Segregation across Workplaces and the Motherhood Wage Gap: Why Do Mothers Work in Low-Wage Establishments?

Segregation across Workplaces and the Motherhood Wage Gap: Why Do Mothers Work in Low-Wage... Abstract While maternal employment has become the norm in advanced industrial nations, gendered norms of parenting and employment disadvantage mothers in the labor force. This paper sheds new light on motherhood pay gaps by investigating the contribution of an understudied dynamic—mothers’ overrepresentation in low-paying workplaces. Estimating between- and within-establishment wage gaps with nationally representative Canadian linked employer-employee data reveals that segregation in low-paying establishments accounts for the bulk of mothers’ wage disadvantage relative to childless women. Pay gaps net of human capital differences are not chiefly a result of mothers’ lower wages vis-à-vis similar women in a given workplace, but rather stem from the fact that mothers are disproportionately employed in workplaces that pay all employees relatively poorly. Having identified the importance of between-establishment segregation, additional analyses probe support for two theories about underlying mechanisms: compensating differentials tied to family-supportive work contexts, and discrimination. While each plays a role, evidence is strongest for discrimination, with organizational characteristics that tend to reduce opportunities for discrimination also dramatically reducing or eliminating motherhood pay gaps. Introduction Across national contexts, gendered norms of parenting and employment work to mothers’ disadvantage (Aisenbrey, Evertsson, and Grunow 2009; Harkness and Waldfogel 2003; Viitanen 2014). While mothers typically earn lower wages than women without children, the reverse is true for fathers (Cooke 2014; Hodges and Budig 2010; Killewald 2012; Petersen, Penner, and Høgsnes 2014; Zhang 2009). Parenthood is thus an important factor underlying gendered inequalities in employment. A substantial body of research has investigated wage gaps between mothers and childless women, but the vast majority has drawn on individual-level survey data. Consequently, relatively little is known about the role of organizational context in shaping motherhood wage gaps. Drawing on linked employer-employee survey data from Canada, this paper investigates one key facet of mothers’ disadvantage—their segregation in lower-paying establishments—and how this is impacted by establishment variation in work arrangements, family benefits, and opportunities for discrimination against mothers. Establishments are important agents in generating patterns of wage inequality insofar as they set wage scales and contracts, make hiring decisions, and earn the revenues from which wages are paid (Baron and Bielby 1980; Bidwell et al. 2013; Sakamoto and Wang 2016). Establishments vary in the extent to which they can afford to offer workers higher or lower wages, as well as in the degree to which workers have the bargaining power to force their employers to share market rents. Much recent sociological theorizing and empirical work about organizational context and group-based inequalities has focused on factors impacting the distribution of wages within organizations, such as the bargaining power of internal constituencies, the height of internal hierarchies, informal workplace cultures, and organizational rules and regulatory mechanisms (e.g., Avent-Holt and Tomaksovic-Devey 2010, 2014; Baron et al. 2007; Tilly 1998). While generating many useful insights, research focusing solely on internal wage hierarchies neglects the potential importance of who works in particular organizations in the first place. Inequalities are generated not only via within-establishment wage differences, but also by virtue of how people are sorted across them. Establishments vary substantially in their overall wage rates, variation that cannot be explained entirely by the characteristics of their workers (Abowd, Kramarz, and Margolis 1999; Bronars and Famulari 1997; Lane, Salmon, and Spletzer 2007). Indeed, wages vary more across establishments than within them (Groshen 1991; Lane, Salmon, and Spletzer 2007). A number of recent studies demonstrate that wage gaps for disadvantaged groups arise in part through their segregation in establishments that, net of workers’ individual and occupational characteristics, tend to offer lower wages (Bayard et al. 2003; Drolet and Mumford 2012; Javdani 2015; Pendakur and Woodcock 2010; Petersen and Morgan 1995). Three point to the relevance of establishment sorting for motherhood wage differentials specifically, although they find it less important than within-establishment wage gaps (Beblo, Bender, and Wolf 2008; Petersen, Penner, and Høgsnes 2010, 2014). These latter studies, however, are not representative of the labor market as a whole and use data from countries (Germany and Norway) with extensive coordination and centralization of wage-setting, which tends to mute the potential role of establishment wage differentials for group wage gaps (OECD 2004; Simón 2010). Moreover, they do not explicitly investigate what it is about motherhood, jobs, and organizations that leads mothers to be disproportionately located in lower-waged establishments. In fact, inattention to the relationship between organization characteristics and between-establishment segregation is a general limitation of quantitative studies focusing on the role of such segregation for wage gaps between groups (e.g., Bayard et al. 2003; Drolet and Mumford 2012; Javdani 2015; Pendakur and Woodcock 2010). Extant research has documented its importance but has not explored its underlying mechanisms. This study extends existing research on establishment segregation and group wage gaps in two directions. First, I present the first decomposition of within- and between-establishment components of motherhood pay differentials using broadly representative North American data, Statistics Canada’s Workplace and Employee Survey (WES). Because wage setting in North America typically takes place at the establishment level, it is an important site for studying the role of establishment wage differentials for group wage gaps. Second, I take advantage of rich information on individual work arrangements and establishment-level characteristics in the WES to consider alternative theories on the mechanisms contributing to motherhood wage gaps tied to establishment segregation: mothers choose lower-wage employers to access more family-friendly jobs and organizations; or, hiring agents disproportionately shuts mothers out of higher-paying establishments where organizational constraints on discrimination are weak. Motherhood pay penalties and organizational segregation Scholarship on labor market inequalities is extensive. Driven in part by the predominance of individual-level data, sociologists and labor economists have largely built empirical models grounded in the human capital model of earnings determination whereby individual investments to raise productive capacity (education, training, on-the-job experience) translate into higher wages. While past research has suggested that lost human capital tied to employment breaks for caregiving contributes to motherhood pay gaps, human capital variables do not typically account for its entirety (Avellar and Smock 2003; Budig and England 2001; Zhang 2009). Rather than seeing wages as arising from an efficient labor market balancing individual skill and market demand, sociologists and organizational scholars often emphasize the social relations and structural features of organizations, as well as the broader environment in which they operate (Avent-Holt and Tomaskovic-Devey 2010; Kalev 2014; Stainback, Ratliff, and Roscigno 2011; Stainback, Tomaskovic-Devey, and Skaggs 2010). Moreover, feminist scholars of work and organization insist that organizational logics are enmeshed with broader societal contexts, notably gendered household dynamics. Such scholars point out critical disjunctures between assumptions often underlying the organization of work (a worker wholly available and devoted to work demands) and the imperatives of care (Acker 2006; Dodson 2013; Epstein et al. 2014; Kelly, Moen, and Tranby 2011; Stone and Hernandez 2013; Williams 2000). Drawing on these insights, the next section develops two arguments specifying how organizational contexts could shape mothers’ distribution across establishments, with consequences for motherhood wage gaps. The first focuses on possible trade-offs mothers might make to access organizations that offer better arrangements for combining employment and caregiving. The second shifts attention from mothers’ constrained choices to employer decisions. Here, the focus is on how organizational features impact the likelihood that bias against mothers will result in discrimination, blocking them from employment in better-paying establishments. Both of the arguments I develop lead to a scenario whereby mothers are disadvantaged via segregation in lower-paying establishments. What differs are the mechanisms leading to this outcome. Family (un)friendly jobs and organizations: compensating differentials The theory of compensating differentials posits that mothers trade higher earnings to accommodate caregiving (Becker 1993; Felfe 2012; Glauber 2012; Heywood, Siebert, and Wei 2007). While often couched in terms of individual choice, the necessity of such trade-offs rests on employment norms that presume a worker able to devote herself entirely to the organization (Acker 1990; Vosko 2009; Williams 2000). Constraints around the need to attend to dependent others challenge this ideal. While men increasingly engage in housework and childcare, mothers remain disproportionately responsible for caregiving and more often adapt their employment to accommodate it (Beaujot and Ravanera 2009; Marshall 2009; Raley, Bianchi, and Wang 2012). “Family-friendly” work conditions such as part-time hours and flexibility in where and when to work presumably ease conflict between care and employment (Anderson, Binder, and Krause 2003; Boushey 2008; Kelly, Moen, and Tranby 2011; Williams 2010). Overtime, conversely, can be unpredictable and difficult to reconcile with family schedules (Golden and Wiens-Tuers 2005). In Canada, almost 60 percent of hourly workers who work overtime have less than one day’s advance notice about overtime schedules (McCrate 2016). Not all researchers find that family-supportive work arrangements are associated with lower wages and/or motherhood pay gaps (Boushey 2008; Gariety and Shaffer 2001; McCrate 2005; Weeden 2005), but some link flexible hours, working at home, and part-time work to lower wages for at least some workers (Bardasi and Gornick 2008; Dau-Schmidt et al. 2009; Glass 2004; McGinnity and McManus 2007; Webber and Williams 2008). By contrast, employers typically pay overtime at a higher rate (at least for hourly workers). Compensating differentials do not necessarily imply a link to establishment wage-differentials, as individuals may make trade-offs within the context of different opportunities within an organization (past research typically does not distinguish at which level effects occur). However, the availability of particular work arrangements is often conditional on one’s employer (Haley-Lock 2011; Heywood, Siebert, and Wei 2007; Sweet et al. 2014). Canadian workers do not have the right to refuse overtime, and while some European countries provide statutory rights to adjust working hours with one’s employer, Canada does not. Even in Germany, where such a right exists, when women have children, switching job dimensions commonly entails employer changes (Felfe 2012). Shifting to a work arrangement more accommodating to caregiving demands may thus require changing employers. Mothers may also trade wages for a more generally amenable work culture (Fakih 2014). An organization that treats care demands as illegitimate and makes them difficult to reconcile with employment can push mothers to look elsewhere for work (Blair-Loy 2003; Herr and Wolfram 2012; Stone and Hernandez 2013). Work culture rests in part on everyday practices of managers and coworkers that are difficult to capture in large-scale datasets.1 However, organizational policies, such as generous provisions around parental leave and employer assistance with family-related matters, can signal an employer’s commitments to some degree.2 If mothers are most interested in accommodating employment to caregiving demands, and if employers need to offset associated costs (such as overhead associated with hiring more employees or problems with coordinating work) (Baughman, DiNardi, and Holtz-Eakin 2003; Fakih 2014; Heywood, Siebert, and Wei 2007),3 this could result in mothers’ segregation in lower-paying establishments. Low-wage employers may also offer part-time positions in particular to minimize worker wages and benefits (Lambert, Haley-Lock, and Henly 2012), which would also imply a link between motherhood penalties, part-time jobs, and lower wages at the establishment level. Opportunities for Discrimination The compensating differentials argument suggests that mothers actively select into organizations paying below-market wages to gain or retain family-supportive work. Organizational segregation could also result more directly from employer action. Efficiency wage theories posit that some firms pay above-market wages to attract the most productive workers, encourage retention, and discourage shirking (Akerlof 1982; Salop 1979; Shapiro and Stiglitz 1984). This matters for mothers in particular, insofar as motherhood negatively impacts assumptions of both competence and commitment, which are key criteria employers use when evaluating workers (Fuegen et al. 2004; Heilman and Okimoto 2008; Ridgeway and Correll 2004). Mothers may therefore face stronger barriers to employment at better-paying establishments concerned with retention and maximizing worker quality and effort. Although bias against mothers may affect decisions on pay and promotions for existing employees, discrimination should be particularly pronounced at the point of hire. It is easier to perceive and contest discrimination in an ongoing employment relationship (Petersen and Saporta 2004).4 Moreover, employers make hiring decisions with limited information, increasing the likelihood that they will base decisions on stereotypes. Notably, unlike gender and race, motherhood involves an identity transformation. Motherhood status is more obvious in the context of an existing employment relationship. Indeed, it may be impossible to discern from a resume, and may or may not come up in the context of a job interview via informal chitchat or employer or employee questions abound how job conditions would impact caregiving arrangements.5 However, the salience of motherhood as a frame for interpreting competence and commitment should be reduced when a woman already has a track record at her establishment. Conversely, being on the job market may be interpreted as a more negative signal for mothers, given the prevalence of stereotypes of them as less committed. Consistent with this, Fuller (2008) and Looze (2014) find that American mothers typically fail to realize the same wage gains with voluntary job changes as do other women, and Glass (2004) finds that mothers lower their wages with employer changes (none of these authors can determine whether this stems from lower wage offers or barriers to hire at better-paying establishments). While simply being on the job market may activate stereotypes about mothers, they should be particularly salient for those returning after parental leave. In this case, motherhood would not only be more visible (via a recent gap on the resume), but uncertainty about a woman’s commitment and how she will manage the responsibilities of employment and motherhood will be highest. This may help account for Fuller’s (2008) finding that “family-related” job changes result in substantial wage penalties for American women net of the impact of lost experience,6 and why returning to the same employer after maternity leave reduces mothers’ pay losses (Felfe 2012; Phipps, Burton, and Lethbridge 2001; Zhang 2010). It is not simply mothers’ positioning that may moderate discrimination. Organizational and institutional features such as legitimacy imperatives and formalization create differences in opportunities for discrimination (Petersen and Saporta 2004; Stainback, Tomaskovic-Devey, and Skaggs 2010). Human rights legislation prohibits family status discrimination in all Canadian provinces save New Brunswick. While this extends to all employers in theory, public-sector organizations face legitimacy concerns and legal environments that create a stronger impetus to be “fair” employers (DiMaggio and Powell 1983; Fuller 2005). The public sector is more subject to equity-enhancing policy, contributing to higher legal awareness of antidiscrimination imperatives (Wilson, Roscigno, and Huffman 2013). Historically, the public sector has provided more equitable employment outcomes for disadvantaged groups (Fuller 2005; Hou and Coulombe 2010; Waite and Denier 2015; Wilson, Roscigno, and Huffman 2013, 2015). There is less research on group-based wage gaps for other kinds of nonprofit organizations, and nonprofits can vary dramatically in their cultures and commitments. Nonetheless, the historic ties between many voluntary-sector organizations and social justice movements heighten attention to concerns with equality as well (Damman, Heyse, and Mills 2014; Mastracci and Herring 2010; Tomlinson and Schwabenland 2010). This may help counter rationales for discrimination against mothers that elevate business concerns above all else (see Byron and Roscigno (2014) for an analysis of this in pregnancy discrimination). Standardized procedures monitored by human resource professionals reduce supervisors’ discretion to incorporate personal biases (Baron et al. 2007; Dobbin 2009; Reskin and McBrier 2000). Collective bargaining imposes more formal rules around hiring as well (Elvira and Saporta 2001; Tomaskovic-Devey, Hällsten, and Avent-Holt 2015). Formalization should be particularly salient with respect to hiring discrimination against mothers insofar as motherhood is not obviously observable. Human resource professionals play a central role in interpreting how legal mandates should be incorporated in organizational practice (Dobbin 2009). In establishments with formalized hiring procedures monitored by professionals, hiring agents are more likely trained not to inquire about family status. In the UK, Adams et al. (2016) find that employers who did not provide training or other support to managers about pregnancy and maternity-related issues were more likely to espouse beliefs inconsistent with legal mandates (i.e., to believe that women should declare if they were pregnant during recruitment and that it is reasonable to ask prospective hires about their childbearing plans). Arguments about legitimacy imperatives and formalization thus imply that mothers will be less segregated in lower-paying establishments among the subset of establishments that are nonprofit/unionized/have formal HR. Data and Methods Data come from the WES, a mandatory linked employer-employee survey fielded by Statistics Canada from 1999 to 2005. Employees were followed for two years, and the employer sample was longitudinal, with the sample refreshed every second year. The target population was all Canadian establishments with paid employees, with the exception of public administration7 and employers in crop and animal production; fishing, hunting, and trapping; private households; and religious organizations. The employer sample was drawn from the Business Registrar, Statistics Canada’s monthly list of all businesses in the country. Establishments are defined as “the smallest organizational unit, comprised of at least one physical location that can provide a complete set of input and output statistics” and are the employer unit of analysis. The sampling frame was stratified by industry, region, and size. Data are representative of Canadian employers and workers outside the above-mentioned exclusions. The mandatory nature of the survey ensures high response rates (in excess of 80 percent). In each odd year, up to 24 employees were randomly sampled from each establishment8 and followed the next year regardless of whether they changed establishments. Analyses are restricted to odd-numbered years to ensure that outcomes reflect the characteristics of workers’ current establishment. I pool data across waves to maximize sample size. I restrict the main sample to women between 24 and 44 because the WES only reveals if women are currently living with children. Older women without resident children would include mothers whose children have left home. I exclude women who have no children under 18 but have older children residing with them. I truncate the sample at 24 because the WES does not reveal whether individuals are currently enrolled in school. This leaves 20,529 individual observations in 5,805 unique establishments. To establishment wage effects, I drop age and gender restrictions and employ the full WES sample of 85,320 individuals. Method Assessing the role of establishment segregation for motherhood wage gaps entails estimating the difference between economy-wide estimates and estimates within establishments. This reveals the extent to which the wage gap stems from how mothers are sorted across establishments. Petersen et al. (2011, 2014) use this approach to assess the contribution of establishment segregation to group wage gaps, and Pendakur and Woodcock (2010) provide a formal proof and associated tests of significance. An OLS regression of motherhood on log-hourly wages conditional on observed individual and job characteristics provides the economy-wide estimates: lnWageij=xijβ+momijδ+εij, (1) where lnWageij is the natural log of hourly wage for individual i in establishment j, xijβ indexes observed individual and job characteristics that affect wages, momijδ captures the impact of motherhood on wages, and εij is a stochastic mean-zero error term. Estimating the within-establishment wage gap requires removing the portion of the gap tied to establishment wage differentials. A challenge is the relatively few observations of women of childbearing age in each establishment (mean = 3.9). If, however, we assume that the establishment wage effect is common to all employees, we can use the entire WES sample to estimate establishment effects, which increases the average number of employees per establishment to 17 (up to a maximum of 79). Canay (2011) exploits the assumption of common wage effects to develop a two-step approach to fixed effects estimation for quantile regression. He shows that as long as fixed effects are the same across different quantiles, this removes the fixed effects and gives consistent estimates of slope parameters. I follow Javdani (2015) in applying Canay’s approach to the WES. I first regress log-hourly wages on the individual and job control variables and dummy variables for each establishment with the full sample. I include a dummy variable for sex in this equation as well, as it is estimated on the full WES sample, which includes both men and women: lnWageij=xijβ+femaleijδ+fijψ+εij, (2) where fij is a vector of indicators for each establishment that is equal to 1 if worker i is employed at firm j, and ψ is a vector of establishment wage effects (average wages conditional on worker and job characteristics). The establishment effects are saved and subtracted from each individual’s log-hourly wage to create a new dependent variable FElnWageij, which is purged of the impact of establishment-constant characteristics. The following equation gives the within-establishment motherhood penalty: FElnWageij=χijβ+Momijδ*+εij. (3) The between-establishment contribution to the wage gap is δˆ−δ˜, where δˆ is the OLS estimate of the motherhood penalty (δ) from equation (1) and δ˜ is the fixed effects estimate of the motherhood penalty (δ*) from equation (3). Hausman tests assess the significance of the contribution (Pendakur and Woodcock 2010). H=(δˆ−δ˜)2var[δ˜]−var[δˆ]~χ12 This approach rests on the assumption that the establishment-specific wage effect is a simple “location shift” in the wage distribution. Lane, Salmon, and Spletzer (2007) establish that establishment wage differentials are highly correlated across occupations in the United States, suggesting that this is generally a reasonable assumption. Nonetheless, if establishments that are high/low wage for men and/or older women do not reward women of childbearing age in the same way, results will be biased. To assess this, I repeat the above analysis estimating establishment-specific effects only for the main analytical sample (women between 25 and 44). There is a strong correlation between establishment wage effects calculated using all workers and those using only women between 25 and 44 (0.88). To further assess the sensitivity of results, I estimate baseline models with both sets of establishment fixed effects and with classic fixed effects equations (with stata’s xtreg command). Results (available on request) are virtually identical regardless of which method of calculating establishment fixed effects is employed. I use employee sample weights and estimate standard errors using 100 sets of bootstrap sample weights provided by Statistics Canada. This ensures that results are representative of the population and the standard errors are appropriately adjusted to account for the non-independence of error terms for workers within the same establishment, for the few workers who are sampled more than once across years, and the complex multistage survey design (Drolet 2002). Measures The wage variable used to assess motherhood pay gaps is the natural logarithm of total hourly wage. This includes not only base earnings but also overtime earnings, bonuses, profit sharing, tips, and so forth.9 The key independent variable indicates whether a woman is living with a child under 18.10 Robustness checks differentiate mothers according to whether children are school aged (≤6) or older and the number of children (1, 2, 3, or more). Measures used to assess arguments about compensating differentials include: part-time work (usual hours <30 hours per week); overtime work (a binary variable that is independent of usual hours of work); working flexible hours (able to vary start and stop times provided one works a set number of hours); whether one works from home for one’s employer some or all of the time and why (no work from home, job requirement, personal or family responsibilities, usual place of work, better conditions/save time, money, other); employer assistance with childcare; and employer-provided payments for parental leaves (these are “top-ups” to payments provided through the employment insurance system). With the exception of top-ups and assistance with childcare, these reflect individuals’ actual work arrangements. All are based on employee responses. It is important to measure individual use when possible rather than formal availability, insofar as workers are often hesitant to use work-life balance policies for fear they will be penalized for violating norms of workplace devotion (Blair-Loy and Wharton 2002; Duxbury and Gover 2011; Williams, Blair-Loy, and Berdahl 2013). Arguments about discrimination are only relevant for mothers who change employers after having children. To determine if this is the case, I compare the age of their oldest child to their tenure with their current employer. I also distinguish mothers who started working for their current employer after a period out of the labor force where they were primarily engaged in caregiving. The WES asks workers who changed employers within the past five years what their prior main activity was. Mothers who answered they were “Working at home, raising family, etc.,” were coded as returning after a leave. Note that while the sampling frame of the WES is establishments, tenure refers to employers, so changing between establishments of the same employer after having children would not be counted as having changed employers. I test arguments about the opportunity structure for discrimination by interacting motherhood