Category: Essentials of Economics: 8e Ch 02, 7e Ch 02

The latest UK house price index reveals that annual house price growth in the UK slowed to just 1.2 per cent in May. This is the lowest rate of growth since January 2013. This is being driven, in part, by the London market where annual house price inflation rates have now been negative for 15 consecutive months. In May the annual rate of house price inflation in London fell to -4.4 per cent, it lowest since August 2009 as the financial crisis was unfolding. However, closer inspection of the figures show that while many other parts of the country continue to experience positive rates of annual house price inflation, once general inflation is accounted for, there is widespread evidence of widespread real house price deflation.

The average UK house price in May 2019 was £229,000. As Chart 1 shows, this masks considerable differences across the UK. In England the average price was £246,000 (an annual increase of 1.0 per cent), in Scotland it was £153,000 (an increase of 2.8 per cent), in Wales £159,000 (an increase of 3.0 per cent) and in Northern Ireland it was £137,000 (an increase of 2.1 per cent). (Click here to download a PowerPoint copy of the chart.)

The London market distorts considerably the English house price figures. In London the average house price in May 2019 was £457,000 (an annual decrease of 4.4 per cent). House prices were lowest in the North East region of England at £128,000. The North East was the only other English region alongside London to witness a negative rate of annual house price inflation, with house prices falling in the year to May 2019 by 0.7 per cent.

Chart 2 allows us to see more readily the rates of house price growth. It plots the annual rates of house price inflation across London, the UK and its nations. What is readily apparent is the volatility of house price growth. This is evidence of frequent imbalances between the flows of property on to the market to sell (instructions to sell) and the number of people looking to buy (instructions to buy). An increase in instructions to buy relative to those to sell puts upwards pressure on prices whereas an increase in the relative number of instructions to sell puts downward pressure on prices. (Click here to download a PowerPoint copy of the chart.)

Despite the volatility in house prices, the longer-term trend in house prices is positive. The average annual rate of growth in house prices between January 1970 and May 2019 in the UK is 9.1 per cent. For England the figure is 9.4 per cent, for Wales 8.8 per cent, for Scotland 8.5 per cent and for Northern Ireland 8.3 per cent. In London the average rate of growth is 10.4 per cent per annum.

As Chart 3 illustrates, the longer-term growth in actual house prices cannot be fully explained by the growth in consumer prices. It shows house price values as if consumer prices, as measured by the Retail Prices Index (RPI), were fixed at their January 1987 levels. We see real increases in house prices or, expressed differently, in house prices relative to consumer prices. In real terms, UK house prices were 3.6 times higher in May 2019 compared to January 1970. For England the figure is 4.1 times, for Wales 3.1 times, for Scotland 2.9 times and for Northern Ireland 2.1 times. In London inflation-adjusted house prices were 5.7 times higher. (Click here to download a PowerPoint copy of the chart.)

The volatility in house prices continues to be evident when adjusted for changes in consumer prices. The UK’s annual rate of real house price inflation was as high as 40 per in January 1973, yet, on the other hand, in June 1975 inflation-adjusted house prices were 16 per cent lower than a year earlier. Over the period from January 1970 to May 2019, the average annual rate of real house price inflation was 3.2 per cent. Hence house prices have, on average, grown at an annual rate of consumer price inflation plus 3.2 per cent.

Chart 4 shows annual rates of real house price inflation since 2008 and, hence, from around the time the financial crisis began to unfold. The period is characterised by acute volatility and with real house prices across the UK falling at an annual rate of 16 per cent in 2009 and by as much 29 per cent in Northern Ireland. (Click here to download a PowerPoint copy of the chart.)

The UK saw a rebound in nominal and real house price growth in the period from 2013, driven by a strong surge in prices in London and the South East, and supported by government initiatives such as Help to Buy designed to help people afford to buy property. But house price growth then began to ease from early/mid 2016. Some of the easing may be partly due to any excessive fizz ebbing from the market, especially in London, and the impact on the demand for buy-to-let investments resulting from reductions in tax relief on interest payments on buy-to-let mortgages.

However, the housing market is notoriously sensitive to uncertainty, which is not surprising when you think of the size of the investment people are making when they enter the market. The uncertainty surrounding Brexit and the UK’s future trading relationships will have been a drag on demand and hence on house prices.

