Category: Economics: Ch 12

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Biden’s green agenda

Back in November, when Joe Biden had just been elected, we considered some of his proposed policies to tackle climate change (see A new era for climate change policy?). On 20th January, the day of his inauguration, he signed 17 executive orders overturning a range of policies of the Trump presidency. Further executive orders followed. Some of these related directly to climate change.

The first was to cancel the Keystone XL oil pipeline project. If it had gone ahead, it would have transported 830 000 barrels of oil per day from the Alberta tar sands in Canada to refineries on the Gulf Coast of Texas. It would have involved building a new pipeline from Alberta to Nebraska, where it would have linked to an existing pipeline to Texas. Extracting oil from tar sands is a particularly dirty process, involves cutting down large areas of forest (a carbon sink) and total emissions are around 20% greater per barrel than from conventional crude.

The pipeline would have cut across First Nations land and any spills would have been highly toxic to the local environment. In terms of profitability, returns on tar sands oil extraction and transportation are very low. This is likely to remain the case as oil prices are likely to remain low, with greater global energy efficiency and the switch to renewables.

Critics of Biden’s decision argue that the pipeline project would have created some 5000 to 6000 temporary jobs in the USA during the two-year construction phase. Also they claim that it would have contributed to greater energy security for the USA.

The second executive order was to rejoin the Paris Climate Agreement, a process that will take 30 days. Rejoining will involve commitments to cut greenhouse gas emissions and the adoption of various measures to bring this about. During the election campaign, Biden pledged to achieve economy-wide net-zero emissions no later than 2050. As we saw in the previous blog, under Biden the USA will play a leading role in the November 2021 UN COP26 climate change conference in Glasgow.

At present, the Paris agreement is for countries to aim to reach a peak of greenhouse gas emissions as soon as possible to achieve a climate neutral world by mid-century. Many countries have have made commitments about when they aim to achieve carbon neutrality, although concrete action is much more limited. It is hoped that the COP26 conference will lead to stronger commitments and actions and that the USA under Biden will play a leading part in driving this forward.

In addition, to cancelling the Keystone XL pipeline and rejoining the Paris Agreement, the executive orders reversed more than 100 other decisions with negative environmental effects taken by the Trump administration – many overturning environmental measures introduced by previous administrations, especially the Obama administration.

These orders included reversing the easing of vehicle emissions standards; stopping reductions in the area of two major national monuments (parks) in Utah; enforcing a temporary moratorium on oil and natural gas leases in Alaska’s Arctic National Wildlife Refuge; and re-establishing a working group on the social costs of greenhouse gasses.

Then there will be new measures, such as adopting strict fuel economy standards and investment in clean public transport. But it remains to be seen how far and fast the Biden administration can move to green the US economy. With the desire for bipartisanship and seeking an end to the divisive policies of Trump, there may be limits to what the new President can achieve in terms of new legislation, especially with a Senate divided 50:50 and only the casting vote of the chair (Kamala Harris as Vice-President) being in Democrat hands.

The articles below consider the various green policies and how likely they are to succeed in their objectives.

Articles

Questions

  1. Find out what other environmental policies are being pursued by President Biden and assess their likely effectiveness in achieving their environmental objectives.
  2. Would policies to reduce carbon emissions necessarily be desirable? How would you assess their desirability?
  3. When is it best to use the ‘precautionary principle’ when devising environmental policies?
  4. To what extent is game theory relevant in understanding the difficulties and opportunities of developing internationally agreed policies on carbon reduction?
  5. If the objective is to tackle global warming, is it better to seek international agreement on limiting the extent of global warming or international agreement on carbon reduction? Explain.
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Lockdown – again.  Is it worth it?

Mid-December saw a rapid rise in coronavirus cases in London and the South East and parts of eastern and central southern England. This was due to a new strain of Covid, which is more infectious. In response, the UK government introduced a new tier 4 level of restrictions for these areas from 20 December. These amount to a complete lockdown. The devolved administrations also announced lockdowns. In addition, the Christmas relaxation of rules was tightened across the UK. Households (up to three) were only allowed to get together on Christmas day and not the days either side (or one day between 23 and 27 December in the case of Northern Ireland). Tier 4 residents were not allowed to visit other households even on Christmas day.

