According to Lacy Hunt, chief economist at Hoisington Investment Management the “business cycle” is actually three different waves occurring in a specific order. They peak and trough in that sequence
Financial cycle – lose and tight monetary policy influence the movement
GDP cycle – monetary policy then impact inflation and risk-taking
Price/labour cycle – this later makes wages and prices rise
Source: Hoisington Investment Management
Can the US Fed stimulate growth?
Although central banks can control the money supply, the velocity that it moves in an economy is very important to the business cycle – creating more money has little effect if people don’t use it. Velocity in the US is now lower than it was in the great depression. This is a serious problem for the US Federal Reserve’s attempts to stimulate growth.
There is also the problem of Marginal revenue product of debt – this is the amount of GDP growth generated by each additional dollar of debt. That has been falling for years and is set to fall even more as higher rates divert a bigger part of the revenue from debt-funded projects to interest payments instead of more productive uses.
Source: Mauldin Economics: Thoughts from the front line – 6th May 2023
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Stats NZ has released its Regional gross domestic product: Year ended March 2022 report, which provides a geographical breakdown of economic activity within New Zealand. New Zealand’s value-added output:
78% within the North Island
22% within the South Island
Auckland region contributing close to 38% of New Zealand’s annual GDP with Wellington coming in second at 12.5%
Highest GDP per capita is the Wellington region $82,772 per capita, followed by the Auckland region $80,328 per capita.
Lowest GDP per capita was the Northland region, at $46,611
The Taranaki region recorded the highest nominal GDP per capita growth over the year (+14.3 percent), followed by the Auckland region (+11.4 percent).
A good exercise with your class is to get them to match the figures with the area of New Zealand. Figures below are in $m
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On my way to work last week there was a very good interview on National Radio (NZ) with Robert MacCulloch an economics professor at the University of Auckland. This ended up to be my lesson plan with my A Level class for the last day of term. MacCulloch argued that the interest rate hike of 50 basis points was too great an increase and could lead to a hard landing and deeper recession that could be avoided. His main arguments were:
Inflation has stabilised as quarterly inflation had dropped from 2.2% to 1.4% therefore no need for a 50 basis point rise.
In other countries (USA) inflation is dropping and those central banks are holding off on interest rate increases.
Stated that the RBNZ wants a hard landing and therefore a recession which can be damaging with higher unemployment.
More gradualist approach should have been adopted.
RBNZ stated that the post-covid inflation was a temporary blip and that stagflation was back in the early 1980’s – we live in a different world today.
Would it be better to go hard early with higher increases and then be able to loosen monetary policy? This may mean recession where you hit mortgage holders and those that become unemployed.
A lot of other central banks adopting a wait and see approach – couldn’t the RBNZ do the same?
Okun’s Law – A slowdown in GDP growth typically coincides with rising unemployment. A hard landing will result in this.
In NZ GDP shrank 2% compared to the UK 11%. NZ grew in 2021 so was there a need to have close to 0% interest rates and print $50bn?
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With the onslaught of COVID one wondered whether the jobs lost during the pandemic would “come back”. Part of the logic was that since robots don’t fall ill, bosses would turn to them instead of to people and COVID would act as a catalyst towards automation.
For a number of years the rhetoric has been that robots will see the end of a lot of jobs and whilst that maybe the case for some occupations the number of people in work has risen to very high levels in developed economies. For instance countries that have the highest presence of robot use e.g. Japan and South Korea also have the lowest unemployment rate. However both those countries do have ageing populations which does make the supply of labour more scarce. A study by Daisuke Adachi of Yale University suggested that between 1978 and 2017 an increase of one robot per 1,000 workers boost firms’ employment by 2.2%. Other research done in Finland concluded that the adoption of advanced technologies led to increases in hiring. According to The Economist there are an estimated 30m unfilled vacancies across the OECD.
“a strong positive association with firm survival, and that greater initial automation was associated with increases in employment”.
Automation and Inequality
However although technology doesn’t necessarily mean a loss of jobs it may have helped to increase the widening gap between incomes. In November 2021 Daron Acemoglu Testified its the US Congress on Automation and Economic Disparity. He identified two types of evidence to show the impact of technology on inequality:
In local labour markets (commuting zones) where there has been faster adoption of industrial robots, we see not just lower employment and wages, but also greater inequality between high-education and low-education workers and a bigger gap between those at the top and bottom of the income distribution.
