AN ESTIMATION OF DISPOSABLE PERSONAL INCOME OF THE SPANISH MUNICIPALITIES IN 1997

Since 1992, Lawrence R. Klein Institute –Autónoma University of Madrid- estimates the disposable income of the Spanish municipalities, recently published in the ‘Anuario Comercial de España’ –Spanish Trade Yearbook- as scaled levels. Municipal personal income has been considered as one of the most important economic indicators, very used in a wide range of studies concerned with regional convergence, welfare analysis, marketing targets, etc. This kind of estimation can be carried out by both direct and indirect methodology. The first proceeding requires a huge information database generally difficult to obtain and not always precise, which main defect is that it cannot reflect the underground economy of Spanish municipalities. That is why direct methodology always has needed the help of indirect proceedings. These last ones find out the statistical relation of the personal disposable income and a group of socio-economic indicators for all the geographic units considered, municipalities, provinces, regions, countries, etc. In this paper, the authors present some of the indirect methods used to estimate the disposable income of Spanish municipalities. Especially the Klein estimation combines some multivariate analysis –panel data, factor and cross-section regression analysis- with a big database of almost 200 socio-economic indicators. The final estimation of the 8.099 municipalities disposable income allows us to acquire a better knowing of Spanish micro-territorial development.

ECOLOGICAL INFERENCE AND SPATIAL HETEROGENEITY - A NEW APPROACH BASED ON ENTROPY ECONOMETRICS

In this paper, we compare the results obtained by the application of three alternative methods of ecological inference. The data is on per capita household disposable income in the 50 provinces and 78 municipalities of Asturias, Spain. The first method is based on Ordinary Least Squares regression model, which assumes constancy or homogeneity. The second method is based on a spatial autocorrelation model, which assumes heterogeneity in two spatial regimes. The third method is based on a varying-coefficients model, which assumes total heterogeneity. The second model is estimated by Maximum Likelihood, whereas the latter is estimated by using Generalized Maximum or Cross Entropy.

Spatial interaction models applied to the design of retail trade areas

Intermetropolitan trade areas are geographical zones defined by consumer movements over space -retail flows- from their municipalities of residence towards a head town, to purchase special goods: clothing and footwear, furniture, food, etc. These market areas own an economic sense that do not have other more commonly used territorial divisions, such as towns, provinces or regions. Since 1992, the Lawrence R. Klein Institute -Autonoma University of Madrid-actualises the Spanish Retail Trade Atlas and determines regional trade areas and sub-areas, using spatial gravity models and survey. The authors' experience in this Project allows them to analyse the different procedures suggested for modelling the consumer store-choice process and from this, estimating the market share of a retail outlet or a town. Store choice models can be classified into two main groups. First, the descriptive-determinist approach includes a group of techniques that rely on observation or normative assumptions. It is well-known the procedure devised by Applebaum (1961) for constructing primary trade areas from customers spotted on a location map or the classical central place theory, based on the nearest-centre hypothesis. 'Reilly's law of retail gravitation' (1931) considers not only distance but also attractiveness of alternative shopping opportunities. Secondly, the explicative-stochastic approach uses information revealed by past behaviour to understand the dynamics of retail competition and how consumers choose among alternative shopping opportunities. Huff was the first to use a utility function and introduced the spatial interaction models to explain consumer behaviour. They argued that consumers rate alternatives on the basis of their evaluation of the total utility of the store and not merely on its location. Huff's model is a particular case of the discrete-choice models known as multinomial logit (McFadden, 1974). Both models satisfies the so-called 'Independece of Irrelevant Alternatives' (IIA) property, that is, the ratio of the probabilities of an individual selecting two alternatives is unaffected by the addition of a third alternative. While this may be reasonably representative of certain aspatial choice situations, it is very unlikely to occur in spatial choice because of the fixed locations of spatial alternatives. The competing destinations model, derived from purely spatial considerations, provides a way of overcoming some problems with the logit and nested logit models that arise from the transference of essentially aspatial theory to the spatial realm. This work focuses on market area delimitation models and presents the estimation process developed by the L.R. Klein Institute in determining intermetropolitan trade areas. It is also applied a competing destinations model to the trade area of Madrid, a very peculiar one because of its magnitude and the important shopping concentration around the capital. Finally, we want to highlight the main applications derived from the knowledge and actualisation of the consumer retail flows. These applications take into account not only retailing but also another economic activities relating with market attraction areas.

ECOLOGICAL INFERENCE AND SPATIAL HETEROGENEITY - A NEW APPROACH BASED ON ENTROPY ECONOMETRICS

In this paper, we compare the results obtained by the application of three alternative methods of ecological inference. The data is on per capita household disposable income in the 50 provinces and 78 municipalities of Asturias, Spain. The first method is based on Ordinary Least Squares regression model, which assumes constancy or homogeneity. The second method is based on a spatial autocorrelation model, which assumes heterogeneity in two spatial regimes. The third method is based on a varying-coefficients model, which assumes total heterogeneity. The second model is estimated by Maximum Likelihood, whereas the latter is estimated by using Generalized Maximum or Cross Entropy

Urban growth and territorial dynamics in Spain (1985-2001): A spatial econometrics analysis

