Abstract
Using U.S. Census data from 1960 to 2000 and American Community Survey data from 2010, this paper estimates the relationship between the husband’s educational attainment and his wife’s annual labor earnings. For full-time working wives, each additional year of completed schooling by the husband was associated with a 2% increase in his wife’s earnings. The returns to spousal education were larger when the couple worked in the same occupation. The estimated relationship has increased slightly since 1970. This increase was larger for younger wives. These results are consistent with cross-productivity and documented increases in educational homogamy.
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Wong (1986), Tiefenthaler (1997), Huang et al. (2009), Groothuis and Gabriel (2010), and Dribe and Nystedt (2013) also examined the association between the wife’s education and the husband’s earnings. Wong (1986) and Tiefenthaler (1997) found estimates similar to those already reviewed. Huang et al. (2009) found an insignificant relationship using Chinese data. The authors claimed that this is due to the patriarchal nature of Chinese marriages. Groothuis and Gabriel (2010) found a positive relationship between the wife’s education and the husband’s earnings, and this relationship grows as the husband acquires more schooling. Dribe and Nystedt (2013) found that men also experience a relative penalty when they enter a hypogamous union. However, the penalty is not as large as it is for women.
Bailey (2006) presented evidence suggesting that access to oral contraception increases female labor force participation and hours worked. This would be particularly true for younger women. Furthermore, oral contraceptives have been linked to reduced marriage rates for women with a college education (Stevenson and Wolfers 2007).
Furtado (2016) showed that native women respond to increases in immigrant inflows by working longer hours due to immigration lowering childcare costs.
The authors showed that the correlation between spousal earnings differs by whether the couple is a newlywed or not (i.e. newlywed versus prevailing couples). For prevailing marriages, the correlation increased from 1970 to the 1990s. Since then, however, there was little increase. For newlyweds, the correlation between spousal earnings remained relatively flat over time.
The survey question asking about school enrollment inquired about enrollment during a reference period. From 1960 to 2000, the period was since February 1 of the survey year. For the 2010 ACS, the reference period was the previous 3 months. The 1960 sample may contain some individuals currently enrolled in school if they are older than 34 because data on school enrollment was not available for that age range in that Census. During that year, the survey question was only asked of individuals younger than 35. Therefore, to keep the samples as comparable as possible across the six decades, the 1960 sample included couples where neither spouse was enrolled in school or where either spouse was at least 35 years old.
The 1980 and 1990 Census also asked about hours worked during the previous week. As a comparison, the 1960/1970 full-time definition was applied to the 1980 and 1990 data. Using the 1980 sample, 87% of the full-time workers in the 1980 data were classified as full-time workers using the 1960/1970 definition. The rate in the 1990 data was 89%. Therefore, using the 1960/1970 full-time definition resulted in little difference in comparability across years. The main analysis was replicated using the 1960/1970 full-time definition on the 1980 and 1990 samples. Results were little changed and available upon request.
The education variable in IPUMS does not have consistent responses from decade to decade. From 1960 to 1980, the Census gathered information on the number of completed years of education. It did not have information on degree completion. Therefore, when constructing the degree categories for 1960 to 1980, a high school degree was equivalent to completing 12 grades, a College Graduate was the equivalent of completing 4 years of college, and Above College included completing at least 5 years of college. Starting in 1990, the Census and ACS used three different types of responses. The first was degree completion (e.g. bachelor’s degree). The second was ranges of grades, such as Grades 1 through 4. The final type was the completed year of education, such as Grade 10. When constructing the Years of Education variable from 1990 to 2010, a high school degree was equivalent to completing 12 grades, an associate’s degree required two years of college, a bachelor’s degree required 4 years of college, and a master’s degree or above required 6 years of college. If the response was a range of grades (e.g. Grades 1 through 4), then the years of education equaled the midpoint of the range. When constructing the educational categories for 1990 to 2010, an associate’s degree was included in Some College, and a master’s degree and above was included in Above College. To maintain consistency across all six decades of data, the continuous measure of education was capped at 19 years of schooling.
In an appendix available upon request, the various tests for assortative mating versus cross-productivity were discussed and performed. Like the earlier literature, the results from these tests were inconclusive regarding which effect was more important when explaining the estimated return to spousal education.