There is an interesting relationship between two groups of workers – those that had their jobs taken over by automation and those that have not experienced much direct automation. Acemoglu’s research showed that those employed in routine tasks that can automated in industries undergoing rapid automation — have almost uniformly experienced large declines in their real wages. These groups include all demographic categories with less than a college degree. However those workers that have not experienced much direct automation, including those with post-graduate degrees and women with college degrees, have seen their earnings increase rapidly over the last 40 years. The Figure below indicates that more than half, and perhaps as much as three quarters, of the surge in wage inequality in the US is related to automation.
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Sources:
Economists are revising their views on robots and jobs. The Economist – January 22nd 2022
Daron Acemoglu – Written Testimony, House Select Committee on Economic Disparity and Fairness in Growth Hearing on Automation and Economic Disparity. November 3, 2021
Although the paradox of thrift has been a regular part of the CIE A Level syllabus it is has only become more relevant since the Global Financial Crisis (GFC). It has its origins in the 1714 book entitled ‘The Fable of Bees’ by Bernard Mandeville but it was John Maynard Keynes who really popularized this concept during the Great Depression of the 1930’s. Classical economic theory suggests that greater levels of saving will increase the amount of loanable funds in the banks and therefore reduce the cost of money – interest rates. This allows people to put off consumption to a later date thereby avoiding the risk of taking on debt and thereby give people security if their jobs became threatened during a recessionary period
Keynes’ beliefs
Keynes argues that saving was not a virtue from a macroeconomic view as he believed that negative or pessimistic expectations during the Depression would dissuade firms from investing. Cutting the rate of interest is supposed to be the escape route from economic recession: boosting the money supply, increasing demand and thus reducing unemployment. He also suggested that sometimes cutting the rate of interest, even to zero, would not help. People, banks and firms could become so risk averse that they preferred the liquidity of cash to offering credit or using the credit that is on offer. In such circumstances, the economy would be trapped in recession, despite the best efforts of monetary policy makers. The graph below shows a liquidity trap. Increases or decreases in the supply of money at an interest rate of X do not affect interest rates, as all wealth-holders believe interest rates have reached the floor.
All increases in money supply are simply taken up in idle balances. Since interest rates do not alter, the level of expenditure in the economy is not affected. Consequently, monetary policy under these circumstances is futile.
Keynes saw the 1930’s as a time when aggregate demand needed boosting – C+I+G+(X-M) – as the economy was in underemployment equilibrium. With the help of the multiplier, output and employment would increase – GDP. But with increased saving leading to reduced consumption and a fall in aggregate demand, a recession will worsen.
The fact that income must always move to the level where the flows of saving and investment are equal leads to one of the most important paradoxes in economics – the paradox of thrift. Keynes explains how, under certain circumstances, an attempt to increase savings may lead to a fall in total savings. Any attempt to save more which is not matched by an equal willingness to invest more will create a deficiency in demand – leakages (savings) will exceed injections (investment) and income will fall to a new equilibrium. In the graph below, the point of equilibrium is at E where the saving curve SS and investment curve II intersect each other. The level of income at equilibrium is OY and saving and Investment are equal at OH. When the aggregate saving increases, the saving curve shifts upwards from SS to S1S1. The new equilibrium point is E1 with OY1 level of income. Saving and investment are equal at point OT. As the level of saving increases, national income decreased from OY to OY1. Similarly, the volume of saving and investment also declined from OH to OT.
Negative Multiplier
People save more → spend less → another’s reduced income → negative multiplier → reduces demand → unemployment ↑ → incomes ↓ → AD↓ therefore planned increase in savings makes a recession worse.
Paradox of thrift and the GFC
The relevance of the paradox of thrift today is different from that during the Great Depression in the 1930’s. Back then consumers weren’t in as much debt as they are today and the government played a much smaller role in the economy with little or no welfare state to provide automatic stabilizers. Also the financial system wasn’t an interconnected as it is today and the financial engineering that evolved in the 2000’s allowed for the creation of instruments that had no real value to the economy – CDO and CDS. But after the GFC the expectations of consumers became very negative and as workers became fearful of losing their jobs what followed was an increase in savings as they wanted less exposure to debt, which negatively affected consumption.
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Over the last couple of decades property has been a significant driver of Chinese growth. The dependence on real estate is shown below and it is interesting to note that China was more dependent on housing construction than Ireland and Spain prior to the Global Financial Crisis.
Real estate related activities’ share of GDP by country, 1997-2017
Source: Rogoff and Yang
Real estate has impacted consumer spending, employment of workers, investment and demand for raw materials. Investment in property has increased by 5% of GDP in 1995 to 13% in 2019 – 70% of which was residential. As for household consumption 23% is spent on real estate. How do you work out the value of output for residential investment and is there a problem with double counting?
