Consumer credit is borrowing by individuals to finance current expenditure on goods and services. Consumer credit is distinct from lending secured on dwellings (referred to more simply as ‘secured lending’). Consumer credit comprises lending on credit cards, lending through overdraft facilities and other loans and advances, for example those financing the purchase of cars. We consider here recent trends in the flows of consumer credit in the UK and discuss their implications.
Analysing consumer credit data is important because the growth of consumer credit has implications for the financial wellbeing or financial health of individuals and, of course, for financial institutions. As we shall see shortly, the data on consumer credit is consistent with the existence of credit cycles. Cycles in consumer credit have the potential to be not only financially harmful but economically destabilising. After all, consumer credit is lending to finance spending and therefore the amount of lending can have significant effects on aggregate demand and economic activity.
Data on consumer credit are available monthly and so provide an early indication of movements in economic activity. Furthermore, because lending flows are likely to be sensitive to changes in the confidence of both borrowers and lenders, changes in the growth of consumer credit can indicate turning points in the economy and, hence, in the macroeconomic environment.
Chart 1 shows the annual flows of net consumer credit since 2000 – the figures are in £ billions. Net flows are gross flows less repayments. (Click here to download a PowerPoint copy of the chart.) In January 2005 the annual flow of net consumer credit peaked at £23 billion, the equivalent of just over 2.5 per cent of annual disposable income. This helped to fuel spending and by the final quarter of the year, the economy’s annual growth rate had reached 4.8 per cent, significantly about its long-run average of 2.5 per cent.
By 2009 net consumer credit flows had become negative. This meant that repayments were greater than additional flows of credit. It was not until 2012 that the annual flow of net consumer credit was again positive. Yet by November 2016, the annual flow of net consumer credit had rebounded to over £19 billion, the equivalent of just shy of 1.5 per cent of annual disposable income. This was the largest annual flow of consumer credit since September 2005.
Although the strength of consumer credit in 2016 was providing the economy with a timely boost to growth in the immediate aftermath of the referendum on the UK’s membership of the EU, it nonetheless raised concerns about its sustainability. Specifically, given the short amount of time that had elapsed since the financial crisis and the extreme levels of financial distress that had been experienced by many sectors of the economy, how susceptible would people and organisations be to a future economic slowdown and/or rise in interest rates?
The extent to which the economy experiences consumer credit cycles can be seen even more readily by looking at the 12-month growth rate in the net consumer credit. In essence, this mirrors the growth rate in the stock of consumer credit. Chart 2 evidences the double-digit growth rates in net consumer credit lending experienced during the first half of the 2000s. Growth rates then eased but, as the financial crisis unfolded, they plunged sharply. (Click here to download a PowerPoint copy of the chart.)
Yet, as Chart 2 shows, consumer credit growth began to recover quickly from 2013 so that by 2016 the annual growth rate of net consumer credit was again in double figures. In November 2016 the 12-month growth rate of net consumer credit peaked at 10.9 per cent. Thereafter, the growth rate has continually eased. In January 2019 the annual growth rate of net consumer credit had fallen back to 6.5 per cent, the lowest rate since October 2014.
The easing of consumer credit is likely to have been influenced, in part, by the resumption in the growth of real earnings from 2018 (see Getting real with pay). Yet, it is hard to look past the economic uncertainties around Brexit.
Uncertainty tends to cause people to be more cautious. With the heightened uncertainty that has has characterised recent times, it is likely that for many people and businesses prudence has dominated impatience. Therefore, in summary, it appears that prudence is helping to steer borrowing along a downswing in the credit cycle. As it does, it helps to put a further brake on spending and economic growth.
- What is the difference between gross and net lending?
- Consider the argument that we should be worried more by excessive growth in consumer credit than on lending secured on dwellings?
- How could we measure whether different sectors of the economy had become financially distressed?
- What might explain why an economy experiences credit cycles?
- Explain how the growth in net consumer credit can affect economic activity?
- If people are consumption smoothers, how can credit cycles arise?
- What are the potential policy implications of credit cycles?
- It is said that when making financial decisions people face an inter-temporal choice. Explain what you understand this by this concept.
- If economic uncertainty is perceived to have increased how could this affect the consumption, saving and borrowing decisions of people?
