Category: Economics 10e: Ch 15

Elections are times of peak deception. Political parties have several ways in which they can use data to persuade people to vote for them. At one extreme, they can simply make up ‘facts’ – in other words, they can lie. There have been various examples of such lies in the run-up to the UK general election of 12 December 2019. The linked article below gives some examples. But data can be used in other deceptive ways, short of downright lies.

Politicians can use data in two ways. First, statistics can be used to describe, explain and interpret the past. Second, they can be used as the basis of forecasts of the future effects of policies.

In terms of past data, one of the biggest means of deception is the selective use of data. If you are the party currently in power, you highlight the good news and ignore the bad. You do the reverse if you are currently in opposition. The data may be correct, but selective use of data can give a totally false impression of events.

In terms of forecast data, you highlight those forecasts, or elements of them, that are favourable to you and ignore those that are not.

Politicians rely on people’s willingness to look selectively at data. People want to see ‘evidence’ that reinforces their political views and prejudices. News media know this and happily do the same as politicians, selectively using data favourable to their political leanings. And it’s not just newspapers that do this. There are many online news sites that feed their readers with data supportive of their position. And there are many social media platforms, where people can communicate with people in their political ‘bubble’.

Genuine fact-checking sites can help, as can independent forecasters, such as the Institute for Fiscal Studies. But too many voters would rather only look at evidence, genuine or not, that supports their political point of view.

This can make life hard for economists who seek to explain the world with an open mind, based on a non-biased use of evidence – and hard for economic forecasters, who want to use full and accurate data in their models and to make realistic assumptions, emphasising that their forecasts are only the most likely outcome, not a certainty. As the article states:

Economic forecasts are flawed and their limitations should be acknowledged. But they should not be blindly dismissed as fake facts. And as far as political debate and discourse is concerned, in the long run, the truth may will out.

Article

Questions

  1. Give some specific examples of ways in which politicians misuse data.
  2. Give some specific examples of ways in which politicians misuse the analysis of economists.
  3. Distinguish between positive and normative statements? Should economists make policy recommendations? If so, in what context?
  4. Why are economic forecasts flawed, but why should they not be dismissed as ‘fake facts’?
  5. Examine the manifestos of two political parties and provide a critique of their economic analysis.

Economists are often criticised for making inaccurate forecasts and for making false assumptions. Their analysis is frequently dismissed by politicians when it contradicts their own views.

But is this fair? Have economists responded to the realities of the global economy and to the behaviour of people, firms, institutions and government as they respond to economic circumstances? The answer is a qualified yes.

Behavioural economics is increasingly challenging the simple assumption that people are ‘rational’, in the sense that they maximise their self interest by weighing up the marginal costs and benefits of alternatives open to them. And macroeconomic models are evolving to take account of a range of drivers of global growth and the business cycle.

The linked article and podcast below look at the views of 2019 Nobel Prize-winning economist Esther Duflo. She has challenged some of the traditional assumptions of economics about the nature of rationality and what motivates people. But her work is still very much in the tradition of economists. She examines evidence and sees how people respond to incentives and then derives policy implications from the analysis.

Take the case of the mobility of labour. She examines why people who lose their jobs may not always move to a new one if it’s in a different town. Partly this is for financial reasons – moving is costly and housing may be more expensive where the new job is located. Partly, however, it is for reasons of identity. Many people are attached to where they currently live. They may be reluctant to leave family and friends and familiar surroundings and hope that a new job will turn up – even if it means a cut in wages. This is not irrational; it just means that people are driven by more than simply wages.

Duflo is doing what economists typically do – examining behaviour in the light of evidence. In her case, she is revisiting the concept of rationality to take account of evidence on what motivates people and the way they behave.

In the light of workers’ motivation, she considers the implications for the gains from trade. Is free trade policy necessarily desirable if people lose their jobs because of cheap imports from China and other developing countries where labour costs are low?

The answer is not a clear yes or no, as import-competing industries are only part of the story. If protectionist policies are pursued, other countries may retaliate with protectionist policies themselves. In such cases, people working in the export sector may lose their jobs.

