likelihood estimation method set forth by Aquaro, Bailey and Pesaran (2015), we rely on a Markov Chain Monte Carlo (MCMC …) estimation methodology. MCMC estimates as applied here with non-informative priors will produce estimates equal to those from …

. Spatial econometrics focuses on the specification and estimation of regression models explicitly incorporating such spatial …, referring to both heterogeneity and interdependence of phenomena occurring in two-dimensional space. Spatial autocorrelation or …

econometric models. We also examine some diagnostic measures to evaluate the spatial autocorrelation of the pseudo … arrangement on the variables in the predictive model and reduce the effect of spatial autocorrelation on prediction errors. In … remove the spatial autocorrelation on pseudo-residuals and improvement in the accuracy of spatial predictive models. …

geometric ergodicity of the model. Simulation results justify the use of limit theory in empirically relevant settings. The …

. It was possible to determine a significant spatial autocorrelation. Therefore one have to consider these spatial … effects ; production of health ; efficiency measurement ; heterogeneity ; spatial effects ; spatial autocorrelation …

error models – to correct for misspecification due to neglected spatial autocorrelation in the data set. Our empirical … spatial structure that is required for the estimation of spatial models improves the forecasting performance of non …

autocorrelation of house prices and explanatory variables within larger distances, whereas the significant spatial autocorrelation of …