GDP andthe Output Approach
Gross domestic product (GDP) is defined as the value of output produced within the domestic boundaries of a country over a given period of time, usually a year. It includes the output of foreign owned firms that are located in that country, such as the majority of trading banks in the market. It does not include output of firms that are located abroad. There are three ways of calculating the value of GDP all of which should sum to the same amount since by identity:
NATIONAL OUTPUT = NATIONAL INCOME = NATIONAL EXPENDITURE
The output approach is the value of output produced by each of the productive sectors in the economy (primary, secondary and tertiary) using the concept of value added.
Value added is the increase in the value of a product at each successive stage of the production process. For example, if the raw materials and components used to make a car cost $16,000 and the final selling price of the car is $20,000, then the value added from the production process is $4,000. We use this approach to avoid the problems of double-counting the value of intermediate inputs. GDP will, therefore, be equal to the sum of each individual producer’s value added.
The Economist look at a simple example of calculating the output approach using a house. House is built and makes up the whole economy. It is made of steel which is made from iron ore.
House is sold – $1m Steel is sold – $600,000 Iron ore is sold – $500,00
How significant is the construction industry? As the builders add $400,000 to the value – 40% of GDP. But if the whole economy is the house is it 100% as the iron ore is an ingredient of the steel that is bought by the builder.
The Economist mention a paper by Kenneth Rogoff and Yuanchen Yang “Has China’s Housing Production Peaked?” in which they take a different view on calculating the value of property. They use the input-output total requirement matrix with the economy divided into 17 industries – manufacture of machinery, construction, transport etc. The coefficients indicate the production required directly and indirectly in each sector when the final demand for domestic production increases by one unit. By adding up the coefficients corresponding to the construction industry they found that 1 unit of increase in the construction sector requires 2.12 units of inputs from forward (other contractors) and backward (raw materials) industries. In breaking down the construction and installation as part of Chinese real estate, investment is RMB 7,630 bn. Thus 2.12 x 7,630 = RMB 16,176 which is the total value.
Therefore in the original option the Rogoff and Yang model would include the iron ore and not the value of the house or the $400,000 value added by the construction industry. Therefore:
Steel $600,000 + Iron ore $500,00 – $1.1m
There way of removing double counting is unusual as if you add the construction output $1m, steel output $600,000 and iron ore output $500,000 there is a double and triple counting:
x2 = Steel – counted twice – purchase of steel and when house is sold x3 = Iron ore – counted three times – purchased in raw material form, when used to produce steel and when house is sold.
The way that is normally talked about in textbooks is to only count the added value at each stage of production. Iron ore $500,000 + steel $100,000 + $400,000 construction costs – $1m = 100% of GDP in a one-house economy.
Sources: China & World Economy / 1–31, Vol. 29, No. 1, 2021. Has China’s Housing Production Peaked? Kenneth Rogoff, Yuanchen Yang
The Economist: Free Exchange – A universe of worry. November 27th 2021
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Supply chain disruptions and large fiscal deficits have been part of the cause of the inflationary problems that have been prevalent in the global economy. Increased aggregate demand from government spending accompanied by supply constraints have seen prices soar. The IMF blog looked at how we should go back on history and look at how globalisation in the past has offered an antidote to inflationary spirals.
In the 1970’s technology improved global supply chains with the introduction of the shipping container which reduced transport costs of goods. Policymakers like the former US Fed Chairman Alan Greenspan see the relationship between globalisation and innovation a transition to low inflation. This idea has been embraced by current Fed Chairman Jerome Powell who talks of not only technology but demographic factors that bring about sustained disinflation. Trade liberalisation had a part of play here with the role of the General Agreement on Tariffs and Trade (GATT) – now know as the World Trade Organisation (WTO) – providing the rules for much of world trade and presided over periods that saw some of the highest growth rates in international commerce – see graph.
Modern inflation targeting by central banks (1-3% in New Zealand) also brought inflation under control as countries established a process that would allow them to attract capital flows or to globalise further. New technologies will produce better growth and increase the potential capacity of the economy (Production Possibility Curve shifts to the right) but requires a lot of cross-border co-operation. Some countries pursue costly ‘friendshoring’ strategies of steering trade to friendly nations and regimes while attempting to hobble rivals. In particular big economies look to protect strategic vital and strategic resources thereby preventing global economic growth. All of this may seem an easy solution to tame inflation but the reality is there are many variables that influence the inflation figure within countries.