with two indicators of formalization: whether the job is covered by a collective bargain and whether the establishment has a human resources department. This is correlated with establishment size (although the relationship is far from perfect), so I include an interaction with size as a control. To assess the impact of the organizational field, I test an interaction between motherhood and nonprofit status. Nonprofit organizations include non-governmental organizations as well as those in the broader public sector, such as schools, hospitals, and public (“crown”) corporations. Unfortunately, the WES does not have an indicator for public/private status. Note that this is not testing whether mothers are more likely to be employed in workplaces with these characteristics per se. There may be reasons other than discrimination that would explain why mothers would be more or less likely to work in organizations with these characteristics, and unionized establishments and those that can afford on-site formalized HR tend to offer higher rather than lower wages. Indeed, simply adding indicators of nonprofit status, unionization, and the presence of formal HR to the models without firm effects does not reduce estimates of motherhood pay differentials. Rather, it is the interaction between motherhood and opportunities for discrimination that matters. The focus is on differences in the degree of mothers’ segregation in lower-wage establishments among the subset of organizations that have versus lack the relevant characteristic. All models include controls for individual and some job-level characteristics relevant to wage-setting: age and its square, seniority with current employer and its square, quintic terms for years of full-time (actual) experience, education (less than high school; high school graduate; non-university postsecondary certificate; undergraduate degree holder; and advanced degree), a combined indicator of racialization and immigration status (white Canadian-born; white immigrant; visible minority11 Canadian-born; visible minority immigrant; and Aboriginal), co-resident spouse (married or common-law), occupation (managers; professionals; sales and service; clerical/administrative; trades/technicians; production workers with no trade certification, operation and maintenance), job covered by collective bargain, and survey year. Models used to estimate establishment fixed effects include all controls and a dummy for sex. A variety of establishment-level characteristics predict establishment-wage differentials (such as industry, size, age, and profitability) (Groshen 1991; Lane, Salmon, and Spletzer 2007). However, there is no particular reason to expect them to be associated with mothers’ sorting across establishments per se, so they are not included as controls in main models. This is in accordance with standard practice in the broader literature on establishment wage effects that defines them as net of individual and job characteristics. Additional analysis (available on request) found no evidence that industry, size, competitive context, profitability (among the subset of for-profit firms), or business strategy (importance of reducing labor costs, increasing employee skills, increasing employee participation, or improving performance) was linked to mothers’ segregation in lower-paying establishments. Descriptive statistics are presented in table 1. Table 1. Means and Proportions of Key Variables by Motherhood Status and Mobility No children Mother All mothers No employer change Employer change after care break Other employer change Part-time 0.183 0.325 0.276 0.523 0.332 Work overtime 0.444 0.356 0.394 0.233 0.347 Flexible hours 0.349 0.352 0.334 0.300 0.367 Work from home  No work from home 0.753 0.755 0.718 0.832 0.768  Job requirement 0.159 0.161 0.189 0.106 0.152  Personal/family responsibilities 0.007 0.029 0.035 0.028 0.026  Usual place of work 0.004 0.006 0.005 0.008 0.006  Better conditions 0.051 0.027 0.028 0.017 0.027  Other 0.025 0.022 0.026 0.009 0.022 Top-ups to leave payments 0.394 0.324 0.407 0.244 0.285 Employer assistance with childcare 0.076 0.067 0.103 0.048 0.049 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Age 33.4 36.9 36.2 36.2 37.4 Race/Immigration  White, Canadian-born 0.786 0.794 0.830 0.770 0.777  Visible minority, Canadian-born 0.040 0.018 0.023 0.010 0.017  Aboriginal 0.019 0.017 0.013 0.021 0.019  White immigrant 0.076 0.076 0.072 0.088 0.076  Visible minority immigrant 0.079 0.094 0.061 0.112 0.110 Spouse 0.527 0.822 0.890 0.828 0.785 Education  <High school 0.279 0.349 0.298 0.454 0.366  High school graduate 0.040 0.072 0.048 0.102 0.082  Postsecondary diploma 0.369 0.398 0.408 0.337 0.399  Bachelor’s 0.259 0.153 0.211 0.085 0.128  Postgraduate 0.053 0.028 0.035 0.022 0.025 Experience 11.210 13.403 13.984 9.810 13.419 Seniority 5.823 6.966 12.233 2.293 4.537 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Proportion of sample 0.413 0.587 0.195 0.033 0.359 Proportion of mothers 0.332 0.056 0.612 No children Mother All mothers No employer change Employer change after care break Other employer change Part-time 0.183 0.325 0.276 0.523 0.332 Work overtime 0.444 0.356 0.394 0.233 0.347 Flexible hours 0.349 0.352 0.334 0.300 0.367 Work from home  No work from home 0.753 0.755 0.718 0.832 0.768  Job requirement 0.159 0.161 0.189 0.106 0.152  Personal/family responsibilities 0.007 0.029 0.035 0.028 0.026  Usual place of work 0.004 0.006 0.005 0.008 0.006  Better conditions 0.051 0.027 0.028 0.017 0.027  Other 0.025 0.022 0.026 0.009 0.022 Top-ups to leave payments 0.394 0.324 0.407 0.244 0.285 Employer assistance with childcare 0.076 0.067 0.103 0.048 0.049 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Age 33.4 36.9 36.2 36.2 37.4 Race/Immigration  White, Canadian-born 0.786 0.794 0.830 0.770 0.777  Visible minority, Canadian-born 0.040 0.018 0.023 0.010 0.017  Aboriginal 0.019 0.017 0.013 0.021 0.019  White immigrant 0.076 0.076 0.072 0.088 0.076  Visible minority immigrant 0.079 0.094 0.061 0.112 0.110 Spouse 0.527 0.822 0.890 0.828 0.785 Education  <High school 0.279 0.349 0.298 0.454 0.366  High school graduate 0.040 0.072 0.048 0.102 0.082  Postsecondary diploma 0.369 0.398 0.408 0.337 0.399  Bachelor’s 0.259 0.153 0.211 0.085 0.128  Postgraduate 0.053 0.028 0.035 0.022 0.025 Experience 11.210 13.403 13.984 9.810 13.419 Seniority 5.823 6.966 12.233 2.293 4.537 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Proportion of sample 0.413 0.587 0.195 0.033 0.359 Proportion of mothers 0.332 0.056 0.612 Table 1. Means and Proportions of Key Variables by Motherhood Status and Mobility No children Mother All mothers No employer change Employer change after care break Other employer change Part-time 0.183 0.325 0.276 0.523 0.332 Work overtime 0.444 0.356 0.394 0.233 0.347 Flexible hours 0.349 0.352 0.334 0.300 0.367 Work from home  No work from home 0.753 0.755 0.718 0.832 0.768  Job requirement 0.159 0.161 0.189 0.106 0.152  Personal/family responsibilities 0.007 0.029 0.035 0.028 0.026  Usual place of work 0.004 0.006 0.005 0.008 0.006  Better conditions 0.051 0.027 0.028 0.017 0.027  Other 0.025 0.022 0.026 0.009 0.022 Top-ups to leave payments 0.394 0.324 0.407 0.244 0.285 Employer assistance with childcare 0.076 0.067 0.103 0.048 0.049 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Age 33.4 36.9 36.2 36.2 37.4 Race/Immigration  White, Canadian-born 0.786 0.794 0.830 0.770 0.777  Visible minority, Canadian-born 0.040 0.018 0.023 0.010 0.017  Aboriginal 0.019 0.017 0.013 0.021 0.019  White immigrant 0.076 0.076 0.072 0.088 0.076  Visible minority immigrant 0.079 0.094 0.061 0.112 0.110 Spouse 0.527 0.822 0.890 0.828 0.785 Education  <High school 0.279 0.349 0.298 0.454 0.366  High school graduate 0.040 0.072 0.048 0.102 0.082  Postsecondary diploma 0.369 0.398 0.408 0.337 0.399  Bachelor’s 0.259 0.153 0.211 0.085 0.128  Postgraduate 0.053 0.028 0.035 0.022 0.025 Experience 11.210 13.403 13.984 9.810 13.419 Seniority 5.823 6.966 12.233 2.293 4.537 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Proportion of sample 0.413 0.587 0.195 0.033 0.359 Proportion of mothers 0.332 0.056 0.612 No children Mother All mothers No employer change Employer change after care break Other employer change Part-time 0.183 0.325 0.276 0.523 0.332 Work overtime 0.444 0.356 0.394 0.233 0.347 Flexible hours 0.349 0.352 0.334 0.300 0.367 Work from home  No work from home 0.753 0.755 0.718 0.832 0.768  Job requirement 0.159 0.161 0.189 0.106 0.152  Personal/family responsibilities 0.007 0.029 0.035 0.028 0.026  Usual place of work 0.004 0.006 0.005 0.008 0.006  Better conditions 0.051 0.027 0.028 0.017 0.027  Other 0.025 0.022 0.026 0.009 0.022 Top-ups to leave payments 0.394 0.324 0.407 0.244 0.285 Employer assistance with childcare 0.076 0.067 0.103 0.048 0.049 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Age 33.4 36.9 36.2 36.2 37.4 Race/Immigration  White, Canadian-born 0.786 0.794 0.830 0.770 0.777  Visible minority, Canadian-born 0.040 0.018 0.023 0.010 0.017  Aboriginal 0.019 0.017 0.013 0.021 0.019  White immigrant 0.076 0.076 0.072 0.088 0.076  Visible minority immigrant 0.079 0.094 0.061 0.112 0.110 Spouse 0.527 0.822 0.890 0.828 0.785 Education  <High school 0.279 0.349 0.298 0.454 0.366  High school graduate 0.040 0.072 0.048 0.102 0.082  Postsecondary diploma 0.369 0.398 0.408 0.337 0.399  Bachelor’s 0.259 0.153 0.211 0.085 0.128  Postgraduate 0.053 0.028 0.035 0.022 0.025 Experience 11.210 13.403 13.984 9.810 13.419 Seniority 5.823 6.966 12.233 2.293 4.537 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Proportion of sample 0.413 0.587 0.195 0.033 0.359 Proportion of mothers 0.332 0.056 0.612 There are a number of limitations to note. Although the WES follows individuals for two years, this is too short to compare women pre- and post-motherhoood. However, Canadian panel data does not reveal evidence that mothers typically earn lower wages than other women in the years before childbirth (Zhang 2009, 2010). Another limitation is that only those currently employed or on leave are observed. While Canadian mothers have high employment rates,12 they are lower than for childless women (Zhang 2007). Employed mothers may be positively selected, with mothers with better earnings prospects more likely to return to the workforce after having children. If lower employment rates for mothers imply a higher reservation wage, estimates of wage penalties will be conservative, insofar as mothers may disproportionately choose non-employment over jobs in low-wage establishments. Results Within- versus between-establishment wage gaps Regressing motherhood on establishment wage effects (calculated from equation (2)) reveals a significant negative coefficient of 0.075. An establishment with 25 percent mothers would thus pay 3.9 percent lower wages than one with 75 percent mothers. How important is this pattern of segregation for motherhood wage gaps overall? The first bar in figure 1 graphically depicts the contribution of between-establishment segregation to the aggregate motherhood wage gap. The overall bar represents the estimated economy-wide motherhood wage gap (in percentage terms) net of controls, which is, in turn, subdivided into within-establishment and between-establishment components. The statistical significance of the components within the stacked bar is indicated with stars to the right. Full results are in model 1 of appendix table A.1. Figure 1 reveals that the aggregate motherhood wage gap is almost entirely due to the between-establishment effect. Segregation in establishments that pay lower wages net of worker characteristics lowers mothers’ wages by around 3 percent across the board. The within- establishment wage gap is much smaller and not significant. Figure 1. View largeDownload slide Motherhood wage gap (%) with and without controls for family-supportive work context Figure 1. View largeDownload slide Motherhood wage gap (%) with and without controls for family-supportive work context Family (un)friendly jobs and organizations: compensating differentials While the importance of establishment segregation for motherhood pay gaps is clear, the first specifications do not reveal what is driving them. The descriptive statistics in table 1 reveal that mothers work part-time more often and overtime less often than childless women. They are more likely to work from home for family-related reasons, but not overall, and there is no difference in flexible working hours. Mothers are actually less likely to work in establishments that offer top-ups to employment insurance (which provides maternity and parental benefits in Canada) and assistance with childcare. This suggests that variation in working hours has the greatest potential to contribute to motherhood pay gaps, although other work characteristics may matter once estimations control for other differences between mothers and childless women. To formally test the compensating differentials argument, I add measures of part-time work, overtime, flexible hours, working from home, employer-provided assistance with childcare, and access to employer top-up payments for maternity/parental leave. The second bar in figure 1 presents estimates from this model. Full results are in model 2 of appendix table A.1. There is a significant reduction in the between-establishment effect to 2 percent with the addition of the family-supportive measures. This suggests that mothers are paying a price for a more family-friendly context, but it is not the major source of their lower wages. This trade-off is solely tied to establishment segregation. There is no change in the estimate of the within-firm motherhood wage gap with the addition of the family-supportive variables. To assess specific variables’ relative contribution, additional models drop one focal term from the full model (results in table O.1 of the online supplement). Flexible hours and assistance with childcare have no discernable impact on the sorting penalty, and mothers’ greater likelihood of working from home to fulfill personal or family responsibilities actually offsets the motherhood penalty, since this is associated with employment in a higher-wage establishment. Top-up payments for maternity/parental leave do help explain the motherhood penalty, but not in a way consistent with the logic of competing differentials (they are associated with higher-wage establishments, and mothers are less likely to have access to them). In fact, the only results that are consistent with the compensating differentials argument are those associated with part-time and overtime work. Dropping these terms shifts the motherhood penalty associated with establishment segregation in the expected direction. Of the two, it is part-time work that has the biggest impact. Most employed mothers in Canada work full-time, but part-time work is common across the educational spectrum (a little less so for the least and most educated, 33–34 percent of mothers who are high school graduates, have a postsecondary diploma, or a bachelor’s degree work part-time, versus 27 percent of those without high school diplomas and 26 percent of those with postgraduate degrees). However, working part-time might have different implications for employer segregation for salaried workers than for women in lower-level jobs paid by the hour. To further assess whether all types of part-time work imply wage trade-offs, additional models distinguish hourly part-time jobs from those held by salaried workers. Results (available on request) reveal that only the former is associated with employment in lower-waged establishments. Mothers with the greatest care demands should be most willing to trade wages for accommodating work. As a robustness check, I re-estimated the above models disaggregating mothers by number of children and age of youngest child (see figure 1 and table A.1). While accounting for family-supportive employment reduces between-establishment motherhood wage gap regardless of the number of children, the drop is largest in percentage terms and only significant for those with two. In particular, both overtime and, especially, part-time work play a much larger role for mothers of two than for those with singletons (see table O.2 in the online supplement for details). Interestingly, mothers of two face the smallest between-establishment wage gap overall, while the gap is most pronounced among those with one child. Figure 1 also reveals that family-un/friendly work characteristics contribute more to the between-establishment motherhood wage gap for those with younger children (largely because of the greater incidence of part-time work). However, the overall between-establishment wage gap is larger for mothers with older children. On balance, mothers with stronger care demands do appear to accept greater wage losses to access accommodating work. However, effects are relatively minor, and a significant between-establishment wage gap remains in all cases. Moreover, the between-establishment wage gap is not greatest for mothers with the most demanding care obligations (see online supplement table O.3 for detailed results). A larger segregation-related wage gap for mothers of singletons is not consistent with the logic of compensating differentials. It may reflect processes of differential selection whereby mothers with more children face stronger pressures to leave the labor force. Those who remain may have unmeasured employment and/or family supports that make combining motherhood and employment easier. It is also possible that employers may be more hesitant to hire mothers of singletons because they presume they will have another child (and that this will be disruptive), whereas women with more children are more likely to have achieved their final family size. Discrimination Hiring discrimination should only affect between-establishment wage gaps for mothers who are no longer working for their pre-childbirth employer and should be strongest for those changing after a recent caregiving leave. The descriptive statistics in table 1 reveal that employer continuity is much less common for single mothers relative to their married counterparts, and also for aboriginal and immigrant mothers relative to white Canadian-born women. Women with a high school degree or less are overrepresented among those changing employers after childbirth, while the reverse is true for more educated women (with educational differences most pronounced among those starting with their employer after a care break). Managers and professionals are underrepresented among both types of employer-changers, but particularly among those who took a care break. Mothers working in sales are most overrepresented among those who took such a break and underrepresented among those with employer continuity (clerical/administrative and technical/trades workers are fairly evenly represented among the mobility groups). Figure 2 depicts wage gaps separately for mothers with the three patterns of im/mobility. Note that as with prior models, controls are included for demographic and job characteristics, so results are not a function of the differences among mothers following the three mobility patterns outlined above. Full results are in model 1 of appendix table A.2. Figure 2. View largeDownload slide Motherhood wage gap (%) by post-birth employer change Figure 2. View largeDownload slide Motherhood wage gap (%) by post-birth employer change Results are broadly consistent with a discrimination story—only mothers who change employers after childbirth work in lower-paying establishments, and this is most pronounced for those who entered their current job after a recent caregiving break. Mothers who remain with their pre-childbirth employer earn higher wages both within and across establishments, but women who change employers after a caregiving leave face a −7.1 percent between-establishment penalty. Because the models control for experience and tenure, lost human capital is not the only factor hurting mothers who fail to return to the same employer after childbirth. Such women also suffer a within-establishment motherhood penalty, although it is smaller. There is a substantial but smaller (−3.5 percent) between-establishment wage gap for other women who changed employers after having children. These women also face a within-establishment penalty, but again it is much smaller than the between-establishment wage gap. But do organizational contexts that should reduce opportunities for discrimination mitigate the wage gap arising by virtue of establishment segregation? To assess this, I add interactions between the motherhood measure that accounts for mobility (mother still working for the same employer, mother who started working with her current employer after a care break, and mother who changed employer after childbirth) and indicators of formalization (unionization and dedicated HR in the establishment), and sensitivity to legitimacy concerns around fairness (nonprofit status). I include all interactions jointly to isolate impacts net of other factors, and report average marginal effects in the figures. Because only mothers who change employers face between-establishment wage gaps, I focus interpretation on them. Full model results are in model 2 of appendix table A.2. Consistent with expectations, formalization weakens between-establishment wage gaps. In non-unionized contexts, mothers who change employers after a caregiving break face a −7 percent between-establishment penalty (see figure 3). Among women whose jobs are covered by a collective bargain, however, this drops to −0.7 percent. The penalty also falls with unionization for other mothers who have changed employers, although the difference is not as dramatic (−1.5 percent with unionization versus −3.8 percent without). Figure 3. View largeDownload slide Motherhood wage gap (%) by union and post-birth employer change, mothers no longer working for pre-birth employer Figure 3. View largeDownload slide Motherhood wage gap (%) by union and post-birth employer change, mothers no longer working for pre-birth employer Segregation in lower-paying establishments is much less pronounced among mothers working for employers with on-site human resource professionals than it is among those working in establishments without them (figure 4). For mothers changing employers after a care break working in establishments without HR professionals, there is a −7.4 percent motherhood wage gap attributable to between-establishment segregation. There is no significant between-establishment wage gap among similar mothers working where HR professionals are present. For those who changed jobs for other reasons, the wage gap drops from −4.1 percent among those working for employers without HR, to a negligible −0.8 percent among those working in establishments where it is present. Figure 4. View largeDownload slide Motherhood wage gap (%) by HR and post-birth employer change, mothers no longer working for pre-birth employer Figure 4. View largeDownload slide Motherhood wage gap (%) by HR and post-birth employer change, mothers no longer working for pre-birth employer Figure 5 presents results related to nonprofit status. Segregation in lower-paying establishments is pronounced among mothers who have changed employers and work in for-profit establishments—there is a −6.4 percent between-establishment wage gap for mothers who changed employers after a care break, and a −4.1 percent gap for those who changed for other reasons. There are significant, albeit smaller, within-establishment penalties. Among women in the nonprofit sector, however, wage gaps due to segregation in lower-paying establishments are much smaller (−1.2 percent) for women who have changed employers after a leave and absent altogether for other mothers who found new jobs after becoming mothers. Figure 5. View largeDownload slide Motherhood wage gap (%) by nonprofit and post-birth employer change, mothers no longer working for pre-birth employer Figure 5. View largeDownload slide Motherhood wage gap (%) by nonprofit and post-birth employer change, mothers no longer working for pre-birth employer Discussion and conclusions Much research has documented the wage penalty women experience if they have children. However, there has been little clarity about whether this results from mothers earning less than childless women in the same establishment, or because mothers are more likely to work in establishments that pay below-market wages. I find that the latter is most important in Canada, with mothers’ segregation into lower-paying establishments accounting for 97 percent of the net aggregate motherhood wage gap. Mothers who change employers after having children do face within-establishment penalties, but they are smaller than those due to establishment segregation. Beyond assessing the importance of establishment segregation for motherhood wage gaps, a goal of the paper was to investigate how this might stem from and be conditioned by organizational context. A substantial literature has focused on organizational family policy and the integration of employment and caregiving (Boushey 2008; Kelly, Moen, and Tranby 2011; Williams 2010; Williams, Blair-Loy, and Berdahl 2013), although how this intersects with establishment segregation has not been investigated. The compensating-differentials argument that mothers accept wage penalties to work in more family-friendly establishments received some support, especially for those with more demanding caregiving obligations. In particular, part-time work, which is more common in lower-waged establishments, helps explain the between-establishment wage gap, as does mothers’ lower likelihood of working overtime to a lesser degree. Although the analysis did not investigate class differences among mothers, the fact that only hourly part-time work was associated with lower-paying establishments suggests that less advantaged mothers bear the brunt of the wage penalty associated with compensating differentials. The European Community Directive on Part-Time Work (97/81/EC) encourages member countries to promote opportunities for workers to adjust working hours (Fahlén 2013). The Liberal government elected in Canada in 2015 promised to introduce such rights for workers subject to Federal Employment Standards.13 If implemented, this should reduce the need for workers to change employers to access more family-supportive working hours. However, even after accounting for the role of part-time work and overtime, the bulk of the between-establishment motherhood wage gap remains unexplained. Government policy giving workers the right to adjust work hours, refuse overtime, and discourage its excessive use may improve work-life integration, but it would not have a major impact on mothers’ wage disadvantage in Canada. On balance, demand-side forces linked to employer discrimination appear to play a stronger role in sorting women into lower-waged establishments than does mothers’ search for a more amenable work context. Results suggest that changing employers after becoming a mother provides a context where motherhood becomes salient and disadvantageous, channeling them into poorer-paying establishments. Results thus complement experimental and audit research that provides direct evidence of discrimination against mothers, albeit in specific and limited scenarios (Correll, Benard, and Paik 2007). Negative establishment sorting is particularly strong for mothers re-entering the labor market after a care leave, highlighting the importance of policy frameworks that protect mothers’ attachment to their employers after childbirth. This is not, however, the only time mothers change employers. Indeed, inter-firm mobility is an increasingly important part of workers’ career trajectories in the context of patterns of firm restructuring that have eroded internal labor markets (Cappelli 1999; Hollister 2011; Kalleberg 2013; Kronberg 2013). There are a number of important caveats to note. Restrictions in the sample’s age range likely result in conservative estimates of motherhood penalties. Repeating key analyses without the lower-bound age restriction (tables available on request) increases the overall size of the motherhood penalty by approximately 1 percent and slightly increases the relative importance of the within-establishment component. This is entirely