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.
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.
If you are studying the Growth unit at CIE or NCEA the image below – from the ‘Visual Capital’ site which is well worth a visit – is a good discussion starter for your class. It has an interactive chart where you can elect individual countries and look at the GDP per capita form 1820 to 2018. The graph below shows the major groups of countries with New Zealand added.
1800 – 80% of global population lived in extreme poverty
1975 – incomes were 10 times higher on average. Post WW2 growth was rapid as Europe etc rebuilt after the war.
2015 – incomes rose faster in developing countries with many lifted out of poverty. Between 1975 and 2015 saw the fastest decline in poverty.
In the 19th Century there was much more equal distribution of income across regions of the world – $1,100 per capita. Many lived below the poverty line but the world had less wealth. Today the GDP global average is approximately $15,212 but although there is more wealth the distribution is less equal.
At the highest end of the spectrum are Western and European countries. Strong economic growth, greater industrial output, and sufficient legal institutions have helped underpin higher GDP per capita numbers. Meanwhile, countries with the lowest average incomes have not seen the same levels of growth. This highlights that poverty, and economic prosperity, is heavily influenced by where one lives.
Sign up to elearneconomics for multiple choice test questions (many with coloured diagrams and models) and the reasoned answers on Real GDP. Immediate feedback and tracked results allow students to identify areas of strength and weakness vital for student-centred learning and understanding.
Below is a look at economic conditions in leading global economies. Unemployment is surprising low and with the rise in the cost of living (see inflation figures) this should put pressure on wages. The unemployment rate within the OECD area fell to 5.2% in February, the first time it has fallen below the pre-pandemic unemployment rate (which was recorded in February 2020). The unemployment rate within the OCED had peaked at 8.8% in April 2020.
Inflation, Unemployment and Interest Rates Annual inflation within the OECD area rose to 8.8% in March 2022, its highest annual increase since 1988. Energy prices have risen by over a third during the past year, while food prices have risen by ten percent within the OECD area. Most central banks have already commenced a tightening programme with the on-going threat of inflation. The Australian Reserve Bank commenced tightening their cash rate in early May, increasing the cash rate by 25 basis points to 0.35%. It is expected that the RBNZ will increase the OCR by 50 basis points next week.
Outlook If you look at conditions in the major economies you find the following:
China – limited growth potential with severe lockdowns
USA – higher interest rates could lead to a bust scenario
Euro Zone – cost of living crisis
Emerging markets – food crisis / famines.
With the indicators looking at recessionary conditions the best news for the global economy would be a withdrawal from Ukraine by Russian troops and an end to a zero-Covid strategy in China. These actions should reduce food and energy prices and therefore save government spending on raising benefits and subsidising food and energy. Economists are fairly optimistic that we will avoid a recession in 2022 as they still have the tools to stimulate if things get worse. However with no end in sight for the Ukraine conflict and interest rates on the rise a recession is on the cards.
Sign up to elearneconomics for multiple choice test questions (many with coloured diagrams and models) and the reasoned answers on Inflation and Unemployment. Immediate feedback and tracked results allow students to identify areas of strength and weakness vital for student-centred learning and understanding.
I came across this graphic by Bruce Mehlman in ‘Thoughts from the frontline’ from Mauldin Economics. It looks at the change that was already evident before COVID-19 and the war in the Ukraine but have accelerated because of these events. The tailwinds for 30 years since the fall of the Berlin Wall are starting to slow/stop and it seems that there are now headwinds rising and reversing the process. The trust element in the global economy is probably at all time low and survey data between 1979 and 2021 saw that the military gain trust. All others—media, religion, courts, schools, labor, business, Congress—lost much and sometimes most of their credibility since then.
However in times crisis humanity can usually conjure up accelerating innovation and change: faster productivity, entrepreneurship, smarter healthcare, and a transition to next-generation energy sources.
Just starting to go through this part of the course with my A2 class and came across a table from some old A Level notes produced by an ex-colleague Russell Tillson (ex Epsom College Economics and Politics Department) to help them understand the principal differences.
Here is a really funny video by the students of Columbia Business School (CBS) – you may have seen it before but I find it very useful when you start teaching monetary policy and interest rates.
Back in 2006 Alan Greenspan vacated the role of chairman of the US Federal Reserve and the two main candidates for the job were Ben Bernanke and Glenn Hubbard. Glen Hubbard was (and still is) the Dean at Columbia Business School and was no doubt disappointed about losing out to Ben Bernanke. His students obviously felt a certain amount of sympathy for him and used the song “Every Breath You Take” by The Police to voice their opinion as to who should have got the job. They have altered the lyrics and the lead singer plays Glenn Hubbard.
Some significant economic words in it are: – interest rates, stagflate, inflate, bps, jobs, growth etc.
