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.
What are the arguments for and against putting a monetary value on a life saved?
Are QALYs the best way of measuring lives saved from a policy such as a lockdown?
Compare the relative merits of cost–benefit analysis and cost–effectiveness analysis.
If the outcomes of a lockdown are highly uncertain, does this strengthen or weaken the case for a lockdown? Explain.
What specific problems are there in estimating the number of lives saved by a lockdown?
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)?
How might you estimate the costs to people who suffer long-term health effects from having had Covid-19?
What are the arguments for and against using discounting in estimating future QALYs?
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).
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.
What are the arguments for and against putting a monetary value on a life saved?
Are QALYs the best way of measuring lives saved from a policy such as a lockdown?
If the outcomes of a lockdown are highly uncertain, does this strengthen or weaken the case for a lockdown? Explain.
What specific problems are there in estimating the number of lives saved by a lockdown?
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)?
How might you estimate the costs to people who suffer long-term health effects from having had Covid-19?
What are the arguments for and against using discounting in estimating future QALYs?
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).
The linked articles below look at the state of the railways in Britain and whether renationalisation would be the best way of securing more investment, better services and lower fares.
Rail travel and rail freight involve significant positive externalities, as people and goods transported by rail reduce road congestion, accidents and traffic pollution. In a purely private rail system with no government support, these externalities would not be taken into account and there would be a socially sub-optimal use of the railways. If all government support for the railways were withdrawn, this would almost certainly result in rail closures, as was the case in the 1960s, following the publication of the Beeching Report in 1963.
Also the returns on rail investment are generally long term. Such investment may not, therefore, be attractive to private rail operators seeking shorter-term returns.
These are strong arguments for government intervention to support the railways. But there is considerable disagreement over the best means of doing so.
One option is full nationalisation. This would include both the infrastructure (track, signalling, stations, bridges, tunnels and marshalling yards) and the trains (the trains themselves – both passenger and freight – and their operation).
At present, the infrastructure (except for most stations) is owned, operated, developed and maintained by Network Rail, which is a non-departmental public company (NDPB) or ‘Quango’ (Quasi-autonomous non-governmental organisation, such as NHS trusts, the Forestry Commission or the Office for Students. It has no shareholders and reinvests its profits in the rail infrastructure. Like other NDPBs, it has an arm’s-length relationship with the government. Network Rail is answerable to the government via the Department for Transport. This part of the system, therefore, is nationalised – if the term ‘nationalised organisations’ includes NDPBs and not just full public corporations such as the BBC, the Bank of England and Post Office Ltd.
Train operating companies, however, except in Northern Ireland, are privately owned under a franchise system, with each franchise covering specific routes. Each of the 17 passenger franchises is awarded under a competitive tendering system for a specific period of time, typically seven years, but with some for longer. Some companies operate more than one franchise.
Companies awarded a profitable franchise are required to pay the government for operating it. Companies awarded a loss-making franchise are given subsidies by the government to operate it. In awarding franchises, the government looks at the level of payments the bidders are offering or the subsidies they are requiring.
But this system has come in for increasing criticism, with rising real fares, overcrowding on many trains and poor service quality. The Labour Party is committed to taking franchises into public ownership as they come up for renewal. Indeed, there is considerable public support for nationalising the train operating companies.
The main issue is which system would best address the issues of externalities, efficiency, quality of service, fares and investment. Ultimately it depends on the will of the government. Under either system the government plays a major part in determining the level of financial support, operating criteria and the level of investment. For this reason, many argue that the system of ownership is less important than the level and type of support given by the government and how it requires the railways to be run.
What categories of market failure would exist in a purely private rail system with no government intervention?
What types of savings could be made by nationalising train operating companies?
The franchise system is one of contestable monopolies. In what ways are they contestable and what benefits does the system bring? Are there any costs from the contestable nature of the system?
Is it feasible to have franchises that allow more than one train operator to run on most routes, thereby providing some degree of continuing competition?
How are rail fares determined in Britain?
Would nationalising the train operating companies be costly to the taxpayer? Explain.
What determines the optimal length of a franchise under the current system?
What role does leasing play in investment in rolling stock?
What are the arguments for and against the government’s decision in November 2017 to allow the Virgin/Stagecoach partnership to pull out of the East Coast franchise three years early because it found the agreed payments to the government too onerous?
Could the current system be amended in any way to meet the criticisms that it does not adequately take into account the positive externalities of rail transport and the need for substantial investment, while also encouraging excessive risk taking by bidding companies at the tendering stage?
How much does the UK spend on welfare? This is a highly charged political question, with some arguing that benefit claimants are putting great demands on ‘hard-working tax payers’. According to information being sent by the government to all 24 million income tax payers in the UK, the figure of £168bn being spent on welfare is around 24.5% of public spending. But what is included in the total? Before you read on, try writing down the categories of government expenditure included under the heading ‘welfare’.
The heading does not include spending on certain parts of the ‘welfare state’, such as health and education. These are services, the production of which contributes to GDP. The category ‘welfare’ does not include expenditure on produced services, but rather transfer payments. The way the government is using the term, it does not include state pensions either, which account for 11.6% of public expenditure. So does the 24.5% largely consist of payments to the unemployed? The answer is no.