a function of more disadvantageous mobility patterns for younger mothers. Analyses that account for differences in such patterns are virtually identical whether or not the lower age bound is relaxed, suggesting that the exclusion of young women has little substantive impact on the key findings. The likelihood that older women will have had children who have left home prevented me from including them in the analysis, as the WES cannot identify mothers without resident children. The larger between-establishment wage gap for mothers of older children suggests a pattern of cumulating disadvantage that could lead to an understatement of the motherhood wage gap given the restricted age range in the study. Without data on non-resident children, however, this cannot be directly assessed. More centrally, it is important to remember that the data and research design do not directly test discrimination. Further, we cannot know if mothers who changed employers were already working in lower-waged establishments prior to having children. Indeed, this may have motivated them to look for a new employer. We also cannot rule out the possibility that mothers who change employers have unobserved characteristics that would hinder them in the labor market generally, or that extra-organizational constraints on geographic mobility make it more difficult for mothers to make wage gains when they change employers. Unmeasured employment amenities, such as the degree of coworker or supervisor support, may also shape mothers’ mobility decisions, motivating them to accept employment in lower-waged establishments. In supplementary analyses, I compared pay gaps for mothers who found jobs via an insider referral and others, since a connection in the organization can provide information about how family-supportive supervisors are in practice. There is a larger penalty associated with working in lower-paying establishments among mothers who learned of their job from friends or family, but the difference is not dramatic (4.2 percent versus 2.8 percent). There is no generalized wage penalty associated with insider referrals. Moreover, while unmeasured employment amenities may help explain the residual motherhood penalty that remains in some estimations, there is little reason to believe that variation in their availability across establishments would be substantial where organizations are for-profit and lack HR departments or collective agreements, but largely absent otherwise. They are thus unlikely to impact the findings with respect to opportunities for discrimination. Indeed, none of these alternative explanations would logically lead to the dramatic and systematic variation in the presence and strength of between-establishment wage gaps that we see with collective bargaining, human resource professionals, and nonprofit status. Overall wage variation across establishments is smaller among nonprofits versus for-profit firms, for those with HR departments than among those without, and for those where jobs are typically unionized versus those without collective bargaining coverage (variance estimates available on request). This would tend to reduce the scope for inter-establishment wage differentials to impact group wage differences in these contexts, and could contribute to the smaller role of establishment segregation for motherhood wage gaps within them. However, substantial establishment wage variation remains among nonprofit establishments and those with HR professionals and collective bargaining. The fact that these institutional features often wiped out segregation penalties altogether implies that reduced wage variance is not solely driving results. Indeed, organizational features that should influence opportunities for discrimination have dramatic effects. Formalization substantially reduces the pay gap associated with mothers’ segregation in lower-paying establishments, especially human resource professionals. This highlights the importance not just of legislation to protect mothers against discrimination (which exists in Canada), but of organizational practices and oversight that ensure decision-makers are not only aware of such prohibitions but act accordingly. I also argued that the nonprofit sector faces legitimacy pressures that should act as a brake on discrimination. Consistent with this, wage gaps attributable to segregation in lower-paying establishments are only evident in the for-profit sector. This study thus underscores the importance of organizational characteristics in shaping mothers’ disadvantage. While past research has explored differences tied to mothers’ own characteristics and those of the countries in which they live, scholars have not systematically studied variation across organizations with nationally representative data. Insofar as organizational context has been theorized as important, it has typically been the “family-friendliness” of work cultures and their promotion of ideal worker norms presumed in conflict with motherhood that garner the most attention (e.g., Blair-Loy 2003; Stone and Hernandez 2013). While such organizational norms are no doubt an important reason why motherhood is salient with respect to hiring in the first place, this study suggests that the difficult job of attempting to shift such norms is not the only avenue to pursue to reduce mothers’ disadvantage. The combination of legal prohibition against family status discrimination and greater oversight and formalization of hiring can also be effective. Because the type of data available in the WES and other surveys cannot provide direct evidence of discrimination, audit studies would be useful to test whether organizational features identified as meaningful reduce hiring discrimination against mothers. More research is also needed to explore how wage gaps tied to employer segregation might vary among mothers. Past research illustrates that motherhood penalties vary considerably along dimensions such as occupation, education, and earnings levels (Anderson, Binder, and Krause 2002; Cooke 2014; Wilde, Batchelder, and Ellwood 2010; Zhang 2009). I find that disadvantage is concentrated among women who have changed employers after childbirth, a pattern that is more common in the WES for less advantaged women: single mothers, immigrants, less educated women, and those working in lower-level jobs. Results thus suggest that differences in exposure to discrimination tied to varying mobility patterns may contribute to stronger motherhood penalties for disadvantaged groups. At the same time, it is possible that characteristics that contribute to mothers’ segregation in lower-paying establishments at the aggregate level matter more for some mothers than others. While preliminary analyses suggest that accounting for variation in effects by education or occupation does not dramatically alter results, a more focused investigation of how motherhood penalties vary within and across establishments for women with different labor market opportunities would be valuable. The role of national context in shaping mothers’ segregation in lower-waged establishments is beyond the scope of this paper, and findings for Canada may not map exactly to those in other countries. Indeed, there is considerable variation in motherhood penalties across countries, and I find segregation in lower-paying establishments much more important for motherhood wage gaps than Petersen, Penner, and Høgsnes (2014) find for Norway, where it accounts for only 14–31 percent of the total motherhood wage gap (depending on time period and number of children). I also only find wage gaps tied to segregation in lower-wage firms for women who are no longer working for their pre-childbirth employer. This is different from what Beblo, Bender, and Wolf (2008) find for West Germany, where mothers who return to the same employer after childbirth are employed in lower-wage establishments. These differences may reflect the greater representativeness of my data rather than country-level differences. More likely, they are tied to the overall greater inter-establishment variability in wages that occurs in countries, like Canada, with more decentralized wage bargaining. In addition, Norway, Germany, and Canada vary across a number of potentially relevant policy dimensions. Petersen, Penner, and Høgsnes (2014) detail how Norway evolved to be an exemplar of gender egalitarian and family-supportive employment. Notwithstanding recent policy changes, Germany has a history of strong support for a traditional male breadwinner family structure with a caregiving mother working at most part-time when children are older (Cooke 2011). Canada stands in the middle. The length of paid leave available after childbirth is very close to the OECD average (OECD 2017a), and in 2011 public spending on pre-primary education and childcare ranked 15 out of the OECD 25 (OECD 2013). Budig, Misra, and Boeckmann (2016) find that government support for childcare and length of leave help explain differences in the magnitude of motherhood wage penalties cross-nationally, and they are also likely relevant to the variability of employment conditions across establishments. In the United States, where long work hours are particularly pronounced and statutory entitlements to care leaves are so meager, organizational family policy may prove more important, while the lack of legal protection against discrimination against mothers may make formalization less so. Exploring variation in the degree to which establishment segregation shapes motherhood wage gaps and in its underlying mechanisms across national contexts is an important avenue for future research. Notes 1 Heywood, Siebert, and Wei (2007) find that employees report higher availability of family-supportive practices than establishment representatives, which likely reflects managerial discretion. 2 Neo-institutional scholars argue that firms may adopt practices to enhance legitimacy without a real commitment (Edelman, Uggen, and Erlanger 1999; Kelly and Dobbin 1998; Stinchcombe 2001). 3 While the theory of compensating differentials posits a positive relationship between wages and poor working conditions, empirical support is mixed (Gunderson and Hyatt 2001; Heywood, Siebert, and Wei 2007; Johnson and Provan 1996). Moreover, practices and policies that enhance work-life balance can enhance productivity, reducing the need to offset their costs with lower wages (Gariety and Shaffer 2001; Glass 2004; Golden, Henly, and Lambert 2013; Johnson and Provan 1996). They are more often present where recruitment and retention of high-performing workers is a priority, and where wages are relatively high (Bloom, Kretschmer, and Van Reenan 2009; Brescoll, Glass, and Sedlovskaya 2013; Winder 2009). In seeking employers who allow flexible hours and working from home and provide family-supportive benefits, mothers may select into higher-paying workplaces, actually offsetting their wage disadvantage. 4 As part of research for another paper, my co-authors and I reviewed every case alleging family status discrimination filed with Canadian Human Rights Tribunals. Only a few alleged discrimination at the point of hire, and none were successful. 5 There is no direct Canadian evidence about the prevalence of employer inquiries or employee disclosures of motherhood status in job interviews. However, a recent UK report finds that only three in 10 employers provided guidelines about employment law to those involved in recruitment, and that a substantial share of employers believed that behavior contradictory to legal mandates against family status discrimination were legitimate (Adams et al. 2016). Crowley (2013) also reports instances of American mothers being asked about how they would handle childcare responsibilities in hiring interviews. 6 Job changes after non-employment are associated with lower wages in part because workers have no fallback position (Keith and McWilliams 1997). However, Fuller (2008) found that, all else equal, the losses associated with family-related quits were larger than for layoffs. 7 Public administration involves the enactment and interpretation of laws and regulations, and the administration of programs based on them (Industry Canada, http://www.ic.gc.ca/cis-sic/cis-sic.nsf/IDE/cis-sic91defe.html). Excluded are key components of the “broader” public sector including health and educational institutions. Public Administration’s share of employment in Canada is 6.5 percent (Statistics Canada 2017). 8 Sample size was proportional to the size of establishment, except in cases with less than four employees, where all were sampled. 9 WES respondents can report different bases of pay, which Statistics Canada converts to an hourly wage rate based on usual weekly hours and weeks and months worked per year. 10 It is not possible to distinguish biological from stepchildren or non-motherhood-type relationships. 11 I use “visible minority” as an descriptor for processes of racialization, as it is the term used by Statistics Canada and prescribed by federal employment equity legislation. StatCan defines “visible minority” as “persons who are non-Caucasian in race or non-white in color and who do not report being Aboriginal.” It includes, for example, people who indicate being of Chinese, South Asian, Black, Latin American, and Arab descent. It does not include those who indicate “White” or “European” along with a response that would otherwise indicate visible minority status (e.g., “White” and “Latin American”). 12 Currently 8 percentage points higher than for American mothers (OECD 2017b). 13 This covers federal government employees and industries crossing provincial boundaries. Appendix Table A.1. Regression Estimates of Economy-Wide, Within-Establishment, and Between-Establishment Effects of Motherhood on Log-Hourly Wages by Family-Supportive Context, Number of Children, and Age of Youngest Child, Women 25–44 (1) Baseline (2) Family-supportive controls (3) Number of children (4) Family-supportive controls by number of children Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Mother −0.032*** 0.002 −0.033*** −0.023*** −0.002 −0.02*** 1 Child −0.054*** −0.006*** −0.049*** −0.046*** −0.008*** −0.039*** 2 Children −0.013*** 0.006*** −0.019*** −0.004 0.001 −0.004*** 3+ Children −0.022*** 0.009** −0.031*** −0.006 0.004 −0.01*** Part-time −0.006** 0.034*** −0.04*** −0.009*** 0.034*** −0.042*** Work overtime 0.076*** 0.019*** 0.057*** 0.077*** 0.019*** 0.058*** Flexible hours −0.015*** −0.003* −0.012*** −0.015*** −0.003* −0.012*** Work from home  Job requirement 0.115*** 0.077*** 0.037*** 0.115*** 0.077*** 0.037***  Personal/family responsibilities 0.177*** 0.110*** 0.067*** 0.173*** 0.109*** 0.064***  Usual place of work 0.218*** 0.159*** 0.059*** 0.215*** 0.158*** 0.057***  Better conditions, save time, money 0.073*** 0.048*** 0.025*** 0.073*** 0.048*** 0.025***  Other 0.079*** 0.061*** 0.018*** 0.079*** 0.061*** 0.018*** Top-ups 0.105*** 0.008*** 0.097*** 0.105*** 0.008*** 0.097*** Employer childcare 0.020*** −0.003 0.024*** 0.021*** −0.003 0.024*** R-squared 0.416 0.364 0.446 0.375 0.447 0.375 (1) Baseline (2) Family-supportive controls (3) Number of children (4) Family-supportive controls by number of children Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Mother −0.032*** 0.002 −0.033*** −0.023*** −0.002 −0.02*** 1 Child −0.054*** −0.006*** −0.049*** −0.046*** −0.008*** −0.039*** 2 Children −0.013*** 0.006*** −0.019*** −0.004 0.001 −0.004*** 3+ Children −0.022*** 0.009** −0.031*** −0.006 0.004 −0.01*** Part-time −0.006** 0.034*** −0.04*** −0.009*** 0.034*** −0.042*** Work overtime 0.076*** 0.019*** 0.057*** 0.077*** 0.019*** 0.058*** Flexible hours −0.015*** −0.003* −0.012*** −0.015*** −0.003* −0.012*** Work from home  Job requirement 0.115*** 0.077*** 0.037*** 0.115*** 0.077*** 0.037***  Personal/family responsibilities 0.177*** 0.110*** 0.067*** 0.173*** 0.109*** 0.064***  Usual place of work 0.218*** 0.159*** 0.059*** 0.215*** 0.158*** 0.057***  Better conditions, save time, money 0.073*** 0.048*** 0.025*** 0.073*** 0.048*** 0.025***  Other 0.079*** 0.061*** 0.018*** 0.079*** 0.061*** 0.018*** Top-ups 0.105*** 0.008*** 0.097*** 0.105*** 0.008*** 0.097*** Employer childcare 0.020*** −0.003 0.024*** 0.021*** −0.003 0.024*** R-squared 0.416 0.364 0.446 0.375 0.447 0.375 (5) Age of youngest (6) Family-supportive controls by age of youngest Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Youngest child <7 −0.002 0.020*** −0.023*** 0.008*** 0.016*** −0.008*** Youngest child 7+ −0.056*** −0.013*** −0.042*** −0.047*** −0.017*** −0.03*** Part-time −0.007*** 0.034*** −0.04*** Work overtime 0.076*** 0.019*** 0.057*** Flexible hours −0.016*** −0.004** −0.012*** Work from home (none)  Job requirement 0.116*** 0.078*** 0.038***  Personal/family resp 0.172*** 0.107*** 0.065***  Usual place of work 0.220*** 0.161*** 0.06***  Better conditions 0.076*** 0.050*** 0.026***  Other 0.080*** 0.062*** 0.019*** Top-ups 0.106*** 0.009*** 0.097*** Employer childcare 0.019*** −0.004* 0.023*** R-squared 0.447 0.376 (5) Age of youngest (6) Family-supportive controls by age of youngest Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Youngest child <7 −0.002 0.020*** −0.023*** 0.008*** 0.016*** −0.008*** Youngest child 7+ −0.056*** −0.013*** −0.042*** −0.047*** −0.017*** −0.03*** Part-time −0.007*** 0.034*** −0.04*** Work overtime 0.076*** 0.019*** 0.057*** Flexible hours −0.016*** −0.004** −0.012*** Work from home (none)  Job requirement 0.116*** 0.078*** 0.038***  Personal/family resp 0.172*** 0.107*** 0.065***  Usual place of work 0.220*** 0.161*** 0.06***  Better conditions 0.076*** 0.050*** 0.026***  Other 0.080*** 0.062*** 0.019*** Top-ups 0.106*** 0.009*** 0.097*** Employer childcare 0.019*** −0.004* 0.023*** R-squared 0.447 0.376 Note: Models control for age, race/immigration, survey year, spouse, education, experience, seniority, occupation, and unionization. * p < 0.05 ** p < 0.01 *** p < 0.001 Table A.1. Regression Estimates of Economy-Wide, Within-Establishment, and Between-Establishment Effects of Motherhood on Log-Hourly Wages by Family-Supportive Context, Number of Children, and Age of Youngest Child, Women 25–44 (1) Baseline (2) Family-supportive controls (3) Number of children (4) Family-supportive controls by number of children Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Mother −0.032*** 0.002 −0.033*** −0.023*** −0.002 −0.02*** 1 Child −0.054*** −0.006*** −0.049*** −0.046*** −0.008*** −0.039*** 2 Children −0.013*** 0.006*** −0.019*** −0.004 0.001 −0.004*** 3+ Children −0.022*** 0.009** −0.031*** −0.006 0.004 −0.01*** Part-time −0.006** 0.034*** −0.04*** −0.009*** 0.034*** −0.042*** Work overtime 0.076*** 0.019*** 0.057*** 0.077*** 0.019*** 0.058*** Flexible hours −0.015*** −0.003* −0.012*** −0.015*** −0.003* −0.012*** Work from home  Job requirement 0.115*** 0.077*** 0.037*** 0.115*** 0.077*** 0.037***  Personal/family responsibilities 0.177*** 0.110*** 0.067*** 0.173*** 0.109*** 0.064***  Usual place of work 0.218*** 0.159*** 0.059*** 0.215*** 0.158*** 0.057***  Better conditions, save time, money 0.073*** 0.048*** 0.025*** 0.073*** 0.048*** 0.025***  Other 0.079*** 0.061*** 0.018*** 0.079*** 0.061*** 0.018*** Top-ups 0.105*** 0.008*** 0.097*** 0.105*** 0.008*** 0.097*** Employer childcare 0.020*** −0.003 0.024*** 0.021*** −0.003 0.024*** R-squared 0.416 0.364 0.446 0.375 0.447 0.375 (1) Baseline (2) Family-supportive controls (3) Number of children (4) Family-supportive controls by number of children Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Mother −0.032*** 0.002 −0.033*** −0.023*** −0.002 −0.02*** 1 Child −0.054*** −0.006*** −0.049*** −0.046*** −0.008*** −0.039*** 2 Children −0.013*** 0.006*** −0.019*** −0.004 0.001 −0.004*** 3+ Children −0.022*** 0.009** −0.031*** −0.006 0.004 −0.01*** Part-time −0.006** 0.034*** −0.04*** −0.009*** 0.034*** −0.042*** Work overtime 0.076*** 0.019*** 0.057*** 0.077*** 0.019*** 0.058*** Flexible hours −0.015*** −0.003* −0.012*** −0.015*** −0.003* −0.012*** Work from home  Job requirement 0.115*** 0.077*** 0.037*** 0.115*** 0.077*** 0.037***  Personal/family responsibilities 0.177*** 0.110*** 0.067*** 0.173*** 0.109*** 0.064***  Usual place of work 0.218*** 0.159*** 0.059*** 0.215*** 0.158*** 0.057***  Better conditions, save time, money 0.073*** 0.048*** 0.025*** 0.073*** 0.048*** 0.025***  Other 0.079*** 0.061*** 0.018*** 0.079*** 0.061*** 0.018*** Top-ups 0.105*** 0.008*** 0.097*** 0.105*** 0.008*** 0.097*** Employer childcare 0.020*** −0.003 0.024*** 0.021*** −0.003 0.024*** R-squared 0.416 0.364 0.446 0.375 0.447 0.375 (5) Age of youngest (6) Family-supportive controls by age of youngest Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Youngest child <7 −0.002 0.020*** −0.023*** 0.008*** 0.016*** −0.008*** Youngest child 7+ −0.056*** −0.013*** −0.042*** −0.047*** −0.017*** −0.03*** Part-time −0.007*** 0.034*** −0.04*** Work overtime 0.076*** 0.019*** 0.057*** Flexible hours −0.016*** −0.004** −0.012*** Work from home (none)  Job requirement 0.116*** 0.078*** 0.038***  Personal/family resp 0.172*** 0.107*** 0.065***  Usual place of work 0.220*** 0.161*** 0.06***  Better conditions 0.076*** 0.050*** 0.026***  Other 0.080*** 0.062*** 0.019*** Top-ups 0.106*** 0.009*** 0.097*** Employer childcare 0.019*** −0.004* 0.023*** R-squared 0.447 0.376 (5) Age of youngest (6) Family-supportive controls by age of youngest Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Youngest child <7 −0.002 0.020*** −0.023*** 0.008*** 0.016*** −0.008*** Youngest child 7+ −0.056*** −0.013*** −0.042*** −0.047*** −0.017*** −0.03*** Part-time −0.007*** 0.034*** −0.04*** Work overtime 0.076*** 0.019*** 0.057*** Flexible hours −0.016*** −0.004** −0.012*** Work from home (none)  Job requirement 0.116*** 0.078*** 0.038***  Personal/family resp 0.172*** 0.107*** 0.065***  Usual place of work 0.220*** 0.161*** 0.06***  Better conditions 0.076*** 0.050*** 0.026***  Other 0.080*** 0.062*** 0.019*** Top-ups 0.106*** 0.009*** 0.097*** Employer childcare 0.019*** −0.004* 0.023*** R-squared 0.447 0.376 Note: Models control for age, race/immigration, survey year, spouse, education, experience, seniority, occupation, and unionization. * p < 0.05 ** p < 0.01 *** p < 0.001 Table A.2. Regression Estimates of Economy-Wide, Within-Establishment, and Between-Establishment Effects of Motherhood on Log-Hourly Wages by Mobility Pattern, Formalization and Nonprofit Status, Women 25–44 (1) Mobility (2) Mobility by formalization and nonprofit Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments No employer change 0.037*** 0.020*** 0.017*** 0.059*** 0.023*** 0.036*** Employer change after caregiving break −0.106*** −0.038*** −0.068*** −0.096*** −0.035*** −0.061*** Other post-motherhood employer change −0.046*** −0.010*** −0.035*** −0.084*** −0.039*** −0.045*** Union −0.005 −0.026*** 0.022*** No employer change*Union 0.040*** 0.026*** 0.014*** Employer change after caregiving break*Union 0.158*** 0.116*** 0.041*** Other post-motherhood employer change*Union 0.064*** 0.055*** 0.009*** HR in establishment 0.074*** 0.028*** 0.046*** No employer change*HR −0.026*** −0.063*** 0.037*** Employer change after caregiving break*HR 0.059*** 0.004 0.055*** Other post-motherhood employer change*HR 0.025*** −0.024*** 0.049*** Nonprofit −0.037*** 0.005** −0.041*** No employer change*Nonprofit −0.035*** −0.014*** −0.021*** Employer change after caregiving break*Nonprofit 0.024** 0.021*** 0.003 Other post-motherhood employer change*Nonprofit 0.023*** −0.016*** 0.039*** Size (0–19)  20–99 0.046*** −0.026*** 0.072***  100–499 0.090*** −0.038*** 0.128***  500 plus 0.161*** −0.039*** 0.201*** No employer change*20–99 −0.012 0.028*** −0.04*** No employer change*100–499 −0.032*** 0.019*** −0.051*** No employer change*500 plus −0.010 0.041*** −0.051*** Employer change after caregiving break*20–99 −0.103*** −0.039*** −0.064*** Employer change after caregiving break*100–499 −0.088*** −0.045*** −0.043*** Employer change after caregiving break*500 plus −0.104*** −0.120*** 0.016 Other post-motherhood employer change*20–99 0.023*** 0.029*** −0.007** Other post-motherhood employer change*100–499 0.004 0.046*** −0.042*** Other post-motherhood employer change*500 plus 0.013 0.044*** −0.031*** R-squared 0.45 0.376 0.469 0.375 (1) Mobility (2) Mobility by formalization and nonprofit Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments No employer change 0.037*** 0.020*** 0.017*** 0.059*** 0.023*** 0.036*** Employer change after caregiving break −0.106*** −0.038*** −0.068*** −0.096*** −0.035*** −0.061*** Other post-motherhood employer change −0.046*** −0.010*** −0.035*** −0.084*** −0.039*** −0.045*** Union −0.005 −0.026*** 0.022*** No employer change*Union 0.040*** 0.026*** 0.014*** Employer change after caregiving break*Union 0.158*** 0.116*** 0.041*** Other post-motherhood employer change*Union 0.064*** 0.055*** 0.009*** HR in establishment 0.074*** 0.028*** 0.046*** No employer change*HR −0.026*** −0.063*** 0.037*** Employer change after caregiving break*HR 0.059*** 0.004 0.055*** Other post-motherhood employer change*HR 0.025*** −0.024*** 0.049*** Nonprofit −0.037*** 0.005** −0.041*** No employer change*Nonprofit −0.035*** −0.014*** −0.021*** Employer change after caregiving break*Nonprofit 0.024** 0.021*** 0.003 Other post-motherhood employer change*Nonprofit 0.023*** −0.016*** 0.039*** Size (0–19)  20–99 0.046*** −0.026*** 0.072***  100–499 0.090*** −0.038*** 0.128***  500 plus 0.161*** −0.039*** 0.201*** No employer change*20–99 −0.012 0.028*** −0.04*** No employer change*100–499 −0.032*** 0.019*** −0.051*** No employer change*500 plus −0.010 0.041*** −0.051*** Employer change after caregiving break*20–99 −0.103*** −0.039*** −0.064*** Employer change after caregiving break*100–499 −0.088*** −0.045*** −0.043*** Employer change after caregiving break*500 plus −0.104*** −0.120*** 0.016 Other post-motherhood employer change*20–99 0.023*** 0.029*** −0.007** Other post-motherhood employer change*100–499 0.004 0.046*** −0.042*** Other post-motherhood employer change*500 plus 0.013 0.044*** −0.031*** R-squared 0.45 0.376 0.469 0.375 Note: Models control for age, race/immigration, survey year, spouse, education, experience, seniority, occupation, and unionization. * p < 0.05 ** p < 0.01 *** p < 0.001 Table A.2. Regression Estimates of Economy-Wide, Within-Establishment, and Between-Establishment Effects of Motherhood on Log-Hourly Wages by Mobility Pattern, Formalization and Nonprofit Status, Women 25–44 (1) Mobility (2) Mobility by formalization and nonprofit Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments No employer change 0.037*** 0.020*** 0.017*** 0.059*** 0.023*** 0.036*** Employer change after caregiving break −0.106*** −0.038*** −0.068*** −0.096*** −0.035*** −0.061*** Other post-motherhood employer change −0.046*** −0.010*** −0.035*** −0.084*** −0.039*** −0.045*** Union −0.005 −0.026*** 0.022*** No employer change*Union 0.040*** 0.026*** 0.014*** Employer change after caregiving break*Union 0.158*** 0.116*** 0.041*** Other post-motherhood employer change*Union 0.064*** 0.055*** 0.009*** HR in establishment 0.074*** 0.028*** 0.046*** No employer change*HR −0.026*** −0.063*** 0.037*** Employer change after caregiving break*HR 0.059*** 0.004 0.055*** Other post-motherhood employer change*HR 0.025*** −0.024*** 0.049*** Nonprofit −0.037*** 0.005** −0.041*** No employer change*Nonprofit −0.035*** −0.014*** −0.021*** Employer change after caregiving break*Nonprofit 0.024** 0.021*** 0.003 Other post-motherhood employer change*Nonprofit 0.023*** −0.016*** 0.039*** Size (0–19)  20–99 0.046*** −0.026*** 0.072***  100–499 0.090*** −0.038*** 0.128***  500 plus 0.161*** −0.039*** 0.201*** No employer change*20–99 −0.012 0.028*** −0.04*** No employer change*100–499 −0.032*** 0.019*** −0.051*** No employer change*500 plus −0.010 0.041*** −0.051*** Employer change after caregiving break*20–99 −0.103*** −0.039*** −0.064*** Employer change after caregiving break*100–499 −0.088*** −0.045*** −0.043*** Employer change after caregiving break*500 plus −0.104*** −0.120*** 0.016 Other post-motherhood employer change*20–99 0.023*** 0.029*** −0.007** Other post-motherhood employer change*100–499 0.004 0.046*** −0.042*** Other post-motherhood employer change*500 plus 0.013 0.044*** −0.031*** R-squared 0.45 0.376 0.469 0.375 (1) Mobility (2) Mobility by formalization and nonprofit Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments No employer change 0.037*** 0.020*** 0.017*** 0.059*** 0.023*** 0.036*** Employer change after caregiving break −0.106*** −0.038*** −0.068*** −0.096*** −0.035*** −0.061*** Other post-motherhood employer change −0.046*** −0.010*** −0.035*** −0.084*** −0.039*** −0.045*** Union −0.005 −0.026*** 0.022*** No employer change*Union 0.040*** 0.026*** 0.014*** Employer change after caregiving break*Union 0.158*** 0.116*** 0.041*** Other post-motherhood employer change*Union 0.064*** 0.055*** 0.009*** HR in establishment 0.074*** 0.028*** 0.046*** No employer change*HR −0.026*** −0.063*** 0.037*** Employer change after caregiving break*HR 0.059*** 0.004 0.055*** Other post-motherhood employer change*HR 0.025*** −0.024*** 0.049*** Nonprofit −0.037*** 0.005** −0.041*** No employer change*Nonprofit −0.035*** −0.014*** −0.021*** Employer change after caregiving break*Nonprofit 0.024** 0.021*** 0.003 Other post-motherhood employer change*Nonprofit 0.023*** −0.016*** 0.039*** Size (0–19)  20–99 0.046*** −0.026*** 0.072***  100–499 0.090*** −0.038*** 0.128***  500 plus 0.161*** −0.039*** 0.201*** No employer change*20–99 −0.012 0.028*** −0.04*** No employer change*100–499 −0.032*** 0.019*** −0.051*** No employer change*500 plus −0.010 0.041*** −0.051*** Employer change after caregiving break*20–99 −0.103*** −0.039*** −0.064*** Employer change after caregiving break*100–499 −0.088*** −0.045*** −0.043*** Employer change after caregiving break*500 plus −0.104*** −0.120*** 0.016 Other post-motherhood employer change*20–99 0.023*** 0.029*** −0.007** Other post-motherhood employer change*100–499 0.004 0.046*** −0.042*** Other post-motherhood employer change*500 plus 0.013 0.044*** −0.031*** R-squared 0.45 0.376 0.469 0.375 Note: Models control for age, race/immigration, survey year, spouse, education, experience, seniority, occupation, and unionization. * p < 0.05 ** p < 0.01 *** p < 0.001 About the Author Sylvia Fuller is Associate Professor at the University of British Columbia. Her research centers on understanding how labor market inequalities develop and erode and the implications of changing employment relations and social policy frameworks for workers’ economic security and mobility. Recent publications explore temporary workers’ employment trajectories, divergence in the career pathways of new immigrants, and trends in the medicalization of welfare among lone mothers. Supplementary Material Supplementary material is available at Social Forces online. References Abowd , John M. , Francis Kramarz , and David N. Margolis . 