Monopoly power – Luxottica and sunglasses

With summer approaching in the northern hemisphere and the days getting brighter you will be looking to don sunglasses on a more regular basis. Sunglasses come in various styles and brands, eg. Rayban, Oakley, Gucci, Prada, Versace to name but a few,  but can be quite expensive when you consider the so-called competition that is in the market which in theory should driving down the price. Sunglasses these days are reasonably homogeneous in that the frames and materials are very similar and it surprised me that 80% of the major sunglass brands are controlled by Luxottica, in a market that is worth US$28 billion.

Luxottica produced the following brands of sunglasses under their name:

Prada, Chanel, Dolce & Gabbana, Versace, Burberry, Ralph Lauren, Tiffany, Bulgari, Vogue, Persol, Coach, DKNY, Rayban, Oakley, Sunglasses Hut, LensCrafters, Oliver Peoples, Pearle Vision, Target Optical and Sears Optical.

This list of brands is fairly comprehensive and by controlling 80% of the market you have a monopoly and dictate the price consumers have to pay for each specific brand since the industry isn’t competitive. Therefore they are Price Makers. But Luxottica also dictate what goes in the shops as they own Sunglass hut, Oliver peoples and Pearle Vision where consumers shop for sunglasses. This makes it very difficult for a brand outside one that is produced by Luxottica to compete as you can’t get your product into those shops. So not only do they have a monopoly in the production but they also control the distribution of sunglasses. See monopoly graph below.

Although a few years old now, in the clip below from ’60 Minutes’ they mention Oakley’s dilemma when their sunglasses became more popular than those produced by Luxottica. When this happen Luxottica proceeded to hold fewer Oakely sunglasses in their Sunglass Hut shops causing Oakley’s stock to plunge. Then in 2007 Oakley was left with no choice but to merge with Luxottica.

US or China for Post Covid-19 financial dominance

Very informative video from The Economist with Matthieu Favas – Finance Correspondent – talking about the balance of power between the USA and China. The US didn’t show global leadership during the pandemic and China might fill the global vacuum that the US has left on the world stage. China has the second biggest bond market in the world and Covid-19 provided a rigorous test to suggest that people trust Chinese bonds. However there is a distrust of Chinese intentions and remember that Chinese officials covered up the spread of COVID-19.

Labour Market – notes for NCEA Level 2

Wage Rate:- The price of labour as determined by market supply and demand.
The demand for labour is said to be derived demand: – the demand for labour is dependent on the demand for the goods & services produced.
Key factors that affect the quantity of labour supplied:-

  • age of population
  • non-wage factors
  • wages
  • Difficulty in acquiring qualifications – eg. doctors
  • social attitudes to employment
  • discrimination

Change in Demand for labour Change in Supply of labour

Wages
A more realistic version of the market model measures the price of labour in real wages rather than in nominal or money wages. The difference is that nominal wages are the actual dollars that are paid for any job while real wages are a measure of the ability of those dollars (earnings) to buy goods and services. Therefore real wages consider the purchasing power of your income.

Sticky Wages
Actual wages will rise much more easily than they will fall. Labour markets are extremely rigid when it comes to reducing wage levels. Several factors encourage wages to stick at higher levels and so prevent the market from clearing, as shown in ‘Supply and Demand Applications’ and below.

Equilibrium and Real Wages

A = Employed B = Involuntary Unemployment C = Voluntary Unemployment

Some of these factors occur through the natural operation of the labour market.

  • Strong trade unions can operate as ‘monopoly suppliers’ of labour. This keeps wages above the equilibrium equilibrium. Fewer workers are hired.
  • Hiring cheap labour may backfire on employers. This labour may not have the same level of skills as that of the firm’s existing workforce. This will increase costs for the firm if it has to provide too much training. Existing workers therefore hold the balance of power and can demand higher wages.
  • The idea that a job has a certain worth, an intrinsic value regardless of the action of demand and supply, can keep wages above equilibrium.
  • The influence of humanity values can be strong. It is easy to pay less for resources other than labour.

Some factors are imposed on the market by the government.

  • Legislated minimum wages prevent the market from clearing. Although these wages aim to protect the incomes of those in the lower paid jobs, the result is fewer jobs for those same workers.
  • Welfare benefits can be over-generous and this may discourage the unemployed from seeking jobs.

Cost Benefit Analysis: mass testing for COVID-19

Paul Solman on PBS last week interviewed Nobel Prize winner Paul Romer about how the US should go about containing the virus and open up the economy. He is proposing mass testing the population every two weeks.

He states that each additional unit of testing frees up approximately 9 people who can go back to work. So how to does the cost of 1 test compare to 9 people being able to go back to work? He gives the example where the cost of 1 test each day of the year = $3,650 but the income generated by getting people back to work = $450,000 – these figures are approximate.

With this model he suggest that $100bn a year needs to be spent on testing which means 23 million tests per day or test the population every 14 days in the US. Worth a look.

