Category: Economics for Business: 8e Ch 09

Each week, BBC Radio 4 broadcasts readings from a book serialised in five 15-minute episodes. In the week beginning 18 January 2021, the readings were from English Pastoral: An Inheritance by James Rebanks, a farmer from the Cumbrian fells. His farm is relatively small, covering 185 acres.

He has attempted to make it much more sustainable and less intensive, reintroducing traditional Herdwick sheep, having a mixture of cows and sheep rather than just sheep, a greater sub-division of fields, and more natural scrubland, peatbogs and trees. As a result, soil quality has improved and there has been an explosion of biodiversity, with an abundance of wild flowers and insects.

Apart from being an autobiography of his time as a farmer and his attempt to move towards more traditional methods, the book examines broader issues of agricultural sustainability. It looks at the pressures of consumers wanting cheap food, the market power of supermarkets and wholesalers, the cost pressures on farmers pushing them towards monoculture to achieve economies of scale, and the role of the agrichemicals industry promoting fertilisers, feeds and pesticides which bring short-term financial gains to farmers, but which cause longer-term damage to the land and to biodiversity.

Rebanks has gained quite a lot of media attention after the publication of his first book, The Shepherd’s Life, including being one of the guests on Desert Island Discs and the subject of an episode of The Food Programme.

Listen to the Food Programme podcast and try answering the questions, which are all based on the podcast in the order of the points made in the interview.

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Questions

  1. What are the incentives of an unregulated market for food that result in monoculture and a loss of biodiversity?
  2. To what extent are consumers responsible for changes in farming methods?
  3. Have the changes helped the urban poor?
  4. How is the monopsony power of supermarkets and food wholesalers impacting on food production and the pattern of agriculture?
  5. There are various (private) economies of scale in food production, but these often involve substantial external costs and long-term private costs too. How does this impact on land use?
  6. What are some of the limits of technology in increasing crop, meat and dairy yields?
  7. Will more recent changes in the pattern of food consumption help to increase mixed farming and biodiversity?
  8. Is it ‘rational’ for many farmers to continue with intensive farming with high levels of artificial fertilisers and pesticides?
  9. Is diversity in farming across farms within a local area a public good? If so, how could such diversity be achieved?
  10. How can farmers be encouraged to think and act holistically?
  11. Is there a trade-off between food output and biodiversity?
  12. What are the dangers in the UK reaching an agricultural trade deal with the USA?
  13. What are the benefits and costs of encouraging local food markets?

Some firms in the high-Covid, tier 3 areas in England are being forced to shut by the government. These include pubs and bars not serving substantial meals. Similarly, pubs in the central belt of Scotland must close. But how should such businesses and their employees be supported?

As we saw in the blog, The new UK Job Support Scheme: how much will it slow the rise in unemployment?, the government will support such businesses by paying two-thirds of each employees’ salary (up to a maximum of £2100 a month) and will give cash grants to the businesses of up to £3000 per month.

This support has been criticised by local leaders, such as those in Greater Manchester, as being insufficient. Workers, they argue, will struggle to pay their bills and the support for firms will be too little to prevent many closing for good. What is more, many firms and their employees in the supply chain, such as breweries, will get no support. Greater Manchester resisted being put into tier 3 unless the level of support was increased. However, tier 3 status was imposed on the authority on 20 October despite lack of agreement with local politicians on the level of support.

Jim O’Neill, Vice Chair of the Northern Powerhouse partnership, has argued that the simplest way of supporting firms forced to close is to guarantee their revenue. He stated that:

The government would be sensible to guarantee the revenues of businesses it is forcing to shut. It is easier, fairer and probably less costly in the long run – and a proper test of the government’s confidence that in the New Year two of the seven vaccines the UK has signed up to will work.

This would certainly help firms to survive and allow them to pay their employees. But would guaranteeing revenues mean that such firms would see an increase in profits? The questions below explore this issue.

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Questions

  1. Identify the fixed and variable costs for a pub (not owned by a brewery).
  2. If a pub closed down but the wages of workers continued to be paid in full, what cost savings would be made?
  3. If a pub closed down but was given a monthly grant by the government equal to its previous monthly total revenue but had to pay the wages of it workers in full, what would happen to its profits?
  4. On 19 October, the Welsh government introduced a two-week lockdown for Wales. Under these restrictions, all non-essential retail, leisure, hospitality and tourism businesses had to close. Find out what support was on offer for such firms and their workforce and compare it to other parts of the UK.
  5. What type of support for leisure and hospitality businesses forced by the government to close would, in your opinion, be optimal? Justify your answer.
  6. Is there any moral hazard from the government providing support for businesses made unprofitable by the Covid-19 crisis? Explain.

