Category Archives: Labour Market

A2 Economics – Marginal Revenue Product Theory

Marginal Revenue Product of Labour

Marginal revenue productivity (MRPL) is a theory of wages where workers are paid the value of their marginal revenue product to the firm.

The MRP theory outlined below is based on the assumption of a perfectly competitive labour market and the theory rests on a number of key assumptions that realistically are unlikely to exist in the real world. Most labour markets are imperfect, one of the reasons for earnings differentials between occupations which we explore a little later on.

  • Workers are homogeneous in terms of their ability and productivity
  • Firms have no buying power when demanding workers (i.e. they have no monopsony power)
  • There are no trade unions (the possible impact on unions on wage determination is considered later)
  • The productivity of each worker can be clearly and objectively measured and the value of output can be calculated
  • The industry supply of labour is assumed to be perfectly elastic. Workers are occupationally and geographically mobile and can be hired at a constant wage rate

Marginal Revenue Product (MRPL) measures the change in total output revenue for a firm as a result of selling the extra output produced by additional workers employed. A straightforward way of calculating the marginal revenue product of labour is as follows:

MRPL = Marginal Physical Product x Price of Output per unit

Therefore the MRP curve represents the firm’s demand for labour curve and the profit maximising condition is where:

MRPL = MCL (Marginal Cost of Labour) where the revenue generating by employing an additional worker (MRPL) = the cost of employing an additional worker (MCL).

Mind Map below adapted from Susan Grant’s book CIE A Level Revision Guide

RNBZ can’t seriously be thinking about reducing the OCR

Today’s labour market data showed a drop in unemployment from 4.4% to 3.9% and an employment rate of 68.3% the highest since the HLFS survey was first reported in 1986. The
unemployment rate of 3.9% is the lowest since June 2008 and towards the lowest bound of the RBNZs estimated 4% to 5.5% range for the Non-Accelerating Inflation Rate of Unemployment (NAIRU). See graph below:

Tomorrow the RBNZ present their November Monetary Policy Statement (MPS) and these figures give them limited time to change any policy direction. Remember that the RBNZ is now tasked “supporting maximum sustainable employment within the economy” alongside its price stability mandate of 1-3% CPI with a target of 2%. However these figures seem to suggest that further easing is not required to meet employment objectives.

What is the Natural Rate of Unemployment?

The natural rate of unemployment is the difference between those who would like a job at the current wage rate – and those who are willing and able to take a job. In the above diagram, it is the level (Q2-Q1).

Source: economicshelp.org

The natural rate of unemployment will therefore include:
Frictional unemployment – those people in-between jobs
Structural unemployment – those people that don’t have the skills that fit the jobs that are available.

It is also referred to as the Non-Accelerating Inflation Rate of Unemployment (NAIRU) – the job market neither pushes up inflation nor holds it back.

Source: BNZ – Economy Watch – 7th November 2018

Shorter hours, higher productivity and yoga

According to surveys today’s millennial job applicants don’t want to work all hours – it seems that younger workers place a work-life balance ahead of career progression. During the GFC an applicant who asked a prospective employer about leaving work early on a Friday to go to yoga wasn’t taken seriously. However with the global economy growing at its fastest rate since 2011, qualified jobseekers are scarce so workers can start to make demands.

IG Metall – Germany’s biggest trade union – struck a deal that allows members to work 28-hour weeks for up to 2 years, typically when they have small children. Although Germany is unique, other national economies might follow suit if they have a limited supply of workers. It is important to note that in boom times the substitution effect comes into play as more people want to substitute money for leisure time – this is shown by the backward bending supply curve of labour. In most A2 courses income and substitution effects are examined. The textbook identifies each as follows:

Income effect – higher real wages might persuade people to work less hours and enjoy extended leisure time (see graph – SS2).

Substitution effect – people have an incentive to work extra hours because the financial rewards of working are raised, and the opportunity cost of not working has increased (see graph – SS1).

Work-life balance is typically discussed as a personal issue and again Germany has been leading the way:

1960 – average West German working year = 2,163 hours
2018 – average German working year = 1,363 hours

Furthermore once they leave work in the mid afternoon a lot of them are actually free of the office and more importantly emails. Daimler automatically erase emails to employees who are on holiday.

Workaholic countries slowing down

Countries that are renowned for working long hour – South Korea, China and Thailand – have already limited school homework. South Korea wants to reduce average annual working hours to less that 1,800 from 2,069 in 2016 – the most for any OECD high-income country.

