Spring has already made its appearance here in Norfolk. Our garden is in full bloom and I am in a particularly spring-philosophical mood today – especially so as I should soon be hearing news from the editorial office of a coveted economics journal. This concerns a paper that I submitted for publication what feels like months ago.
And just as I was reflecting on this thought, a paper by Firmuc and Paphawasit (2018) landed on my desk, evaluating the impact of physical attractiveness on academic research productivity in the field of economics. More specifically, the authors pull together information about the research productivity of about 2000 published economics researchers. They then find photos of them and rate their attractiveness (yes, seriously!) using an online survey. In particular:
Besides collecting some basic information on the authors, we also rated their attractiveness. To this effect, we circulated a number of online survey links to potential participants at Brunel University and elsewhere, using direct communication, email and social networks. Each online survey collected basic background information on the assessor (gender, age, ethnicity, highest education, and whether they are currently enrolled as a student) followed by 30 randomly-chosen and randomly-ordered photos, with each picture placed on a separate page.
…Each rater was asked to rate the attractiveness of the person in the photo on an 11-point scale, from 0 (unattractive) to 10 (very attractive). No information on the photographed individuals was provided and the raters were told that the survey studies the formation of perceptions of beauty. The raters were also asked whether they recognised the person in the picture, or whether the picture did not load properly: in such instances, their scores were excluded from the analysis.
The average beauty score was 3.9, with the most attractive academic scoring 7.6
They even attach photographs of the three most attractive male authors in their sample in an appendix (thankfully the other end of the distribution was left out – I had to check to make sure, as I was worried for a few minutes I would find my photo posted there!).
Their results show that there is a link between authors’ attractiveness and quality of journals where their papers are published, as well as number of citations that they receive. According to their findings, this association matters most for more productive authors (‘of intermediate and high productivity’), whereas there seems to be very small or no effect for less productive authors. Some of these effects disappear once controlling for journal quality:
…attractive authors tend to publish their research in better journals, but once their work is published, it does not attract more citations than other papers published in the same journal by less good-looking authors.
Although there are many methodological parts of this paper that I do not quite understand (probably because it is not my area of specialisation), it does remind us that looks do matter in labour markets. There is a well-established literature in labour economics discussing the association between appearance/beauty and wages and the so-called ‘halo effect’ (referring to the physical attractiveness premium that more attractive workers are likely to command in labour markets – see also Langlois et al., 2000; Zebrowitz et al., 2002; Kanazawa and Kovar, 2004; for a detailed discussion on this).
I was also surprised to read that this beauty bias can be also gender specific. For instance, Cash et al (1977) and Johnson et al. (2010) find that the effect goes the other way (negative impact) when considering female candidates applying for jobs traditionally perceived as ‘masculine’ ones. By contrast, male candidates are more likely to experience a positive return on good looks, irrespective of the type of job that they do (see also Johnson et al., 2010).
No surprise then that ‘guyliners’, ‘make up for men’ and other male beauty products are becoming increasingly popular amongst younger workers – in Europe it is not as common yet as it is in parts of Asia (Japan comes to mind), but I imagine it is a matter of time, as more workers realise that there are positive returns to be made!
References
- Beautiful Minds: Physical Attractiveness and Research Productivity in Economics
Institute of Labor Economics conference paper, Jan Fidrmucand Boontarika Paphawasit (July 2018)
- Maxims or myths of beauty? A meta-analytic and theoretical review
Psychological Bulletin, Vol 126(3), pp.390–423, Judith H Langlois, Lisa Kalakanis, Adam J Rubenstein, Andrea Larson, Monica Hallam and Monica Smoot (May 2000)
- Looking Smart and Looking Good: Facial Cues to Intelligence and their Origins
Personality and Social Psychology Bulletin, Leslie A Zebrowitz, Judith A Hall, Nora A Murphy, Gillian Rhodes (February 2002)
- Why beautiful people are more intelligent
Intelligence, Vol 32, pp.227–243, Satoshi Kanazawa and Jody L Kovar (2004)
- Sexism and beautyism in personnel consultant decision making
Journal of Applied Psychology, Vol 62(3), pp.301–10, Thomas Cash, Barry Gillen and D S Burns (January 1977)
- Physical Attractiveness Biases in Ratings of Employment Suitability: Tracking Down the “Beauty is Beastly” Effect
The Journal of Social Psychology, 150(3), pp.301–18, Stefanie K Johnson, Kenneth E Podratz, Robert L Dipboye and Ellie Gibbons (April 2010)
Article
Questions
- Read some of the papers posted above and explain the main argument about the link between physical attraction and wages. What does the empirical evidence show on this?
