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!
- 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)
- 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?
How would your life be without the internet? For many of you, this is a question that may be difficult to answer – as the internet has probably been an integral part of your life, probably since a very young age. We use internet infrastructure (broadband, 4G, 5G) to communicate, to shop, to educate ourselves, to keep in touch with each other, to buy and sell goods and services. We use it to seek and find new information, to learn how to cook, to download music, to watch movies. We also use the internet to make fast payments, transfer money between accounts, manage our ISA or our pension fund, set up direct debits and pay our credit-card bills.
I could spend hours writing about all the things that we do over the internet these days, and I would probably never manage to come up with a complete list. Just think about how many hours you spend online every day. Most likely, much of your waking time is spent using internet-based services one way or another (including apps on your phone, streaming on your phone, tablet or your smart TV and similar). If your access to the internet was disrupted, you would certainly feel the difference. What if you just couldn’t afford to have computer or internet access? What effect would that have on your education, your ability to find a job, and your income?
Martin Jenkins, a former homeless man, now entrepreneur, thinks that the magnitude of this effect is rather significant. In fact, he is so convinced about the importance of bringing the internet to poorer households, that he recently founded a company, Neptune, offering low-income households in the Bronx district of New York free access to online education, healthcare and finance portals. His venture was mentioned in a recent (and very interesting) BBC article – a link to which can be found at the end of this blog. But is internet connectivity really that important when it comes to economic and labour market outcomes? And is there a systematic link between economic growth and internet penetration rates?
These are all questions that have been the subject of intensive debate over the last few years, in the context of both developed and developing economies. Indeed, the ‘digital divide’ as it is known (the economic gap between the internet haves and have nots) is not something that concerns only developing countries. According to a recent policy brief published by the New York City Comptroller:
More than one-third (34 percent) of households in the Bronx lack broadband at home, compared to 30 percent in Brooklyn, 26 percent in Queens, 22 percent in Staten Island, and 21 percent in Manhattan.
The report goes on to present data on the percentage of households with internet connection at home by NYC district, and it does not take advanced econometric skills for one to notice that there is a clear link between median district income and broadband access. Wealthier districts (e.g. Manhattan Community District 1 & 2 – Battery Park City, Greenwich Village & Soho PUMA), tend to have a significantly higher share of households with broadband access, than less affluent ones (e.g. NYC-Brooklyn Community District 13 – Brighton Beach & Coney Island PUMA) – 88% of total households compared with 58%.
But, do these large variations in internet connectivity matter? The evidence is mixed. On the one hand, there are several studies that find a clear, strong link between internet penetration and economic growth. Czernich et al (2011), for instance, using data on OECD countries over the period 1996–2007, find that “a 10 percentage point increase in broadband penetration raised annual per capita growth by 0.9–1.5 percentage points”.
Another study by Koutroumpis (2018) examined the effect of rolling out broadband in the UK.
For the UK, the speed increase contributed 1.71% to GDP in total and 0.12% annually. Combining the effect of the adoption and speed changes increased UK GDP by 6.99% cumulatively and 0.49% annually on average”. (pp.10–11)
The evidence is less clear, however, when one tries to estimate the benefits between different types of workers – low and high skilled. In a recent paper, Atasoy (2013) finds that:
gaining access to broadband services in a county is associated with approximately a 1.8 percentage point increase in the employment rate, with larger effects in rural and isolated areas.
But then he adds:
most of the employment gains result from existing firms increasing the scale of their labor demand and from growth in the labor force. These results are consistent with a theoretical model in which broadband technology is complementary to skilled workers, with larger effects among college-educated workers and in industries and occupations that employ more college-educated workers.
Similarly, Forman et al (2009) analyse the effect of business use of advanced internet technology and local variation in US wage growth, over the period 1995–2000. Their findings show that:
Advanced internet technology is associated with larger wage growth in places that were already well off. These are places with highly educated and large urban populations, and concentration of IT-intensive industry. Overall, advanced internet explains over half of the difference in wage growth between these counties and all others.
