Who Cares - And Does It Matter? Measuring Wage Penalties for Caring Work

Hirsch, Barry T.; Manzella, Julia

doi:10.2139/ssrn.2550448

Cited by 5 publications

(6 citation statements)

References 35 publications

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“…More recently some research suggests that "care work"-occupations in which "concern for the well-being of others is likely to affect the quality of services provided"-may pay less ceteris paribus. For a review, see Folbre (2012), quotation is from p. 66; see also Hirsch and Manzella (2015). Women are disproportionately represented in such jobs.…”

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confidence: 99%

The Gender Wage Gap: Extent, Trends, and Explanations

Blau

Kahn

2017

Journal of Economic Literature

1,984

740

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Using Panel Study of Income Dynamics (PSID) microdata over the 1980–2010 period, we provide new empirical evidence on the extent of and trends in the gender wage gap, which declined considerably during this time. By 2010, conventional human capital variables taken together explained little of the gender wage gap, while gender differences in occupation and industry continued to be important. Moreover, the gender pay gap declined much more slowly at the top of the wage distribution than at the middle or bottom and by 2010 was noticeably higher at the top. We then survey the literature to identify what has been learned about the explanations for the gap. We conclude that many of the traditional explanations continue to have salience. Although human-capital factors are now relatively unimportant in the aggregate, women's work force interruptions and shorter hours remain significant in high-skilled occupations, possibly due to compensating differentials. Gender differences in occupations and industries, as well as differences in gender roles and the gender division of labor remain important, and research based on experimental evidence strongly suggests that discrimination cannot be discounted. Psychological attributes or noncognitive skills comprise one of the newer explanations for gender differences in outcomes. Our effort to assess the quantitative evidence on the importance of these factors suggests that they account for a small to moderate portion of the gender pay gap, considerably smaller than, say, occupation and industry effects, though they appear to modestly contribute to these differences. ( JEL I26, J16, J24, J31, J71)

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confidence: 99%

The Gender Wage Gap: Extent, Trends, and Explanations

Blau

Kahn

2017

Journal of Economic Literature

1,984

740

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“…A similar approach has also been extended to the study of specific types of care work, such as nurturant or reproductive care work (Dwyer 2013). Continuous measurement of specific social skill dimensions has begun to develop only recently (Deming 2015;Green 2012;Hirsch and Manzella 2015;Liu and Grusky 2013). Although these latest approaches acknowledge and explore the complexities of social skills, they are still limited in that they focus on a small and predetermined set of social skill categories.…”

Section: Skill Measurement and Dimensionalitymentioning

confidence: 99%

Social Skill Dimensions and Career Dynamics

Wyant

Manzoni

McDonald

2018

Socius: Sociological Research for a Dynamic World

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All work is social, yet little is known about social skill dimensions or how social skill experiences accumulate across careers. Using occupational data (O*NET) on social tasks, the authors identify social skills’ latent dimensions. They find four main types: emotion, communication, coordination, and sales. O*NET provides skill importance scores for each occupation, which the authors link to individual careers (Panel Study of Income Dynamics). The authors then analyze cumulative skill exposure among three cohorts of workers using multitrajectory modeling. They find substantial variability in social skill experience across early-, middle-, and late-career workers. White, female, and highly educated workers are the most likely to accumulate social skill experience, net of total years of experience. Group differences in cumulative exposure to social skill are rooted in early-career experiences. This study enhances the understanding of social skill exposure across careers and has important implications for future research on social stratification and economic inequality.

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“…There is an extensive literature suggesting that wage inequality is socially constructed and that work in women's occupations is undervalued by reason of institutionalized bias against women (see, for example, Treiman and Hartmann, 1981;Kilbourne et al, 1994;Magnusson, 2009) even if the skills required for lower-paid female dominated jobs are comparable to those in better-paid maledominated jobs. One of the more transparent aspects of bias is the devaluation of caring and nurturing skills associated with women (Hirsch and Manzella, 2015).…”

Section: Theoretical Considerationsmentioning

confidence: 99%

The Occupational Feminization of Wages

Addison¹,

Öztürk²,

Wang

2017

ILR Review

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The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Macpherson and Hirsch (1995) of the effects of occupational gender composition on earnings using monthly CPS data for 1973-1993. In the updating process, we correct for biases in this dataset due to the inclusion of imputed earners and the misreporting of occupation. CPS data for 1996-2010 are used to provide cross-sectional estimates of the impact of feminization on wages as well as its contribution to the gender wage gap. Longitudinal CPS data indicates that the negative effects of gender composition on earnings observed in cross section are lessened (much reduced) when we control for observed (unobserved) heterogeneity. These findings are confirmed using much longer panels from the NLSY. Finally, constructing synthetic panels of aging cohorts suggests that wage penalties are largest for younger cohorts in female occupations. (134 words) JEL Classification: J31, J71 Keywords: wages, gender composition, gender wage gap At first blush, the negative effect of the gender composition of an occupation -that is, its proportion female -on the earnings of women (and men) in that occupation might seem to offer a blueprint for policy initiatives. Such measures might include quotas to increase the female component in male jobs and comparable worth, together with more conventional instruments seeking to strengthen human capital endowments. Unfortunately, the empirical consensus does not extend much beyond agreement on the stylized facts of earnings disparities that are increasing in feminization. Acting to blunt policy activism, therefore, is disputation as regards the size and persistence of the negative correlation between gender composition and wages as well as disagreement as to underlying causation.At root, the controversy has a basis in a literature often containing scant controls for observables such as occupational characteristics that may influence earnings and earning development. Further, the number of studies using longitudinal analysis is still somewhat meager. In the latter context the gender composition variable may in practice be correlated with unmeasured skill and taste differences among workers, and in the former with controls for occupational attributes that might reasonably be expected to influence earnings.The present paper is motivated by an important study of occupational sex segregation by Macpherson and Hirsch (1995) that is notable in three principal respects: first, in its use of several large datasets; second, in its deployment of arguments not typically found in...

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Who Cares - And Does It Matter? Measuring Wage Penalties for Caring Work

Cited by 5 publications

References 35 publications

The Gender Wage Gap: Extent, Trends, and Explanations

The Gender Wage Gap: Extent, Trends, and Explanations

Social Skill Dimensions and Career Dynamics

The Occupational Feminization of Wages

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