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.
Articles
Questions
- 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?
Economists were generally in favour of the UK remaining in the EU and highly critical of the policy proposals of Donald Trump. And yet the UK voted to leave the EU and Donald Trump was elected.
People rejected the advice of most economists. Many blamed the failure of most economists to predict the 2007/8 financial crisis and to find solutions to the growing gulf between rich and poor, with the majority stuck on low incomes.
So to what extent are economists to blame for the rise in populism – a wave that could lead to electoral upsets in various European countries? The podcast below brings together economists and politicians from across the political spectrum. It is over an hour long and provides an in-depth discussion of many of the issues and the extent to which economists can provide answers.
Podcast
Should economists share the blame for populism? Guardian Politics Weekly podcast, Heather Stewart, joined by Andrew Lilico, Ann Pettifor, Jonathan Portes, Rachel Reeves and Vince Cable (23/2/17)
Questions
- Why has globalisation become a dirty word?
- Assess the arguments for and against an open policy towards immigration?
- In what positive ways may economists contribute to populism?
- Do economists concentrate too much on growth in GDP rather than on its distribution?
- Give some examples of ways in which various popular interpretations of economic phenomena may confuse correlation with causality.
- Why did the proportions of people who voted for and against Brexit differ considerably from one part of the country to another, from one age group to another and from one social group to another?
- In what ways have economists and the subject of economics contributed towards a growth in human welfare?
- What are the advantages and disadvantages of the trend for undergraduate economics curricula to become more mathematical (at least until relatively recently)?
Is too much expected of economists? When economic forecasts turn out to be wrong, as they often are, economists are criticised for having inaccurate or unrealistic models. But is this a fair criticism?
The following article by Richard Whittle from Manchester Metropolitan University looks at what economists can and cannot do. The article highlights two key problems for economic forecasting.
The first concerns human behaviour, which is influenced by a whole range of factors and can change very rapidly in response to changing circumstances. Moods of optimism or pessimism can quickly spread in response to a news item, such as measures announced by Donald Trump or latest data on growth or the housing market.
The second concerns the whole range of possible economic shocks. Such shocks, by their very nature, are hard to predict and can quickly make forecasts wrong. They could be a surprise election result, a surprise government policy change, a natural disaster, a war or a series of terrorist attacks. And these shocks, in turn, affect human behaviour. Consumption and investment may rise or fall as the events affect confidence and herd behaviour.
But is it a fair criticism of economics that it cannot foretell the future? Do economists, as the article says, throw up their hands and curse economics as a futile endeavour? Not surprisingly, the answer given is no! The author gives an analogy with medicine.
A doctor cannot definitely prevent illness, but can offer advice on prevention and hopefully offer a cure if you do get ill. This is the same for the work economists do.
Economists can offer advice on preventing crises or slowdowns but cannot definitively prevent them from happening. Economists can also offer robust advice on restoring growth, although when the advice is that the economy has grown too fast and should slow, it is often not welcomed by policy makers.
Helping understanding the various drivers in an economy and how humans are likely to respond to various incentives is a key part of what economists do. But making predictions with 100% certainty is asking too much of economists.
And just as medical professionals can predict that if you smoke, eat unhealthy food or take no exercise you are likely to be less healthy and die younger, but cannot say precisely when an individual will die, so too economists can predict that certain policy measures are likely to increase or decrease GDP or employment or inflation, but they cannot say precisely how much they will be affected.
As the article says, “the true value of the economist lies not in mystical fortune telling, but in achieving a better understanding of the nature of the economies in which we live and work.”
Article
How to be an economist in 2017 The Conversation, Richard Whittle (24/1/17)
Questions
- For what reasons has economics been ‘in crisis’? What is the solution to this crisis?
- Look at some macroeconomic forecasts for a country of your choice made two years ago for today (see, for example, forecasts made by the IMF, OECD or a central bank). How accurate were they? Explain any inaccuracies.
- To what extent is economic forecasting like weather forecasting?
- What is meant by cumulative causation? Give some examples. Why does cumulative causation make economic forecasting difficult?
- How is the increased usage of contactless card payments likely to affect spending patterns? Explain why.
- Why is it difficult to forecast the effects of Brexit?
- How can economic advisors help governments in designing policy?
- Why do people tend to overweight high probabilities and underweight low ones?