She also looks at how people may respond to a rise or cut in tax rates. Again the answer is not clear cut and an examination of empirical evidence is necessary to devise appropriate policy. Not only is there an income and substitution effect from tax changes, but people are motivated to work by factors other than take-home pay. Likewise, firms are encouraged to invest by factors other than the simple post-tax profitability of investment.

Podcast

Article

Questions

  1. In traditional ‘neoclassical’ economics, what is meant by ‘rationality’ in terms of (a) consumer behaviour; (b) producer behaviour?
  2. How might the concept of rationality be expanded to take into account a whole range of factors other than the direct costs and benefits of a decision?
  3. What is meant by bounded rationality?
  4. What would be the effect on workers’ willingness to work more or fewer hours as a result of a cut in the marginal income tax rate if (a) the income effect was greater than the substitution effect; (b) the substitution effect was greater than the income effect? Would your answers to (a) and (b) be the opposite in the case of a rise in the marginal income tax rate?
  5. Give some arguments that you consider to be legitimate for imposing controls on imports in (a) the short run; (b) the long run. How might you counter these arguments from a free-trade perspective?

A general election has been called in the UK for 12 December. Central to the debates between the parties will be their policy on Brexit.

They range from the Liberal Democrats’, Plaid Cymru’s and Sinn Féin’s policy of cancelling Brexit and remaining in the EU, to the Scottish Nationalists’ and Greens’ policy of halting Brexit while a People’s Vote (another referendum) is held, with the parties campaigning to stay in the EU, to the Conservative Party’s policy of supporting the Withdrawal Agreement and Political Declaration negotiated between the Boris Johnson government and the EU, to the DUP which supports Brexit but not a version which creates a border between Great Britain and Northern Ireland, to the Brexit Party and UKIP which support leaving the EU with no deal (what they call a ‘clean break’) and then negotiating individual trade deals on a country-by-country basis.

The Labour Party also supports a People’s Vote, but only after renegotiating the Withdrawal Agreement and Political Declaration, so that if Brexit took place, the UK would have a close relationship with the single market and remain in a customs union. Also, various laws and regulations on environmental protection and workers’ rights would be retained. The referendum would take place within six months of the election and would be a choice between this new deal and remain.

But what are the economic costs and benefits of these various alternatives? Prior to the June 2016 referendum, the Treasury costed various scenarios. After 15 years, a deal would make UK GDP between 3.4% and 7.8% lower than if it remained in the EU, depending on the nature of the deal. No deal would make GDP between 5.4% and 9.5% lower.

Then in November 2018, the Treasury published analysis of the original deal negotiated by Theresa May in July 2018 (the ‘Chequers deal’). It estimated that GDP would be up to 3.9% lower after 15 years than it would have been if the UK had remained in the EU. In the case of a no-deal Brexit, GDP would be up to 9.3% lower after 15 years.

When asked for Treasury forecasts of the effects of Boris Johnson’s deal, the Chancellor, Sajid Javid, said that the Treasury had not been asked to provide forecasts as the deal was “self-evidently in our economic interest“.

Other forecasters, however, have analysed the effects of the Johnson deal. The National Institute for Economic and Social Research (NIESR), the UK’s longest established independent economic research institute, has estimated the costs of various scenarios, including the Johnson deal, the May deal, a no-deal scenario and also a scenario of continuing uncertainty with no agreement over Brexit. The NIESR estimates that, under the Johnson deal, with a successful free-trade agreement with the EU, in 10 years’ time UK GDP will be 3.5% lower than it would be by remaining in the EU. This represents a cost of £70 billion. The costs would arise from less trade with the EU, lower inward investment, slower growth in productivity and labour shortages from lower migration. These would be offset somewhat by savings on budget contributions to the EU.

Under Theresa May’s deal UK GDP would be 3.0% lower (and thus slightly less costly than Boris Johnson’s deal). Continuing in the current situation with chronic uncertainty about whether the UK would leave or remain would leave the UK 2% worse off after 10 years. In other words, uncertainty would be less damaging than leaving. The costs from the various scenarios would be in addition to the costs that have already occurred – the NIESR estimates that GDP is already 2.5% smaller than it would have been as a result of the 2016 Brexit vote.