- Using examples and anecdotal evidence, do you agree with these findings?
- If these findings are representative of the real world, what do they suggest about the functioning of modern labour markets?
Women in the UK on average earn less per hour than men. According to the Annual Survey of Hours and Earnings, the mean hourly pay for women in 2015 was 17.5% less than that for men. This figure is for all employees, full and part time. As far as full-time employees is concerned, the gap was slightly smaller at 13.9%. Nevertheless, as you can see from Table 6 in the linked Excel file, these gaps have decreased in recent years – but only slightly.
A recent paper from the Institute for Fiscal Studies has disaggregated the figures to give a better picture of this wage gap. It finds that having children is a major contributing factor to the gap. It also finds that this has a bigger impact on the earnings of graduates and those without a degree but with A levels.
On entry to the labour market, men and women earn roughly the same. People’s wages tend to rise during their 20s, but men’s rise slightly faster than women’s, causing a pay gap to open and widen – but slowly at first. Average (mean) men’s wages continue to grow during their 30s and a bit during their 40s. However, average women’s wages flatline. Thus the wage gap grows substantially, especially for the higher educated.
The paper argues that the arrival of children is a major contributing factor to this picture. It looks at the gap before and after the arrival of children. “The crucial observation is that the gap opens up gradually after the first child arrives and continues to widen for many years after that point.” By 12 years after the first child is born, the wage gap has widened to 33%.
The paper does not offer reasons for the small gap that exists before the arrival of children. But it does give possible reasons for the widening gap after having children. A major one, it suggests, has to do with labour market experience.
“As women are likely to do less paid work after the arrival of children, the level of labour market experience they have falls further and further behind that of their male counterparts, and the wage gap therefore widens.” They may also miss out on promotions.
Each year a woman spends away from the labour market is associated with an average 2% drop in pay compared with those who remain in work. For those with at least A levels, the penalty is 4%; but there is no drop in pay for those without A levels.
Other possible explanations include mothers taking work that requires a lower skill level, and at lower hourly pay, in order to gain flexibility in working hours. However, the evidence suggests that women who move to part-time work on having a child suffer no immediate drop in pay. But their hourly pay does grow more slowly, thus contributing to a widening of the gap.
Another explanation is employers exercising market power to discriminate against women with children. The paper does not consider this explanation.
The articles discussing the paper look at policy implications and identify various things that can be done to narrow the gap. Read the paper and articles and try answering the questions below.
