For those of you embarking on a course in economics, one of the first things you’ll come across is the distinction between microeconomics and macroeconomics. The news is full of both microeconomic and macroeconomic issues and you’ll quickly see how relevant both branches of economics are to analysing real-world events, problems and policies.
As we state in Economics (updated 10th edition), ‘microeconomics is concerned with the individual parts of the economy. It is concerned with the demand and supply of particular goods, services and resources such as cars, butter, clothes, haircuts, plumbers, accountants, blast furnaces, computers and oil.’ In particular, it is concerned with the buying, selling, production and employment decisions of individuals and firms. When you go shopping and make choices of what to buy you are making microeconomic decisions. When firms choose how much of particular products to produce, what techniques of production to use and how many people to employ, these choices are microeconomic ones.
Microeconomics examines people’s behaviour when they make choices. In fact many of the recent developments in microeconomics involve analysing the behaviour of individuals and firms and the factors that influence this behaviour.
Open any newspaper, turn on the TV news or access any news site and you will see various microeconomic issues covered. Why are rents soaring? How is AI affecting various businesses’ productivity? How rapidly is the switch taking place to green energy? How do supermarkets influence spending patterns? Why are wages so low in the social care sector? Why are private PCR tests so expensive for holidaymakers retuning from abroad?
Many of the blogs on this news site will examine microeconomic issues. We hope that they provide useful case studies for your course.
Articles
Questions
- Look through news sites and identify five current microeconomic issues. What makes them ‘micro’ issues?
- If world oil and gas prices rise, why is this a microeconomic issue?
- What do you understand by ‘scarcity’? How is microeconomics related to scarcity?
- Are all goods scarce?
- What is meant by ‘opportunity cost’? Give some examples of how opportunity cost has affected recent decisions you have made.
The government has announced outlines of the new system of immigration controls from January 2021 when the Brexit transition period is scheduled to finish. It plans to introduce an Australian-style points-based system. This will apply to all EU and Non-EU citizens. The aim is to attract skilled workers, while preventing non-skilled or low-skilled workers from entering the UK for employment.
But even skilled workers will need to meet three criteria in order to obtain a work visa: (i) having the offer of a job paying a minimum of £25,600 per annum, except in designated jobs where there is a shortage of labour; (ii) being able to speak English; (iii) having qualifications equivalent to A levels.
To apply for a work visa, applicants must have at least 70 points according to the following table:
In certain jobs where there is a shortage of labour, designated by the Migration Advisory Committee (MAC), immigrants will be able to earn a lower income, provided it is above £20,480 per annum. They will earn 20 points for such jobs, which can offset not meeting the £25,600 threshold. Such jobs could include those in healthcare and farming. There will also be temporary visas for seasonal workers, such as fruit pickers.
The government argues that the new system will encourage employers to substitute technology for labour, with greater investment in equipment and computers. This would increase labour productivity and wages without reducing employment.
This is illustrated in the diagram, which illustrates a low-paid job which will be impacted by the restrictions. If there is a rise in productivity through technological change, the marginal revenue product of labour curve shifts upwards from MRPL1 to MRPL2 and offsets the leftward shift in labour supply (caused by the decline in immigration) from ACL1 to ACL2 and the marginal cost of labour from MCL1 to MCL2. Employment is where the marginal cost of labour equals the marginal revenue product of labour. This remains at Q1. Wages are given by the supply curve of labour and rise from W1 to W1. (Click here for a PowerPoint of the diagram.)
Even if the upward shift in the MRPL curve is not sufficient to offset the leftward shift in the labour supply curve, wages will still rise, but there will be a fall in employment.
In higher-paid skilled jobs where people meet the points requirement, there will be little effect on wages and employment, except where people are generally discouraged by a points system, even if they have the points themselves.
The government also argues that there is a large pool of UK residents who can take up jobs that would otherwise have been filled by immigrants. The Home Secretary referred to the 8.48 million people who are economically inactive who could fill jobs no longer filled by immigrants. However, as the data show, most 
of these people are not available for work. Some 2.3 million are students, 1.9 million are carers at home looking after relatives, 2.1 million are long-term sick and 1.1 million are retired. Only 1.9 million (22.1% of the economically inactive) would like a job and not all these would be able to take up one (e.g. the long-term sick).
