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Demography

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21.10.2015

Opting Out and Leaning In: The Life Course Employment Profiles of Early Baby Boom Women in the United States

verfasst von: Javier García-Manglano

Erschienen in: Demography | Ausgabe 6/2015

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Abstract

Most literature on female employment focuses on the intersection between women’s labor supply and family events such as marriage, divorce, or childbearing. Even when using longitudinal data and methods, most studies estimate average net effects over time and assume homogeneity among women. Less is known about diversity in women’s cumulative work patterns over the long run. Using group-based trajectory analysis, I model the employment trajectories of early Baby Boom women in the United States from ages 20 to 54. I find that women in this cohort can be classified in four ideal-type groups: those who were consistently detached from the labor force (21 %), those who gradually increased their market attachment (27 %), those who worked intensely in young adulthood but dropped out of the workforce after midlife (13 %), and those who were steadily employed across midlife (40 %). I then explore a variety of traits associated with membership in each of these groups. I find that (1) the timing of family events (marriage, fertility) helps to distinguish between groups with weak or strong attachment to the labor force in early adulthood; (2) external constraints (workplace discrimination, husband’s opposition to wife’s work, ill health) explain membership in groups that experienced work trajectory reversals; and (3) individual preferences influence labor supply across women’s life course. This analysis reveals a high degree of complexity in women’s lifetime working patterns, highlighting the need to understand women’s labor supply as a fluid process.

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For the empirical work, I use the Stata traj plugin, developed by Jones and Nagin (2012).

Because I model the probability of being employed at a given age (dummy variable), this section presents the logistic specification of GBTA.

Using time-invariant covariates might raise endogeneity concerns, which are otherwise unavoidable in this type of analysis given that GBTA is not primarily aimed at elucidating causality. To assuage this concern, I ran alternative models (available upon request) in which key independent variables were defined early in adulthood. Results were substantively similar; I provide further comments on these models in the Discussion section.

I considered dropping more generally all observations in which women were enrolled in school, but decided against it because (1) higher education is often combined with employment, and the data don’t allow us to decipher which of the two activities was given priority at each point in time; and (2) this is a study of women’s labor supply, and the possibility that education might have lead some women to take up low-paying or part-time work is less relevant than the fact that they were employed.

Table 5 in the appendix lists all the variables used, including the years in which each of them was available.

A minority of women were never observed to be working for pay between the ages of 20 and 54. These “undefined” cases are given the value 0, because workplace discrimination was not a relevant issue for them. The same decision was made for the dummy variables “being dissatisfied with work” and “having a husband who opposes her employment” for women never observed to be employed and married, respectively. Analyses, available upon request, in which “undefined” values were imputed using three alternative methods (grouping into a separate category, multiple imputation, and listwise deletion) produced consistent results.

Following prior literature (Hayford 2009; Ryder and Westoff 1971), which found these concepts to be empirically similar, I use the terms “expectations,” “plans,” “intentions,” “orientations,” and “preferences” interchangeably throughout this article.

This model with four quadratic trajectory groups was replicated using Mplus (Muthén and Muthén 2014), allowing me to confirm that the results reported here are not the result of local maxima and that my models achieved a satisfactory entropy score (0.71). Mplus scripts are available upon request.

The results shown here correspond to a common multinomial logistic model. However, to better illustrate differences between pairs of groups, I switched reference categories and split the results in different tables. For the full model, including all possible groups comparisons, see Table 6 in the appendix.

Unfortunately, recent NLS surveys did not collect data on key variables, such as husband’s opposition to their wives’ employment, women’s own work plans and expectations, satisfaction with the role of caring for children, and the health of relatives. Roughly similar analyses of the employment trajectories of women in the NLSY-79 cohort—whose older members are in their early 50s as of this writing—reveal the existence of similar groups, with slightly different compositions: (1) Consistently Detached (16 %); (2) Increasingly Attached (25 %); (3) Increasingly Detached (22 %); and (4) Consistently Attached (36 %). These results are available upon request. However, because of the lack of key covariates, conducting a fully comparable analysis of the traits associated with group membership is not possible using more recent NLS cohorts.

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Titel: Opting Out and Leaning In: The Life Course Employment Profiles of Early Baby Boom Women in the United States
verfasst von: Javier García-Manglano
Publikationsdatum: 21.10.2015
Verlag: Springer US
Erschienen in: Demography / Ausgabe 6/2015
Print ISSN: 0070-3370
Elektronische ISSN: 1533-7790
DOI: https://doi.org/10.1007/s13524-015-0438-6

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