Another report also costs the various scenarios. In ‘The economic impact of Boris Johnson’s Brexit proposals’, Professors Anand Menon and Jonathan Portes and a team at The UK in a Changing Europe estimate the effects of a decline in trade, migration and productivity from the various scenarios – again, 10 years after new trading arrangements are in place. According to their analysis, UK GDP would be 4.9%, 6.4% and 8.1% lower with the May deal, the Johnson deal and no deal respectively than it would have been from remaining in the EU.

But how much reliance should we put on such forecasts? How realistic are their assumptions? What other factors could they have taken into account? Look at the two reports and at the articles discussing them and then consider the questions below which are concerned with the nature of economic forecasting.

Articles

Reports

Questions

  1. What are the arguments in favour of the assumptions and analysis of the two recent reports considered in this blog?
  2. What are the arguments against the assumptions and analysis of the two reports?
  3. How useful are forecasts like these, given the inevitable uncertainty surrounding (a) the outcome of negotiations post Brexit and (b) the strength of the global economy?
  4. If it could be demonstrated beyond doubt to everyone that each of the Brexit scenarios meant that UK GDP would be lower than if it remained in the EU, would this prove that the UK should remain in the EU? Explain.
  5. If economic forecasts turn out to be inaccurate, does this mean that economists should abandon forecasting?

The latest UK house price index reveals that annual house price growth in the UK slowed to just 1.2 per cent in May. This is the lowest rate of growth since January 2013. This is being driven, in part, by the London market where annual house price inflation rates have now been negative for 15 consecutive months. In May the annual rate of house price inflation in London fell to -4.4 per cent, it lowest since August 2009 as the financial crisis was unfolding. However, closer inspection of the figures show that while many other parts of the country continue to experience positive rates of annual house price inflation, once general inflation is accounted for, there is widespread evidence of widespread real house price deflation.

The average UK house price in May 2019 was £229,000. As Chart 1 shows, this masks considerable differences across the UK. In England the average price was £246,000 (an annual increase of 1.0 per cent), in Scotland it was £153,000 (an increase of 2.8 per cent), in Wales £159,000 (an increase of 3.0 per cent) and in Northern Ireland it was £137,000 (an increase of 2.1 per cent). (Click here to download a PowerPoint copy of the chart.)

The London market distorts considerably the English house price figures. In London the average house price in May 2019 was £457,000 (an annual decrease of 4.4 per cent). House prices were lowest in the North East region of England at £128,000. The North East was the only other English region alongside London to witness a negative rate of annual house price inflation, with house prices falling in the year to May 2019 by 0.7 per cent.

Chart 2 allows us to see more readily the rates of house price growth. It plots the annual rates of house price inflation across London, the UK and its nations. What is readily apparent is the volatility of house price growth. This is evidence of frequent imbalances between the flows of property on to the market to sell (instructions to sell) and the number of people looking to buy (instructions to buy). An increase in instructions to buy relative to those to sell puts upwards pressure on prices whereas an increase in the relative number of instructions to sell puts downward pressure on prices. (Click here to download a PowerPoint copy of the chart.)

Despite the volatility in house prices, the longer-term trend in house prices is positive. The average annual rate of growth in house prices between January 1970 and May 2019 in the UK is 9.1 per cent. For England the figure is 9.4 per cent, for Wales 8.8 per cent, for Scotland 8.5 per cent and for Northern Ireland 8.3 per cent. In London the average rate of growth is 10.4 per cent per annum.

As Chart 3 illustrates, the longer-term growth in actual house prices cannot be fully explained by the growth in consumer prices. It shows house price values as if consumer prices, as measured by the Retail Prices Index (RPI), were fixed at their January 1987 levels. We see real increases in house prices or, expressed differently, in house prices relative to consumer prices. In real terms, UK house prices were 3.6 times higher in May 2019 compared to January 1970. For England the figure is 4.1 times, for Wales 3.1 times, for Scotland 2.9 times and for Northern Ireland 2.1 times. In London inflation-adjusted house prices were 5.7 times higher. (Click here to download a PowerPoint copy of the chart.)