Average wages are not above pre-crisis levels in all developed countries except the UK and Greece. The eurozone’s jobless rate is the lowest and US wage growth the fastest since 2009. Shorter hours won’t help the poorest paid workers, who can’t afford to work less but for the broad middle in rich countries a new working life is emerging. It could look like Germany – shorter workdays, high productivity and yoga.

Source: Why the 30-hour week is almost here – Simon Kuper – FT Magazine February 15 2018

The NAIRU in New Zealand

Below is an extract from a RBNZ paper from March this year on Estimating the NAIRU and the Natural Rate of Unemployment. Especially useful for A2 students.


The headline unemployment rate in New Zealand has been trending down over time. This fall in the unemployment rate has not been accompanied by a rise in inflation, suggesting that the underlying natural rate and the NAIRU may have also declined through time. In this section, we document some of the changes in the New Zealand economy that have influenced the unemployment rate over history.

As a first step, we disaggregate the unemployment rate into three sub-components as follows:

a. Cyclical unemployment results from changes in aggregate demand conditions over the course of a business cycle. As firms experience weaker demand, existing workers may be laid off and fewer new workers will be hired.
b. Frictional unemployment refers to the regular short-term churn in the labour market, both within, and in and out of, the labour force. It is determined by the efficiency of the matching process given the diversity of job-seekers and vacancies.
c. Structural unemployment represents a more fundamental mismatch between those hiring and job seekers given their skills and geographic location. This could arise from long-lasting changes in the structure of the economy such as socio-demographic trends, technological change, or a rapid change in the mix of industries.

The lines between these categorisations can be indistinct. For example, some argue that a prolonged period of cyclical unemployment could also lead to hysteresis effects that could spill over to structural unemployment. For example, an extended period of unemployment may lead to an erosion of human capital making workers less attractive to employers and hence reducing their bargaining power. In principle, frictional unemployment and structural unemployment should be captured by the trend in the NAIRU or the natural rate, as both forms of unemployment may continue to exist even if the labour market is in equilibrium. This is because those that are structurally unemployed may not be easily drawn back into employment despite an increase in labour demand and an upward adjustment in wages. In addition, the level of frictional unemployment is largely determined by the efficiency with which potential workers and employers can find jobs. In contrast, cyclical unemployment captures when the labour market may be operating below capacity as a result of a shortfall in demand.

Monetary policy has little influence over the level of frictional and structural employment. These are largely determined by the evolution of technology and the obsolescence of skills, and by structural policies to facilitate the acquisition of new skills and improve the match between employers and job-seekers. For example, policies that affect the cost of hiring (e.g. employment protection laws), the incentives for job finding (e.g. unemployment insurance), or the bargaining power of workers (unionisation and labour contract laws).

In Figure 3, we decompose the pool of unemployed workers on the basis of unemployment durations. In particular, we categorise those who have been unemployed for less than 4 weeks as contributing to frictional unemployment, 4 to 52 weeks as cyclical unemployment, and greater than 52 weeks as structural unemployment.

New Zealand’s Phillips Curve 1993-2017

Bill Phillips (a New Zealander) discovered a stable relationship between the rate of inflation (of wages, to be precise) and unemployment in Britain from the 1850’s to 1960’s. Higher inflation, it seemed, went with lower unemployment. To economists and policymakers this presented a tempting trade-off: lower unemployment could be bought at the price of a bit more inflation. The downward-sloping Phillips curve is apparent in the graph below which plots core inflation against headline unemployment for New Zealand.

There has been also an apparent shift inwards of this relationship where lower rates of unemployment have become possible for a given level of inflation, particularly relative to the 1990s. The simple plot in the graph does not take into account other factors such as changes in import prices, inflationary expectations and capacity constraints which also have the potential to shift the Phillips Curve. These are discussed further below:

1. The price of imports. As the price of imports increase whether it is raw materials or finished products, the price of local goods become more expensive which increase the general price level. Also if a country finds that its exchange rate depreciates the price of imports rises. Oil is a very inelastic import and with a barrel of oil below $30 in 2016 there was little pressure on the CPI. Where inflation has been higher is in those countries that have withdrawn price subsidies and also had sharply falling currencies – Argentina 24% and Egypt 32%.

