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 …

as employment, requires an understanding of spatial (or spatio-temporal) autocorrelation effects associated with a … deal with the analysis of and accounting for spatial autocorrelation by means of spatial filtering t! echniques for data …

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 …

-economic network theories (e.g. entropy maximization, spatial interaction theory, etc.); (ii) the nature of the analytical relationship …

spatial econometric techniques are available in the literature, which deal with the spatial autocorrelation in geographically …-referenced data. The experiments carried out in this article are concerned with the analysis of the spatial autocorrelation observed … of the residual spatial autocorrelation in the data …

. 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 … dependence can be detected by means of cross-correlation statistics in univariate as well as multivariate data settings. We …