One of the most enduring characteristics of the macroeconomic environment since the financial crisis of the late 2000s has been its impact on people’s pay. We apply the distinction between nominal and real values to evidence the adverse impact on the typical purchasing power of workers. While we do not consider here the distributional impact on pay, the aggregate picture nonetheless paints a very stark picture of recent patterns in pay and, in turn, the consequences for living standards and wellbeing.
While the distinction between nominal and real values is perhaps best know in relation to GDP and economic growth (see the need to get real with GDP), the distinction is also applied frequently to analyse the movement of one price relative to prices in general. One example is that of movements in pay (earnings) relative to consumer prices.
Pay reflects the price of labour. The value of our actual pay is our nominal pay. If our pay rises more quickly than consumer prices, then our real pay increases. This means that our purchasing power rises and so the volume of goods and services we can afford increases. On the other hand, if our actual pay rises less quickly than consumer prices then our real pay falls. When real pay falls, purchasing power falls and the volume of goods and services we can afford falls.
Figures from the Office for National Statistics show that in January 2000 regular weekly pay (excluding bonuses and before taxes and other deductions from pay) was £293. By December 2018 this had risen to £495. This is an increase of 69 per cent. Over the same period the consumer prices index known as the CPIH, which, unlike the better-known CPI, includes owner-occupied housing costs and Council Tax, rose by 49 per cent. Therefore, the figures are consistent with a rise both in nominal and real pay between January 2000 to December 2018. However, this masks the fact that in recent times real earnings have fallen.
Chart 1 shows the annual percentage changes in actual (nominal) regular weekly pay and the CPIH since January 2001. Each value is simply the percentage change from 12 months earlier. The period up to June 2008 saw the annual growth of weekly pay outstrip the growth of consumer prices – the blue line in the chart is above the red line. Therefore, the real value of pay rose. However, from June 2008 to August 2014 pay growth consistently fell short of the rate of consumer price inflation – the blue line is below the red line. The result was that average real weekly pay fell. (Click here to download a PowerPoint copy of the chart.)
Chart 2 show the average levels of nominal and real weekly pay. The real series is adjusted for inflation. It is calculated by deflating the nominal pay values by the CPIH. Since the CPIH is a price index whose value averages 100 across 2015, the real pay values are at constant 2015 prices. From the chart, we can see that the real value of weekly pay peaked in March 2008 at £482.01 at 2015 prices. The subsequent period saw rates of pay inflation that were lower than rates of consumer price inflation. This meant that by March 2014 the real value of weekly pay had fallen by 8.8 per cent to £439.56 at 2015 prices. (Click here to download a PowerPoint copy of the chart.)
Although real (inflation-adjusted) pay recovered a little during 2015 and 2016, 2017 again saw consumer price inflation rates greater than those of pay inflation (see Chart 1). Consequently, the average level of real weekly pay fell by 1 per cent between January and November 2017. Since then, real regular pay has again increased. In December 2018, average real pay weekly pay was £462.18 at 2015 prices: an increase of 1.1 per cent from November 2017. Nonetheless, inflation-adjusted average weekly pay in December 2018 remained 4.1 per cent below its March 2008 level.
Chart 3 shows very clearly the importance of the distinction between real and nominal when analysing the growth of earnings. The sustained period of real pay deflation (negative rates of pay inflation) that followed the financial crisis can be seen much more clearly by plotting growth rates rather than their levels. Since June 2008 the average annual growth of real regular weekly pay has been −0.2 per cent, despite nominal pay increasing at an annual rate of 2 per cent. In the period from January 2001 to May 2008 real regular weekly pay had grown at an annual rate of 2.1 per cent with nominal pay growing at an annual rate of 4.0 per cent. (Click here to download a PowerPoint copy of the chart.)
The distinction between nominal and real helps us to understand better why some argue that patterns in pay, living standards and well-being have been fundamental in characterising the macroeconomic environment since the financial crisis. Indeed, it is not unreasonable to suggest that these patterns have helped to shape macroeconomic debates and broader conversations around the role of government and of public policy and its priorities.
- Using the example of GDP and earnings, explain how the distinction between nominal and real relates to the distinction between values and volumes.
- In what circumstances would an increase in actual pay translate into a reduction in real pay?
- In what circumstances would a decrease in actual pay translate into an increase in real pay?
- What factors might explain the reduction in real rates of pay seen in the UK following the financial crisis?
- Of what importance might the growth in real rates of pay be for consumption and aggregate demand?
- Why is the growth of real pay an indicator of financial well-being? What other indicators might be included in measuring financial well-being?
