To begin with, the key concept of IEOp in this paper is closely related to the issue of social mobility. EstimatingθIEOpb can be regarded as isomorphic to measuring intergenerational persistence of IEOp. For the latter, following Galton, one usually regresses a child’s (yit) on parental outcomes (yi,t−1):
yit=βyi,t−1+it, (10)
with β as measure of persistence. If one used family background variables instead of parental
outcome variables for (yi,t−1), then the R2 measure of immobility (Equation (10)) would be similar
toθbIOP (Equation (7) in Section 3.2) as long as thecircumstances vector contains mostly family
background variables. In this regard, θIEOpb can be connected to measures of intergenerational
educational immobility, which can be used to measure social (im)mobility (such asβ Equation (10)).
In analogy, this is also related to the findings that childhood wealth can serve as a proxy for circumstances explaining future wealth inequality (Boserup, Kopczuk, & Kreiner, 2016). Moreover, intergenerational income elasticity and the Gini coefficient of incomes have been shown to be highly correlated (Great Gatsby Curve) which points to a link between IEOp and intergenerational social mobility (Black & Devereux, 2011). The connection between both concepts can be characterized by
two adjoint forces,upward and downward social mobility.
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For completeness, the DiD estimation results are provided in Table A.17 forModel Base-MT and Table A.18 for
Base-ST. For thehypothetical Control Groupthe DiD estimate is negative in the short term and gets less negative in the medium term, whereas for control group C the effect is positive in the short term and rises in the medium term. However, pre-reform tests for Ch (Table A.5) indicate that any results based on it should be interpreted cautiously.
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A decrease in IEOp would be indicative for improvedupwardmobility, as it means thatcircumstances, such as the SES of the family in which one grows up, became less important for a student’s academic performance. Therefore, if lower IEOp translates into providing more equalizing learning conditions such that ability, but in particulareffortsare rewarded, extending equality of educational opportunities would be welfare enhancing in a society with meritocratic preferences. However, while decreasing IEOp may lead to socialupward mobility for high-performing students from disadvantaged backgrounds, it may also lead to socialdownward mobility for students with beneficialcircumstances who lack talent and/or effortsto maintain their position as soon as the importance ofcircumstances for the determination of a student’s educational outcome decreases.
Returning to the G-8 reform, we can provide the following explanation for the observed findings. First, the fact that increased learning intensity had only a limited impact on IEOp in the short
run may be indicative for the reform heterogeneously promoting both downward mobility among
students with advantageouscircumstances andupward mobility among those with disadvantaged
circumstanceswho having managed to enter the Gymnasiummay have already undergone a harder
selection process.52 As the implementation process of the reform suggests, the reform-induced
increase in learning intensity surprised affected students and their parents in a manner that they could not adapt to immediately. For instance, being the first one confronted with the newly intensified system, it is harder to adapt as one can not easily rely on the experiences of older students as was the case for later cohorts in the new G-8 model. This may explain why IEOp increased only moderately or not at all in the short term. Thus, in the initial reform period, the
lag with which favorable circumstancesadapt to help a student implies that downward rather than
upward mobility forces may have been more relevant for the first affected student cohorts.
Second, in the medium term, after favorablecircumstanceshad time to adapt and provide support to
the associated students,upward mobility would be lessened in conjunction with downward mobility.
For instance, parents are more likely to be aware and prepared to deal with the increased requirements of a G-8 model and new forms of additional professional tuition services may become available in response to the reform based on the experiences of the first affected cohorts. Consequently,
favorable circumstances may then allow students quicker, easier and better access to a support
system helping them to deal with the higher learning intensity. Then, increased IEOp associated
with lowerupward rather than higherdownward mobility may be expected in the medium term after
the G-8 reform was enacted. Descriptive evidence on the evolution of additional, paid tuition for
students attending aGymnasiumavailable from PISA questionnaires supports the explanation given
abov (cf. Figure A.9). There has been a rise in extra tuition following the reform, with this effect being stronger in the treatment compared to the control group federal states. Moreover, the increase in extra tuition has been more pronounced for students from more privileged family environments (circumstances), such as those living in academic households. A further potential mechanism involves the time investment made by mothers depending on their educational background into their children.
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The high correlation of parental education and a student’s probability of entering theGymnasiumhas been shown (e.g. Klime et al. (2010;PISA 2009)to be persistent in the German school system at least over the last two decades.
More highly educated women were more likely to work part-time in order to support their children in treatment states after the reform compared to the situation in control group states (Figure A.10). Moreover, looking across the medium-term effect evidence (Table 4) DiD estimates of the effect of increased learning intensity on IEOp reveal some subject-related patterns. The level of IEOp is consistently higher for both mathematics and science compared to reading across all treatment and control group specifications. This observation can be interpreted as evidence in favor of the existence of heterogeneous subject-dependent curricular flexibilities. In fact, reading skills comprise more general competencies that are not only learnt in language-related courses at school, but also indirectly in other school courses as well as in everyday life - reading being often a necessary prerequisite to simply comprehend, learn or interact with other people. Consequently, variations in learning intensity might have less influence on reading skills. In contrast, mathematics/science can be regarded as requiring more specific skills which are mainly accumulated through taught courses at school and less likely to be learnt indirectly through other courses at school or in everyday life. Thus, for the complementary skills set required by mathematics/science, it seems to be plausible
that positive circumstances such as growing up in an academic household are relatively more
important than for reading. Beneficial resources improving the accumulation of skills relevant for mathematics/science tend to be more exclusive than those important for reading. In that context, the fact that the impact of the reform with respect to reading skills is less pronounced, could be interesting for another reason. It might raise the question of whether in order to improve reading skills, current curricula and teaching methods need to be adjusted. But, it could also only indicate that the reading practice from additional teaching only balances out the negative impact of increased intensity on the actual learning process - which would be another potential part of the explanation for why IEOp levels for the domain of reading may be less pronounced than in the other domains. However, given the broad definition of learning intensity this may still be compatible with findings that the G-8 reform itself had small positive effects on mathematics/science test scores in contrast to reading test scores (Camarero Garcia, 2012; Andrietti, 2016; Huebener et al., 2017; Büttner & Thomsen, 2015). Furthermore, Dahmann (2017) shows that cognitive skills measured by IQ proxies did not causally change due to the reform, but only gender-specific differences may be reinforced. The fact, that there appear to be no SES-specific differences supports my findings: the observed overall increase in IEOp seems to be mainly driven by heterogeneous parental support opportunities to deal with the higher learning intensity and cannot be simply explained by potential differences in ability. Finally, as the reform did not adjust teaching-related quality factors for the first affected cohorts, the findings might be regarded to be merely a lower bound for the effects of increased learning intensity on performance, in particular as the variance of test scores did not change much. In summary, even though it is beyond the scope of this article to precisely detect all underlying channels and mechanisms explaining how IEOp may be changed and all implications for its translation
into both upward and downward mobility, this paper does reveal one mechanism of how IEOp can