Empirical research on the family cites the tendency for couples to relocate for husbands’ careers as evidence against the gender neutrality of household economic decisions. For these studies, occupational segregation is a concern because occupations are not random by sex and mobility is not random by occupation. I find that the tendency for households to relocate for husbands’ careers is better explained by the segregation of women into geographically dispersed occupations rather than by the direct prioritization of men’s careers. Among never-married workers, women relocate for work less often than men, and the gender effect disappears after occupational segregation is accounted for. Although most two-earner families feature husbands in geographically clustered jobs involving frequent relocation for work, families are no less likely to relocate for work when it belongs to the wife. I conclude that future research in household mobility should treat occupational segregation occurring prior to marriage rather than gender bias within married couples as the primary explanation for the prioritization of husbands’ careers in household mobility decisions.
This is a preview of subscription content, access via your institution.
The study of the segregation of women into low-paying jobs within firms is a familiar application of this approach; fine-grained controls reduce and virtually eliminate the estimated effect of sex (see, for example, Petersen and Morgan 1995 or Reskin and Bielby 2005). However, because relocations for work are rare, introducing occupational fixed effects makes tests very weak. Including a linear term for clustering instead maintains the statistical power of the test while tying results to the specific theoretical construct provided by clustering.
The 2000 PUMS distinguishes 337 occupations by (up to) a six-digit SOC code. By exploiting the hierarchical nature of SOC codes, it is easy to show that aggregating occupations (for example, to three-digit categories) reduces the magnitude of the effects, suggesting potential aggregation bias. Reskin (1993:243) also noted this bias: “. . . ‘college and university teacher’ includes someone teaching night classes on repairing office machines at Parkland Community College as well as a distinguished professor of mathematics at Harvard.” Likewise, segregation into highly mobile subspecialties within occupations would not be captured by aggregate measures like SOC codes. The resulting measurement error (in the independent variable) is expected to cause attenuation bias, reducing the magnitude of the estimated coefficients and increasing the standard errors.
The March CPS features six-digit SOC codes beginning in 2003. Unlike the census or PSID, it asks relocating households to report the primary reason for relocating in the prior year, including “for work or job transfer.” Only 10 % of relocations are for work, and geographic flexibility may lead workers to relocate for reasons other than work, confounding estimates that use observed relocations for all reasons. The March CPS also has much greater statistical power than the PSID. Data are available on the IPUMS website (http://www.cps.ipums.org) (see Ruggles et al. 2010).
Unfortunately, although the CPS reports the principal reason for household relocations, its sample size is far too small to estimate relocation likelihoods by occupation.
“Physicists and astronomers” are treated as distinct from “postsecondary teachers” by the U.S. Bureau of Labor Statistics.
To sign the omitted variable bias posed by the correlation between sex and occupational clustering, I examine pairwise correlations between a female dummy variable, a worker’s occupational clustering score, and an indicator variable denoting that the worker relocates for work. The correlation between the female dummy variable and the clustering score is negative (Hypothesis 1A), and the correlation between the clustering score and relocation for work is positive (Hypothesis 1B), both with p < .01. Therefore, without controlling for clustering, the raw correlation between female and relocation will be biased downward. These correlations are each robust and significant in all nine explored specifications: the full sample, by age less than 35, for never-married and married workers, and by college education (i.e., 1 + 23). Although correlations were strongest among the young and college educated, this check suggests that the OVB very broadly leads to downwardly biased estimates of the independent effect of sex on relocation for work.
Primary reason for relocation is a self-reported variable, and I also examine relocation reported for reasons other than work (results are available upon request). As shown in Table 2, treating “all relocations” as the dependent variable has the following effects: the magnitude of all coefficients is reduced, the coefficient for clustering remains a statistically significant predictor of relocations, and the coefficient for the female variable loses significance in columns 3 and 7. Treating relocations primarily “for family” as the dependent variable has the following effects: the coefficient on clustering loses significance, and the coefficient for the female variable rises. I interpret results to suggest that never-married women are more likely than men to cite family as the primary reason why they relocate, and the geographic clustering of a job is a better predictor of relocations that households report are primarily “for work.”
Among dual-earner couples, 5.09 % of men and women have the same occupation. To avoid bias, the terms for maximal clustering is zero for both spouses when occupations match. These couples are significantly more likely to relocate for work than spouses where the occupations do not match (23.9 %, with a standard error of 9.3 %). One possibility is that work relocations are easier when the husband and wife have the same occupation.
There are also exceptions to the generalization that engineering and technical occupations are geographically clustered; for example, civil engineers, accountants, and auditors are technical occupations, and they are dispersed. They also have rapidly absorbed highly educated women.