Below is a useful flow diagram from the ANZ bank which adds Large Scale Asset Purchases (LSAP) and Funding for Lending Programme (FLP) to the Official Cash Rate (OCR – Base Rate)
LSAP – this is the buying of up $100 billion of government bonds – quantitative easing FLP – this gives banks cheap lending based on the Official Cash Rate – could be about $28 billion based on take up OCR – wholesale interest rate currently at 0.75%. Commercial banks borrow at 0.5% above OCR and can save at the Reserve Bank of New Zealand (RBNZ) at 1% below OCR.
With FLP and more LSAP this will mean lower lending rates and deposit rates. This should provide more stimulus in the economy and allay fears of future funding constraints making banks more confident about lending. Add to this a third stimulus – an OCR of 0.75%. Although there is currently a tightening policy the rate is probably still stimulatory. The flow chart shows the impact that these three stimulus policies have on a variety of variables including – exchange rates – inflation -unemployment – consumer spending – investment – GDP. Very useful for a class discussion on the monetary policy mechanism.
For more on Monetary Policy view the key notes (accompanied by fully coloured diagrams/models) on elearneconomics that will assist students to understand concepts and terms for external examinations, assignments or topic tests.
Been covering this topic with my A2 Economics class. Below is a recent video from Venezuela outlining the size of the informal sector. It is estimated that 50% of the workforce make some sort of living from selling items on the street usually for US$. This explains one of the limitations of GDP as a measurement of a country’s standard of living.
The informal economy is generally associated with low productivity, poverty, high unemployment, and slower economic growth. It is also more prevalent in low-income countries because as countries develop, the easier it is for workers to transition to the formal sector. At the same time, it provides employment and income to people who would otherwise not find employment, or it supplements their income from employment in the formal, regulated sector. IMF The Global Informal Economy: Large but On The Decline. 30-10-19
Sign up to elearneconomics for multiple choice test questions (many with coloured diagrams and models) and the reasoned answers on GDP and its limitations. Immediate feedback and tracked results allow students to identify areas of strength and weakness vital for student-centred learning and understanding.
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.
For more on Inequality view the key notes (accompanied by fully coloured diagrams/models) on elearneconomics that will assist students to understand concepts and terms for external examinations, assignments or topic tests.
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
This video about the book ‘Limits’ is useful when teaching the CIE A2 course Unit 4. It looks at the problem of unlimited wants and needs versus finite resources and the need for limits in society. With countries addiction to GDP growth, limits can enhance greater freedom.
This book reclaims, redefines, and makes an impassioned plea for limits – a notion central to environmentalism – clearing them from their association with Malthusianism and the ideology and politics that go along with it.
Very good FT video with Martin Sandbu and James Kynge discussing the fact that although the Chinese economy has grown at an alarming rate over the last 40 years, will it become the global superpower? Some of the main points:
Global economy is now becoming more regionalised
From 1979 to 2018 China’s GDP growth rate averaged 9.5%
2,000 years ago everyone was poor – centre of gravity of global economy followed population size
Key change in the mid ’90s, when China began to allow the sons and daughters of farmers to migrate from the village to these big factory towns.
Liberalised global trade in 1980’s helped China access markets
China still very much a developing nations – ranks 61st in terms average per-capita income but got an excellent infrastructure.
China’s middle class approx 400m but that means approx 1bn of the population are poor
Middle income trap – getting from poor to middle income is a very different process from getting to middle income to high income.
Economy needs to change from a growth model based on accumulating labour and capital to a growth model led by technological development and technological progress.
China is either a global leader or at least close to the cutting edge, wind and solar power, online payment systems, digital currencies, aspects of artificial intelligence, 5G telecoms, drones, ultra-high-voltage power transmission.
Three major trading hubs – EU, US and China – with trade being more regionalised. China reluctant to lose export markets in EU and US as they are big drivers of exports
Three trading blocs will lead to protectionism and decoupling of supply chains. unless the EU, the US, and China can sort out their differences.
The ANZ Truckometer is a set of two economic indicators derived using traffic volume data from around the country. Traffic flows are a real-time and real-world proxy for economic activity –particularly for the New Zealand economy, where a large proportion of freight is moved by road. It represents an extremely timely barometer of economic momentum.
Heavy traffic is the more useful indicator in these strange times. Over Q4 as a whole the index was up 5.3%. As figure 3 (over) shows, this is consistent with our early Q4 GDP pick for a 2.5% increase (heavy traffic moves roughly twice as much as GDP). This represents a partial bounce-back from the lockdown-induced 3.7% fall in GDP in Q3.
Really enjoyed the David McWilliams podcast entitled ‘The Economics of Football’ in which he interviews Simon Kuper of Soccernomics fame. 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.
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.
Recently published by Stats NZ was the Tourism satellite account which presents information on tourism’s contribution to the New Zealand economy in terms of expenditure and employment. The March 2021 data is significant as it captures the impact of COVID-19 on the sector. As expected the international spending was down by 91.5% from the previous year with the total spend falling by 37.3%.