1999 . “ High Wage Workers and High Wage Firms .” Econometrica 67 ( 2 ): 251 – 333 . Google Scholar CrossRef Search ADS Acker , Joan . 1990 . “ Hierarchies, Jobs, Bodies: A Theory of Gendered Organizations .” Gender & Society 4 ( 2 ): 139 – 58 . Google Scholar CrossRef Search ADS ——— . 2006 . “ Inequality Regimes Gender, Class, and Race in Organizations .” Gender & Society 20 ( 4 ): 441 – 64 . Google Scholar CrossRef Search ADS Adams , Lorna , Mark Winterbotham , Katie Oldfield , Jenny McLeish , Alasdair Stuart , Alice Large , Liz Murphy , Helen Rossiter , and Sam Selner . 2016 . “Pregnancy and Maternity-Related Discrimination and Disadvantage: Experiences of Employers.” London : Department for Business, Innovation and Skills and the Equality and Human Rights Commission, Great Britain . Aisenbrey , Silke , Marie Evertsson , and Daniela Grunow . 2009 . “ Is There a Career Penalty for Mothers’ Time Out? A Comparison of Germany, Sweden and the United States .” Social Forces 88 ( 2 ): 573 – 605 . Google Scholar CrossRef Search ADS Akerlof , George A. 1982 . “ Labor Contracts as Partial Gift Exchange .” Quarterly Journal of Economics 97 ( 4 ): 543 – 69 . Google Scholar CrossRef Search ADS Anderson , Deborah J. , Melissa Binder , and Kate Krause . 2002 . “ The Motherhood Wage Penalty: Which Mothers Pay It and Why? ” American Economic Review 92 ( 2 ): 354 – 58 . Google Scholar CrossRef Search ADS ——— . 2003 . “ The Motherhood Wage Penalty Revisited: Experience, Heterogeneity, Work Effort, and Work-Schedule Flexibility .” Industrial & Labor Relations Review 56 ( 2 ): 273 – 94 . Google Scholar CrossRef Search ADS Avellar , Sarah , and Pamela J. Smock . 2003 . “ Has the Price of Motherhood Declined over Time? A Cross-Cohort Comparison of the Motherhood Wage Penalty .” Journal of Marriage and Family 65 ( 3 ): 597 – 607 . Google Scholar CrossRef Search ADS Avent-Holt , Dustin , and Donald Tomaskovic-Devey . 2010 . “ The Relational Basis of Inequality: Generic and Contingent Wage Distribution Processes .” Work and Occupations 37 ( 2 ): 162 – 93 . Google Scholar CrossRef Search ADS ——— . 2014 . “ A Relational Theory of Earnings Inequality .” American Behavioral Scientist 58 ( 3 ): 379 – 99 Google Scholar CrossRef Search ADS Bardasi , Elena , and Janet C. Gornick . 2008 . “ Working for Less? Women’s Part-Time Wage Penalties across Countries .” Feminist Economics 14 ( 1 ): 37 – 72 . Google Scholar CrossRef Search ADS Baron , J. N. , and W. T. Bielby. 1980 . “ Bringing the Firms Back. In: Stratification, Segmentation, and the Organization of Work .” American Sociological Review 45 ( 5 ): 737 – 65 . Google Scholar CrossRef Search ADS Baron , James N. , Michael T. Hannan , Greta Hsu , and Özgecan Koçak . 2007 . “ In the Company of Women Gender Inequality and the Logic of Bureaucracy in Start-Up Firms .” Work and Occupations 34 ( 1 ): 35 – 66 . Google Scholar CrossRef Search ADS Baughman , Reagan , Daniela DiNardi , and Douglas Holtz-Eakin . 2003 . “ Productivity and Wage Effects of ‘Family-Friendly’ Fringe Benefits .” International Journal of Manpower 24 ( 3 ): 247 – 59 . Google Scholar CrossRef Search ADS Bayard , Kimberly , Judith Hellerstein , David Neumark , and Kenneth Troske . 2003 . New Evidence on Sex Segregation and Sex Differences in Wages from Matched Employee-Employer Data . Journal of Labour Economics 21 ( 4 ): 887 – 922 . Beaujot , Roderic , and Zenaida R. Ravanera . 2009 . “ Family Models for Earning and Caring: Implications for Child Care and for Family Policy .” Canadian Studies in Population 36 ( 1 – 2 ): 145 – 66 . Google Scholar CrossRef Search ADS Beblo , Miriam , Stefan Bender , and Elke Wolf . 2008 . “ Establishment-Level Wage Effects of Entering Motherhood .” Oxford Economic Papers 61 : i11 – i34 . Google Scholar CrossRef Search ADS Becker , Gary S. 1993 . A Treatise on the Family , rev. ed. Cambridge, MA : Harvard University Press . Bidwell , Matthew , Forrest Briscoe , Isabel Fernandez-Mateo , and Adina Sterling . 2013 . “ The Employment Relationship and Inequality: How and Why Changes in Employment Practices Are Reshaping Rewards in Organizations .” Academy of Management Annals 7 ( 1 ): 61 – 121 . Google Scholar CrossRef Search ADS Blair-Loy , Mary . 2003 . Competing Devotions: Career and Family among Women Executives . Boston : Harvard University Press . Blair-Loy , Mary , and Amy S. Wharton . 2002 . “ Employees’ Use of Work-Family Policies and the Workplace Social Context .” Social Forces 80 ( 3 ): 813 – 45 . Google Scholar CrossRef Search ADS Bloom , Nick , Tobias Kretschmer , and John Van Reenan . 2009 . “Work-Life Balance, Management Practices and Productivity.” In International Differences in the Business Practices and Productivity of Firms , edited by Richard B. Freeman and Kathryn L. Shaw , pp. 15 – 54 . Chicago, IL : University of Chicago Press . Google Scholar CrossRef Search ADS Boushey , Heather . 2008 . “ Family Friendly Policies: Helping Mothers Make Ends Meet .” Review of Social Economy 66 ( 1 ): 51 – 70 . Google Scholar CrossRef Search ADS Brescoll , Victoria L. , Jennifer Glass , and Alexandra Sedlovskaya . 2013 . “ Ask and Ye Shall Receive? The Dynamics of Employer-Provided Flexible Work Options and the Need for Public Policy .” Journal of Social Issues 69 ( 2 ): 367 – 88 . Google Scholar CrossRef Search ADS Bronars , Stephen G. , and Melissa Famulari . 1997 . “ Wage, Tenure, and Wage Growth Variation within and across Establishments .” Journal of Labor Economics 15 ( 2 ): 285 – 317 . Google Scholar CrossRef Search ADS Budig , Michelle J. , and Paula England . 2001 . “ The Wage Penalty for Motherhood .” American Sociological Review 66 ( 2 ): 204 – 25 . Google Scholar CrossRef Search ADS Budig , Michelle J. , Joya Misra , and Irene Boeckmann . 2016 . “ Work-Family Policy Trade-Offs for Mothers? Unpacking the Cross-National Variation in Motherhood Earnings Penalties .” Work and Occupations 43 ( 2 ): 119 – 77 . Google Scholar CrossRef Search ADS Byron , Reginald A. , and Vincent J. Roscigno . 2014 . “ Relational Power, Legitimation, and Pregnancy Discrimination .” Gender & Society 28 ( 3 ): 435 – 62 . Google Scholar CrossRef Search ADS Canay , Ivan A. 2011 . “ A Simple Approach to Quantile Regression for Panel Data .” Econometrics Journal 14 ( 3 ): 368 – 86 . Google Scholar CrossRef Search ADS Cappelli , Peter . 1999 . The New Deal at Work: Managing the Market-Driven Workforce . Boston : Harvard Business Press . Correll , Shelley J. , Stephen Benard , and In Paik . 2007 . “ Getting a Job: Is There a Motherhood Penalty? ” American Journal of Sociology 112 ( 5 ): 1297 – 1338 . Google Scholar CrossRef Search ADS Cooke , Lynn Prince . 2011 . Gender-Class Equality in Political Economies . New York : Routledge . ——— . 2014 . “ Gendered Parenthood Penalties and Premiums across the Earnings Distribution in Australia, the United Kingdom, and the United States .” European Sociological Review 30 ( 3 ): 360 – 72 . Google Scholar CrossRef Search ADS Crowley , Jocelyn Elise . 2013 . “ Perceiving and Responding to Maternal Workplace Discrimination in the United States .” Women’s Studies International Forum 40 : 192 – 202 . Google Scholar CrossRef Search ADS Damman , Marleen , Liesbet Heyse , and Melinda Mills . 2014 . “ Gender, Occupation, and Promotion to Management in the Nonprofit Sector .” Nonprofit Management and Leadership 25 ( 2 ): 97 – 111 . Google Scholar CrossRef Search ADS Dau-Schmidt , Kenneth G. , Marc S. Galanter , Kaushik Mukhopadhaya , and Kathleen E. Hull . 2009 . “ Men and Women of the Bar: The Impact of Gender on Legal Careers .” Michigan Journal of Gender and Law 16 ( 1 ): 49 – 145 . DiMaggio , Paul , and Walter W. Powell . 1983 . “ The Iron Cage Revisited: Collective Rationality and Institutional Isomorphism in Organizational Fields .” American Sociological Review 48 ( 2 ): 147 – 60 . Google Scholar CrossRef Search ADS Dobbin , Frank . 2009 . Inventing Equal Opportunity . Princeton, NJ : Princeton University Press . Google Scholar CrossRef Search ADS Dodson , Lisa . 2013 . “ Stereotyping Low-Wage Mothers Who Have Work and Family Conflicts .” Journal of Social Issues 69 ( 2 ): 257 – 78 . Google Scholar CrossRef Search ADS Drolet , Marie . 2002 . “ Can the Workplace Explain Canadian Gender Pay Differentials? ” Canadian Public Policy 28 ( 1 ): 41 – 63 . Google Scholar CrossRef Search ADS Drolet , Marie , and Karen Mumford . 2012 . “ The Gender Pay Gap for Private-Sector Employees in Canada and Britain .” British Journal of Industrial Relations 50 ( 3 ): 529 – 53 . Google Scholar CrossRef Search ADS Duxbury , Linda , and Laura Gover . 2011 . “Exploring the Link between Organizational Culture and Work-Family Conflict.” In The Handbook of Organizational Culture and Climate , edited by Neal M. Ashkanasy , Celeste Wilderom , and Mark F. Peterson , pp. 271 – 90 . Thousand Oaks, CA : Sage Publications . Google Scholar CrossRef Search ADS Edelman , Lauren B. , Christopher Uggen , and Howard S. Erlanger . 1999 . “ The Endogeneity of Legal Regulation: Grievance Procedures as Rational Myth .” American Journal of Sociology 105 ( 2 ): 406 – 54 . Google Scholar CrossRef Search ADS Elvira , Marta M. , and Ishak Saporta . 2001 . “ How Does Collective Bargaining Affect the Gender Pay Gap? ” Work and Occupations 28 ( 4 ): 469 – 90 . Google Scholar CrossRef Search ADS Epstein , Cynthia Fuchs , Carroll Seron , Bonnie Oglensky , and Robert Saute . 2014 . The Part-Time Paradox: Time Norms, Professional Life, Family and Gender . New York and London : Routledge . Fahlén , Susanne . 2013 . “Worklife Balance: The Agency and Capabilities Gap.” In The Agency and Capabilities Gap in Work—Life Balance Across European and Asian Societies and within Work Organizations , edited by Barbara Hobson , pp. 35 – 56 . New York : Oxford University Press . Fakih , Ali . 2014 . “Availability of Family-Friendly Work Practices and Implicit Wage Costs: New Evidence from Canada.” IZA Discussion Papers No. 8190:1–31. Felfe , Christina . 2012 . “ The Motherhood Wage Gap: What About Job Amenities? ” Labour Economics 19 ( 1 ): 59 – 67 . Google Scholar CrossRef Search ADS Fuegen , Kathleen , Monica Biernat , Elizabeth Haines , and Kay Deaux . 2004 . “ Mothers and Fathers in the Workplace: How Gender and Parental Status Influence Judgments of Job-Related Competence .” Journal of Social Issues 60 ( 4 ): 737 – 54 . Google Scholar CrossRef Search ADS Fuller , Sylvia . 2005 . “ Public Sector Employment and Gender Wage Inequalities in British Columbia: Assessing the Effects of a Shrinking Public Sector .” Canadian Journal of Sociology 30 ( 4 ): 405 – 39 . ——— . 2008 . “ Job Mobility and Wage Trajectories for Men and Women in the United States .” American Sociological Review 73 ( 1 ): 158 – 83. Google Scholar CrossRef Search ADS Gariety , Bonnie Sue , and Sherrill Shaffer . 2001 . “ Wage Differentials Associated with Flextime .” Monthly Labour Review 124 ( 3 ): 68 – 75 . Glass , Jennifer . 2004 . “ Blessing or Curse? Work-Family Policies and Mother’s Wage Growth over Time .” Work and Occupations 31 ( 3 ): 367 – 94 . Google Scholar CrossRef Search ADS Glauber , Rebecca . 2012 . “ Women’s Work and Working Conditions: Are Mothers Compensated for Lost Wages? ” Work and Occupations 39 ( 2 ): 115 – 38 . Google Scholar CrossRef Search ADS Golden , Lonnie , Julia R. Henly , and Susan Lambert . 2013 . “ Work Schedule Flexibility: A Contributor to Happiness? ” Journal of Social Research & Policy 4 ( 2 ): 107 . Golden , Lonnie , and Barbara Wiens-Tuers . 2005 . “ Mandatory Overtime Work in the United States: Who, Where, and What? ” Labor Studies Journal 30 ( 1 ): 1 – 25 . Google Scholar CrossRef Search ADS Groshen , Erica L. 1991 . “ Sources of Intra-Industry Wage Dispersion: How Much Do Employers Matter? ” Quarterly Journal of Economics 106 ( 3 ): 869 – 84 . Google Scholar CrossRef Search ADS Gunderson , Morley , and Douglas Hyatt . 2001 . “ Workplace Risks and Wages: Canadian Evidence from Alternative Models .” Canadian Journal of Economics/Revue Canadienne D’économique 34 ( 2 ): 377 – 95 . Google Scholar CrossRef Search ADS Haley-Lock , Anna . 2011 . “ Place-Bound Jobs at the Intersection of Policy and Management: Comparing Employer Practices in US and Canadian Chain Restaurants .” American Behavioral Scientist 55 ( 7 ): 823 – 42 . Google Scholar CrossRef Search ADS Harkness , Susan , and Jane Waldfogel . 2003 . “ The Family Gap in Pay: Evidence from Seven Industrialized Countries .” Research in Labor Economics 22 : 369 – 414 . Google Scholar CrossRef Search ADS Heilman , Madeline E. , and Tyler G. Okimoto . 2008 . “ Motherhood: A Potential Source of Bias in Employment Decisions .” Journal of Applied Psychology 93 ( 1 ): 189 . Google Scholar CrossRef Search ADS Herr , Jane Leber , and Catherine D. Wolfram . 2012 . “ Work Environment and Opt-Out Rates at Motherhood across High-Education Career Paths .” Industrial & Labor Relations Review 65 ( 4 ): 928 – 50 . Google Scholar CrossRef Search ADS Heywood , John S. , W. Stanley Siebert , and Xiangdong Wei . 2007 . “ The Implicit Wage Costs of Family Friendly Work Practices .” Oxford Economic Papers 59 ( 2 ): 275 – 300 . Google Scholar CrossRef Search ADS Hodges , Melissa J. , and Michelle J. Budig . 2010 . “ Who Gets the Daddy Bonus? Organizational Hegemonic Masculinity and the Impact of Fatherhood on Earnings .” Gender & Society 24 ( 6 ): 717 – 45 . Google Scholar CrossRef Search ADS Hollister , Matissa . 2011 . “ Employment Stability in the US Labor Market: Rhetoric versus Reality .” Annual Review of Sociology 37 ( 1 ): 305 – 24 . Google Scholar CrossRef Search ADS Hou , Feng , and Simon Coulombe . 2010 . “ Earnings Gaps for Canadian-Born Visible Minorities in the Public and Private Sectors .” Canadian Public Policy 36 ( 1 ): 29 – 43 . Google Scholar CrossRef Search ADS Javdani , Mohsen . 2015 . “ Glass Ceilings or Glass Doors? The Role of Firms in Male-Female Wage Disparities .” Canadian Journal of Economics/Revue canadienne d’économique 48 ( 2 ): 529 – 60 . Google Scholar CrossRef Search ADS Johnson , Nancy Brown , and Keith G. Provan . 1996 . “ The Relationship between Work/Family Benefits and Earnings: A Test of Competing Predictions .” Journal of Socio-Economics 24 ( 4 ): 571 – 84 . Google Scholar CrossRef Search ADS Kalev , Alexandra . 2014 . “ How You Downsize Is Who You Downsize: Biased Formalization, Accountability, and Managerial Diversity .” American Sociological Review 79 ( 1 ): 109 – 35 . Google Scholar CrossRef Search ADS Kalleberg , Arne . 2013 . Good Jobs, Bad Jobs: The Rise of Polarized and Precarious Employment Systems in the United States, 1970s to 2000s . New York : Russell Sage Foundation Keith , Kristen , and Abagail McWilliams . 1997 . “ Job Mobility and Gender-Based Wage Growth Differentials .” Economic Inquiry 35 ( 2 ): 320 – 33 . Google Scholar CrossRef Search ADS Kelly , Erin , and Frank Dobbin . 1998 . “ How Affirmative Action Became Diversity Management Employer Response to Antidiscrimination Law, 1961 to 1996 .” American Behavioral Scientist 41 ( 7 ): 960 – 84 . Google Scholar CrossRef Search ADS Kelly , Erin L. , Phyllis Moen , and Eric Tranby . 2011 . “ Changing Workplaces to Reduce Work-Family Conflict .” American Sociological Review 76 ( 2 ): 265 . Google Scholar CrossRef Search ADS Killewald , Alexandra . 2012 . “ A Reconsideration of the Fatherhood Premium: Marriage, Coresidence, Biology, and Fathers’ Wages .” American Sociological Review 78 ( 1 ): 96 – 116 . Google Scholar CrossRef Search ADS Kronberg , Anne-Kathrin . 2013 . “ Stay or Leave? Externalization of Job Mobility and the Effect on the US Gender Earnings Gap, 1979–2009 .” Social Forces 91 ( 4 ): 1117 – 46 . Google Scholar CrossRef Search ADS Lambert , Susan , Anna Haley-Lock , and Julia R. Henly . 2012 . “ Schedule Flexibility in Hourly Jobs: Unanticipated Consequences and Promising Directions .” Community, Work & Family 15 ( 3 ): 293 – 315 . Google Scholar CrossRef Search ADS Lane , Julia I. , Laurie A. Salmon , and James R. Spletzer . 2007 . “ Establishment Wage Differentials .” Monthly Labour Review 130 ( 3 ): 3 – 17 . Looze , Jessica . 2014 . “ Young Women’s Job Mobility: The Influence of Motherhood Status and Education .” Journal of Marriage and Family 76 ( 4 ): 693 – 709 . Google Scholar CrossRef Search ADS Looze , Jessica . 2009 . “ The Family Work Week .” Perspectives on Labour and Income 21 ( 2 ): 21 – 9 . Mastracci , Sharon H. , and Cedric Herring . 2010 . “ Nonprofit Management Practices and Work Processes to Promote Gender Diversity .” Nonprofit Management and Leadership 21 ( 2 ): 155 – 75 . Google Scholar CrossRef Search ADS McCrate , Elaine . 2005 . “ Flexible Hours, Workplace Authority, and Compensating Wage Differentials in the U.S .” Feminist Economics 11 ( 1 ): 11 – 39 . Google Scholar CrossRef Search ADS ——— . 2016 . “Unstable Scheduling, Precarious Employment, and Gender.” Working Paper, EINet Measurement Group. McGinnity , Frances , and Patricia McManus . 2007 . “ Paying the Price for Reconciling Work and Family Life: Comparing the Wage Penalty for Women’s Part-Time Work in Britain, Germany and the United States .” Journal of Comparative Policy Analysis 9 ( 2 ): 115 – 34 . Google Scholar CrossRef Search ADS OECD . 2004 . “Wage-Setting Institutions and Outcomes.” In OECD Employment Outlook. Geneva : OECD . ——— . 2013 . “Chart Pf3.1.A Expenditure on Childcare and Pre-Pimary, 2011.” In OECD Family Database. ——— . 2017 a. “Chart LMF1.2.A Maternal Employment Rates, 2014 or Latest Available Year.” In OECD Family Database. Paris. Accessed November 2017. ——— . 2017 b. “Chart Pf2.5. Trends in Leave Entitlements Around Childbirth.” In OECD Family Database. Paris. Pendakur , Krishna , and Simon Woodcock . 2010 . “ Glass Ceilings or Glass Doors? Wage Disparity Within and Between Firms .” Journal of Business & Economic Statistics 28 ( 1 ): 181 – 89 . Google Scholar CrossRef Search ADS Petersen , Trond , and Laurie A. Morgan . 1995 . “ Separate and Unequal: Occupation-Establishment Sex Segregation and the Gender Wage Gap .” American Journal of Sociology 101 ( 2 ): 329 – 65 . Google Scholar CrossRef Search ADS Petersen , Trond , Andrew M. Penner , and Geir Høgsnes . 2010 . “ The Within-Job Motherhood Wage Penalty in Norway, 1979–1996 .” Journal of Marriage and Family 72 ( 5 ): 1274 – 88 . Google Scholar CrossRef Search ADS ——— . 2011 . “ The Male Marital Wage Premium: Sorting vs. Differential Pay .” ILR Review 64 ( 2 ): 283 – 304 . Google Scholar CrossRef Search ADS ——— . 2014 . “ From Motherhood Penalties to Husband Premia: The New Challenge for Gender Equality and Family Policy, Lessons from Norway .” American Journal of Sociology 119 ( 5 ): 1434 – 72 . Google Scholar CrossRef Search ADS Petersen , Trond , and Ishak Saporta . 2004 . “ The Opportunity Structure for Discrimination .” American Journal of Sociology 109 ( 4 ): 852 – 901 . Google Scholar CrossRef Search ADS Phipps , Shelley , Peter Burton , and Lynn Lethbridge . 2001 . “ In and Out of the Labour Market: Long-Term Income Consequences of Child-Related Interruptions to Women’s Paid Work .” Canadian Journal of Economics/Revue Canadienne d’Economique 34 ( 2 ): 411 – 29 . Google Scholar CrossRef Search ADS Raley , Sara , Suzanne M. Bianchi , and Wendy Wang . 2012 . “ When Do Fathers Care? Mothers’ Economic Contribution and Fathers’ Involvement in Child Care .” American Journal of Sociology 117 ( 5 ): 1422 – 59 . Google Scholar CrossRef Search ADS Reskin , Barbara F. , and Debra Branch McBrier . 2000 . “ Why Not Ascription? Organizations’ Employment of Male and Female Managers .” American Sociological Review 65 ( 2 ): 210 – 33 . Google Scholar CrossRef Search ADS Ridgeway , Cecilia L. , and Shelley J. Correll . 2004 . “ Motherhood as a Status Characteristic .” Journal of Social Issues 60 ( 4 ): 683 – 700 . Google Scholar CrossRef Search ADS Sakamoto , Arthur , and Sharron Xuanren Wang . 2016 . “ Occupational and Organizational Effects on Wages among College-Educated Workers in 2003 and 2010 .” Social Currents 4 ( 2 ): 175 – 95 . Google Scholar CrossRef Search ADS Salop , Steven C. 1979 . “ A Model of the Natural Rate of Unemployment .” American Economic Review 69 ( 1 ): 117 – 25 . Shapiro , Carl , and Joseph E. Stiglitz . 1984 . “ Equilibrium Unemployment as a Worker Discipline Device .” American Economic Review 74 ( 3 ): 433 – 44 . Simón , Hipólito . 2010 . “ International Differences in Wage Inequality: A New Glance with European Matched Employer–Employee Data .” British Journal of Industrial Relations 48 ( 2 ): 310 – 46 . Google Scholar CrossRef Search ADS Stainback , Kevin , Thomas N. Ratliff , and Vincent J. Roscigno . 2011 . “ The Context of Workplace Sex Discrimination: Sex Composition, Workplace Culture and Relative Power .” Social Forces 89 ( 4 ): 1165 – 88 . Google Scholar CrossRef Search ADS Stainback , Kevin , Donald Tomaskovic-Devey , and Sheryl Skaggs . 2010 . “ Organizational Approaches to Inequality: Inertia, Relative Power, and Environments .” Annual Review of Sociology 36 ( 1 ): 225 – 47 . Google Scholar CrossRef Search ADS Statistics Canada . 2017 . Table 281-0024 Survey of Employment, Payrolls, and Hours (SEPH), Employment by Type of Employee and Detailed North American Industry Classification System (NAICS), Annual (persons), CANSIM (database). Accessed May 2017. Stinchcombe , Arthur L. 2001 . When Formality Works: Authority and Abstraction in Law and Organizations . Chicago : University of Chicago Press . Stone , Pamela , and Lisa Ackerly Hernandez . 2013 . “ The All-or-Nothing Workplace: Flexibility Stigma and ‘Opting Out’ among Professional-Managerial Women .” Journal of Social Issues 69 ( 2 ): 235 – 56 . Google Scholar CrossRef Search ADS Sweet , Stephen , Marcie Pitt-Catsouphes , Elyssa Besen , and Lonnie Golden . 2014 . “ Explaining Organizational Variation in Flexible Work Arrangements: Why the Pattern and Scale of Availability Matter .” Community, Work & Family 17 ( 2 ): 115 – 41 . Google Scholar CrossRef Search ADS Tilly , Charles . 1998 . Durable Inequalities. Berkeley : University of California Press . Tomaskovic-Devey , Donald , Martin Hällsten , and Martin Avent-Holt . 2015 . “ Where Do Immigrants Fare Worse? Modeling Workplace Wage Gap Variation with Longitudinal Employer-Employee Data .” American Journal of Sociology 120 ( 4 ): 1095 – 1143 . Google Scholar CrossRef Search ADS Tomlinson , Frances , and Christina Schwabenland . 2010 . “ Reconciling Competing Discourses of Diversity? The UK Non-Profit Sector between Social Justice and the Business Case .” Organization 17 ( 1 ): 101 – 21 . Google Scholar CrossRef Search ADS Viitanen , Tarja . 2014 . “ The Motherhood Wage Gap in the UK over the Life Cycle .” Review of Economics of the Household 12 ( 2 ): 259 – 76 . Google Scholar CrossRef Search ADS Vosko , Leah F. 2009 . Managing the Margins: Gender, Citizenship, and the International Regulation of Precarious Employment . Toronto : Oxford University Press . Waite , Sean , and Nicole Denier . 2015 . “ Gay Pay for Straight Work Mechanisms Generating Disadvantage .” Gender & Society 29 ( 4 ): 561 – 88 . Google Scholar CrossRef Search ADS Webber , Gretchen , and Christine Williams . 2008 . “ Mothers in ‘Good’ and ‘Bad’ Part-Time Jobs: Different Problems, Same Results .” Gender & Society 22 ( 6 ): 752 – 77 . Google Scholar CrossRef Search ADS Weeden , Kim A. 2005 . “ Is There a Flexiglass Ceiling? Flexible Work Arrangements and Wages in the United States .” Social Science Research 34 ( 2 ): 454 – 82 . Google Scholar CrossRef Search ADS Wilde , Elizabeth Ty , Lily Batchelder , and David T. Ellwood . 2010 . The Mommy Track Divides: The Impact of Childbearing on Wages of Women of Differing Skill Levels. National Bureau of Economic Research . Williams , Joan . 2000 . Why Work and Family Conflict and What to Do About It . New York : Oxford University Press . ——— . 2010 . Reshaping the Work-Family Debate . Cambridge, MA : Harvard University Press . Williams , Joan , Mary Blair-Loy , and Jennifer Berdahl . 2013 . “ Cultural Schemas, Social Class, and the Flexibility Stigma .” Journal of Social Issues 69 ( 2 ): 209 – 34 . Google Scholar CrossRef Search ADS Wilson , George , Vincent J. Roscigno , and Matt L. Huffman . 2013 . “ Public Sector Transformation, Racial Inequality and Downward Occupational Mobility .” Social Forces 91 ( 3 ): 975 – 1006 . Google Scholar CrossRef Search ADS ——— . 2015 . “ Racial Income Inequality and Public Sector Privatization .” Social Problems 62 ( 2 ): 163 – 85. Google Scholar CrossRef Search ADS Winder , Katie L. 2009 . “ Flexible Scheduling and the Gender Wage Gap .” B. E. Journal of Economic Analysis & Policy 9 ( 1 ):1935–1682. Zhang , Xuelin . 2007 . “ Returning to the Job after Childbirth .” Perspectives on Labour and Income 20 ( 1 ): 18 – 24 . ——— . 2009 . “ Earnings of Women with and without Children .” Perspectives on Labour and Income 10 ( 3 ): 5 – 13 . ——— . 2010 . “ Can Motherhood Earnings Losses Be Ever Regained? Evidence from Canada .” Journal of Family Issues 31 ( 12 ): 1671 – 88 . Google Scholar CrossRef Search ADS Author notes The author gratefully acknowledges funding from the Social Sciences and Humanities Research Council of Canada. The analysis was conducted at the Simon Fraser University Branch of the Canadian Research Data Centre Network (CRDCN), which is supported by the SSHRC, the CIHR, the CFI, Statistics Canada, and SFU. Helpful feedback and advice was provided by Lynn Prince Cooke, Beth Hirsh, Mohsen Javdani, Rima Wilkes, and Cristobal Young. Able research assistance was provided by Christina Trealeven and Natasha Stecy-Hildebrandt. © The Author 2017. Published by Oxford University Press on behalf of the University of North Carolina at Chapel Hill. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Social Forces Oxford University Press

Segregation across Workplaces and the Motherhood Wage Gap: Why Do Mothers Work in Low-Wage Establishments?

