The last two weeks have been quite busy for macroeconomists, HM Treasury staff and statisticians in the UK. The Chancellor of the Exchequer, Mr Phillip Hammond, delivered his (fairly upbeat) Spring Budget Statement on 13 March, highlighting among other things the ‘stellar performance’ of UK labour markets. According to a Treasury Press Release:
Employment has increased by 3 million since 2010, which is the equivalent of 1,000 people finding work every day. The unemployment rate is close to a 40-year low. There is also a joint record number of women in work – 15.1 million. The OBR predict there will be over 500,000 more people in work by 2022.
To put these figures in perspective, according to recent ONS estimates, in January 2018 the rate of UK unemployment was 4.3 per cent – down from 4.4 per cent in December 2017. This is the lowest it has been since 1975. This is of course good news: a thriving labour market is a prerequisite for a healthy economy and a good sign that the UK is on track to full recovery from its 2008 woes.
The Bank of England welcomed the news with a mixture of optimism and relief, and signalled that the time for the next interest rate hike is nigh: most likely at the next MPC meeting in May.
But what is the practical implication of all this for UK consumers and workers?
For workers it means it’s a ‘sellers’ market’: as more people get into employment, it becomes increasingly difficult for certain sectors to fill new vacancies. This is pushing nominal wages up. Indeed, UK wages increased on average by 2.6 per cent year-to-year.
In real terms, however, wage growth has not been high enough to outpace inflation: real wages have fallen by 0.2 per cent compared to last year. Britain has received a pay rise, but not high enough to compensate for rising prices. To quote Matt Hughes, a senior ONS statistician:
Employment and unemployment levels were both up on the quarter, with the employment rate returning to its joint highest ever. ‘Economically inactive’ people — those who are neither working nor looking for a job — fell by their largest amount in almost five and a half years, however. Total earnings growth continues to nudge upwards in cash terms. However, earnings are still failing to outpace inflation.
An increase in interest rates is likely to put further pressure on indebted households. Even more so as it coincides with the end of the five-year grace period since the launch of the 2013 Help-to-Buy scheme, which means that many new homeowners who come to the end of their five year fixed rate deals, will soon find themselves paying more for their mortgage, while also starting to pay interest on their Help-to-buy government loan.
Will wages grow fast enough in 2018 to outpace inflation (and despite Brexit, which is now only 12 months away)? We shall see.
The President of the United States, Donald Trump, announced recently that he will be pushing ahead with plans to impose a 25% tariff on imports of steel and a 10% tariff on aluminium. This announcement has raised concerns among the USA’s largest trading partners – including the EU, Canada and Mexico, which, according to recent calculations, expect to lose more than $5 billion in steel exports and over $1 billion in aluminium exports.
A number of economists and policymakers are worried that such policies restrict trade and are likely to provoke retaliation by the affected trade partners. In recent statements, the EU has pledged to take counter-measures if the bloc is affected by these policies. In a recent press conference, the Commissioner for Trade, Cecilia Malmstrom, stated that:
We have made it clear that a move that hurts the EU and puts thousands of European jobs in jeopardy will be met with a firm and proportionate response.
She added that, ‘I truly hope that this will not happen. A trade war has no winners.’
Why is everyone so worried about trade wars then? Trade wars, by definition, result in trade diversion which can hurt employment, wealth creation and overall economic performance in the affected countries. As affected states are almost certain to retaliate, these losses are likely to be felt by all parties that are involved in a trade war – including the one that instigated it. This results in a net welfare loss, the size of which depends on a number of factors, including the relative size of the countries that take part in the trade war, the importance of the affected industries to the local economy and others.
A number of studies have attempted to estimate the effect of trade restrictions and tariff wars on welfare: see for instance Anderson and Wincoop (2001), Syropoulos (2002), Fellbermayr et al. (2013). The results vary widely, depending on the case. However, there seems to be consensus that the more similar (in terms of size and industry composition) the adversaries are, the more mutually damaging a trade war is likely to be (and, therefore, less likely to happen).
As Miyagiwa et al (2016, p43) explain:
A country initiates contingent protection policy against a trading partner only if the latter has a considerably smaller domestic market than its own, while avoiding confrontation with a country having a substantially larger domestic market than its own.
As both Canada and the EU are very large advanced market economies, it remains to be seen how much risk (and potential damage to the local and global economy) US trade policymakers are willing to take.
Last week was a rough week for Britain. The “Beast from the East” and storm Emma swept through the country, bringing with them unusually heavy snowfall, which resulted in severe disruption across nearly all parts of the country. Some recent estimates put the cost of these extreme weather conditions at up to £1 billion per day. The construction industry suffering the biggest hit as work came to a halt for the best part of the week. Losses for the industry were estimated to be up to £2 billion.
Closed restaurants, empty shops and severely disrupted transport networks were all part of the effect that this extreme weather had on the overall economy. According to Howard Archer, chief economic adviser of the EY ITEM Club (a UK forecasting group):
It is possible that the severe weather [of the last few days] could lead to GDP growth being reduced by 0.1 percentage point in Q1 2018 and possibly 0.2 percentage points if the severe weather persist.
