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Spatial Filtering And Eigenvector Stability: Space-Time Models For German Unemployment Data

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Author Info
Roberto Patuelli () (University of Lugano, Switzerland The Rimini Centre for Economic Analysis, Rimini, Italy)
Daniel A. Griffith (University of Texas at Dallas, USA)
Michael Tiefelsdorf (University of Texas at Dallas, USA)
Peter Nijkamp (VU University Amsterdam, The Netherlands)

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Abstract

Regions, independent of their geographic level of aggregation, are known to be interrelated partly due to their relative locations. Similar economic performance among regions can be attributed to proximity. Consequently, a proper understanding, and accounting, of spatial liaisons is needed in order to effectively forecast regional economic variables. Several spatial econometric techniques are available in the literature, which deal with the spatial autocorrelation in geographically-referenced data. The experiments carried out in this paper are concerned with the analysis of the spatial autocorrelation observed for unemployment rates in 439 NUTS-3 German districts. We employ a semi-parametric approach – spatial filtering – in order to uncover spatial patterns that are consistently significant over time. We first provide a brief overview of the spatial filtering method and illustrate the data set. Subsequently, we describe the empirical application carried out: that is, the spatial filtering analysis of regional unemployment rates in Germany. Furthermore, we exploit the resulting spatial filter as an explanatory variable in a panel modelling framework. Additional explanatory variables, such as average daily wages, are used in concurrence with the spatial filter. Our experiments show that the computed spatial filters account for most of the residual spatial autocorrelation in the data.

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Publisher Info
Paper provided by Rimini Centre for Economic Analysis in its series Working Paper Series with number 02-09.

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Date of creation: Jan 2009
Date of revision: Jan 2009
Handle: RePEc:rim:rimwps:02-09

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Keywords: spatial filtering; eigenvectors; Germany; unemployment;

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Find related papers by JEL classification:
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data
E24 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution
R12 - Urban, Rural, and Regional Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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This page was last updated on 2009-11-4.

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