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2018 | OriginalPaper | Buchkapitel

Italian Industrial Districts and the 2008 Recession

verfasst von : Giorgio Brunello, Monica Langella

Erschienen in: Agglomeration and Firm Performance

Verlag: Springer International Publishing

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Abstract

Using a “difference-in-differences” approach, we show that the share of entrepreneurs in Italy declined more in industrial districts than in comparable labour markets during the 3 years following the 2008 recession. We have examined alternative explanations of this finding, thus concluding that it is consistent with the idea that intense social interactions typical of industrial districts act as a multiplier that amplifies the response to shocks. However, we cannot exclude that this may translate into a positive effect on employment as the flows from entrepreneurship to employment appear to be greater within industrial districts.

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Vorheriges Kapitel Coping with Economic Crisis: Cluster Associations and Firm Performance in the Basque Country

Nächstes Kapitel Industrial Districts/Clusters and Smart Specialisation Policies

We decided to exclude the South of Italy from this analysis due to the lack of this type of industrial agglomerations in the area. As we will further explain in the remainder of the paper, we also exclude large urban areas and local labour markets that show a limited level of comparability to industrial districts. The reason for this is to increase precision of our estimates, although, as we will discuss including those areas that does not alter the core of our findings.

This is the age range that concentrates the bulk of the entrepreneurial rate. Very few entrepreneurs are observed below the age of 35, and we excluded people aged more than 55 due to high rates of attrition to retirement.

This assumption is consistent with x_f ∈ [0, 1].

Wage bargaining in Italy occurs mainly at the national and sectorial level (Du Caju et al. 2009). Ammermuller (2010) find that wages in Italy do not respond to local unemployment. Guiso and Schivardi (2011) assume that the common wage is determined by the condition that national labour demand equals national labour supply.

Small and medium enterprises are defined by the European Commission as firms having less than 250 employees and an annual turnover of up to EUR 50 million or a balance sheet total of no more than EUR 43 million (Commission Recommendation of May 6 2003). Italian industrial structure is characterised by the prevalence of SME. According to the Italian Statistical Institute (ISTAT), in 2013 the average firm size in Italy is of 3.7 employees.

As discussed below, using a broader definition (self-employment status) does not affect qualitatively our empirical results.

The average share of entrepreneurs with employees in 2006 was 11.5% for individuals aged 35–55, 6.4 for those aged 30–34 and 3.1% for individuals aged 25–29.

We exclude urban areas such as Turin, Milan, Venice, Genoa, Bologna, Florence and Rome. We exclude large urban areas and the South of Italy in order to increase the precision of our estimates. South of Italy is characterised by the lack of the industrial agglomerations we focus on in this chapter, while large urban areas show a different industrial structure with respect to the rest of the country. Including those in the analysis does not substantially alter our results.

Formal tests of the hypothesis that pretreatment tests are parallel are discussed below.

Regional values are from the Italian regional accounts.

The propensity score is defined as e(x) = Pr ob(ID = 1| X = x), the probability of being treated conditional on observables X.

The low rate might seem surprising. Notice however that unemployment in Italy is the highest among those living in the South, who are excluded from our sample.

The number of observations in Table 2, column (1) and Table 3, column (4), slightly differs because of differences in the common support identified by the propensity score.

As in the previous experiments, as a preliminary step, we redefine the common support by excluding exports from the vector of covariates defining the propensity score. We have also experimented with real 2007 exports per local inhabitant rather than log real exports, with no qualitative change. Results are available from the authors upon request.

Measures (a) and (b) are calculated for the time interval of 2004–2005 on the basis of municipal data (source: Banca d’Italia) aggregated at the local labour market level.

Labour pooling as a feature of Italian industrial districts has been investigated by D’Addario, 2011, who finds that living in an ID area increases the probability of finding a job, and by Andini et al. (2012), who conclude that the two concepts are broadly unrelated.

The estimated differential effect for the inactive (column (2) of the table) is very small and imprecisely estimated.

These rates are computed by dividing the flows by the state variable in the previous year.

Similar qualitative patterns emerge for inflows from out of the labour force to entrepreneurship.

See De Blasio and Di Addario (2005).

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Titel: Italian Industrial Districts and the 2008 Recession
verfasst von: Giorgio Brunello
Monica Langella
Verlag: Springer International Publishing
Buch: Agglomeration and Firm Performance
Print ISBN: 978-3-319-90574-7

Electronic ISBN: 978-3-319-90575-4

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-90575-4_15

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