Abstract
We examine whether the positive effects of educational attainment on views toward ethnic diversity and a sense of world citizenship are influenced by personal views related to gender equality, civil rights for all, and sexual orientation. Our hypothesis is that tolerance toward those of different ethnic backgrounds is enhanced with greater educational attainment, but the effect is weaker for those with intolerant views toward those with different sexual orientations or to equal rights (or status) for women. Thus, basic views of civil rights, gender equality, and tolerance for those with different sexual orientations are a foundational condition for education having a strong positive effect on attitudes toward those of different ethnic backgrounds as well. In environments where these basic views of gender and sexual equality do not exist, additional education does not seem to have a meaningful impact on individual attitudes toward those of different ethnic backgrounds.
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Notes
Ethnicity is identity related to a specific cultural or national tradition. Ethnic diversity refers to the presence of people from a variety of cultural and ethnic backgrounds or identities. An immigrant is a person who migrates to another country other than that of their birth, usually for permanent residence. Places with immigrants from a large number of different countries will thus have a larger degree of ethnic diversity.
We need to add the caveat that our results should also be viewed as statistically significant associative correlations and not necessarily causal due to possible endogeneity, reverse causality, sample selection, finite-sample issues, or omitted variables. We employ IV estimation, establish identification by addressing omitted variable bias, and utilize inverse probability weight estimates to address endogeneity that could arise out of sample selection bias. For a discussion of these methods and issues see Persson and Tabellini (2006), Clemens et al. (2012), Murray (2006), and Baum (2008).
To be clear, the underlying survey variable has multiple responses, and we have recoded it as a binary variable for "agree" or not. Thus, our variable takes the value of one for a response of either "agree" or "strongly agree," and zero otherwise. This is true throughout our analysis; for example, in other cases we use a similar approach to construct "disagree" (a combination of both strongly disagree and disagree, and zero otherwise).
A value of 0 indicates no formal education, 1 indicates incomplete primary education, 2 indicates completed primary education, 3 indicates incomplete vocational/technical secondary education, 4 indicates completed vocational/technical secondary education, 5 indicates incomplete university/college preparatory secondary education, 6 indicates complete university/college preparatory secondary education, 7 indicates incomplete university education, and 8 represents a complete university education status.
As an alternate measure of income, the survey also includes self-reported income deciles in addition to self-reported class membership. For robustness, we checked if using these to construct alternative class measures (lowest three deciles coded lowest class, middle four deciles coded as middle class, and top three deciles coded as upper class) affected the results, which it did not, our results remain robust.
While our dataset is cross-national, one cannot help but to wonder if this relationship we uncover is not partially a good explanation for the differentials across the US states in respect of ethnic diversity and immigrants, and how strongly correlated they are with states which were the first to legalize same-sex marriages, and overall average levels of education. Our results would predict that states that legalized same-sex marriages first, and that had higher levels of education, would be the most accepting of immigrants and those from different ethnic backgrounds. Or, in reverse, that in those states where individuals were mostly opposed to legalizing same-sex marriages, even those with higher education are less accepting of immigrants and those from different ethnic backgrounds.
While we try to provide evidence of the linear relationships with education in Fig. 1, there is still the possibility, as there is in any empirical analysis, that nonlinearities could exist with this or the other independent variables that could cause potential biases.
Murray (2006) and Baum (2008) point out that the finite-sample properties of IV estimates are problematic. If instruments are weak, IV estimators may not be an improvement over OLS estimators (Clemens et al. 2012). Persson and Tabellini (2006) note the difficulty in finding efficient, time varying instruments that are strictly exogenous.
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Dutta, N., Sobel, R.S. Is education’s positive impact on views toward ethnic diversity affected by views toward gender and LGBTQ+ equality?. J. Soc. Econ. Dev. (2024). https://doi.org/10.1007/s40847-023-00283-8
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DOI: https://doi.org/10.1007/s40847-023-00283-8