An Empirical Analysis of Natural and Cyclical Unemployment at the Provincial Level in Spain

Abstract

The differences in the regional unemployment rates, as well as their formation mechanism and persistence, have given rise to a great number of papers in the last decades. This work contributes to that strand of literature from two different perspectives. In the first part of our work, we follow the methodological proposal established by Hofler and Murphy (1989) and Aysun et al. (2014). We make use of an estimation of a stochastic cost frontier to breakdown the Spanish provincial effective unemployment (NUTS-3) in two different components: first one associated with aggregate supply side factors, and the other one more related to the aggregate demand side factors. The second part of our research analyzes the existence of spatial dependence patterns among the Spanish provinces in the effective unemployment and in both above mentioned components. The decomposition performed in the first part of our research will let us know the margin that the policymakers have when they deal with unemployment reductions by means of aggregate supply and aggregate demand policies. Finally, the spatial analysis of the unemployment rates amongst the Spanish provinces can potentially have also significant implications from an economic policy viewpoint since we find that there are common formation patterns or clusters of unemployment.

Regional unemployment and cyclical sensitivity in Spain

“…This pattern reveals, moreover, that regions with higher unemployment rates are not the most sensitive. Our results are in line with the new side of the literature indicating that the regional-specific unemployment rate is not important at all in the unemployment trend but that geographical factors do matter (Cuéllar-Martín et al 2019). In this vein, Camacho et al (2018) also find a geographical pattern in the propagation of economic crisis and the way the unemployment rate reacts to recessions.…”

“…Focusing on Spain, there are large differences in the unemployment rate among regions (Bande et al 2008;Cuéllar-Martín et al 2019) becoming more persistent over time, and bigger after the last economic crisis (Jimeno and Bentolila 1998;Albulescu and Tiwari 2018). So that, it is necessary to pay attention to these differences and address them in terms of cyclical sensitivity.…”

“…Regional unemployment and cyclical sensitivity in Spain cyclical sensibility based on dividing regions with high and low unemployment (Bande and Karanassou 2009;Sala and Trivín 2014) . Other block of researches focuses on doing spatial analyses of unemployment disparities to find clusters of similar behaviors (Cuéllar-Martín et al 2019). Finally, some papers have focused on looking for regional characteristics that motivate regional differences (López-Bazo and Motellón 2013;Melguizo 2017).…”

Crisis, Adjustment and Resilience in the Greek Labor Market: An Unemployment Decomposition Approach

“… 2. Other analyses of regional unemployment evolutions include structural models seeking to decompose the cyclical and structural components of unemployment (Aysun, Bouvet, and Hofler 2014; Cuéllar-Martín, Martín-Román, and Moral 2019) and spatial models exploring cross-regional spillover effects (Patacchini and Zenou 2007; Cracolici,Cuffaro, and Nijkamp 2007; Halleck-Vega and Elhorst 2016). …”

Labor supply and the business cycle: The “bandwagon worker effect”

“…More specifically, the role played by space in the analysis of different topics concerning the labour market at the macro level has attracted much attention. For instance, studies have analysed the differences in the unemployment rates among territories (e.g., countries, regions) and their persistence in time (Molho, 1995; Jimeno & Bentolila, 1998; Overman & Puga, 2002; López‐Bazo, Barrio, & Artis, 2002; López‐Bazo, Barrio, & Artís, 2005; Filiztekin, 2009; Kondo, 2015; Halleck‐Vega & Elhorst, 2016; Cuéllar‐Martín, Martín‐Román, & Moral de Blas, 2019). Furthermore, other studies have focused on the role that space plays in the process of matching individuals in the labour market (Haller & Heuermann, 2016).…”