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Unemployment and suicide in Italy: evidence of a long-run association mitigated by public unemployment spending

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Abstract

From the mid-1990s on, the suicide rate in Italy declined steadily, then apparently rose again after the onset of the Great Recession, along with a sharp increase in unemployment. The aim of this study is to test the association between the suicide rate and unemployment (i.e., the unemployment rate for males and females in the period 1977–2015, and the long-term unemployment rate in the period 1983–2012) in Italy, by means of cointegration techniques. The analysis was adjusted for public unemployment spending (referring to the period 1980–2012). The study identified a long-run relationship between the suicide rate and long-term unemployment. On the other hand, an association between suicide and unemployment rate emerged, though statistically weaker. A 1% increase in long-term unemployment increases the suicide rate by 0.83%, with a long-term effect lasting up to 18 years. Public unemployment spending (as percentage of the Italian gross domestic product) may mitigate this association: when its annual growth rate is higher than 0.18%, no impact of unemployment on suicide in detectable. A decrease in the suicide rate is expected for higher amounts of social spending, which may be able to compensate for the reduced level of social integration resulting from unemployment, helping the individual to continue to integrate into society. A corollary of this is that austerity in times of economic recession may exacerbate the impact of the economic downturn on mental health. However, a specific “flexicurity” system (intended as a combination of high employment protection, job satisfaction and labour-market policies) may have a positive impact on health.

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Source: Istat [1]

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Notes

  1. See Stock and Watson [36] for details.

  2. In the Johansen procedure, ECM models are estimated from a vector autoregression representation of the variables (VAR). For this reason in this section we refer to the VAR lag length to test for cointegration. Note that there is a correspondence between the VAR lag structure and the lags in the ECM. For example a VAR(2), i.e., a model with two lags, corresponds to an ECM (1), i.e., with one lag in the variables. AIC: Akaike information criterion; BIC: Schwartz information criterion; HQC:Hannan-Quinn criterion.

  3. The convergence to a particular lag structure depends on the parametrization of the starting model used, hence we use a reduction strategy from a VAR(5) to VAR(2) to choose the final VAR lag length. This reduction strategy is available upon request to the authors. When there is no convergence in indicating the lag length, Table 2 shows the cointegration results for all VAR models suggested by each criterium or combination of criteria.

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Acknowledgements

The authors wish to thank Prof. William J. Bromwich for the linguistic revision of the manuscript. The authors also thank Marcello D’Amato and Andrea Marchioni for their useful suggestions. Barbara Pistoresi gratefully acknowledges the financial support provided by Fondo per le Agevolazioni alla Ricerca (FAR) 2017 provided by the University of Modena and Reggio Emilia, Italy.

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Authors and Affiliations

  1. Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via G. Campi, 287, 41125, Modena, Italy

    Giorgio Mattei

  2. Department of Economics and Marco Biagi Foundation, University of Modena and Reggio Emilia, Via J. Berengario, 51, 41121, Modena, Italy

    Giorgio Mattei

  3. Department of Economics and ReCent, University of Modena and Reggio Emilia, Viale Berengario 51, Modena, Italy

    Barbara Pistoresi

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  1. Giorgio Mattei
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Correspondence to Giorgio Mattei.

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Mattei, G., Pistoresi, B. Unemployment and suicide in Italy: evidence of a long-run association mitigated by public unemployment spending. Eur J Health Econ 20, 569–577 (2019). https://doi.org/10.1007/s10198-018-1018-7

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