Marshallian labour market pooling: Evidence from Italy

Abstract

This paper employs a unique Italian data source to take a comprehensive approach to labour market pooling. It jointly considers many different aspects of the agglomeration -labour market relationship, including turnover, learning, matching, and hold up. It also considers labour market pooling from the perspective of both workers and firms and across a range of industries. Overall, the paper finds some support for theories of labour market pooling, but the support is weak. Specifically, there is a general positive relationship of turnover to local population density, which is consistent with theories of agglomeration and uncertainty. There is also evidence of on-the-job learning that is consistent with theories of labour pooling, labour poaching, and hold up. In addition, the paper provides evidence consistent with agglomeration improving job matches. However, the labour market pooling gains that we measure are small in magnitude and seem unlikely to account for a substantial share of the agglomeration benefits accruing to Italian workers and firms. Abstract: This paper employs a unique Italian data source to take a comprehensive approach to labor market pooling. It jointly considers many different aspects of the agglomeration -labor market relationship, including turnover, learning, matching, and hold up. It also considers labor market pooling from the perspective of both workers and firms and across a range of industries. Overall, the paper finds some support for theories of labor market pooling, but the support is weak. Specifically, there is a general positive relationship of turnover to local population density, which is consistent with theories of agglomeration and uncertainty. There is also evidence of on-the-job learning that is consistent with theories of labor pooling, labor poaching, and hold up. In addition, the paper provides evidence consistent with agglomeration improving job matches. However, the labor market pooling gains that we measure are small in magnitude and seem unlikely to account for a substantial share of the agglomeration benefits accruing to Italian worker and firms.Key words: local labor markets, matching, turnover, learning, hold-up, agglomeration jel classification: r23, j60 * We are deeply indebted to the researchers in the Statistics Department of the Bank of Italy who helped us to phrase the questions included in the shiw and sisf special sections on local labor markets. Our sincere thanks as well go to

Apprentice Poaching in Regional Labor Markets

“…Brunello and Gambarotto (2007) for example find a negative relationship between regional employment density, as well as industrial specialization, and employer-provided training in the UK. Similarly, Brunello and De Paola (2008) and Andini et al (2013) detect a negative relationship between regional employment density and firmsponsored training in Italy. Most closely related to our study, Mühlemann and Wolter (2011) find for Switzerland that the density of firms in the same region and industry is negatively related to firms' apprenticeship training activity.…”

“…Against this background, and because within-industry and within-occupation mobility allows for a better transfer of skills and knowledge acquired on the job, employers in dense regional labor markets are expected to be particularly reluctant to provide training to their workers. Empirical studies indeed find a negative relationship between regional competition and firm-sponsored training (Brunello and Gambarotto, 2007;Brunello and De Paola, 2008;Mühlemann and Wolter, 2011;Andini et al, 2013). …”

“…Similar results are obtained by Mühlemann, Ryan, and Wolter (2013) and Hirsch, Jahn, and Oberfichtner (2016), who also find that wages are higher in denser (and hence more competitive) regions, in order to limit the turnover of skilled employees. Moreover, there is ample evidence that worker mobility in dense regional labor markets is concentrated within industries and occupations (Bleakley and Lin, 2012;Andini et al, 2013), that is, dense regional labor markets allow for a better skill match between workers and firms (as predicted by theories of agglomeration advantages). Against this background, and because within-industry and within-occupation mobility allows for a better transfer of skills and knowledge acquired on the job, employers in dense regional labor markets are expected to be particularly reluctant to provide training to their workers.…”

Agglomeration Effect of Skill-Based Local Labor Pooling: Evidence of South Korea

“…Abel and Deitz [8] provided empirical findings that a thick labor market helps college graduates in the United States find jobs that more closely match their education. Andini et al [13] examined four aspects of local labor pools, including turnover, learning, matching, and hold up, and their Italian empirical analysis showed a positive association between turnover and on-the-job training and labor market density. Roca and Ruga [14] argued that workers accumulate their human capital in large cities.…”

Local agglomeration, entrepreneurship and the 2008 recession: Evidence from Italian industrial districts

“…We also find that in industrial districts, the increase in the flows from entrepreneurship to employment after the crisis is driven mainly by flows within the same industrial sector (from 0.65 to 1.29 percent), contrary to other areas, where these flows have declined (from 0.71 to 0.36 percent), suggesting that the agglomeration of firms in a dominant manufacturing industry -a typical feature of industrial districtscreates a pooled market for specialized workers and entrepreneurs with industry -specific skills, which 26 Labour pooling as a feature of Italian industrial districts has been investigated by Di Addario, 2011, who finds that living in an ID area increases the probability of finding a job, and by Andini, De Blasio, Duranton and Strange, 2012, who conclude that labour pooling and ID are broadly unrelated. 27 The estimated differential effect for the inactive (column (2) of the table) is very small and imprecisely estimated.…”