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The transition to tertiary education and parental background over time

Abstract

We analyze the role of parental background for transitions to tertiary education in Germany and answer three questions: (a) does the relevance of parental background shift from short-term (contemporary income) to long factors (ability, parental education) at higher levels of education? (b) Did the impact of parental background on participation in tertiary education change over time? (c) Are there different patterns by sex and region? Parental income significantly affects transitions to tertiary education. Its impact seems to have lost magnitude over time. We find no clear differences by sex and larger parental income effects in West than in East Germany.

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Notes

  1. This result is disputed by Belley and Lochner (2007) but supported by Mayer (2008).

  2. This methodological shortcoming also characterizes more recent sociological analyses of education transmission in Germany, e.g. Mayer et al. (2007), Maaz (2006).

  3. In addition, there are comprehensive schools where pupils can obtain either level of education. However, only a share of about four percent of every cohort attends these.

  4. The requirements for male military or substitute civil service have been shortened in recent years. The duration of military service was shortened from 15 months (1984–1990), to 12 months (1990–1996), 10 months (1996–2002), and nine months since 2002. Alternative civilian service obligations were as high as 20 months (1984–1990), then 15 months (1990–1996), reaching 10 months between 2002 and 2004, and nine months since.

  5. It is not useful to compare the rates in Table 2 to those in Table 1 or Fig. 1, as Table 2 combines all individuals entering tertiary education in a given calendar year, independent of their age, while Table 1 and Fig. 1 condition on the year of leaving school. As cohort sizes vary substantially over time the difference in conditioning affects the cohort shares.

  6. We used the small samples with available grade information to compare individual grades by age at Abitur. In two out of the three subjects (German and foreign language) those individuals who completed the Abitur early, i.e. at age 17 or 18, indeed had better grades than those who graduated at older age. In addition, the most recent data on a sample of high school graduates eligible to enter tertiary education (“Studienberechtigte 2008”) yield a significant positive correlation between a young age at Abitur and high scholastic attainment.

  7. Individuals who did not indicate to attend school in the year before they first claimed a high school degree are not considered in the group of new high school graduates.

  8. Individuals attaining a ”Fachabitur” degree are not part of our sample because they are not eligible for university education.

  9. In the regression we adjust the age at Abitur variable for individuals who graduated in states with shorter Gymnasium schooling requirements: in Thuringia and Saxony-Anhalt the Abitur can be attained after 12 instead of 13 years of schooling, which were required everywhere else during the time of our observations.

  10. A panel survey of Advanced School graduates yielded that between 18 and 29 percent of males and 29 and 39 percent of females did not plan to take up tertiary education half a year after leaving Advanced School (Heine et al. 2006). The remaining difference in transition rates with our data is partly due to transitions to tertiary education outside of our observation window (i.e. after year five after the Abitur) and partly to panel attrition of young individuals in the German Socioeconomic Panel.

  11. Ideally, one might want to control for the number of siblings supported by parents, however this information is not available for all observations in our sample. In a robustness test (discussed below), we determine whether the equivalence correction affects our results.

  12. The psychological literature clearly indicates the inheritability of ability, see e.g. Plomin et al. (2001).

  13. In principle one might want to separately model entry to the Gymnasium and successful completion in greater detail. Since our data does not provide information on individual secondary school careers we combine these events in our first stage outcome.

  14. This longitudinal modeling strategy goes beyond the classic bivariate probit application as it requires panel data also for the first stage selection equation.

  15. Our estimation results are robust to omitting the instruments measuring parental age.

  16. We expect that our sample is too small to reflect the generally found pattern of scholastic attainment by age at Abitur.

  17. The hypothesis that the coefficients of the instruments are jointly equal to zero was rejected at the one percent significance level in all cases. In addition to testing the joint significance of our instruments in the Abitur-equation we performed an overidentification test as described in Bratti (2007): since the estimator is identified by functional form we omitted the instruments from the first-stage (Abitur) equation and added them to the second-stage equation. Here they were neither individually nor jointly statistically significant (p-value of joint test: 0.5929).

  18. For results of the first stage regression see Table 8 Panel C. Interestingly, the marginal effects of parental education are substantially stronger and those of parental income are smaller for the first stage outcomes in Panel D. This confirms the broad sociological evidence on changing parental background effects at increasingly higher educational stages as discussed by Cameron and Heckman (1998).

  19. The number of observations in East Germany (824) appears to be too small to split this sample.

  20. In the overall income distribution East German households are positioned at lower percentile ranks than their West German counterparts (average rank East: 58th, average rank West: 69th percentile among those attaining the Abitur degree). However, since separate models are estimated this difference should not affect our results.

  21. In contrast to the results based on panel data, parental educational background indicators remain statistically significant in Panel B of Table 12 and the error term correlation is at times positive and insignificant. We expect that our instrumental variables, which mainly identify the selection into Abitur based on state-specific developments over time, provide insufficient variation in the first stage of the selection model which as before controls for federal state fixed effects.

  22. After taking these ability related determinants of income out of the income indicator the estimated marginal effect may be interpreted as the ’nurture’ effect of income, as opposed to genetic or ’nature’ effects.

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Acknowledgements

We thank two anonymous referees, Thomas K. Bauer, Knut Wenzig as well as participants of the 2008 meeting of the population economics group of the Verein für Socialpolitik in Bielefeld, seminar participants at the universities of Erlangen-Nuremberg, Groningen, Linz, Mainz, Milan, Mannheim, and Würzburg for helpful comments.

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Correspondence to Regina T. Riphahn.

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Responsible editor: Christian Dustmann

Appendix

Appendix

Table 12 Reestimation of Table 8 using cross-section data
Table 13 Reestimation of Table 8 with income residuals
Table 14 Results of subsample with grades: with and without grade control

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Riphahn, R.T., Schieferdecker, F. The transition to tertiary education and parental background over time. J Popul Econ 25, 635–675 (2012). https://doi.org/10.1007/s00148-010-0347-3

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Keywords

  • Intergenerational transmission
  • Human capital investment
  • Tertiary education

JEL Classification

  • I2
  • I23
  • C25