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PERSISTENCE OF REGIONAL UNEMPLOYMENT: APPLICATION OF A SPATIAL FILTERING APPROACH TO LOCAL LABOR MARKETS IN GERMANY

Authors


  • The first author wishes to thank Paolo Foschi and Simone Giannerini (University of Bologna, Italy), as well as Cristian Bianchi, Alberto Ferrante, and Alex Villazon (University of Lugano, Switzerland), for their help in executing the computational problems encountered during the preparation of this paper. We also wish to thank, for useful comments and suggestions, the editor, three anonymous referees, participants to seminars at VU University Amsterdam and the University of Lugano, and to sessions at the 55th Annual North American Meetings of the Regional Science Association International (New York, NY), the 49th European Congress of the Regional Science Association International (Łódź), the ZEW/IAB Workshop on Spatial Dimensions of the Labour Market (Mannheim), the SSES Annual Meeting 2010 (Fribourg), and the 16th International Conference on Panel Data (Amsterdam).

Abstract

ABSTRACT The geographical distribution and persistence of regional/local unemployment rates in heterogeneous economies (such as Germany) have been, in recent years, the subject of various theoretical and empirical studies. Several researchers have shown an interest in analyzing the dynamic adjustment processes of unemployment and the average degree of dependence of the current unemployment rates or gross domestic product from the ones observed in the past. In this paper, we present a new econometric approach to the study of regional unemployment persistence, in order to account for spatial heterogeneity and/or spatial autocorrelation in both the levels and the dynamics of unemployment. First, we propose an econometric procedure suggesting the use of spatial filtering techniques as a substitute for fixed effects in a panel estimation framework. The spatial filter computed here is a proxy for spatially distributed region-specific information (e.g., the endowment of natural resources, or the size of the “home market”) that is usually incorporated in the fixed effects coefficients. The advantages of our proposed procedure are that the spatial filter, by incorporating region-specific information that generates spatial autocorrelation, frees up degrees of freedom, simultaneously corrects for time-stable spatial autocorrelation in the residuals, and provides insights about the spatial patterns in regional adjustment processes. We present several experiments in order to investigate the spatial pattern of the heterogeneous autoregressive coefficients estimated for unemployment data for German NUTS-3 regions. We find widely heterogeneous but generally high persistence in regional unemployment rates.

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