How important then is internet access as a determinant of growth and economic activity and what role does it have in bridging economic disparities between communities? The answer to this question is most likely ‘very important’ – but less straightforward than one might have assumed.
- Comptroller, New York City, Internet Inequality
- Czernich, N., Falck, O., Kretschmer, T. and Woessmann, L., 2011, Broadband infrastructure and economic growth, The Economic Journal, 121(552), pp.505–32
- Koutroumpis, P., 2018, The economic impact of broadband: evidence from OECD countries, Ofcom
- Atasoy, H., 2013, The effects of broadband internet expansion on labor market outcomes, ILR Review, 66(2), pp.315–45
- Forman, C., Goldfarb, A. and Greenstein, S., 2009, The Internet and Local Wages: Convergence or Divergence? (No. w14750), National Bureau of Economic Research
- Is there a link between economic growth and internet access? Discuss, using examples.
- Explain the arguments for and against government intervention to subsidise internet access of poorer households.
- How important is the internet to you and your day to day life? Take a day offline (yes, really – a whole day). Then come back and write about it.
I admit it, the title of my blog today is a little bit misleading – but at the same time very appropriate for today’s topic. Nancy Sinatra certainly wasn’t thinking about emigration when she was singing this song – it had nothing to do with it, after all. It is, however, very relevant to economists: Indeed, there are many economics papers discussing the effects of skilled immigration on host and source economies and regions.
Economists often use the term ‘brain drain’ to describe the migration of highly skilled workers from poor/developing to rich/developed economies. Such flows are anything but unusual. As The Economist points out in a recent article, ‘[I]n the decade to 2010–11 the number of university-educated migrants in the G20, a group of large economies that hosts two-thirds of the world’s migrants, grew by 60% to 32m according to the OECD, a club of mostly rich countries.’.
The effects of international migration are found to be overwhelmingly positive for both skilled migrant workers and their hosts. This is particularly true for highly skilled workers (such as academics, physicians and other professionals), who, through emigration, get the opportunity to earn a significantly higher return on their skills that what they might have had in their home country. Very often their home country is saturated and oversupplied with skilled workers competing for a very limited number of jobs. Also, they get the opportunity to practise their profession – which they might not have had otherwise.
But what about their home countries? Are they worse off for such emigration?
There are different views when it comes to answering this question. One argument is that the prospect of international migration incentivises people in developing countries to accumulate skills (brain gain) – which they might not choose to do otherwise, if the expected return to skills was not high enough to warrant the effort and opportunity cost that comes with it. Beine et al (2011) find that:
Our empirical analysis predicts conditional convergence of human capital indicators. Our findings also reveal that skilled migration prospects foster human capital accumulation in low-income countries. In these countries, a net brain gain can be obtained if the skilled emigration rate is not too large (i.e. it does not exceed 20–30% depending on other country characteristics). In contrast, we find no evidence of a significant incentive mechanism in middle-income, and not surprisingly, high-income countries.
Other researchers find that emigration can have a significant negative effect on source economies (countries or regions) – especially if it affects a large share of the local workforce within a short time period. Ha et al (2016), analyse the effect of emigration on human capital formation and economic growth of Chinese provinces:
First, we find that permanent emigration is conducive to the improvement of both middle and high school enrollment. In contrast, while temporary emigration has a significantly positive effect on middle school enrollment it does not affect high school enrollment. Moreover, the different educational attainments of temporary emigrants have different effects on school enrollment. Specifically, the proportion of temporary emigrants with high school education positively affects middle school enrollment, while the proportion of temporary emigrants with middle school education negatively affects high school enrollment. Finally, we find that both permanent and temporary emigration has a detrimental effect on the economic growth of source regions.
So yes or no? Good or bad? As everything else in economics, the answer quite often is ‘it depends’.