This approach would also build on research on the migration of college-educated couples into large metropolitan areas that may be amenable to supporting two careers (see, e.g., Costa and Kahn 2000).
Acker, J. (1990). Hierarchies, jobs, bodies: A theory of gendered organizations. Gender and Society, 4, 139–158.
Anker, R. (1997). Theories of occupational segregation by sex: An overview. International Labour Review, 136, 129–155.
Bailey, A., & Cooke, T. (1998). Family migration and employment: The importance of migration history and gender. International Regional Science Review, 21, 99–118.
Battu, H., Seaman, P., & Sloane, P. (1998). Are married women spatially constrained? A test of gender differentials in labour market outcomes (ERSA Conference Paper). Vienna, Austria: European Regional Science Association. Retrieved from http://www.ersa.org
Becker, P., & Moen, P. (1999). Scaling back: Dual-earner couples’ work-family strategies. Journal of Marriage and the Family, 61, 995–1007.
Benson, A. (Forthcoming). A theory of dual job search and sex-based occupational clustering. Industrial Relations.
Bielby, D., & Bielby, W. (1992). I will follow him: Family ties, gender-role beliefs, and reluctance to relocate for a better job. American Journal of Sociology, 97, 1241–1267.
Blau, F., & Ferber, M. (1991). Career plans and expectations of young women and men: The earnings gap and labor force participation. Journal of Human Resources, 26, 581–607.
Boyle, P., Cooke, T., Halfacree, K., & Smith, D. (2001). A cross-national comparison of the impact of family migration on women’s employment status. Demography, 38, 201–213.
Brandén, M., & Ström, S. (2013). Couples’ education and regional mobility—The importance of occupation, income, and gender. Population, Space and Place, 19, 522–536.
Brewster, K., & Padavic, I. (2004). Change in gender-ideology, 1977–1996: The contributions of intracohort change and population turnover. Journal of Marriage and Family, 62, 477–487.
Ciabattari, T. (2001). Changes in men’s conservative gender ideologies. Gender and Society, 15, 574–591.
Clark, W. A. V., & Huang, Y. (2006). Balancing move and work: Women’s labour market exits and entries after family migration. Population, Space and Place, 12, 31–44.
Cohen, P., & Huffman, M. (2003). Individuals, jobs, and labor markets: The devaluation of women’s work. American Journal of Sociology, 68, 443–463.
Compton, J., & Pollak, R. A. (2007). Why are power couples increasingly concentrated in large metropolitan areas? Journal of Labor Economics, 25, 475–512.
Cooke, T. (2003). Family migration and the relative earnings of husbands and wives. Annals of the Association of American Geographers, 93, 338–349.
Costa, D. L., & Kahn, M. E. (2000). Power couples: Changes in the locational choice of the college educated, 1940–1990. Quarterly Journal of Economics, 115, 1287–1315.
Daymont, T. N., & Andrisani, P. J. (1984). Job preferences, college major, and the gender gap in earnings. Journal of Human Resources, 19, 408–428.
Echevarria, C., & Merlo, A. (1999). Gender differences in education in a dynamic household bargaining model. International Economic Review, 40, 265–286.
Ellison, G., & Glaeser, E. L. (1997). Geographic concentration in U.S. manufacturing industries: A dartboard approach. Journal of Political Economy, 105, 889–927.
Engineer, M., & Welling, L. (1998). Human capital, true love, and gender roles: Is sex destiny? Journal of Economic Behavior and Organization, 40(2), 155–178.
Epstein, C. F. (1990). Deceptive distinctions: Sex, gender, and the social order. Binghampton, NY: Vail-Ballou Press.
Fernandez, R., & Su, C. (2004). Space in the study of labor markets. Annual Review of Sociology, 30, 545–569.
Friede Westring, A., & Ryan, A. M. (2011). Anticipated work-family conflict: A construct investigation. Journal of Vocational Behavior, 79, 596–610.
Gill, L., & Haurin, D. (2002). Wherever he may go: How wives affect their husband’s career decisions. Social Science Research, 27, 264–279.
Hadfield, G. (1999). A coordination model of the sexual division of labor. Journal of Economic Behavior and Organization, 40, 125–153.
Hanson, S., & Pratt, G. (1995). Gender, work, and space. New York, NY: Routledge.
Helppie, B., & Murray-Close, M. (2010). Moving out or moving up? New economists sacrifice job opportunities for proximity to significant others—and vice versa (Working paper). Retrieved from http://www-personal.umich.edu/~Ebhelppie/helppie_ch2.pdf
Jacobsen, J., & Levin, L. (2000). The effects of internal migration on the relative economic status of women and men. Journal of Socio-Economics, 29, 291–304.
