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Unlucky to be young? The long-term effects of school starting age on smoking behavior and health

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Abstract

The literature on school entry laws has shown that relative school starting age affects smoking behavior and health in adolescence, yet it remains unclear whether these effects persist into adulthood. Filling this gap, we analyze the long-term effects of relative school starting age on smoking behavior and health in adulthood. This study employs a fuzzy regression discontinuity design, using school entry rules combined with birth month as an instrument for school starting age. The analysis adopts data from the German Socio-Economic Panel. The results reveal that an increase in relative school starting age significantly reduces the long-term risk of smoking, improves long-term health, and affects physical rather than mental health. Several robustness checks confirm these results. In addition, we present suggestive evidence that the relative age composition of peers and the school environment are important mechanisms.

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Notes

  1. The World Health Organization standardizes national smoker rates by applying age-specific smoker rates by sex in each population to a statistical standard population to enable cross-country comparisons.

  2. This branch of literature and our study exploit legal school starting age cutoffs to analyze the effects of relative differences in individual school starting age. By contrast, Fletcher and Kim (2016) analyze the effects of shifts in school entry cutoffs that change the absolute school starting age.

  3. These studies interpret the higher number of diagnoses among younger school starters as misdiagnoses, which is confirmed by Dalsgaard et al. (2012).

  4. Figures 1 and 2 are based on data from the German Health Interview and Examination Survey for Children and Adolescents (KiGGS), 2003–2006, administered by the Robert Koch Institute. KiGGS is a nationwide clustered random sample of 17,641 children and adolescents (0–17 years) and their parents (Hölling et al. 2012).

  5. Biewen and Tapalaga (2017) analyze life-cycle educational choices in Germany and give an overview of the German education system.

  6. We neglect repeated observations for two reasons. First, Eibich (2015) and Godard (2016) show that retirement reduces the likelihood of smoking and improves health; thus, including observations close to retirement might bias the estimated effects of school starting age. Second, selective sample attrition will likely become an issue if older observations are included in the sample because unhealthy individuals are more likely to drop out of the sample than healthy individuals. However, the robustness checks show that the main results are robust to both the inclusion of all available observations for each respondent and exclusion of respondents at least 60 years old.

  7. Table 10 in the Appendix shows that respondents’ average age at the time of the SOEP interview is about 35.5–37.9 years, depending on the analyzed outcome and specification. Furthermore, it shows that respondents’ age does not statistically differ between persons born before or after the cutoff.

  8. “Quasi-objective” means that the respective health measure enables health comparisons across different groups of persons (e.g., age groups).

  9. Table 11 in the Appendix provides an overview of the availability of outcome measures across SOEP waves.

  10. We use the absolute school starting age rather than the relative school starting age. Although we use an absolute measure, our approach reflects the effects of one’s individual school starting age relative to that of class and school peers. This approach is in line with the literature on school starting age effects (e.g., Bedard and Dhuey 2006; Fredriksson and Öckert2014).

  11. Before the German reunification in 1990, the starting month differed by federal state. Before 1964, the starting month in the Federal Republic of Germany was April or August. However, in 1964, the Hamburger Abkommen harmonized the start of primary school to August 1st. The starting month in the German Democratic Republic was September 1st but in 1990, it was also changed to August 1st.

  12. In the Federal Republic of Germany, some federal states had school entry cutoffs other than June 30th (about 21% of the sample), although this was later harmonized with the ratification of the Hamburger Abkommen on October 28, 1964. Before the German reunification in 1990, the school entry cutoff in the German Democratic Republic was May 31st (about 21% of the sample). Thus, the June 30th cutoff is relevant for about 58% of the sample. The following analyses include observations from all cutoffs.

  13. Respondents who started school in the former GDR are assigned a GDR indicator.

  14. Modeling higher degree polynomials of the running variable is infeasible in this application, because the running variable is discrete rather than continuous.

