The Population Crisis

According to popular legend, the science of economics was christened “the dismal science” by Thomas Carlyle following the publication by Thomas Malthus in 1798 of “An Essay on the Principle of Population”. In this he suggested that poverty and hunger would be a country’s natural state since increases in population would tend to outstrip increases in food supply. Fortunately he was proved wrong as birth rates fell and new techniques increased the supply of food and the science of economics moved on.

We are currently focused on short-term issues such as Brexit but it is worth taking a longer perspective following the publication of a report in ‘The Lancet’ which has highlighted falling fertility rates across the world between 1950 and 2017. The reasons behind the fall include better education and employment prospects for women, improved access to contraception, better maternal education for mothers and prospective mothers and improvements in infant mortality. As a result, 91 out of 195 countries have been identified as having a fertility rate below 2.05 – the minimum necessary for stable population growth. For example, in Britain over the period, the fertility rate fell from 2.2 to 1.7.

The implications of falling fertility rates in richer countries, partially masked by inward immigration, focus on the conflict between increased life expectancy, creating an increased number of elderly pensioners receiving benefits and increasingly needing expensive medical care, and a falling supply of workers who are paying taxes to support the elderly. These workers will therefore face a greater burden in terms of the taxes they will need to pay to support the elderly.

This is already significant in Japan where 28% of the population are over 65, the highest proportion in the world, compared with 18% in the UK and 22% in Germany. One offsetting feature in Japan is that people often work on beyond their retirement age – 3% of their labour force is over 80! Although it is not suggested that working until 80 becomes the norm, the retirement age in many countries is being increased as a result of increased life expectancy and, in the UK, it will reach 66 by October 2020 and 67 by 2028 for both men and women. This will reduce pension payments and increase tax revenue but, alone, is unlikely to be enough to prevent developed countries facing increasing budget deficits to finance care and benefits for the elderly.

As this crisis unfolds, the people who will suffer most are not the elderly but younger generations who will not only be working longer and paying higher taxes but will face student debt and higher house prices than experienced by their grandparents

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How are we doing?

Those of you who are Manchester United fans will have been pleased by their comeback against Newcastle over the weekend. However, in the excitement, you might have missed the news that former United star, David Beckham, and his wife Victoria have sold their Beverley Hills house (or mansion) which has six bedrooms and nine bathrooms, for $33million. They bought it eleven years ago for $22milion. At the other end of the scale, you might also have missed the report from the Social Metrics Commission, (SMC) putting forward a new measure of poverty for the UK.

Measuring the number of people in poverty is difficult. Some countries, such as the USA, focus on absolute poverty where an income is identified as the minimum needed to meet a family’s basic needs and those below it are deemed to be in poverty. A variant of this approach involves estimating a minimum standard above which people should live. An alternative, which has become the benchmark for the UK, is to focus on relative poverty (i.e. compared to other people) and consider those in poverty as living in households with incomes below 60% of the median.  However this is not straight-forward since there are two different ways of considering income (before and after housing costs are deducted) and the measure excludes assets people possess.

The SMC focusses strictly on measuring poverty, which, for them, is not having the resources available to meet current needs to be able to “engage adequately in a life regarded as the “norm” in society.”

To assess the number in poverty they consider the resources available to households, namely net income (net earnings from employment and self-employment, benefits and unearned net income (e.g. from rent or interest). They also include assets, such as savings which can be easily accessed and subtract any costs that the family must pay. These costs include debt repayment, housing costs (rent or mortgage payments), service charges in flats, building insurance, council tax, water rates, the community charge, childcare costs and additional costs faced by the disabled. Subtracting these costs gives an estimate of the resources available to a household. The next stage was to estimate the required level of resources needed to meet their benchmark and then set a poverty line at a threshold of 55% of the three-year median resources available measure.

Using this approach, their key findings, using 2016/17 data, were that:

  • 22% of the population (14.2 million) is living in a family considered to be in poverty. However 52% of people in lone-parent families (2.6 million) are in poverty.
  • Of those in poverty, 8.4 million are working-age adults; 4.5 million are children and 1.4 million are pension age adults.
  • The poverty rate for working-age adults is 21.6%; for children it is 32.6%; and for pension-age adults it is 11.4%. For pensioners, the rate has fallen from 20.8% in 2001 to 11.4% in 2017.
  • The majority (68.0%) of people living in workless families are in poverty, compared to 9.0% for people living in families where all adults work full time.
  • Those in poverty are not equally distributed across the country. Poverty rates in Scotland are lower and Welsh poverty rates are higher than in other UK countries. England has the highest child poverty rate and the overall poverty rate in London is more than 10% higher than in some other English regions.
  • The report also found that the number of people (2.5 million) above the threshold by 10% or less is almost identical to the number of people (2.7 million) below the threshold by 10% or less, suggesting that small changes in circumstances can either take people out of or put them into poverty. However 2/3 of those in poverty (12% of the total population) have been in persistent poverty, (being in poverty for two out of the last three years), suggesting that although they might be close to the benchmark, it is not easy to escape from poverty.