The lockdowns aimed to slow the spread of the virus and reduce deaths. But this comes at a considerable short-term economic cost, especially to the retail and leisure sectors, which are required to close while the lockdowns remain in force. In taking the decision to introduce these tougher measures, the four administrations had to weigh up the benefits of reduced deaths and illness and pressure on the NHS against the short-term economic damage. As far a long-term economic damage is concerned, this might be even greater if lockdowns were not imposed and the virus spread more rapidly.

In a blog back in September, we examined the use of cost–benefit analysis (CBA) to aid decision-making about such decisions. The following is an updated version of that blog.

The use of cost–benefit analysis

It is commonplace to use cost–benefit analysis (CBA) in assessing public policies, such as whether to build a new hospital, road or rail line. Various attempts in the past few months have been made to use CBA in assessing policies to reduce the spread of the coronavirus. These have involved weighing up the costs and benefits of national or local lockdowns or other containment measures. But, as with other areas where CBA is used, there are serious problems of measuring costs and benefits and assessing risks. This is particularly problematic where human life is involved and where a value has to be attached to a life saved or lost.

The first step in a CBA is to identify the benefits and costs of the policy.

Identifying the benefits and costs of the lockdown

The benefits of the lockdown include lives saved and a reduction in suffering, not only for those who otherwise would have caught the virus but also for their family and friends. It also includes lives saved from other diseases whose treatment would have been put (even more) on hold if the pandemic had been allowed to rage and more people were hospitalised with the virus. In material terms, there is the benefit of saving in healthcare and medicines and the saving of labour resources. Then there are the environmental gains from less traffic and polluting activities.

On the cost side, there is the decline in output from businesses being shut and people being furloughed or not being able to find work. There is also a cost if schools have to close and children’s education is thereby compromised. Then there is the personal cost to people of being confined to home, a cost that could be great for those in cramped living conditions or in abusive relationships. Over the longer term, there is a cost from people becoming deskilled and firms not investing – so-called scarring effects. Here there are the direct effects and the multiplier effects on the rest of the economy.

Estimating uncertain outcomes

It is difficult enough identifying all the costs and benefits, but many occur in the future and here there is the problem of estimating the probability of their occurrence and their likely magnitude. Just how many lives will be saved from the policy and just how much will the economy be affected? Epidemiological and economic models can help, but there is a huge degree of uncertainty over predictions made about the spread of the disease, especially with a new strain of the virus, and the economic effects, especially over the longer term.

One estimate of the number of lives saved was made by Miles et al. in the NIESR paper linked below. A figure of 440 000 was calculated by subtracting the 60 000 actual excess deaths over the period of the first lockdown (March to June 2020) from a figure of 500 000 lives lost which, according to predictions, would have been the consequence of no lockdown. However, the authors acknowledge that this is likely to be a considerable overestimate because:

It does not account for changes in behaviour that would have occurred without the government lockdown; it does not count future higher deaths from side effects of the lockdown (extra cancer deaths for example); and it does not allow for the fact that some of those ‘saved’ deaths may just have been postponed because when restrictions are eased, and in the absence of a vaccine or of widespread immunity, deaths may pick up again.

Some help in estimating likely outcomes from locking down or not locking down the economy can be gained by comparing countries which have taken different approaches. The final article in the first list below compares the approaches in the UK and Sweden. Sweden had much lighter control measures than the UK and did not impose a lockdown. Using comparisons of the two approaches, the authors estimate that some 20 000 lives were saved by the lockdown – considerably less than the 440 000 estimate.

Estimating the value of a human life

To assess whether the saving of 20 000 lives was ‘worth it’, a value would have to be put on a life saved. Although putting a monetary value on a human life may be repugnant to many people, such calculations are made whenever a project is assessed which either saves or costs lives. As we say in the 10th edition of Economics (page 381):

Some people argue ‘You can’t put a price on a human life: life is priceless.’ But just what are they saying here? Are they saying that life has an infinite value? If so, the project must be carried out whatever the costs, and even if other benefits are zero! Clearly, when evaluating lives saved from the project, a value less than infinity must be given.
 
Other people might argue that human life cannot be treated like other costs and benefits and put into mathematical calculations. But what are these people saying? That the question of lives saved should be excluded from the cost–benefit study? If so, the implication is that life has a zero value! Again this is clearly not the case.

In practice, there are two approaches used to measure the value of a human life.

