We apply a heterogenous coefficient spatial autoregressive panel model from Aquaro, Bailey and Pesaran (2015) to … 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 …

heterogeneity and spatial correlation across units. We discuss instrumental variable estimation under both the fixed and the random … autocorrelation in the disturbances. We derive the large sample properties of our estimation procedures and show that the test … small panels. -- spatial econometrics ; panel data ; random effects estimator ; within estimator ; Hausman test …

spatial panel model. The analysis of regional differences is of particular interest in the German case due to its specific …, we specify both a static and a dynamic spatial panel model. The spatial econometric literature provides various types of …-maximum likelihood estimator proposed by Lee and Yu (2010, Econometric Theory). To incorporate the spatial information into the model, we …

Focus is on efficient estimation of a dynamic space-time panel data model that incorporates spatial dependence … of spatial units and T the number of time periods. Quasi-maximum likelihood (QML) estimation in cases involving large N … estimates that require numerous inversions of large matrices. We set forth a Markov Chain Monte Carlo (MCMC) estimation …

Durbin panel model. The model is designed to test the existence and strength of the country-effect of innovativeness on the …

A space–time filter is set forth for spatial panel data situations that include random effects. We propose a general … spatial dynamic specification that encompasses several spatiotemporal models previously used in the panel data literature. We … apply the model to the case of highway induced travel demand. The theory of induced travel demand asserts that increased …