Chart 4 shows that by May 2019 all the UK nations were experiencing negative rates of real house price inflation, despite still experiencing positive rates of nominal house price inflation. In Wales the real annual house price inflation rate was -0.1 per cent, in Scotland -0.2 per cent, in Northern Ireland -0.9 per cent and in England -2.0 per cent. Meanwhile in London, where annual house price deflation has been evident for 15 consecutive months, real house prices in May 2019 were falling at an annual rate of 7.2 per cent.

Going forward the OBR’s Fiscal Risks Report predicts that, in the event of a no-deal, no-transition exit of the UK from the European Union, nominal UK house prices would fall by almost 10 per cent between the start of 2019 and mid-2021. This forecast is driven by the assumption that the UK would enter a year-long recession from the final quarter of 2019. It argues that property transactions and prices ‘move disproportionately’ during recessions. (See John’s blog The costs of a no-deal Brexit for a fuller discussion of the economics of a no-deal Brexit). The danger therefore is that the housing market becomes characterised by both nominal and real house price falls.

Articles

Questions

  1. Explain the difference between a rise in the rate of house price inflation a rise in the level of house prices.
  2. Explain the difference between nominal and real house prices.
  3. If nominal house prices rise can real house price fall? Explain your answer.
  4. What do you understand by the terms instructions to buy and instructions to sell?
  5. What factors are likely to affect the levels of instructions to buy and instructions to sell?
  6. How does the balance between instructions to buy and instructions to sell affect house prices?
  7. How can we differentiate between different housing markets? Illustrate your answer with examples.

The latest UK house price index continues to show an easing in the rate of house price inflation. In the year to January 2019 the average UK house price rose by 1.7 per cent, the lowest rate since June 2013 when it was 1.5 per cent. This is significantly below the recent peak in house price inflation when in May 2016 house prices were growing at 8.2 per cent year-on-year. In this blog we consider how recent patterns in UK house prices compare with those over the past 50 years and also how the growth of house prices compares to that in consumer prices.

The UK and its nations

The average UK house price in January 2019 was £228,000. As Chart 1 shows, this masks considerable differences across the UK. In England the average price was £245,000 (an annual increase of 1.5 per cent), while in Scotland it was £149,000 (an increase of 1.3 per cent), Wales £160,000 (an increase of 4.6 per cent) and £137,000 in Northern Ireland (an increase of 5.5 per cent). (Click here to download a PowerPoint copy of the chart.)

Within England there too are considerable differences in house prices, with London massively distorting the English average. In January 2019 the average house price in inner London was recorded at £568,000, a fall of 1.9 per cent on January 2018. In Outer London the average price was £426,000, a fall of 0.2 per cent. Across London as a whole the average price was £472,000, a fall of 1.6 per cent. House prices were lowest in the North East at £125,000, having experienced an annual increase of 0.9 per cent.

The Midlands can be used as a reference point for English house prices outside of the capital. In January 2019 the average house price in the West Midlands was £195,000 while in the East Midlands it was £193,000. While the annual rate of house price inflation in London is now negative, the annual rate of increase in the Midlands was the highest in England. In the West Midlands the annual increase was 4 per cent while in the East Midlands it was 4.4 per cent. These rates of increase are currently on par with those across Wales.

Long-term UK house price trends

Chart 2 shows the average house price for the UK since 1969 alongside the annual rate of house price inflation, i.e. the annual percentage change in the level of house prices. The average UK house price in January 1969 was £3,750. By January 2019, as we have seen, it had risen to around £228,000. This is an increase of nearly 6,000 per cent. Over this period, the average annual rate of house price inflation was 9 per cent. However, if we measure it to the end of 2007 it was 11 per cent. (Click here to download a PowerPoint copy of the chart.)

The significant effect of the financial crisis on UK house prices is evident from Charts 1 and 2. In February 2009 house prices nationally were 16 per cent lower than a year earlier. Furthermore, it was not until August 2014 that the average UK house rose above the level of September 2007. Indeed, some parts of the UK, such as Northern Ireland and the North East of England, remain below their pre-financial crisis level even today.

Nominal and real UK house prices

But how do house price patterns compare to those in consumer prices? In other words, what has happened to inflation-adjusted or real house prices? One index of general prices is the Retail Prices Index (RPI). This index measures the cost of a representative basket of consumer goods and services. Since January 1969 the RPI has increased by nearly 1,600 per cent. While substantial in its own right, it does mean that house prices have increased considerably more rapidly than consumer prices.