As the occurrence of freak weather increases across the globe due to climate change, so does the economic cost of these events. The figure above shows the estimated costs of extreme weather events in the USA between 1980 and 2012 and it is reproduced from Jahn (see link below), who also fits a quadratic trend to show that these costs have been increasing over time. He goes on to characterise the impact of different types of extreme weather (including cold waves, heat waves, storms and others) on different sectors of the local economy – ranging from tourism and agriculture, to housing and the insurance sector.
Linnenluecke et al (linked below) argue that extreme weather caused by climate change could influence the decision of firms on where to locate and could lead to a reshuffle of economic activity across the world and have important policy implications. As the authors explain:
Climate change-related relocation has been given consideration in policy-oriented discussions, but not in management decisions. The effects of climate change and extreme weather events have been considered as peripheral or as a risk factor, but not as a determining factor in firm relocation processes…. This paper therefore [provides] insights for understanding how firms can enhance strategic decision-making in light of understanding and assessing their vulnerability as well as likely impacts that climate change may have on relocation decisions.
The likelihood and associated costs of extreme weather events could therefore become an increasingly important matter for discussion amongst economists and policy makers. Such weather events are likely to have profound economic implications for the world.
Would you start a family if you were pessimistic about the future of the economy? Buckles et al (2017) (see link below) believe that fewer of us would do so and, therefore, fertility rates could be used by investors and central banks as an early signal to pick up subtle changes in consumer confidence and overall economic climate.
Their study titled ‘Fertility is a leading economic indicator’ uses ‘live births’ data, sourced from US birth certificates, to explore if there is any association between fertility changes (measured as the rate of change in number of births) and GDP growth. Their results suggest that, in the case of the USA, there is: dips in fertility rates tend to precede by several quarters slowdown in economic activity. As the authors state:
The growth rate of conceptions declines prior to economic downturns and the decline occurs several quarters before recessions begin. Our measure of conceptions is constructed using live births; we present evidence suggesting that our results are indeed driven by changes in conceptions and not by changes in abortion or miscarriage. Conceptions compare well with or even outperform other economic indicators in anticipating recessions.
Although this is not the first piece of academic writing to claim that fertility has pro-cyclical qualities (see for instance, Adsera (2004, 2011), Adsera and Menendez (2011), Currie and Schwandt (2014) and Chatterjee and Vogle (2016) linked below), it is, to the best of our knowledge, the most recent paper (in terms of data used) to depict this relationship and to explore the suitability of fertility as a macroeconomic indicator to predict recessions.
Economies, after all, are groups of people who participate actively in day-to-day production and consumption activities – as consumers, workers and business leaders. Changes in their environment should affect their expectations about the future.
Are people, however, forward-looking enough to guide their current behaviours by their expectations of future economic outcomes? They may be, according to the findings of this study.
Did you know, for instance, that sales of ties tend to increase in economic downturns, as men buy more ties to show that they are working harder, in fear of losing their job[1]? But this is probably a topic for another blog.
Give two reasons why fertility rates may be a good indicator of economic activity.
Give two reasons why fertility rates may NOT be a good indicator of economic activity.
Do a literature search to identify and explain an ‘unorthodox’ macroeconomic indicator of your choice, and how it has been used to track economic activity.
The Winter Olympics are full on as athletes from all over the world compete against each other, hoping to set new world records, win medals and be known as Olympians. Pyeongchang, the South Korean county that hosts the 2018 Winter games, enjoys a large influx of tourists – estimated at 80,000 people a day. This is certainly an unusually large number of tourists for a region that has a regular winter-time population of no more than 45,000 people.
Having such a high number of visitors to the Winter Olympics, and even more to the larger Summer Olympics, is not an unusual occurrence, however, and it is often mentioned as one of the benefits of being a host to the Olympic Games.
Baade and Matheson (see link below) distinguish between three key benefits of hosting the Olympic Games: “the short-run benefits of tourist spending during the Games; the long-run benefits or the ‘Olympic legacy’, which might include improvements in infrastructure and increased trade, foreign investment, or tourism after the Games; and intangible benefits such as the ‘feel-good effect’ or civic pride”.
On these grounds, a number of studies have been authored, attempting to analyse some or all of these benefits, distinguishing between short-term and long-term effects. Müller (see link below), uses data from the 2014 Oympic Games in Sochi, Russia, to assess the net economic outcome for the host region. He concludes that any short-term economic benefits caused by the investment influx (before and during the games) could not offset the long-term costs, leading to an estimated net loss of $1.2 billion per year.
Zimbalist (2015) and Szymanski (2011) report similar results when analysing data from the London Games (2012) and past major sporting events (Games and FIFA World Cup). Kasimati (2003) points out the significant economic benefits that host regions tend to enjoy for years after hosting the games, but argues that the overall effect depends on a number of factors (including pre-existing infrastructure and location).
The jury is, therefore, still out on what is the overall economic effect of being host to this ancient institution. But I must now dash as women’s hockey is soon to start. “Let everyone shine”.
Using supply and demand diagrams, explain whether you would expect hotel room prices to change during the hosting of a major sports event, such as the Winter Olympics.
List three economic (or economics-related) arguments in favour of and against the hosting of the Olympic games. Relate your answer to the empirical evidence presented in the literature.
Why is it so difficult to estimate with accuracy the net economic effect of the Olympic Games?