Does equal pay mean equal time? Lyndall Strazdins with Huong Dinh Jenny Welsh NATIONAL CENTRE FOR EPIDEMIOLOGY & POPULATION HEALTH

Gender equality in Australia, now Women are as skilled as men: Bachelor Degree or above (42% women, 31% men; 25 - 29 years of age) Yet they are less likely to be employed: (65% women, 78% men) When they do work they earn less: (Women earn 18% or $4.10 less per hour same job, $700K less over as lifetime) When they age, they are poorer: Women’s super balance $53K, Men’s $83K)

Widening income inequality More Unequal Inequality Index  Those labour market changes I outlined earlier have been a key driver of income inequality trends in Australia. The earnings gap between the 10% best and least paid full-time workers increased by a fifth between 1980 and in 2008. and underneath this earnings gap lies a gender and care gap- it is, I would argue, all about family. More Equal Source: OECD 2011 www.oecd.org/els/social/inequality

Of the top earners, 25% are fathers, just under 4% are mothers

It doesn’t go away Women’s time use by type of care HILDA Wave 9 data But the problem with time is that it doesn’t go away The time in the market just gets added to time on care and domestic work. Explain graph % women ‘often’ or ‘always’ rushed and pressed for time. ‘NILF’ refers to women not in the labour force Part-time hours 1-34 hours Full-time hours 35 + hours a week. Women’s time use by type of care HILDA Wave 9 data

Background If we want equality should women work like men (long full time hours)? Can they? What about care? What about health? Men and women do not bring to their jobs a similar set of social resources in terms of power and status, even with comparable education or other skills they do not earn as the same money for their time at their job (gender wage gap), and they do not face similar time demands (from care or unpaid work responsibilities) outside of work (gender time gap). Thus the resources and demands linked to work hours and to health are distinct for men and women (in terms of time, quality of jobs, rewards and power) generating a gendering of health resources and hazards on and off the job.

Data Six waves of Household Income and Labour Dynamics in Australia Survey (wave 5 –wave 10) Employed people, aged from 24 to 65 Series of equations that do/do not assume men and women are equal on measured and unmeasured variables including non work time demands

Methodology A simultaneous three-equation system: Eq1: Work hours = f(Lagged work hours, Mental health, Wages, X1) Eq2: Wages = f(Lagged wages, Mental health, X2) Eq3: Mental health = f(Lagged mental health, Work hours, Work hours squared, Wages, X3) X1, X2, X3 – vectors of covariates (e.g., education, marital status, non-salary household income) As you see, in this system, one dependent variable can become a predictor in the other equation. This helps us to deal with the endogeneity problem, allowing us to disentangle the causal relationships between dependent variables. by estimating the all three equations at the same time, we are able to control for the correlation between the error terms of individual equations, making the estimate more efficient In each equation, we also use the lagged dependent variable. This allows us to use the past values to predict the current values. in other words, autocorrelation are taken into account. In this equation systems, we also control for a bunch of covariates related to demographic and socio-economic characteristics. They might be overlapped between equations.

Work hour thresholds averaged over gender, all things being equal Better Mental health Figure 1 Thresholds that ignore gender: We first test the validity of the 48 hour thresholds using the 3 stage simultaneous equation approach to address endogeneity. We do this on a pooled sample, and simply adjust for gender to estimate an average tipping point. Controlling for gender we find a threshold of 40 hours per week, working past this is reflected in a deterioration in mental health, and 40 appears to be the optimal hours to work, all other covariates (including gender) being equal. The current 48 hour week therefore underestimates the true threshold for when work hours harm health. Worse 40 hours for everyone

Work hour thresholds, stratified by gender, all else not equal (real life) Better Mental health Figure 3 Gender thresholds when all else is not equal: Stratification removes the assumption that other covariates operate similarly for men and women, including unmeasured factors such as discrimination and power on and off the job, which may affect the way paid hours affect health. We find that stratification leads to a widening of the gender gap in work hour health thresholds, and the threshold lowers for women to 34 hours per week and increases for men to 47 (13 hour threshold gap) which we propose is a more accurate estimate of the work hour –health relationship for men and women and the gendered health disadvantage current limits represent. Worse 34 for women, 47 for men