2. Public Expectations. In recent years more attention has been paid to the psychological effects which rising prices have on people’s behaviour. The various groups which make up the economy, acting in their own self-interest, will actually cause inflation to rise faster than otherwise would be the case if they believe rising prices are set to continue.

Workers, who have tended to get wage rises to ‘catch up’ with previous price increases, will attempt to gain a little extra compensate them for the expected further inflation, especially if they cannot negotiate wage increases for another year. Consumers, in belief that prices will keep rising, buy now to beat the price rises, but this extra buying adds to demand pressures on prices. In a country such as New Zealand’s before the 1990’s, with the absence of competition in many sectors of the economy, this behaviour reinforces inflationary pressures. ‘Breaking the inflationary cycle’ is an important part of permanently reducing inflation. If people believe prices will remain stable, they won’t, for example, buy land and property as a speculation to protect themselves. In Japan firms and employees have become conditioned to expect a lower rate of inflation. Prime minister Shinzo Abe has called for companies to raise wages by 3% to try and kick start inflation.

3. Capacity pressures. This refers to how much ‘slack’ there is in the economy or the ability to increase total output. If capacity pressures are tight that means an economy will find it difficult to increase output so there will be more pressure on prices as goods become more scarce. Unemployment is the most used gauge to measure the slack in the economy and as the economy approached full employment the scarcity of workers should push up the price pf labour – wages. With increasing costs for the firm it is usual for them to increase their prices for the consumer and therefore increasing the CPI. However many labour markets around the world (especially Japan and the USA) have been very tight but there is little sign of inflation. This assumes that the Phillips curve (trade-off between inflation and unemployment) has become less steep. Research by Olivier Blanchard found that a drop in the unemployment rate in the US has less than a third as much power to raise inflation as it did in the mid 1970’s.

This flatter Phillips curve suggests that the cost for central banks in higher inflation of delaying interest-rate rises is rather low.

Wages in the English Premier League – Demand-Pull Inflation

You are no doubt are well aware of the staggering wages that the English Premier League player receive especially when you consider other occupations.

What ultimately the salary explosion has been driven by the huge amounts of money that is now at the disposable of some of the top clubs. In economics this refers to the concept of demand-pull inflation where the supply has not kept apace with the demand for world-class players. Below is graph showing both demand-pull and cost-push.

Volvo Ocean Race and the Multiplier Effect.

I am quite an avid watcher of the Volvo Ocean Race with the daily race updates and the excellent graphics on their website – currently they are in Auckland before setting sail for Itajaí in Brazil. Most days they have news on the current positions of the yachts and who has made gains and losses in the last 24 hours. A recent race update dealt with the economic impact that the race has had on the Spanish economy and it just happens that I am covering the multiplier with my A2 Economics class.

The Multiplier Explained

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

Source: CIE Revision Guide by Susan Grant

Impact of Volvo Ocean Race on Spanish Economy

PriceWaterhouseCoopers (PwC) conducted a study measuring the impact of the Volvo Ocean Race on the Region of Valencia and Spain. Some their findings are:

  • The impact in the Region of Valencia has grown to 68.6 million euros in GDP and 1,270 full-time equivalent jobs.
  • Hotels, restaurants and local business were the sectors to benefit the most.
  • Alicante received 345,602 visitors from October 11 to 22, 2017, (10.3% more than in 2014-15 and 17.6% more than in 2011-12).
  • The Volvo Ocean Race had a significant positive effect on national tax revenue, adding more than 41 million euros.
  • The media value directly linked to coverage mentioning the Alicante brand over the period of the race start exceeds 36 million euros.

The Volvo Ocean Race 2017-18 has added 96.2 million euros to the Spanish Gross Domestic Product (GDP), an increase of 7.6% over the 2014-15 edition. The race also generated the equivalent of 1,700 full time jobs in Spain, according to an economic impact study delivered by PriceWaterhouseCoopers (PwC) measuring the impact of the Volvo Ocean Race on the Region of Valencia and Spain.

The impact in the Region of Valencia grew to 68.6 million euros of GDP, a 3.3% increase on the 2014-15 edition. The sectors of activity that benefited the most were local businesses and restaurants, each by more than 10 million euros. In terms of employment, the equivalent of 1,270 full-time jobs were generated, a figure similar to the last edition.

The PwC study estimates a positive effect on tax collection in Spain of more than 41 million euros as a result of an increase in economic activity and employment generated by the Volvo Ocean Race 2017-18.

