Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions
Defining the Spatial Scale in Modern Regional Analysis: New Challenges from Data at Local Level, 2012
In any economic analysis, regions or municipalities should not be regarded as isolated spatial un... more In any economic analysis, regions or municipalities should not be regarded as isolated spatial units, but rather as highly interrelated small open economies. These spatial interrelations must be considered also when the aim is to forecast economic variables. For example, policy makers need accurate forecasts of the unemployment evolution in order to design short- or long-run local welfare policies. These predictions should then consider the spatial interrelations and dynamics of regional unemployment. In addition, a number of papers have demonstrated the improvement in the reliability of long-run forecasts when spatial dependence is accounted for. We estimate a heterogeneouscoefficients dynamic panel model employing a spatial filter in order to account for spatial heterogeneity and/or spatial autocorrelation in both the levels and the dynamics of unemployment, as well as a spatial vector-autoregressive (SVAR) model. We compare the short-run forecasting performance of these methods, and in particular, we carry out a sensitivity analysis in order to investigate if different number and size of the administrative regions influence their relative forecasting performance. We compute short-run unemployment forecasts in two countries with different administrative territorial divisions and data frequency: Switzerland (26 regions, monthly data for 34 years) and Spain (47 regions, quarterly data for 32 years)
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Papers by Matías Mayor
In this paper we focus on the shift-share model as a useful tool in the definition of economic scenarios, based on the different components that contribute to the change of a given economic
magnitude (the so called national, sectoral and competitive effects).
Although the most commonly used methodology is based on the “constant shift” and the “constant share” hypotheses, additional options can be considered based on the expected behaviour of the competitive effect, thus leading to more realistic scenarios.
Once these new options are developed, this approach is applied to the definition of scenarios for the future evolution of the regional employment.
Therefore, stochastic models have been developed as an extension of classical shift and share analysis, allowing the implementation of inferential processes and forecasting tools. The aim of this paper is to analyze the recent evolution of the employment in the European Union, developing a stochastic shift and share model and testing the sources of regional and sectoral differences.
Estos dos últimos aspectos constituyen puntos clave de nuestro trabajo, ya que Asturias presenta condiciones más desfavorables que el conjunto nacional en lo que se refiere a las tasas de actividad, empleo y paro. Además, esta desventaja relativa de nuestra región se hace aún más patente cuando se analizan los indicadores correspondientes a la población femenina.
En esta situación, Asturias se enfrenta al importante reto de introducir mejoras en su mercado laboral, que le permitan acercarse a los objetivos fijados en el Consejo Europeo de Estocolmo de 2001 (tasa de empleo del 67% para la población total y del 57% para la población femenina). De ahí el interés de tratar de identificar los factores claves de la evolución reciente del empleo regional, cuantificando sus efectos diferenciales por sectores y sexos y elaborando escenarios de futuro para los próximos años.