A Spatial-dependence Continuous-time Model for Regional Unemployment in Germany PDF Download
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Languages : en
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This paper analyzes patterns of regional labour market development in Germany over the period 2000-2003 by means of a spatial-dependence continuous-time model. (Spatial) panel data are routinely modelled in discrete time. However, there are compelling arguments for continuous time modelling of (spatial) panel data. Particularly, most social processes evolve in continuous time such that analysis in discrete time is an oversimplification, gives a distorted representation of reality and leads to misinterpretation of estimation results. The most compelling reason for continuous time modelling is that, in contrast to discrete time modelling, it allows for adequate modelling of dynamic adjustment processes (see, for example, Special Issue 62:1, 2008, of Statistica Neerlandica). We introduce spatial dependence in a continuous time modelling framework and apply the unified framework to regional labour market development in Germany. The empirical results show substantial autoregressive effects for unemployment and population development, as well as a negative effect of unemployment development on population development. The reverse effect is not significant. Neither are the effects of the development of regional average wages and of the manufacturing sector on the development of unemployment and population.
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Languages : en
Pages :
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Book Description
This paper analyzes patterns of regional labour market development in Germany over the period 2000-2003 by means of a spatial-dependence continuous-time model. (Spatial) panel data are routinely modelled in discrete time. However, there are compelling arguments for continuous time modelling of (spatial) panel data. Particularly, most social processes evolve in continuous time such that analysis in discrete time is an oversimplification, gives a distorted representation of reality and leads to misinterpretation of estimation results. The most compelling reason for continuous time modelling is that, in contrast to discrete time modelling, it allows for adequate modelling of dynamic adjustment processes (see, for example, Special Issue 62:1, 2008, of Statistica Neerlandica). We introduce spatial dependence in a continuous time modelling framework and apply the unified framework to regional labour market development in Germany. The empirical results show substantial autoregressive effects for unemployment and population development, as well as a negative effect of unemployment development on population development. The reverse effect is not significant. Neither are the effects of the development of regional average wages and of the manufacturing sector on the development of unemployment and population.
Author: Annekatrin Niebuhr
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Languages : en
Pages : 29
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Languages : en
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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.
Author: Norbert Schanne
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ISBN: 9783763940950
Category :
Languages : en
Pages : 204
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Author: Roberto Patuelli
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Category :
Languages : en
Pages : 0
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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 article 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.
Author: Roberto Patuelli
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Languages : en
Pages : 0
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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 analysing 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 parameters. 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 parameters estimated for unemployment data for German NUTS-3 regions. We find widely heterogeneous but generally high persistence in regional unemployment rates.
Author: René Fahr
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ISBN:
Category :
Languages : en
Pages : 40
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Author: Eleonora Patacchini
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Languages : en
Pages :
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By explicitly considering the spatial dimension of local regional labor markets, we develop a simple dynamic model that explains the spatial correlation between unemployment rates. We then test this model by using UK local data. Our evidence shows a significant spatial dependence that has been growing over time and characterized by a low distance decay. Highly localized effects are explained by commuting flows. These results are consistent with the theoretical model.
Author: Christian Oberst
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ISBN:
Category :
Languages : en
Pages : 39
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Author: Norbert Schanne
Publisher: wbv Media GmbH & Company KG
ISBN: 3763940960
Category : Law
Languages : en
Pages : 209
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Warum sollen Regionen innerhalb eines Landes unabhängige Inseln sein? Und warum sollen, über das gesamte Land hinweg, einheitlich starke ökonomische oder soziale Wirkungszusammenhänge bestehen? Diese zwei Annahmen werden in der angewandten empirischen Wirtschafts- und Sozialforschung üblicherweise implizit unterstellt. Wie in statistischen Verfahren von dieser unrealistischen Modellstruktur unter Ausnutzung der räumlichen Strukturen in beobachteten Variablen und unterstellten Zusammenhängen abgewichen werden kann, diskutiert Norbert Schanne im vorliegenden Band. Möglichkeiten, unser Verständnis der Ökonomie zu vertiefen, werden ebenso verdeutlicht, wie Chancen und Tücken beim Einsatz der Methoden in Studien zu verschiedenen Aspekten der Arbeitsmarktdynamik.