The first uses the value of a statistical life (VSL). This is based on the amount extra the average person would need to be paid to work in a job where there is a known probability of losing their life. So if people on average needed to be paid an extra £10 000 to work in a job with a 1% chance of losing their life, they would be valuing a life at £1 000 000 (£10 000/0.01). To avoid the obvious problem of young people’s lives being valued the same as old people’s ones, even though a 20 year-old on average will live much longer than a 70 year-old, a more common measure is the value of a statistical life year (VSLY).

A problem with VSL or VSLY measures is that they only take into account the quantity of years of life lost or saved, not the quality.

A second measure rectifies this problem. This is the ‘quality of life adjusted year (QALY)’. This involves giving a value to a year of full health and then reducing it according to how much people’s quality of life is reduced by illness, injury or poverty. The problem with this measure is the moral one that a sick or disabled person’s life is being valued less than the life of a healthy person. But it is usual to make such adjustments when considering medical intervention with limited resources.

One adjustment often made to QALYs or VSLYs is to discount years, so that one year gained would be given the full value and each subsequent year would be discounted by a certain percentage from the previous year – say, 3%. This would give a lower weighting to years in the distant future than years in the near future and hence would reduce the gap in predicted gains from a policy between young and old people.

Cost–effectiveness analysis (CEA)

Even using QALYs, there is still the problem of measuring life and health/sickness. A simpler approach is to use cost–effectiveness analysis (CEA). This takes a social goal, such as reducing the virus production rate (R) below 1 (e.g. to 0.9), and then finding the least-cost way of achieving this. As Mark Carney says in his third Reith Lecture:

As advocated by the economists Nick Stern and Tim Besley, the ideal is to define our core purpose first and then determine the most cost-effective interventions to achieve this goal. Such cost–effectiveness analysis explicitly seeks to achieve society’s values.

Cost–effectiveness analysis can take account of various externalities – as many of the costs will be – by giving them a value. For example, the costs of a lockdown to people in the hospitality sector or to the education of the young could be estimated and included in the costs. The analysis can also take into account issues of fairness by identifying the effects on inequality when certain groups suffer particularly badly from Covid or lockdown policies – groups such as the poor, the elderly and children. Achieving the goal of a specific R for the least cost, including external costs and attaching higher weights on the effects on certain groups then becomes the goal. As Carney says:

R brings public health and economics together. Relaxations of restrictions increase R, with economic, health and social consequences. A strategic approach to Covid is the best combination of policies to achieve the desired level of infection control at minimum economic cost with due respect for inequality, mental health and other social consequences, and calculating those costs then provides guidance when considering different containment strategies. That means paying attention to the impact on measures of fairness, the social returns to education, intergenerational equity and economic dynamism.

Conclusion

Given the uncertainties surrounding the measurement of the number of lives saved and the difficulties of assigning a value to them, and given the difficulties of estimating the economic and social effects of lockdowns, it is not surprising that the conclusions of a cost–benefit analysis, or even a cost–effectiveness analysis of a lockdown will be contentious. But, at least such analysis can help to inform discussion and drive future policy decisions. And a cost–effectiveness analysis can be a practical way of helping politicians reach difficult decisions about life and death and the economy.

Articles (original blog)

Articles (additional)

Questions

  1. What are the arguments for and against putting a monetary value on a life saved?
  2. Are QALYs the best way of measuring lives saved from a policy such as a lockdown?
  3. Compare the relative merits of cost–benefit analysis and cost–effectiveness analysis.
  4. If the outcomes of a lockdown are highly uncertain, does this strengthen or weaken the case for a lockdown? Explain.
  5. What specific problems are there in estimating the number of lives saved by a lockdown?
  6. How might the age distribution of people dying from Covid-19 affect the calculation of the cost of these deaths (or the benefits or avoiding them)?
  7. How might you estimate the costs to people who suffer long-term health effects from having had Covid-19?
  8. What are the arguments for and against using discounting in estimating future QALYs?
  9. The Department of Transport currently uses a figure of £1 958 303 (in 2018 prices) for the value of a life saved from a road safety project. Find out how this is figure derived and comment on it. See Box 12.5 in Economics 10th edition and Accident and casualty costs, Tables RAS60001 and RA60003, (Department of Transport, 2019).
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How values affect outcomes

Each year the BBC hosts the Reith Lectures – a series of talks given by an eminent person in their field. This year’s lecturer is Mark Carney, former Governor of the Bank of England. His series of four weekly lectures began on 2 December 2020. Their topic is ‘How we get what we value’. As the BBC site states, the lectures:

chart how we have come to esteem financial value over human value and how we have gone from market economies to market societies. He argues that this has contributed to a trio of crises: of credit, Covid and climate. And the former Bank of England governor will outline how we can turn this around.