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Below is a very good video from CNBC that covers the main causes of recessions – overheated economy, asset bubbles and black swan events. Good analysis of soft and hard landings as well as the wage price spiral effect.
“History teaches us that recessions are inevitable,” said David Wessel, a senior fellow in economic studies at The Brookings Institution. “I think there are things we can do with a policy that makes recessions less likely or when they occur, less severe. We’ve learned a lot, but we haven’t learned enough to say that we’re never going to have another recession.” As the nation’s authority on monetary policies, the Federal Reserve plays a critical role in managing recessions. The Fed is currently attempting to avoid a recession by engineering what’s known as a “soft landing,” in which incremental interest rate hikes are used to curb inflation without pushing the economy into recession.
Below is a link to an interview with RBNZ Governor Adrian Orr on National Radio’s Morning Report last week. For those new to economics he explains the concept of supply and demand in layman’s terms with regard to inflation. Notice that he doesn’t mention the word ‘recession’ although talks of a couple of quarters of negative activity. As was predicted the RBNZ increased the OCR by 50 basis points to 4.75%.
Remember in 2012 the focus for inflation was given to 2% which is the mid-point in the 1-3% band. Later in 2018 an additional policy objective was added to maintain a maximum sustained employment. Worth a listen. Also below is a mindmap on monetary policy which might be useful.
Unit 9 of the new CAIE Economics course looks at national income and the 45 degree line graph. The graph below covers what you need to know and is one of the more complex graphs in the course. Aggregate expenditure shows the quantity of goods and services which households, firms and government are prepared to buy at different values of the general price level. The early classical economists believed that the size of the aggregate expenditure for output would be sufficient to employ everyone who wanted to work. John Maynard Keynes suggested that the achievement of a full and stable level of employment required the government to play an active part in determining the level of total expenditure. This policy known as demand management, was adopted by most governments in the post-war period. If a government is to manage aggregate demand effectively, it must be capable of influencing the components of aggregate demand i.e.. C+I+G+X-M. Government spending and taxation will be important instruments for this purpose, and by running budget deficits (spend more than they earn) or surpluses(spend less than they earn), the government can inject or withdraw purchasing power into or from the economy. Demand management policies were applied with considerable success in the two decades following the end of Second World War. Unemployment and inflation remained at very low levels throughout this period. However, these policies have proved to be much less successful since the mid-1960s.
The components of Aggregate Demand – AD = C + I + G + X – M
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Over the last 10 years a lot has been said about ‘Social Capital’ and its impact on the functioning of an economy. It has been argued that variations in social capital can account for differences in income levels, rates of economic growth, political involvement etc.
However, before going any further, what is social capital? There have been many explanations, nonetheless, the most widely used definition was first proposed in 1993 by Robert Putnam. It is as follows:
Social capital refers to ‘trust, norms and networks that shape the quality and quantity of a society’s social interactions’.
The majority of people would say that social capital is vital, as they would have a preference to live in a society where others can be trusted, where people are inclined to cooperate with each other, and where networks are all-embracing. Therefore, the trust variable impacts on the business investment and ultimately the country’s economy.
Recent research (Storonyanska et al. 2022) focuses on the area of trust and its positive effect on economic growth. Traditionally models (Robert Solow 1956) have focused on two ways in which to achieve higher GDP per capita growth – increased investment in business and improvements in productivity. Trust impacts these two processes (see mind map) – by boosting increasing long-term investment in fixed assets and productivity with reduced expenses, the economic value of a worker’s experience and skills and organisational improvement.
The lack of trust can make some investments too risky and countries with low trust levels usually invest in short-term projects. Investment in R&D requires a special trust as the future outcomes are sometimes very difficult to forecast. Therefore a lack of trust can direct investment into less ambitious projects, the implementation of which is easier to control. Instead, ambitious innovative projects generate increased demand for highly educated and productive employees and boost economic productivity in general. Trust can also add to productivity by decentralisation of decision making in organisations is among these mechanisms. Decentralised decision making allows using the capacity of employees that are “closer to the problem” to solve it faster.
Measuring trust The easiest way to measure social capital is to use the World Values Survey (http://www.worldvaluessurvey.org/ ) which addresses values and cultural changes in societies all over the world. The survey asks the question “Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people?” This question seeks to capture ‘generalised trust’, which is whether two randomly selected individuals can trust each other in their own country.