Economic forecasting came in for much criticism at the time of the financial crisis and credit crunch. Few economists had predicted the crisis and its consequences. Even Queen Elizabeth II, on a visit to the London School of Economics in November 2008, asked why economists had got it so wrong. Similar criticisms have emerged since the Brexit vote, with economic forecasters being accused of being excessively pessimistic about the outcome.
The accuracy of economic forecasts was one of the topics discussed by Andy Haldane, Chief Economist at the Bank of England. Speaking at the Institute for Government in London, he compared economic forecasting to weather forecasting (see section from 15’20” in the webcast):
“Remember that? Michael Fish getting up: ‘There’s no hurricane coming but it will be very windy in Spain.’ Very similar to the sort of reports central banks – naming no names – issued pre-crisis, ‘There is no hurricane coming but it might be very windy in the sub-prime sector.” (18’40”)
The problem with the standard economic models which were used for forecasting is that they were essentially equilibrium models which work reasonably well in ‘normal’ times. But when there is a large shock to the economic system, they work much less well. First, the shocks themselves are hard to predict. For example, the sub-prime crisis in 2007/8 was not foreseen by most economists.
Then there is the effect of the shocks. Large shocks are much harder to model as they can trigger strong reactions by consumers and firms, and governments too. These reactions are often hugely affected by sentiment. Bouts of pessimism or even panic can grip markets, as happened in late 2008 with the collapse of Lehman Brothers. Markets can tumble way beyond what would be expected by a calm adjustment to a shock.
It can work the other way too. Economists generally predicted that the Brexit vote would lead to a fall in GDP. However, despite a large depreciation of sterling, consumer sentiment held up better than was expected and the economy kept growing.
But is it fair to compare economic forecasting with weather forecasting? Weather forecasting is concerned with natural phenomena and only seeks to forecast with any accuracy a few days ahead. Economic forecasting, if used correctly, highlights the drivers of economic change, such as government policy or the Brexit vote, and their likely consequences, other things being equal. Given that economies are constantly being affected by economic shocks, including government or central bank actions, it is impossible to forecast the state of the macroeconomy with any accuracy.
This does not mean that forecasting is useless, as it can highlight the likely effects of policies and take into account the latest surveys of, say, consumer and business confidence. It can also give the most likely central forecast of the economy and the likely probabilities of variance from this central forecast. This is why many forecasts use ‘fan charts’: see, for example, Bank of England forecasts.
What economic forecasts cannot do is to predict the precise state of the economy in the future. However, they can be refined to take into account more realistic modelling, including the modelling of human behaviour, and more accurate data, including survey data. But, however refined they become, they can only ever give likely values for various economic variables or likely effects of policy measures.
Webcast
Andy Haldane in Conversation Institute for Government (5/1/17)
Articles
‘Michael Fish’ Comments From Andy Haldane Pounced Upon By Brexit Supporters Huffington Post, Chris York (6/1/17)
Crash was economists’ ‘Michael Fish’ moment, says Andy Haldane BBC News (6/1/17)
The Bank’s ‘Michael Fish’ moment BBC News, Kamal Ahmed (6/1/17)
Bank of England’s Haldane admits crisis in economic forecasting Financial Times, Chris Giles (6/1/17)
Chief economist of Bank of England admits errors in Brexit forecasting BBC News, Phillip Inman (5/1/17)
Economists have completely failed us. They’re no better than Mystic Meg The Guardian, Simon Jenkins (6/1/17)
Five things economists can do to regain trust The Guardian, Katie Allen and Phillip Inman (6/1/17)
Andy Haldane: Bank of England has not changed view on negative impact of Brexit Independent, Ben Chu (5/1/17)
Big data could help economists avoid any more embarrassing Michael Fish moments Independent, Hamish McRae (7/1/17)
Questions
- In what ways does economic forecasting differ from weather forecasting?
- How might economic forecasting be improved?
- To what extent were the warnings of the Bank of England made before the Brexit vote justified? Did such warnings take into account actions that the Bank of England was likely to take?
- How is the UK economy likely to perform over the coming months? What assumptions are you making here?
- Brexit hasn’t happened yet. Why is it extremely difficult to forecast today what the effects of actually leaving the EU will be on the UK economy once it has happened?
- If economic forecasting is difficult and often inaccurate, should it be abandoned?
