Tag: risk

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The growth of autarky: is globalisation dead?

Over the decades, economies have become increasingly interdependent. This process of globalisation has involved a growth in international trade, the spread of technology, integrated financial markets and international migration.

When the global economy is growing, globalisation spreads the benefits around the world. However, when there are economic problems in one part of the world, this can spread like a contagion to other parts. This was clearly illustrated by the credit crunch of 2007–8. A crisis that started in the sub-prime market in the USA soon snowballed into a worldwide recession. More recently, the impact of Covid-19 on international supply chains has highlighted the dangers of relying on a highly globalised system of production and distribution. And more recently still, the war in Ukraine has shown the dangers of food and fuel dependency, with rapid rises in prices of basic essentials having a disproportionate effect on low-income countries and people on low incomes in richer countries.

Moves towards autarky

So is the answer for countries to become more self-sufficient – to adopt a policy of greater autarky? Several countries have moved in this direction. The USA under President Trump pursued a much more protectionist agenda than his predecessors. The UK, although seeking new post-Brexit trade relationships, has seen a reduction in trade as new barriers with the EU have reduced UK exports and imports as a percentage of GDP. According to the Office for Budget Responsibility’s November 2022 Economic and Fiscal Outlook, Brexit will result in the UK’s trade intensity being 15 per cent lower in the long run than if it had remained in the EU.

Many European countries are seeking to achieve greater energy self-sufficiency, both as a means of reducing reliance on Russian oil and gas, but also in pursuit of a green agenda, where a greater proportion of energy is generated from renewables. More generally, countries and companies are considering how to reduce the risks of relying on complex international supply chains.

Limits to the gains from trade

The gains from international trade stem partly from the law of comparative advantage, which states that greater levels of production can be achieved by countries specialising in and exporting those goods that can be produced at a lower opportunity cost and importing those in which they have a comparative disadvantage. Trade can also lead to the transfer of technology and a downward pressure on costs and prices through greater competition.

But trade can increase dependence on unreliable supply sources. For example, at present, some companies are seeking to reduce their reliance on Taiwanese parts, given worries about possible Chinese actions against Taiwan.

Also, governments have been increasingly willing to support domestic industries with various non-tariff barriers to imports, especially since the 2007–8 financial crisis. Such measures include subsidies, favouring domestic firms in awarding government contracts and using regulations to restrict imports. These protectionist measures are often justified in terms of achieving security of supply. The arguments apply particularly starkly in the case of food. In the light of large price increases in the wake of the Ukraine war, many countries are considering how to increase food self-sufficiency, despite it being more costly.

Also, trade in goods involves negative environmental externalities, as freight transport, whether by sea, air or land, involves emissions and can add to global warming. In 2021, shipping emitted over 830m tonnes of CO2, which represents some 3% of world total CO2 emissions. In 2019 (pre-pandemic), the figure was 800m tonnes. The closer geographically the trading partner, the lower these environmental costs are likely to be.

The problems with a globally interdependent world have led to world trade growing more slowly than world GDP in recent years after decades of trade growth considerably outstripping GDP growth. Trade (imports plus exports) as a percentage of GDP peaked at just over 60% in 2008. In 2019 and 2021 it was just over 56%. This is illustrated in the chart (click here for a PowerPoint). Although trade as a percentage of GDP rose slightly from 2020 to 2021 as economies recovered from the pandemic, it is expected to have fallen back again in 2022 and possibly further in 2023.

But despite this reduction in trade as a percentage of GDP, with de-globalisation likely to continue for some time, the world remains much more interdependent than in the more distant past (as the chart shows). Greater autarky may be seen as desirable by many countries as a response to the greater economic and political risks of the current world, but greater autarky is a long way from complete self-sufficiency. The world is likely to remain highly interdependent for the foreseeable future. Reports of the ‘death of globalisation’ are premature!

Podcasts

Articles

Report

Questions

  1. Explain the law of comparative advantage and demonstrate how trade between two countries can lead to both countries gaining.
  2. What are the main economic problems arising from globalisation?
  3. Is the answer to the problems of globalisation to move towards greater autarky?
  4. Would the expansion/further integration of trading blocs be a means of exploiting the benefits of globalisation while reducing the risks?
  5. Is the role of the US dollar likely to decline over time and, if so, why?
  6. Summarise Karl Polanyi’s arguments in The Great Transformation (see the Daniel W. Drezner article linked below). How well do they apply to the current world situation?
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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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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).
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PFI RIP?

One of the announcements in the recent UK Budget was the ending of the Private Finance Initiative (PFI), including its revised form, PF2. PFI was introduced by the Conservative government in 1992. Subsequently, it was to become central to the Labour government’s ‘Third-way’ approach of using the private sector to deliver public projects and services.