The study of the territorial/regional development in Spain has nowadays a relatively long tradition, but from the point of view of cities development the number of studies and documents decreases drastically. This paper tries to improve the knowledge of the Spanish urban system. The aim of this paper is twofold: firstly, to determine the factors that explain the urban growth of Spanish cities; secondly, to observe the cities situation in terms of ¡§winners¡¨ and ¡§losers¡¨ after the long period of integration of Spain in the EU. A spatial conditional ƒÒ- convergence equation is specified and the Durbin-Wu-Haussman exogeneity test is used to check on the existence of simultaneity between urban growth and the control variables. The classic problems of spread and backwash are studied by including a spatial autoregressive term and spatial regimes ¡Vconvergence clubs- in the growth model.Urban growth, Spanish cities, conditional ƒÒ-convergence, endogeneity, Durbin-Wu-Haussman, spatial autocorrelation, spatial heterogeneity, convergence clubs

SPACE-TIME LAGS: SPECIFICATION STRATEGY IN SPATIAL REGRESSION MODELS

he purpose of this article is to analyse the dynamic trend of spatial dependence, which is not only contemporary but time-lagged in many socio-economic phenomena. Firstly, we show some of the commonly used exploratory spatial data analysis (ESDA) techniques and we propose other new ones, the exploratory space-time data analysis (ESTDA) that evaluates the instantaneity of spatial dependence. We also propose the space-time correlogram as an instrument for a better specification of spatial lag models, which should include both kind of spatial dependence. Some applications with economic data for Spanish provinces shed some light upon these issues.Spatial dependence, spatial diffusion, ESDA, correlogram, Spanish provinces

Spatial interaction models applied to the design of retail trade areas

Intermetropolitan trade areas are geographical zones defined by consumer movements over space -retail flows- from their municipalities of residence towards a head town, to purchase special goods: clothing and footwear, furniture, food, etc. These market areas own an economic sense that do not have other more commonly used territorial divisions, such as towns, provinces or regions. Since 1992, the Lawrence R. Klein Institute -Autonoma University of Madrid-actualises the Spanish Retail Trade Atlas and determines regional trade areas and sub-areas, using spatial gravity models and survey. The authors' experience in this Project allows them to analyse the different procedures suggested for modelling the consumer store-choice process and from this, estimating the market share of a retail outlet or a town. Store choice models can be classified into two main groups. First, the descriptive-determinist approach includes a group of techniques that rely on observation or normative assumptions. It is well-known the procedure devised by Applebaum (1961) for constructing primary trade areas from customers spotted on a location map or the classical central place theory, based on the nearest-centre hypothesis. 'Reilly's law of retail gravitation' (1931) considers not only distance but also attractiveness of alternative shopping opportunities. Secondly, the explicative-stochastic approach uses information revealed by past behaviour to understand the dynamics of retail competition and how consumers choose among alternative shopping opportunities. Huff was the first to use a utility function and introduced the spatial interaction models to explain consumer behaviour. They argued that consumers rate alternatives on the basis of their evaluation of the total utility of the store and not merely on its location. Huff's model is a particular case of the discrete-choice models known as multinomial logit (McFadden, 1974). Both models satisfies the so-called 'Independece of Irrelevant Alternatives' (IIA) property, that is, the ratio of the probabilities of an individual selecting two alternatives is unaffected by the addition of a third alternative. While this may be reasonably representative of certain aspatial choice situations, it is very unlikely to occur in spatial choice because of the fixed locations of spatial alternatives. The competing destinations model, derived from purely spatial considerations, provides a way of overcoming some problems with the logit and nested logit models that arise from the transference of essentially aspatial theory to the spatial realm. This work focuses on market area delimitation models and presents the estimation process developed by the L.R. Klein Institute in determining intermetropolitan trade areas. It is also applied a competing destinations model to the trade area of Madrid, a very peculiar one because of its magnitude and the important shopping concentration around the capital. Finally, we want to highlight the main applications derived from the knowledge and actualisation of the consumer retail flows. These applications take into account not only retailing but also another economic activities relating with market attraction areas

Spatial Analysis of Urban Growth in Spain (1900-2001)

The purpose of this paper is to improve the knowledge of the Spanish urban system. We study the evolution of population growth among the group of 722 municipalities included in the Spanish urban areas over the period from 1900-2001. Urban population cross-sectional distribution is characterized by means of nonparametric estimations of density functions, and the growth process is modeled as a first-order stationary Markov chain. A spatial SUR model is also estimated for the Zipf's law. Spatial effects are then introduced within the Markov chain framework using regional conditioning and spatial Markov chains

Modelos de regresión espacio temporales en la estimación de la renta municipal. Estimación de la renta en los municipios de la Región de Murcia.

Recently municipal household income has been estimated with spatial econometrics techniques explicitly including spatial autocorrelation in the econometric models. Spatial econometric tools have highly improved the explicative and predictive capacity of the models and more effort must be done in this direction. The purpose of this article is to state an alternative way to estimate household income in small areas with a space-time model, which both correct spatial effects and introduce time dimension, borrowing strength to estimate the municipal distribution of disposable income. We have selected a spatial SUR model, which includes both spatial and space-time autocorrelation effects. Finally, this model is applied to the estimation of municipal household income in the Region of Murcia.Spatial Econometric, SUR Models, Household Income, Región de Murcia