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This paper presents a generalized moments (GM) approach to estimating an R-th order spatial regressive process in a panel data error component model. We derive moment conditions to estimate the parameters of the higher order spatial regressive process and the optimal weighting matrix required to...
Persistent link: https://www.econbiz.de/10010264361
This paper generalizes the approach to estimating a first-order spatial autoregressive model with spatial autoregressive disturbances (SARAR(1,1)) in a cross-section with heteroskedastic innovations by Kelejian and Prucha (2008) to the case of spatial autoregressive models with spatial...
Persistent link: https://www.econbiz.de/10010264403
This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM)...
Persistent link: https://www.econbiz.de/10010264566
This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM)...
Persistent link: https://www.econbiz.de/10003808637
Persistent link: https://www.econbiz.de/10003711864
Persistent link: https://www.econbiz.de/10009356093
This paper generalizes the approach to estimating a first-order spatial autoregressive model with spatial autoregressive disturbances (SARAR(1,1)) in a cross-section with heteroskedastic innovations by Kelejian and Prucha (2008) to the case of spatial autoregressive models with spatial...
Persistent link: https://www.econbiz.de/10003748246
Persistent link: https://www.econbiz.de/10003741600
Persistent link: https://www.econbiz.de/10003946571
We estimate the speed of income convergence for a sample of 196 European NUTS 2 regions over the period 1985-1999. So far there is no direct estimator available for dynamic panels with strong spatial dependencies. We propose a two-step procedure, which involves first spatial filtering of the...
Persistent link: https://www.econbiz.de/10010295552