The volatility in house prices continues to be evident when adjusted for changes in consumer prices. The UK’s annual rate of real house price inflation was as high as 40 per in January 1973, yet, on the other hand, in June 1975 inflation-adjusted house prices were 16 per cent lower than a year earlier. Over the period from January 1970 to May 2019, the average annual rate of real house price inflation was 3.2 per cent. Hence house prices have, on average, grown at an annual rate of consumer price inflation plus 3.2 per cent.

Chart 4 shows annual rates of real house price inflation since 2008 and, hence, from around the time the financial crisis began to unfold. The period is characterised by acute volatility and with real house prices across the UK falling at an annual rate of 16 per cent in 2009 and by as much 29 per cent in Northern Ireland. (Click here to download a PowerPoint copy of the chart.)

The UK saw a rebound in nominal and real house price growth in the period from 2013, driven by a strong surge in prices in London and the South East, and supported by government initiatives such as Help to Buy designed to help people afford to buy property. But house price growth then began to ease from early/mid 2016. Some of the easing may be partly due to any excessive fizz ebbing from the market, especially in London, and the impact on the demand for buy-to-let investments resulting from reductions in tax relief on interest payments on buy-to-let mortgages.

However, the housing market is notoriously sensitive to uncertainty, which is not surprising when you think of the size of the investment people are making when they enter the market. The uncertainty surrounding Brexit and the UK’s future trading relationships will have been a drag on demand and hence on house prices.

Chart 4 shows that by May 2019 all the UK nations were experiencing negative rates of real house price inflation, despite still experiencing positive rates of nominal house price inflation. In Wales the real annual house price inflation rate was -0.1 per cent, in Scotland -0.2 per cent, in Northern Ireland -0.9 per cent and in England -2.0 per cent. Meanwhile in London, where annual house price deflation has been evident for 15 consecutive months, real house prices in May 2019 were falling at an annual rate of 7.2 per cent.

Going forward the OBR’s Fiscal Risks Report predicts that, in the event of a no-deal, no-transition exit of the UK from the European Union, nominal UK house prices would fall by almost 10 per cent between the start of 2019 and mid-2021. This forecast is driven by the assumption that the UK would enter a year-long recession from the final quarter of 2019. It argues that property transactions and prices ‘move disproportionately’ during recessions. (See John’s blog The costs of a no-deal Brexit for a fuller discussion of the economics of a no-deal Brexit). The danger therefore is that the housing market becomes characterised by both nominal and real house price falls.

Articles

Questions

  1. Explain the difference between a rise in the rate of house price inflation a rise in the level of house prices.
  2. Explain the difference between nominal and real house prices.
  3. If nominal house prices rise can real house price fall? Explain your answer.
  4. What do you understand by the terms instructions to buy and instructions to sell?
  5. What factors are likely to affect the levels of instructions to buy and instructions to sell?
  6. How does the balance between instructions to buy and instructions to sell affect house prices?
  7. How can we differentiate between different housing markets? Illustrate your answer with examples.

Confidence figures suggest that sentiment weakened across several sectors in June with significant falls recorded in retail and construction. This is consistent with the monthly GDP estimates from the ONS which suggest that output declined in March and April by 0.1 per cent and 0.4 per cent respectively. The confidence data point to further weakness in growth down the line. Furthermore, it poses the risk of fuelling a snowball effect with low growth being amplified and sustained by low confidence.

Chart 1 shows the confidence balances reported by the European Commission each month since 2007. It highlights the collapse in confidence across all sectors around the time of the financial crisis before a strong and sustained recovery in the 2010s. However, in recent months confidence indicators have eased significantly, undoubtedly reflecting the heightened uncertainty around Brexit. (Click here to download a PowerPoint copy of the chart.)

Between June 2016 and June 2019, the confidence balances have fallen by at least 8 percentage points. In the case of the construction the fall is 14 points while in the important service sector, which contributes about 80 per cent of the economy’s national income, the fall is as much as 15 points.

