Many are boasting good news on the ‘gender wage gap’—I agree, it’s great news: the Office for National Statistics’ findings offer more proof that wage gaps have very little to do with gender, and much more to do with choices each gender is prone to make.
The average full-time pay gap between men and women is at its narrowest since comparative records began in 1997, official figures show.
The difference stood at 9.4% in April compared with 10% a year earlier, the Office for National Statistics (ONS) said, a gap of about £100 a week.
This as well:
Hourly earnings figures reveal that, in April 2014, women working for more than 30 hours a week were actually paid 1.1% more than men in the 22 to 29 age bracket and, for the first time were also paid more in the 30 to 39 age bracket…
…The government said that, from next year, it was extending the rights for shared parental leave. It had also invested in training and mentoring for women to move into higher skilled, higher paid jobs, and guidance to women looking to compare their salaries with male counterparts.
Women, from the start of their careers, are now earning a higher salary than men; and, if they choose to make the decision to stay in the work force, they are more likely to be promoted than their male counterparts as well.The real gap, it seems, is not between women and men, but between mothers and child-less women. Leaving a job early on in one’s career or for an extended period of time to have children will impact a women’s salary when she returns to the work force.
As this is the case, I think the government is probably right to extend rights for shared parental leave (though the money put into training will surely be a waste; women who are ambitious and attracted to careers in science, business, and formerly male-dominated sectors aren’t having much trouble pursuing them). But anything legislated from the top-down can only go so far to change cultural opinions that have been in place for centuries about the role of women and the household.
In reality, women’s choice in their private and home lives will be the greatest determinate as to what further changes we see in wage gaps. It seems there’s evidence that good economic climates actually lead more women to stay at home with their kids rather to go out and get jobs – at the same time, we are witnessing an increase in stay-at-home-dads, which, most likely, has multiple reasoning to it: more women are demanding to work, and more men feel comfortable making the choice to stay home.
Either way, it seems there is no obvious discrimination between men and women when they enter the work place; as far the element of motherhood is concerned, we should be less focused on the numbers and far more focused on ensuring that women are not being socially pressured, either way, to make any decision that is not completely their own.
We’re often told that the UK is one of the most unequal countries in Europe. We’re also often told that this is bad, very bad, and something must be done. We’ve pointed out a number of times that there’s another difference in the UK economy, something that makes us rather different from other European economies. And that’s the massive importance of London in our economy. In the latest release of figures from the ONS we can see this quite clearly too:
The UK’s highest earners live in Wandsworth, Westminster, and Richmond upon Thames – all in London.
The weekly wage of the average worker in those areas was £660.90, £655.70 and £655 respectively in April 2014.
At the other end of the spectrum, the average weekly earnings of someone in West Somerset were just £287.30.
The ONS prefers to use the median as its measure of average earnings “as it is less affected by a relatively small number of very high earners and the skewed distribution of earnings”.
Because we’re using the median we’re not just recording those bankers in the City there. This is the number which 50% of the people earn more than and 50% less than in each area. And a goodly part of that recorded UK inequality is because of these regional differences in income.
It’s also true that living costs vary wildly across the country. Most especially housing costs of course although that’s not all. London prices for a pint would choke a fellow from West Somerset just as much as rents or house prices would do.
Given that this is all so then actual inequality is rather lower than we’re always told it it. For, of course, we should, if we’re going to be concerned about inequality at all, be concerned about inequality of consumption. And if people in one part of the country have higher wages but also face higher living costs then that’s an inequality that shouldn’t be concerning us.
In no other European country is the capital such a dominant force or influence in the economy,. Thus our inequality is different from their: and arguably our inequality is lower than it is elsewhere, given this specific difference.
The socioeconomic profile of drinkers and smokers across countries are similar. Smoking and drinking is more prevalent amongst the less fortunate, the disadvantaged and the uneducated. In the UK, it is no different. Hiscock, Bauld, Amos & Platt (2012) found that smoking rates were four times higher amongst the disadvantaged versus the more affluent (60.7% versus 15.3% – the factors that determined disadvantage included unemployment, income, housing tenure, car availability, lone parenting and an index of multiple deprivation).
Fone, Farewell, White, Lyons & Dunstan (2013) found that “respondents in the most deprived neighbourhoods were more likely to binge drink than in the least deprived (adjusted estimates: 17.5% versus 10.6%…)”. Clearly, the incidence of these taxes falls disproportionately on the disadvantaged.
People often smoke and drink for pleasure; this means that these taxes stifle those with fewer resources from attaining pleasure. Conversely, affluent people generally have less trouble substituting consumption goods or in quitting substance use altogether. This prevention of stress alleviation and pleasure attainment will be reflected in sub-potential labour productivity.
The Biopsychosocial model of health suggests that any biological health benefits could be offset by the emotional and financial strain that these taxes induce. The situation is worse for those who are both addicted and poor since they substitute consumption even less than their poor, non-addicted counterparts (thereby reducing their consumption of other important goods). This simultaneously deprives their dependents (quite often children).
A primary concern is that the increase in smoking and drinking will cause several negative externalities (especially in the form of increased healthcare costs). One should consider that, if a drinker or a smoker is aware of the threat of liver failure or lung cancer and yet they choose to ignore it, it is ultimately their choice, their body and their health. A certain degree of respect must be afforded to choice especially since we cannot fully empathise with others.
However, one’s disregard for one’s own health often incurs costs for taxpayers whilst, personally, there are negligible financial costs. In this sense, many may feel disinclined to take care of their health as they might have if treatments weren’t free. So whilst the NHS is still around in its current form, it makes (some, albeit limited) sense to heavily tax alcohol and tobacco. Alternatively, a healthcare system that is at least partially privatised (e.g healthcare vouchers) would enable lower taxation of the disadvantaged and impoverished.
According to Huebner (2005) the per capita rate of innovation has been falling steadily since 1873 (it doesn’t look quite like that from the chart below, which is just of patents, because patent laws changed a lot during the period). He constructs an index of innovation by looking at independently-created lists of events in the history of science and technology and from US patent records and compares them to the world population.
Woodley (2012), looking at the numbers for a different purpose, compared them with three alternative indices of development, and found that they correlated well with different numbers gathered for different purposes. For example, they correlate highly (with a coefficient of 0.865) with the numbers in Charles Murray’s Human Accomplishment, which quantifies contributions to science and arts partly by how much space encyclopaedias devote to particular individuals.
It also correlates 0.853 with Gary (1993)‘s separate index, which was computed from Isaac Asimov’s Chronology of Science and Discovery. Finally, it correlates with another separate index, created in Woodley (2012), computed from raw numbers in Bryan Bunch & Alexander Hellemans (2004) The History of Science and Technology, and divided only by developed country population numbers in case there is something special about them in creating innovation.
The result seems quite robust, although I am hoping my friend Anton Howes (who has an excellent new blog on the industrial revolution, and is working on a PhD on innovation and the industrial revolution) will construct an even better index. Should we worry?
There are a few reasons for optimism. Firstly, the population is going up, so per capita declines in innovation are being counteracted by there being more people around to innovate. For example, even if Gary (1993) is right in thinking there has been a roughly five-fold decline in per capita innovation in the past 100 years—there has been almost a four-fold increase in population, balancing much of that out. Secondly, some of the innovations we are getting will allow us to raise our IQ—including genetic engineering and iterated embryo selection—and we know that IQ is one important factor in innovation. Thirdly and finally, there are many countries (such as China and India) who have so far been too poor to have many of their population engaged in innovative activities, but who will surely soon be.