- Open future: What educated people from poor countries make of the “brain drain” argument
The Economist, R.S. (27/8/18)
- Brain drain, brain gain, and economic growth in China
China Economic Review, Wei Ha, Junjian Yi and Junsen Zhang (April 2016)
- A Panel Data Analysis of the Brain Gain
World Development, Michel Beine, Ric Docquier and Cecily Oden-Defoort (Vol 39, No 4, pp 523–532, 2011)
- ‘The brain drain makes a bad situation worse, by stripping developing economies of their most valuable assets: skilled workers’. Discuss.
- Using Google, find data on the inflows and outflows of skilled labour for a developing country of your choice. Explain your results.
- ‘Brain drain’ or ‘brain gain’? What is your personal view on this debate? Explain your opinion by using anecdotal evidence, personal experience and examples.
- Referring to the previous question, write a critique of your answer.
The UK Chancellor of the Exchequer, Philip Hammond, announced in the Budget this week that national insurance contributions (NICs) for self-employed people will rise from 9% to 11% by 2019. These are known as ‘Class 4’ NICs. The average self-employed person will pay around £240 more per year, but those on incomes over £45,000 will pay £777 more per year. Many of the people affected will be those working in the so-called ‘gig economy’. This sector has been growing rapidly in recent years and now has over 4 million people working in it.
Workers in the gig economy are self employed, but are often contracted to an employer. They are paid by the job (or ‘gig’: like musicians), rather than being paid a wage. Much of the work is temporary, although many in the gig economy, such as taxi drivers and delivery people stick with the same job. The gig economy is just one manifestation of the growing flexibility of labour markets, which have also seen a rise in temporary employment, part-time employment and zero-hour contracts.
Working in the gig economy provides a number of benefits for workers. Workers have greater flexibility in their choice of hours and many work wholly or partly from home. Many do several ‘gigs’ simultaneously, which gives variety and interest.
In terms of economic theory, this flexibility gives workers a greater opportunity to work the optimal amount of time. This optimum involves working up to the point where the marginal benefit from work, in terms of pay and enjoyment, equals the marginal cost, in terms of effort and sacrificed leisure.
For firms using people from the gig economy, it has a number of advantages. They are generally cheaper to employ, as they do not need to be paid sick pay, holiday pay or redundancy; they are not entitled to parental leave; there are no employers’ national insurance contributions to pay (which are at a rate of 13.8% for employers); the minimum wage does not apply to such workers as they are not paid a ‘wage’. Also the firm using such workers has greater flexibility in determining how much work individuals should do: it chooses the amount of service it buys in a similar way that consumers decide how much to buy.
Many of these advantages to firms are disadvantages to the workers in the gig economy. Many have little bargaining power, whereas many firms using their services do. It is not surprising then that the Chancellor’s announcement of a 2 percentage point rise in NICs for such people has met with such dismay by the people affected. They will still pay less than employed people, but they claim that this is now not enough to compensate for the lack of benefits they receive from the state or from the firms paying for their services.
Some of the workers in the gig economy can be seen as budding entrepreneurs. If you have a specialist skill, you may use working in the gig economy as the route to setting up your own business and employing other people. A self-employed plumber may set up a plumbing company; a management consultant may set up a management consultancy agency. Another criticism of the rise in Class 4 NICs is that this will discourage such budding entrepreneurs and have longer-term adverse supply-side effects on the economy.
As far as the government is concerned, there is a worry about people moving from employment to self-employment as it tends to reduce tax revenues. Not only will considerably less NIC be paid by previous employers, but the scope for tax evasion is greater in self-employment. There is thus a trade-off between the extra output and small-scale investment that self-employment might bring and the lower NIC/tax revenue for the government.