One the biggest problems concerns low-paid sectors where it is very difficult to substitute capital for labour through use of technology. Examples include social care, health care, the leisure and hospitality industry and certain jobs in farming. There could be severe shortages of labour in such industries. It remains to be seen whether such industries will be given exemptions or more relaxed conditions by the government in line with advice from the Migration Advisory Committee.
More details will emerge of the points system in the coming months. It will be interesting to see how responsive the government will be to the concerns of employers and workers.
Videos
Articles
Questions
- Find out how the proposed points-based system for immigration differs from the current system that applies to non-EU citizens.
- What will be the likely impact of reducing immigration of unskilled and low-skilled people?
- What barriers are there to substituting capital for labour in the caring and leisure sectors?
- What would be the macroeconomic effects of a substantial reduction in immigration?
It’s been a while since I last blogged about labour markets and, in particular, about the effect of automation on wages and employment. My most recent post on this topic was on the 14th of April 2018 and it was mostly a reflection on some interesting findings that had been reported by Acemoglu et al (2017). More specifically, Acemoglu and Restrepo (2017) developed a theoretical framework to evaluate the effect of AI on employment and wages. They concluded that the effect was negative and potentially sizeable (for a more detailed discussion see my blog).
Using a model in which robots compete against human labor in the production of different tasks, we show that robots may reduce employment and wages … According to our estimates, one more robot per thousand workers reduces the employment to population ratio by about 0.18–0.34 percentage points and wages by 0.25–0.5 percent.
Since then, I have seen a constant stream of news on my news feed about the development of ever more advanced industrial robots and artificial intelligence. And this was not because of some spooky coincidence (or worse). It has been merely a reflection of the speed at which technology has been progressing in this field.
There are now robots that can run, jump, hold conversations with humans, do gymnastics (and even sweat for it!) and more. It is really impressive how fast change has been happening recently in this field – and, unsurprisingly, it has stimulated the interest of labour economists!
A paper that has recently come to my attention on this subject is by Graetz and Michaels (2018). The authors put together a panel dataset on robot adoption within seventeen countries from 1993 to 2007 and use advanced econometric techniques to evaluate the effect of these technologies on employment and productivity growth. Their analysis focuses exclusively on developed economies (due to data limitations, as they explain) – but their results are nevertheless intriguing:
We study here for the first time the relationship between industrial robots and economic outcomes across much of the developed world. Using a panel of industries in seventeen countries from 1993 to 2007, we find that increased use of industrial robots is associated with increases in labor productivity. We find that the contribution of increased use of robots to productivity growth is substantial and calculate using conservative estimates that it comes to 0.36 percentage points, accounting for 15% of the aggregate economy-wide productivity growth.
The pattern that we document is robust to including various controls for country trends and changes in the composition of labor and other capital inputs. We also find that robot densification is associated with increases in both total factor productivity and wages, and reductions in output prices. We find no significant relationship between the increased use of industrial robots and overall employment, although we find that robots may be reducing the employment of low-skilled workers.
This is very positive news for most – except, of course, for low-skilled workers. Indeed, like Acemoglu and Restrepo (2017) and many others, this study shows that the effect of automation on employment and labour market outcomes is unlikely to be uniform across all types of workers. Low-skilled workers are found again to be likely to lose out and be significantly displaced by these technologies.
And if you are wondering which sectors are likely to be disrupted most/first by automation, the rankings developed by McKinsey and Company (see chart below) would give you an idea of where the disruption is likely to start. Unsurprisingly, the sectors that seem to be the most vulnerable, are the ones that use the highest share of low-skilled labour.
Articles
Questions
- “The effect of automation on wages and employment is likely to be positive overall”. Discuss.
- Using examples and anecdotal evidence, do you agree with these findings?
- Using Google Scholar, put together a list of 5 recent (i.e. 2015 or later) articles and working papers on labour markets and automation. Compare and discuss their findings.
