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Suicide and socioeconomic determinants in Canada: beyond morality and philosophy

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Abstract

This paper provides new and exciting insight of suicide between genders in Canada for 39 years from a socio-economic perspective. A theoretical framework based on sound economic theory of suicide using Vector Autoregression (VAR) model to establish meaningful relationships between variables incorporated. Additional causality test and beyond sample analysis (forecasting) will be helpful inbeautifying the linkages among the variables employed in this study. It is suggested that both female and male suicidal behaviour can be explained by socio-economic indicators. The findings provide useful insights for policy makers and suicide related agencies to perform a novel approach in dealing with suicides in addition to traditional behavioural correction and counselling strategies in hand. This study should also be helpful in understanding suicide from a broad perspective and analysing suicide in a new economic framework of rational choice theory.

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Fig. 1

Sources: Statistics Canada, CANSIM, Table 102-0551

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Notes

  1. According to Shaver (1990), Canadian suicide rates have been increasing significantly in 1970’s. The suicide rates continue to increase until 1980’s and eventually it reached the highest rate in Canadian’s suicide history.

  2. In the literature survey by Chen et al. (2012), they focus on economic theories of suicide and then present a summary of a variety of empirical studies from the socio-economic perspective of which we includes in the present study. In much more recent literature focussing on Canada provinces, Jalles and Andresen (2015), highlighting the importance of having gender-based suicide rates with the socioeconomics determinants rather than the aggregate ones.

  3. Statistics Canada (2011) (http://www.statcan.gc.ca), Organisation for Economic Co-Operation and Development (http://www.oecd.org), World Economic Outlook published by International Monetary Fund (http://www.imf.org), International Labour Organization (http://www.ilo.org) and U.S. Bureau of Labor Statistics ( http://www.bls.gov).

  4. The cointegration analysis, vector error correction model (VECM) and FORECAST ERROR VARIANCE DECOMPOSITION (FEVD) is a standard analysis that has been discussed extensively in many previous literatures hence will not be explained in detail here. Interested reader may want to refer to the original article of Johansen and Juselius (1990), Granger (1988), Lutkepohl (1991) for further understanding.

  5. The summary of the outcome of the stationarity test is presented here after the comments made by the anonymous referee.

  6. Following the suggestion made by Johansen and Juselius (1990) in the case where both tests produce different outcome, we opt for Maximum Eigenvalue test. In this sense, one cointegrating vector exists in Models 1 and 2.

  7. If cointegration is detected, then the Granger causality must be conducted in VECM to avoid problems of misspecification (Granger 1988). Otherwise, the analyses may be conducted as a standard first difference vector autoregressive (VAR) model.

  8. Although many other short-run relationships can be found from the results, author will only discussed the one related to suicide rate since it is the objectives of this paper. Any by-products relationships from the analysis will not be discussed.

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Acknowledgments

This paper has benefited from the constructive comments from anonymous referee and the editor of this journal. The authors gratefully acknowledges financial support from Universiti Malaysia Sarawak (UNIMAS) Geran Penyelidikan Khas (Top Down) 03(TD04)/1054/2013(02). The usual disclaimer regarding errors and omissions applies.

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Lau, E., Hamzah, S., Tan, S.C.C. et al. Suicide and socioeconomic determinants in Canada: beyond morality and philosophy. Qual Quant 51, 1843–1858 (2017). https://doi.org/10.1007/s11135-016-0370-x

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