2 Literature screening
3 A more detailed look at the genetic aspect
4 Some comments on genes
This paper examines the impact of family background on children’s schooling attainments. It outlines the discussion in the economic community presenting studies that give empirical evidence of several important characteristics as parents’ education, income and other environmental factors that lead to a higher level of children’s schooling. Based on a research that claims to have quantified genetic influence on schooling using data of adopted children, this paper discusses possible methodological problems arguing that the authors’ estimation seems to ignore an important intervenient variable, the age of the adopted children at adoption.
In public discussions it is frequently argued that investments in human capital and R&D are important especially for countries without or few natural resources, i.e. coal, oil and gas. Theories of human capital are discussed by the economic community already for quite a long time. Schultz (1960: 573) wrote, for example, that “Students study, which is work, and this work, … helps create human capital. Students are … ‘self-employed’ producers of capital”.
Not only concerning labor-economics (e.g. problems of ‘hysteresis’), human capital formation is an important factor for economics. Endogenizing technical change by including investments in human capital, Uzawa (1965) and later Lucas (1988) founded the new Growth Theory. Nowadays, the Lisbon Agenda voted for by the Council of the European Union in 2000 once again highlights investments in human capital and R&D as a main strategy “to become the most competitive and dynamic knowledge-based economy in the world” (Council of the European Union 2000: No.5). Therefore European Member States accepted to increase investments per capita in human capital annually and to half “the number of 18 to 24 year olds with only lower-secondary level education who are not in further education and training” (Council of the European Union 2000: No. 26). It would be interesting to evaluate if the Member States did so in educational policy – but will not be covered in this paper.
In the following I will concentrate on human capital formation – precisely the family background for children’s educational attainments. In 2000 the OECD ‘Program for International Student Assessment’ (PISA-Study) shocked Germany ranking German’s pupils in the middle field of the 32 investigated countries. Artelt et al. (2001: 37) analyzed, that the correlation between social parental status and children’s competences in Germany is one of the highest ones, while other countries succeed to reduce this connection. Moreover, in the recently published EUROSTUDENT III-Study the German HIS (Hochschul-Informations-System) (2008: 11) finds out that “an under-representation of low socioeconomic groups [i.e. low income and education] prevails in all higher education systems”. The most relevant question discussed in economics and other social sciences concerning an increase in education is therefore the following one: Is it the schooling system, social inequality, a question of culture and income distribution, the world around us that make children from poorer families have worse educational attainment as argue sociologists as e.g. Bourdieu (1984) or is it a genetic process, as argue for example Plug and Vijverberg (2003)? Are abilities, competences and intelligence socialized or inherited?
This paper will take a closer look at several empirical investigations about this key question. In section 2, there will be a short literature screening, followed by part 3 taking a more detailed view on papers treating the genetic aspect. Section 4 then discusses these argumentations and findings.
2 Literature screening
This section presents in short some papers and the author’s findings and conclusions. Mainly authors whose papers are presented on the following pages are not only trying to estimate the relationship between independent variables – e.g. parental income, education, social environment and also a kind of genetic endowment – and child’s educational attainment as the dependent variable. Figure 1 shows a stylized plot of the assumed relationship and Table 1 summarizes the main information about the cited papers.
Figure 1: Estimated relationship
illustration not visible in this excerpt
Most of the following studies assume that human capital is intergenerationally transmitted following a model by Becker and Tomes (1986). In quite an interesting paper they try to answer theoretically the question, how human capital, earnings, consumption and assets are passed to next generations. In a basic model Becker and Tomes (1986: S9) derive that today’s (i.e. children’s) earnings are a function of parents’ income, parents’ luck, children’s endowed luck, inheritability of endowments, governmental expenditures in human capital formation, expenditures in human capital by parents and grandparents, the rate of expenditure’s return for children and parents, the social environment and a stochastic component (luck) that is autocorrelated with parents’ luck. They distinguish between open and imperfect access to capital and extend the framework by two variables that catch the parents’ and grandparents’ generosity towards children and an uncertainty-term about children’s luck (for the imperfect access-case). Becker and Tomes (1986: S19) then take a closer look at the utility maximizing process for parents. Splitting their utility into a part gathering their own consumption and a part that catches the parents’ utility from their children’s characteristics depending on parents’ altruism (e.g. generosity that also covers the discounted utility of all coming descendents), parents then maximize their utility depending on uncertainty, richness and so forth (for further and detailed discussions see Becker and Tomes 1986: S18-S23). Obviously – as in all intertemporal models – the discount rate that determines investments and consumption differs for all individuals. It is expected that the discount rate is lower for well-off people (i.e. high investments in children’s human capital) and higher for needy people (i.e. lower investments in children’s human capital).
