Genetic and environmental contributions to educational attainment in Australia

Miller, Paul W.; Mulvey, Charles; Martin, Nick

doi:10.1016/s0272-7757(00)00018-2

Cited by 54 publications

(50 citation statements)

References 33 publications

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“…First, we estimate sibling correlations for several traits, some of which have never before been studied in large samples, and we confirm that there is a robust separation of the monozygotic (identical twin) and dizygotic (fraternal twin) correlations. We obtain heritability estimates that are consistent with typical estimates previously reported for both political attitudes (19) and economic preferences (20,23,24), as well as educational attainment (45,46). Overall, these results are consistent with the hypothesis that, for each of the 10 phenotypes, there exists a moderate correlation with genetic factors.…”

Section: Discussionsupporting

confidence: 90%

The genetic architecture of economic and political preferences

Benjamin

Cesarini

Loos

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

233

166

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Preferences are fundamental building blocks in all models of economic and political behavior. We study a new sample of comprehensively genotyped subjects with data on economic and political preferences and educational attainment. We use dense single nucleotide polymorphism (SNP) data to estimate the proportion of variation in these traits explained by common SNPs and to conduct genome-wide association study (GWAS) and prediction analyses. The pattern of results is consistent with findings for other complex traits. First, the estimated fraction of phenotypic variation that could, in principle, be explained by dense SNP arrays is around one-half of the narrow heritability estimated using twin and family samples. The molecular-genetic-based heritability estimates, therefore, partially corroborate evidence of significant heritability from behavior genetic studies. Second, our analyses suggest that these traits have a polygenic architecture, with the heritable variation explained by many genes with small effects. Our results suggest that most published genetic association studies with economic and political traits are dramatically underpowered, which implies a high false discovery rate. These results convey a cautionary message for whether, how, and how soon molecular genetic data can contribute to, and potentially transform, research in social science. We propose some constructive responses to the inferential challenges posed by the small explanatory power of individual SNPs.genoeconomics | genopolitics | GCTA T here has been growing enthusiasm for the use of molecular genetic data in social science research. This enthusiasm is based on a number of potential contributions that such research could make to social science (1-3). For example, if specific genetic markers can be identified that are associated with a behavioral trait, then such predictive markers may shed light on the biological pathways underlying that trait (3, 4). If a set of genetic markers is sufficiently predictive, then these markers could be used in social science research as control variables, as instrumental variables (5, 6; for critical perspectives, see refs. 7, 8) or, under certain conditions, as factors for identifying at-risk individuals (1-3).The extent to which this potential of molecular genetic data will be fulfilled for a given trait hinges on the trait's "molecular genetic architecture," i.e., the joint distribution of effect sizes and allele frequencies of the causal genetic variants (9). The architecture-which is the result of evolutionary forces, including mutation, drift, and selection-determines the difficulty with which the genetic variants associated with a trait can be identified and what sample sizes will be required for gene discovery. It also determines the out-of-sample aggregate predictability that can be derived from a set of genetic markers considered jointly.Existing studies claiming to have established genetic associations with economic and political traits typically use samples of several hundred individuals, and no...

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Section: Discussionsupporting

confidence: 90%

The genetic architecture of economic and political preferences

Benjamin

Cesarini

Loos

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

233

166

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“…This approach is used in several econometric analyses in behavioural genetics (see also Miller et al 1996and 2001, Nicolaou et al 2008). Although they do not formally prove it, Cropanzano and James (1990) also argue that the model requires a correction for potential variables for researchers to be able to make strong statements about the effects of genetics and shared environments on the outcome variable.…”

Section: [Insert Tables 2-3 Here]mentioning

confidence: 99%

“…both educational and occupational interests, which are also heritable (Miller et al 2001, Whiston et al 2004.…”

Section: [Insert Tables 2-3 Here]mentioning

confidence: 99%

“…This is relatively surprising given that the behavioral genetics literature provides convincing empirical evidence regarding heritable effects on a variety of sociological and economic outcomes. This branch of the literature includes Miller et al (2001), who investigate the genetic heritability of education; Johnson et al (2004), who find that marital status is mainly explained by genetic factors; Whiston and Keller (2004) for their review of occupational preferences; Keller et al (1992), who study the heritability of work values; Plomin and Spinath (2004), who focus on ability; and Cesarini et al (2009), who examine the genetic heritability of risk-taking. Because all of these attritubes also contribute to public sector 3 See also Maczulskij and Pehkonen (2011), who found evidence that differences in industry-specific valuations of skills explain a significant part of the pay gaps in Finland (together with human capital variables).…”

Section: Introductionmentioning

confidence: 99%

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Employment sector and pay gaps: Genetic and environmental influences

Maczulskij

2013

Labour Economics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Additional findings suggest that genetic factors may encourage people to engage in public sector employment through at least one mechanism: educational attainment. The pay gap analysis provides evidence that females receive 4-5 per cent less in the public sector and indicates that this gap is explained by neither genetic effects nor the influence of a shared environment. For males, the pay gap is zero rather than negative 7 per cent as conventionally estimated, and this difference is mainly caused by genetic factors such as intelligence. Terms of use: Documents in EconStor may

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“…4 Other attributes of an environmental nature such as (the threat of) unemployment ) and the institutional environment (Freytag and Thurik 2007) may play moderating roles. (Arvey et al 1989), vocational interests (Betsworth et al 1994), work values (Keller et al 1992), novelty seeking (Ebstein et al 1996;Kluger et al 2002), gambling (Pérez de Castro et al 1997;Comings et al 1996), general cognitive ability and intelligence (Deary et al 2006;Plomin 1999;Plomin and Kosslyn 2001;Plomin and Spinath 2004), educational attainment (Miller et al 2001), and overconfidence (Cesarini et al 2009b). …”

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confidence: 99%

Genome-wide association studies in economics and entrepreneurship research: promises and limitations

et al. 2010

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The recently developed genome-wide association study (GWAS) design enables the identification of genes specifically associated with economic outcomes such as occupational and other choices. This is a promising new approach for economics research which we aim to apply to the choice for entrepreneurship. However, due to multiple testing issues, very large sample sizes are needed to differentiate between true and false positives. For a GWAS on entrepreneurship, we expect that a sample size of at least 30,000 observations is required.

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Genetic and environmental contributions to educational attainment in Australia

Cited by 54 publications

References 33 publications

The genetic architecture of economic and political preferences

The genetic architecture of economic and political preferences

Employment sector and pay gaps: Genetic and environmental influences

Genome-wide association studies in economics and entrepreneurship research: promises and limitations

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