PFI involves a public–private partnership (PPP). The private sector builds and/or runs public projects, such as new schools, hospitals, roads, bridges, student accommodation, and so on. The public sector, in the form of government departments, NHS foundation trusts, local authorities, etc., then pays the private sector company a rent for the infrastructure or pays the company to provide services. The benefit of PFI is that it allows private-sector capital to be used for new projects and thus reduces the need for government to borrow; the disadvantage is that it commits the public-sector body to payments over the long-term to the company involved.

As the chart shows, PFI became an important means of funding public service provision during the 2000s. In the 10-year period up to financial year 2007/08, more than 50 new projects were being signed each year.

As the number of projects grew and with them the long-term financial commitments of the public sector, so criticisms mounted. These included:

  • Quality and cost. It was claimed that PFI projects were resulting in poorer quality of provision and that cost control was often poor, resulting in a higher burden for the taxpayer in the long term.
  • Credit availability. PFI projects are typically dependent on the private partner using debt finance to acquire the necessary funds. Therefore, credit conditions affect the ability of PFI to fund the delivery of public services. With the credit crunch of 2008/9, many firms operating PFI projects found it difficult to raise finance.
  • The financial health of the private partner. What happens if the private company runs into financial difficulties. In 2005, the engineering company Jarvis only just managed to avoid bankruptcy by securing refinancing on all 14 of its PFI deals.

PF2

Recognising these problems, in 2011 the government set up a review of PFI. The result was a revised form of PFI, known as ‘PF2’. PF2 projects involved tighter financial control, with the government acting as a minority co-investor; more robust tendering processes, with bidders required to develop a long-term financing solution, where bank debt does not form the majority of the financing of the project; the removal of cleaning, catering and other ‘soft services’.

Despite the government’s intention that PPPs remain an important plank of its funding of public services, the number of new PFI/PF2 projects has nonetheless declined sharply during the 2010s as the chart shows. Of the 715 PPP projects as of 31 March 2017, 631 had been signed before May 2010. Indeed, in 2016/17 only 1 new project was signed.

The collapse of Carillion

Concerns over PPPs remained despite the reforms under PF2. These were brought dramatically into focus with the collapse of Carillion plc (see the blog, Outsourcing, PFI and the demise of Carillion). Carillion was a British company focused on construction and facilities management (i.e. support services for organisations). It was a significant private-sector partner in PPP projects. By 2014 it had won 60 PPP projects in the UK and Canada, including hospitals, schools, university buildings, prisons, roads and railways.

However, Carillion had increasing burdens of debt, caused, in part, by various major acquisitions, including McAlpine in 2008. Events came to a head when, on 15 January 2018, an application was made to the High Court for a compulsory liquidation of the company.

A subsequent report for the House of Commons Public Administration and Constitutional Affairs Committee in light of the collapse of Carillion found that procurement procedures were fundamentally flawed. It found that contracts were awarded based on cost rather than quality. This meant that some contracts were not sustainable. Between 2016 and the collapse of Carillion the government had been forced to renegotiate more than £120m of contracts so that public services could continue.

The ending of PPPs?

On 18 January 2018, the National Audit Office published an assessment of PFI and PF2. The report stated that there were 716 PFI and PF2 projects at the time, either under construction or in operation, with a total capital value of £59.4 billion. In recent years, however, ‘the government’s use of the PFI and PF2 models had slowed significantly, reducing from, on average, 55 deals each year in the five years to 2007/8 to only one in 2016/17.’

At its conference in September 2018, the Labour shadow chancellor, John McDonnell, said that, if elected, a Labour government would not award any new PFI/PF2 contracts. He claimed that PFI/PF2 contracts were set to cost the taxpayer £200bn over the coming decade. Labour policy would be to review all existing PFI/PF2 contracts and bring the bulk of them fully back into the public sector.

Then in the Budget of 29 October 2018, the Chancellor announced that no further PFI/PF2 projects would be awarded, although existing ones would continue.

I have never signed off a PFI contract as chancellor, and I can confirm today that I never will. I can announce that the government will abolish the use of PFI and PF2 for future projects.

We will honour existing contracts. But the days of the public sector being a pushover, must end. We will establish a centre of excellence to actively manage these contracts in the taxpayers’ interest, starting in the health sector.

But does this mean that there will be no more public-private partnerships, of which PFI is just one example? The answer is no. As the Chancellor stated:

And in financing public infrastructure, I remain committed to the use of public-private partnership where it delivers value for the taxpayer and genuinely transfers risk to the private sector.

