MAPS OF CONTINUOUS SPATIAL DEPENDENCE

Heterogeneity is one of the distinguishing features in spatial econometric models. It is a frequent problem in applied work and can be very damaging for statistical inference. In this paper, we focus on the problems implied by the existence of instabilities in the mechanism of spatial dependence in a spatial lag model, assuming that the other terms of the specification remain stable. We begin the discussion with the role played by the algorithms of local estimation in detecting the instabilities. Problems appear when one must decide what to do once the existence of heterogeneity has been confirmed. The logical reaction is trying to parameterize this lack of stability. However, the solution is not obvious. Assuming that a set of indicators related to the problem has been identified, we propose a simple technique to deal with the unknown functional form. In the final part of the paper, we present some Monte Carlo evidence and an application to evaluate the instability in the mechanisms of spatial dependence in the convergence process of the European Regions.DEPENDENCE, LOCAL ESTIMATION, MONTE-CARLO, SPATIAL INSTABILITY

Pautas recientes de la movilidad laboral entre las provincias españolas. Periodo 2001-2006

En el trabajo tratamos de caracterizar la movilidad espacial existente en el mercado laboral español, tomando como referencia lo sucedido en el periodo comprendido entre los años 2001 a 2006. Para ello utilizamos datos sobre contratación producidos por el Instituto Nacional de Empleo. El objetivo que inicialmente nos proponemos es caracterizar la estructura espacial que subyace en los datos relativos a migración contratada. El análisis lo ampliamos introduciendo cierto detalle sectorial y sociodemográfico, en busca de singularidades y aspectos de interés. Sin embargo, la estructura espacial que encontramos es débil por lo que, en la segunda parte del trabajo, avanzamos hacia un modelo panel de tipo dinámico. Esta solución nos permite combinar la dimensión espacial, que da soporte físico a los datos, con la secuencia temporal que subyace en los flujos

A Non-Parametric Approach to Spatial Causality

The purpose of this paper is to show the capacity of a new non-parametric test based on symbolic entropy and symbolic dynamics to deal with the detection of linear and non-linear spatial causality. The good performance of the new test in detecting spatial causality and causal weighting matrix is notable and gives rise to an expectation that it may form a adequate tool for constructive specification searches.Causality; Spatial Dependence; Spatial Weight Matrices

Testing for breaks in the weighting matrix

A weighting matrix, W, say, connecting pairs of observation sites, is a key element in the specification of many spatial models. Typically this matrix is fixed a priori by the investigator, which is seldom satisfactory. Recent proposals advocate a more data-driven approach in which W may be estimated. Where panel data are available it may be possible not only to estimate W but also to test its constancy through time. When the time dimension of the panel is large there is a non-negligible risk of breaks in model parameters, including possibly the weights. Ignoring such breaks when they are present will produce at best inefficient parameter estimates, and in most cases, biases. The paper focuses on the stability of W by adapting to the spatial panel context tests for the constancy of covariance matrices developed in the multivariate statistics literature. Information provided by these tests is a prerequisite for a satisfactory analysis of models in which W appears. The utility of our approach is illustrated by two case studies of the contemporary Spanish economy

Spatial SUR models: Specification, Testing and Selection

Our paper focuses on the case of SUR models with spatial effects. Specifically, the problem that we pose is testing for the presence of spatial effects in these multivariate models, considering that one of our main interests is to deal with the question of selecting the most adequate specification for the data. In order to do this, we obtain several tests that check for the fundamental hypothesis of the model, including the assumption of time stability of the spatial dependence mechanisms. We solve the discussion in a maximum-likelihood framework because this facilitates the obtaining of appropriate tests. The second part of the paper contains a Monte Carlo experiment in order to study the behaviour of the two most popular model selection strategies, Specific-to- General or General-to-Specific, using the collection of tests that have been proposed.This work has been carried out with the financial support of project ECO2009-10534/ECON of the Ministerio de Ciencia y Tecnología of the Reino de España

Propuesta de una escala para medir el grado de orientación al mercado de las cooperativas agroalimentarias españolas

El interés de este papel reside en el estudio de la orientación al mercado en un sector en el que la búsqueda del beneficio económico no es un factor prioritario: el sector cooperativista español. Como señala la legislación española, su objetivo es fundamentalmente la satisfacción de las necesidades de los socios cooperativistas, justificando de esta forma su pertenencia al sector no lucrativo. Este trabajo realiza la depuración de la escala de orientación al mercado propuesta por Kohli, Jaworski y Kumar (1993), adaptándola al contexto de las cooperativas vitivinícolas de Aragón (España). Con este propósito se realiza un exhaustivo análisis compuesto por una etapa de carácter exploratorio y otra en la que se realizaron análisis más robustos de tipo confirmatorio. Tras estos análisis queda demostrada la fiabilidad, dimensionalidad y validez de esta escala en dicho contexto específico.Sector Cooperativista, Orientación al Mercado, Validación de Escalas

spsur: An R Package for Dealing with Spatial Seemingly Unrelated Regression Models

Spatial seemingly unrelated regression (spatial SUR) models are a useful multiequational econometric specification to simultaneously incorporate spatial effects and correlated error terms across equations. The purpose of the spsur R package is to supply a complete set of functions to test for spatial structures in the residual of a SUR model; to estimate the most popular specifications by applying different methods and test for linear restrictions on the parameters. The package also facilitates the estimation of socalled spatial impacts, conveniently adapted to a SUR framework. The package includes functions to simulate datasets with the features decided by the user, which may be useful in teaching activities or in more general research projects. The article concludes with a real data application showing the potential that spsur has to examine the relation of individual mobility over geographic areas and the incidence of COVID-19 in Spain during the first lockdown