- Assume that you have been asked to undertake a distributional analysis of real earnings since the financial crisis. What might be the focus of your analysis? What information would you therefore need to collect?
The latest consumer confidence figures from the European Commission point to consumer confidence in the UK remaining at around its long-term average. Despite this, confidence is markedly weaker than before the outcome of the EU referendum. Yet, the saving ratio, which captures the proportion of disposable income saved by the household sector, is close to its historic low. We consider this apparent puzzle and whether we can expect the saving ratio to rise.
The European Commission’s consumer confidence measure is a composite indicator based on the balance of responses to 4 forward-looking questions relating to the financial situation of households, the general economic situation, unemployment expectations and savings.
Chart 1 shows the consumer confidence indicator for the UK. The long-term average (median) of –6.25 shows that negative responses across the four questions typically outweigh positive responses. In October 2018 the confidence balance stood at –5.2, essentially unchanged from its September value of –5.8. While above the long-term average, recent values mark a weakening in confidence from levels before the EU referendum. At the beginning of 2016 the aggregate confidence score was running at around +4. (Click here to download a PowerPoint of the chart.)
Chart 1 shows two periods where consumer confidence fell markedly. The first was in the early 1990s. In 1990 the UK joined the Exchange Rate Mechanism (ERM). This was a semi-fixed exchange rate system whereby participating EU countries allowed fluctuations against each other’s currencies, but only within agreed bands, while being able to collectively float freely against all other currencies. In attempting to staying in the ERM, the UK was obliged to raise interest rates in order to protect the pound. The hikes to rates contributed to a significant dampening of aggregate demand and the economy slid into recession. Britain crashed out of the ERM in September 1992.
The second period of declining confidence was during the global financial crisis in the late 2000s. The retrenchment among financial institutions meant a significant tightening of credit conditions. This too contributed to a significant dampening of aggregate demand and the economy slid into recession. Whereas the 1992 recession saw the UK national output contract by 2.0 percent, this time national output fell by 6.3 per cent.
The collapses in confidence from 1992 and from 2007/08 are likely to have helped propagate the effects of the fall in aggregate demand that were already underway. The weakening of confidence in 2016 is perhaps a better example of a ‘confidence shock’, i.e. a change in aggregate demand originating from a change in confidence. Nonetheless, a fall in confidence, whether it amplifies existing shocks or is the source of the shock, is often taken as a signal of greater economic uncertainty. If we take this greater uncertainty to reflect a greater range of future income outcomes, including potential income losses, then households may look to insure themselves by increasing current saving.
It is usual to assume that people suffer from diminishing marginal utility of total consumption. This means that while total satisfaction increases as we consume more, the additional utility from consuming more (marginal utility) decreases. An implication of this is that a given loss of consumption reduces utility by more than an equivalent increase in consumption increases utility. This explains why people prefer more consistent consumption levels over time and so engage in consumption smoothing. The utility, for example, from an ‘average’ consumption level across two time periods, is higher, than the expected utility from a ‘low’ level of consumption in period 1 and a ‘high’ level of consumption in period 2. This is because the loss of utility from a ‘low’ level of consumption relative to the ‘average’ level is greater than the additional utility from the ‘high’ level relative to the ‘average’ level.
If greater uncertainty, such as that following the EU referendum, increases the range of possible ‘lower’ consumption values in the future even when matched by an increase in the equivalent range of possible ‘higher’ consumption values, then expected future utility falls. The incentive therefore is for people to build up a larger buffer stock of saving to minimise utility losses if the ‘bad state’ occurs. Hence, saving which acts as a from of self-insurance in the presence of uncertainty is known as buffer-stock saving or precautionary saving.
Chart 2 plots the paths of the UK household-sector saving ratio and consumer confidence. The saving ratio approximates the proportion of disposable income saved by the household sector. What we might expect to see if more uncertainty induces buffer-stock saving is for falls in confidence to lead to a rise in the saving ratio. Conversely, less uncertainty as proxied by a rise in confidence would lead to a fall in the saving ratio. (Click here to download a PowerPoint of the chart.)
The chart provides some evidence that of this. The early 1990s and late 2000s certainly coincided with both waning confidence and a rising saving ratio. The saving ratio rose to as high as 15.2 per cent in 1993 and 12.0 per cent in 2009. Meanwhile the rising confidence seen in the late 1990s coincided with a fall in the saving ratio to 4.7 per cent in 1999.