If we eliminate the increase in consumer prices from the actual (nominal) house price figures what is left is the increase in house prices relative to consumer prices. To do this we estimate house prices as if consumer prices had remained at their January 1987 level. This creates a series of average UK house prices at constant January 1987 consumer prices.

Chart 3 shows the average nominal and real UK house price since 1969. It shows that in real terms the average UK house price increased by around 266 per cent between January 1969 and January 2019. Therefore, the average real UK house price was 3.7 times more expensive in 2019 compared with 1969. This is important because it means that general price inflation cannot explain all the long-term growth seen in average house prices. (Click here to download a PowerPoint copy of the chart.)

Real UK house price cycles

Chart 4 shows that annual rates of nominal and real house price inflation. As we saw earlier, the average nominal house price inflation rate since 1969 has been 9 per cent. The average real rate of increase in house prices has been 3.1 per cent per annum. In other words, house prices have on average each each year increased by the annual rate of RPI inflation plus 3.1 percentage points. (Click here to download a PowerPoint copy of the chart.)

Chart 4 shows how, in addition to the long-term relative increase in house prices, there are also cycles in the relative price of houses. This is evidence of a volatility in house prices that cannot be explained by general prices. This volatility reflects frequent imbalances between the demand and supply of housing, i.e. between instructions to buy and sell property. Increasing levels of housing demand (instructions to buy) relative to housing supply (instructions to supply) will put upward pressure on house prices and vice versa.

In January 2019 the annual real house price inflation across the UK was -0.9 per cent. While the rate was slightly lower in Scotland at -1.2 per cent, the biggest drag on UK house price inflation was the London market where the real house price inflation rate was -4.0 per cent. In contrast, January saw annual real house price inflation rates of 2 per cent in Wales, 2.3 per cent in Northern Ireland and 1.8 per cent in the East Midlands.

Inflation-adjusted inflation rates in London have been negative consistently since June 2017. From their July 2016 peak, following the result of the referendum on UK membership of the EU, to January 2019 inflation-adjusted house prices fell by 7.6 per cent. This reflects, in part, the fact that the London housing market, like that of other European capitals, is a more international market than other parts of the country. Therefore, the current patterns in UK house prices are rather distinctive in that the easing is being led by London and southern England.

Articles

Questions

  1. What is meant by the annual rate of house price inflation?
  2. How is a rise in the rate of house price inflation different from a rise in the level of house prices?
  3. What factors are likely to determine housing demand (instructions to buy)?
  4. What factors are likely to affect housing supply (instructions to sell)?
  5. Explain the difference between nominal and real house prices.
  6. What does a decrease in real house prices mean? Can this occur even if actual house prices have risen?
  7. How might we explain the recent differences between house price inflation rates in London relative to other parts of the UK, like the Midlands and Wales?
  8. Why were house prices so affected by the financial crisis?
  9. Assume that you asked to measure the affordability of housing. What data might you collect?

Today’s title is inspired from the British Special Air Service (SAS) famous catchphrase, ‘Who Dares Wins’ – similar variations of which have been adopted by several elite army units around the world. The motto is often credited to the founder of the SAS, Sir David Stirling (although similar phrases can be traced back to ancient Rome – including ‘qui audet adipiscitur’, which is Latin for ‘who dares wins’). The motto was used to inspire and remind soldiers that to successfully accomplish difficult missions, one has to take risks (Geraghty, 1980).

In the world of economics and finance, the concept of risk is endemic to investments and to making decisions in an uncertain world. The ‘no free lunch’ principle in finance, for instance, asserts that it is not possible to achieve exceptional returns over the long term without accepting substantial risk (Schachermayer, 2008).

Undoubtedly, one of the riskiest investment instruments you can currently get your hands on is cryptocurrencies. The most well-known of them is Bitcoin (BTC), and its price has varied spectacularly over the past ten years – more than any other asset I have laid my eyes on in my lifetime.

The first published exchange rate of BTC against the US dollar dates back to 5 October 2009 and it shows $1 to be exchangeable for 1309.03 BTC. On 15 December 2017, 1 BTC was traded for $17,900. But then, a year later the exchange rate was down to just over $1 = $3,500. Now, if this is not volatility I don’t know what is!