Social Forces , Volume Advance Article (4) – Dec 8, 2017

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Abstract

Abstract While maternal employment has become the norm in advanced industrial nations, gendered norms of parenting and employment disadvantage mothers in the labor force. This paper sheds new light on motherhood pay gaps by investigating the contribution of an understudied dynamic—mothers’ overrepresentation in low-paying workplaces. Estimating between- and within-establishment wage gaps with nationally representative Canadian linked employer-employee data reveals that segregation in low-paying establishments accounts for the bulk of mothers’ wage disadvantage relative to childless women. Pay gaps net of human capital differences are not chiefly a result of mothers’ lower wages vis-à-vis similar women in a given workplace, but rather stem from the fact that mothers are disproportionately employed in workplaces that pay all employees relatively poorly. Having identified the importance of between-establishment segregation, additional analyses probe support for two theories about underlying mechanisms: compensating differentials tied to family-supportive work contexts, and discrimination. While each plays a role, evidence is strongest for discrimination, with organizational characteristics that tend to reduce opportunities for discrimination also dramatically reducing or eliminating motherhood pay gaps. Introduction Across national contexts, gendered norms of parenting and employment work to mothers’ disadvantage (Aisenbrey, Evertsson, and Grunow 2009; Harkness and Waldfogel 2003; Viitanen 2014). While mothers typically earn lower wages than women without children, the reverse is true for fathers (Cooke 2014; Hodges and Budig 2010; Killewald 2012; Petersen, Penner, and Høgsnes 2014; Zhang 2009). Parenthood is thus an important factor underlying gendered inequalities in employment. A substantial body of research has investigated wage gaps between mothers and childless women, but the vast majority has drawn on individual-level survey data. Consequently, relatively little is known about the role of organizational context in shaping motherhood wage gaps. Drawing on linked employer-employee survey data from Canada, this paper investigates one key facet of mothers’ disadvantage—their segregation in lower-paying establishments—and how this is impacted by establishment variation in work arrangements, family benefits, and opportunities for discrimination against mothers. Establishments are important agents in generating patterns of wage inequality insofar as they set wage scales and contracts, make hiring decisions, and earn the revenues from which wages are paid (Baron and Bielby 1980; Bidwell et al. 2013; Sakamoto and Wang 2016). Establishments vary in the extent to which they can afford to offer workers higher or lower wages, as well as in the degree to which workers have the bargaining power to force their employers to share market rents. Much recent sociological theorizing and empirical work about organizational context and group-based inequalities has focused on factors impacting the distribution of wages within organizations, such as the bargaining power of internal constituencies, the height of internal hierarchies, informal workplace cultures, and organizational rules and regulatory mechanisms (e.g., Avent-Holt and Tomaksovic-Devey 2010, 2014; Baron et al. 2007; Tilly 1998). While generating many useful insights, research focusing solely on internal wage hierarchies neglects the potential importance of who works in particular organizations in the first place. Inequalities are generated not only via within-establishment wage differences, but also by virtue of how people are sorted across them. Establishments vary substantially in their overall wage rates, variation that cannot be explained entirely by the characteristics of their workers (Abowd, Kramarz, and Margolis 1999; Bronars and Famulari 1997; Lane, Salmon, and Spletzer 2007). Indeed, wages vary more across establishments than within them (Groshen 1991; Lane, Salmon, and Spletzer 2007). A number of recent studies demonstrate that wage gaps for disadvantaged groups arise in part through their segregation in establishments that, net of workers’ individual and occupational characteristics, tend to offer lower wages (Bayard et al. 2003; Drolet and Mumford 2012; Javdani 2015; Pendakur and Woodcock 2010; Petersen and Morgan 1995). Three point to the relevance of establishment sorting for motherhood wage differentials specifically, although they find it less important than within-establishment wage gaps (Beblo, Bender, and Wolf 2008; Petersen, Penner, and Høgsnes 2010, 2014). These latter studies, however, are not representative of the labor market as a whole and use data from countries (Germany and Norway) with extensive coordination and centralization of wage-setting, which tends to mute the potential role of establishment wage differentials for group wage gaps (OECD 2004; Simón 2010). Moreover, they do not explicitly investigate what it is about motherhood, jobs, and organizations that leads mothers to be disproportionately located in lower-waged establishments. In fact, inattention to the relationship between organization characteristics and between-establishment segregation is a general limitation of quantitative studies focusing on the role of such segregation for wage gaps between groups (e.g., Bayard et al. 2003; Drolet and Mumford 2012; Javdani 2015; Pendakur and Woodcock 2010). Extant research has documented its importance but has not explored its underlying mechanisms. This study extends existing research on establishment segregation and group wage gaps in two directions. First, I present the first decomposition of within- and between-establishment components of motherhood pay differentials using broadly representative North American data, Statistics Canada’s Workplace and Employee Survey (WES). Because wage setting in North America typically takes place at the establishment level, it is an important site for studying the role of establishment wage differentials for group wage gaps. Second, I take advantage of rich information on individual work arrangements and establishment-level characteristics in the WES to consider alternative theories on the mechanisms contributing to motherhood wage gaps tied to establishment segregation: mothers choose lower-wage employers to access more family-friendly jobs and organizations; or, hiring agents disproportionately shuts mothers out of higher-paying establishments where organizational constraints on discrimination are weak. Motherhood pay penalties and organizational segregation Scholarship on labor market inequalities is extensive. Driven in part by the predominance of individual-level data, sociologists and labor economists have largely built empirical models grounded in the human capital model of earnings determination whereby individual investments to raise productive capacity (education, training, on-the-job experience) translate into higher wages. While past research has suggested that lost human capital tied to employment breaks for caregiving contributes to motherhood pay gaps, human capital variables do not typically account for its entirety (Avellar and Smock 2003; Budig and England 2001; Zhang 2009). Rather than seeing wages as arising from an efficient labor market balancing individual skill and market demand, sociologists and organizational scholars often emphasize the social relations and structural features of organizations, as well as the broader environment in which they operate (Avent-Holt and Tomaskovic-Devey 2010; Kalev 2014; Stainback, Ratliff, and Roscigno 2011; Stainback, Tomaskovic-Devey, and Skaggs 2010). Moreover, feminist scholars of work and organization insist that organizational logics are enmeshed with broader societal contexts, notably gendered household dynamics. Such scholars point out critical disjunctures between assumptions often underlying the organization of work (a worker wholly available and devoted to work demands) and the imperatives of care (Acker 2006; Dodson 2013; Epstein et al. 2014; Kelly, Moen, and Tranby 2011; Stone and Hernandez 2013; Williams 2000). Drawing on these insights, the next section develops two arguments specifying how organizational contexts could shape mothers’ distribution across establishments, with consequences for motherhood wage gaps. The first focuses on possible trade-offs mothers might make to access organizations that offer better arrangements for combining employment and caregiving. The second shifts attention from mothers’ constrained choices to employer decisions. Here, the focus is on how organizational features impact the likelihood that bias against mothers will result in discrimination, blocking them from employment in better-paying establishments. Both of the arguments I develop lead to a scenario whereby mothers are disadvantaged via segregation in lower-paying establishments. What differs are the mechanisms leading to this outcome. Family (un)friendly jobs and organizations: compensating differentials The theory of compensating differentials posits that mothers trade higher earnings to accommodate caregiving (Becker 1993; Felfe 2012; Glauber 2012; Heywood, Siebert, and Wei 2007). While often couched in terms of individual choice, the necessity of such trade-offs rests on employment norms that presume a worker able to devote herself entirely to the organization (Acker 1990; Vosko 2009; Williams 2000). Constraints around the need to attend to dependent others challenge this ideal. While men increasingly engage in housework and childcare, mothers remain disproportionately responsible for caregiving and more often adapt their employment to accommodate it (Beaujot and Ravanera 2009; Marshall 2009; Raley, Bianchi, and Wang 2012). “Family-friendly” work conditions such as part-time hours and flexibility in where and when to work presumably ease conflict between care and employment (Anderson, Binder, and Krause 2003; Boushey 2008; Kelly, Moen, and Tranby 2011; Williams 2010). Overtime, conversely, can be unpredictable and difficult to reconcile with family schedules (Golden and Wiens-Tuers 2005). In Canada, almost 60 percent of hourly workers who work overtime have less than one day’s advance notice about overtime schedules (McCrate 2016). Not all researchers find that family-supportive work arrangements are associated with lower wages and/or motherhood pay gaps (Boushey 2008; Gariety and Shaffer 2001; McCrate 2005; Weeden 2005), but some link flexible hours, working at home, and part-time work to lower wages for at least some workers (Bardasi and Gornick 2008; Dau-Schmidt et al. 2009; Glass 2004; McGinnity and McManus 2007; Webber and Williams 2008). By contrast, employers typically pay overtime at a higher rate (at least for hourly workers). Compensating differentials do not necessarily imply a link to establishment wage-differentials, as individuals may make trade-offs within the context of different opportunities within an organization (past research typically does not distinguish at which level effects occur). However, the availability of particular work arrangements is often conditional on one’s employer (Haley-Lock 2011; Heywood, Siebert, and Wei 2007; Sweet et al. 2014). Canadian workers do not have the right to refuse overtime, and while some European countries provide statutory rights to adjust working hours with one’s employer, Canada does not. Even in Germany, where such a right exists, when women have children, switching job dimensions commonly entails employer changes (Felfe 2012). Shifting to a work arrangement more accommodating to caregiving demands may thus require changing employers. Mothers may also trade wages for a more generally amenable work culture (Fakih 2014). An organization that treats care demands as illegitimate and makes them difficult to reconcile with employment can push mothers to look elsewhere for work (Blair-Loy 2003; Herr and Wolfram 2012; Stone and Hernandez 2013). Work culture rests in part on everyday practices of managers and coworkers that are difficult to capture in large-scale datasets.1 However, organizational policies, such as generous provisions around parental leave and employer assistance with family-related matters, can signal an employer’s commitments to some degree.2 If mothers are most interested in accommodating employment to caregiving demands, and if employers need to offset associated costs (such as overhead associated with hiring more employees or problems with coordinating work) (Baughman, DiNardi, and Holtz-Eakin 2003; Fakih 2014; Heywood, Siebert, and Wei 2007),3 this could result in mothers’ segregation in lower-paying establishments. Low-wage employers may also offer part-time positions in particular to minimize worker wages and benefits (Lambert, Haley-Lock, and Henly 2012), which would also imply a link between motherhood penalties, part-time jobs, and lower wages at the establishment level. Opportunities for Discrimination The compensating differentials argument suggests that mothers actively select into organizations paying below-market wages to gain or retain family-supportive work. Organizational segregation could also result more directly from employer action. Efficiency wage theories posit that some firms pay above-market wages to attract the most productive workers, encourage retention, and discourage shirking (Akerlof 1982; Salop 1979; Shapiro and Stiglitz 1984). This matters for mothers in particular, insofar as motherhood negatively impacts assumptions of both competence and commitment, which are key criteria employers use when evaluating workers (Fuegen et al. 2004; Heilman and Okimoto 2008; Ridgeway and Correll 2004). Mothers may therefore face stronger barriers to employment at better-paying establishments concerned with retention and maximizing worker quality and effort. Although bias against mothers may affect decisions on pay and promotions for existing employees, discrimination should be particularly pronounced at the point of hire. It is easier to perceive and contest discrimination in an ongoing employment relationship (Petersen and Saporta 2004).4 Moreover, employers make hiring decisions with limited information, increasing the likelihood that they will base decisions on stereotypes. Notably, unlike gender and race, motherhood involves an identity transformation. Motherhood status is more obvious in the context of an existing employment relationship. Indeed, it may be impossible to discern from a resume, and may or may not come up in the context of a job interview via informal chitchat or employer or employee questions abound how job conditions would impact caregiving arrangements.5 However, the salience of motherhood as a frame for interpreting competence and commitment should be reduced when a woman already has a track record at her establishment. Conversely, being on the job market may be interpreted as a more negative signal for mothers, given the prevalence of stereotypes of them as less committed. Consistent with this, Fuller (2008) and Looze (2014) find that American mothers typically fail to realize the same wage gains with voluntary job changes as do other women, and Glass (2004) finds that mothers lower their wages with employer changes (none of these authors can determine whether this stems from lower wage offers or barriers to hire at better-paying establishments). While simply being on the job market may activate stereotypes about mothers, they should be particularly salient for those returning after parental leave. In this case, motherhood would not only be more visible (via a recent gap on the resume), but uncertainty about a woman’s commitment and how she will manage the responsibilities of employment and motherhood will be highest. This may help account for Fuller’s (2008) finding that “family-related” job changes result in substantial wage penalties for American women net of the impact of lost experience,6 and why returning to the same employer after maternity leave reduces mothers’ pay losses (Felfe 2012; Phipps, Burton, and Lethbridge 2001; Zhang 2010). It is not simply mothers’ positioning that may moderate discrimination. Organizational and institutional features such as legitimacy imperatives and formalization create differences in opportunities for discrimination (Petersen and Saporta 2004; Stainback, Tomaskovic-Devey, and Skaggs 2010). Human rights legislation prohibits family status discrimination in all Canadian provinces save New Brunswick. While this extends to all employers in theory, public-sector organizations face legitimacy concerns and legal environments that create a stronger impetus to be “fair” employers (DiMaggio and Powell 1983; Fuller 2005). The public sector is more subject to equity-enhancing policy, contributing to higher legal awareness of antidiscrimination imperatives (Wilson, Roscigno, and Huffman 2013). Historically, the public sector has provided more equitable employment outcomes for disadvantaged groups (Fuller 2005; Hou and Coulombe 2010; Waite and Denier 2015; Wilson, Roscigno, and Huffman 2013, 2015). There is less research on group-based wage gaps for other kinds of nonprofit organizations, and nonprofits can vary dramatically in their cultures and commitments. Nonetheless, the historic ties between many voluntary-sector organizations and social justice movements heighten attention to concerns with equality as well (Damman, Heyse, and Mills 2014; Mastracci and Herring 2010; Tomlinson and Schwabenland 2010). This may help counter rationales for discrimination against mothers that elevate business concerns above all else (see Byron and Roscigno (2014) for an analysis of this in pregnancy discrimination). Standardized procedures monitored by human resource professionals reduce supervisors’ discretion to incorporate personal biases (Baron et al. 2007; Dobbin 2009; Reskin and McBrier 2000). Collective bargaining imposes more formal rules around hiring as well (Elvira and Saporta 2001; Tomaskovic-Devey, Hällsten, and Avent-Holt 2015). Formalization should be particularly salient with respect to hiring discrimination against mothers insofar as motherhood is not obviously observable. Human resource professionals play a central role in interpreting how legal mandates should be incorporated in organizational practice (Dobbin 2009). In establishments with formalized hiring procedures monitored by professionals, hiring agents are more likely trained not to inquire about family status. In the UK, Adams et al. (2016) find that employers who did not provide training or other support to managers about pregnancy and maternity-related issues were more likely to espouse beliefs inconsistent with legal mandates (i.e., to believe that women should declare if they were pregnant during recruitment and that it is reasonable to ask prospective hires about their childbearing plans). Arguments about legitimacy imperatives and formalization thus imply that mothers will be less segregated in lower-paying establishments among the subset of establishments that are nonprofit/unionized/have formal HR. Data and Methods Data come from the WES, a mandatory linked employer-employee survey fielded by Statistics Canada from 1999 to 2005. Employees were followed for two years, and the employer sample was longitudinal, with the sample refreshed every second year. The target population was all Canadian establishments with paid employees, with the exception of public administration7 and employers in crop and animal production; fishing, hunting, and trapping; private households; and religious organizations. The employer sample was drawn from the Business Registrar, Statistics Canada’s monthly list of all businesses in the country. Establishments are defined as “the smallest organizational unit, comprised of at least one physical location that can provide a complete set of input and output statistics” and are the employer unit of analysis. The sampling frame was stratified by industry, region, and size. Data are representative of Canadian employers and workers outside the above-mentioned exclusions. The mandatory nature of the survey ensures high response rates (in excess of 80 percent). In each odd year, up to 24 employees were randomly sampled from each establishment8 and followed the next year regardless of whether they changed establishments. Analyses are restricted to odd-numbered years to ensure that outcomes reflect the characteristics of workers’ current establishment. I pool data across waves to maximize sample size. I restrict the main sample to women between 24 and 44 because the WES only reveals if women are currently living with children. Older women without resident children would include mothers whose children have left home. I exclude women who have no children under 18 but have older children residing with them. I truncate the sample at 24 because the WES does not reveal whether individuals are currently enrolled in school. This leaves 20,529 individual observations in 5,805 unique establishments. To establishment wage effects, I drop age and gender restrictions and employ the full WES sample of 85,320 individuals. Method Assessing the role of establishment segregation for motherhood wage gaps entails estimating the difference between economy-wide estimates and estimates within establishments. This reveals the extent to which the wage gap stems from how mothers are sorted across establishments. Petersen et al. (2011, 2014) use this approach to assess the contribution of establishment segregation to group wage gaps, and Pendakur and Woodcock (2010) provide a formal proof and associated tests of significance. An OLS regression of motherhood on log-hourly wages conditional on observed individual and job characteristics provides the economy-wide estimates: lnWageij=xijβ+momijδ+εij, (1) where lnWageij is the natural log of hourly wage for individual i in establishment j, xijβ indexes observed individual and job characteristics that affect wages, momijδ captures the impact of motherhood on wages, and εij is a stochastic mean-zero error term. Estimating the within-establishment wage gap requires removing the portion of the gap tied to establishment wage differentials. A challenge is the relatively few observations of women of childbearing age in each establishment (mean = 3.9). If, however, we assume that the establishment wage effect is common to all employees, we can use the entire WES sample to estimate establishment effects, which increases the average number of employees per establishment to 17 (up to a maximum of 79). Canay (2011) exploits the assumption of common wage effects to develop a two-step approach to fixed effects estimation for quantile regression. He shows that as long as fixed effects are the same across different quantiles, this removes the fixed effects and gives consistent estimates of slope parameters. I follow Javdani (2015) in applying Canay’s approach to the WES. I first regress log-hourly wages on the individual and job control variables and dummy variables for each establishment with the full sample. I include a dummy variable for sex in this equation as well, as it is estimated on the full WES sample, which includes both men and women: lnWageij=xijβ+femaleijδ+fijψ+εij, (2) where fij is a vector of indicators for each establishment that is equal to 1 if worker i is employed at firm j, and ψ is a vector of establishment wage effects (average wages conditional on worker and job characteristics). The establishment effects are saved and subtracted from each individual’s log-hourly wage to create a new dependent variable FElnWageij, which is purged of the impact of establishment-constant characteristics. The following equation gives the within-establishment motherhood penalty: FElnWageij=χijβ+Momijδ*+εij. (3) The between-establishment contribution to the wage gap is δˆ−δ˜, where δˆ is the OLS estimate of the motherhood penalty (δ) from equation (1) and δ˜ is the fixed effects estimate of the motherhood penalty (δ*) from equation (3). Hausman tests assess the significance of the contribution (Pendakur and Woodcock 2010). H=(δˆ−δ˜)2var[δ˜]−var[δˆ]~χ12 This approach rests on the assumption that the establishment-specific wage effect is a simple “location shift” in the wage distribution. Lane, Salmon, and Spletzer (2007) establish that establishment wage differentials are highly correlated across occupations in the United States, suggesting that this is generally a reasonable assumption. Nonetheless, if establishments that are high/low wage for men and/or older women do not reward women of childbearing age in the same way, results will be biased. To assess this, I repeat the above analysis estimating establishment-specific effects only for the main analytical sample (women between 25 and 44). There is a strong correlation between establishment wage effects calculated using all workers and those using only women between 25 and 44 (0.88). To further assess the sensitivity of results, I estimate baseline models with both sets of establishment fixed effects and with classic fixed effects equations (with stata’s xtreg command). Results (available on request) are virtually identical regardless of which method of calculating establishment fixed effects is employed. I use employee sample weights and estimate standard errors using 100 sets of bootstrap sample weights provided by Statistics Canada. This ensures that results are representative of the population and the standard errors are appropriately adjusted to account for the non-independence of error terms for workers within the same establishment, for the few workers who are sampled more than once across years, and the complex multistage survey design (Drolet 2002). Measures The wage variable used to assess motherhood pay gaps is the natural logarithm of total hourly wage. This includes not only base earnings but also overtime earnings, bonuses, profit sharing, tips, and so forth.9 The key independent variable indicates whether a woman is living with a child under 18.10 Robustness checks differentiate mothers according to whether children are school aged (≤6) or older and the number of children (1, 2, 3, or more). Measures used to assess arguments about compensating differentials include: part-time work (usual hours <30 hours per week); overtime work (a binary variable that is independent of usual hours of work); working flexible hours (able to vary start and stop times provided one works a set number of hours); whether one works from home for one’s employer some or all of the time and why (no work from home, job requirement, personal or family responsibilities, usual place of work, better conditions/save time, money, other); employer assistance with childcare; and employer-provided payments for parental leaves (these are “top-ups” to payments provided through the employment insurance system). With the exception of top-ups and assistance with childcare, these reflect individuals’ actual work arrangements. All are based on employee responses. It is important to measure individual use when possible rather than formal availability, insofar as workers are often hesitant to use work-life balance policies for fear they will be penalized for violating norms of workplace devotion (Blair-Loy and Wharton 2002; Duxbury and Gover 2011; Williams, Blair-Loy, and Berdahl 2013). Arguments about discrimination are only relevant for mothers who change employers after having children. To determine if this is the case, I compare the age of their oldest child to their tenure with their current employer. I also distinguish mothers who started working for their current employer after a period out of the labor force where they were primarily engaged in caregiving. The WES asks workers who changed employers within the past five years what their prior main activity was. Mothers who answered they were “Working at home, raising family, etc.,” were coded as returning after a leave. Note that while the sampling frame of the WES is establishments, tenure refers to employers, so changing between establishments of the same employer after having children would not be counted as having changed employers. I test arguments about the opportunity structure for discrimination by interacting motherhood with two indicators of formalization: whether the job is covered by a collective bargain and whether the establishment has a human