The regional distribution of Spanish unemployment: A spatial analysis

López‐Bazo, Enrique; Castro, Tomás del Barrio; Artı́s, Manuel

doi:10.1007/s101100200128

Cited by 55 publications

(49 citation statements)

References 19 publications

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“…Some recent contributions have taken into account the spatial dimension of regional labour markets and pointed out the high degree of interdependence of local labour markets (Molho 1995;López-Bazo et al 2002;Overman and Puga 2002). Furthermore, Patacchini and Zenou (2007) analyse the reasons for spatial dependence in local unemployment rates.…”

Section: Introductionmentioning

confidence: 99%

Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions

Mayor

Patuelli

2012

Defining the Spatial Scale in Modern Regional Analysis

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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) 2

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Section: Introductionmentioning

confidence: 99%

Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions

Mayor

Patuelli

2012

Defining the Spatial Scale in Modern Regional Analysis

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“…There is an abundance of empirical literature that tries to explain the differences between geographical areas in terms of unemployment rates (see, e.g., Fischer and Nijkamp 1987;Decressin and Fatás 1995;Jimeno and Bentolila 1998;López-Bazo et al 2002.…”

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confidence: 99%

“…housing, sectorial composition, etc. ); local population and labour demand (see, e.g., Molho 1995;Patridge and Rickman 1997;Niebuhr 2003;López-Bazo et al 2002). In the model proposed, the unemployment is explained by a proxy for labour demand and by some control variables; moreover, to take into account the neighbouring effects of labour markets (see Overman and Puga 2002) spatial econometric tools have been used.…”

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confidence: 99%

“…The applied analyses are mainly based on time series, using standard statistical methods, both parametric and non-parametric (see Decressin and Fatás 1995;Jimeno and Bentolila 1998;Martin 1997;López-Bazo et al 2002). There are only a very few analyses using spatial data and spatial parametric tools (see Molho 1995;Aragon et al 2003;Niebuhr 2003;López-Bazo et al 2002).…”

mentioning

confidence: 99%

“…There are only a very few analyses using spatial data and spatial parametric tools (see Molho 1995;Aragon et al 2003;Niebuhr 2003;López-Bazo et al 2002).…”

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confidence: 99%

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A spatial analysis on Italian unemployment differences

2008

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Using spatial econometric models, this paper focuses attention on the spatial structure of provincial unemployment disparities of Italian provinces for the year 2003. On the basis of findings from the economic literature and of the available socio-economic data, various model specifications including supply-and demandside variables are tested. Further we use ESDA analysis as equivalent to integration analysis on time series; therefore it is applied on each variable, dependent and independent, involved in the statistical model. The suggestions of ESDA lead us to the most adequate statistical model, which estimates indicate that there is a significant degree of neighbouring effect (i.e. positive spatial correlation) among labour markets at the provincial level in Italy; this effect is present notwithstanding we controlled for local characteristics. The unemployment shows a polarized spatial pattern that is strongly connected to labour demand and to a much lesser extent to the share of young population and economic structural composition.

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Self-Employment and Unemployment in Spanish Regions in the Period 1979–2001

Golpe¹,

Stel

2008

International Studies in Entrepreneurship

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis paper investigates the relation between changes in self-employment and changes in unemployment at the regional level in Spain in the period 1979-2001. We estimate a vector autoregression model as proposed by Audretsch, Carree, van Stel and Thurik (2005) using a data base for Spanish regions. By estimating the model we are able to empirically distinguish between two directions of causality. On the one hand increases in selfemployment may contribute to lower unemployment rates (the 'entrepreneurial' effect). On the other hand, higher unemployment rates may push individuals into selfemployment, thereby contributing to higher self-employment rates (the 'refugee' effect). In our analysis of these two effects we distinguish between higher and lower income regions within Spain. We find empirical support for the 'entrepreneurial' effect to exist, both in higher income and in lower income regions. As regards the 'refugee' effect, the evidence is mixed. We find empirical support for this effect for higher income regions. Remarkably, we do not find evidence for a 'refugee' effect in lower income regions of Spain, even though unemployment rates are on average higher in these regions. We argue that this may be partly related to a lack of incentives for unemployed individuals in these regions to find paid employment. JEL-classification: E24, L11, M13, O10, O52

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The regional distribution of Spanish unemployment: A spatial analysis

Cited by 55 publications

References 19 publications

Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions

Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions

A spatial analysis on Italian unemployment differences

Self-Employment and Unemployment in Spanish Regions in the Period 1979–2001

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