Work hour thresholds, stratified by time demands (care and domestic work) all else equal Better Median unpaid time 16.8hrs Mental health Figure 4 Time or gender? Is it the unequal time resources men and women bring to their job, or are there other gender-based vulnerabilities at play? To test whether work hour –health thresholds depend on the time demands workers face off the job (which may at least partly explain the gender hour-health thresholds we have observed) we stratify the pooled sample by time spent on care and domestic work time (Huong what are the time cut-offs please?). We first estimate the work-hour health thresholds averaged across gender, on the pooled sample (which does not take into account other gendered vulnerabilities that may affect this relationship). We find that thresholds change significantly depending on non-work time resources, on average, when workers time is ‘unencumbered’, the tipping point for their health is 44 paid work hours per week. However when care and domestic work demands are relatively high, health deteriorates when work hours increase beyond 34. These findings reveal that care or domestic work demands are an important drivers of the work- hour health relationship, and challenge the notion of setting a maximum working week that is valid only for those with little or no care or other responsibilities. Worse 34 high time loads 44 low, (everyone)

Work hour thresholds, for workers without care, imagining all else was equal Better Mental health Figure 7 Gender, worktime and health if all else is equal and workers don’t have care responsibilities. What if all else was equal and neither men nor women faced significant time demands outside of work? To consider this we stratify our sample by their (nonwork) time commitments and then estimates gender differences in thresholds. Like the pooled sample analysis this approach assumes that all covariates and any unmeasured factors operate similarly for both men and women. We find that under these ‘ideal’ time and social conditions, the work hour –health thresholds converge. The three hour gap in the threshold is not significant, women’s hour-health tipping point is at its highest – 46 hours per week while men’s is 49. Under these ‘ideal and unencumbered’ social circumstances, women do not suffer a health disadvantage if they hold full time jobs and the maximum working week becomes relatively protective to both men and women’s health. Worse 46 for women, 49 for men (unencumbered)

Conclusions There is a work hour-health ceiling that varies by gender and time demands If women ‘work like men’ >40 hours they face health trade-offs, as do men or women who combine work with care Women (or those who care) must either compromise their health or entrench gender inequality In conclusion, our paper shows that there is a complexity of the interplay between work hours, wages and mental health. To our knowledge, this is the first paper examines this interplay. By using the SEM, we are able to disentangle the bi-directional relationships between them and see in which way the relationship is stronger. The paper also found different thresholds of work hours that benefits mental health. The findings in the paper confirms that time is a resource for health although it is finite.

Australia Korea Ratio of women’s to men’s unpaid time 1.8 5.0

Australia Japan Ratio of women’s to men’s unpaid time 1.8 4.8

Australia Finland 1.8 1.5 Ratio of women’s to men’s unpaid time In 2007 25% of Australian men worked 50 or more hours a week, 8% of women In Japan (note differen Working hour limits: (information from {Lee, 2007 #39} Both Japan and Finland currently have 40 hour legal limit on the normal full-time work week; Australia has just introduced a universal statutory limit on normal weekly hour limits. In Finland, 86.3% of men and 94.2% of women work at or below the legal limit. In Japan however, 73.3% of women and just 41.0% of men worked at or above the legal limit. These figures demonstrate that “standard hours are not necessarily ‘standard’ in practice”. Despite long term trends which show decreasing total work hours per employee {OECD, 2009 #42}, time use data (which is able to take increasing part-time employment into account) has demonstrated that the proportion of workers working more than 10 hours per day is increasing. In 1995, 17% of workers spent more than 10 hours per day in paid work, and this number grew to 21% in 2010 {Kobayashi, 2011 #43}. Japan also has some of the lowest leave entitlements for its workers in the OECD. Japanese workers have access to a minimum 10 days paid annual leave per year, compared to 20 days available to Australian workers and 25 days for Finnish workers. t work hours categories) 4-% of men and 13% of women Ratio of women’s to men’s unpaid time 1.8 1.5

Australia Denmark Ratio of women’s to men’s unpaid time 1.8 1.3

Australia Sweden Ratio of women’s to men’s unpaid time 1.8 1.3

Equal pay = equal time?

ACKNOWLEDGEMENTS Huong Dinh, Jenny Welsh Jenny Baxter (AIFS), Jianghong Li (WZB) ARC Linkage LP100100106 ARC Future Fellowship FT110100686 Rotary mental health grant All views I express today are mine, and I take full responsibility for them. Thank you