  15. Staiger and Stock (1997) suggest that an F statistic of larger than 10 suffices.

  16. For example, Angrist and Krueger (1991) and Robertson (2011) use season of birth as an instrument.

  17. In Table 2, only few specifications show small statistically significant differences in the share of people with migration background, the share of mothers with higher secondary school degrees and fathers with lower secondary school degrees. However, these differences are statistically significant only at the 10% level in few specifications and are statistically non-significant in the large majority of specifications. Adding further validity to the approach, Table 12 in the Appendix shows that a father’s and mother’s age and occupational prestige are also balanced around the cutoff.

  18. The values for school degree type do not aggregate to 100% because some respondents’ parents have other or unspecified types of school degrees.

  19. The difference in the physical health score is divided by 10, which is the variable’s standard deviation in the initial calibration of the SF12 score in the 2004 SOEP sample.

  20. Table 13 in the Appendix reports the first-stage estimates for the preferred specification.

  21. Black et al. (2011) find that school starting age has a significant, but small effect on the mental health of 18–20-year-old males, using Norwegian military record data on mental health measured by psychologists’ assessment. By contrast, we show that school starting age has no significant effect later in life by including both males and females in the analysis, using German survey data comprising self-reported mental health measures.

  22. The results of restricting the sample to a 4-month window around the cutoff are shown in Table 14 in the Appendix.

  23. Note that the loss of statistical significance is not surprising given the substantial decrease in the sample size.

  24. Two point estimates for the effect on mental health are statistically significant at the 10% level when young respondents are excluded from the estimation; however, this effect is statistically non-significant when persons older than 60 years are excluded. Moreover, the effect is always statistically non-significant when a 4-month window is used instead of a 2-month window (see Table 14 in the Appendix).

  25. To characterize compliers relative to the entire sample, we adopted the methodology as explained in Angrist and Pischke (2009).

  26. For instance, the smoking behavior of a person’s reference group might affect his/her own smoking behavior (endogenous effect). Moreover, an individual’s smoking behavior may be influenced by the observed socioeconomic status of the reference group (contextual effect). However, it might also be affected by the unobserved work environment that both the person and reference group share (correlated effect).

  27. The relative age of friends is calculated by dividing the average age of friends by the respondent’s own age.

  28. For respondents who had not yet finished their secondary education, we included their current school type as a covariate.

  29. Elder and Lubotsky (2009) reveal that a 1-year increase in kindergarten entry age decreases the likelihood of grade retention by 13.1 percentage points in the first and second grade and by 15.5 percentage points in any grade in the first 8 years of schooling.

  30. These studies interpret this finding as evidence for misdiagnosis of ADHD.

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Acknowledgements

We thank Thomas Siedler and Jan Marcus for beneficial discussions that improved this study. We further thank participants of the seminars at Universität Hamburg, Hamburg Center for Health Economics (HCHE), the 12th International German Socio-Economic Panel User Conference, and the 11th European Conference on Health Economics. We are grateful to three anonymous referees for their help and guidance.

Funding

This study has received funding from the Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research), project “Nicht-monetäre Erträge von Bildung in den Bereichen Gesundheit, nicht-kognitive Fähigkeiten sowie gesellschaftliche und politische Partizipation.”

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  1. Fakultät für Wirtschafts- und Sozialwissenschaften, Universität Hamburg, Esplanade 36, 20354, Hamburg, Germany

    Michael Bahrs & Mathias Schumann

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Appendix

Appendix

Table 10 Average age of respondents by outcome
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Table 11 Availability of outcome variables in the SOEP
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Table 12 Further parental characteristics at the school entry cutoff
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Table 13 OLS and fuzzy RDD results
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Table 14 Fuzzy RDD: including all observations per respondent in the estimation and robustness by age groups (4-month window)
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Table 15 Fuzzy RDD: network of friends (all months and trends)
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Bahrs, M., Schumann, M. Unlucky to be young? The long-term effects of school starting age on smoking behavior and health. J Popul Econ 33, 555–600 (2020). https://doi.org/10.1007/s00148-019-00745-6

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