The earnings gap between men and women is well-documented and depending on how we measure it, we get different figures. One of the most common measures is mean earnings per hour. The latest estimates suggest that women are paid around 20% less than men, though other data does give lower figures. Though actions have been taken to reduce the inequality between men and women, it still persists in many areas and this has led to plans for new league tables from Nicky Morgan.
The inequality gap has certainly come down. Back in 1970, the wage differential was around 37 per cent, so progress has been made, although the wage gap in the UK has stabilised somewhat. The gender wage gap is at least in part explained by occupations, as women have tended to be prevalent in some of the more poorly paid occupations. However, significant earnings differentials still exist within occupations. We see fewer women in the more senior positions; women tend to take career breaks and hence this can cause more investment into training and promoting men. Furthermore, we often simply see some form of prejudice or discrimination whereby women are just paid less than men, despite the Equal Pay Act.
As a means of combatting this inequality, Nicky Morgan, the Women and Equalities Minister, has announced plans that will require private companies and voluntary organisations employing more than 250 workers to reveal their pay gap. They will have to produce this information online and this will a means to bring down the inequality that exists between men and women in the same occupations. The first League Table of this pay gap will be published in April 2018 so companies will have to begin compiling the information from April 2017. This has received criticism from some, as it is not starting soon enough, but it is seen as a step in the right direction.
Carolyn Fairbairn, CBI Director-General warned that these League Tables shouldn’t be used to name and shame firms, as many factors might explain wage differentials. She noted:
“Where reporting can be useful is as a prompt for companies to ask the right questions about how they can eradicate the gender pay gap … The government should consult closely with business to ensure that this new legislation helps close the gender pay gap, rather than ending up as a box-ticking exercise.”
Clearly there are some close links between the gender pay gap and concerns about poverty and minimum wages and although the League Tables perhaps should not be used to name and shame, one might think it is inevitable that this is how they will be viewed. The following articles consider Nicky Morgan’s inequality plans.
Reports
Gender Pay Gap European Commission
Annual Survey of Hours and Earnings, 2015 Provisional Results Office for National Statistics (November 2015)
Pay gap reporting Equal Pay Portal2016
Articles
Gender pay gap reporting for big firms to start in 2018 Guardian, Rowena Mason (12/02/16)
Gender pay gap to be revealed by employers to tackle inequality Financial Times, Sarah O’Connor (12/02/16)
Firms forced to reveal gender pay gap BBC News (12/02/16)
Gender pay gap League Tables to ‘name and shame’ companies Telegraph, Steven Swinford (12/02/16)
UK companies must reveal gender pay gap under new plans Independent, Oliver Wright (12/02/16)
Companies told to publish gender pay gap Sky News (12/102/16)
Gender pay gap: Business groups mixed on Nicky Morgan’s new name-and-shame plans International Business Times, Bauke Schram (12/02/16)
Now every firm with more than 250 staff must put gender pay gap data online in move to encourage companies to reward staff equally Mail Online, Jack Doyle and Rosie Taylor (12/02/16)
Questions
- Use a labour market diagram to explain how gender pay gaps can emerge based on different marginal products.
- How can gender pay gaps emerge because of women taking career breaks and being less geographically mobile?
- Use information on the ONS website to compare pay differentials across occupations. Are the biggest and smallest differentials where you would expect?
- There are numerous reasons why men have traditionally been paid more than women. Which reasons could be said to be irrational and which are rational?
- If employers were forced to give genuinely equal pay for equal work, how would this affect the employment of women and men? What would determine the magnitude of these effects?
- Do you think this naming and shaming will be effective in reducing the gender pay gap amongst the largest companies? Can you suggest any other policy options?
- If the Equal Pay Act is in place, why can companies still pay women less?
In a post last August we looked at the rising number of workers employed on ‘zero-hours’ contracts. These are contracts where there are no guaranteed minimum hours. Such contracts give employers the flexibility to employ workers as much or as little as suits the business. Sometimes it benefits workers, who might be given the flexibility to request the hours that suit them, but usually workers simply have to take the hours on offer.