The table and graph below show the drop off of international tourism in 2021. Domestic tourism did increase by 2.6% but was never going to absorb the drop in international spending of $16,195m.
Over the same period direct employment in tourism fell by 33.1% from 218,580 full-time employees to 146,295.
Tourism – direct contribution to GDP 2020 – $16.2bn – 5.5% of GDP 2021 – $8.5bn – 2.9% of GDP
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
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 – $1m = 100% of GDP in a one-house economy.
Sources: China & World Economy / 1–31, Vol. 29, No. 1, 2021. Has China’s Housing Production Peaked? Kenneth Rogoff, Yuanchen Yang
The Economist: Free Exchange – A universe of worry. November 27th 2021
Sustainable development is part of the CIE A2 Economic Syllabus and greenhouse emissions are significant barrier in trying to achieve specific goals. Sustainable Development Goals (SDG) requires a collective agreement and to advance towards a society which is more respectful of the environment, whilst at the same time working towards economic growth and sustainable development. Kaya identity tries to explain the relationship between four factors:
Global carbon dioxide emissions, in carbon dioxide (CO2);
Global primary energy consumption, in Ton of Oil Equivalent (TOE);
GDP, in dollars ($);
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. See the formula below:
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.
The focus from government and the private sector in reducing climate change has been on two of the four factors: Global carbon dioxide emissions, in carbon dioxide (CO2) and Global primary energy consumption, in Ton of Oil Equivalent (TOE). However should there be more emphasis on the other two: GDP and Global population? GDP can be influenced by government policy but there are political dangers if going down this avenue. Firstly by reducing growth you may limit the creation of jobs and the advancement of economies. Secondly developing economies depend on the demand from developed world to drive them out of poverty. Limiting population growth is not a policy that government’s can respectably push towards. Ultimately the global economy needs more than a power source without emissions but investment and innovation which can reverse the damage that emissions have already done. Below is an informative video on carbon markets from The Economist.
If you look at the housing data over the last 15 years it has been a bit of a rollercoaster. The boom period of the early 2000’s saw significant increases in the house prices which was sharply curtailed by the Global Financial Crisis in 2008. Following the GFC the RBNZ embarked on an expansionary monetary policy with near zero level interest rates which saw rebound in house prices up to 2016. However up to 2018 price increases start to plateau as the economy entered a phase of slower growth with average household debts reaching 162% of their disposable income and this debt-fuelled growth proved unsustainable.
Since the first lockdown in 2020 prices have escalated and this could be partly due to the fact that as well as demand outstripping supply, people have spent more income on refurbishing their house for a future sale. This came about by their inability to spend money on holidays or overseas trips. So why is there a forecast of decreasing and even negative house price increase? Below are some reasons:
Increase in official cash rate (OCR) from the RBNZ will be passed onto consumers – higher mortgage rates – see graph below showing the correlation between interest rates and house prices.
The tightening of lending regulations by the RBNZ – debt-to-income limits on mortgage lending.
With the borders being closed population growth has decreased significantly and therefore less demand.
There is less of a financial incentive for developers as material and labour costs have risen rapidly. Also a cooling housing market could lead to fewer projects.
A good example of the output gap from the RBNZ Monetary Policy Statement last week – see graph above. There are strong capacity pressures which are the result of the unleashing of domestic demand and supply chain disruptions. Although the latter has increased it is presently unable to keep up with the the overall aggregate demand of the economy and subsequently this has driven inflation up to 4.9% above the 1 to 3% remit target band.
With unemployment at 3.4% and *underutilisation of 9.2%, annual employment growth of 4.3% (September 2021) cannot be maintained with this pressure on the labour market. There has been strong demand for more workers in some sectors, but it has been difficult for businesses to recruit extra staff. This has seen wages rise as firms compete for workers. However it is important to remember that on 29th October there were still 1,282,152 jobs being supported by a wage subsidy. A total of NZ$3,719.7 million had been paid via the COVID-19 Wage Subsidy August 2021. With the continued demand for labour, wage pressure and salary costs are expected to increase. Consequently a rising unemployment rate could be evident.
*underutilisation – measures spare capacity in New Zealand’s labour market. People do not have a job, but are available to work and are actively seeking employment
Notes on the output gap
If there is no long-term trade-off, low inflation does not permanently choke growth. Moreover, by keeping inflation low and stable, a central bank, in effect, stabilises output and jobs. In the graph below the straight line represents the growth in output that the economy can sustain over the long run; the wavy line represents actual output. When the economy is producing below potential (ie, unemployment is above the NAIRU), at point A, inflation will fall until the “output gap” is eliminated. When output is above potential, at point B, inflation will rise for as long as demand is above capacity. If inflation is falling (point A), then a central bank will cut interest rates, helping to boost growth in output and jobs; when inflation is rising (point B), it will raise interest rates, dampening down growth. Thus if monetary policy focuses on keeping inflation low and stable, it will automatically help to stabilise employment and growth.