In such a market, wouldn’t it be wonderful if you could somehow predict changes in market sentiment and volatility trends? In a hot-off-the press article, Shen et al (2019) assert that it may be possible to predict changes in trading volumes and realised volatility of BTC by using the number of BTC-related tweets as a measure of attention. The authors source Twitter data on Bitcoin from BitInfoCharts.com and tick data from Bitstamp, one of the most popular and liquid BTC exchanges, over the period 4/9/2014 to 31/8/2018.

According to the authors:

This measure of investor attention should be more informed than that of Google Trends and therefore may reflect the attention Bitcoin is receiving from more informed investors. We find that the volume of tweets are significant drivers of realised [price] volatility (RV) and trading volume, which is supported by linear and nonlinear Granger causality tests.

They find that, according to Granger causality tests, for the period from 4/9/2014 to 8/10/2017, past days’ tweeting activity influences (or at least forecasts) trading volume. While from 9/10/2017 to 31/8/2018, previous tweets are significant drivers/forecasters of not only trading volume but also realised price volatility.

And before you reach out for your smartphone, let me clarify that, although previous days’ tweets are found in this paper to be good predictors of realised price volatility and trading volume, they have no significant effect on the returns of Bitcoin.

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References

Questions

  1. Explain how the number of tweets can be used to gauge investors’ intentions and how it can be linked to changes in trading volume.
  2. Using Google Scholar, make a list of articles that have used Twitter and Google Trends to predict returns, volatility and trading volume in financial markets. Present and discuss your findings.
  3. Would you invest in Bitcoin? Why yes? Why no?

Back in October, we examined the rise in oil prices. We said that, ‘With Brent crude currently at around $85 per barrel, some commentators are predicting the price could reach $100. At the beginning of the year, the price was $67 per barrel; in June last year it was $44. In January 2016, it reached a low of $26.’ In that blog we looked at the causes on both the demand and supply sides of the oil market. On the demand side, the world economy had been growing relatively strongly. On the supply side there had been increasing constraints, such as sanctions on Iran, the turmoil in Venezuela and the failure of shale oil output to expand as much as had been anticipated.

But what a difference a few weeks can make!

Brent crude prices have fallen from $86 per barrel in early October to just over $50 by the end of the year – a fall of 41 per cent. (Click here for a PowerPoint of the chart.) Explanations can again be found on both the demand and supply sides.

On the demand side, global growth is falling and there is concern about a possible recession (see the blog: Is the USA heading for recession?). The Bloomberg article below reports that all three main agencies concerned with the oil market – the U.S. Energy Information Administration, the Paris-based International Energy Agency and OPEC – have trimmed their oil demand growth forecasts for 2019. With lower expected demand, oil companies are beginning to run down stocks and thus require to purchase less crude oil.

Fracking (Source: US Bureau of Land Management Environmental Assessment, public domain image)

On the supply side, US shale output has grown rapidly in recent weeks and US output has now reached a record level of 11.7 million barrels per day (mbpd), up from 10.0 mbpd in January 2018, 8.8 mbpd in January 2017 and 5.4 mbpd in January 2010. The USA is now the world’s biggest oil producer, with Russia producing around 11.4 mpbd and Saudi Arabia around 11.1 mpbd.

Total world supply by the end of 2018 of around 102 mbpd is some 2.5 mbpd higher than expected at the beginning of 2018 and around 0.5 mbpd greater than consumption at current prices (the remainder going into storage).

So will oil prices continue to fall? Most analysts expect them to rise somewhat in the near future. Markets may have overcorrected to the gloomy news about global growth. On the supply side, global oil production fell in December by 0.53 mbpd. In addition OPEC and Russia have signed an accord to reduce their joint production by 1.2 mbpd starting this month (January). What is more, US sanctions on Iran have continued to curb its oil exports.

But whatever happens to global growth and oil production, the future price will continue to reflect demand and supply. The difficulty for forecasters is in predicting just what the levels of demand and supply will be in these uncertain times.

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Data

Questions

  1. Identify the factors on both the demand and supply sides of the oil market that have affected prices recently.
  2. What determines the amount that changes in these factors affect the oil price?
  3. What determines (a) the price elasticity of demand for oil; (b) the income elasticity of demand for oil; (c) the price elasticity of supply of oil?
  4. Why might oil prices overshoot the equilibrium price that reflects changed demand and supply conditions?
  5. Use demand and supply diagrams to illustrate (a) the destabilising effects that speculation could have on oil prices; (b) a stabilising effect.
  6. Is the holding or large stocks of oil likely to stabilise or destabilise oil prices? Explain.
  7. What will determine the likely success of the joint OPEC/Russian policy to support oil prices by reducing supply?