resources department. This is correlated with establishment size (although the relationship is far from perfect), so I include an interaction with size as a control. To assess the impact of the organizational field, I test an interaction between motherhood and nonprofit status. Nonprofit organizations include non-governmental organizations as well as those in the broader public sector, such as schools, hospitals, and public (“crown”) corporations. Unfortunately, the WES does not have an indicator for public/private status. Note that this is not testing whether mothers are more likely to be employed in workplaces with these characteristics per se. There may be reasons other than discrimination that would explain why mothers would be more or less likely to work in organizations with these characteristics, and unionized establishments and those that can afford on-site formalized HR tend to offer higher rather than lower wages. Indeed, simply adding indicators of nonprofit status, unionization, and the presence of formal HR to the models without firm effects does not reduce estimates of motherhood pay differentials. Rather, it is the interaction between motherhood and opportunities for discrimination that matters. The focus is on differences in the degree of mothers’ segregation in lower-wage establishments among the subset of organizations that have versus lack the relevant characteristic. All models include controls for individual and some job-level characteristics relevant to wage-setting: age and its square, seniority with current employer and its square, quintic terms for years of full-time (actual) experience, education (less than high school; high school graduate; non-university postsecondary certificate; undergraduate degree holder; and advanced degree), a combined indicator of racialization and immigration status (white Canadian-born; white immigrant; visible minority11 Canadian-born; visible minority immigrant; and Aboriginal), co-resident spouse (married or common-law), occupation (managers; professionals; sales and service; clerical/administrative; trades/technicians; production workers with no trade certification, operation and maintenance), job covered by collective bargain, and survey year. Models used to estimate establishment fixed effects include all controls and a dummy for sex. A variety of establishment-level characteristics predict establishment-wage differentials (such as industry, size, age, and profitability) (Groshen 1991; Lane, Salmon, and Spletzer 2007). However, there is no particular reason to expect them to be associated with mothers’ sorting across establishments per se, so they are not included as controls in main models. This is in accordance with standard practice in the broader literature on establishment wage effects that defines them as net of individual and job characteristics. Additional analysis (available on request) found no evidence that industry, size, competitive context, profitability (among the subset of for-profit firms), or business strategy (importance of reducing labor costs, increasing employee skills, increasing employee participation, or improving performance) was linked to mothers’ segregation in lower-paying establishments. Descriptive statistics are presented in table 1. Table 1. Means and Proportions of Key Variables by Motherhood Status and Mobility No children Mother All mothers No employer change Employer change after care break Other employer change Part-time 0.183 0.325 0.276 0.523 0.332 Work overtime 0.444 0.356 0.394 0.233 0.347 Flexible hours 0.349 0.352 0.334 0.300 0.367 Work from home  No work from home 0.753 0.755 0.718 0.832 0.768  Job requirement 0.159 0.161 0.189 0.106 0.152  Personal/family responsibilities 0.007 0.029 0.035 0.028 0.026  Usual place of work 0.004 0.006 0.005 0.008 0.006  Better conditions 0.051 0.027 0.028 0.017 0.027  Other 0.025 0.022 0.026 0.009 0.022 Top-ups to leave payments 0.394 0.324 0.407 0.244 0.285 Employer assistance with childcare 0.076 0.067 0.103 0.048 0.049 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Age 33.4 36.9 36.2 36.2 37.4 Race/Immigration  White, Canadian-born 0.786 0.794 0.830 0.770 0.777  Visible minority, Canadian-born 0.040 0.018 0.023 0.010 0.017  Aboriginal 0.019 0.017 0.013 0.021 0.019  White immigrant 0.076 0.076 0.072 0.088 0.076  Visible minority immigrant 0.079 0.094 0.061 0.112 0.110 Spouse 0.527 0.822 0.890 0.828 0.785 Education  <High school 0.279 0.349 0.298 0.454 0.366  High school graduate 0.040 0.072 0.048 0.102 0.082  Postsecondary diploma 0.369 0.398 0.408 0.337 0.399  Bachelor’s 0.259 0.153 0.211 0.085 0.128  Postgraduate 0.053 0.028 0.035 0.022 0.025 Experience 11.210 13.403 13.984 9.810 13.419 Seniority 5.823 6.966 12.233 2.293 4.537 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Proportion of sample 0.413 0.587 0.195 0.033 0.359 Proportion of mothers 0.332 0.056 0.612 No children Mother All mothers No employer change Employer change after care break Other employer change Part-time 0.183 0.325 0.276 0.523 0.332 Work overtime 0.444 0.356 0.394 0.233 0.347 Flexible hours 0.349 0.352 0.334 0.300 0.367 Work from home  No work from home 0.753 0.755 0.718 0.832 0.768  Job requirement 0.159 0.161 0.189 0.106 0.152  Personal/family responsibilities 0.007 0.029 0.035 0.028 0.026  Usual place of work 0.004 0.006 0.005 0.008 0.006  Better conditions 0.051 0.027 0.028 0.017 0.027  Other 0.025 0.022 0.026 0.009 0.022 Top-ups to leave payments 0.394 0.324 0.407 0.244 0.285 Employer assistance with childcare 0.076 0.067 0.103 0.048 0.049 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Age 33.4 36.9 36.2 36.2 37.4 Race/Immigration  White, Canadian-born 0.786 0.794 0.830 0.770 0.777  Visible minority, Canadian-born 0.040 0.018 0.023 0.010 0.017  Aboriginal 0.019 0.017 0.013 0.021 0.019  White immigrant 0.076 0.076 0.072 0.088 0.076  Visible minority immigrant 0.079 0.094 0.061 0.112 0.110 Spouse 0.527 0.822 0.890 0.828 0.785 Education  <High school 0.279 0.349 0.298 0.454 0.366  High school graduate 0.040 0.072 0.048 0.102 0.082  Postsecondary diploma 0.369 0.398 0.408 0.337 0.399  Bachelor’s 0.259 0.153 0.211 0.085 0.128  Postgraduate 0.053 0.028 0.035 0.022 0.025 Experience 11.210 13.403 13.984 9.810 13.419 Seniority 5.823 6.966 12.233 2.293 4.537 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Proportion of sample 0.413 0.587 0.195 0.033 0.359 Proportion of mothers 0.332 0.056 0.612 Table 1. Means and Proportions of Key Variables by Motherhood Status and Mobility No children Mother All mothers No employer change Employer change after care break Other employer change Part-time 0.183 0.325 0.276 0.523 0.332 Work overtime 0.444 0.356 0.394 0.233 0.347 Flexible hours 0.349 0.352 0.334 0.300 0.367 Work from home  No work from home 0.753 0.755 0.718 0.832 0.768  Job requirement 0.159 0.161 0.189 0.106 0.152  Personal/family responsibilities 0.007 0.029 0.035 0.028 0.026  Usual place of work 0.004 0.006 0.005 0.008 0.006  Better conditions 0.051 0.027 0.028 0.017 0.027  Other 0.025 0.022 0.026 0.009 0.022 Top-ups to leave payments 0.394 0.324 0.407 0.244 0.285 Employer assistance with childcare 0.076 0.067 0.103 0.048 0.049 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Age 33.4 36.9 36.2 36.2 37.4 Race/Immigration  White, Canadian-born 0.786 0.794 0.830 0.770 0.777  Visible minority, Canadian-born 0.040 0.018 0.023 0.010 0.017  Aboriginal 0.019 0.017 0.013 0.021 0.019  White immigrant 0.076 0.076 0.072 0.088 0.076  Visible minority immigrant 0.079 0.094 0.061 0.112 0.110 Spouse 0.527 0.822 0.890 0.828 0.785 Education  <High school 0.279 0.349 0.298 0.454 0.366  High school graduate 0.040 0.072 0.048 0.102 0.082  Postsecondary diploma 0.369 0.398 0.408 0.337 0.399  Bachelor’s 0.259 0.153 0.211 0.085 0.128  Postgraduate 0.053 0.028 0.035 0.022 0.025 Experience 11.210 13.403 13.984 9.810 13.419 Seniority 5.823 6.966 12.233 2.293 4.537 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Proportion of sample 0.413 0.587 0.195 0.033 0.359 Proportion of mothers 0.332 0.056 0.612 No children Mother All mothers No employer change Employer change after care break Other employer change Part-time 0.183 0.325 0.276 0.523 0.332 Work overtime 0.444 0.356 0.394 0.233 0.347 Flexible hours 0.349 0.352 0.334 0.300 0.367 Work from home  No work from home 0.753 0.755 0.718 0.832 0.768  Job requirement 0.159 0.161 0.189 0.106 0.152  Personal/family responsibilities 0.007 0.029 0.035 0.028 0.026  Usual place of work 0.004 0.006 0.005 0.008 0.006  Better conditions 0.051 0.027 0.028 0.017 0.027  Other 0.025 0.022 0.026 0.009 0.022 Top-ups to leave payments 0.394 0.324 0.407 0.244 0.285 Employer assistance with childcare 0.076 0.067 0.103 0.048 0.049 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Age 33.4 36.9 36.2 36.2 37.4 Race/Immigration  White, Canadian-born 0.786 0.794 0.830 0.770 0.777  Visible minority, Canadian-born 0.040 0.018 0.023 0.010 0.017  Aboriginal 0.019 0.017 0.013 0.021 0.019  White immigrant 0.076 0.076 0.072 0.088 0.076  Visible minority immigrant 0.079 0.094 0.061 0.112 0.110 Spouse 0.527 0.822 0.890 0.828 0.785 Education  <High school 0.279 0.349 0.298 0.454 0.366  High school graduate 0.040 0.072 0.048 0.102 0.082  Postsecondary diploma 0.369 0.398 0.408 0.337 0.399  Bachelor’s 0.259 0.153 0.211 0.085 0.128  Postgraduate 0.053 0.028 0.035 0.022 0.025 Experience 11.210 13.403 13.984 9.810 13.419 Seniority 5.823 6.966 12.233 2.293 4.537 Occupation  Managers 0.106 0.098 0.117 0.054 0.093  Professionals 0.229 0.204 0.260 0.092 0.183  Sales 0.087 0.103 0.049 0.209 0.123  Clerical/Administrative 0.206 0.221 0.210 0.241 0.225  Technical/Trades 0.327 0.328 0.326 0.331 0.329  Production workers 0.045 0.046 0.039 0.074 0.047 Union 0.216 0.254 0.332 0.195 0.218 Proportion of sample 0.413 0.587 0.195 0.033 0.359 Proportion of mothers 0.332 0.056 0.612 There are a number of limitations to note. Although the WES follows individuals for two years, this is too short to compare women pre- and post-motherhoood. However, Canadian panel data does not reveal evidence that mothers typically earn lower wages than other women in the years before childbirth (Zhang 2009, 2010). Another limitation is that only those currently employed or on leave are observed. While Canadian mothers have high employment rates,12 they are lower than for childless women (Zhang 2007). Employed mothers may be positively selected, with mothers with better earnings prospects more likely to return to the workforce after having children. If lower employment rates for mothers imply a higher reservation wage, estimates of wage penalties will be conservative, insofar as mothers may disproportionately choose non-employment over jobs in low-wage establishments. Results Within- versus between-establishment wage gaps Regressing motherhood on establishment wage effects (calculated from equation (2)) reveals a significant negative coefficient of 0.075. An establishment with 25 percent mothers would thus pay 3.9 percent lower wages than one with 75 percent mothers. How important is this pattern of segregation for motherhood wage gaps overall? The first bar in figure 1 graphically depicts the contribution of between-establishment segregation to the aggregate motherhood wage gap. The overall bar represents the estimated economy-wide motherhood wage gap (in percentage terms) net of controls, which is, in turn, subdivided into within-establishment and between-establishment components. The statistical significance of the components within the stacked bar is indicated with stars to the right. Full results are in model 1 of appendix table A.1. Figure 1 reveals that the aggregate motherhood wage gap is almost entirely due to the between-establishment effect. Segregation in establishments that pay lower wages net of worker characteristics lowers mothers’ wages by around 3 percent across the board. The within- establishment wage gap is much smaller and not significant. Figure 1. View largeDownload slide Motherhood wage gap (%) with and without controls for family-supportive work context Figure 1. View largeDownload slide Motherhood wage gap (%) with and without controls for family-supportive work context Family (un)friendly jobs and organizations: compensating differentials While the importance of establishment segregation for motherhood pay gaps is clear, the first specifications do not reveal what is driving them. The descriptive statistics in table 1 reveal that mothers work part-time more often and overtime less often than childless women. They are more likely to work from home for family-related reasons, but not overall, and there is no difference in flexible working hours. Mothers are actually less likely to work in establishments that offer top-ups to employment insurance (which provides maternity and parental benefits in Canada) and assistance with childcare. This suggests that variation in working hours has the greatest potential to contribute to motherhood pay gaps, although other work characteristics may matter once estimations control for other differences between mothers and childless women. To formally test the compensating differentials argument, I add measures of part-time work, overtime, flexible hours, working from home, employer-provided assistance with childcare, and access to employer top-up payments for maternity/parental leave. The second bar in figure 1 presents estimates from this model. Full results are in model 2 of appendix table A.1. There is a significant reduction in the between-establishment effect to 2 percent with the addition of the family-supportive measures. This suggests that mothers are paying a price for a more family-friendly context, but it is not the major source of their lower wages. This trade-off is solely tied to establishment segregation. There is no change in the estimate of the within-firm motherhood wage gap with the addition of the family-supportive variables. To assess specific variables’ relative contribution, additional models drop one focal term from the full model (results in table O.1 of the online supplement). Flexible hours and assistance with childcare have no discernable impact on the sorting penalty, and mothers’ greater likelihood of working from home to fulfill personal or family responsibilities actually offsets the motherhood penalty, since this is associated with employment in a higher-wage establishment. Top-up payments for maternity/parental leave do help explain the motherhood penalty, but not in a way consistent with the logic of competing differentials (they are associated with higher-wage establishments, and mothers are less likely to have access to them). In fact, the only results that are consistent with the compensating differentials argument are those associated with part-time and overtime work. Dropping these terms shifts the motherhood penalty associated with establishment segregation in the expected direction. Of the two, it is part-time work that has the biggest impact. Most employed mothers in Canada work full-time, but part-time work is common across the educational spectrum (a little less so for the least and most educated, 33–34 percent of mothers who are high school graduates, have a postsecondary diploma, or a bachelor’s degree work part-time, versus 27 percent of those without high school diplomas and 26 percent of those with postgraduate degrees). However, working part-time might have different implications for employer segregation for salaried workers than for women in lower-level jobs paid by the hour. To further assess whether all types of part-time work imply wage trade-offs, additional models distinguish hourly part-time jobs from those held by salaried workers. Results (available on request) reveal that only the former is associated with employment in lower-waged establishments. Mothers with the greatest care demands should be most willing to trade wages for accommodating work. As a robustness check, I re-estimated the above models disaggregating mothers by number of children and age of youngest child (see figure 1 and table A.1). While accounting for family-supportive employment reduces between-establishment motherhood wage gap regardless of the number of children, the drop is largest in percentage terms and only significant for those with two. In particular, both overtime and, especially, part-time work play a much larger role for mothers of two than for those with singletons (see table O.2 in the online supplement for details). Interestingly, mothers of two face the smallest between-establishment wage gap overall, while the gap is most pronounced among those with one child. Figure 1 also reveals that family-un/friendly work characteristics contribute more to the between-establishment motherhood wage gap for those with younger children (largely because of the greater incidence of part-time work). However, the overall between-establishment wage gap is larger for mothers with older children. On balance, mothers with stronger care demands do appear to accept greater wage losses to access accommodating work. However, effects are relatively minor, and a significant between-establishment wage gap remains in all cases. Moreover, the between-establishment wage gap is not greatest for mothers with the most demanding care obligations (see online supplement table O.3 for detailed results). A larger segregation-related wage gap for mothers of singletons is not consistent with the logic of compensating differentials. It may reflect processes of differential selection whereby mothers with more children face stronger pressures to leave the labor force. Those who remain may have unmeasured employment and/or family supports that make combining motherhood and employment easier. It is also possible that employers may be more hesitant to hire mothers of singletons because they presume they will have another child (and that this will be disruptive), whereas women with more children are more likely to have achieved their final family size. Discrimination Hiring discrimination should only affect between-establishment wage gaps for mothers who are no longer working for their pre-childbirth employer and should be strongest for those changing after a recent caregiving leave. The descriptive statistics in table 1 reveal that employer continuity is much less common for single mothers relative to their married counterparts, and also for aboriginal and immigrant mothers relative to white Canadian-born women. Women with a high school degree or less are overrepresented among those changing employers after childbirth, while the reverse is true for more educated women (with educational differences most pronounced among those starting with their employer after a care break). Managers and professionals are underrepresented among both types of employer-changers, but particularly among those who took a care break. Mothers working in sales are most overrepresented among those who took such a break and underrepresented among those with employer continuity (clerical/administrative and technical/trades workers are fairly evenly represented among the mobility groups). Figure 2 depicts wage gaps separately for mothers with the three patterns of im/mobility. Note that as with prior models, controls are included for demographic and job characteristics, so results are not a function of the differences among mothers following the three mobility patterns outlined above. Full results are in model 1 of appendix table A.2. Figure 2. View largeDownload slide Motherhood wage gap (%) by post-birth employer change Figure 2. View largeDownload slide Motherhood wage gap (%) by post-birth employer change Results are broadly consistent with a discrimination story—only mothers who change employers after childbirth work in lower-paying establishments, and this is most pronounced for those who entered their current job after a recent caregiving break. Mothers who remain with their pre-childbirth employer earn higher wages both within and across establishments, but women who change employers after a caregiving leave face a −7.1 percent between-establishment penalty. Because the models control for experience and tenure, lost human capital is not the only factor hurting mothers who fail to return to the same employer after childbirth. Such women also suffer a within-establishment motherhood penalty, although it is smaller. There is a substantial but smaller (−3.5 percent) between-establishment wage gap for other women who changed employers after having children. These women also face a within-establishment penalty, but again it is much smaller than the between-establishment wage gap. But do organizational contexts that should reduce opportunities for discrimination mitigate the wage gap arising by virtue of establishment segregation? To assess this, I add interactions between the motherhood measure that accounts for mobility (mother still working for the same employer, mother who started working with her current employer after a care break, and mother who changed employer after childbirth) and indicators of formalization (unionization and dedicated HR in the establishment), and sensitivity to legitimacy concerns around fairness (nonprofit status). I include all interactions jointly to isolate impacts net of other factors, and report average marginal effects in the figures. Because only mothers who change employers face between-establishment wage gaps, I focus interpretation on them. Full model results are in model 2 of appendix table A.2. Consistent with expectations, formalization weakens between-establishment wage gaps. In non-unionized contexts, mothers who change employers after a caregiving break face a −7 percent between-establishment penalty (see figure 3). Among women whose jobs are covered by a collective bargain, however, this drops to −0.7 percent. The penalty also falls with unionization for other mothers who have changed employers, although the difference is not as dramatic (−1.5 percent with unionization versus −3.8 percent without). Figure 3. View largeDownload slide Motherhood wage gap (%) by union and post-birth employer change, mothers no longer working for pre-birth employer Figure 3. View largeDownload slide Motherhood wage gap (%) by union and post-birth employer change, mothers no longer working for pre-birth employer Segregation in lower-paying establishments is much less pronounced among mothers working for employers with on-site human resource professionals than it is among those working in establishments without them (figure 4). For mothers changing employers after a care break working in establishments without HR professionals, there is a −7.4 percent motherhood wage gap attributable to between-establishment segregation. There is no significant between-establishment wage gap among similar mothers working where HR professionals are present. For those who changed jobs for other reasons, the wage gap drops from −4.1 percent among those working for employers without HR, to a negligible −0.8 percent among those working in establishments where it is present. Figure 4. View largeDownload slide Motherhood wage gap (%) by HR and post-birth employer change, mothers no longer working for pre-birth employer Figure 4. View largeDownload slide Motherhood wage gap (%) by HR and post-birth employer change, mothers no longer working for pre-birth employer Figure 5 presents results related to nonprofit status. Segregation in lower-paying establishments is pronounced among mothers who have changed employers and work in for-profit establishments—there is a −6.4 percent between-establishment wage gap for mothers who changed employers after a care break, and a −4.1 percent gap for those who changed for other reasons. There are significant, albeit smaller, within-establishment penalties. Among women in the nonprofit sector, however, wage gaps due to segregation in lower-paying establishments are much smaller (−1.2 percent) for women who have changed employers after a leave and absent altogether for other mothers who found new jobs after becoming mothers. Figure 5. View largeDownload slide Motherhood wage gap (%) by nonprofit and post-birth employer change, mothers no longer working for pre-birth employer Figure 5. View largeDownload slide Motherhood wage gap (%) by nonprofit and post-birth employer change, mothers no longer working for pre-birth employer Discussion and conclusions Much research has documented the wage penalty women experience if they have children. However, there has been little clarity about whether this results from mothers earning less than childless women in the same establishment, or because mothers are more likely to work in establishments that pay below-market wages. I find that the latter is most important in Canada, with mothers’ segregation into lower-paying establishments accounting for 97 percent of the net aggregate motherhood wage gap. Mothers who change employers after having children do face within-establishment penalties, but they are smaller than those due to establishment segregation. Beyond assessing the importance of establishment segregation for motherhood wage gaps, a goal of the paper was to investigate how this might stem from and be conditioned by organizational context. A substantial literature has focused on organizational family policy and the integration of employment and caregiving (Boushey 2008; Kelly, Moen, and Tranby 2011; Williams 2010; Williams, Blair-Loy, and Berdahl 2013), although how this intersects with establishment segregation has not been investigated. The compensating-differentials argument that mothers accept wage penalties to work in more family-friendly establishments received some support, especially for those with more demanding caregiving obligations. In particular, part-time work, which is more common in lower-waged establishments, helps explain the between-establishment wage gap, as does mothers’ lower likelihood of working overtime to a lesser degree. Although the analysis did not investigate class differences among mothers, the fact that only hourly part-time work was associated with lower-paying establishments suggests that less advantaged mothers bear the brunt of the wage penalty associated with compensating differentials. The European Community Directive on Part-Time Work (97/81/EC) encourages member countries to promote opportunities for workers to adjust working hours (Fahlén 2013). The Liberal government elected in Canada in 2015 promised to introduce such rights for workers subject to Federal Employment Standards.13 If implemented, this should reduce the need for workers to change employers to access more family-supportive working hours. However, even after accounting for the role of part-time work and overtime, the bulk of the between-establishment motherhood wage gap remains unexplained. Government policy giving workers the right to adjust work hours, refuse overtime, and discourage its excessive use may improve work-life integration, but it would not have a major impact on mothers’ wage disadvantage in Canada. On balance, demand-side forces linked to employer discrimination appear to play a stronger role in sorting women into lower-waged establishments than does mothers’ search for a more amenable work context. Results suggest that changing employers after becoming a mother provides a context where motherhood becomes salient and disadvantageous, channeling them into poorer-paying establishments. Results thus complement experimental and audit research that provides direct evidence of discrimination against mothers, albeit in specific and limited scenarios (Correll, Benard, and Paik 2007). Negative establishment sorting is particularly strong for mothers re-entering the labor market after a care leave, highlighting the importance of policy frameworks that protect mothers’ attachment to their employers after childbirth. This is not, however, the only time mothers change employers. Indeed, inter-firm mobility is an increasingly important part of workers’ career trajectories in the context of patterns of firm restructuring that have eroded internal labor markets (Cappelli 1999; Hollister 2011; Kalleberg 2013; Kronberg 2013). There are a number of important caveats to note. Restrictions in the sample’s age range likely result in conservative estimates of motherhood penalties. Repeating key analyses without the lower-bound age restriction (tables available on request) increases the overall size of the motherhood penalty by approximately 1 percent and slightly increases