Inequality set to be greater than previous shocks

Unemployment around the world is increasing at an alarming rate and one only needs to look at the USA to see the impact of COVID-19 on the rate. Today the number of people claiming benefit is 35 million which equates to 14.7% of the labour force. This is contrast to 3.5% in February this year. More jobs were lost during March than the whole of the GFC in 2008-2009.

Globally it is estimated that 200 million jobs will be lost in 2020 with about 40% of the global workforce in jobs that face a high risk of becoming obsolete – International Labour Organisation. These job losses worldwide will mean mean increasing inequality as the lower income groups more likely to experience unemployment and financial insecurities and therefore more vulnerable to labour market fluctuations resulting from macroeconomic changes. In reality a lot of people on low incomes live from week to week and when their pay suddenly stops the situation becomes desperate. A lot of the jobs that lower incomes do (in the service sector) have now gone with the closure of bars, restaurants, offices etc. Some still work in essential services like hospitals but are now in the front line and exposed to the virus. Research has shown that pandemics lead to a persistent and significant increase in the net Gini Coefficient measure of inequality – see graph below). Government support in a lot of economies has not protected those that are most vulnerable and COVID-19 could end up being a catalyst to increasing inequality more than other previous pandemic episodes.

What is the Gini Coefficient? The Gini Coefficient is derived from the same information used to create a Lorenz Curve. The co-efficient indicates the gap between two percentages: the percentage of population, and the percentage of income received by each percentage of the population. In order to calculate this you divide the area between the Lorenz Curve and the 45° line by the total area below the 45° line eg.

Area between the Lorenz Curve and the 45° line
Total area below the 45° line

The resulting number ranges between:
0 = perfect equality where say, 1% of the population = 1% of income, and
1 = maximum inequality where all the income of the economy is acquired by a single recipient.

The straight line (45° line) shows absolute equality of income. That is, 10% of the households earn 10% of income, 50% of households earn 50% of income.

A2 Eco: Micro – Long-Run Average Cost – Envelope Curve

Having covered the macro part of the course with my A2. I’ve made a start on productive and allocative efficiency. One concept that the course covers is the Long-Run Average Cost (LAC).

In the short run at least one factor of production is fixed but In the long run the firm can alter all of its inputs, using greater quantities of any of the factors of production. It is now operating on a larger scale. So all of the factors of production are variable in the long run. In the very long run, technological change can alter the way the entire production process is organised, including the nature of the products themselves. In a society with rapid technological progress this will shrink the time period between the short run and the long run.

The long-run average cost (LAC) curve shows the least costly combination of producing any particular quantity. The graph below shows short-run average costs (SATC) and the LAC. The LAC forms a tangent with the SATC and it is therefore the lowest possible average cost for each level of output where the factors of production are all variable – it is formed from a series of SATC curves. The diagram shows:

From the diagram A is the least-cost way to make output Q1 in the short run. B is the least-cost way to make an output Q2. It must be more costly to make Q2 using the wrong combination of factors of production, for example the quantity corresponding to point E. For the combination of factors of production at A, SATC1 shows the cost of producing each output, including Q2. Hence SATC1 must lie above LAC at every point except A, the output level for which the combination of factors of production is best

The LAC is a flatter U-shape than the SATC curves and can be explained by economies of scale and diseconomies of scale. However it is really important to note that the firm does not necessarily produce at the minimum point on each of its SATC curves. Thus the LAC curve shows the minimum average cost way to produce a given output when all factors can be varied, not the minimum average cost at which a given plant can produce.
Note:

The Long-Run Average Cost is sometimes abbreviated to LRAC
The Short-Run Average Cost is sometimes abbreviated to SRAC

This LAC is also know as the envelope curve (looks similar to the back of an old style envelope) – see image.

Source: Economics by Begg 7th Edition

Macroeconomic Policies – Mind map

Just covering macro policies / conflicts with my A2 Economics class and produced this mind map in OmniGraffle (Apple software). I found it a useful starting point for students to discuss the effectiveness of each policy and the conflicts within macro objectives. This is a very common essay question in CIE Paper 4.

My question would be what policies has the government in your country implemented since Covid-19 and how successful have they been in meeting macro economic objectives?

Adapted from Susan Grant – CIE AS and A Level Revision

Global remittances take a hit with Covid-19

Emerging economies have been affected in numerous ways by Covid-19. The following are just some:

  • Limited movement of their population
  • loss of export earnings
  • drop in foreign direct investment
  • fall in remittances.

Regarding the last one – the World Bank have estimated that global remittances will decline by 20% in 2020 – more than US$100bn – due to the Covid-19 pandemic and shutdown. There are expected to fall across the regions – see graph below:

In 2019 remittances reached a record US$554 billion but are estimated to be US$445bn in 2020. With the fall in foreign direct investment they have become even more important to low and middle income countries (LMIC). In 2019 remittances were greater than foreign direct investment and were the biggest source of capital in LMIC – 8.9% of GDP. This is especially prevalent when you consider that FDI is expected to plunge by more than 35% to LMIC in 2020.