The return as a percentage was calculated as \(\left( {e^{{\hat{\beta }}} - 1} \right)\;*\;100\).
In results not shown, Eq. (1) was re-estimated after removing husband’s education from the regression. When doing so, the returns to own education changed by 1.5 percentage points or less.
Instead of using educational dummy variables to allow for a non-linear relationship between the husband’s education and his wife’s earnings, an alternative strategy is to include a quadratic in his years of schooling. Equation (1) was re-estimated when including the husband’s years of schooling and years of schooling squared in the regression instead of the educational dummy variables. Results showed that wives experienced a positive return to spousal schooling for every year of completed schooling of the husband. The only exception to this was in 1960 when the husband had 19 years of completed education. However, this value of education only applied to 2% of the sample used in 1960. Furthermore, from 1960 to 1980, wives’ earnings increased at a decreasing rate with the husbands’ years of schooling. This pattern is reversed starting in 1990. From 1990 onwards, wives’ earnings increased at an increasing rate with the husbands’ years of schooling. These results are available upon request.
The results from this study are not directly comparable to those in Jepsen’s (2005) analysis. The author used an age range of 18–64, allowed individuals to be enrolled in school, and used a slightly different set of independent variables in the earnings equations. Specifically, Jepsen (2005) included potential experience instead of age and had fewer industry and occupation dummy variables. Additionally, Jepsen’s (2005) definition of full-time work was working at least 35 h in a week and working at least 45 weeks during the year, as opposed to 40 weeks used in this paper. The difference in the definition of full-time work occurred because the weeks worked variable in the IPUMS dataset was recorded as an interval, with one of the intervals ranging from 40 to 47 weeks.
While the sample used here consisted of full-time working wives, no sample selection correction was performed. This is because the log of annual earnings was used as the dependent variable (recall, a consistent measure of wage cannot be constructed). Annual earnings change because of changes in wages and/or labor supply. For proper identification, sample selection correction methodologies (such as Heckman’s two-step procedure) require a variable in the first stage regression that affects participation and not earnings. Since earnings here consist of wages and labor supply, this type of variable is not clear. Anything that affects participation would most likely affect hours worked and, therefore, annual earnings. A variable typically included in the first stage and excluded in the second is number of children. Therefore, the Heckman two-step procedure was conducted here when including the number of children and the number of children under 5 years old in the first stage regression. Results from the second stage regression showed that the effect of spousal education on wives’ annual earnings equaled 0.018 in 1960, 0.016 in 1970, 0.015 in 1980, 0.018 in 1990, 0.020 in 2000, and 0.018 in 2010. Therefore, the main results from the analysis hold with this sample selection correction procedure. However, the number of children and the number of children under five years old do affect annual earnings. Equation (1) was re-estimated after including these two variables. With each decade of data, these two variables were jointly significant. The results from Table 2 are little changed when including these two variables. The estimated coefficients equaled 0.015 in 1960, 0.012 in 1970, 0.012 in 1980, 0.015 in 1990, 0.018 in 2000, and 0.019 in 2010. Estimates were similar when also including age of the oldest and youngest child in the home in the regressions. Since including these variables did not change the estimated returns to spousal schooling in any meaningful manner, they were not presented in the main results here to maintain comparability to Jepsen’s (2005) analysis.
Equation (1) was also estimated separately based upon the nativity of the wife. The results are available upon request. The coefficient associated with spousal schooling was larger for native-born, full-time working wives relative to their foreign-born counterparts. Furthermore, while the coefficient grew over time for native born women, it was relatively stable for the foreign-born group.
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Acknowledgements
I thank Yilan Liu for motivating this study and providing research assistance. Gwendolyn Davis, Delia Furtado, Marina Gindelsky, Peter Groothuis, Richard Hill, two anonymous referees, the editor, and seminar participants at Marquette University, DePaul University, University of Wisconsin—Milwaukee, and the Western Economic Association International 2017 Annual Meeting provided helpful comments on earlier drafts. All errors are my own.
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Jolly, N.A. Female Earnings and the Returns to Spousal Education Over Time. J Fam Econ Iss 40, 691–709 (2019). https://doi.org/10.1007/s10834-019-09637-z
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DOI: https://doi.org/10.1007/s10834-019-09637-z