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The income gradient and child mental health in Australia: does it vary by assessors?


In this paper, we examine the income gradient in child mental health using longitudinal data from a large, national cohort of Australian children. We contribute to the body of existing literature by: (i) investigating whether and to what extent a child’s mental health levels and their relationship to income vary when a child’s mental health is assessed by the child’s parent, the child’s teacher and the child her/himself; (ii) exploring whether the reporting differences in a child’s mental health is associated systematically with household income; and (iii) examining the child mental health gradient and the evolution of this gradient by the child’s age. We found that a child’s mental health and the income gradient vary depending on who assesses the child’s mental health (the gradient was the largest when assessed by parents and the smallest when assessed by the child). Furthermore, the magnitude of the effect of mental health and income gradient faded when we controlled for some important variables, such as maternal health.

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  1. 1.

    We thank a reviewer of this journal for this suggestion.

  2. 2.

    The weekly income data was collected from responses to the following question “Before income tax is taken out, how much does … usually receive from all sources in total?” Unfortunately, LSAC lacks sufficient information on the income of other household members, so we were unable to use household income similar to Johnston et al. [26] and instead we used parental income.

  3. 3.

    Parental reports come from the child’s main carer, or Parent 1 in LSAC (i.e. the parent who knows the child best). In these data, in over 95 % of the cases this is the child’s biological mother. For simplicity, in the remainder of the paper we refer to Parent 1 as the mother.

  4. 4.

    However, we provide the results of fixed-effects estimator in the Appendix for interested readers.


  1. 1.

    AIFS (2005) Longitudinal study of Australian children data user guide. Australian institute of family studies

  2. 2.

    Apouey, B., Geoffard, P.-Y.: Family income and child health in the UK. J. Health Econ. 32(4), 715–727 (2013)

    Article  Google Scholar 

  3. 3.

    Bago d’Uva, T., Van Doorslaer, E., Lindeboom, M., O’donnell, O.: Does reporting heterogeneity bias the measurement of health disparities? Health Econ. 17(3), 351–375 (2008)

    Article  Google Scholar 

  4. 4.

    Brown, J.D., Wissow, L.S., Gadomski, A., Zachary, C., Bartlett, E., Horn, I.: Parent and teacher mental health ratings of children using primary-care services: interrater agreement and implications for mental health screening. Ambul. Pediatr. 6(6), 347–351 (2006)

    Article  Google Scholar 

  5. 5.

    Burgess, S., Greaves, E.: Test scores, subjective assessment, and stereotyping of ethnic minorities. J. Labor Econ. 31, 535–576 (2013)

    Article  Google Scholar 

  6. 6.

    Case, A., Lubotsky, D., Paxson, C.: Economic status and health in childhood: the origins of the gradient. Am. Econ. Rev. 92(5), 1308–1344 (2002)

    Article  Google Scholar 

  7. 7.

    Condliffe, S., Link, C.R.: The relationship between economic status and child health: evidence from the United States. Am. Econ. Rev. 98(4), 1605–1618 (2008)

    Article  Google Scholar 

  8. 8.

    Cornaglia, F., Crivellaro, E., McNally, S.: Mental health and education decisions. Labour Economics 33, 1–12 (2015)

    Article  Google Scholar 

  9. 9.

    Currie, J., Stabile, M.: Socioeconomic status and child health: why Is the relationship stronger for older children? Am. Econ. Rev. 93(5), 1813–1823 (2003)

    Article  Google Scholar 

  10. 10.

    Currie, J., Stabile, M.: Child mental health and human capital accumulation: the case of ADHD. J Health Econ 25(6), 1094–1118 (2006)

    Article  Google Scholar 

  11. 11.

    Currie, A., Shields, M.A., Price, S.W.: The child health/family income gradient: evidence from England. J. Health Econ. 26(2), 213–232 (2007)

    Article  Google Scholar 

  12. 12.

    Davé, S., Nazareth, I., Senior, R., Sherr, L.: A comparison of father and mother report of child behaviour on the strengths and difficulties questionnaire. Child Psychiatry Hum. Dev. 39(4), 399–413 (2008)

    Article  Google Scholar 

  13. 13.

    Etilé, F., Milcent, C.: Income-related reporting heterogeneity in self-assessed health: evidence from France. Health Econ. 15(9), 965–981 (2006)

    Article  Google Scholar 

  14. 14.

    Fitzsimons, E., Goodman, A., Kelly, E., Smith, J.P.: Poverty dynamics and parental mental health: determinants of childhood mental health in the UK. Soc. Sci. Med. 175, 43–51 (2017)

    Article  Google Scholar 

  15. 15.