After briefly having considered the basic assumptions, I will now have a closer look at specific empirical studies estimating the importance of parents’ background on their children’s schooling.
Ermisch and Francesconi (2001) investigate the impact of parental education, family income and the effects of being brought-up in single-parent-families on children’s educational attainments. In short, the authors assume that parents maximize their utility depending on their own consumption, investments in their children’s human capital and transfer to them so that the marginal return equals marginal costs of education (depending on a discount rate, similar to Becker and Tomes 1986). They distinguish two cases: ‘poor’ families, i.e. families that cannot transfer any money for children’s educational attainments and ‘rich’ parents who can (for further details see Ermisch and Francesconi 2001: 138-142). Ermisch and Francesconi (2001) use then data from the British Household Panel Study with about 1,157 individuals born between 1974 and 1981, disregarding (biological) parentage for estimating the questioned impact using an Ordered Logit Model. As independent variables they use e.g. mother’s age at children’s birth, ethnical background, parents’ education, number of siblings, income, house ownership and so forth.
Main findings of their paper are as follows: First, parents’ education influences significantly children’s schooling outcome; especially the effect of mother’s educational level on children’s educational performance seems to be stronger than the father’s one (Ermisch and Francesconi 2001: 146). Second, growing up in a single-parents-household affects schooling attainments negatively especially for ‘poor’ parents (Ermisch and Francesconi 2001: 148) and family structure has in general a significant impact on schooling’s attainments (e.g. intact (non-intact) family-structure increases (decreases) probability of high attainments; see Ermisch and Francesconi 2001: 151). Third, poverty, i.e. having lower financial opportunities, has a negative impact on children’s schooling performance (Ermisch and Francesconi 2001: 152).
Datcher (1982) tries to answer the question, how family and community background (e.g. neighborhood) affect schooling attainments of children. This is a special matter, because she does not only concentrate on parents’ background but includes the socio-economic communal environment with respect to differences for black and white youth in her analysis. For estimating Datcher (1982: 33) includes following explanatory variables: parents’ education, family income, number of siblings, size of place and region of origin, neighborhood’s income, a share of white neighbors in the neighborhood, etc. She considers two cases: Using Ordinary Least Squares (OLS) she estimates on the one hand years of schooling depending on the mentioned variables and on the other hand children’s future earnings depending on these variables and years of schooling (see for further discussion Datcher 1982: 33). The data used for this study is taken from the University of Michigan Panel Study of Income Dynamics consisting of about 550 young male heads of households, aged between 23-32 in 1978. The author’s main findings are as follows: family background is significant, but also community quality is considered to be an “important factor generating differences in education and earnings of young men” (Datcher 1982: 41) that not only influences in general children’s educational attainments and future earnings but also reinforces racial differences.
 See Artelt et al. 2001: 37: There is a strong “Zusammenhang zwischen Sozialschichtzugehörigkeit und erworbenen Kompetenzen über alle untersuchten Domänen hinweg … Die Entwicklung des Zusammenhangs von sozialer Herkunft und Leistung scheint ein kumulativer Prozess zu sein, der lange vor der Grundschule beginnt und an Übergangsstellen des Bildungssystems verstärkt wird.“ And Artelt et al. 2001: 41: “Während in Deutschland die Kopplung von sozialer Lage der Herkunftsfamilie und dem Kompetenzerwerb der nachwachsenden Generation ungewöhnlich straff ist, gelingt es in anderen Staaten … trotz ähnlicher Sozialstruktur der Bevölkerung, die Auswirkungen der sozialen Herkunft zu begrenzen.“
 Participating countries of EUROSTUDENT III are Austria, Bulgaria, Czech Republic, England/Wales, Estonia, Finland, France, Germany, Ireland, Italy, Latvia, Lithuania, Netherlands, Norway, Portugal, Romania, Scotland, Slovak Republic, Slovenia, Spain, Sweden, Switzerland and Turkey.
- Quote paper
- Henner Will (Author), 2009, The Value of Family Background for Educational Attainment , Munich, GRIN Verlag, https://www.grin.com/document/147004