But just what form future PPPs will take is unclear. Clearly, the government will want to get value for money, but that depends on the mechanisms used to ensure efficient and high-quality projects. What is more, there is still the danger that the companies involved could end up with unsustainable levels of debt if economic circumstances change and it will still involve a burden on the taxpayer for the future.

Articles

Questions

  1. Find out how PF2 differs from PFI and assess the extent to which it overcame the problems identified with PFI.
  2. The government is not bringing back existing PFI contracts into the public sector, whereas the Labour Party would do so – at least with some of them. Assess the arguments for and against bringing PFI contracts ‘in-house’.
  3. Find out why Carillion collapsed. To what extent was this due to its taking on PFI contracts?
  4. What were the main findings of the National Audit Office’s assessment of PFI and PF2?
  5. The government still supports the use of public-private partnerships (PPPs). What form could these take other than as PFI/PF2 contracts? Would the problems associated with PFI/PF2 also apply to PPPs in general?
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Should they stay or should they go? A primer on cryptocurrencies

How much do you know about cryptocurrencies? Even if you don’t know much you are very likely to have heard about the most popular member of the family: Bitcoin. Bitcoin (BTC) has been around for some time now (see the blog Bubbling Bitcoin). It was first released in 2009 by its inventor (the mysterious Satoshi Nakamoto, whose real identity still remains unknown), and since then it has gradually increased in popularity.

According to the Bitcoin Market Journal (a specialised blog, commenting on trends in digital currencies – primarily Bitcoin), there are currently about 29 million digital wallets holding at least 0.001 BTC, although some individual users may own multiple wallets.

Although BTC is the most popular digital currency (and the first one to become widely recognisable), it is certainly not the only one. There are currently more than 400 recognisable cryptocurrencies traded in special digital exchanges (twice this number if you count smaller, less successful ones) with a total capitalisation of $700 billion at its peak (January 3, 2018) – although since then the market has lost a significant part of this value (but it’s still worth 100s of billion of US dollars).

If you have heard about Bitcoin before, chances are you first searched for it sometime between December 2017 and January 2018; that is when the value of Bitcoin soared to $20 000 a piece. A search on Google Trends (a Google utility that shows how many people have searched over a period of time for a certain term – in this case “Bitcoin”) shows this very clearly.

So what do people do with Bitcoin and other cryptocurrencies? The truth is that the majority of users use them for speculative purposes: they buy and sell them, in the hope of making a profit. Due to its extreme volatility (it is very common for the price of the larger cryptocurrencies to fluctuate by 10–20% daily) and the unregulated nature of the cryptocurrency market, it is hardly surprising that most users treat them as very high-risk commodity. This is also why digital currencies tend to attract attention (and new users) when their price soars.

However, cryptocurrencies are not only used for speculation. They can also be used to facilitate transactions. Indeed, according to Wikipedia, there are currently more than 100 000 merchants accepting BTC as a form of payment (online or offline with wallet readers). Financial technology (‘Fintech’) is catching up with this market and some new companies try to compete with the traditional payment networks (Mastercard, Visa and others) by launching plastic cards linked with crypto-wallets (primarily Bitcoin).

Santander bank has expressed an interest in exploring this market further. It is certain that if the market for cryptocurrencies keeps growing at this pace, there will be a lot more challenger fintech firms launching new products that will make it easier to use digital currencies in everyday life.

Cryptocurrencies, therefore, are likely to have a significant impact on the way we pay for our transactions. They can be used to lower transaction costs (e.g. by simplifying the process of sending money abroad), speed up the processing of payments, facilitate microfinancing and transactions in some of the poorest places on earth – where the closest bank may be 50 miles away or further from where people live).

But there is a dark side to these products. They have been linked to tax-evasion for instance, as many people who trade digital currencies fail to declare capital gains to national tax authorities. They can be used to overcome capital controls and other restrictions imposed by national governments (the case of Greece comes to mind as a recent example).

They have also been blamed for facilitating illegal trading activities, such as in drugs and weapons, due to the anonymity that some of these coins are thought to offer to their users – although quite often they are much easier to trace than their users believe.

Cryptocurrencies do have the potential to change the way we live. They also have the potential to become the biggest Ponzi scheme in the history of mankind.

Over the next few months, I will write a number of blogs to explore the literature on the economics of cryptocurrencies, and discuss some of the major challenges that needs to be overcome if this technology is to become mainstream.

Articles and information

Questions

  1. How much do you know about Bitcoin and other cryptocurrencies? When did you first find out about them and what triggered your interest?
  2. Would you be willing to accept payment in BTC? Why yes? Why no?
  3. Identify five ways in which the use of cryptocurrencies can benefit or damage the global economy.