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Social Indicators Research
Erschienen in: Social Indicators Research 1/2016

24.09.2015

Industrial Districts and Socio-economic Well-Being: An Investigation on the Italian Provinces Disparities

verfasst von: Claudio Di Berardino, Giuseppe Mauro, Davide Quaglione, Alessandro Sarra

Erschienen in: Social Indicators Research | Ausgabe 1/2016

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Abstract

This paper examines the territorial disparities between Italian provinces through an alternative measure (well-being composite index) as opposed to traditional ones (value added), in order to assess the possible industrial district (ID) effect on growth performance. The analysis shows that the ID effect is absent when considering (per capita) value added growth, which confirms recent empirical evidence, while it is significant when considering well-being. Furthermore, “highly ID provinces” show a relatively better performance in terms of population growth rates, which, combined with their better socio-economic conditions, sheds new light on the explanation of the persistence of Italian disparities and gives interesting insights for the design of sounder local policy measures.
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Fußnoten
1
See Jordá and Sarabia (2015) for a discussion of the concept of convergence in well-being.
 
2
In fact, as stated in the Stiglitz Report (Stiglitz et al. 2009: 8), “the GDP is not wrong as such, but wrongly used. What is needed is a better understanding of the appropriate use of each measure”; or, Costanza et al. (2009: 4) “it is also important to recognize that GDP is not inherently bad—it measures what it measures. Rather it is being misused as an indicator of something it doesn’t measure and was never intended to measure”.
 
3
Especially with reference to the European Union, the European Commission (Commission of the European Communities 2009) has promoted many initiatives on the issue of well-being aimed at rethinking policies on economic and human development.
 
4
The authors develop new sub-indices in line with the guidelines suggested by Stiglitz et al. (2009) and the OECD (2011). The new dimensions taken into account in the construction of the aggregate index of well-being reflect the most important information resulting from the analysis of Italian disparities conducted on a wide range of economic, social and civic indicators (Banca d’Italia 2010).
 
5
There are studies in the literature that deal with similar issues. However, these studies do not address the question of whether IDs have any effects on socio-economic growth performance, rather they assess the role of social factors as originators of IDs (Di Giacinto and Nuzzo 2005; Micucci and Nuzzo 2005; Signorini and Omiccioli 2005).
 
6
Becattini (1989: 112) defined an ID as “socio-economic territorial entity characterized by the active co-presence—in a geographically limited, historically and naturalistically defined area—of a community of people and a population of industrial enterprises that have internalized a system of values and of rules of behavior that foster competition and cooperation among local businesses” [authors note: our translation].
 
7
As emphasized by Munda (2013), well-being is a very complex and fuzzy concept, and a reduction of this complexity through indicators and indexes is a necessary precondition for policy making. In such a multi-dimensional framework, the construction of composite indicators can be consistently based on the multi-criteria evaluation. However, composite indicators may present several risks, such as oversimplification, inappropriate policy insights and biased results caused by hidden subjective assumptions.
 
8
It is worth noting that the choice of the variables that eventually enter into the calculation of the indices represent a compromise between the availability of statistical data (provided by ISTAT) and the need that they be representative enough of the observed phenomena (Grasso 2002).
 
9
This value is determined by considering that the index proposed by UNDP refers to a $40,000 upper threshold.
 
10
For further details see the book edited by Signorini and Omiccioli (2005) and in particular the included contribution by De Arcangelis and Ferri (2005), who adopt similar methodologies to assess the ID effect.
 
11
The relatively short time period (2000–2007) analysed suggests caution in the interpretation of the results. However, the equation must be considered as valid, given that the model is based on an approximation around the steady state and it is consequently supposed to capture the transition dynamics around the steady state (Durlauf et al. 2005; Islam 1995).
 
12
Italian provinces show, in fact, big differences in terms of population size, which ranges from a minimum value of 58,000 to a maximum value of 3.7 million inhabitants.
 
13
If the new control variable is statistically significant and the coefficient b has a higher value, this means that the “ID provinces” are characterised by higher performances in terms of disparities reduction.
 
14
These results are confirmed even when the dummies (DIS and DIS_HIGH) are tested individually.
 
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Metadaten
Titel
Industrial Districts and Socio-economic Well-Being: An Investigation on the Italian Provinces Disparities
verfasst von
Claudio Di Berardino
Giuseppe Mauro
Davide Quaglione
Alessandro Sarra
Publikationsdatum
24.09.2015
Verlag
Springer Netherlands
Erschienen in
Social Indicators Research / Ausgabe 1/2016
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI
https://doi.org/10.1007/s11205-015-1105-4

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