Heather Joshi’s presentation to the UCL Institute of Clinical Trials and Methodology, 7th June 2021

Foliano, F

Joshi, H

Wilkinson, D

English

UCL Discovery

The Gender Pay Gap in the British cohort studies, past, present and future.Heather Joshi, Dave Wilkinson, Francesca FolianoUCL Institute of Social ResearchInstitute of Clinical Trials & Methodology Seminar, June 7th, 2021Motivation• Unequal pay for equal work by men and women is inequitable, inefficient, and since 1970, unlawful in UK• It introduces bias against the use of female talent and reinforces unequal gender relations• This talk reviews some evidence on whether a pay penalty for women is becoming a thing of the past.Outline• History of pay gap observed between women and men in national British  data• Components of pay gap• Explained by differences in characteristics and differences in remuneration• Analysis of pay gap in birth cohort studies- extracts from several papers• Over life-cycle• Over the earnings distribution at  given ages• Comparison with recently published findings on pay gaps for doctors• Future of gender pay gapSecular trend in gender pay gap: various series and some policy landmarks0%10%20%30%40%50%60%1921 1931 1941 1946 1951 1956 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011 2016 2020Gender Gap in hourly pay, 1921-2020, per cent of men's averageFT Manual FT All  NES FT All   ASHE All workers: ASHEEqual PayActEqualities ActNational MinimumWageFalling trend with time: age pattern within cohortsTrend within the pay distribution since 1998: difference has fallen least among top earners• Narrowing gap for low earners especially since National Minimum Wage  of 1999• Widening gender gaps at the top of the earnings distribution and some well-paid occupations.• In this context we turn to recent studies of the pay gap in medicine  at the end of this presentation to complement evidence within the national cohort studiesNotional components of  the Gender Pay Gap• Personal (human capital) characteristics contributing to productivity• Job characteristics • ‘Equal work’ under Equal Pay Act• May contribute to unequal treatment if  allocation  to job type is discriminatory – subject of other equal opps law• UNEXPLAINED• RESIDUAL/ ‘adjusted’ ‘standardized’ componentUnequal rewards to a given characteristic for men and women.• Could arise from omitted explanatory factors (eg data without work histories)Contributions to components• Human capital characteristics• Education• Skills• Age• Experience• Family responsibilities• Job characteristics• Full/part-time• Occupation• vertical or horizontal segregation• Employer characteristics• Sector, contract, bargaining, size,  institutional structure• UNEXPLAINEDUnequal rewards to a given characteristic for men and womenarising from:• Employer/ee preference against hiring, promoting, training or retaining women,  institutional culture• Women’s preference for flexibility or female workmates• Lower bargaining power and travel range    • Asymmetric social expectations of men’s and women’s family roles.Some arguably discriminatoryAnalysis• Dependent Variable• Log of hourly wages at time of interview, all employees: • RPI deflated• Blocks of controls• Education – highest qualification• plus controls for region etc• Work history • months in full and part-time jobs over all years since school leaving• (months in current job)• Family composition• Presence of dependent children by age, presence of a partner, ever been a parent of co-resident childMethods• Analysis performed on log wages rather than ratios • gap in log and percentage points very similar up to around 15% of male wages but it can be added up)An accounting exercise not an exploration of causalityDecomposition  - Oaxaca-Blinder  (Kitigawa) • Explained gap,- difference in characteristics; • Parameter gap,  differences in treatment• Various formulae  for weighting used here, some allow for an interaction of remuneration and attributes• Explanatory variables with and without job characteristicsData from the British Cohort Studies• 1946 National Survey of Health and Development• Continues into their 70s• We use age 26 sweep , 1972• National Child Development Survey (NCDS)• 1958 Birth cohort, 9 sweeps to age 55 • Originally ca 1800  births in GB• we use 6 sweeps 23-55, mostly omitting postal at age 46• British Cohort Survey (BCS)• 1970 birth cohort, 9 sweeps to age 42• Originally ca 1800  births in GB• We use 5 sweeps 26 to 42 including postal at 26• Next Steps (NS) • formerly Longitudinal Study of Young People in England, born 1989/90• We use data from interview in 2015, age 25Gender differences in pay are underlain by gender difference in employment participation. In NCDS the main employment gap(full-time), starts in childrearing