Modelling of Dynamic Spatial Processes

The paper is concerned with econometric modeling of the dynamic spatial processes on the example of the GDP per capita in selected European countries. The considerations of the paper are focused on investigations of the structure of components of the spatio-temporal process. As a result of the analysis some specifications of the dynamic spatial models have been obtained. Next the issues of the estimation and verification of the models are presented. The main conclusion from the analysis is that the econometric models of the spatio-temporal processes ought to be of the dynamic character, e.g. considering the spatial and spatio-temporal trends and spatial, temporal and spatio-temporal autodependence as well.spatio-temporal trend, autocorrelation, spatial lag model, dynamic spatial model.

On the specification of spatial econometric models

In this paper we discuss the specification process of a spatial econometric model. There are a lot of results available in a time series context, which form a very well structured phase, but little has been said when the domain of the model is the Space in relation to this question. There are several points that merit some special attention. For example, it is not clear if the concepts of integration and cointegration are also relevant in a spatial context. Moreover, at this moment we do not have any specific criteria in order to solve the selection of the variables. This weakness lead us to another question, which is related to the correlation problem: Which kind of cross-sectional dynamics could be allowed in a spatial specification? At present, in case of finding spatial autocorrelation in a model we try to model it immediatly, without considerer that if it may reflect a previous specification error. Finally, there is the problem of the outliers which are of paramount importance in time series but just unkown in a spatial context. We will discuss each one of this topics making reference to a general specification and looking also at the final stage of model selection.

Agglomeration, accessibility and industrial location: evidence from spanish municipalities

This paper deals with the location decisions of manufacturing firms in Spain. We analyse how agglomeration economies and transport accessibility influence the location decisions of firms at municipality level and in three industries. The main empirical contributions of this paper are the econometric techniques used (spatial econometric models) and some of the explanatory variables (local gross domestic product, road accessibility, and the characteristics of firms in neighbouring municipalities). The results show that agglomeration economies and accessibility are important in industrial location decision-making.Agglomeration, Accessibility, Industrial location, Spatial econometrics, Spain

Testing the spatial scale and the dynamic structure in regional models (a contribution to spatial econometric specification analysis)

This article addresses the problem of specification uncertainty in modeling spatial economic theories in stochastic form. It is ascertained that the traditional approach to spatial econometric modeling does not adequately deal with the type and extent of specification uncertainty commonly encountered in spatial economic analyses. Two alternative spatial econometric modeling procedures proposed in the literature are reviewed and shown to be suitable for analyzing systematically two sources of specification uncertainty, viz., the level of aggregation and the spatio-temporal dynamic structure in multiregional econometric models. The usefulness of one of these specification procedures is illustrated by the construction of a simple multiregional model for The Netherlands

Spatial Chow-Lin Methods for Data Completion in Econometric Flow Models

Flow data across regions can be modeled by spatial econometric models, see LeSage and Pace (2009). Recently, regional studies became interested in the aggregation and disaggregation of flow models, because trade data cannot be obtained at a disaggregated level but data are published on an aggregate level. Furthermore, missing data in disaggregated flow models occur quite often since detailed measurements are often not possible at all observation points in time and space. In this paper we develop classical and Bayesian methods to complete flow data. The Chow and Lin (1971) method was developed for completing disaggregated incomplete time series data. We will extend this method in a general framework to spatially correlated flow data using the cross-sectional Chow-Lin method of Polasek et al. (2009). The missing disaggregated data can be obtained either by feasible GLS prediction or by a Bayesian (posterior) predictive density.Missing values in spatial econometrics, MCMC, non-spatial Chow-Lin (CL) and spatial Chow-Lin (SCL) methods, spatial internal flow (SIF) models, origin and destination (OD) data

Spatio-Temporal Analysis of Unemployment Rate in Poland

The aim of this paper is to present results of spatio-temporal analysis of unemployment rate in Poland, with the usage of advanced spatial econometric methods. The analysis was done on data collected for ‘powiat’ level between 2006 and 2010. GlS and ESDA tools were applied for visualization of the spatiotemporal data and identification of spatial interactions between polish counties on labor market. Multi-equation spatial econometric models were used to describe unemployment rate in relation to selected social-economic variables.Celem opracowania jest przestrzenno-czasowa analiza poziomu stopy bezrobocia w Polsce, z wykorzystaniem zaawansowanych metod ekonometrii przestrzennej. Badanie przeprowadzono na danych statystycznych zebranych na poziomie powiatu, w latach 2006-2010. Narzędzia GIS i ESDA zostały wykorzystane w celu wizualizacji zmiennych oraz identyfikacji interakcji przestrzennych zachodzących pomiędzy badanymi jednostkami terytorialnymi na rynku pracy. Wielorównaniowe modele o równaniach pozornie niezależnych zastosowano do opisu wpływu wybranych zmiennych makroekonomicznych na kształtowanie się poziomu stopy bezrobocia w Polsce w badanym okresie