Returns to education: what do twin studies control?

The most straightforward method of assessing the value of education has been to examine the differences in income of those with varying amounts of education. One obvious problem arising from this method is that individuals who differ in amounts of education consumed and income earned may also systematically differ on other dimensions, such as cognitive ability or personality, confounding the comparison. Ideally, researchers would like to know what an individual’s income would have been if they had pursued additional education and, in a separate but identical reality, what that individual’s income would have been had they not pursued additional education. Such perfect counterfactuals do not exist, so scientists have investigated proxies, such as twins using the MZ co-twin control method. As a result of their matching genetic background and rearing environment, MZ twins are often used as counterfactuals for one another in experimental designs such as the MZ co-twin control (McGue et al., 2010). Numerous twin studies in several nations have produced estimates of the economic benefits of education, and all attempt to reduce the error variance inherent in such estimates by reducing biasing individual differences (Isacsson, 2004; Ashenfelter & Krueger, 1994; Miller et al., 2006). In general, ordinary least squares estimates of the returns to education based on unrelated individuals are around 13% (i.e., an individual’s annual income can be expected to rise 13% with each additional year of schooling, controlling for gender and year of birth) (Leigh & Ryan, 2008). When such individual-level estimates are also adjusted for marital status and full-time worker status, returns to education fall to around 10% in Western countries (Leigh & Ryan, 2008). Further, when MZ twins who are discordant for level of education are used to estimate the returns to education by comparing the income of the twin with more education to the income of the twin with less education, researchers often report estimates around 5% (Miller et al., 2006). Estimates of the returns to education vary based on the cohort examined, level of country development, demographic variables included in the model, types of corrections made to adjust for errors in measurement, and numerous other variables, but in all, the estimates often fall in the 3–15% range (Ashenfelter et al., 1999). Addressing previous concerns by Griliches (1979) and later echoed by Neumark (1999) and others, the current research investigates the tenability of the assumptions that underlie the co-twin control method and may contribute to these differing estimates. Specifically, we examine if twins are similar enough before university to attribute post-university income differences to differences in levels of education. The answer to this query also provides information as to how well the co-twin control method reduces error variance due to individual differences. The twin difference, or MZ co-twin control, method was logically applied to the problem of estimating the returns to education for several reasons. Primarily, it became apparent that ability, environment, personality, and other factors were biasing estimates based on comparisons of unrelated individuals (Card, 2001). MZ twins offer an appealing solution to these confounding issues as MZ twins are assumed to have similar environments and identical genetic material. Given these similarities, any resulting difference in income is more likely attributable to differences in amount of education between the twins. Such a string of logic holds as long as prior to the decision of attending university the twins are matched on variables that are relevant to later income. However, such assumptions are idealistic. More broadly, even MZ twins are likely to differ to some degree in personality, behavior, and abilities and these differences are almost certainly related to later outcomes. If it can be established that MZ twins are significantly different on dimensions related to university attendance that are also related to later life outcomes, then the MZ co-twin control method will not completely account for relevant confounders in estimating the returns to education, both financial and social. We hypothesize that MZ twins differ significantly on several important dimensions before university age, that these differences are related to university attendance, and that these pre-existing differences are also related to later income levels and could thus be biasing MZ co-twin control method estimates of the returns to education. Furthermore, we predict that the MZ twin who attends university will have higher income compared to their non-university attending twin. Within the final prediction, we recognize that MZ twins are highly similar in intelligence (r ~ .80), so we expect the MZ co-twin control method to work well in that regard, although it may not perform as well regarding factors such as personality, which MZ twins are less similar on (r ~ .50) (McGue & Bouchard, 1998). If the MZ co-twin control method fully accounted for confounders when estimating the returns to education, we would expect to see no pre-existing differences within a twin pair on variables that relate to later income in twins before university attendance. The present study investigated a large, longitudinal sample of twins and asked two main questions: 1. To what extent are twins who are discordant for university attendance matched on variables that predict going to university, and 2. If they are not matched, are the differentiating factors also related to later income?