As Chart 2 shows, the easing of confidence since 2016 has coincided with a period where the saving ratio has been historically low. Across 2017 the saving ratio stood at just 4.5 per cent. In the first half of 2018 the ratio averaged just 4.2 per cent. While the release of the official figures for the saving ratio are less timely than those for confidence, the recent very low saving ratio may be seen to raise concerns. Can softer confidence data continue to co-exist with such a low saving ratio?
There are a series of possible explanations for the recent lows in the saving ratio. On one hand, the rate of price inflation has frequently exceeded wage inflation in recent years so eroding the real value of earnings. This has stretched household budgets and limited the amount of discretionary income available for saving. On the other hand, unemployment rates have fallen to historic lows. The rate of unemployment in the three months to August stood at 4 per cent, the lowest since 1975. Unemployment expectations are important in determining levels of buffer stock saving because of the impact of unemployment on household budgets.
Another factor that has fuelled the growth of spending relative to income, has been the growth of consumer credit. In the period since July 2016, the annual rate of growth of consumer credit, net of repayments, has averaged 9.7 per cent. Behavioural economists argue that foregoing spending can be emotionally painful. Hence, spending has the potential to exhibit more stickiness than might otherwise be predicted in a more uncertain environment or in the anticipation of income losses. Therefore, the reluctance or inability to wean ourselves off credit and spending might be a reason for the continuing low saving ratio.
We wait to see whether the saving ratio increases over the coming months. However, for now, the UK household sector appears to be characterised by low saving and fragile confidence. Whether or not this is a puzzle, is open to question. Nonetheless, it does appear to carry obvious risks should weaker income growth materialise.
- Draw up a series of factors that you think might affect consumer confidence.
- Which of the following statements is likely to be more accurate: (a) Consumer confidence drives economic activity or (b) Economic activity drives consumer confidence?
- What macroeconomic indicators would those compiling the consumer confidence indicator expect the indicator to predict?
- How does the diminishing marginal utility of consumption (or income) help explain why people engage in buffer stock saving (precautionary saving)?
- How might uncertainty affect consumer confidence?
- How does greater income uncertainty affect expected utility? What affect might this have on buffer stock saving?
Ten years ago, the financial crisis deepened and stock markets around the world plummeted. The trigger was the collapse of Lehman Brothers, the fourth-largest US investment bank. It filed for bankruptcy on September 15, 2008. This was not the first bank failure around that time. In 2007, Northern Rock in the UK (Aug/Sept 2007) had collapsed and so too had Bear Stearns in the USA (Mar 2008).
Initially there was some hope that the US government would bail out Lehmans. But when Congress rejected the Bank Bailout Bill on September 29, the US stock market fell sharply, with the Dow Jones falling by 7% the same day. This was mirrored in other countries: the FTSE 100 fell by 15%.
At the core of the problem was excessive lending by banks with too little capital. What is more, much of the capital was of poor quality. Many of the banks held securitised assets containing ‘sub-prime mortgage debt’. The assets, known as collateralised debt obligations (CDOs), were bundles of other assets, including mortgages. US homeowners had been lent money based on the assumption that their houses would increase in value. When house prices fell, homeowners were left in a position of negative equity – owing more than the value of their house. With many people forced to sell their houses, prices fell further. Mortgage debt held by banks could not be redeemed: it was ‘sub-prime’ or ‘toxic debt’.
Response to the crisis
The outcome of the financial crash was a series of bailouts of banks around the world. Banks cut back on lending and the world headed for a major recession.
Initially, the response of governments and central banks was to stimulate their economies through fiscal and monetary policies. Government spending was increased; taxes were cut; interest rates were cut to near zero. By 2010, the global economy seemed to be pulling out of recession.
However, the expansionary fiscal policy, plus the bailing out of banks, had led to large public-sector deficits and growing public-sector debt. Although a return of economic growth would help to increase revenues, many governments felt that the size of the public-sector deficits was too large to rely on economic growth.
As a result, many governments embarked on a period of austerity – tight fiscal policy, involving cutting government expenditure and raising taxes. Although this might slowly bring the deficit down, it slowed down growth and caused major hardships for people who relied on benefits and who saw their benefits cut. It also led to a cut in public services.
