper introduces dynamic panel spatial vector autoregressive models. We study features that an SVAR model can generate and divide the model into stable or unstable cases by partitioning parameter spaces. For different cases, we investigate identification and a unified QML estimation when simultaneity and correlated relationships occur. Asymptotic properties and bias-corrected estimators are presented. To detect unknown cointegration relationships, we introduce a sequential likelihood ratio testing procedure. Simulations show the advantage of QML estimators on bias reduction and efficiency gains. The empirical application provides evidences on grain market integration.
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