    Fletcher, J.: Adolescent depression: diagnosis, treatment, and educational attainment. Health. Econ. 17(11), 1215–1235 (2008)

    Article  Google Scholar 

  16. 16.

    Fletcher, J., Wolfe, B.: Child mental health and human capital accumulation: the case of ADHD revisited. J Health Econ 27(3), 794–800 (2008)

    Article  Google Scholar 

  17. 17.

    Frijters, P., Johnston, D.W., Shields, M.A.: The effect of mental health on employment: evidence from Australian panel data. Health Econ. 23(9), 1058–1071 (2014)

    Article  Google Scholar 

  18. 18.

    Goodman, A., Goodman, R.: Strengths and difficulties questionnaire as a dimensional measure of child mental health. J. Am. Acad. Child Adolesc. Psychiatry 48(4), 400–403 (2009)

    Article  Google Scholar 

  19. 19.

    Goodman, R., Ford, T., Simmons, H., Gatward, R., Meltzer, H.: Using the strengths and difficulties Questionnaire (SDQ) to screen for child psychiatric disorders in a community sample. British J Psychiatry 177(6), 534–539 (2000)

    CAS  Article  Google Scholar 

  20. 20.

    Gibbons, S., Chevalier, A.: Assessment and age 16+ education participation. Res. Pap. Educ. 23(2), 113–123 (2008)

    Article  Google Scholar 

  21. 21.

    Gregg, P., Washbrook, E., Propper, C., Burgess, S.: The effects of a mother’s return to work decision on child development in the UK. Econ J 115(501), F48–F80 (2005). Retrieved from

    Article  Google Scholar 

  22. 22.

    Gupta, N.D., Lausten, M., Pozzoli D.: Does mother know best? Parental discrepancies in assessing child functioning. Discussion Paper Series, Forschungsinstitut zur Zukunft der Arbeit (2012)

  23. 23.

    Halleröd, B., Gustafsson, J.-E.: A longitudinal analysis of the relationship between changes in socio-economic status and changes in health. Soc. Sci. Med. 72(1), 116–123 (2011)

    Article  Google Scholar 

  24. 24.

    Harvey, A.C.: Estimating regression models with multiplicative heteroscedasticity Econom. J. Econ. Soc. 44(3), 461–465 (1976)

    Google Scholar 

  25. 25.

    Johnston, D.W., Propper, C., Shields, M.A.: Comparing subjective and objective measures of health: evidence from hypertension for the income/health gradient. J Health Econ 28(3), 540–552 (2009)

    Article  Google Scholar 

  26. 26.

    Johnston, D., Propper, C., Pudney, S., Shields, M.: The income gradient in childhood mental health: all in the eye of the beholder? J. R. Stat. Soc. Ser. A 177(4), 807–827 (2014)

    Article  Google Scholar 

  27. 27.

    Kuehnle, D.: The causal effect of family income on child health in the UK. J. Health Econ. 36, 137–150 (2014)

    Article  Google Scholar 

  28. 28.

    Khanam, R., Nghiem, H.S., Connelly, L.B.: Child health and the income gradient: evidence from Australia. J. Health Econ. 28(4), 805–817 (2009)

    Article  Google Scholar 

  29. 29.

    Khanam, R., Nghiem, H.S., Connelly, L.B.: What roles do contemporaneous and cumulative incomes play in the income-child health gradient for young children? Evidence from an Australian panel. Health Econ. 23(8), 879–893 (2014)

    Article  Google Scholar 

  30. 30.

    Kessler, R.C., Green, J.G., Gruber, M.J., Sampson, N.A., Bromet, E., Cuitan, M., Furukawa, T.A., Gureje, O., Hinkov, H., Hu, C.-H., Lara, C., Lee, S., Mneimneh, Z., Myer, L., Oakley-Browne, M., Posada-Villa, J., Sagar, R., Viana, M.C., Zaslavsky, A.M.: Screening for serious mental illness in the general population with the K6 screening scale: results from the WHO World Mental Health (WMH) survey initiative. Int. J. Methods Psychiatr. Res. 20(1), 62–62 (2011)

    Article  Google Scholar 

  31. 31.

    Khanam, R., Nghiem, S.: Family income and child cognitive and noncognitive development in Australia: does money matter? Demography 53(3), 597–621 (2016)

    Article  Google Scholar 

  32. 32.