The SMC findings raise questions about the benefit system and how we deal with poverty.

Are we happy that over half of single parent families are in poverty?

Are we happy that 2/3 of those in families where no one is working are in poverty?

Are we happy that twice as many working age adults and three times as many children are classed as living in poverty compared to the percentage of pensioners in poverty?

UK Consumer Spending

Consumer spending is a major component of GDP and, to assist in its analysis, the Office for National Statistics has just produced an analysis of spending within regions across the UK. The data was collected using two surveys –  the Living Costs and Food Survey (also used as the basis of the Consumer Price Index) and the Annual Business Survey which records sales of businesses. The former looks at 5,000 households (not a particularly large number when broken down into regions) which are interviewed and keep a diary of their expenditure for a two-week period; the latter records retail sales of 80,000 businesses, so provides a larger sample, but suffers in accuracy because some sales go to businesses, not consumers.

The data is broken down into twelve categories which are in turn subdivided into narrower classifications. The twelve categories are food and soft drinks, alcohol and tobacco (and narcotics), clothing and footwear, household goods and services, housing, health, transport, communications, recreation and culture, education, restaurants and hotels, and a miscellaneous category covering items not included in previous sections. The data is also split down into nine English regions, Scotland, Northern Ireland and Wales.

The average spending per person in 2016 in the UK was £18,787 and, not surprisingly because of high incomes and high housing costs, London had the highest national expenditure (£24,545), while the lowest spending was in the West Midlands (£15,276) and Wales (£15,965). The region with the highest growth between 2015 and 2016 was the North East (8.1%) while the lowest growth was in Northern Ireland (- 0.4%), the only area to see a fall in spending per person in this period.

The survey also provided information about the levels of savings across the country with an average savings ratio (savings out of disposable income) of 6.9%. The ratio was highest in London (14.5%) while the lowest levels occurred in the South West, (1.5%).

The ONS looked at the breakdown of spending between the different categories. London stood out, with 42% of spending going on housing, compared to the UK average of 27%. As a result, it spent proportionately less in the other categories. Excluding London, there is relatively little variation between the regions although, proportionately, spending on tobacco in Northern Ireland is high, spending on food and clothing in Yorkshire is lower than in other regions and spending on recreation and culture in London is the lowest of all areas. The UK averages were: Food 10%, Alcohol and tobacco 4%; Clothing and footwear 5%; Housing 27%; Household goods and services 5%; Health 2%; Transport 13%; Communications 2%; Recreation and culture 10%; Education 1%; Restaurants and hotels 10%; Miscellaneous 13%.

Since 2014, among the sub-categories are drugs and prostitution and their inclusion has added about £10billion to the UK’s GDP. However, because these activities are traded in the shadow or hidden economy and the suppliers do not disclose their earnings to the tax authorities, the ONS has warned that the accuracy of these two categories is low. Nevertheless, it was still able to suggest that more is spent on prostitution than on gardening and DIY activities.

The impact of technology – The Fourth Industrial Revolution?

Amazon has opened a shop in Seattle with no checkouts and customers who do not pay on leaving. Instead, with the appropriate app to link the shopping to an Amazon account, all that is needed is to go round the store, put items in a bag and scanners and sensors do the rest. After leaving the store, payment is debited from your account. There are no queues and no cashiers.  So successful has it proved that more have been opened. It already has three in Seattle and one in Chicago and plans ten by the end of 2018, 50 by the end of 2019 and, according to some press reports, 3,000 such shops within three years.

Electric cars have also been in the news over the summer, with a focus on how they will reduce the environmental damage from driving. What has been less well-publicised is their possible impact on the demand for workers in the factories of the future. Electric cars are easier to manufacture than current ones because their mechanism has fewer moving parts than the internal combustion engine. This means both that fewer workers will be needed and those on the manufacturing process will be less skilled, making it easier to outsource manufacture to other countries. However new technology in the motor industry could, potentially, have an even greater impact with the arrival of driverless vehicles. Uber is already looking into driverless taxis and black cab and white van drivers could become a distant memory in the same way that stokers on railways are no longer with us and blacksmiths are a rarity.