Thriving in the gig economy Philippine Daily Inquirer, Michael Baylosis (10/3/17)
6 charts that show how the ‘gig economy’ has changed Britain – and why it’s not a good thing Business Insider, Ben Moshinsky (21/2/17)
What is the ‘gig’ economy? BBC News, Bill Wilson (10/2/17)
Great Freelance, Contract and Part-Time Jobs for 2017 CareerCast (10/3/17)
We have the laws for a fairer gig economy, we just need to enforce them The Guardian, Stefan Stern (7/2/17)
The gig economy will finally have to give workers the rights they deserve Independent, Ben Chu (12/2/17)
Gig economy chiefs defend business model BBC News (22/2/17)
Spring Budget 2017 tax rise: What’s the fuss about? BBC News, Kevin Peachey (9/3/17)
Self-employed hit by national insurance hike in budget The Guardian, Simon Goodley and Heather Stewart (8/3/17)
What national insurance is – and where it goes The Conversation, Jonquil Lowe (10/3/17)
Britain’s tax raid on gig economy misses the mark Reuters, Carol Ryan (9/3/17)
Economics collides with politics in Philip Hammond’s budget The Economist (9/3/17)
UK government publications
Contract types and employer responsibilities – 5. Freelancers, consultants and contractors GOV.UK
Spring Budget 2017 GOV.UK (8/3/17)
Spring Budget 2017: documents HM Treasury (8/3/17)
National Insurance contributions (NICs) HMRC and HM Treasury (8/3/17)
- Give some examples of work which is generally or frequently done in the gig economy.
- What are the advantages and disadvantages to individuals from working in the gig economy?
- What are the advantages and disadvantages to firms from using the services of people in the gig economy rather than employing people?
- In the case of employed people, both the employees and the employers have to pay NICs. Would it be fair for both such elements to be paid by self-employed people on their own income?
- Discuss ways in which the government might tax the firms which buy the services of people in the gig economy.
- How does the rise of the gig economy affect the interpretation of unemployment statistics?
- What factors could cause a substantial growth in the gig economy over the coming years?
When UK unemployment was 7.7% in July 2013, Mark Carney, the newly arrived governor of the Bank of England, said that the Bank would probably have to rise interest rates when the unemployment rate dropped below 7%. Below that rate, it was expected that inflation would rise. In other words, 7% was the NAIRU – the non-accelerating rate of inflation. The most recent figure for the unemployment rate is 4.8% and yet the Bank of England has not raised interest rates. In fact, in response to the Brexit vote, it cut Bank Rate from 0.5% to 0.25% in August last year. (Click here for a PowerPoint of the chart below.)
The NAIRU is a similar, although not identical, concept to the natural rate of unemployment. The natural rate is the equilibrium rate consistent with an overall long-term balance of aggregate labour demand and supply: i.e. the rate after short-term cyclical movements in unemployment have been discounted. It is thus a long-term concept.
The NAIRU, although similar, focuses on the relationship between inflation and unemployment. With inflation caused solely by demand-side factors, the natural rate and the NAIRU will be similar if not identical. However, if cost-push factors change – say there is a poor harvest, which pushes up food prices and inflation (temporarily), or a substantial depreciation of the exchange rate caused by political factors (such as Brexit) – the NAIRU would increase, at least in the short term, as a higher rate of unemployment would be necessary to stop inflation rising. In the long term, although being defined differently, the NAIRU and the natural rate will be the same.
In practice, because the Bank of England is targeting inflation at a 24-month time horizon, the NAIRU for the UK at that point could also be seen as the natural rate.
So with the Bank of England not raising interest rates despite the considerable fall in the unemployment rate, does this imply a fall in the natural rate of unemployment? The answer is yes. The reason has to do with changes in the structure of the labour market.
The proportion of young people and women with children returning to the labour market has fallen. Such people have a higher-than-average rate of unemployment since they typically spend a period of time searching for a job.
Tax and benefit reforms over the years have increased the incentive for the unemployed to take work.
Perhaps the biggest factor is a greater flexibility in the labour market. As union power has waned and as people are increasingly working on flexible contracts, including zero-hour contracts, so this has moderated wage increases. At the same time, many firms are facing increased competition both from abroad and domestically via the Internet. This has put downward pressure on prices and hence on the wages firms are willing to pay.