ages010203040506070809010023 33 42 46 50 55% employedMale all employedMale All employeeMale FTFemale all employedFemale All employeeFemale -FTAll employed = employees + self employedThe work experience of workers  NCDS0510152025303540men 23 33 42 50 55 women 23 33 42 50 55Years of work experience: wage samplesfulltime part-time0.150.340.400.340.320.300.320.360.310.280.1600.2730.1800.1220.1080.000.050.100.150.200.250.300.350.400.4523 33 42 50 55Rawmodel 1 EDUCATION etcmodel 3 ED +FAMmodel 4 ED +EXP+FAMGender pay gap: NCDS  23 - 55, logs: raw and adjustedPay gaps from youth to midlife: two cohortsExplained gap fell more than unexplainedNB  NCDS reworked, Gaps adjusted for qualifications, work experience and region0.400.180.000.100.200.300.400.5023 33 42Log pay gap at meanNCDS born 1958Raw Adjusted0.330.150.000.100.200.300.400.5026 30 34 38 42Log pay gap at meanBCS born 1970Raw AdjustedDecomposition across the distribution at mid-life: encounters with a glass ceiling?NB Gaps adjusted for qualifications, work experience and region0.370.430.050.250.000.100.200.300.400.500.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9Quantile effect -log pointsNCDS born 1958 at age 42Total difference Effects of characteriticsEffects of coefficients0.310.350.050.200.000.100.200.300.400.500.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9Quantile effect -log pointsBCS born 1970 at age 42Total difference Effects of characteriticsEffects of coefficientsYoung adults across cohort studies 1972-2015, Gender pay gap adjusted for human capital*-0.0500.050.10.150.20.250.30.350.41972 26 1981 23 1996  26 2015 25log pay gap at meanUnexplained Explained ( by HC)1946 NSHD1958 NCDS1970 BCS 1990 N Steps* Quals, experience ( all) ; cognitive scores @11 (NSHD); subject studied, family, (NCDS-NS); attitudes @16( NCDS+NS)No adjustment for selection into wage sample.Young adults ( 23.26.25) GPG across the distribution Human capital adjustment** Quals, subject studied,  experience, family, attitudes at 16( NCDS+NS)Next Steps Age 25  in 2015Widening gaps within highest paid jobsAdjusted for Human Capital Adjusted also for Job Characteristics**Occupation at  1 digit; % female and % graduate in 4 digit occupation, hoursRecent studies of the gender pay gap within an elite occupation - medicine •Dept of Health and Social Care ( 2020)•Mend the Gap: The Independent Review into Gender Pay Gaps in Medicine in England•Chair - Professor Dame Jane Dacre, •Lead Researcher - Professor Carol Woodhams ( U of Surrey Business School, et al)NHS payroll  Quoting here total pay, not just basic, from one set of earners.Melanie Jones and Ezgi Kaya ( 2021)The Gender Pay Gap in UK Medicine• Cardiff University and  Institute of Labor Economics (IZA discussion paper 14177),ASHE (tax) records, medical practitioners in public sector and other groupsRecent analyses of gender pay gap in medicineJones & Kaha 2021, hourly pay, public sector doctors ( hospital  and some salaried GPS)Mend the Gap,  FTE of total pay NHS mainly hospital doctors0 0.1 0.2 0.3NHS hospital doctors 2009-2018, EnglandPublic sector doctors 2018, UKlog pay gapboth control for age, and  various other  characteristicsExplained, grade/speciality not includedExplained includingGrade/specialityUnexplainedVertical segregation by NHS Grades‘Glass ceiling’ within medicineJones and Kaha 2021, using ASHE 2018ASHE. 2018Decomposition of log hourly pay gap at percentiles, depends on sector Jones and Kaha 2021The future?• Over time, GPG has reduced, helped by a number of policies affecting unequal treatment of male and female workers and narrowing differences in their human capital.• Differences remain, particularly among parents, higher earners and some elite occupations, including parts of medicine• Policies to tackle differences in culture in the workplace and some pay-setting institutions  are still needed to speed the pipeline of cohort succession.• Meanwhile the impact of the pandemic on the distribution of employment and future career records is likely to provide a new source of female disadvantage, differential employment records and differential rates of pay for male and female parents.• Working from home may exacerbate or redress  the unequal pay of mothers and fathers – but that is still under investigation in our project.Thank you for your attentionand commentsPlease  visit our websitehttps://www.ucl.ac.uk/ioe/departments-and-centres/centres/quantitative-social-science/gender-wage-gap-evidence-cohort-studies

The Gender Pay Gap in the British cohort studies, past, present and future

https://discovery.ucl.ac.uk/10129266/1/GPG_%20Past_Present_FutureJUNE72021.pdf

The Gender Pay Gap in the British cohort studies, past, present and future

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