In lectures 2, 3 and 4, he looks at three crises and how they have shaped and are shaping what we value. The crises are the financial crisis of 2007–9, the coronavirus pandemic and the climate crisis. They have challenged how we value money, health and the environment respectively and, more broadly, have prompted people to question what is valuable for individuals and society, both today and into the future.

The questions posed by Carney are how can we establish what is valuable to individuals and society, how well are such values met by economies and how can mechanisms be improved to ensure that we make the best use of resources in meeting those values.

Value and the market

In the first lecture he probes the concept of value. He explores how economists and philosophers have tried to value the goods, services and human interactions that we desire.

First there is ‘objective value’ propounded by classical economists, such as Adam smith, David Ricardo and Karl Marx. Here the value of goods and services depends on the amount of resources used to make them and fundamentally on the amount of labour. In other words, value is a supply-side concept.

This he contrasts with ‘subjective value’. Here the value of goods and services depends on how well they satisfy wants – how much utility they give the consumer. For these neoclassical economists, value is in the eye of the beholder; it is a demand-side concept.

The two are reconciled in the market, with market prices reflecting the balance of demand and supply. Market prices provided a solution to the famous diamonds/water paradox (see Box 4.2 in Economics (10th edition) or Case Study 4.3 in Essentials of Economics (8th edition) – the paradox of ‘why water, which is essential for life, is virtually free, but diamonds, which have limited utility beyond their beauty, are so expensive.’ The answer is to do with scarcity and marginal utility. Because diamonds are rare, the marginal utility is high, even though the total utility is low. And because water is abundant, even though its total utility is high, for most people its marginal utility is low. In other words, the value at the margin depends on the balance of demand and supply. Diamonds are much scarcer than water.

But is the market balance the right balance? Are the values implied by the market the same as those of society? ‘Why do financial markets rate Amazon as one of the world’s most valuable companies, but the value of the vast region of the Amazon appears on no ledger until it’s stripped of its foliage and converted into farmland?’ – another paradox highlighted by Carney.

It has long been recognised that markets fail in a number of ways. They are not perfect, with large firms able to make supernormal profits by charging more and producing less, and consumers often being ill-informed and behaving impulsively or being swayed by clever marketing. And many valuable things that we experience, such as human interaction and the beauty of nature, are not bought and sold and thus do not appear in measures of GDP – one of the main ways of valuing a country.

What is more, many of things that are produced in the market have side-effects which are not reflected in prices. These externalities, whether good or bad, can be substantial: for example, the global warming caused by CO2 emissions from industry, transport and electricity production from fossil fuels.

And markets reflect people’s biases towards the present and hence lead to too little investment for the future, whether in healthcare, the environment or physical and social infrastructure. Markets reflect the scant regard many give to the damage we might be doing to the lives of future generations.

What is particularly corrosive, according to Carney, is the

drift from moral to market sentiments. …Increasingly, the value of something, some act or someone is equated with its monetary value, a monetary value that is determined by the market. The logic of buying and selling no longer applies only to material goods, but increasingly it governs the whole of life from the allocation of healthcare, education, public safety and environmental protection. …Market value is taken to represent intrinsic value, and if a good or activity is not in the market, it is not valued.

The drift from moral to market sentiments accelerated in the Thatcher/Regan era, when governments were portrayed as inefficient allocators, which stifled competition, innovation and the movement of capital. Deregulation and privatisation were the order of the day. This, according to Carney, ‘unleashed a new dynamism’ and ‘with the fall of communism at the end of the 1980s, the spread of the market grew unchecked.’

But this drift failed to recognise market failures. It has taken three crises, the financial crisis, Covid and the climate crisis to bring these failures to the top of the public agenda. They are examined in the other three lectures.