the relative importance of the within-establishment component. This is entirely a function of more disadvantageous mobility patterns for younger mothers. Analyses that account for differences in such patterns are virtually identical whether or not the lower age bound is relaxed, suggesting that the exclusion of young women has little substantive impact on the key findings. The likelihood that older women will have had children who have left home prevented me from including them in the analysis, as the WES cannot identify mothers without resident children. The larger between-establishment wage gap for mothers of older children suggests a pattern of cumulating disadvantage that could lead to an understatement of the motherhood wage gap given the restricted age range in the study. Without data on non-resident children, however, this cannot be directly assessed. More centrally, it is important to remember that the data and research design do not directly test discrimination. Further, we cannot know if mothers who changed employers were already working in lower-waged establishments prior to having children. Indeed, this may have motivated them to look for a new employer. We also cannot rule out the possibility that mothers who change employers have unobserved characteristics that would hinder them in the labor market generally, or that extra-organizational constraints on geographic mobility make it more difficult for mothers to make wage gains when they change employers. Unmeasured employment amenities, such as the degree of coworker or supervisor support, may also shape mothers’ mobility decisions, motivating them to accept employment in lower-waged establishments. In supplementary analyses, I compared pay gaps for mothers who found jobs via an insider referral and others, since a connection in the organization can provide information about how family-supportive supervisors are in practice. There is a larger penalty associated with working in lower-paying establishments among mothers who learned of their job from friends or family, but the difference is not dramatic (4.2 percent versus 2.8 percent). There is no generalized wage penalty associated with insider referrals. Moreover, while unmeasured employment amenities may help explain the residual motherhood penalty that remains in some estimations, there is little reason to believe that variation in their availability across establishments would be substantial where organizations are for-profit and lack HR departments or collective agreements, but largely absent otherwise. They are thus unlikely to impact the findings with respect to opportunities for discrimination. Indeed, none of these alternative explanations would logically lead to the dramatic and systematic variation in the presence and strength of between-establishment wage gaps that we see with collective bargaining, human resource professionals, and nonprofit status. Overall wage variation across establishments is smaller among nonprofits versus for-profit firms, for those with HR departments than among those without, and for those where jobs are typically unionized versus those without collective bargaining coverage (variance estimates available on request). This would tend to reduce the scope for inter-establishment wage differentials to impact group wage differences in these contexts, and could contribute to the smaller role of establishment segregation for motherhood wage gaps within them. However, substantial establishment wage variation remains among nonprofit establishments and those with HR professionals and collective bargaining. The fact that these institutional features often wiped out segregation penalties altogether implies that reduced wage variance is not solely driving results. Indeed, organizational features that should influence opportunities for discrimination have dramatic effects. Formalization substantially reduces the pay gap associated with mothers’ segregation in lower-paying establishments, especially human resource professionals. This highlights the importance not just of legislation to protect mothers against discrimination (which exists in Canada), but of organizational practices and oversight that ensure decision-makers are not only aware of such prohibitions but act accordingly. I also argued that the nonprofit sector faces legitimacy pressures that should act as a brake on discrimination. Consistent with this, wage gaps attributable to segregation in lower-paying establishments are only evident in the for-profit sector. This study thus underscores the importance of organizational characteristics in shaping mothers’ disadvantage. While past research has explored differences tied to mothers’ own characteristics and those of the countries in which they live, scholars have not systematically studied variation across organizations with nationally representative data. Insofar as organizational context has been theorized as important, it has typically been the “family-friendliness” of work cultures and their promotion of ideal worker norms presumed in conflict with motherhood that garner the most attention (e.g., Blair-Loy 2003; Stone and Hernandez 2013). While such organizational norms are no doubt an important reason why motherhood is salient with respect to hiring in the first place, this study suggests that the difficult job of attempting to shift such norms is not the only avenue to pursue to reduce mothers’ disadvantage. The combination of legal prohibition against family status discrimination and greater oversight and formalization of hiring can also be effective. Because the type of data available in the WES and other surveys cannot provide direct evidence of discrimination, audit studies would be useful to test whether organizational features identified as meaningful reduce hiring discrimination against mothers. More research is also needed to explore how wage gaps tied to employer segregation might vary among mothers. Past research illustrates that motherhood penalties vary considerably along dimensions such as occupation, education, and earnings levels (Anderson, Binder, and Krause 2002; Cooke 2014; Wilde, Batchelder, and Ellwood 2010; Zhang 2009). I find that disadvantage is concentrated among women who have changed employers after childbirth, a pattern that is more common in the WES for less advantaged women: single mothers, immigrants, less educated women, and those working in lower-level jobs. Results thus suggest that differences in exposure to discrimination tied to varying mobility patterns may contribute to stronger motherhood penalties for disadvantaged groups. At the same time, it is possible that characteristics that contribute to mothers’ segregation in lower-paying establishments at the aggregate level matter more for some mothers than others. While preliminary analyses suggest that accounting for variation in effects by education or occupation does not dramatically alter results, a more focused investigation of how motherhood penalties vary within and across establishments for women with different labor market opportunities would be valuable. The role of national context in shaping mothers’ segregation in lower-waged establishments is beyond the scope of this paper, and findings for Canada may not map exactly to those in other countries. Indeed, there is considerable variation in motherhood penalties across countries, and I find segregation in lower-paying establishments much more important for motherhood wage gaps than Petersen, Penner, and Høgsnes (2014) find for Norway, where it accounts for only 14–31 percent of the total motherhood wage gap (depending on time period and number of children). I also only find wage gaps tied to segregation in lower-wage firms for women who are no longer working for their pre-childbirth employer. This is different from what Beblo, Bender, and Wolf (2008) find for West Germany, where mothers who return to the same employer after childbirth are employed in lower-wage establishments. These differences may reflect the greater representativeness of my data rather than country-level differences. More likely, they are tied to the overall greater inter-establishment variability in wages that occurs in countries, like Canada, with more decentralized wage bargaining. In addition, Norway, Germany, and Canada vary across a number of potentially relevant policy dimensions. Petersen, Penner, and Høgsnes (2014) detail how Norway evolved to be an exemplar of gender egalitarian and family-supportive employment. Notwithstanding recent policy changes, Germany has a history of strong support for a traditional male breadwinner family structure with a caregiving mother working at most part-time when children are older (Cooke 2011). Canada stands in the middle. The length of paid leave available after childbirth is very close to the OECD average (OECD 2017a), and in 2011 public spending on pre-primary education and childcare ranked 15 out of the OECD 25 (OECD 2013). Budig, Misra, and Boeckmann (2016) find that government support for childcare and length of leave help explain differences in the magnitude of motherhood wage penalties cross-nationally, and they are also likely relevant to the variability of employment conditions across establishments. In the United States, where long work hours are particularly pronounced and statutory entitlements to care leaves are so meager, organizational family policy may prove more important, while the lack of legal protection against discrimination against mothers may make formalization less so. Exploring variation in the degree to which establishment segregation shapes motherhood wage gaps and in its underlying mechanisms across national contexts is an important avenue for future research. Notes 1 Heywood, Siebert, and Wei (2007) find that employees report higher availability of family-supportive practices than establishment representatives, which likely reflects managerial discretion. 2 Neo-institutional scholars argue that firms may adopt practices to enhance legitimacy without a real commitment (Edelman, Uggen, and Erlanger 1999; Kelly and Dobbin 1998; Stinchcombe 2001). 3 While the theory of compensating differentials posits a positive relationship between wages and poor working conditions, empirical support is mixed (Gunderson and Hyatt 2001; Heywood, Siebert, and Wei 2007; Johnson and Provan 1996). Moreover, practices and policies that enhance work-life balance can enhance productivity, reducing the need to offset their costs with lower wages (Gariety and Shaffer 2001; Glass 2004; Golden, Henly, and Lambert 2013; Johnson and Provan 1996). They are more often present where recruitment and retention of high-performing workers is a priority, and where wages are relatively high (Bloom, Kretschmer, and Van Reenan 2009; Brescoll, Glass, and Sedlovskaya 2013; Winder 2009). In seeking employers who allow flexible hours and working from home and provide family-supportive benefits, mothers may select into higher-paying workplaces, actually offsetting their wage disadvantage. 4 As part of research for another paper, my co-authors and I reviewed every case alleging family status discrimination filed with Canadian Human Rights Tribunals. Only a few alleged discrimination at the point of hire, and none were successful. 5 There is no direct Canadian evidence about the prevalence of employer inquiries or employee disclosures of motherhood status in job interviews. However, a recent UK report finds that only three in 10 employers provided guidelines about employment law to those involved in recruitment, and that a substantial share of employers believed that behavior contradictory to legal mandates against family status discrimination were legitimate (Adams et al. 2016). Crowley (2013) also reports instances of American mothers being asked about how they would handle childcare responsibilities in hiring interviews. 6 Job changes after non-employment are associated with lower wages in part because workers have no fallback position (Keith and McWilliams 1997). However, Fuller (2008) found that, all else equal, the losses associated with family-related quits were larger than for layoffs. 7 Public administration involves the enactment and interpretation of laws and regulations, and the administration of programs based on them (Industry Canada, http://www.ic.gc.ca/cis-sic/cis-sic.nsf/IDE/cis-sic91defe.html). Excluded are key components of the “broader” public sector including health and educational institutions. Public Administration’s share of employment in Canada is 6.5 percent (Statistics Canada 2017). 8 Sample size was proportional to the size of establishment, except in cases with less than four employees, where all were sampled. 9 WES respondents can report different bases of pay, which Statistics Canada converts to an hourly wage rate based on usual weekly hours and weeks and months worked per year. 10 It is not possible to distinguish biological from stepchildren or non-motherhood-type relationships. 11 I use “visible minority” as an descriptor for processes of racialization, as it is the term used by Statistics Canada and prescribed by federal employment equity legislation. StatCan defines “visible minority” as “persons who are non-Caucasian in race or non-white in color and who do not report being Aboriginal.” It includes, for example, people who indicate being of Chinese, South Asian, Black, Latin American, and Arab descent. It does not include those who indicate “White” or “European” along with a response that would otherwise indicate visible minority status (e.g., “White” and “Latin American”). 12 Currently 8 percentage points higher than for American mothers (OECD 2017b). 13 This covers federal government employees and industries crossing provincial boundaries. Appendix Table A.1. Regression Estimates of Economy-Wide, Within-Establishment, and Between-Establishment Effects of Motherhood on Log-Hourly Wages by Family-Supportive Context, Number of Children, and Age of Youngest Child, Women 25–44 (1) Baseline (2) Family-supportive controls (3) Number of children (4) Family-supportive controls by number of children Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Mother −0.032*** 0.002 −0.033*** −0.023*** −0.002 −0.02*** 1 Child −0.054*** −0.006*** −0.049*** −0.046*** −0.008*** −0.039*** 2 Children −0.013*** 0.006*** −0.019*** −0.004 0.001 −0.004*** 3+ Children −0.022*** 0.009** −0.031*** −0.006 0.004 −0.01*** Part-time −0.006** 0.034*** −0.04*** −0.009*** 0.034*** −0.042*** Work overtime 0.076*** 0.019*** 0.057*** 0.077*** 0.019*** 0.058*** Flexible hours −0.015*** −0.003* −0.012*** −0.015*** −0.003* −0.012*** Work from home  Job requirement 0.115*** 0.077*** 0.037*** 0.115*** 0.077*** 0.037***  Personal/family responsibilities 0.177*** 0.110*** 0.067*** 0.173*** 0.109*** 0.064***  Usual place of work 0.218*** 0.159*** 0.059*** 0.215*** 0.158*** 0.057***  Better conditions, save time, money 0.073*** 0.048*** 0.025*** 0.073*** 0.048*** 0.025***  Other 0.079*** 0.061*** 0.018*** 0.079*** 0.061*** 0.018*** Top-ups 0.105*** 0.008*** 0.097*** 0.105*** 0.008*** 0.097*** Employer childcare 0.020*** −0.003 0.024*** 0.021*** −0.003 0.024*** R-squared 0.416 0.364 0.446 0.375 0.447 0.375 (1) Baseline (2) Family-supportive controls (3) Number of children (4) Family-supportive controls by number of children Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Mother −0.032*** 0.002 −0.033*** −0.023*** −0.002 −0.02*** 1 Child −0.054*** −0.006*** −0.049*** −0.046*** −0.008*** −0.039*** 2 Children −0.013*** 0.006*** −0.019*** −0.004 0.001 −0.004*** 3+ Children −0.022*** 0.009** −0.031*** −0.006 0.004 −0.01*** Part-time −0.006** 0.034*** −0.04*** −0.009*** 0.034*** −0.042*** Work overtime 0.076*** 0.019*** 0.057*** 0.077*** 0.019*** 0.058*** Flexible hours −0.015*** −0.003* −0.012*** −0.015*** −0.003* −0.012*** Work from home  Job requirement 0.115*** 0.077*** 0.037*** 0.115*** 0.077*** 0.037***  Personal/family responsibilities 0.177*** 0.110*** 0.067*** 0.173*** 0.109*** 0.064***  Usual place of work 0.218*** 0.159*** 0.059*** 0.215*** 0.158*** 0.057***  Better conditions, save time, money 0.073*** 0.048*** 0.025*** 0.073*** 0.048*** 0.025***  Other 0.079*** 0.061*** 0.018*** 0.079*** 0.061*** 0.018*** Top-ups 0.105*** 0.008*** 0.097*** 0.105*** 0.008*** 0.097*** Employer childcare 0.020*** −0.003 0.024*** 0.021*** −0.003 0.024*** R-squared 0.416 0.364 0.446 0.375 0.447 0.375 (5) Age of youngest (6) Family-supportive controls by age of youngest Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Youngest child <7 −0.002 0.020*** −0.023*** 0.008*** 0.016*** −0.008*** Youngest child 7+ −0.056*** −0.013*** −0.042*** −0.047*** −0.017*** −0.03*** Part-time −0.007*** 0.034*** −0.04*** Work overtime 0.076*** 0.019*** 0.057*** Flexible hours −0.016*** −0.004** −0.012*** Work from home (none)  Job requirement 0.116*** 0.078*** 0.038***  Personal/family resp 0.172*** 0.107*** 0.065***  Usual place of work 0.220*** 0.161*** 0.06***  Better conditions 0.076*** 0.050*** 0.026***  Other 0.080*** 0.062*** 0.019*** Top-ups 0.106*** 0.009*** 0.097*** Employer childcare 0.019*** −0.004* 0.023*** R-squared 0.447 0.376 (5) Age of youngest (6) Family-supportive controls by age of youngest Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Youngest child <7 −0.002 0.020*** −0.023*** 0.008*** 0.016*** −0.008*** Youngest child 7+ −0.056*** −0.013*** −0.042*** −0.047*** −0.017*** −0.03*** Part-time −0.007*** 0.034*** −0.04*** Work overtime 0.076*** 0.019*** 0.057*** Flexible hours −0.016*** −0.004** −0.012*** Work from home (none)  Job requirement 0.116*** 0.078*** 0.038***  Personal/family resp 0.172*** 0.107*** 0.065***  Usual place of work 0.220*** 0.161*** 0.06***  Better conditions 0.076*** 0.050*** 0.026***  Other 0.080*** 0.062*** 0.019*** Top-ups 0.106*** 0.009*** 0.097*** Employer childcare 0.019*** −0.004* 0.023*** R-squared 0.447 0.376 Note: Models control for age, race/immigration, survey year, spouse, education, experience, seniority, occupation, and unionization. * p < 0.05 ** p < 0.01 *** p < 0.001 Table A.1. Regression Estimates of Economy-Wide, Within-Establishment, and Between-Establishment Effects of Motherhood on Log-Hourly Wages by Family-Supportive Context, Number of Children, and Age of Youngest Child, Women 25–44 (1) Baseline (2) Family-supportive controls (3) Number of children (4) Family-supportive controls by number of children Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Mother −0.032*** 0.002 −0.033*** −0.023*** −0.002 −0.02*** 1 Child −0.054*** −0.006*** −0.049*** −0.046*** −0.008*** −0.039*** 2 Children −0.013*** 0.006*** −0.019*** −0.004 0.001 −0.004*** 3+ Children −0.022*** 0.009** −0.031*** −0.006 0.004 −0.01*** Part-time −0.006** 0.034*** −0.04*** −0.009*** 0.034*** −0.042*** Work overtime 0.076*** 0.019*** 0.057*** 0.077*** 0.019*** 0.058*** Flexible hours −0.015*** −0.003* −0.012*** −0.015*** −0.003* −0.012*** Work from home  Job requirement 0.115*** 0.077*** 0.037*** 0.115*** 0.077*** 0.037***  Personal/family responsibilities 0.177*** 0.110*** 0.067*** 0.173*** 0.109*** 0.064***  Usual place of work 0.218*** 0.159*** 0.059*** 0.215*** 0.158*** 0.057***  Better conditions, save time, money 0.073*** 0.048*** 0.025*** 0.073*** 0.048*** 0.025***  Other 0.079*** 0.061*** 0.018*** 0.079*** 0.061*** 0.018*** Top-ups 0.105*** 0.008*** 0.097*** 0.105*** 0.008*** 0.097*** Employer childcare 0.020*** −0.003 0.024*** 0.021*** −0.003 0.024*** R-squared 0.416 0.364 0.446 0.375 0.447 0.375 (1) Baseline (2) Family-supportive controls (3) Number of children (4) Family-supportive controls by number of children Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Mother −0.032*** 0.002 −0.033*** −0.023*** −0.002 −0.02*** 1 Child −0.054*** −0.006*** −0.049*** −0.046*** −0.008*** −0.039*** 2 Children −0.013*** 0.006*** −0.019*** −0.004 0.001 −0.004*** 3+ Children −0.022*** 0.009** −0.031*** −0.006 0.004 −0.01*** Part-time −0.006** 0.034*** −0.04*** −0.009*** 0.034*** −0.042*** Work overtime 0.076*** 0.019*** 0.057*** 0.077*** 0.019*** 0.058*** Flexible hours −0.015*** −0.003* −0.012*** −0.015*** −0.003* −0.012*** Work from home  Job requirement 0.115*** 0.077*** 0.037*** 0.115*** 0.077*** 0.037***  Personal/family responsibilities 0.177*** 0.110*** 0.067*** 0.173*** 0.109*** 0.064***  Usual place of work 0.218*** 0.159*** 0.059*** 0.215*** 0.158*** 0.057***  Better conditions, save time, money 0.073*** 0.048*** 0.025*** 0.073*** 0.048*** 0.025***  Other 0.079*** 0.061*** 0.018*** 0.079*** 0.061*** 0.018*** Top-ups 0.105*** 0.008*** 0.097*** 0.105*** 0.008*** 0.097*** Employer childcare 0.020*** −0.003 0.024*** 0.021*** −0.003 0.024*** R-squared 0.416 0.364 0.446 0.375 0.447 0.375 (5) Age of youngest (6) Family-supportive controls by age of youngest Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Youngest child <7 −0.002 0.020*** −0.023*** 0.008*** 0.016*** −0.008*** Youngest child 7+ −0.056*** −0.013*** −0.042*** −0.047*** −0.017*** −0.03*** Part-time −0.007*** 0.034*** −0.04*** Work overtime 0.076*** 0.019*** 0.057*** Flexible hours −0.016*** −0.004** −0.012*** Work from home (none)  Job requirement 0.116*** 0.078*** 0.038***  Personal/family resp 0.172*** 0.107*** 0.065***  Usual place of work 0.220*** 0.161*** 0.06***  Better conditions 0.076*** 0.050*** 0.026***  Other 0.080*** 0.062*** 0.019*** Top-ups 0.106*** 0.009*** 0.097*** Employer childcare 0.019*** −0.004* 0.023*** R-squared 0.447 0.376 (5) Age of youngest (6) Family-supportive controls by age of youngest Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments Youngest child <7 −0.002 0.020*** −0.023*** 0.008*** 0.016*** −0.008*** Youngest child 7+ −0.056*** −0.013*** −0.042*** −0.047*** −0.017*** −0.03*** Part-time −0.007*** 0.034*** −0.04*** Work overtime 0.076*** 0.019*** 0.057*** Flexible hours −0.016*** −0.004** −0.012*** Work from home (none)  Job requirement 0.116*** 0.078*** 0.038***  Personal/family resp 0.172*** 0.107*** 0.065***  Usual place of work 0.220*** 0.161*** 0.06***  Better conditions 0.076*** 0.050*** 0.026***  Other 0.080*** 0.062*** 0.019*** Top-ups 0.106*** 0.009*** 0.097*** Employer childcare 0.019*** −0.004* 0.023*** R-squared 0.447 0.376 Note: Models control for age, race/immigration, survey year, spouse, education, experience, seniority, occupation, and unionization. * p < 0.05 ** p < 0.01 *** p < 0.001 Table A.2. Regression Estimates of Economy-Wide, Within-Establishment, and Between-Establishment Effects of Motherhood on Log-Hourly Wages by Mobility Pattern, Formalization and Nonprofit Status, Women 25–44 (1) Mobility (2) Mobility by formalization and nonprofit Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments No employer change 0.037*** 0.020*** 0.017*** 0.059*** 0.023*** 0.036*** Employer change after caregiving break −0.106*** −0.038*** −0.068*** −0.096*** −0.035*** −0.061*** Other post-motherhood employer change −0.046*** −0.010*** −0.035*** −0.084*** −0.039*** −0.045*** Union −0.005 −0.026*** 0.022*** No employer change*Union 0.040*** 0.026*** 0.014*** Employer change after caregiving break*Union 0.158*** 0.116*** 0.041*** Other post-motherhood employer change*Union 0.064*** 0.055*** 0.009*** HR in establishment 0.074*** 0.028*** 0.046*** No employer change*HR −0.026*** −0.063*** 0.037*** Employer change after caregiving break*HR 0.059*** 0.004 0.055*** Other post-motherhood employer change*HR 0.025*** −0.024*** 0.049*** Nonprofit −0.037*** 0.005** −0.041*** No employer change*Nonprofit −0.035*** −0.014*** −0.021*** Employer change after caregiving break*Nonprofit 0.024** 0.021*** 0.003 Other post-motherhood employer change*Nonprofit 0.023*** −0.016*** 0.039*** Size (0–19)  20–99 0.046*** −0.026*** 0.072***  100–499 0.090*** −0.038*** 0.128***  500 plus 0.161*** −0.039*** 0.201*** No employer change*20–99 −0.012 0.028*** −0.04*** No employer change*100–499 −0.032*** 0.019*** −0.051*** No employer change*500 plus −0.010 0.041*** −0.051*** Employer change after caregiving break*20–99 −0.103*** −0.039*** −0.064*** Employer change after caregiving break*100–499 −0.088*** −0.045*** −0.043*** Employer change after caregiving break*500 plus −0.104*** −0.120*** 0.016 Other post-motherhood employer change*20–99 0.023*** 0.029*** −0.007** Other post-motherhood employer change*100–499 0.004 0.046*** −0.042*** Other post-motherhood employer change*500 plus 0.013 0.044*** −0.031*** R-squared 0.45 0.376 0.469 0.375 (1) Mobility (2) Mobility by formalization and nonprofit Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments No employer change 0.037*** 0.020*** 0.017*** 0.059*** 0.023*** 0.036*** Employer change after caregiving break −0.106*** −0.038*** −0.068*** −0.096*** −0.035*** −0.061*** Other post-motherhood employer change −0.046*** −0.010*** −0.035*** −0.084*** −0.039*** −0.045*** Union −0.005 −0.026*** 0.022*** No employer change*Union 0.040*** 0.026*** 0.014*** Employer change after caregiving break*Union 0.158*** 0.116*** 0.041*** Other post-motherhood employer change*Union 0.064*** 0.055*** 0.009*** HR in establishment 0.074*** 0.028*** 0.046*** No employer change*HR −0.026*** −0.063*** 0.037*** Employer change after caregiving break*HR 0.059*** 0.004 0.055*** Other post-motherhood employer change*HR 0.025*** −0.024*** 0.049*** Nonprofit −0.037*** 0.005** −0.041*** No employer change*Nonprofit −0.035*** −0.014*** −0.021*** Employer change after caregiving break*Nonprofit 0.024** 0.021*** 0.003 Other post-motherhood employer change*Nonprofit 0.023*** −0.016*** 0.039*** Size (0–19)  20–99 0.046*** −0.026*** 0.072***  100–499 0.090*** −0.038*** 0.128***  500 plus 0.161*** −0.039*** 0.201*** No employer change*20–99 −0.012 0.028*** −0.04*** No employer change*100–499 −0.032*** 0.019*** −0.051*** No employer change*500 plus −0.010 0.041*** −0.051*** Employer change after caregiving break*20–99 −0.103*** −0.039*** −0.064*** Employer change after caregiving break*100–499 −0.088*** −0.045*** −0.043*** Employer change after caregiving break*500 plus −0.104*** −0.120*** 0.016 Other post-motherhood employer change*20–99 0.023*** 0.029*** −0.007** Other post-motherhood employer change*100–499 0.004 0.046*** −0.042*** Other post-motherhood employer change*500 plus 0.013 0.044*** −0.031*** R-squared 0.45 0.376 0.469 0.375 Note: Models control for age, race/immigration, survey year, spouse, education, experience, seniority, occupation, and unionization. * p < 0.05 ** p < 0.01 *** p < 0.001 Table A.2. Regression Estimates of Economy-Wide, Within-Establishment, and Between-Establishment Effects of Motherhood on Log-Hourly Wages by Mobility Pattern, Formalization and Nonprofit Status, Women 25–44 (1) Mobility (2) Mobility by formalization and nonprofit Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments No employer change 0.037*** 0.020*** 0.017*** 0.059*** 0.023*** 0.036*** Employer change after caregiving break −0.106*** −0.038*** −0.068*** −0.096*** −0.035*** −0.061*** Other post-motherhood employer change −0.046*** −0.010*** −0.035*** −0.084*** −0.039*** −0.045*** Union −0.005 −0.026*** 0.022*** No employer change*Union 0.040*** 0.026*** 0.014*** Employer change after caregiving break*Union 0.158*** 0.116*** 0.041*** Other post-motherhood employer change*Union 0.064*** 0.055*** 0.009*** HR in establishment 0.074*** 0.028*** 0.046*** No employer change*HR −0.026*** −0.063*** 0.037*** Employer change after caregiving break*HR 0.059*** 0.004 0.055*** Other post-motherhood employer change*HR 0.025*** −0.024*** 0.049*** Nonprofit −0.037*** 0.005** −0.041*** No employer change*Nonprofit −0.035*** −0.014*** −0.021*** Employer change after caregiving break*Nonprofit 0.024** 0.021*** 0.003 Other post-motherhood employer change*Nonprofit 0.023*** −0.016*** 0.039*** Size (0–19)  20–99 0.046*** −0.026*** 0.072***  100–499 0.090*** −0.038*** 0.128***  500 plus 0.161*** −0.039*** 0.201*** No employer change*20–99 −0.012 0.028*** −0.04*** No employer change*100–499 −0.032*** 0.019*** −0.051*** No employer change*500 plus −0.010 0.041*** −0.051*** Employer change after caregiving break*20–99 −0.103*** −0.039*** −0.064*** Employer change after caregiving break*100–499 −0.088*** −0.045*** −0.043*** Employer change after caregiving break*500 plus −0.104*** −0.120*** 0.016 Other post-motherhood employer change*20–99 0.023*** 0.029*** −0.007** Other post-motherhood employer change*100–499 0.004 0.046*** −0.042*** Other post-motherhood employer change*500 plus 0.013 0.044*** −0.031*** R-squared 0.45 0.376 0.469 0.375 (1) Mobility (2) Mobility by formalization and nonprofit Economy-wide Within establishment Between establishments Economy-wide Within establishment Between establishments No employer change 0.037*** 0.020*** 0.017*** 0.059*** 0.023*** 0.036*** Employer change after caregiving break −0.106*** −0.038*** −0.068*** −0.096*** −0.035*** −0.061*** Other post-motherhood employer change −0.046*** −0.010*** −0.035*** −0.084*** −0.039*** −0.045*** Union −0.005 −0.026*** 0.022*** No employer change*Union 0.040*** 0.026*** 0.014*** Employer change after caregiving break*Union 0.158*** 0.116*** 0.041*** Other post-motherhood employer change*Union 0.064*** 0.055*** 0.009*** HR in establishment 0.074*** 0.028*** 0.046*** No employer change*HR −0.026*** −0.063*** 0.037*** Employer change after caregiving break*HR 0.059*** 0.004 0.055*** Other post-motherhood employer change*HR 0.025*** −0.024*** 0.049*** Nonprofit −0.037*** 0.005** −0.041*** No employer change*Nonprofit −0.035*** −0.014*** −0.021*** Employer change after caregiving break*Nonprofit 0.024** 0.021*** 0.003 Other post-motherhood employer change*Nonprofit 0.023*** −0.016*** 0.039*** Size (0–19)  20–99 0.046*** −0.026*** 0.072***  100–499 0.090*** −0.038*** 0.128***  500 plus 0.161*** −0.039*** 0.201*** No employer change*20–99 −0.012 0.028*** −0.04*** No employer change*100–499 −0.032*** 0.019*** −0.051*** No employer change*500 plus −0.010 0.041*** −0.051*** Employer change after caregiving break*20–99 −0.103*** −0.039*** −0.064*** Employer change after caregiving break*100–499 −0.088*** −0.045*** −0.043*** Employer change after caregiving break*500 plus −0.104*** −0.120*** 0.016 Other post-motherhood employer change*20–99 0.023*** 0.029*** −0.007** Other post-motherhood employer change*100–499 0.004 0.046*** −0.042*** Other post-motherhood employer change*500 plus 0.013 0.044*** −0.031*** R-squared 0.45 0.376 0.469 0.375 Note: Models control for age, race/immigration, survey year, spouse, education, experience, seniority, occupation, and unionization. * p < 0.05 ** p < 0.01 *** p < 0.001 About the Author Sylvia Fuller is Associate Professor at the University of British Columbia. Her research centers on understanding how labor market inequalities develop and erode and the implications of changing employment relations and social policy frameworks for workers’ economic security and mobility. Recent publications explore temporary workers’ employment trajectories, divergence in the career pathways of new immigrants, and trends in the medicalization of welfare among lone mothers. Supplementary Material Supplementary material is available at Social Forces online. References Abowd , John M. , Francis Kramarz , and David N. Margolis . 