Expanding the economy was left to central banks, which kept monetary policy very loose. Rock-bottom interest rates were then accompanied by quantitative easing. This was the expansion of the money supply by central-bank purchases of assets, largely government bonds. A massive amount of extra liquidity was pumped into economies. But with confidence still low, much of this ended up in other asset purchases, such as stocks and shares, rather than being spent on goods and services. The effect was a limited stimulation of the economy, but a surge in stock market prices.
With wages rising slowly, or even falling in real terms, and with credit easy to obtain at record low interest rates, so consumer debt increased.
So have the lessons of the financial crash been learned? Would we ever have a repeat of 2007–9?
On the positive side, financial regulators are more aware of the dangers of under capitalisation. Banks’ capital requirements have increased, overseen by the Bank for International Settlements. Under its Basel II and then Basel III regulations (see link below), banks are required to hold much more capital (‘capital buffers’). Some countries’ regulators (normally the central bank), depending on their specific conditions, exceed these the Basel requirements.
But substantial risks remain and many of the lessons have not been learnt from the financial crisis and its aftermath.
There has been a large expansion of household debt, fuelled by low interest rates. This constrains central banks’ ability to raise interest rates without causing financial distress to people with large debts. It also makes it more likely that there will be a Minsky moment, when a trigger, such as a trade war (e.g. between the USA and China), causes banks to curb lending and consumers to rein in debt. This can then lead to a fall in aggregate demand and a recession.
Total debt of the private and public sectors now amounts to $164 trillion, or 225% of world GDP – 12 percentage points higher than in 2009.
China poses a considerable risk, as well as being a driver of global growth. China has very high levels of consumer debt and many of its banks are undercapitalised. It has already experienced one stock market crash. From mid-June 2015, there was a three-week fall in share prices, knocking about 30% off their value. Previously the Chinese stock market had soared, with many people borrowing to buy shares. But this was a classic bubble, with share prices reflecting exuberance, not economic fundamentals.
Although Chinese government purchases of shares and tighter regulation helped to stabilise the market, it is possible that there may be another crash, especially if the trade war with the USA escalates even further. The Chinese stock market has already lost 20% of its value this year.
Then there is the problem with shadow banking. This is the provision of loans by non-bank financial institutions, such as insurance companies or hedge funds. As the International Business Times article linked below states:
A mind-boggling study from the US last year, for example, found that the market share of shadow banking in residential mortgages had rocketed from 15% in 2007 to 38% in 2015. This also represents a staggering 75% of all loans to low-income borrowers and risky borrowers. China’s shadow banking is another major concern, amounting to US$15 trillion, or about 130% of GDP. Meanwhile, fears are mounting that many shadow banks around the world are relaxing their underwriting standards.
Another issue is whether emerging markets can sustain their continued growth, or whether troubles in the more vulnerable emerging-market economies could trigger contagion across the more exposed parts of the developing world and possibly across the whole global economy. The recent crises in Turkey and Argentina may be a portent of this.
Then there is a risk of a cyber-attack by a rogue government or criminals on key financial insitutions, such as central banks or major international banks. Despite investing large amounts of money in cyber-security, financial institutions worry about their vulnerability to an attack.
Any of these triggers could cause a crisis of confidence, which, in turn, could lead to a fall in stock markets, a fall in aggregate demand and a recession.
Finally there is the question of the deep and prolonged crisis in capitalism itself – a crisis that manifests itself, not in a sudden recession, but in a long-term stagnation of the living standards of the poor and ‘just about managing’. Average real weekly earnings in many countries today are still below those in 2008, before the crash. In Great Britain, real weekly earnings in July 2018 were still some 6% lower than in early 2008.
- The Lehman Brothers Crash And The Chaos That Followed – Everything You Need To Know
HuffPost, Isabel Togoh (15/9/18)
- Ten years after the crash: have the lessons of Lehman been learned?
The Guardian, Yanis Varoufakis, Ann Pettifor, Mark Littlewood, David Blanchflower, Olli Rehn, Nicky Morgan and Micah White (14/9/18)
- Financial crisis 10 years on: Who are the winners and losers?
