Infogr.am and data wrapper compared
19 Feb 2017 Leave a comment
in administration, gender, labour economics Tags: gender wage gap
Occupational segregation a weak reed to hang #genderwagegap @FairnessNZ
17 Feb 2017 Leave a comment
in applied price theory, discrimination, economics, gender, health and safety, human capital, labour economics, labour supply, occupational choice, poverty and inequality Tags: gender wage gap, occupational segregation
NZ has a gender wage gap of 6% according to the OECD and 12% according to the Ministry of Women’s Affairs, with 30% of that explained by occupational segregation. That is 2 to 4 percentage points.
You have to explain occupational segregation. Men are represented more in occupations that are riskier. They are paid more for that. There are systematic differences in the occupational choices of married parents, single parents and single mothers regarding the risks of injury. Again, that feeds into wages.
Occupational segregation explains 2 to 4 percentage points of wages. Given that risk premiums – danger money – and trading lower wages for greater flexibility in a job can easily reduce wages or increase them by 2-4%, occupational segregation is simply a proxy for measurement error.
Still more of wage premiums has to be poured into this 2-4% of wages such as occupational segregation in unsocial work hours. Many more women than men work 9 to 5 during the week. Men would then have a wage premium for working nights and weekends. A hell a lot has to be explained away by just 2 to 4% wages.
What does undervalued work mean? Does it mean it is very profitable to employ women in certain occupations such as caring. That implies that high profits will lead new firms to enter these industries bidding up wages and equalising them with other competing jobs.
More on who is winning the battle of the sexes
09 Feb 2017 Leave a comment
in discrimination, economics of education, gender, human capital, labour economics Tags: behavioural genetics, educational psychology, gender gap, gender wage gap, reversing gender gap
Why no progress on the gender wage gap in @SenSanders’ favourite countries
02 Feb 2017 Leave a comment
Gender pay gap by British generations
28 Jan 2017 Leave a comment
in discrimination, gender, labour economics Tags: gender wage gap
Is America an imperialist, white-supremacist, capitalist patriarchy? | FACTUAL FEMINIST
21 Jan 2017 2 Comments
in defence economics, development economics, discrimination, gender, labour economics Tags: feminism, foreign policy, gender wage gap, imperialism, racial discrimination, racism
British gender pay gap now negative for 20 something women
13 Jan 2017 Leave a comment
in discrimination, gender, human capital, labour economics, labour supply, occupational choice, poverty and inequality Tags: British economy, gender wage gap, reversing gender gap
10 Male “Privileges”
10 Dec 2016 Leave a comment
in discrimination, economics of crime, gender, health economics, human capital, labour economics, labour supply, law and economics, occupational choice Tags: gender wage gap, reverse gender gap
Undergraduate majors favoured by women pay less 10 years after graduation
02 Dec 2016 Leave a comment
Women Working: What’s the Pill Got to Do With It?
01 Dec 2016 Leave a comment
in applied price theory, discrimination, economic history, economics of education, gender, health economics, human capital, labour economics, labour supply, occupational choice Tags: contraception, gender gap, gender wage gap
Skill-specific atrophy rates drive the STEM gender gap
08 Nov 2016 Leave a comment
in discrimination, economics of education, gender, human capital, labour economics, minimum wage, occupational choice Tags: gender wage gap, reversing gender gap
Rendall and Rendall (2016) found that women prefer occupations where their skills depreciate slowest when taking time out from motherhood. Verbal and reading skills depreciate at a far slower rate than mathematical and scientific skills so this gives women yet another strong reason to avoid science, technology, engineering and maths (STEM) careers.
we show that college educated women avoid occupations requiring significant math skills due to the costly skill atrophy experienced during a career break. In contrast, verbal skills are very robust to career interruptions.
The results support the broadly observed female preference for occupations primarily requiring verbal skills – even though these occupations exhibit lower average wages. Thus, skill-specific atrophy during employment leave and the speed of skill repair upon returning to the labour market are shown to be important factors underpinning women’s occupational outcomes.
Not only do women have vastly superior verbal and reading skills, worth somewhere near 6 to 12 months extra schooling, these skills do not depreciate much during career breaks. Indeed, reading and verbal skills tend to naturally increase with age until your late 60s.
Source: Reading performance (PISA) – International student assessment (PISA) – OECD iLibrary.
Maths skills get rusty if not used while knowledge of computer languages and the like and of specific technologies can be quickly overtaken by events while on maternity leave. Rendall and Rendall (2016) again
… college educated females avoid math-heavy occupations, and pursue verbal-heavy occupations instead. This is due to the high skill atrophy associated with math skills, and the ability of verbal skills to act as “skill insurance” against gaps.
Additionally, for college educated individuals, math is the skill most vulnerable to loss during employment gaps, which also implies a slow rebuilding post-break. In contrast, non-college educated individuals experience a much smaller math skill loss.
Rendall and Rendall’s point about college educated women avoiding maths heavy occupations even if it costs them wages so as to maximise the lifetime income may explain the larger gender wage gap at the top of the income distribution than at the bottom.
At the bottom of the income distribution, skill atrophy do not really matter much. At the top, it do. Women make occupational choices where annual income may be lower but lifetime income may be higher because of the lower rates of skill depreciation when they are out having children.
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