The relationship between trust and economic development (see fig below) is indirect proof of the benefit of its benefits. The trust data is taken from the WVS (2017-2021) and the level of economic development in the country – 2019. High level of trust is unique to Scandinavian countries and Northern Europe with high living standards, social stability, and consistent economic growth. However Estonia and Lithuania have turned out to be even higher (34% and 31.7%, respectively) than in prosperous France (26.3%) or Italy (26.6%). Going against the trend are China and Belarus which have higher levels of trust than countries with similar GDP per capita. The same goes for Singapore and Macau with very high levels of GDP per capital but much lower levels of trust compared to the trend line.
Trust and Developing Economies The study by Zak (2003) also illustrated that if trust is suitably low (below 30% for the average country in figure 1), then the investment rate will be so low that income will languish or even decline. Economists call this a ‘poverty trap’, and the primary reason for a poverty trap is ineffective legal structures that result in low levels of generalised trust, and therefore little investment. Additionally, the threshold level of trust necessary for positive economic growth is increasing in per capita income; that is, the poorer a country currently is, the more trust is required to generate sufficient investment to raise living standards. This makes the low-trust poverty trap difficult to escape from. However, researchers have examined the effects of social capital (trust) on income differences across villages in developing countries. It was established that where villages have higher levels of social capital they also have higher levels of income per capita.
The social philosopher John Stuart Mill wrote in 1848 that:
‘The advantage to mankind of being able to trust one another penetrates into every crevice and cranny of human life: the economical is perhaps the smallest part of it, yet even this is incalculable.’
Sources: Iryna Storonyanska, Olena Ivashko, and Elena Mieszajkina. Trust as a Catalyst of Economic Growth: A National and Regional Breakdown. 2022 Christian Bjornskov. Happiness in the Nordic World. 2021 Zak.P. Trust – Journal of Financial Transformation Vol. 7 April 2003
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Below is a useful graph from ANZ Bank which looks at the breakdown of components that make up GDP in New Zealand. The GDP of a country is made up of four things: C+I+G+(X-M).
C = Private Consumption
I = Business Investment
G = Government Consumption
(X-M) = Net Exports
Notice the movement in GDP over the years with the GFC in 2008 where exports revenue brought economic growth into positive territory. However up to 2020 it was private consumption that was the most prevalent with investment. COVID-19 saw a significant downturn with consumption and investment again helping GDP. Overall, domestic demand is set to get smaller, but the exports services such as education and tourism and less demand for imports should counterbalance the lack of domestic demand – see the graph. But the RBNZ has signaled that in order to get inflation down they need the domestic economy to experience a recession (two consecutive quarters of negative GDP) with private consumption falling significantly.
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Just covering the multiplier with my A2 and will be later with my NCEA Level 3 class. Think of the multiplier effect as a still pond. Women’s Football World Cup being held in Australia and New Zealand later this year – the direct impact of spending on the World Cup is like a stone hitting the water and creating ripples which will get smaller and smaller. With spectators coming to Auckland to watch a game they will make additional spending on accommodation, transport, food, tourist attractions etc. Where a hotel makes a lot of money form the event they may chose to extend the numbers of rooms which means they will have to employ contractors who will receive more income. The contractor might spend this additional income on a new vehicle for the business which then adds income to the car dealership – and it goes on with the ripples getting smaller and smaller.
Economic forecasters tend to use a simple formula to estimate the multiplier effect of sports event. They will estimate the number of spectators, how long they will stay and what they, on average, will spend whilst at the event.
Problems of forecasting Unrealistic projections of the number of visitors or their potential spending will lead to inaccurate multiplier effects. Factors that might overestimate the true economic impact of a sporting event. Substitution effect: this happens when the spending on a sporting event would have been spent elsewhere in the local economy and therefore doesn’t generate new economic activity. Crowding out: crowds and congestion may dissuade other economic activity from occurring. For example London Olympics 2012 590,000 visitors arrive in connection with the Olympics but the number of visitors fell by 1 million between summers of 2011 and 2012. Leakages: higher costs for restaurants, hotels etc associated with hosting the event doesn’t necessarily mean that employees working in those areas will be paid more. Also where there are guest workers from overseas the money is less likely to be recirculated. For some venues on the coast cruise ships have been used but this is only during the event.
Research into the impact of sporting events whether it would be the Champions League Final, World Cup, Olympic Games etc has found there is little short-run economic effect on the host city. The table above shows the research before and after sporting events with conflicting data. Some economists joke that if you really want to know what the true economic impact of a sporting event is, just take whatever number the promoters give you and then move the decimal point one place to the left.