The actual value of the multiplier is not mentioned in the report but from all accounts the Volvo Ocean Race has had a very positive impact on Valencia.

Is the Natural Rate of Unemployment in the US lower than economists think?

The natural rate of unemployment is the difference between those who would like a job at the current wage rate – and those who are willing and able to take a job. In the above diagram, it is the level (Q2-Q1).

Source: economicshelp.org

The natural rate of unemployment will therefore include:
Frictional unemployment – those people in-between jobs
Structural unemployment – those people that don’t have the skills that fit the jobs that are available.

It is also referred to as the Non-Accelerating Inflation Rate of Unemployment (NAIRU) – the job market neither pushes up inflation nor holds it back.

US Labour Market – tight but little wage growth.

The recent (February 2018) US Federal Reserve Monetary Policy Report stated that the US labour market appears to be near or a little beyond full employment. In theory this should suggest major labour shortages which ultimately end in higher wages for workers. Although employers report having more difficulties finding qualified workers, hiring continues apace, and serious labour shortages would likely have brought about larger wage increases than have been evident to date. The unemployment rate appears to be below most estimates of the natural rate.

January US unemployment rate = 4.1%
Congressional Budget Office’s (CBO) current estimate of the natural rate = 4.6%

The Unemployment Gap


The unemployment rate gap is the unemployment rate minus the CBO’s estimate of the natural rate of unemployment. The shaded bars indicate periods of business recession.

The median of Federal Open Market Committee (FOMC) participants’ estimates of the longer-run normal rate of unemployment and the CBO’s estimate of the natural rate of unemployment have both been revised down by about 1% over the past few years, one indication of the substantial uncertainty surrounding estimates of the “full employment” rate of unemployment.

The US Fed have suggested that with many advanced economies experiencing such low inflation that more persistent factors may be restraining price growth therefore the NRU could be lower in some countries than many economists think. Prices in many industries have been subdued due to technological changes – internet shopping which allows easy comparison – which restricts businesses ability to demand higher prices.

What could be the reasons for less wage growth?

• Employees need less compensation as the inflation rate has been low
• An increase in part-time employment
• Spare capacity in the labour market
• Employees keen on job security so put less emphasis on wage bargaining
• Increasing number of people participating in the labour force.
• Shorter working week
• Ageing and declining working age population

Although in the US there have been labour shortages in some areas of the economy, this hasn’t flowed through into the aggregate labour market. However speculation of higher inflationary pressure through higher wages has alerted markets that the US Fed may increase interest rates although they will remain reluctant to tighten too aggressively.

Source: US Federal Reserve Monetary Policy Report – February 2018.

Full v Fulfilling Employment

Just going through the Natural Rate of Unemployment with my A2 class and I remembered a post I did last year. Free Exchange in The Economist had an article which looked at the change in terminology used by Janet Yellen ex-chairman of the Federal Reserve. In a statement last year she alluded to the US economy near maximum employment and that rate rises could ensue. However only 69% of American adults have a job.

Full employment has normally been the concept that has been used to describe a situation where there is no cyclical or deficient-demand unemployment, but unemployment does exist as allowances must be made for frictional unemployment and seasonal factors – also referred to as the natural rate of unemployment or Non-Accelerating Inflation Rate of Unemployment (NAIRU). If a central bank wishes to stimulate demand below this level there is the concern that inflation will increase therefore they take a guess as to what is the natural rate of unemployment – the lowest rate of unemployment where prices don’t accelerate. Maximum unemployment is the same in that it refers to the labour market being as tight as it can be without increasing prices. Natural rates in the US have varied – around 5.3% in 1950 and then peaking at 6.3% in the stagflation period before falling 4.9% in 2008 and then rising to 5.1% after the GFC, see graph below.

NRU and its causes

The NRU mainly depends on the level of frictional unemployment – defined as those who are in between jobs. This number can vary as at different times of the business cycle as there can be a delay in matching those looking for work with the vacancies themselves – a mismatch sometimes referred to as Structural Unemployment. The increase in frictional unemployment in the 1970’s and 80’s was largely due to the decline in manufacturing jobs with the advent of automation and more right wing policies (Reagan and Thatcher). Workers would stay unemployed in the hope that good high paid manufacturing jobs would reappear.

Unions can also influence the NRU with protecting workers jobs and pushing up wages so that employers find it too costly to employ more labour. However the fall in the 1990’s could be due to the advent of technology in the hiring process and the growth of part-time jobs which assisted those workers facing a career change.