The category ‘welfare’ as used by the government includes the following elements. The percentages are of total managed expenditure (i.e. government spending).
•
Public service pensions, paid to retired public-sector employees, such as teachers, police officers, doctors and nurses
(2.6%)
•
Other support for the elderly, including pension credit, winter fuel allowance, bus passes, etc.
(1.5%)
•
Sickness and disability benefits, including long-term care for the elderly, sick and disabled
(6.6%)
•
Support for families and children, such as child benefit and child tax credits
(3.4%)
•
Social exclusion, including income support and housing benefit
(7.8%)
•
Unemployment benefits, including Job Seekers Allowance
(0.7%)
•
Other
(1.9%)
Lumping all these together under a single heading ‘welfare’ can be highly misleading, as many people have strongly held preconceptions about who gets welfare. In fact the term is used pejoratively by many who resent their taxes being given to those who do not work.
But, as you can see from the figures, only a small proportion goes to the unemployed, the majority of whom (around 65%) are unemployed for less than a year as they move between jobs (see). The bulk of benefits goes to children, the retired and the working poor.
Another preconception is that much of welfare spending goes to fraudulent claimants. But, as the article by Professor Hills states:
Just 0.7% of all benefits was over-paid as the result of fraud, less than the amount underpaid as a result of official error. For the main benefit for unemployed people, Jobseeker’s Allowance, estimated fraud was 2.9%, or an annual total of £150million.
It is also important to consider people’s life cycle. The same people receive benefits (via their parents or guardians) as children, pay taxes when they work and receive benefits when they retire or fall sick. Thus you might be a net contributor to public finances at one time and a net beneficiary at another. For example, the majority of pensioners were net contributors when they were younger and are now mainly net beneficiaries. Many unemployed people who rely on benefits now were net contributors when they had a job.
The message is that you should be careful when interpreting statistics, even if these statistics are factually accurate. How figures are grouped together and the labels put on them can give a totally misleading impression. And politicians are always keen to ‘spin’ statistics to their advantage – whether in government or opposition.
What benefits do you receive? How would you expect this to change over your lifetime?
What are the arguments for (a) reducing and (b) increasing welfare payments. In each case, under which categories of welfare would you decrease or increase the level of benefits?
Referring to Table 5.2 in the PESA data below (the table used for the government’s calculations), which of the categories would be classified as expenditure on goods and services and which as transfer payments?
Assess the arguments of the IFS for the reclassification of the categories of ‘welfare’ payments.
Referring to the pie chart above, also in the BBC video and articles and Table 5.2 in the PESA data, assess the arguments about the size of the UK’s contributions to the EU budget.
HS2 has been a controversial topic for some time now. Between the disruption it would cause to countless neighbourhoods and the protests that have emerged and the debate about the cost effectiveness of the project, it’s been in the news a fair amount. The transport network in the UK needs improving, not only for businesses located here, but also to encourage more investment into the country. HS2 is one of the solutions offered.
The latest estimate for the cost of HS2 is over £40 billion. However, many suggest that the benefits HS2 will bring do not cover the full costs. Furthermore, as noted above, other concerns include the disruption that it will bring to countless households who will be living along the proposed routes. Cost benefit analysis have been carried out to determine the viability of the project, but they are invariably difficult to do. As they involve determining all of the private and social costs and benefits and putting a monetary estimate onto them, there will inevitably be factors that are over-looked, under-estimated or over-estimated. The suggestions here are that the costs have been under-estimated and the benefits over-estimated.
In September, KPMG produced a report that estimated the overall benefit to the UK economy would be a boost to growth of 0.8%, which would benefit many businesses and communities. The British Chambers of Commerce said:
Business communities in dozens of cities and towns, from many parts of the UK, remain strongly supportive of HS2.
The railway network is also approaching full capacity and this is one of the reasons why HS2 has been proposed. A government source said:
We need to do something because our railways are nearly full, but the alternative to HS2 is a patch and mend job that would cause 14 years of gridlock, hellish journeys and rail replacement buses … The three main routes to the north would be crippled and the economy would be damaged.
However, this report has faced criticism, in particular because it ignored a variety of supply-side constraints and because they argue it would be more effective to simply update the existing network. However, a new government-commissioned report has suggested that this alternative to HS2 would involve 14 years of weekend route closures and much longer journey times. However, those in favour of updating existing routes have said that this new report commissioned by the government is ‘a complete fabrication’. Hilary Wharf of the HS2 Action Alliance commented:
This government-funded report is a complete fabrication. The main alternative to HS2 involves longer trains and reduced first-class capacity to provide more standard class seats…No work is required at Euston to deliver the necessary capacity increase. Work is only required at three locations on the WCML [West Coast Main Line], and this is comparable to the work being carried out on the route at present.
The debate regarding HS2 will continue for the time being and it is just another area that is fuelling the political playing field. Whatever is done, the rail network certainly requires investment, whether it is through HS2 or upgrades to the existing routes. The following reports and articles consider the latest developments and controversy regarding HS2.
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.
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.
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.
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.
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).
Lecture 3: From Covid Crisis to Renaissance (Transcript)