1999 . “ High Wage Workers and High Wage Firms .” Econometrica 67 ( 2 ): 251 – 333 . Google Scholar CrossRef Search ADS Acker , Joan . 1990 . “ Hierarchies, Jobs, Bodies: A Theory of Gendered Organizations .” Gender & Society 4 ( 2 ): 139 – 58 . Google Scholar CrossRef Search ADS ——— . 2006 . “ Inequality Regimes Gender, Class, and Race in Organizations .” Gender & Society 20 ( 4 ): 441 – 64 . Google Scholar CrossRef Search ADS Adams , Lorna , Mark Winterbotham , Katie Oldfield , Jenny McLeish , Alasdair Stuart , Alice Large , Liz Murphy , Helen Rossiter , and Sam Selner . 2016 . “Pregnancy and Maternity-Related Discrimination and Disadvantage: Experiences of Employers.” London : Department for Business, Innovation and Skills and the Equality and Human Rights Commission, Great Britain . Aisenbrey , Silke , Marie Evertsson , and Daniela Grunow . 2009 . “ Is There a Career Penalty for Mothers’ Time Out? A Comparison of Germany, Sweden and the United States .” Social Forces 88 ( 2 ): 573 – 605 . Google Scholar CrossRef Search ADS Akerlof , George A. 1982 . “ Labor Contracts as Partial Gift Exchange .” Quarterly Journal of Economics 97 ( 4 ): 543 – 69 . Google Scholar CrossRef Search ADS Anderson , Deborah J. , Melissa Binder , and Kate Krause . 2002 . “ The Motherhood Wage Penalty: Which Mothers Pay It and Why? ” American Economic Review 92 ( 2 ): 354 – 58 . Google Scholar CrossRef Search ADS ——— . 2003 . “ The Motherhood Wage Penalty Revisited: Experience, Heterogeneity, Work Effort, and Work-Schedule Flexibility .” Industrial & Labor Relations Review 56 ( 2 ): 273 – 94 . Google Scholar CrossRef Search ADS Avellar , Sarah , and Pamela J. Smock . 2003 . “ Has the Price of Motherhood Declined over Time? A Cross-Cohort Comparison of the Motherhood Wage Penalty .” Journal of Marriage and Family 65 ( 3 ): 597 – 607 . Google Scholar CrossRef Search ADS Avent-Holt , Dustin , and Donald Tomaskovic-Devey . 2010 . “ The Relational Basis of Inequality: Generic and Contingent Wage Distribution Processes .” Work and Occupations 37 ( 2 ): 162 – 93 . Google Scholar CrossRef Search ADS ——— . 2014 . “ A Relational Theory of Earnings Inequality .” American Behavioral Scientist 58 ( 3 ): 379 – 99 Google Scholar CrossRef Search ADS Bardasi , Elena , and Janet C. Gornick . 2008 . “ Working for Less? Women’s Part-Time Wage Penalties across Countries .” Feminist Economics 14 ( 1 ): 37 – 72 . Google Scholar CrossRef Search ADS Baron , J. N. , and W. T. Bielby. 1980 . “ Bringing the Firms Back. In: Stratification, Segmentation, and the Organization of Work .” American Sociological Review 45 ( 5 ): 737 – 65 . Google Scholar CrossRef Search ADS Baron , James N. , Michael T. Hannan , Greta Hsu , and Özgecan Koçak . 2007 . “ In the Company of Women Gender Inequality and the Logic of Bureaucracy in Start-Up Firms .” Work and Occupations 34 ( 1 ): 35 – 66 . Google Scholar CrossRef Search ADS Baughman , Reagan , Daniela DiNardi , and Douglas Holtz-Eakin . 2003 . “ Productivity and Wage Effects of ‘Family-Friendly’ Fringe Benefits .” International Journal of Manpower 24 ( 3 ): 247 – 59 . Google Scholar CrossRef Search ADS Bayard , Kimberly , Judith Hellerstein , David Neumark , and Kenneth Troske . 2003 . New Evidence on Sex Segregation and Sex Differences in Wages from Matched Employee-Employer Data . Journal of Labour Economics 21 ( 4 ): 887 – 922 . Beaujot , Roderic , and Zenaida R. Ravanera . 2009 . “ Family Models for Earning and Caring: Implications for Child Care and for Family Policy .” Canadian Studies in Population 36 ( 1 – 2 ): 145 – 66 . Google Scholar CrossRef Search ADS Beblo , Miriam , Stefan Bender , and Elke Wolf . 2008 . “ Establishment-Level Wage Effects of Entering Motherhood .” Oxford Economic Papers 61 : i11 – i34 . Google Scholar CrossRef Search ADS Becker , Gary S. 1993 . A Treatise on the Family , rev. ed. Cambridge, MA : Harvard University Press . Bidwell , Matthew , Forrest Briscoe , Isabel Fernandez-Mateo , and Adina Sterling . 2013 . “ The Employment Relationship and Inequality: How and Why Changes in Employment Practices Are Reshaping Rewards in Organizations .” Academy of Management Annals 7 ( 1 ): 61 – 121 . Google Scholar CrossRef Search ADS Blair-Loy , Mary . 2003 . Competing Devotions: Career and Family among Women Executives . Boston : Harvard University Press . Blair-Loy , Mary , and Amy S. Wharton . 2002 . “ Employees’ Use of Work-Family Policies and the Workplace Social Context .” Social Forces 80 ( 3 ): 813 – 45 . Google Scholar CrossRef Search ADS Bloom , Nick , Tobias Kretschmer , and John Van Reenan . 2009 . “Work-Life Balance, Management Practices and Productivity.” In International Differences in the Business Practices and Productivity of Firms , edited by Richard B. Freeman and Kathryn L. Shaw , pp. 15 – 54 . Chicago, IL : University of Chicago Press . Google Scholar CrossRef Search ADS Boushey , Heather . 2008 . “ Family Friendly Policies: Helping Mothers Make Ends Meet .” Review of Social Economy 66 ( 1 ): 51 – 70 . Google Scholar CrossRef Search ADS Brescoll , Victoria L. , Jennifer Glass , and Alexandra Sedlovskaya . 2013 . “ Ask and Ye Shall Receive? The Dynamics of Employer-Provided Flexible Work Options and the Need for Public Policy .” Journal of Social Issues 69 ( 2 ): 367 – 88 . Google Scholar CrossRef Search ADS Bronars , Stephen G. , and Melissa Famulari . 1997 . “ Wage, Tenure, and Wage Growth Variation within and across Establishments .” Journal of Labor Economics 15 ( 2 ): 285 – 317 . Google Scholar CrossRef Search ADS Budig , Michelle J. , and Paula England . 2001 . “ The Wage Penalty for Motherhood .” American Sociological Review 66 ( 2 ): 204 – 25 . Google Scholar CrossRef Search ADS Budig , Michelle J. , Joya Misra , and Irene Boeckmann . 2016 . “ Work-Family Policy Trade-Offs for Mothers? Unpacking the Cross-National Variation in Motherhood Earnings Penalties .” Work and Occupations 43 ( 2 ): 119 – 77 . Google Scholar CrossRef Search ADS Byron , Reginald A. , and Vincent J. Roscigno . 2014 . “ Relational Power, Legitimation, and Pregnancy Discrimination .” Gender & Society 28 ( 3 ): 435 – 62 . Google Scholar CrossRef Search ADS Canay , Ivan A. 2011 . “ A Simple Approach to Quantile Regression for Panel Data .” Econometrics Journal 14 ( 3 ): 368 – 86 . Google Scholar CrossRef Search ADS Cappelli , Peter . 1999 . The New Deal at Work: Managing the Market-Driven Workforce . Boston : Harvard Business Press . Correll , Shelley J. , Stephen Benard , and In Paik . 2007 . “ Getting a Job: Is There a Motherhood Penalty? ” American Journal of Sociology 112 ( 5 ): 1297 – 1338 . Google Scholar CrossRef Search ADS Cooke , Lynn Prince . 2011 . Gender-Class Equality in Political Economies . New York : Routledge . ——— . 2014 . “ Gendered Parenthood Penalties and Premiums across the Earnings Distribution in Australia, the United Kingdom, and the United States .” European Sociological Review 30 ( 3 ): 360 – 72 . Google Scholar CrossRef Search ADS Crowley , Jocelyn Elise . 2013 . “ Perceiving and Responding to Maternal Workplace Discrimination in the United States .” Women’s Studies International Forum 40 : 192 – 202 . Google Scholar CrossRef Search ADS Damman , Marleen , Liesbet Heyse , and Melinda Mills . 2014 . “ Gender, Occupation, and Promotion to Management in the Nonprofit Sector .” Nonprofit Management and Leadership 25 ( 2 ): 97 – 111 . Google Scholar CrossRef Search ADS Dau-Schmidt , Kenneth G. , Marc S. Galanter , Kaushik Mukhopadhaya , and Kathleen E. Hull . 2009 . “ Men and Women of the Bar: The Impact of Gender on Legal Careers .” Michigan Journal of Gender and Law 16 ( 1 ): 49 – 145 . DiMaggio , Paul , and Walter W. Powell . 1983 . “ The Iron Cage Revisited: Collective Rationality and Institutional Isomorphism in Organizational Fields .” American Sociological Review 48 ( 2 ): 147 – 60 . Google Scholar CrossRef Search ADS Dobbin , Frank . 2009 . Inventing Equal Opportunity . Princeton, NJ : Princeton University Press . Google Scholar CrossRef Search ADS Dodson , Lisa . 2013 . “ Stereotyping Low-Wage Mothers Who Have Work and Family Conflicts .” Journal of Social Issues 69 ( 2 ): 257 – 78 . Google Scholar CrossRef Search ADS Drolet , Marie . 2002 . “ Can the Workplace Explain Canadian Gender Pay Differentials? ” Canadian Public Policy 28 ( 1 ): 41 – 63 . Google Scholar CrossRef Search ADS Drolet , Marie , and Karen Mumford . 2012 . “ The Gender Pay Gap for Private-Sector Employees in Canada and Britain .” British Journal of Industrial Relations 50 ( 3 ): 529 – 53 . Google Scholar CrossRef Search ADS Duxbury , Linda , and Laura Gover . 2011 . “Exploring the Link between Organizational Culture and Work-Family Conflict.” In The Handbook of Organizational Culture and Climate , edited by Neal M. Ashkanasy , Celeste Wilderom , and Mark F. Peterson , pp. 271 – 90 . Thousand Oaks, CA : Sage Publications . Google Scholar CrossRef Search ADS Edelman , Lauren B. , Christopher Uggen , and Howard S. Erlanger . 1999 . “ The Endogeneity of Legal Regulation: Grievance Procedures as Rational Myth .” American Journal of Sociology 105 ( 2 ): 406 – 54 . Google Scholar CrossRef Search ADS Elvira , Marta M. , and Ishak Saporta . 2001 . “ How Does Collective Bargaining Affect the Gender Pay Gap? ” Work and Occupations 28 ( 4 ): 469 – 90 . Google Scholar CrossRef Search ADS Epstein , Cynthia Fuchs , Carroll Seron , Bonnie Oglensky , and Robert Saute . 2014 . The Part-Time Paradox: Time Norms, Professional Life, Family and Gender . New York and London : Routledge . Fahlén , Susanne . 2013 . “Worklife Balance: The Agency and Capabilities Gap.” In The Agency and Capabilities Gap in Work—Life Balance Across European and Asian Societies and within Work Organizations , edited by Barbara Hobson , pp. 35 – 56 . New York : Oxford University Press . Fakih , Ali . 2014 . “Availability of Family-Friendly Work Practices and Implicit Wage Costs: New Evidence from Canada.” IZA Discussion Papers No. 8190:1–31. Felfe , Christina . 2012 . “ The Motherhood Wage Gap: What About Job Amenities? ” Labour Economics 19 ( 1 ): 59 – 67 . Google Scholar CrossRef Search ADS Fuegen , Kathleen , Monica Biernat , Elizabeth Haines , and Kay Deaux . 2004 . “ Mothers and Fathers in the Workplace: How Gender and Parental Status Influence Judgments of Job-Related Competence .” Journal of Social Issues 60 ( 4 ): 737 – 54 . Google Scholar CrossRef Search ADS Fuller , Sylvia . 2005 . “ Public Sector Employment and Gender Wage Inequalities in British Columbia: Assessing the Effects of a Shrinking Public Sector .” Canadian Journal of Sociology 30 ( 4 ): 405 – 39 . ——— . 2008 . “ Job Mobility and Wage Trajectories for Men and Women in the United States .” American Sociological Review 73 ( 1 ): 158 – 83. Google Scholar CrossRef Search ADS Gariety , Bonnie Sue , and Sherrill Shaffer . 2001 . “ Wage Differentials Associated with Flextime .” Monthly Labour Review 124 ( 3 ): 68 – 75 . Glass , Jennifer . 2004 . “ Blessing or Curse? Work-Family Policies and Mother’s Wage Growth over Time .” Work and Occupations 31 ( 3 ): 367 – 94 . Google Scholar CrossRef Search ADS Glauber , Rebecca . 2012 . “ Women’s Work and Working Conditions: Are Mothers Compensated for Lost Wages? ” Work and Occupations 39 ( 2 ): 115 – 38 . Google Scholar CrossRef Search ADS Golden , Lonnie , Julia R. Henly , and Susan Lambert . 2013 . “ Work Schedule Flexibility: A Contributor to Happiness? ” Journal of Social Research & Policy 4 ( 2 ): 107 . Golden , Lonnie , and Barbara Wiens-Tuers . 2005 . “ Mandatory Overtime Work in the United States: Who, Where, and What? ” Labor Studies Journal 30 ( 1 ): 1 – 25 . Google Scholar CrossRef Search ADS Groshen , Erica L. 1991 . “ Sources of Intra-Industry Wage Dispersion: How Much Do Employers Matter? ” Quarterly Journal of Economics 106 ( 3 ): 869 – 84 . Google Scholar CrossRef Search ADS Gunderson , Morley , and Douglas Hyatt . 2001 . “ Workplace Risks and Wages: Canadian Evidence from Alternative Models .” Canadian Journal of Economics/Revue Canadienne D’économique 34 ( 2 ): 377 – 95 . Google Scholar CrossRef Search ADS Haley-Lock , Anna . 2011 . “ Place-Bound Jobs at the Intersection of Policy and Management: Comparing Employer Practices in US and Canadian Chain Restaurants .” American Behavioral Scientist 55 ( 7 ): 823 – 42 . Google Scholar CrossRef Search ADS Harkness , Susan , and Jane Waldfogel . 2003 . “ The Family Gap in Pay: Evidence from Seven Industrialized Countries .” Research in Labor Economics 22 : 369 – 414 . Google Scholar CrossRef Search ADS Heilman , Madeline E. , and Tyler G. Okimoto . 2008 . “ Motherhood: A Potential Source of Bias in Employment Decisions .” Journal of Applied Psychology 93 ( 1 ): 189 . Google Scholar CrossRef Search ADS Herr , Jane Leber , and Catherine D. Wolfram . 2012 . “ Work Environment and Opt-Out Rates at Motherhood across High-Education Career Paths .” Industrial & Labor Relations Review 65 ( 4 ): 928 – 50 . Google Scholar CrossRef Search ADS Heywood , John S. , W. Stanley Siebert , and Xiangdong Wei . 2007 . “ The Implicit Wage Costs of Family Friendly Work Practices .” Oxford Economic Papers 59 ( 2 ): 275 – 300 . Google Scholar CrossRef Search ADS Hodges , Melissa J. , and Michelle J. Budig . 2010 . “ Who Gets the Daddy Bonus? Organizational Hegemonic Masculinity and the Impact of Fatherhood on Earnings .” Gender & Society 24 ( 6 ): 717 – 45 . Google Scholar CrossRef Search ADS Hollister , Matissa . 2011 . “ Employment Stability in the US Labor Market: Rhetoric versus Reality .” Annual Review of Sociology 37 ( 1 ): 305 – 24 . Google Scholar CrossRef Search ADS Hou , Feng , and Simon Coulombe . 2010 . “ Earnings Gaps for Canadian-Born Visible Minorities in the Public and Private Sectors .” Canadian Public Policy 36 ( 1 ): 29 – 43 . Google Scholar CrossRef Search ADS Javdani , Mohsen . 2015 . “ Glass Ceilings or Glass Doors? The Role of Firms in Male-Female Wage Disparities .” Canadian Journal of Economics/Revue canadienne d’économique 48 ( 2 ): 529 – 60 . Google Scholar CrossRef Search ADS Johnson , Nancy Brown , and Keith G. Provan . 1996 . “ The Relationship between Work/Family Benefits and Earnings: A Test of Competing Predictions .” Journal of Socio-Economics 24 ( 4 ): 571 – 84 . Google Scholar CrossRef Search ADS Kalev , Alexandra . 2014 . “ How You Downsize Is Who You Downsize: Biased Formalization, Accountability, and Managerial Diversity .” American Sociological Review 79 ( 1 ): 109 – 35 . Google Scholar CrossRef Search ADS Kalleberg , Arne . 2013 . Good Jobs, Bad Jobs: The Rise of Polarized and Precarious Employment Systems in the United States, 1970s to 2000s . New York : Russell Sage Foundation Keith , Kristen , and Abagail McWilliams . 1997 . “ Job Mobility and Gender-Based Wage Growth Differentials .” Economic Inquiry 35 ( 2 ): 320 – 33 . Google Scholar CrossRef Search ADS Kelly , Erin , and Frank Dobbin . 1998 . “ How Affirmative Action Became Diversity Management Employer Response to Antidiscrimination Law, 1961 to 1996 .” American Behavioral Scientist 41 ( 7 ): 960 – 84 . Google Scholar CrossRef Search ADS Kelly , Erin L. , Phyllis Moen , and Eric Tranby . 2011 . “ Changing Workplaces to Reduce Work-Family Conflict .” American Sociological Review 76 ( 2 ): 265 . Google Scholar CrossRef Search ADS Killewald , Alexandra . 2012 . “ A Reconsideration of the Fatherhood Premium: Marriage, Coresidence, Biology, and Fathers’ Wages .” American Sociological Review 78 ( 1 ): 96 – 116 . Google Scholar CrossRef Search ADS Kronberg , Anne-Kathrin . 2013 . “ Stay or Leave? Externalization of Job Mobility and the Effect on the US Gender Earnings Gap, 1979–2009 .” Social Forces 91 ( 4 ): 1117 – 46 . Google Scholar CrossRef Search ADS Lambert , Susan , Anna Haley-Lock , and Julia R. Henly . 2012 . “ Schedule Flexibility in Hourly Jobs: Unanticipated Consequences and Promising Directions .” Community, Work & Family 15 ( 3 ): 293 – 315 . Google Scholar CrossRef Search ADS Lane , Julia I. , Laurie A. Salmon , and James R. Spletzer . 2007 . “ Establishment Wage Differentials .” Monthly Labour Review 130 ( 3 ): 3 – 17 . Looze , Jessica . 2014 . “ Young Women’s Job Mobility: The Influence of Motherhood Status and Education .” Journal of Marriage and Family 76 ( 4 ): 693 – 709 . Google Scholar CrossRef Search ADS Looze , Jessica . 2009 . “ The Family Work Week .” Perspectives on Labour and Income 21 ( 2 ): 21 – 9 . Mastracci , Sharon H. , and Cedric Herring . 2010 . “ Nonprofit Management Practices and Work Processes to Promote Gender Diversity .” Nonprofit Management and Leadership 21 ( 2 ): 155 – 75 . Google Scholar CrossRef Search ADS McCrate , Elaine . 2005 . “ Flexible Hours, Workplace Authority, and Compensating Wage Differentials in the U.S .” Feminist Economics 11 ( 1 ): 11 – 39 . Google Scholar CrossRef Search ADS ——— . 2016 . “Unstable Scheduling, Precarious Employment, and Gender.” Working Paper, EINet Measurement Group. McGinnity , Frances , and Patricia McManus . 2007 . “ Paying the Price for Reconciling Work and Family Life: Comparing the Wage Penalty for Women’s Part-Time Work in Britain, Germany and the United States .” Journal of Comparative Policy Analysis 9 ( 2 ): 115 – 34 . Google Scholar CrossRef Search ADS OECD . 2004 . “Wage-Setting Institutions and Outcomes.” In OECD Employment Outlook. Geneva : OECD . ——— . 2013 . “Chart Pf3.1.A Expenditure on Childcare and Pre-Pimary, 2011.” In OECD Family Database. ——— . 2017 a. “Chart LMF1.2.A Maternal Employment Rates, 2014 or Latest Available Year.” In OECD Family Database. Paris. Accessed November 2017. ——— . 2017 b. “Chart Pf2.5. Trends in Leave Entitlements Around Childbirth.” In OECD Family Database. Paris. Pendakur , Krishna , and Simon Woodcock . 2010 . “ Glass Ceilings or Glass Doors? Wage Disparity Within and Between Firms .” Journal of Business & Economic Statistics 28 ( 1 ): 181 – 89 . Google Scholar CrossRef Search ADS Petersen , Trond , and Laurie A. Morgan . 1995 . “ Separate and Unequal: Occupation-Establishment Sex Segregation and the Gender Wage Gap .” American Journal of Sociology 101 ( 2 ): 329 – 65 . Google Scholar CrossRef Search ADS Petersen , Trond , Andrew M. Penner , and Geir Høgsnes . 2010 . “ The Within-Job Motherhood Wage Penalty in Norway, 1979–1996 .” Journal of Marriage and Family 72 ( 5 ): 1274 – 88 . Google Scholar CrossRef Search ADS ——— . 2011 . “ The Male Marital Wage Premium: Sorting vs. Differential Pay .” ILR Review 64 ( 2 ): 283 – 304 . Google Scholar CrossRef Search ADS ——— . 2014 . “ From Motherhood Penalties to Husband Premia: The New Challenge for Gender Equality and Family Policy, Lessons from Norway .” American Journal of Sociology 119 ( 5 ): 1434 – 72 . Google Scholar CrossRef Search ADS Petersen , Trond , and Ishak Saporta . 2004 . “ The Opportunity Structure for Discrimination .” American Journal of Sociology 109 ( 4 ): 852 – 901 . Google Scholar CrossRef Search ADS Phipps , Shelley , Peter Burton , and Lynn Lethbridge . 2001 . “ In and Out of the Labour Market: Long-Term Income Consequences of Child-Related Interruptions to Women’s Paid Work .” Canadian Journal of Economics/Revue Canadienne d’Economique 34 ( 2 ): 411 – 29 . Google Scholar CrossRef Search ADS Raley , Sara , Suzanne M. Bianchi , and Wendy Wang . 2012 . “ When Do Fathers Care? Mothers’ Economic Contribution and Fathers’ Involvement in Child Care .” American Journal of Sociology 117 ( 5 ): 1422 – 59 . Google Scholar CrossRef Search ADS Reskin , Barbara F. , and Debra Branch McBrier . 2000 . “ Why Not Ascription? Organizations’ Employment of Male and Female Managers .” American Sociological Review 65 ( 2 ): 210 – 33 . Google Scholar CrossRef Search ADS Ridgeway , Cecilia L. , and Shelley J. Correll . 2004 . “ Motherhood as a Status Characteristic .” Journal of Social Issues 60 ( 4 ): 683 – 700 . Google Scholar CrossRef Search ADS Sakamoto , Arthur , and Sharron Xuanren Wang . 2016 . “ Occupational and Organizational Effects on Wages among College-Educated Workers in 2003 and 2010 .” Social Currents 4 ( 2 ): 175 – 95 . Google Scholar CrossRef Search ADS Salop , Steven C. 1979 . “ A Model of the Natural Rate of Unemployment .” American Economic Review 69 ( 1 ): 117 – 25 . Shapiro , Carl , and Joseph E. Stiglitz . 1984 . “ Equilibrium Unemployment as a Worker Discipline Device .” American Economic Review 74 ( 3 ): 433 – 44 . Simón , Hipólito . 2010 . “ International Differences in Wage Inequality: A New Glance with European Matched Employer–Employee Data .” British Journal of Industrial Relations 48 ( 2 ): 310 – 46 . Google Scholar CrossRef Search ADS Stainback , Kevin , Thomas N. Ratliff , and Vincent J. Roscigno . 2011 . “ The Context of Workplace Sex Discrimination: Sex Composition, Workplace Culture and Relative Power .” Social Forces 89 ( 4 ): 1165 – 88 . Google Scholar CrossRef Search ADS Stainback , Kevin , Donald Tomaskovic-Devey , and Sheryl Skaggs . 2010 . “ Organizational Approaches to Inequality: Inertia, Relative Power, and Environments .” Annual Review of Sociology 36 ( 1 ): 225 – 47 . Google Scholar CrossRef Search ADS Statistics Canada . 2017 . Table 281-0024 Survey of Employment, Payrolls, and Hours (SEPH), Employment by Type of Employee and Detailed North American Industry Classification System (NAICS), Annual (persons), CANSIM (database). Accessed May 2017. Stinchcombe , Arthur L. 2001 . When Formality Works: Authority and Abstraction in Law and Organizations . Chicago : University of Chicago Press . Stone , Pamela , and Lisa Ackerly Hernandez . 2013 . “ The All-or-Nothing Workplace: Flexibility Stigma and ‘Opting Out’ among Professional-Managerial Women .” Journal of Social Issues 69 ( 2 ): 235 – 56 . Google Scholar CrossRef Search ADS Sweet , Stephen , Marcie Pitt-Catsouphes , Elyssa Besen , and Lonnie Golden . 2014 . “ Explaining Organizational Variation in Flexible Work Arrangements: Why the Pattern and Scale of Availability Matter .” Community, Work & Family 17 ( 2 ): 115 – 41 . Google Scholar CrossRef Search ADS Tilly , Charles . 1998 . Durable Inequalities. Berkeley : University of California Press . Tomaskovic-Devey , Donald , Martin Hällsten , and Martin Avent-Holt . 2015 . “ Where Do Immigrants Fare Worse? Modeling Workplace Wage Gap Variation with Longitudinal Employer-Employee Data .” American Journal of Sociology 120 ( 4 ): 1095 – 1143 . Google Scholar CrossRef Search ADS Tomlinson , Frances , and Christina Schwabenland . 2010 . “ Reconciling Competing Discourses of Diversity? The UK Non-Profit Sector between Social Justice and the Business Case .” Organization 17 ( 1 ): 101 – 21 . Google Scholar CrossRef Search ADS Viitanen , Tarja . 2014 . “ The Motherhood Wage Gap in the UK over the Life Cycle .” Review of Economics of the Household 12 ( 2 ): 259 – 76 . Google Scholar CrossRef Search ADS Vosko , Leah F. 2009 . Managing the Margins: Gender, Citizenship, and the International Regulation of Precarious Employment . Toronto : Oxford University Press . Waite , Sean , and Nicole Denier . 2015 . “ Gay Pay for Straight Work Mechanisms Generating Disadvantage .” Gender & Society 29 ( 4 ): 561 – 88 . Google Scholar CrossRef Search ADS Webber , Gretchen , and Christine Williams . 2008 . “ Mothers in ‘Good’ and ‘Bad’ Part-Time Jobs: Different Problems, Same Results .” Gender & Society 22 ( 6 ): 752 – 77 . Google Scholar CrossRef Search ADS Weeden , Kim A. 2005 . “ Is There a Flexiglass Ceiling? Flexible Work Arrangements and Wages in the United States .” Social Science Research 34 ( 2 ): 454 – 82 . Google Scholar CrossRef Search ADS Wilde , Elizabeth Ty , Lily Batchelder , and David T. Ellwood . 2010 . The Mommy Track Divides: The Impact of Childbearing on Wages of Women of Differing Skill Levels. National Bureau of Economic Research . Williams , Joan . 2000 . Why Work and Family Conflict and What to Do About It . New York : Oxford University Press . ——— . 2010 . Reshaping the Work-Family Debate . Cambridge, MA : Harvard University Press . Williams , Joan , Mary Blair-Loy , and Jennifer Berdahl . 2013 . “ Cultural Schemas, Social Class, and the Flexibility Stigma .” Journal of Social Issues 69 ( 2 ): 209 – 34 . Google Scholar CrossRef Search ADS Wilson , George , Vincent J. Roscigno , and Matt L. Huffman . 2013 . “ Public Sector Transformation, Racial Inequality and Downward Occupational Mobility .” Social Forces 91 ( 3 ): 975 – 1006 . Google Scholar CrossRef Search ADS ——— . 2015 . “ Racial Income Inequality and Public Sector Privatization .” Social Problems 62 ( 2 ): 163 – 85. Google Scholar CrossRef Search ADS Winder , Katie L. 2009 . “ Flexible Scheduling and the Gender Wage Gap .” B. E. Journal of Economic Analysis & Policy 9 ( 1 ):1935–1682. Zhang , Xuelin . 2007 . “ Returning to the Job after Childbirth .” Perspectives on Labour and Income 20 ( 1 ): 18 – 24 . ——— . 2009 . “ Earnings of Women with and without Children .” Perspectives on Labour and Income 10 ( 3 ): 5 – 13 . ——— . 2010 . “ Can Motherhood Earnings Losses Be Ever Regained? Evidence from Canada .” Journal of Family Issues 31 ( 12 ): 1671 – 88 . Google Scholar CrossRef Search ADS Author notes The author gratefully acknowledges funding from the Social Sciences and Humanities Research Council of Canada. The analysis was conducted at the Simon Fraser University Branch of the Canadian Research Data Centre Network (CRDCN), which is supported by the SSHRC, the CIHR, the CFI, Statistics Canada, and SFU. Helpful feedback and advice was provided by Lynn Prince Cooke, Beth Hirsh, Mohsen Javdani, Rima Wilkes, and Cristobal Young. Able research assistance was provided by Christina Trealeven and Natasha Stecy-Hildebrandt. © The Author 2017. Published by Oxford University Press on behalf of the University of North Carolina at Chapel Hill. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Social ForcesOxford University Press

Published: Dec 8, 2017

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