A robot is being developed, based on technology used in the NASA Rover to explore Mars, which will drive itself round battery chicken sheds, measuring the chickens by sight and checking their temperatures. This machine is likely to be popular if farmers face a shortage of labour after Brexit since they will replace human workers.

There is considerable dispute over the numbers and what the future will look like. Some suggest traditional, full-time jobs will decline and there will be an increase in remote working but overall, there will  be little impact on the number of jobs. Others argue that the impact will be positive, with new technology creating more jobs than are lost. They suggest there will be a much greater need for workers to develop, build and maintain the new technology and there will be some areas such as the care industry (growing because of an ageing population) where more human workers are likely to be needed to care for patients. McKinsey, a worldwide consultancy form,  recently predicted that robots will have the same impact on the global economy as the development of the steam engine, adding 1.2%pa to global growth by 2030.

A report by the World Economic Forum (The Future of Jobs, 2018), one of the more optimistic forecasters, has suggested that 42% of the world’s jobs will be done by machines by 2022, up from 29% today. It also estimates that although 75 million jobs will be lost by 2022, 133 million new jobs will be generated, resulting in an additional 58 million jobs. They see losses in administration, clerical, manufacturing, construction, legal, and maintenance sectors but increased demand for those in data analysis, management, computing, architecture, engineering, sales, education and training. Different numbers come from PWC, a worldwide firm of accountants, who predicted in July that about 7 million jobs will be lost by 2020 because of technology but 7.2 million will be created. They see losses in manufacturing, transport and public administration while the increases will occur in healthcare, science and technology and education.

Others are less optimistic. During the summer, Andy Haldane, the Bank of England’s chief economist, made the news by predicting that the impact of artificial intelligence could be more disruptive than previous industrial revolutions and would lead to widespread job losses. He argued that previously machines had replaced labour doing manual tasks whereas increasingly machines, because of developments in AI, are undertaking tasks previously thought to be beyond them. Mr Carney, the Governor of the Bank of England, suggested that the latest industrial revolution would threaten 10% of jobs in the UK and, while some workers would benefit from being more productive and earning higher wages, others, losing their jobs,  would not easily be able to find employment providing a reasonable standard of living and would need to be able to access education and re-training throughout their lives.

However the big issue will be that the people filling the new jobs are unlikely to be those losing the old ones. How society copes with this will be a major issue for the future.

Inflation in Venezuela

It is difficult to be precise about the rate of inflation in Venezuela since the government has significantly reduced its publication of economic data.  The Economist recently quoted a current rate of 46,000% per year, other estimates put it closer to 100,000% and the IMF estimates it will rise to 1 million per cent by the end of the year! The impact of such a rate mirrors what happened in Germany in the 1920s, Hungary in 1946 where inflation at one point reached 150,000% PER DAY, and Zimbabwe’s two episodes of hyperinflation in the last ten years. In Germany, workers were paid twice a day, and given breaks to buy things before prices went up even further, using wheelbarrows and suitcases to carry their money to the shops. Although the Venezuelan president, Nicolas Maduro, has blamed opposition activists, officials in Washington and criminal gangs for the hyperinflation, independent observers suggest it is caused largely by the government printing money to pay its budget deficit, currently running at 30% of GDP. Ironically in Venezuela today, almost everyone is a millionaire but 4/5 of the population live in poverty and their average weight is falling because they cannot afford enough food. There are reports of shoppers falling ill because the only meat they can afford is discounted because it is no longer fresh.

The effects of such high levels of inflation on the metro in Caracas (capital of Venezuela) epitomise the problems caused by hyperinflation. The metro, built in 1983, was once heralded as a sign of the efficiency and progress of the economy. It was highly efficient and ran on time. The price of a ticket was fixed at 4 bolivars by the government which now equates to only a tiny fraction of 1p but, even if they wanted to, travellers cannot pay the government has run out of the paper needed to print them so all the ticket machines are marked as being out of order and people travel for free. However the journey is unlikely to be trouble-free. Demand has risen since people cannot afford taxis or fuel for private cars and the system now transports 2.5m people a day, three and a half times the number it was designed for. Only half the trains are working. Despite there being 11,000 workers officially employed, there is a shortage of workers since pay is only around 50p per week.

In Venezuela at present, it is more profitable scavenging for food in rubbish dumps than working. Output is falling for the third successive year and, despite having rich reserves of oil, which should make Venezuela one of the richest South American economies, oil production, which accounts for 95%  of export earnings in the country and a quarter of gross domestic product, (total output of the country) fell by a half between January 2016 and January 2018. Venezuela has been unable to stop a six-year-long production decline, caused by inadequate investment, US sanctions and a lack of skilled workers who have left the country for a better standard of living elsewhere.