Kanter, R. M. (1977). Men and women of the corporation. Cambridge, MA: Harvard University Press.
Long, L. (1974). Women’s labor force participation and the residential mobility of families. Social Forces, 52, 342–348.
Markham, W., & Pleck, J. (1986). Sex and willingness to move for occupational advancement: Some national results. Sociological Quarterly, 27, 121–143.
McKinnish, T. (2008). Spousal mobility and earnings. Demography, 45, 829–849.
McNeil, L., & Sher, M. (2008). Dual-science career couples: Survey results. Physics Today, 52(7), 32–37.
Mincer, J. (1978). Family migration decisions. Journal of Political Economy, 86, 749–773.
Nivalainen, S. (2005). Interregional migration and post-move employment in two-earner families: Evidence from Finland. Regional Studies, 39, 891–907.
Noe, R., Steffy, B., & Barber, A. (1988). An investigation of the factor influencing employees’ willingness to accept mobility opportunities. Personnel Psychology, 41, 559–580.
Ostroff, C., & Clark, M. (2001). Maintaining an internal market: Antecedents of willingness to change jobs. Journal of Vocational Behavior, 59, 425–453.
Petersen, T., & Morgan, L. (1995). Separate and unequal: Occupation-establishment sex segregation and the gender wage gap. American Journal of Sociology, 101, 329–365.
Pixley, J. (2008). Life course patterns of career-prioritizing decisions and occupational attainment in dual-earner couples. Work and Occupations, 35(2), 127–163.
Pixley, J., & Moen, P. (2003). It’s about time: Couples and careers. Ithaca, NY: Cornell University Press.
Reskin, B. (1993). Sex segregation in the workplace. Annual Review of Sociology, 19, 241–270.
Reskin, B., & Bielby, D. (2005). A sociological perspective on gender and career outcomes. Journal of Economic Perspectives, 191, 71–86.
Ressner, U. (1987). The hidden hierarchy: Democracy and equal opportunities. Gower, UK: Aldershot.
Ruggles, S., Alexander, T., Genadek, K., Goeken, R., Schroeder, M. B., & Sobek, M. (2010). Integrated public use microdata series: Version 5.0 [Machine-readable database]. Minneapolis: University of Minnesota.
Sandell, S. (1977). Women and the economics of family migration. Review of Economics and Statistics, 59, 406–414.
Shauman, K. (2010). Gender asymmetry in family migration: Occupational inequality or interspousal comparative advantage? Journal of Marriage and Family, 72, 375–392.
Shauman, K., & Noonan, M. (2007). Family migration and labor force outcomes: Sex differences in occupational context. Social Forces, 85, 1735–1764.
Shihadeh, E. (1991). The prevalence of husband-centered migration: Employment consequences for married mothers. Journal of Marriage and the Family, 53, 432–444.
Simon, R., & Landis, J. (1989). Women’s and men’s attitudes about a woman’s place and role. Public Opinion Quarterly, 53, 265–276.
Sorenson, O., & Dahl, M. (2011). Geography, joint choices, and the reproduction of gender inequality (Working paper). Retrieved from http://ssrn.com/abstract=1968440
Swain, L. L., & Garasky, S. (2007). Migration decisions of dual-earner families: An application of multilevel modeling. Journal of Family and Economic Issues, 28, 151–170.
Turban, D., Campion, J., & Eyring, A. (1992). Factors relating to relocation decisions of research and development employees. Journal of Vocational Behavior, 41, 183–199.
Zvonkovic, A., Greaves, K., Schmiege, C., & Hall, L. (1996). The marital construction of gender through work and family decisions: A qualitative analysis. Journal of Marriage and the Family, 58, 91–100.
I thank Dan Fehder, Roberto Fernandez, Stephanie Hurder, Erin Kelly, George Lan, Colleen Manchester, Matt Marx, Paul Osterman, Gina Rumore, workshop participants at MIT and the Minnesota Population Center, IWER Workshop participants, and MPC Workshop participants for their helpful feedback. I also gratefully acknowledge support from the Minnesota Population Center (5R24HD041023). Replication materials are available upon request. The usual disclaimer applies.
About this article
Cite this article
Benson, A. Rethinking the Two-Body Problem: The Segregation of Women Into Geographically Dispersed Occupations. Demography 51, 1619–1639 (2014). https://doi.org/10.1007/s13524-014-0324-7
- Household mobility
- Occupational segregation