Videos and podcasts
IFS: gender pay gap widens after first child Compendium of News Reports from BBC News at Six, Channel 4 News, ITV News at Ten and BBC Newsnight from Incorrigible Forever on YouTube (23/8/16)
Gender Pay Gap Hits Women With Children Hardest Sky News (23/8/16)
In Business: Supportive partner = success at work World of Business, BBC Radio 4, Peter Day (25/8/15)
Gender Pay Gap More or Less, BBC Radio 4, Tim Harford (26/8/16)
Gender pay gap: Why do mums increasingly earn less? BBC Victoria Derbyshire programme (23/8/16)
Articles
UK women still far adrift on salary and promotion as gender pay gap remains a gulf The Guardian, Katie Allen (23/8/16)
Gender pay gap: mothers returning to work earn a third less than men The Telegraph, Tim Wallace (23/8/16)
Mothers’ pay lags far behind men BBC News (23/8/16)
Four ways the gender pay gap isn’t all it seems BBC News Magazine, Simon Maybin (29/8/16)
Six ways to tackle the gender pay gap BBC News, Emma Atkinson (23/8/16)
Wage gap for UK women unchanged in 20 years Financial Times, Gemma Tetlow (23/8/16)
The UK’s slow march to gender pay equality Financial Times (23/8/16)
Gender Pay Gap For Mothers Widens For 12 Years After Having Children, New Research Finds Huffington Post, Jack Sommers (23/8/16)
Motherhood costs women a third of their salary compared to men, report reveals Independent, Joe Watts (23/8/16)
The gender pay gap means that more women will be in poverty later in life – but there is something the government can do Independent, Claire Turner (26/8/16)
Gender pay gap won’t close until 2069, says Deloitte The Guardian, Katie Allen (24/9/16)
Papers and Reports
Gender wage gap grows year on year after childbirth as mothers in low-hours jobs see no wage progression IFS Press Release (23/8/16)
The Gender Wage Gap IFS Briefing Note BN18, William Elming , Robert Joyce and Monica Costa Dias (23/8/16)
Women in STEM: Technology, career pathways and the gender pay gap Deloitte (September 2016)
Data
Gender pay differences: Annual Survey of Hours and Earnings: 2015 Provisional Results ONS Statistical Bulletin (18/11/15)
All data related to Annual Survey of Hours and Earnings: 2015 Provisional Results ONS datasets (18/11/15)
ASHE 1997 to 2015 selected estimates (See Tables 1 to 4, 6 and 9) ONS dataset (18/11/15)
All Employees – ASHE: Table 1 ONS dataset (18/11/15)
Questions
- Identify possible reasons for the wage gap between men and women.
- Why is the median wage gap different from the mean wage gap?
- Why is the wage penalty for periods without work greater for more highly educated women?
- To what extent is the gender wage gap a reflection of marginal productivity differences?
- Is the gender pay gap primarily about men and women being paid differently for doing the same job?
- What evidence is provided by the Chartered Management Institute (CMI) on women’s lack of pay progression?
- What could the government do to reduce the wage gap?
- Discuss the relative effectiveness of different policy alternatives.
It was the 12th May 2010 and George Osborne’s first day as the UK’s new Chancellor of the Exchequer. His arrival at HM Treasury coincided with the latest ONS labour market release. Just in case you were rather distracted by political events, we take the opportunity here to trawl through some of the latest labour market numbers, focusing, in particular, on those that may pose real challenges for George Osborne and the new coalition government.
From the ONS release we observe that in the three months to March the total number of economically active individuals in the UK was 31.340 million. Of these, 28.829 million were employed while 2.510 million were unemployed (but actively seeking work). The number of people employed fell by 76,000 over the quarter (and by 341,000 over the year) while the number unemployed rose by 53,000 (279,000 over the year).
Now we consider the rate of unemployment. The unemployment rate expresses the total number unemployed as a percentage of those economically active. Over the first quarter of 2010 the unemployment rate rose to 8.0%, a rise of 0.2 percentage points on the previous quarter and a rise of 0.9 percentage points from a year earlier. It is the highest quarterly unemployment rate since the 8.1% recorded in Q3 1996.
Next, consider unemployment and gender. Of those unemployed in the first quarter of the year, 61.6% were male and 38.4% were female. The increase in the male unemployment rate during the economic slowdown has been especially marked. The male unemployment rate in Q1 2010 rose to 9.2%, up from 7.9% a year ago and 5.6% two years ago. The female unemployment rate has increased to 6.7% in Q1 2010 from 6.1% in Q1 2009 and 4.8% in Q1 2008. Therefore, over the past two years the male unemployment rate has risen by 3.6 percentage points while the female rate has increased by 2.1 percentage points.
