Estimation of dynamic panel spatial vector autoregression: Stability and spatial multivariate cointegration
| Autor: | Kai Yang, Lung-fei Lee |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Economics and Econometrics
Multivariate statistics Simultaneity Cointegration Applied Mathematics 05 social sciences Estimator 01 natural sciences Stability (probability) 010104 statistics & probability Identification (information) Autoregressive model 0502 economics and business Econometrics 0101 mathematics 050205 econometrics Mathematics Euclidean vector |
| Zdroj: | Journal of Econometrics. 221:337-367 |
| ISSN: | 0304-4076 |
| DOI: | 10.1016/j.jeconom.2020.05.010 |
| Popis: | This paper introduces dynamic panel spatial vector autoregressive models. We study features of dynamics and spatial interactions that an SVAR model can generate and classify the model into stable or unstable cases by partitioning parameter spaces. For stable, spatial cointegration, and mixed cointegration cases, we investigate identification and QML estimation of the models to take into account simultaneity and correlated relationships. 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 QMLEs on bias reduction and efficiency gains. The empirical application provides evidences on ancient China’s market integration. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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