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Getting Stuck in the Blues: Persistence of Mental Health Problems in Australia

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  • Roy, John

    (Victoria University of Wellington)

  • Schurer, Stefanie

    (University of Sydney)

Abstract

Do episodes of mental health problems cause future mental health problems, and if yes, how strong are these dynamics? We quantify the degree of persistence in mental health problems using nationally-representative, longitudinal data from Australia and system GMM-IV and correlated random effects approaches are applied to separate true from spurious state dependence. Our results suggest only a moderate degree of persistence in mental health problems when assuming that persistence is constant across the mental health distribution once individual-specific heterogeneity is accounted for. However, individuals who fell once below a threshold that indicates an episode of depression are up to five times more likely to experience such a low score again a year later, indicating a strong element of state dependence in depression. Low income is a strong risk factor in state dependence for both men and women, which has important policy implications.

Suggested Citation

  • Roy, John & Schurer, Stefanie, 2013. "Getting Stuck in the Blues: Persistence of Mental Health Problems in Australia," IZA Discussion Papers 7451, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp7451
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    Cited by:

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    2. Ohrnberger, Julius & Fichera, Eleonora & Sutton, Matt, 2017. "The dynamics of physical and mental health in the older population," The Journal of the Economics of Ageing, Elsevier, vol. 9(C), pages 52-62.
    3. Dias, Mateus & Fontes, Luiz Felipe, 2020. "The Effects of a Large-Scale Mental-Health Reform: Evidence from Brazil," MPRA Paper 104753, University Library of Munich, Germany.
    4. Chris Muris & Pedro Raposo & Sotiris Vandoros, 2020. "A dynamic ordered logit model with fixed effects," Papers 2008.05517, arXiv.org.
    5. David W. Johnston & Olena Stavrunova, 2021. "Subjective Wellbeing Dynamics," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 54(4), pages 518-529, December.
    6. Tran, My (Michelle) & Gannon, Brenda, 2021. "The regional effect of the consumer directed care model for older people in Australia," Social Science & Medicine, Elsevier, vol. 280(C).
    7. Bom, Judith & Bakx, Pieter & Schut, Frederik & van Doorslaer, Eddy, 2019. "Health effects of caring for and about parents and spouses," The Journal of the Economics of Ageing, Elsevier, vol. 14(C).
    8. Daghagh Yazd, Sahar & Wheeler, Sarah Ann & Zuo, Alec, 2020. "Understanding the impacts of water scarcity and socio-economic demographics on farmer mental health in the Murray-Darling Basin," Ecological Economics, Elsevier, vol. 169(C).
    9. Lu Liu & Wei Nai & Zan Yang, 2022. "Measuring the State Dependence Effect in Hospital Payment Adjustment," IJERPH, MDPI, vol. 19(21), pages 1-17, October.
    10. Mujcic, Redzo, 2014. "Are fruit and vegetables good for our mental and physical health? Panel data evidence from Australia," MPRA Paper 59149, University Library of Munich, Germany.
    11. Bubonya, Melisa & Cobb-Clark, Deborah A. & Ribar, David C., 2019. "The reciprocal relationship between depressive symptoms and employment status," Economics & Human Biology, Elsevier, vol. 35(C), pages 96-106.
    12. Melisa Bubonya & Deborah A. Cobb-Clark & David C. Ribar, 2017. "The Bilateral Relationship between Depressive Symptoms and Employment Status," Melbourne Institute Working Paper Series wp2017n10, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    13. Paul Contoyannis & Jinhu Li, 2014. "The Dynamics of Depression from Adolescence to Early Adulthood," Department of Economics Working Papers 2014-09, McMaster University.
    14. Sefa Awaworyi Churchill & Lisa Farrell & Russell Smyth, 2019. "Neighbourhood ethnic diversity and mental health in Australia," Health Economics, John Wiley & Sons, Ltd., vol. 28(9), pages 1075-1087, September.
    15. Mateus Dias & Luiz Felipe Fontes, 2020. "The Effects of a Large-Scale Mental Health Reform: Evidence from Brazil," Working Papers 09, Instituto de Estudos para Políticas de Saúde.
    16. Anam Bilgrami & Kompal Sinha & Henry Cutler, 2020. "The impact of introducing a national scheme for paid parental leave on maternal mental health outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 29(12), pages 1657-1681, December.
    17. Moscone, F. & Tosetti, E. & Vittadini, G., 2016. "The impact of precarious employment on mental health: The case of Italy," Social Science & Medicine, Elsevier, vol. 158(C), pages 86-95.
    18. Stefanie Schurer & Michael Alspach & Jayden MacRae & Gregory Martin, 2016. "The Medical Care Costs of Mood Disorders: A Coarsened Exact Matching Approach," The Economic Record, The Economic Society of Australia, vol. 92(296), pages 81-93, March.
    19. Peter Butterworth & Carmel Poyser & Aino Suomi, 2021. "Mental Health," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 54(4), pages 530-541, December.
    20. Peter Butterworth & Sonja C. de New & Chris Schilling & Karinna Saxby & Dennis Petrie & Clement Wong, 2021. "Dynamics of Mental Health and Healthcare Use among Children and Young Adults," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 54(1), pages 130-142, March.
    21. Paul Contoyannis & Jinhu Li, 2017. "The dynamics of adolescent depression: an instrumental variable quantile regression with fixed effects approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 907-922, June.

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    More about this item

    Keywords

    mental health; depression and anxiety; dynamic panel data models; GMM-IV; HILDA;
    All these keywords.

    JEL classification:

    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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