The Reith Lectures

Questions

  1. Distinguish between objective and subjective value.
  2. If your income rises, will you necessarily be happier? Explain.
  3. How is the concept of diminishing marginal utility of income relevant to explaining why ‘A Christmas bonus of £1000 means less to Mark Zuckerberg then £500 does to someone on a minimum wage.’
  4. Does the use of social cost–benefit analysis enable us to use adjusted prices as a measure of value?
  5. Listen to lectures 2, 3 and 4 and provide a 500-word summary of each.
  6. Assess the arguments Mark Carney uses in one of these three lectures.
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All change for the railways

The UK rail industry was privatised by the Conservative government in the mid-1990s. As Case Study 14.8 on the Economics 10th edition website states:

The management of rail infrastructure, such as track, signalling and stations, was to be separated from the responsibility for running trains. There would be 25 passenger train operating companies (TOCs), each having a franchise lasting between seven and fifteen years. These companies would have few assets, being forced to rent track and lease stations from the infrastructure owner (Railtrack), and to lease trains and rolling stock from three new rolling-stock companies. …In practice, the 25 franchises were operated by just 11 companies (with one, National Express, having nine of the franchises).

In 1996, at the start of the franchise era, the train operating companies were largely private-sector companies such as National Express, Stagecoach, Virgin Rail and Prism Rail. By 2020, most of the franchises were operated by a foreign state-owned business or a joint venture with a foreign state-owned firm.

As a result of poor performance (see above case study), Railtrack was effectively renationalised in 2002 as Network Rail – a not-for-profit company, wholly dependent upon the UK Treasury for any shortfall in its funds.

TOCs had mixed success. Some performed so poorly that their franchise contracts had to be temporarily taken over by a state-owned operator. For example, in June 2003 the Strategic Rail Authority withdrew the operating licence of the French company Connex South Eastern. The franchise was temporarily taken over by the publicly-owned South Eastern Trains from November 2003 until March 2006 before being returned to a private operator.

Perhaps the most troubled franchise has been the East Coast Main Line between London and Scotland. It was renationalised in 2009, reprivatised in 2015 and renationalised in 2018.

The effect of the coronavirus pandemic

The spread of the coronavirus and the accompanying lockdowns and social distancing saw a plummeting of rail travel. Passenger numbers fell to just 10% of pre-pandemic levels. In March 2020, the UK Government introduced Emergency Measures Agreements (EMAs), which temporarily replaced rail franchise agreements. TOCs were paid a 2% fee (based on pre-Covid costs) to run trains and losses were borne by the government.

When the EMAs ran out on the 20 September, they were replaced by Emergency Recovery Measures Agreements (ERMAs), set to last until no later than April 2022. Under these measures, the fees paid to TOCs were reduced to a maximum of 1.5%. These consist partly of a fixed fee (again based on pre-Covid costs) and partly on a performance payment, depending on punctuality, passenger satisfaction and financial performance. As with the EMAs, the new arrangements involve virtually no risk for the TOCs (except for the size of the performance-related fee). Costs and revenue will be passed to the Department for Transport, which will bear any losses.

TOCs were required to run a virtually full service to allow reduced passenger numbers to observe social distancing. Despite journeys still being only 30% of pre-pandemic levels, social distancing on trains meant that many trains were sold out.

The ERMAs also contain provisions for the replacement of franchises when they come to an end. The precise nature of these will be spelt out in a White Paper, which will respond to the recommendations of the Williams Review of the railways. This review was set up in 2018 in the aftermath of difficulties with various franchises and a chaotic nationwide timetable change. The review’s findings were originally scheduled to be published in Autumn 2019, but were then put back because of the general election and the disruptions caused by the pandemic. The government hopes that it will be published before the end of 2020.

It is expected that the review will recommend replacing the franchise system with something similar to the currents ERMAs. TOCs awarded a contract will be paid a performance-related fee and revenues will go to the government, which will bear the costs. While this is not quite renationalisation, it is not the previous franchise system where TOCs bore the risks. It is in effect a contract system where private companies are paid to deliver a public service.

The CrossCountry franchise

The first test of this new approach to contracting with TOCs came this month. Arriva’s franchise for running CrossCountry trains ran out and was replaced by a three-year contract to run the services, which span much of the length of Great Britain from Aberdeen to Penzance via Edinburgh, Glasgow, Newcastle, Sheffield, Birmingham, Bristol and Plymouth; from Bournemouth to Manchester via Reading, Oxford, Wolverhampton and Stoke; from Cardiff to Nottingham via Gloucester, Birmingham and Derby; and from Birmingham to Stanstead Airport via Leicester and Cambridge.