Source: The Economics of Sport (2018) – M. Leeds, P. Von Allmen and V. Matheson
The theory behind the multiplier. Consider a $300 million increase in business capital investment. This will set off a chain reaction of increases in expenditures. Firms who produce the capital goods that are ultimately purchased will experience an increase in their incomes. If they in turn, collectively spend about 3/5 of that additional income, then $180m will be added to the incomes of others. At this point, total income has grown by ($300m + (0.6 x $300m). The sum will continue to increase as the producers of the additional goods and services realise an increase in their incomes, of which they in turn spend 60% on even more goods and services. The increase in total income will then be ($300m + (0.6 x $300m) + (0.6 x $180m). The process can continue indefinitely. But each time, the additional rise in spending and income is a fraction of the previous addition to the circular flow.
The value of the multiplier can be found by the equation 1 ÷ (1-MPC) You can also use the following formula which represents a four sector economy 1 ÷ MPS+MRT+MPM
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Below is an excellent video from German state broadcaster Deutsche Welle (DW). It outlines the decline in China’s GDP which is now at historic lows. DW look at the problems that have been building in China as for the first time in two decades, its output fell behind that of the rest of Asia. It also addresses the history of economic rise and the mountain of debt that it has accumulated. Add to that the demographic change and international threats. Below are some points from the video:
The draconian measures to contain COVID has sapped domestic consumption crippled small businesses and kept China’s factories closed.
The Chinese government has shielded its economy for years with infrastructure projects – building roads, dams, harbours, rail networks etc. It is the latter that is a good example of excess capacity and mounting financial losses – the network keeps growing even less populated locations where there isn’t much demand and now maintenance costs and interest payments have overtaken the railway’s income.
With the working population declining it is hard to maintain dynamic growth. Less workers puts pressure on wages and for China to maintain its cheap prices it has to improve productivity. Demographic change is a long-term phenomenon so the Chinese government still has room to respond and it has already switched to a three-child policy.
Also the demand for China’s exports has decreased as the global economy goes through an economic slowdown with surging inflation. Exports declines from 36% of GDP in 2006 to 20% in 2021 – see graph. Therefore more domestic consumption is needed to maintain growth and an expansionary fiscal policy like that in western economies might be the way to go.
With the recent World Cup in Qatar I thought I would share this post again on the Economics of Football. The David McWilliams podcast entitled ‘The Economics of Football’ in which he interviews Simon Kuper of Soccernomics fame, is particularly insightful. What he basically says is that the vast majority of clubs are not businesses and are not trying to make profits. They are pursuing trophies and with this intention spend what money they do make on buying the best players. If you look at the teams in the four English Divisions in 1921 there has been little change even when some clubs go bankrupt. As they are fan based institutions they seem to be unaffected by things like debt in a normal business. For example if a club (limited company) goes bankrupt you discard the old company and form a new limited company changing the name of the club (ABC City to ABC United) but playing at the same ground with the same strip etc. To put it in perspective a typical Premier League club is the size of a branch of IKEA.
Football clubs are huge emotional brands but not very big businesses. For example in 2019 Barcelona was the first club to made over $1bn in revenue but that equates to 0.02% of what Walmart made that year. The problem that football clubs have is how to monetise that passion for the club without affecting their fan base.
Bundesliga should be the richest league in Europe? When you look at the economic indicators of the German economy – population size, income levels, GDP growth etc – it should be the league with the most money. Why is this not the case? The German FA doesn’t want foreign money coming into their clubs like Chelsea, Manchester City, Paris Saint-Germain etc. Also the German Bundesliga has a rule that over 50% of a club must be controlled by its supporters.
New breed of foreign owners and European Super League The owners of Manchester United, Tottenham and Arsenal are more focused on making money out of the football club compared to others – Man City, Chelsea, PSG – whose owners want success at the expense of profit. This new breed of owner has come under a lot of pressure from the club’s supporters in that some are borrowing money to buy the club and then taking money out. Take for instance Man United – in the 5 years up to 2020, no owners in the Premier League have taken out more money than Man Utd £133m (dividends £112m, share buy back £21m). In stark contrast, some owners have put in significant funds: Everton £348m, Aston Villa £337m and Chelsea £255m – see graphic.