The importance of remittances is also significant when pooling a poverty figures – it is estimated that a 10% increase in remittances reduces poverty by 3%.

A fall in remittances means:

  • less spending the economy as a whole
  • more people below the poverty line
  • more people unable to afford food, healthcare and basic needs

The World Bank estimate that in 2019 there were 272m international migrants of which 26m were refugees. As well there were in 700m migrants within a country providing financial support elsewhere. However with a downturn in the economy due to Covid-19 it is the foreign workers who are first to lose their job. 2021 might see a slight recovery with remittances set to rise by 5.6% to US$470bn but many things can eventuate over the next year.

A2 Economics – Wage Price Spiral and the Long Run Phillips Curve

Just covering this topic with my A2 class. Part of the CIE A2 macro syllabus focuses on the wage price spiral which relates to the Phillips Curve. Here are some excellent notes that I picked up from Russell Tillson in my early days teaching at Epsom College. As from previous posts, the Phillips Curve analysed data for money wages against the rate of unemployment over the period 1862-1958. Money wages and prices were seen to be strongly correlated, mainly because the former are the most significant costs of production. Hence the resulting curve purported to provide a “trade-off’ between inflation and unemployment – i.e. the government could ‘select’ its desired position on the curve.During the 1970’s higher rates of inflation than previously were associated with any given level of unemployment. It was generally considered that the whole curve had shifted right – i.e. to achieve full employment a higher rate of inflation than previously had to be accepted.

Milton Friedman’s expectations-augmented Phillips Curve denies the existence of any long-run trade off between inflation and unemployment. In short, attempts to reduce unemployment below its natural rate by fiscal reflation will succeed only at the cost of generating a wage-price spiral, as wages are quickly cancelled out by increases in prices.

Each time the government reflates the economy, a period of accelerating inflation will follow a temporary fall in unemployment as workers anticipate a future rise in inflation in their pay demands, and unemployment returns to its natural rate.

The process can be seen in the diagram below – a movement from A to B to C to D to E

Friedman thus concludes that the long-run Phillips Curve (LRPC) is vertical (at the natural rate of unemployment), and the following propositions emerge:

1. At the natural rate of unemployment, the rate of inflation will be constant (but not necessarily zero).

2. The rate of unemployment can only be maintained below its natural rate at the cost of accelerating inflation. (Reflation is doomed to failure).

3. Reduction in the rate of inflation requires deflation in the economy – i.e. unemployment must rise (in the short term at least) above its natural rate.

Some economists go still further, and argue that the natural rate has increased over time and that the LRPC slopes upwards to the right. If inflation is persistently higher in one country that elsewhere, the resulting loss of competitiveness reduces sales and destroys capacity. Hence inflation is seen to be a cause of higher inflation.

Rational expectations theorists deny Friedman’s view that reflation reduces unemployment even in the short-run. Since economic agents on average correctly predicted that the outcome of reflation will be higher inflation, higher money wages have no effect upon employment and the result of relations simply a movement up the LRPC to a higher level of inflation.

Moral hazard and Covid-19

Nobel Prize winning economist Paul Krugman defined moral hazard as:

Any situation in which one person makes the decision about how much risk to take, while someone else bears the cost if things go badly.

Companies exploiting moral hazard privatise the reward (they keep the profit) but socialise the risk (government bails them out if everything goes wrong)

Moral Hazard and the GFC
During the Great Depression more than 6000 American banks went bankrupt between 1930-33 and caused significant levels of unemployment. Learning from this event authorities believe that in future banks should be bailed out and this eventuated after the GFC in 2008. The main cause of the GFC was the sub-prime mortgage market where lenders faced a situation of moral hazard. Because the banks were taking on the risk the mortgage brokers, who sold the mortgages to the banks, didn’t really check whether the person taking on the mortgage could actually pay it back. Brokers were encourages to lie on the mortgage contracts about the income etc of their clients.

Moral Hazard and Covid-19
With corporate stimulus packages rolling out in most countries one wonders if there have been thorough enough checks on corporate behaviour. Issues like firing employees and bonuses to the top executives of companies have been prevalent in the past especially during the GFC. Then large businesses were favoured over small businesses. Today some of the wealthiest people made their money by borrowing from the banks to buy their own company shares in order to inflate its price. Following this they then sold their shares for a profit on the market. Now some of them are asking for bailouts as their company starts to struggle to survive. As well as government bailouts the central banks around the world have also engaged in the purchase of bonds and risky high-yielding debt. This is to ensure liquidity in the market but this intervention could shape how people perceive risk in the future and reward those institutions that behaved recklessly before the pandemic. Also more generous unemployment by the government might encourage people to be laid off and not seek work. However the time taken to minimise the moral hazard could have meant greater economic harm to the economy as a whole.