The contract will last three years. The Department for Transport will gain the revenues and cover the costs and pay Arriva (owned by Deutsche Bahn) a management fee that is ‘performance related’ – as yet unspecified. This, like the EMAs and then the ERMAs, will remove the risks from Arriva.

Nationalisation in Wales

The Welsh government has announced that Transport for Wales will be taken over by a publicly owned company in February 2021. TfW operates many of the routes in Wales and the borders and most of the branch lines in Wales, including the valley commuter lines into Cardiff. It is currently owned by KeolisAmey (a joint company owned 70% by the French company, Keolis (part of SNCF), and 30% by the UK company, Amey), which took over the franchise in 2018 from Arriva. The Welsh government considered that KeolisAmey would collapse if it did not provide support. Ministers decided that nationalisation would give it greater control than simply subsidising KeolisAmey.

James Price, chief executive of the Welsh Government, stated that this allows it:

to reduce the profit we pay to the private sector massively over time, and make sure that when the revenue comes back, it comes back in to the taxpayer.

Under emergency measures, KeolisAmey has already been supported by the Welsh government to the tune of £105 million (£40 million in March and £65 million in June) to continue operating the franchise. Passenger numbers fell by 95% as the pandemic hit.

Is nationalisation a better way forward, or should private train operating companies continue with the government taking on the risks, or should the franchise system be amended with greater support from the government but with the TOCs still bearing risk? The articles below consider these issues.

Articles

Questions

  1. Explain how the franchising system worked (prior to March 2020).
  2. To what extent could each franchise be described as a ‘contestable monopoly’?
  3. What incentives were built into the franchising system to deliver improvements in service for passengers?
  4. What were the weaknesses of the franchising system?
  5. In the context of post-pandemic rail services, compare the relative merits of nationalisation with those of awarding contracts where the government receives the revenues and bears the costs and pays train operating companies a fee for operating the services where the size of the fee is performance related.
  6. What are the arguments for subsidising rail transport? What should determine the size of the subsidy?
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Assessing policies to tackle coronavirus: the use of cost–benefit analysis

It is commonplace to use cost–benefit analysis (CBA) in assessing public policies, such as whether to build a new hospital, road or rail line. Various attempts in the past few months have been made to use CBA in assessing policies to reduce the spread of the coronavirus. These have involved weighing up the costs and benefits of national or local lockdowns or other containment measures. But, as with other areas where CBA is used, there are serious problems of measuring costs and benefits and assessing risks. This is particularly problematic where human life is involved and where a value has to be attached to a life saved or lost.

Take the case of whether the government should have imposed a lockdown: an important question if there were to be a second wave and the government was considering introducing a second lockdown. The first step in a CBA is to identify the benefits and costs of the policy.

Identifying the benefits and costs of the lockdown

The benefits of the lockdown include lives saved and a reduction in suffering, not only for those who otherwise would have caught the virus but also for their family and friends. It also includes lives saved from other diseases whose treatment would have been put (even more) on hold if the pandemic had been allowed to rage and more people were hospitalised with the virus. In material terms, there is the benefit of saving in healthcare and medicines and the saving of labour resources. Then there are the environmental gains from less traffic and polluting activities.

On the cost side, there is the decline in output from businesses being shut and people being furloughed or not being able to find work. There is also a cost from schools being closed and children’s education being compromised. Then there is the personal cost to people of being confined to home, a cost that could be great for those in cramped living conditions or in abusive relationships. Over the longer term, there is a cost from people becoming deskilled and firms not investing – so-called scarring effects. Here there are the direct effects and the multiplier effects on the rest of the economy.

Estimating uncertain outcomes

It is difficult enough identifying all the costs and benefits, but many occur in the future and here there is the problem of estimating the probability of their occurrence and their likely magnitude. Just how many lives will be saved from the policy and just how much will the economy be affected? Epidemiological and economic models can help, but there is a huge degree of uncertainty over predictions made about the spread of the disease and the economic effects, especially over the longer term.

