An empirical puzzle: Falling migration and growing unemployment differentials among Italian regions

Faini, Riccardo; Galli, Giampaolo; Gennari, Pietro; Rossi, Fulvio

doi:10.1016/s0014-2921(97)00023-8

Cited by 176 publications

(127 citation statements)

References 3 publications

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“…Italy (Faini, Galli, Gennari, and Rossi, 1997) and that economic activity in Italy is less concentrated than in some other countries. For instance, the four most populated Italian cities host less than 20% of the national population whereas in the uk or France, the same proportion is attained by the largest city only.…”

Section: Our Main Estimating Equation Ismentioning

confidence: 94%

Marshallian labour market pooling: Evidence from Italy

Andini

Blasio

Duranton

et al. 2013

Regional Science and Urban Economics

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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

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Section: Our Main Estimating Equation Ismentioning

confidence: 94%

Marshallian labour market pooling: Evidence from Italy

Andini

Blasio

Duranton

et al. 2013

Regional Science and Urban Economics

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“…This pattern of migration between the mid-1970s and mid-1990s has been termed the 'empirical puzzle' (Faini et al, 1997), in that while major differences still persisted between high unemployment rates in the south and low unemployment rates in the north, southÁnorth migration rates were surprisingly low, and in particular much lower than in the previous decades. The reasons for this slow down in migration between the mid-1970s and mid-1990s are still not entirely clear and various explanations have been put forward, including the role of public sector investment in southern regions (Attanasio & Padoa-Schioppa, 1991), increasing northÁsouth house price differentials (Cannari et al, 2000), the growth in the absolute living standards in the south (Faini & Venturini, 1994), inefficiencies in interregional job matching processes (Casavola & Sestito, 1993;Faini et al, 1997), and changes in industrial structures and systems (Murat & Paba, 2001).…”

Section: Interregional Migration In Italymentioning

confidence: 99%

“…The reasons for this slow down in migration between the mid-1970s and mid-1990s are still not entirely clear and various explanations have been put forward, including the role of public sector investment in southern regions (Attanasio & Padoa-Schioppa, 1991), increasing northÁsouth house price differentials (Cannari et al, 2000), the growth in the absolute living standards in the south (Faini & Venturini, 1994), inefficiencies in interregional job matching processes (Casavola & Sestito, 1993;Faini et al, 1997), and changes in industrial structures and systems (Murat & Paba, 2001). …”

Section: Interregional Migration In Italymentioning

confidence: 99%

“…Such a detailed analysis has not been done before for the Italian case. Most migration research in Italy has examined interregional flows among larger areas, either regions or groups of regions, and has not examined the differences in the determinants of movements of different lengths (Attanasio & Padoa-Schioppa, 1991;Faini et al, 1997;Daveri & Faini, 1999;Cannari et al, 2000;Furceri, 2006;Basile & Causi, 2007;Etzo, 2008).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Long and Short Distance Migration in Italy: The Role of Economic, Social and Environmental Characteristics

Biagi

Faggian

McCann

2011

Spatial Economic Analysis

159

136

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This paper analyses Italian interregional migration flows. The approach taken is to decompose labour mobility flows into short distance and long distance migration and to model the effects of economic variables, social capital and quality of life variables, and amenity variables, on the mobility behaviour of individuals. We estimate these different types of migration flows using a negative binomial model, augmented with instruments to control for potential endogeneity issues. Our findings demonstrate that long distance migration reflects a disequilibrium model of migration whereas short distance migration largely reflects an equilibrium model of migration. As such, attempts to model interregional migration in general will be mis-specified as the simultaneously-operating underlying mobility systems are quite different in nature.Migration éloignée et rapprochée en Italie : rôle de facteurs économiques, sociaux et environnementaux RÉ SUMÉ La présente communication analyse les flux migratoires interrégionaux en Italie. Le principe adopté consiste à décomposer les flux de mobilité de la main-d'oeuvre en migrations rapprochée et migration éloignée, puis de modéliser les effets de variables économiques, de variables propres au capital social et à la qualité de vie, et de variables sur le plan de l'agrément sur le comportement de la mobilité des particuliers. Nous effectuons une estimation de ces différents types de flux migratoires en utilisant un modèle binomial négatif, renforcé par des instruments pour le contrôle de questions d'endogénéité potentielles. Nos conclusions démontrent que la migration éloignée reflète un modèle de déséquilibre de la migration, alors que la migration rapprochée reflète en grand partie un modèle déséquilibre de la migration. De cette façon, toutes tentatives de modélisation de migrations interrégionales seront spécifiées de façon erronée, du fait de la nature différente des systèmes de mobilité sous-jacents agissant simultanément. Spatial Economic Analysis, Vol. 6, No. 1, March 2011La migración de larga y corta distancia en Italia: el papel de las características económicas, sociales y ambientales RESUMEN En este trabajo se analizan los flujos migratorios interregionales de Italia. El método adoptado es la descomposición de los flujos de movilidad laboral en migración de corta y migración de larga distancia, y modelar los efectos de las variables económicas, las variables de capital social y de calidad de vida, y las variables de bienestar, con base en el comportamiento de la movilidad de los individuos. Estimamos estos tipos de flujos migratorios diferentes a través de un modelo binomial negativo, ampliado con instrumentos que permiten controlar los posibles problemas de endogeneidad. Nuestras conclusiones demuestran que la migración de larga distancia refleja un modelo desequilibrado de migración, mientras que la migración de corta distancia refleja en gran medida un modelo equilibrado de migración. Como tal, los intentos para modelar la migración interregional, en términos gen...

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“…High unemployment Italy had comparatively low mobility (1.1%) in 1970 and which actually fell to 0.5% in 1987. Mobility is low and unemployment-especially youth unemployment-is particularly high in Italy (32% in 1998): Faini et al (1997) have shown that migrations between northern and southern Italy declined steadily from 1970 to 1990. The 1990 level was approximately one seventh the 1970 level.…”

Section: What Can Be Done To Reduce Unemployment In Eastern and Centrmentioning

confidence: 99%