Independent, Kate Hughes (14/9/18)
- Investment winners and losers 10 years after the crash
Financial Times, Kate Beioley (14/9/18)
- Nine Lessons From the Global Financial Crisis
Bloomberg, Mohamed A. El-Erian (13/9/18)
- Lehman — why we need a change of mindset
Deutsche Welle, Thomas Straubhaar (14/9/18)
- ‘The world is sleepwalking into a financial crisis’ – Gordon Brown
The Guardian, Larry Elliott (12/9/18)
- Economists warn of new financial crisis on anniversary of 2008 crash
Channel 4 news, Helia Ebrahimi (15/9/18)
- Financial crisis 2008: Five biggest risks of a new crash
International Business Times, Nafis Alam (14/9/18)
- Carney warns against complacency on 10th anniversary of financial crisis
BBC News, Kamal Ahmed (12/9/18)
- A cyberattack could trigger the next financial crisis, new report says
CNBC, Bob Pisani (13/9/18)
Information and data
- Explain the major causes of the financial market crash in 2008.
- Would it have been a good idea to have continued with expansionary fiscal policy beyond 2009?
- Summarise the Basel III banking regulations.
- How could quantitative easing have been differently designed so as to have injected more money into the real sector of the economy?
- What are the main threats to the global economy at the current time? Are any of these a ‘hangover’ from the 2007–8 financial crisis?
- What is meant by ‘shadow banking’ and how might this be a threat to the future stability of the global economy?
- Find data on household debt in two developed countries from 2000 to the present day. Chart the figures. Explain the pattern that emerges and discuss whether there are any dangers for the two economies from the levels of debt.
The median pay of chief executives of the FTSE 100 companies rose 11% in 2017 to £3.93 million per year, according to figures released by the High Pay Centre. By contrast, the median pay of full-time workers rose by just 2%. Given two huge pay increases for the CEOs of Persimmon and Melrose Industries of £47.1 million and £42.8 million respectively, the mean CEO pay rose even more – by 23%, from £4.58 million in 2016 to £5.66 million in 2017. This brings the ratio of the mean pay of FTSE 100 CEOs to that of their employees to 145:1. In 2000, the ratio was around 45:1.
These huge pay increases are despite criticisms from shareholders and the government over excessive boardroom pay awards and the desire for more transparency. In fact, under new legislation, companies with more than 250 employees must publish the ratio of the CEO’s total remuneration to the full-time equivalent pay of their UK employees on the 25th, 50th (median) and 75th percentiles. The annual figures will be for pay starting from the financial year beginning in 2019, which for most companies would mean the year from April 2019 to April 2020. Such a system has been introduced in the USA this year.
So why has the gap in pay widened so much? One reason is that there is no formal mechanism whereby workers can apply downward pressure on such awards. Although Theresa May, in her campaign to become Prime Minister in 2016, promised to put workers on company boards, the government has since abandoned the idea.
Executive pay is awarded by remuneration committees. Membership of such committees consists of independent non-executive directors, but their degree of independence has frequently been called into question and there has been much criticism of such committees being influenced by their highest paying competitors or peers. This has had the effect of ratcheting up executive pay.
Then there is the question of the non-salary element in executive pay. The incentive and bonus payments are often linked to the short-term performance of the company, as reflected in, for example, the company’s share price. In a period when share prices in general rise rapidly – as we have seen over the past two years – executive pay tends to rise rapidly too. A frequent criticism of large UK businesses is that they have been too short-termist. What is more, bonuses are often paid despite poor performance.
There has been some move in recent years to make incentive pay linked more to long-term performance, but this has still led to many CEOs getting large pay increases despite lack-lustre long-term performance.
Then there is the question of shareholders and their influence on executive pay. Despite protests by many smaller shareholders, a large proportion of shares are owned by investment funds and their managers are often only too happy to vote through large executive pay increases at shareholder meetings.
So, while the pressures for containing the rise in executive pay remain small, the pay gap is likely to continue to widen. This raises the whole question of a society becoming increasingly divided between the few at the top and a large number of people ‘just getting by’ – or not even that. Will this make society even more fractured and ill at ease with itself?
Information and data
- How would you set about establishing whether CEOs’ pay is related to their marginal revenue product?
- To what extent is executive pay a reflection of oligopolistic/oligopsonistic behaviour?
- In what ways can game theory shed light on the process of setting the remuneration packages of CEOs? Is there a Nash equilibrium?
- What are the advantages and disadvantages of linking senior executives’ remuneration to (a) short-term company performance; (b) long-term company performance?
- What is/are the best indicator(s) of long-term company performance for determining the worth of senior executives?
- Consider the arguments for and against capping the ratio of CEOs’ remuneration to a particular ratio of either the mean or median pay of employees. What particular ratio might be worth considering for such a cap?