    Khanam, R., Nghiem, S.: Behavioural and emotional problems in children and educational outcomes: a dynamic panel data analysis. Adm. Policy. Ment. Health. 45(3), 472–483 (2018)

    Article  Google Scholar 

  33. 33.

    Lindeboom, M., Van Doorslaer, E.: Cut-point shift and index shift in self-reported health. J Health Econ 23(6), 1083–1099 (2004)

    Article  Google Scholar 

  34. 34.

    Mackenbach, J.P., Looman, C., der Meer, J.Van: Differences in the misreporting of chronic conditions, by level of education: the effect on inequalities in prevalence rates. Am. J. Public Health 86(5), 706–711 (1996)

    CAS  Article  Google Scholar 

  35. 35.

    Nghiem, H.S., Nguyen, H.T., Khanam, R., Connelly, L.B.: Does school type affect cognitive and non-cognitive development in children? Evidence from Australian primary schools. Labour Econ 33, 55–65 (2015)

    Article  Google Scholar 

  36. 36.

    Papageorgiou, V., Kalyva, E., Dafoulis, V., Vostanis, P.: Differences in parents’ and teachers’ ratings of ADHD symptoms and other mental health problems. European J Psychiatry 22(4), 200–210 (2008)

    Article  Google Scholar 

  37. 37.

    Perales, F., Johnson, S.E., Baxter, J., Lawrence, D., Zubrick, S.R.: Family structure and childhood mental disorders: new findings from Australia. Soc. Psychiatry Psychiatr. Epidemiol. 52(4), 423–433 (2017)

    Article  Google Scholar 

  38. 38.

    Propper, C., Rigg, J., Burgess, S.: Child health: evidence on the roles of family income and maternal mental health from a UK birth cohort. Health Econ. 16(11), 1245–1269 (2007)

    Article  Google Scholar 

  39. 39.

    Reinhold, S., Jürges, H.: Parental income and child health in Germany. Health Econ. 21(5), 562–579 (2012)

    Article  Google Scholar 

  40. 40.

    Reiss, F.: Socioeconomic inequalities and mental health problems in children and adolescents: a systematic review. Soc. Sci. Med. 90, 24–31 (2013)

    Article  Google Scholar 

  41. 41.

    Richards. M., Abbott, R.: Childhood mental health and life chances in post-war Britain. Centre. Mental. Health. (2009) Retrieved from

  42. 42.

    Soloff, C., Lawrence, D., Johnstone, R.: LSAC technical paper no. 1: sample design. Melbourne, Australia: Australian Institute of Family Studies (2005)

  43. 43.

    Strohschein, L.: Parental divorce and child mental health trajectories. J Marriage Fam 67(5), 1286–1300 (2005)

    Article  Google Scholar 

  44. 44.

    Youngstrom, E.A., Findling, R.L., Calabrese, J.R.: Who are the comorbid adolescents? Agreement between psychiatric diagnosis, youth, parent, and teacher report. J. Abnorm. Child Psychol. 31(3), 231–245 (2003)

    Article  Google Scholar 

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We greatly acknowledge the contribution of Dr. Francisco (Paco) Perales (Institute for Social Science Research, The University of Queensland) on the initial draft of the paper. We also grateful to two anonymous referees of this journal and the participants of the 14th International Conference of Western Economic Association International for their feedback. This paper uses unit record data from Growing Up in Australia, the Longitudinal Study of Australian Children. The study is conducted in partnership between the Department of Social Services (DSS), the Australian Institute of Family Studies (AIFS), and the Australian Bureau of Statistics (ABS). Appropriate ethical approval was gained during the study. The findings and views reported in this paper are those of the authors and should not be attributed to the DSS, the AIFS, or the ABS.


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Correspondence to Rasheda Khanam.

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See Table 4, Full estimates from models of child mental health with extended covariates. 5, 6, 7, 8, 9, and Fig. 4.

Table 4 Descriptive statistics
Table 5 OLS
Table 6 Random-effects
Table 7 Fixed effects
Table 8 F tests (p value) for differences in SDQ scores by raters
Table 9 SDQ: the SDQ scores are produced from responses to the following questions about child’s behaviour over the past 6 months
Fig. 4

Distribution of SDQ scores and log of income

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Khanam, R., Nghiem, S. & Rahman, M. The income gradient and child mental health in Australia: does it vary by assessors?. Eur J Health Econ 21, 19–36 (2020).

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  • Income
  • Child mental health
  • Children’s socio-emotional outcomes
  • Assessors
  • Australia
  • Panel data

JEL Classification

  • I12
  • I14