Accessible Unlicensed Requires Authentication Published by De Gruyter January 17, 2019

Do Local Institutions Affect Labour Market Participation? The Italian Case

Massimiliano Agovino, Antonio Garofalo and Massimiliano Cerciello

Abstract

Italy features very low labour market participation rates for both men and women, coupled with a sizeable participation gender gap. This work investigates empirically the relation between institutional quality and labour market participation at the local level. Using official records on the Italian provinces over the 2004–2012 timespan and the Institutional Quality Index, we use a Spatial Lag of X model to gauge the direct and indirect impact of local institutions on male and female participation rates, with particular regard to the participation gender gap. The results support the idea that institutional quality has a significant impact on local labour market participation, for both men and women, while it does not affect the participation gap. Moreover, institutions generate spatial spillovers, affecting participation in neighbouring provinces. Finally, the availability of public child care facilities is as a key determinant of female participation.

JEL Classification: J16; R12; R23

Appendix

A Historical Distribution of Local Language Families

When studying the local languages of Italy, modern linguists count more than 30 distinct languages (Coluzzi 2009). However, some of them belong to the same family and are mutually intelligible. This is why we narrow down the analysis to ten families:

  1. Sicilian, located in Sicily and in the southernmost areas of mainland Italy;

  2. Neapolitan-Calabrese, spoken in the rest of the South and in parts of Central Italy;

  3. Sardinian and Corso-Sardinian, featured in Sardinia;

  4. Central Italian, spoken in Latium, Umbria, most of Marche and part of Tuscany;

  5. Tuscanian, spoken in Tuscany;

  6. The Gallo-Italic family, found in many varieties in Northern and North-Western Italy;

  7. Venetian, typical of Veneto;

  8. Friulian/Ladin, limited to the North-Eastern border with Slovenia;

  9. Tirolese, spoken by the German minority in Sudtirol;

  10. Franco-Provençal, spoken in Val d’Aosta.

For each local language, we introduce a dummy variable that takes value 1 if the language is the most spoken in the local province and 0 otherwise. The local languages are mapped in Figure 8.

Figure 8: Local language families across Italy.Source:Tagliavini (1964).

Figure 8:

Local language families across Italy.

Source:Tagliavini (1964).

IQI Exogeneity: Second Stage Estimates

To ascertain the exogeneity of the IQI, we instrument it with the language dummies and then we compare the robust estimator but inefficient estimator obtained with the more efficient estimator computed from our main regressions in Table 3. The Hausman tests in Table 4 fail to reject the null hypothesis of consistency for both estimators, indicating that the IQI is exogenous.

Table 4:

Hausman tests for the IQI.

Queen ContiguityCommuting Proximity
MenWomenGapMenWomenGap
Hausman Test1.138.314.161.844.1210.3
(0.862)(0.220)(0.545)(0.782)(0.664)(0.189)
N824824824824824824
Economic ProximityInstitutional Proximity
MenWomenGapMenWomenGap
Hausman Test3.125.228.034.413.896.76
(0.703)(0.331)(0.168)(0.519)(0.402)(0.236)
N824824824824824824

  1. * p < 0.1; ** p < 0.05; *** p < 0.01

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Published Online: 2019-01-17

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