identification of spatial durbin panel models (replication data)

This paper considers identification of spatial Durbin dynamic panel models under 2SLS and ML estimations. We show that the parameters are generally identified via 2SLS moment relations or expected log-likelihood or quasi-likelihood functions. Monte Carlo experiments suggest that omitting relevant Durbin terms can result in significant biases in regression estimates, while including an irrelevant Durbin term causes no obvious loss of efficiency. Empirical illustration of the international spillover of economic growth through bilateral trade shows that inclusion of Durbin terms can be important.

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Suggested Citation

Lee, Lung-fei; Yu, Jihai (2016): Identification of Spatial Durbin Panel Models (replication data). Version: 1. Journal of Applied Econometrics. Dataset.