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.

It’s been a while since I last blogged about labour markets and, in particular, about the effect of automation on wages and employment. My most recent post on this topic was on the 14th of April 2018 and it was mostly a reflection on some interesting findings that had been reported by Acemoglu et al (2017). More specifically, Acemoglu and Restrepo (2017) developed a theoretical framework to evaluate the effect of AI on employment and wages. They concluded that the effect was negative and potentially sizeable (for a more detailed discussion see my blog).

Using a model in which robots compete against human labor in the production of different tasks, we show that robots may reduce employment and wages … According to our estimates, one more robot per thousand workers reduces the employment to population ratio by about 0.18–0.34 percentage points and wages by 0.25–0.5 percent.

Since then, I have seen a constant stream of news on my news feed about the development of ever more advanced industrial robots and artificial intelligence. And this was not because of some spooky coincidence (or worse). It has been merely a reflection of the speed at which technology has been progressing in this field.

There are now robots that can run, jump, hold conversations with humans, do gymnastics (and even sweat for it!) and more. It is really impressive how fast change has been happening recently in this field – and, unsurprisingly, it has stimulated the interest of labour economists!

A paper that has recently come to my attention on this subject is by Graetz and Michaels (2018). The authors put together a panel dataset on robot adoption within seventeen countries from 1993 to 2007 and use advanced econometric techniques to evaluate the effect of these technologies on employment and productivity growth. Their analysis focuses exclusively on developed economies (due to data limitations, as they explain) – but their results are nevertheless intriguing:

We study here for the first time the relationship between industrial robots and economic outcomes across much of the developed world. Using a panel of industries in seventeen countries from 1993 to 2007, we find that increased use of industrial robots is associated with increases in labor productivity. We find that the contribution of increased use of robots to productivity growth is substantial and calculate using conservative estimates that it comes to 0.36 percentage points, accounting for 15% of the aggregate economy-wide productivity growth.
 
The pattern that we document is robust to including various controls for country trends and changes in the composition of labor and other capital inputs. We also find that robot densification is associated with increases in both total factor productivity and wages, and reductions in output prices. We find no significant relationship between the increased use of industrial robots and overall employment, although we find that robots may be reducing the employment of low-skilled workers.

This is very positive news for most – except, of course, for low-skilled workers. Indeed, like Acemoglu and Restrepo (2017) and many others, this study shows that the effect of automation on employment and labour market outcomes is unlikely to be uniform across all types of workers. Low-skilled workers are found again to be likely to lose out and be significantly displaced by these technologies.

And if you are wondering which sectors are likely to be disrupted most/first by automation, the rankings developed by McKinsey and Company (see chart below) would give you an idea of where the disruption is likely to start. Unsurprisingly, the sectors that seem to be the most vulnerable, are the ones that use the highest share of low-skilled labour.

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Questions

  1. “The effect of automation on wages and employment is likely to be positive overall”. Discuss.
  2. Using examples and anecdotal evidence, do you agree with these findings?
  3. Using Google Scholar, put together a list of 5 recent (i.e. 2015 or later) articles and working papers on labour markets and automation. Compare and discuss their findings.

When did you last think about buying a new car? If not recently, then you may be in for a surprise next time you shop around for car deals. First, you will realise that the range of hybrid cars (i.e. cars that combine conventional combustion and electric engines) has widened significantly. The days when you only had a choice of Toyota Prius and another two or three hybrids are long gone! A quick search on the web returned 10 different models (although five of them belong to the Toyota Prius family), including Chevrolet Malibu, VW Jetta and Ford Fusion. And these are only the cars that are currently available in the UK market.

But the biggest surprise of all may be the number of purely (plug-) electric cars that are available to UK buyers these days. The table below provides a summary of total registrations of light-duty plug-electric cars by model in the UK, between 2010 and June 2016.

Registration of light-duty highway legal plug-electric cars by model in the UK between 2010 and June 2016

Model

Total registered at the end of(1)

Registrations by year between 2010 and December 2013

2Q 2016

2015

2014

2013

2012

2011

2010

Mitsubishi Outlander P-HEV

21 708

16 100

5 273

 

 

 

 

Nissan Leaf

12 837

11 219

6 838

1 812

699

635

 

BMW i3

4 457

3 574

1 534

NA

 

 

 

Renault Zoe

4 339

3 327

1 356

378

 

 

 

Mercedes-Benz C350 e

3 337

628

0

 

 

 

 

Tesla Model S

3 312

2 087

698

 

 

 

 

Volkswagen Golf GTE

2 657

1 359

0

 