Changes in confidence are thought, in part, to reflect levels of economic uncertainty. In particular, they may reflect the confidence around future income streams with greater uncertainty pulling confidence down. This is pertinent because of the uncertainty around the UK’s future trading relationships following the 2016 referendum which saw the UK vote to leave the EU. In simple terms, uncertainty reduces the confidence people and businesses have when forming expectations of what they can expect to earn in the future.

Greater uncertainty and, hence, lower confidence tend to make people and businesses more prudent. The caution that comes from prudence counteracts the inherent tendency of many of us to be impatient. This impatience generates an impulse to spend now. On the other hand, prudence encourages us to take actions to increase net worth, i.e. wealth. This may be through reducing our exposure to debt, perhaps by looking to repay debts or choosing to borrow smaller sums than we may have otherwise done. Another option may be to increase levels of saving. In either case, the effect of greater prudence is the postponement of spending. Therefore, in times of high uncertainty, like those of present, people and businesses would be expected to want to have greater financial resilience because they are less confident about what the future holds.

To this point, the saving ratio – the proportion of disposable income saved by households – has remained historically low. In Q1 2019 the saving ratio was 4.4 per cent, well below its 60-year average of 8.5 per cent. This appears to contradict the idea that households respond to uncertainty by increasing saving. However, at least in part, the squeeze seen over many years following the financial crisis on real earnings, i.e. inflation-adjusted earnings, restricted the ability of many to increase saving. With real earnings having risen again over the past year or so, though still below pre-crisis levels, households may have taken this opportunity to use earnings growth to support spending levels rather than, as we shall see shortly, looking to borrow.

Another way in which the desire for greater financial resilience can affect behaviour is through the appetite to borrow. In the case of consumers, it could reduce borrowing for consumption, while in the case of firms it could reduce borrowing for investment, i.e. spending on capital, such as that on buildings and machinery. The reduced appetite for borrowing may also be mirrored by a tightening of credit conditions by financial institutions if they perceive lending to be riskier or want to increase their own financial capacity to absorb future shocks.

Chart 2 shows consumer confidence alongside the annual rate of growth of consumer credit (net of repayments) to individuals by banks and building societies. Consumer credit is borrowing by individuals to finance current expenditure on goods and services and it comprises borrowing through credit cards, overdraft facilities and other loans and advances, for example those financing the purchase of cars or other large ticket items. (Click here to download a PowerPoint copy of the chart.)

The chart allows us to view the confidence-borrowing relationship for the past 25 years or so. It suggests a fairly close association between consumer confidence and consumer credit growth. Whether changes in confidence occur ahead of changes in borrowing is debatable. However, the easing of confidence following the outcome of the EU referendum vote in June 2016 does appear to have led subsequently to an easing in the annual growth of consumer credit. From its peak of 10.9 per cent in the autumn of 2016, the annual growth rate of consumer credit dropped to 5.6 per cent in May 2019.

The easing of credit growth helps put something of a brake on consumer spending. It is, however, unlikely to affect all categories of spending equally. Indeed, the ONS figures for May on retail sales shows a mixed picture for the retail sector. Across the sector as a whole, the 3 month-on-3 month growth rate for the volume of purchases stood at 1.6 per cent, having fallen as low as 0.1 percent in December of last year. However, the 3 month-on-3 month growth rate for spending volumes in department stores, which might be especially vulnerable to a slowdown in credit, fell for the ninth consecutive month.

Going forward, the falls in confidence might be expected to lead to further efforts by the household sector, as well as by businesses, to ensure their financial resilience. The vulnerability of households, despite the slowdown in credit growth, so soon after the financial crisis poses a risk for a hard landing for the sector. After falls in national output in March and April, the next monthly GDP figures to be released on 10 July will be eagerly anticipated.

Articles

Questions

  1. Which of the following statements is likely to be more accurate: (a) Confidence drives economic activity or (b) Economic activity drives confidence?
  2. Explain the difference between confidence as a source of economic volatility as compared to an amplifier of volatility?
  3. Discuss the links between confidence, economic uncertainty and financial resilience.
  4. Discuss the ways in which people and businesses could improve their financial resilience to adverse shocks.
  5. What are the potential dangers to the economy of various sectors being financially distressed or exposed?