Economic factors and suicide rates: associations over time in four countries



Suicides account for more than 30,000 deaths per year in the US alone. Suicide rates change over time, and the factors influencing them remain poorly understood. Economic factors, in particular unemployment, have been suggested as a major influence. However, the evidence for this has been inconsistent, which may be partly explained by shortcomings of the statistical methods used.


Time series analytical techniques (unit root and co-integration tests) were applied to test the associations over time between economic factors, i.e. unemployment, real gross domestic product per capita (RGDP) and the consumer price index (CPI) and death rates by suicide as collected by national agencies in the UK (1901–2006), US (1900–1997), France (1970–2004) and Italy (1970–2001). Traditional correlation analyses were used when appropriate.


Co-integration and correlation tests showed a long-run association between economic factors and suicide rates. Increase/decrease of unemployment predicted an increase/decrease of suicide rates over long historical periods and in different nations. RGDP and the CPI were also linked with suicide rates, but this was not consistently so and the direction of the association varied.


Unemployment is a major factor influencing suicide rates over long periods of time and in different national contexts. It needs to be considered as a confounding factor in evaluations of suicide prevention strategies.

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  1. 1.

    In Table 1, we report the co-integrating vector only if the null hypothesis of no co-integration (i.e. r = 0) was rejected at the 5% significance level, whereas the null hypothesis r = 1 was not rejected at the 10% significance level. For instance the standardised co-integrating vector reported for France female population, SU bivariate comparison “S − 0.30MA7(U)” means that the generalised Eigenvectors of A with respect to (A + c[A −1]/n 2)−1 for n = 4 and c = 1 are

    $$ \begin{array}{*{20}c} {0.30} \hfill & 1 \hfill \\ 1 \hfill & { - 0.30} \hfill \\ \end{array} $$

    The last Eigenvector spans the space of co-integrating vectors and the space of co-integrating vectors is spanned by the following standardised vector

    $$ \begin{array}{*{20}c} 1 \hfill & { \to {\text{Suicide}},\,{\text{females}},\,{\text{both}}\,{\text{sexes}}} \hfill \\ { - 0.30} \hfill & { \to {\text{Mov}} . {\text{Aver}}.7[U]} \hfill \\ \end{array} $$

    Regarding the direction of the association, if the sign of socio-economic variables was the opposite of S, the model predicted changes in the same direction, whilst the same sign predicted changes in the opposite direction.

  2. 2.

    In Table 2 we report a summary of pair-wise Johansen’s tests of co-integration among rates of suicide and economic variables. For brevity we reported only the error correction term whenever the null hypothesis of no co-integration (i.e. r = 0) was rejected at the 5% significance level (lambda-max test) and the null hypothesis r = 1 is not rejected at the 10% significance level (trace test) of a vector error correction model (VECM) with intercepts and co-integrating restrictions. The Standardised co-integrating vector is not reported in the tables but it can be easily derived from the error correction term. For instance in the co-integration model of S and U in France, the error correction term is S(−1) − 0.66MA7[U](−1) − 0.001(t − 1), and therefore the standardised co-integrating vector is S − 0.66MA7[U] − 0.001t, where MA7 stands for moving average after 7 periods.


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Correspondence to Stefan Priebe.

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Ceccherini-Nelli, A., Priebe, S. Economic factors and suicide rates: associations over time in four countries. Soc Psychiatry Psychiatr Epidemiol 46, 975–982 (2011).

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  • Suicide
  • Economic factors
  • Unemployment
  • Time factors