Latest figures published by the Office for National Statistics show that zero-hours contracts are on the increase. In 2014 quarter 4, 697,000 workers were recorded as being on zero-hours contracts. 
This represents 2.3% of people in employment. Ten years ago (2004, Q4) the figures were 108,000 or 0.4%: see chart. (Click here for a PowerPoint of the chart.)
Around one third of the 697,000 people on zero-hours contracts wanted more work if they could get it and most wanted it in their current job rather than having to move jobs. These people wanting more work can be classed as underemployed. They also include those not on a zero-hours contract who would like to work more if they could.
According to the ONS:
‘People on zero-hours contracts are more likely to be women, in full-time education or in young or older age groups when compared with other people in employment. On average, someone on a zero-hours contract usually works 25 hours a week.’ (See section 4 of the report for more details.)
As we saw in the earlier post, many public- and private-sector employers use such contracts, including many small and medium-sized enterprises and many well-known large companies, such as Sports Direct, Amazon, JD Wetherspoon and Cineworld. It gives them the flexibility to adjust the hours they employ people. It allows them to keep people in employment when demand is low. It also makes them more willing to take on staff when demand rises, as it removes the fear of being over-staffed if demand then falls back.
As we also saw, zero-hours contracts are not the only form of flexible working. Other examples include: ‘self-employed’ workers, contracted separately for each job they do for a company; people paid largely or wholly on commission; on-call working; part-time working, where the hours are specified in advance, but where these are periodically re-negotiated; overtime; people producing a product or service for a company (perhaps at home), where the company varies the amount paid per unit according to market conditions.
The extent of zero-hours contracts varies dramatically from one sector of the economy to another. Only 0.6% of workers in the Information, Finance and Professional sectors were on zero-hours contracts in 2014 Q4, whereas 10% in the Accommodation and Food sectors were.
The flexibility that such contracts give employers may make them more willing to keep on workers when demand is low – they can reduce workers’ hours rather than laying them off. It also may make them more willing to take on workers (or increase their hours) when demand is expanding, not having to worry about being over staffed later on.
However, many workers on such contracts find it hard to budget when their hours are not guaranteed and can vary significantly from week to week.
Articles
lmost 700,000 people in UK have zero-hours contract as main job The Guardian, Phillip Inman (25/2/15)
UK firms use 1.8m zero-hours contracts, says ONS BBC News (25/1/15)
Zero-hours contracts jump in UK Financial Times, Emily Cadman (25/2/15)
Zero-hours contracts ‘disturbingly’ hit 1.8 million in 2014 International Business Times, Ian Silvera (25/2/15)
Zero-hours contracts a reality for almost 700,000 UK workers, ONS figures show Independent, Antonia Molloy (25/1/15)
Data
Contracts with No Guaranteed Hours, Zero Hour Contracts, 2014 ONS Release (25/1/15)
Supplementary LFS data on zero hours contracts – October to December 2014 ONS dataset (25/2/15)
Analysis of Employee Contracts that do not Guarantee a Minimum Number of Hours ONS Report (25/1/15)
Questions
- Distinguish between open unemployment, disguised unemployment and underemployment?
- Distinguish between functional, numerical and financial flexibility? Which type or types of flexibility do zero-hours contracts give the firm?
- In a ‘flexible’ labour market, what forms can that flexibility take?
- Why does the Accommodation and Food sector have a relatively high proportion of people employed on zero-hours contracts?
- What are the benefits and costs to employers of using zero-hours contracts?
- If a company introduces a system of zero-hours contracts, is this in accordance with the marginal productivity theory of profit maximisation from employment?
- What are the benefits and costs to employees of working on zero-hours contracts?
- Why has the use of zero-hours contracts risen so rapidly?
- Using the ONS data, find out how the use of zero-hours contracts varies by occupation and explain why.
- Identify what forms of flexible contracts are used for staff in your university or educational establishment. Do they benefit (a) staff; (b) students?
- Consider the arguments for and against (a) banning and (b) regulating zero-hours contracts.