One of the key developments in economics in recent years has been the growing influence of behavioural economics. We considered some of the insights of behavioural economics in a blog in 2016 (A nudge in the right direction?). As the post stated, ‘Behavioural economists study how people’s buying, selling and other behaviour responds to various incentives and social situations. They don’t accept the simplistic notion that people are always rational maximisers.’ The post quoted from a Livemint article (see first linked article below):

According to behavioural economists, the human brain neither has the time nor the ability to process all the information involved in decision making, as assumed by the rational model.

Instead, people use heuristics. A heuristic technique is any approach to problem-solving, such as deciding what to buy, which is practical and sufficient for the purpose, but not necessarily optimal. For example, people may resort to making the best guess, or to drawing on past experiences of similar choices that turned out to be good or bad. On other accasions, when people are likely to face similar choices in the future, they resort to trial and error. They try a product. If they like it, they buy it again; if not, they don’t.

On other occasions, they may use various rules of thumb: buying what their friends do, or buying products on offer or buying trusted brands. These rules of thumb can lead to estimates that are reasonably close to the utility people will actually get and can save on time and effort. However, they sometimes lead to systematic and predictable misjudgements about the likelihood of certain events occurring.

In traditional models of consumer choice, individuals aim to maximise their utility when choosing between goods, or bundles of goods. The context in which the choices are offered is not considered.

Yet, in real life, we see that context is important; people will often make different choices when they are presented, or framed, in different ways. For example, people will buy more of a good when it is flagged up as a special offer than they would if there is no mention of an offer, even though the price is the same.

The recognition that framing is important to choices has led to the development of nudge theory. Indeed, it underpins many marketing techniques. These seek to persuade people to make a particular choice by framing it in an optimistic way or presenting it in a way that makes it easy to decide.

Governments too use nudge theory. In the UK, the Coalition government (2010–15) established the Behavioural Insights Team (BIT) (also unofficially known as the Nudge Unit) in the Cabinet Office in 2010. A major objective of this team is to use ideas from behavioural economics to design policies that enable people to make better choices for themselves.

The podcast linked below, looks at the use of nudge theory. The presenter, Mary Ann Sieghart looks at how we are being encouraged to change our behaviour. She also looks at the work of UCL’s Love Lab which researches the way we make decisions. As the programme notes state:

Mary Ann is grilled in UCL’s Love Lab to find out how she makes decisions; she finds taking the pound signs off the menu in a restaurant encourages her spend more and adding adjectives to the food really makes it taste better.

Walking through the Nudge Unit, she hears how powerful a tiny tweak on a form or text can get be, from getting people back to work to creating a more diverse police force. Popular with the political left and right, it has been embraced around the world; from Guatemala to Rwanda, Singapore to India it is used to reduce energy consumption, encourage organ donation, combat corruption and even stop civil wars.

But the podcast also looks at some of the darker sides of nudging. Just as we can be nudged into doing things in our interests, so too we can be nudged to do things that are not so. Politicians and businesses may seek to manipulate people to get them to behave in ways that suit the government or the business, rather than the electorate or the consumer. The dark arts of persuasion are also something that behavioural economists study.

The articles below explore some of the areas where nudge theory is used to devise policy to influence our behaviour – for good or bad.

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Questions

  1. Explain what are meant by ‘bounded rationality’ and ‘heuristics’.
  2. How may populist politicians use nudge theory in their campaigning?
  3. Give some examples from your own behaviour of decisions made using rules of thumb.
  4. Should we abandon models based on the assumption of rational maximising behaviour (e.g. attempts to maximise consumer surplus or to maximise profit)?
  5. Find out some other examples of how people might be nudged to behave in ways that are in their own interest or that of society.
  6. How might we be nudged into using less plastic?
  7. How might people be nudged to eat more healthily or to give up smoking?
  8. To what extent can financial incentives, such as taxes, fines, grants or subsidies be regarded as nudging? Explain.
  9. Would you advise all GP surgeries and hospital outpatient departments to text reminders to people about appointments? What should such reminders say? Explain.