 

 

 

Toyota Prius PHV

1 655

1 580

1 324

509

470

 

 

Audi A3 e-tron

1 634

1 218

66

 

 

 

 

Nissan e-NV200

1 487

1 047

399

 

 

 

 

BMW 330e iPerformance

1 479

 

 

 

 

 

 

BMW i8

1 307

1 022

279

 

 

 

 

Vauxhall Ampera

1 267

1 272

1 169

175

455

4

 

Volvo XC90 T8

813

38

 

 

 

 

 

Renault Kangoo Z.E

785

740

663

 

 

 

 

Porsche Panamera S E-Hybrid

475

395

241

 

 

 

 

Volvo V60 Plug-in Hybrid

410

337

232

 

 

 

 

Peugeot iOn

405

374

368

26(2)

251

124

 

Mercedes-Benz B-Class Electric Drive

303

162

0

 

 

 

 

Mitsubishi i MiEV

252

251

266

1(2)

107

125

27

Smart electric drive

215

212

205

3(2)

13

 

63

Citroën C-Zero

213

167

202

45(2)

110

46

 

Kia Soul EV

193

145

20

 

 

 

 

BMW 225xe

163

 

 

 

 

 

 

Volkswagen e-Up!

154

142

118

 

 

 

 

Mercedes-Benz S500 PHEV

125

157

14

 

 

 

 

Volkswagen e-Golf

123

114

47

 

 

 

 

Chevrolet Volt

119

122

124

23(2)

67

 

 

Renault Fluence Z.E.

79

70

73

7(2)

67

 

 

Ford Focus Electric

22

19

19

 

 

 

 

Mercedes-Benz Vito E-Cell

22

23

23

 

 

 

 

Mia electric

15

15

14

 

 

 

 

Volkswagen Passat GTE

1

 

 

 

 

 

 

BYD e6

0

0

0

50(2)

 

 

 

Total registrations

66 374

47 920

21 504

3 586

2 254

1 082

138

Notes: NA: not available. Registrations figures seldom correspond to same sales figure.

(1) Registrations at the end of a period are cumulative figures. (2) CYTD through June 2013.

Source: Wikipedia, “Plug-in electric vehicles in the United Kingdom”

In 2010 there were nly 138 electric vehicles in total registered in the UK. They were indeed an unusual sight at that time – and good luck to you if you had one and you happened to run out of power in the middle of a journey. In 2011 this (small) number increased sevenfold – an increase that was driven mostly by the successful introduction of Nissan Leaf (635 electric Nissans were registered in the UK that year). And since then the number of electric vehicles registered in the country has increased with spectacular speed, at an average rate of 252% per year.

There is clearly strong interest in electric vehicles – an interest likely to increase as their price becomes more competitive. However, they are still very expensive items to buy, especially when compared with their conventional fuel-engine counterparts. What makes electric cars expensive? One thing is the cost of purchasing and maintaining a battery that can deliver a reasonable range. But the cost of batteries is falling, as more and more companies realise the potential of this new market and join the R&D race. As mentioned in a special report that was published recently in the FT:

The cost of lithium-ion batteries has fallen by 75 per cent over the past eight years, measured per kilowatt hour of output. Every time battery production doubles, costs fall by another 5 per cent to 8 per cent, according to analysts at Wood Mackenzie.

There is no doubt that more research will result in more efficient batteries, and will increase the interest in electric cars not only by consumers but also by producers, who already see the opportunity of this new global market. Does this mean that prices will necessarily fall further? You might think so, but then you have to take into consideration the availability and cost of mining further raw materials to make these batteries (such as cobalt, which is one of the materials used in the making of lithium-ion batteries and nearly half of which is currently sourced from the Democratic Republic of Congo). This may lead to bottlenecks in the production of new battery units. In which case, the price of batteries (and, by extension, the price of electric cars) may not fall much further until some new innovation happens that changes either the material or its efficiency.

The good news is that a lot of researchers are currently looking into these questions, and innovation will do what it always does: give solutions to problems that previously appeared insurmountable. They had better be fast because, according to estimates by Wood Mackenzie, the number of electric vehicles globally is expected to rise by over 50 times – from 2 million (in 2017) to over 125 million by 2035.

How many economists does it take to charge an electric car? I guess we are going to find out!

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Questions

  1. Using a demand and supply diagram, explain the relationship between the price of a battery and the market (equilibrium) price of a plug-in electric vehicle.
  2. List all non-price factors that influence demand for plug-in electric vehicles. Briefly explain each.
  3. Should the government subsidise the development and production of electric car batteries? Explain the advantages and disadvantages of such intervention and take a position.