Another influence on the NRU is wage growth as with the higher wages you attract more of the labour force to engage in actively looking for work.

A central bank will have to use trial and error to make a decision on how much spare capacity there is in an economy. Only when prices start to increase do they have an idea how capacity is running.

Quality not Quantity

As alluded to by The Economist the goal of full employment must consider the quality of jobs as well. With the acceleration of technology over labour, maximum employment should consider more than capacity constraints or inflationary pressure.

Rather, governments need to consider the options available to workers: not just how easily they can find jobs they want, but also how readily they can refuse jobs they do not. By lifting obstacles to job changes and giving workers a social safety net that enables them to refuse the crummiest jobs, societies can foster employment that is not just full, but fulfilling.

Sources: The Economist 28th January 2017, St Louis Federal Reserve – Natural Rate of Unemployment

Are smartphones causing a loss of productivity?

A recent article on the Bank of England blog written by Dan Nixon caught my attention as it is something that I have long been concerned about – that is the amount of time we spend on our phones / devices and its impact on people’s productivity in the workplace.

Smartphone use and the amount of notifications that we get is enormous. Research in 2015 found that on average we check our 150 times a day – roughly 6½ mins – and spend 2½ hours each day on the phone, spread across 76 sessions. From this the ‘attention economy’ emerges as a scarce and valuable resource and is seen as one of the greatest problems of our time – American philosopher William James noted, our life experience ultimately amounts to whatever we had paid attention to.

The attention economy and the workplace.

The graph below makes for interesting interpretation – productivity growth has been very weak whilst shipments on smartphones has increase by 10 fold. You would expect that the output of a worker would depend on his/her ability to focus and be able to pay attention to the task in hand. However research into observing inner states (attention) and mapping those outcomes with attention (productivity) is fraught with difficulty.

Cyberslacking – The US Chamber of Commerce Foundation finds that people typically spend one hour of their workday on social media – rising to 1.8 hours for millennials. Another survey, meanwhile, found that traffic to shopping sites surged between 2pm to 6pm on weekday afternoons. An influx of emails and phone calls, for example, is estimated to reduce workers’ IQ by 10 points – equivalent to losing a night’s sleep.

Frequent distractions – might lead to a persistently lower capacity to work, over and above the direct effects. What is the argument for this being the case?

1. There’s habit formation – what we do is designed by smartphone apps which make us be as addictive as possible – to ‘hijack the mind’, as Tristan Harris puts it. The psychological mechanism at play here – “intermittent variable rewards” – is the same as the one that gets people hooked on slot machines.

2. The more choice of notifications we have the more time we will spend scanning them looking for instant gratification. Cal Newport goes so far as saying that media like email, far from enhancing our productivity, serve to ultimately deskill the labour force.

Algorithms and attention
Ultimately what we look at is determined by algorithms – so the more technology the less we make the decisions ourselves and our suggested we buy certain goods or services because of out previous behaviours. There has been a lot of talk about artificial intelligence and machines that will be capable of an increasingly wide set of tasks. But most agree on the need to cultivate our distinctively human skills in order to differentiate ourselves from machines. And the human ability to empathise – central to the work of social workers, performers and nurses, among others

But is technology all bad?

IT does help business for the following reasons:

  • Speeds up communication
  • Allows documents to be shared remotely
  • Easier to find information own the Internet.

From the above productivity surged in the late 1990’s and early 2000’s as email, databases and the Internet have had a significant effect on the productivity of business processes.

Is the cause of weak productivity distraction?

Distraction is not the whole story with regard to weak productivity. Industries such as manufacturing and construction have had disappointing productivity rates but this can hardly be due to workers being on their smartphones. As pointed out by The Economist ‘Free Exchange’ productivity is also a consequence of the movement of workers from industries with relatively high rates of growth to more stagnant ones. For instance in the US productivity half of total employment growth since 2000 has been in low productivity areas such as education and health care.

Final thought

According to Dan Nixon constant notifications results in workers becoming less empathetic which is a serious side-effect in an economy where human connections with customers are cast as a defense against automation. Distraction also appears to reduce happiness which ultimately impact on worker productivity. Must end this post now – better check my email accounts, twitter, Facebook and Linkedin.

 

Sources: 

Dan Nixon – Bank Underground blog

Free Exchange – The Economist.