2015
DOI: 10.1002/jae.2450
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Identification of Spatial Durbin Panel Models

Abstract: 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 e… Show more

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Cited by 81 publications
(37 citation statements)
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“…Furthermore, the model in Equation () is endogenous because of the presence of the spatial lag; therefore, the log‐likelihood function is highly nonlinear. This estimation is performed by using the quasi likelihood method for panel proposed by Millo and Piras (2012), which provides consistent results (Lee & Yu, 2016).…”
Section: Methodsmentioning
confidence: 60%
“…Furthermore, the model in Equation () is endogenous because of the presence of the spatial lag; therefore, the log‐likelihood function is highly nonlinear. This estimation is performed by using the quasi likelihood method for panel proposed by Millo and Piras (2012), which provides consistent results (Lee & Yu, 2016).…”
Section: Methodsmentioning
confidence: 60%
“…Therefore, compared to other spatial models, the SDM is a more generalized form. However, for making sure the applicability of SDM to certain regression analyses, it is necessary to perform relevant statistical tests, and the Wald and likelihood ratio (LR) test shall be carried out for confirming if the SDM can be reduced to a SLM or SEM [50]. The Hausman test helps the study to confirm that which effect is adopted by the spatial econometric model, fixed effect or random effect [51].…”
Section: Methodsmentioning
confidence: 99%
“…Specifically, we allow banks to be treated the same by the public irrespective of the distance between them, for example, banks are allowed to have interbank connections around the whole banking sector. Note that the identification in the spatial models is an ongoing issue (see, e.g., Gibbons and Overman , Gibbon, Overman and Patacchini , and Lee and Yu among others) . Gibbons and Overman (, p. 180) notes that, “in theory if W is not idempotent, identification is possible, but the parameters in the spatial Durbin model are likely only weakly identified in practice.” Note that spatial Durbin model is a combination of the SAR (Spatial Autoregressive Model) and the SLX (Spatial Lag of X) model.…”
Section: Methodsmentioning
confidence: 99%
“…In a later paper, Gibbons, Overman, and Patacchini () also discuss this issue in detail and note that spatial models are identified when the spatial‐weights matrix is nonblock diagonal. Lee and Yu () also address this issue and show that spatial specifications are identified under likelihood estimation. In our analysis, the equal weights W matrix with zero diagonal elements is not idempotent.…”
Section: Methodsmentioning
confidence: 99%