Category: Essential Economics for Business: Ch 01

The global economic impact of the coronavirus outbreak is uncertain but potentially very large. There has already been a massive effect on China, with large parts of the Chinese economy shut down. As the disease spreads to other countries, they too will experience supply shocks as schools and workplaces close down and travel restrictions are imposed. This has already happened in South Korea, Japan and Italy. The size of these effects is still unknown and will depend on the effectiveness of the containment measures that countries are putting in place and on the behaviour of people in self isolating if they have any symptoms or even possible exposure.

The OECD in its March 2020 interim Economic Assessment: Coronavirus: The world economy at risk estimates that global economic growth will be around half a percentage point lower than previously forecast – down from 2.9% to 2.4%. But this is based on the assumption that ‘the epidemic peaks in China in the first quarter of 2020 and outbreaks in other countries prove mild and contained.’ If the disease develops into a pandemic, as many health officials are predicting, the global economic effect could be much larger. In such cases, the OECD predicts a halving of global economic growth to 1.5%. But even this may be overoptimistic, with growing talk of a global recession.

Governments and central banks around the world are already planning measures to boost aggregate demand. The Federal Reserve, as an emergency measure on 3 March, reduced the Federal Funds rate by half a percentage point from the range of 1.5–1.75% to 1.0–1.25%. This was the first emergency rate cut since 2008.

Economic uncertainty

With considerable uncertainty about the spread of the disease and how effective containment measures will be, stock markets have fallen dramatically. The FTSE 100 fell by nearly 14% in the second half of February, before recovering slightly at the beginning of March. It then fell by a further 7.7% on 9 March – the biggest one-day fall since the 2008 financial crisis. This was specifically in response to a plunge in oil prices as Russia and Saudi Arabia engaged in a price war. But it also reflected growing pessimism about the economic impact of the coronavirus as the global spread of the epidemic accelerated and countries were contemplating more draconian lock-down measures.

Firms have been drawing up contingency plans to respond to panic buying of essential items and falling demand for other goods. Supply-chain managers are working out how to respond to these changes and to disruptions to supplies from China and other affected countries.

Firms are also having to plan for disruptions to labour supply. Large numbers of employees may fall sick or be advised/required to stay at home. Or they may have to stay at home to look after children whose schools are closed. For some firms, having their staff working from home will be easy; for others it will be impossible.

Some industries will be particularly badly hit, such as airlines, cruise lines and travel companies. Budget airlines have cancelled several flights and travel companies are beginning to offer substantial discounts. Manufacturing firms which are dependent on supplies from affected countries have also been badly hit. This is reflected in their share prices, which have seen large falls.

Longer-term effects

Uncertainty could have longer-term impacts on aggregate supply if firms decide to put investment on hold. This would also impact on the capital goods industries which supply machinery and equipment to investing firms. For the UK, already having suffered from Brexit uncertainty, this further uncertainty could prove very damaging for economic growth.

While aggregate supply is likely to fall, or at least to grow less quickly, what will happen to the balance of aggregate demand and supply is less clear. A temporary rise in demand, as people stock up, could see a surge in prices, unless supermarkets and other firms are keen to demonstrate that they are not profiting from the disease. In the longer term, if aggregate demand continues to grow at past rates, it will probably outstrip the growth in aggregate supply and result in rising inflation. If, however, demand is subdued, as uncertainty about their own economic situation leads people to cut back on spending, inflation and even the price level may fall.

How quickly the global economy will ‘bounce back’ depends on how long the outbreak lasts and whether it becomes a serious pandemic and on how much investment has been affected. At the current time, it is impossible to predict with any accuracy the timing and scale of any such bounce back.

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Questions

  1. Using a supply and demand diagram, illustrate the fall in stock market prices caused by concerns over the effects of the coronavirus.
  2. Using either (i) an aggregate demand and supply diagram or (ii) a DAD/DAS diagram, illustrate how a fall in aggregate supply as a result of the economic effects of the coronavirus would lead to (a) a fall in real income and (i) a fall in the price level or (ii) a fall in inflation; (b) a fall in real income and (i) a rise in the price level or (ii) a rise in inflation.
  3. What would be the likely effects of central banks (a) cutting interest rates; (b) engaging in further quantitative easing?
  4. What would be the likely effects of governments running a larger budget deficit as a means of boosting the economy?
  5. Distinguish between stabilising and destabilising speculation. How would you characterise the speculation that has taken place on stock markets in response to the coronavirus?
  6. What are the implications of people being paid on zero-hour contracts of the government requiring workplaces to close?
  7. What long-term changes to working practices and government policy could result from short-term adjustments to the epidemic?
  8. Is the long-term macroeconomic impact of the coronavirus likely to be zero, as economies bounce back? Explain.

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.

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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.

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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.

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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?