- The Bank of England is forecasting that inflation will rise in the coming months. Discuss reasons why this forecast is likely to prove correct and reasons why it may prove incorrect.
- How could economic forecasters take the possibility of a Trump victory into account when making forecasts six months ago of the state of the global economy a year or two ahead?
- How might the use of big data transform economic forecasting?
Some commentators have seen the victory of Donald Trump and, prior to that, the Brexit vote as symptoms of a crisis in capitalism. Much of the campaigning in the US election, both by Donald Trump on the right and Bernie Sanders on the left focused on the plight of the poor. Whether the blame was put on immigration, big government, international organisations, the banks, cheap imports undercutting jobs or a lack of social protection, the message was clear: capitalism is failing to improve the lot of the majority. A small elite is getting significantly richer while the majority sees little or no gain in their living standards and a rise in uncertainty.
The articles below look at this crisis. They examine the causes, which they agree go back many years as capitalism has evolved. The financial crash of 2008 and the slow recovery since are symptomatic of the underlying changes in capitalism.
The Friedman article focuses on the slowing growth in technological advance and the problem of aging populations. What technological progress there is is not raising incomes generally, but is benefiting a few entrepreneurs and financiers. General rises in income may eventually come, but it may take decades before robotics, biotechnological advances, e-commerce and other breakthrough technologies filter through to higher incomes for everyone. In the meantime, increased competition through globalisation is depressing the incomes of the poor and economically immobile.
All the articles look at the rise of the rich. The difference with the past is that the people who are gaining the most are not doing so from production but from financial dealing or rental income; they have gained while the real economy has stagnated.
The gains to the rich have come from the rise in the value of assets, such as equities (shares) and property, and from the growth in rental incomes. Only a small fraction of finance is used to fund business investment; the majority is used for lending against existing assets, which then inflates their prices and makes their owners richer. In other words, the capitalist system is moving from driving growth in production to driving the inflation of asset prices and rental incomes.
The process whereby financial markets grow and in turn drive up asset prices is known as ‘financialisation’. Not only is the process moving away from funding productive investment and towards speculative activity, it is leading to a growth in ‘short-termism’. The rewards of senior managers often depend on the price of their companies’ shares. This leads to a focus on short-term profit and a neglect of long-term growth and profitability – to a neglect of investment in R&D and physical capital.
The process of financialisation has been driven by deregulation, financial innovation, the growth in international financial flows and, more recently, by quantitative easing and low interest rates. It has led to a growth in private debt which, in turn, creates more financial instability. The finance industry has become so profitable that even manufacturing companies are moving into the business of finance themselves – often finding it more profitable than their core business. As the Foroohar article states, “the biggest unexplored reason for long-term slower growth is that the financial system has stopped serving the real economy and now serves mainly itself.”
So will the election of Donald Trump, and pressure from populism in other countries too, mean that governments will focus more on production, job creation and poverty reduction? Will there be a movement towards fiscal policy to drive infrastructure spending? Will there be a reining in of loose monetary policy and easy credit?
Or will addressing the problem of financialisation and the crisis of capitalism result in the rich continuing to get richer at the expense of the poor, but this time through more conventional channels, such as increased production and monopoly profits and tax cuts for the rich? Trump supporters from among the poor hope the answer is no. Those who supported Bernie Sanders in the Democratic primaries think the answer will be yes and that the solution to over financialisation requires more, not less, regulation, a rise in minimum wages and fiscal policies aimed specifically at the poor.
Articles
Can Global Capitalism Be Saved? Project Syndicate, Alexander Friedman (11/11/16)
American Capitalism’s Great Crisis Time, Rana Foroohar (12/5/16)
The Corruption of Capitalism by Guy Standing review – work matters less than what you own The Guardian, Katrina Forrester (26/10/16)
Questions
- Do you agree that capitalism is in crisis? Explain.
- What is meant by financialisation? Why has it grown?
- Will the policies espoused by Donald Trump help to address the problems caused by financialisation?
- What alternative policies are there to those of Trump for addressing the crisis of capitalism?
- Explain Schumpeter’s analysis of creative destruction.
- What technological innovations that are currently taking place could eventually benefit the poor as well as the rich?
- What disincentives are there for companies investing in R&D and new equipment?
- What are the arguments for and against a substantial rise in the minimum wage?