Source: SwissRamble
You can therefore see why some owners were keen on the European Super League. The proposed ESL was all but free-market capitalism with an American style franchise system with 12 teams guaranteed a place in the competition – significant barriers to entry and not conducive to competition. So much for Joseph Schumpeter’s creative destruction with a group of elite clubs protecting their market and the owners being rentier capitalists. The ESL’s proposed move is similar to what has been happening in the market place – a structure of businesses taking huge debt and taking little interest in competition as long as they are making money. Manchester United, probably the most famous club in the world, got knocked out of the Champions League in the group stage in 2021 but are still making a lot of money for the owners. It seems that the desire to win trophies has been superseded by profit – the proposed ESL avoids competition as member clubs are protected against the risk of failure. Not to say this is not already happening as the EPL and many other leagues in Europe are dominated by a small number of clubs which have significant funds available.
The Taylor Rule is a specific policy rule for fixing interest rates proposed by the Stanford University economist John Taylor. The rule is a formula for setting interest rates depending on changes in the inflation rate and economic growth.
A simplified formula is: r = p + 0.5y + 0.5 (p – 2) + 2 r = the short term interest rate in percentage terms per annum. p = the rate of inflation over the previous four quarters. y = the difference between real GDP from potential output. This assumes that target inflation is 2% and equilibrium real interest rate is 2%
Taylor argued that when:
Real Gross Domestic Product (GDP) = Potential Gross Domestic Product
Inflation = its target rate of 2%,
Federal Funds Rate (FFR) should be 4% (that is a 2% real interest rate).
If the real GDP rises 1% above potential GDP, then the FFR should be raised by 0.5%. If inflation rises 1% above its target rate of 2%, then the FFR should be raised by 1.5%. He stated that the real interest rates should be 1.5 times the inflation rate.
This rule has been suggested as one that could be adopted by other central banks – ECB, Bank of England, etc for setting official cash rates. However, the rule does embody an arbitrary 2% inflation target rather than, say 3% or 4%, and it may need to be amended to embody alternative inflation targets at different times or by different central banks. The advantages of having such as explicit interest rate rule is that its very transparency can create better conditions for business decisions and can help shape business people’s and consumers’ expectations. Central banks prefer to maintain an air of intelligent discretion over the conduct of their policies than to follow rules, but to some extent they do unwittingly follow a Taylor rule. This makes the rule a useful benchmark against which actual policies can be judged.
New Zealand and the Taylor rule When the Taylor Rule is applied to the New Zealand economy it suggests an optimal, OCR of more than 8% – see graphic from live gross domestic product (GDP) tracker. A rate as high as this would do significant damage to the economy even if inflation did get down to the 2% target for inflation. Households and businesses would find it particularly hard with incomes being squeezed. An OCR of this level would have an unwieldly impact on households and businesses, squeezing incomes.
Criticisms of Taylor rule The theory assumes that only the central bank can affect the equilibrium real rate of interest and there is a closed economy with households that have identical consumption patterns and the same declining marginal utility. However, an economy is a much more intricate machine which aims to allocate scarce resources to satisfy the utility of economic agents such as individuals, firms and government. The dominant model for many years has been “Dynamic Stochastic General Equilibrium” (DSGE) and it takes all the characteristics of an individual (this person is typically called the representative agent) which is then cloned and taken to represent the typical person in an economy. These agents make supposedly perfect decisions by optimising, working out the kinds of mathematical problems in an instant. This almost rules out any fluctuations in the natural rate that might arise from alterations in how individuals discount the future, from how consumption preferences may differ among individuals or alter over time for one individual, or from differences in the distribution of wealth.
With the global economy experiencing supply chain pressures, inflationary problems, higher interest and geopolitical tensions are we seeing a move to more regionalisation rather than globalisation?
Part of this change has come about from the decoupling of the American, European and Japanese economies from China. This ultimately alters trade and investment flows around the global economy and will mean lower economic growth and less liquidity. For instance consider the restrictions on technology including complex microchips being placed by the US on China. Janet Yellen the US Treasury secretary referred to ‘friendshoring’ which means relocating production to countries that fall within the US economic sphere of influence. Apple’s recent announcement that it would begin sourcing sophisticated chips from North America is the signal that many global firms have been waiting for to begin reducing their exposure to China.
Furthermore as well as the impact of decoupling of trade with China, a shortage of labour will also add to production costs and will result in slower rates of growth. Labour force participation rates have dropped as there have been less migrant workers coming into countries. This scarcity of labour will put further pressure on wages and ultimately inflation. To counteract the latter interest rates will continue to climb and this will lead to further problems:
The cost of financing economic expansion will become more expensive.
