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Identification of Spatial Durbin Panel Models
Author(s) -
Lee Lungfei,
Yu Jihai
Publication year - 2015
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2450
Subject(s) - econometrics , spillover effect , identification (biology) , panel data , regression , instrumental variable , monte carlo method , moment (physics) , spatial econometrics , economics , regression analysis , mathematics , statistics , macroeconomics , botany , physics , classical mechanics , biology
Summary 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. Copyright © 2015 John Wiley & Sons, Ltd.