Another troubling issue is unemployment amongst the young. The unemployment rate amongst those aged 18-24 is considerably higher than the overall rate. In the three months to March the unemployment rate for this age group was 17.9% compared with the overall rate of 8%. But, more than this, the current rate of unemployment amongst those aged 18-24 is actually higher than during the early 1990s when it peaked at 17.8% in Q1 1993. The male unemployment rate amongst this age group is especially high having risen to 20.7% in the first quarter of the year, up 2 percentage points on the year and up from 14.2% in Q1 2008. The female rate amongst this age group is 14.6%, up 1.3 percentage points on the year and up from 9.8% in Q1 2008.
Another issue that emerges out of the statistics is the rise in long-term unemployment. The number of people unemployed for more than one year rose to 757,000 in the first quarter, up from 509,000 a year ago and 397,000 two years ago. Perhaps, it is easier to see the magnitude of this problem when we note that 30.2% of those unemployed have been unemployed for at least one year – this is up from 24.5% in Q1 2008. Amongst females, 25% of those unemployed have been without work for at least one year, but amongst males this rises to 33.4%. In other words, one-quarter of unemployed females and one-third of unemployed males are now regarded as being long-term unemployed.
As troubling as these numbers are, the issue of long-term unemployment is one that, over the past two decades, has never really gone away. On average since 1992, 29.4% of those unemployed have been without work for at least one year (34.2% amongst men and 21.6% amongst women).
And now to our final observation: the historically high number of economically inactive individuals of working age. In the first quarter of 2010, 8.166 million of those of working age were economically inactive, up by 86,000 over the year. As a proportion of the working population, this equates to 21.5%, which is not in itself a record high – during 1983 it reached 23.2% – but it is, nonetheless, up from 20.7% a year ago. The inactivity rate amongst those of working age is highest amongst females at 25.9% (up from 25.7% a year ago) compared with 17.4% amongst men (up from 16.1% a year ago).
One factor that helps to explain the overall rise in inactivity is the 43,000 increase in the number of students who have become economically inactive over the past year. But, we also note upward pressures on inactivity over the past year from the increase of 37,000 in the number of people who are ‘long-term sick’ and from the 13,000 increase in the number who feel ‘discouraged’ from seeking work. These pressures highlight some of the many costs that arise from unemployment and potentially raise some tricky policy challenges for the new government.
Articles
UK unemployment rises in first quarter Investment Week, Hannah Smith (12/5/10)
UK unemployment climbs to a 16-year high Irish Independent, Svenja O’Donnell Brian Groom (13/5/10)
UK unemployment increases to 2.51 million BBC News (12/5/10)
Unemployment: what the experts say Guardian (12/5/10)
UK unemployment hits highest since 1994 The Times, Robert Lindsay (12/5/10)
Jobs recovery still fragile, ‘dire’ data shows Financial Times, Brian Groom (12/5/10)
Scottish unemployment rises by 10,000 in three months BBC News (12/5/10)
Unemployment rises to highest level since 1994, ONS says inthenews.co.uk, Sarah Garrod (12/5/10)
Data
Latest on employment and unemployment Office for National Statistics (12/5/10)
Labour Market Statistics, May 2010 Office for National Statistics (12/5/10)
Labour market statistics page Office for National Statistics
For macroeconomic data for EU countries and other OECD countries, such as the USA, Canada, Japan, Australia and Korea, see:
AMECO online European Commission
Questions
- What is meant by somebody being economically active? Do they have to be in a job to be economically active?
- Using the figures in the commentary, calculate the number of economically active people in Q1 2009 and so the change up to Q1 2010.
- If the number of people unemployed rises does this mean the rate of unemployment rises? Explain your answer.
- What factors might explain the persistent problem of long-term unemployment? What policy prescriptions would you offer the new coalition government in attempting to tackle this problem?
- Looking back through the commentary, pick out some of the notable gender differences. What factors might help to explain these?
- Are there any factors identified in the commentary that may be affecting the economy’s potential output?