Firms that have lived off 0% interest rates and negative real rates (nominal interest rate – inflation) will face increasing problems on their balance sheets
In the medium term interest rates are determined by inflationary expectations and rates tend to move lower in periods of disinflation and higher in periods of inflation. The risk for all central banks and policymakers is if the rate of inflation goes above that of expectations there can be a further tightening cycle.
Response to shocks – GFC and COVID-19
The GFC and COVID-19 saw the primary policy response of an expansionary monetary policy (near 0% interest) due to insufficient aggregate demand. The result of this policy has changed the economic landscape. Today things are quite different:
insufficient aggregate supply,
persistent supply shocks,
higher inflation,
higher interest rates
slow growth.
After years of loose fiscal, monetary, and credit policies and major negative supply shocks, stagflationary pressures are now putting the squeeze on a massive mountain of public- and private-sector debt. Recession (negative GDP for two consecutive quarters) seems on the cards.
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Always been interested in the Nordic economies especially when you look at their standing in HDI and other indicators like happiness, trust and ease of doing business etc. There is a series of three books that looks at the fundamental features of these societies whether it be Equality, Economic Performance and Happiness – see image.
The Nordic countries rank amongst the best for equality in society. How is it possible that these economies are some of the richest and the most equal? Many people compare the Nordic model of equality to a bumblebee. The bumblebee tends to go against the laws of aerodynamics – a very big body with tiny wings. The Nordic countries model of inequality is very expensive but there is still economic growth in the economy. Carsten Jensen talks of 3 aspects of Nordic society that makes this possible.
The flexicurity system – flexibility and security. This is where employment regulation is fairly lenient (ability to make employees redundant) combined with a generous welfare programme The welfare support has two main aims: to protect against loss of income that come with losing your job and ensuring that you have the right skills to better fit the labour market. Should be noted that the government play an important role in the provision of free education at the tertiary level in Nordic countries. This leads to the golden triangle of flexicurity – flexible labour markets, training and retraining, and unemployment protection – see fig below.
The business friendly environment. The World Bank’s Ease of Doing Business Index ranks countries according to how conducive their regulatory environment is to establishing and running a company. In the 2020 Index Denmark were 4th, Norway 9th and Sweden 10th. However this does not imply that equality is somehow intrinsically good for a country’s commercial environment.
Social trust – this is important for growth as it make cooperation between individual citizens and companies easier. The lower transaction costs from social trust mean the environment is more conducive to investment from entrepreneurs and banks. Those countries that have less social trust spend more time and money on monitoring employees, other companies and consumers.
The topic Inequality on elearneconomics has fully integrated flash (cue) cards linked back to the key notes that assist students to understand economic vocabulary, improve their skills, develop knowledge and build their confidence.
Starting some CIE Economics revision courses this week. Here is a graphic that summarises production possibility curves. Usually the second multiple-choice question in the AS paper.
Martin Sandbu of the Financial Times in his Free Lunch on Film produced a very good video (see below) on how, with the help of technology, the global economy can be decarbonised without impacting on what is seen as normal growth rates. He travels to his native Norway where Oslo has around 30% of all its passenger cars being EV’s. The key to its success has been to make EV’s as affordable and attractive as conventional cars. Policies of tax exemptions on EV’s, lower tolls, cheaper parking and taxes on polluting vehicles have directed consumers to the cleaner option. He goes on to talk about the Kaya Identity. This is the relationship between four factors:
Global carbon dioxide emissions, in carbon dioxide (CO2);
Global primary energy consumption, in Ton of Oil Equivalent (TOE);
GDP, in dollars ($);
Global population, in billions.
In other words global CO2 emissions from a human source = global population x quality of life x energy intensity x intensity of carbon in the energy mix.
GDP/Per Capita: represents the total value of output in an economy divided by the population
Energy/GDP: represents the energy intensity, i.e. the amount of energy used (in kWh) necessary to create a monetary unit, meaning to manufacture a product or provide a service. This intends to encourage us to rationalise our use of energy.
CO2/energy: represents the intensity of carbon in the global energy mix. This relationship demands a reduction in CO2 emissions in the production of energy, in particular through the promotion of energies low in carbon, such as renewable energy.
So from Kaya we can decarbonise in 3 ways:
shrink the world’s population.
limit and reduce incomes.
lower the amount of CO2 emitted for each dollar of GDP.
In some areas, like ground transport, it’s technologically feasible, even easy, to take the carbon out. In other areas, it’s more costly, more difficult, maybe even impossible to do by 2050: flying, cement making, meat production. The video is well worth the time to watch.
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