There was even a shortage of banknotes which are imported. Last year the banks were forced to limit cash withdrawals to the equivalent of one US dollar a day. Increasingly, transactions are made electronically but those trying to make even a medium-sized purchase via a debit card found that many screens in shops or on their phones were too small to handle the large number of zeros needed. One of most popular television programmes, a Venezuelan version of “Who wants to be a Millionaire”, was abandoned because of the fall in the value of the currency – were it being broadcast today, the top prize would be worth 13p!

To solve the problems caused by hyperinflation, the government has raised the minimum wage by 3,500%, and  President Maduro has announced plans to reduce the government’s budget deficit (the amount the government borrows) from 30% of GDP to zero by increasing VAT and the price of fuel, which is currently very heavily subsidised, therefore admitting implicitly that high government borrowing and the printing of money was a key cause of the hyperinflation. In addition, in August, the government devalued the currency from 250,000 to the US dollar to the black market rate of 6m to the dollar and then introduced a new bolivar, converting 100,000 old bolivars to 1 new bolivar. However the future does not look promising since the value of the new currency fell by 18 % on the black market in the first two weeks after devaluation.

New insights into GDP

A new book “The Growth Delusion” by David Pilling, a Financial Times journalist, provides interesting insights into our obsession with economic growth and how we measure it. This blog highlights only some of his key points which are relevant to A’level and IB economics. The book is definitely worth a read. Modern GDP statistics (“the value of goods and services produced in a given period”)  have their origin in the USA around the 1930s with the work of Kuznets, who produced the first national income data to see the impact of the Great Depression on the US economy. They became more important during the Second World War when the UK government, prompted by Keynes, and the US government needed to be able to manage the war effort to maximum effect while still providing enough resources for consumption.

Pilling points out the many failings of GDP as an economic indicator such as the way it takes no account of what is produced, merely its value. Thus he points out that  wars can be good for GDP if they involve countries producing more tanks, weapons and aircraft. Similarly, two forks are, in GDP terms, as useful as a knife and fork, but less useful in reality when trying to spread jam on toast or cut one’s steak.  He is also scathing about the use of averages and points out that while a rich country might have a high average GDP, and therefore, according to economists, a high standard of living, if this is held by a very small number of people, the standard of living of the majority might be below that of a country with a lower average of GDP.

Measurement of GDP is difficult since it is impossible to measure every transaction and therefore relies on surveys e.g. the Living Costs and Food Survey for about 5,000 households and monthly surveys of approximately 45,000 businesses. The development of technology has made the measurement of GDP more difficult. The UK Government set up an inquiry under Charlie Bean – OB and former Deputy Governor of the Bank of England – who made comments similar to those expressed by David Pilling in terms of activities which are now much harder to measure and value such as using Google Maps rather than buying a paper OS map or streaming films rather than buying or renting DVDs. Another problem is that many things have become cheaper and better – my new recorder is easier to use and records more than a previous DVD recorder  but, in GDP terms, it is less valuable because it is cheaper.

There have been many debates over what should be included in GDP and although these might seem largely irrelevant, they matter when trying to compare countries’ GDP. In the past certain things, such as the sale of cannabis in cafes in Holland were legal and therefore recorded while a similar purchase in Romford would not be counted. However Eurostat wanted consistency among its members and decided that all transactions for goods or services involving money were to be recorded, whether they legal, illegal, good or bad. Therefore, in a purely numerical way, those who argue in favour of increasing GDP as being a key government objective, could argue that encouraging the sale of drugs or prostitution is as valid as increased spending on education or health – something even an economist would find hard to justify! More relevantly sales of guns in the UK  are part of the shadow economy but in the US they are legal, widespread and contribute to their GDP.

Pilling also considers the problems of measuring GDP in developing countries where a significant percentage of production takes place in the shadow economy; for example in Zimbabwe only 6% of the is formally employed. Similarly, my purchase of bottled water from Waitrose  is counted in the UK’s GDP, but the effort of a African villager who spends hours walking to and from a stream or well to collect “free” water has no value according to GDP statistics. He describes the way lights at night are used to indicate economic activity in different areas with increases in intensity over time indicating growth. Such methods indicate that the proportion of economic activity occurring in villages, and not always measured, is more significant than thought and therefore the GDP of many developing countries is, similarly, larger than previously calculated.