The effect has been a fall in the NAIRU and probably the natural rate. Frictions in the labour market have reduced and people losing their jobs because of changes in industrial structure find it easier to get jobs in low-skilled service industries, where employers’ risks of taking on such workers have fallen because of the loss of rights for such workers.
So what is the natural rate of unemployment today? It is certainly much lower than 7%; the consensus is that it is probably below 5%. As Kristin Forbes, External MPC Member of the Bank of England stated in a recent speech:
[Unemployment] is forecast to increase gradually from its current 4.8% to a high of 5.0% in the second half of 2017, before falling back to its current rate by the end of 2019. To put this in context, 5.0% was previously believed to be around the UK’s natural rate of unemployment – the rate below which unemployment could not fall without wages picking up to levels inconsistent with sustaining inflation around the 2% target. Unemployment at 5.0% is also below the average unemployment rate for the UK over the pre-crisis period from 1997 to 2007 (when it was 5.5%).
She went on to discuss just what the figure is for the natural, or ‘equilibrium’, rate of unemployment (U*). One problem here is that there is considerable uncertainty over the figure in the current forecast made by the Bank.
[An] assumption in the forecast about which there is substantial uncertainty is of the equilibrium unemployment rate – or U* for short. Since I have been on the MPC, the Committee has assumed that U* was around 5%. This implied that the more by which unemployment exceeded 5%, the more slack existed in the economy, and the less upward momentum would be expected in wages (controlling for other factors, such as productivity growth).
As part of our annual assessment of regular supply-side conditions this January, Bank staff presented several pieces of analysis that suggested U* may be lower than 5% today [see, for example]. The majority of the MPC voted to lower our estimate of U* to 4.5%, based partly on the persistent weakness of wage growth over the past few years after accounting for other factors in our models. [See page 20 of the February 2017 Inflation Report.]
My own assessment, however, suggested that although U* was likely lower than 5% today, it is likely not as low as 4.5%. If true, this would suggest that there is less slack in the economy than in the MPC’s central forecast, and wage growth and inflation could pick up faster than expected.
Against that, however, uncertainty related to Brexit negotiations could make firms more cautious about raising wages, thereby dampening wage growth no matter where unemployment is relative to its equilibrium. Moreover, even if we could accurately measure the level of U* in the economy today, it could easily change over the next few years as the labour force adjusts to any changes in the movement of labour between the UK and European Union.
Determining the precise figure of the current natural rate of unemployment, and predicting it for the medium term, is very difficult. It involves separating out demand-side factors, which are heavily dependent on expectations. It also involves understanding the wage elasticity of labour supply in various markets and how this has been affected by the increased flexibility of these markets.
When will Britons get a pay rise? The Guardian, Phillip Inman (26/2/17)
BoE decision, Inflation Report – Analysts react DigitalLook, Alexander Bueso (2/2/17)
Bank of England hikes UK economic growth forecasts but warns of rising inflation The Telegraph, Szu Ping Chan (2/2/17)
Bank of England publications
Inflation Report Bank of England (February 2017)
A MONIAC (not manic) economy Bank of England Speeches, Kristin Forbes (8/2/17)
The labour market Bank of England Speeches, Michael Saunders (31/1/17)
- Distinguish between the following terms: natural rate of unemployment, NAIRU, equilibrium rate of unemployment, disequilibrium rate of unemployment.
- For what reasons did the Monetary Policy Committee members feel that the equilibrium rate of unemployment might be as low as 4.25%?
- Why might it be as high as 5%?
- How are changes in migration trends likely to affect (a) wage growth and (b) unemployment?
- How is the amount of slack in an economy measured? What impact does the degree of slack have on wage growth and inflation?
- What is meant by the ‘gig’ economy? How has the development of the gig economy impacted on unemployment and wages?
- Why has there been a considerable rise in self employment?
- How may questions of life style choice and control over the hours people wish to work impact on the labour market?
- If people are moving jobs less frequently, does this imply that the labour market is becoming less flexible?
- Why may firms in the current climate be cautious about raising wages even if aggregate demand picks up?