One estimate of the number of lives saved was made by Miles et al. in the NIESR paper linked below. A figure of 440 000 was calculated by subtracting the 60 000 actual excess deaths over the period of the lockdown from a figure of 500 000 lives lost which, according to predictions, would have been the consequence of no lockdown. However, the authors acknowledge that this is likely to be a considerable overestimate because:

It does not account for changes in behaviour that would have occurred without the government lockdown; it does not count future higher deaths from side effects of the lockdown (extra cancer deaths for example); and it does not allow for the fact that some of those ‘saved’ deaths may just have been postponed because when restrictions are eased, and in the absence of a vaccine or of widespread immunity, deaths may pick up again.

Some help in estimating likely outcomes from locking down or not locking down the economy can be gained by comparing countries which have taken different approaches. The final article below compares the approaches in the UK and Sweden. Sweden had much lighter control measures than the UK and did not impose a lockdown. Using comparisons of the two approaches, the authors estimate that some 20 000 lives were saved by the lockdown – considerably less than the 440 000 estimate.

Estimating the value of a human life

To assess whether the saving of 20 000 lives was ‘worth it’, a value would have to be put on a life saved. Although putting a monetary value on a human life may be repugnant to many people, such calculations are made whenever a project is assessed which either saves or costs lives. As we say in the 10th edition of Economics (page 381):

Some people argue ‘You can’t put a price on a human life: life is priceless.’ But just what are they saying here? Are they saying that life has an infinite value? If so, the project must be carried out whatever the costs, and even if other benefits are zero! Clearly, when evaluating lives saved from the project, a value less than infinity must be given.
 
Other people might argue that human life cannot be treated like other costs and benefits and put into mathematical calculations. But what are these people saying? That the question of lives saved should be excluded from the cost–benefit study? If so, the implication is that life has a zero value! Again this is clearly not the case.

In practice there are two approaches used to measuring the value of a human life.

The first uses the value of a statistical life (VSL). This is based on the amount extra the average person would need to be paid to work in a job where there is a known probability of losing their life. So if people on average needed to be paid an extra £10 000 to work in a job with a 1% chance of losing their life, they would be valuing a life at £1 000 000 (£10 000/0.01). To avoid the obvious problem of young people’s lives being valued the same as old people’s ones, even though a 20 year-old on average will live much longer than a 70 year-old, a more common measure is the value of a statistical life year (VSLY).

A problem with VSL or VSLY measures is that they only take into account the quantity of years of life lost or saved, not the quality.

A second measure rectifies this problem. This is the ‘quality of life adjusted year (QALY)’. This involves giving a value to a year of full health and then reducing it according to how much people’s quality of life is reduced by illness, injury or poverty. The problem with this measure is the moral one that a sick or disabled person’s life is being valued less than the life of a healthy person. But it is usual to make such adjustments when considering medical intervention with limited resources.

One adjustment often made to QALYs or VSLYs is to discount years, so that one year gained would be given the full value and each subsequent year would be discounted by a certain percentage from the previous year – say, 3%. This would give a lower weighting to years in the distant future than years in the near future and hence would reduce the gap in predicted gains from a policy between young and old people.

Conclusion

Given the uncertainties surrounding the measurement of the number of lives saved and the difficulties of assigning a value to them, it is not surprising that the conclusions of a cost–benefit analysis of a lockdown will be contentious. And we have yet to see what the long-term effects on the economy will be. But, at least a cost–benefit analysis of the lockdown can help to inform discussion and help to drive future policy decisions about tackling a second wave, whether internationally, nationally or locally.

Articles

Questions

  1. What are the arguments for and against putting a monetary value on a life saved?
  2. Are QALYs the best way of measuring lives saved from a policy such as a lockdown?
  3. If the outcomes of a lockdown are highly uncertain, does this strengthen or weaken the case for a lockdown? Explain.
  4. What specific problems are there in estimating the number of lives saved by a lockdown?
  5. How might the age distribution of people dying from Covid-19 affect the calculation of the cost of these deaths (or the benefits or avoiding them)?
  6. How might you estimate the costs to people who suffer long-term health effects from having had Covid-19?
  7. What are the arguments for and against using discounting in estimating future QALYs?
  8. The Department of Transport currently uses a figure of £1 958 303 (in 2018 prices) for the value of a life saved from a road safety project. Find out how this is figure derived and comment on it. See Box 12.5 in Economics 10th edition and Accident and casualty costs, Tables RAS60001 and RA60003, (Department of Transport, 2019).