The Productivity Puzzle

As you should be aware, productivity gains are the key to wealth gains, and the UK does not have a startling record on this  - for some years now. Much has been written about this, but if you want a short, snappy way of encapsulating this and inserting it into an essay, try the following two paragraphs; after that I have put the full blog post, which is harder to read, so is not essential, although it does give some comparative figures for other countries:

KEY POINTS:

Is it the service sector?

To my mind a large factor in the productivity puzzle has been the switch from actual things being produced to more intangible types of economic growth. If we look at it in a stereotypical sense we see output of cars replaced by output of haircuts or teaching or nursing. The latter is much harder to measure in productivity terms as who wants teachers to be more productive via larger class sizes?

It is even worse for nurses as who would want to be in a hospital ward with fewer nurses? The problem here is we need a measure of quality of the output and we struggle to define and measure that. Even worse, some areas of production face a future of possible enormous gains in labour productivity by the use of robotics and artificial intelligence but where does that leave the labour? Can we have too much of something that is usually considered to be good.

Looking forwards as Sarah O’Connor points out we are likely to see more growth in the service sector.

The undramatic truth is that many of the jobs of the future are also those of the present. Prime among them are jobs that involve humans looking after other humans. The US Bureau of Labor Statistics has predicted the top 30 fastest-growing occupations for the next 10 years; more than half are some variety of nurse, therapist, healthcare worker or carer. This feels like a safe bet — and not just in the US.

She also points out that this growth will be in jobs that we tend to not value.

Social care jobs, for example, are defined by economists everywhere as low-skilled or unskilled…….Personal care and home health aides in the US make roughly $23,000 a year on average. In Britain, a prolonged squeeze on public spending has had knock-on effects on care workers, many of whom work for private companies that rely on public sector contracts. In England last year, 43 per cent of care workers earned less than £7.50 an hour.

AND THE FULL BLOG POST

Are we measuring the wrong type of productivity?

Posted on May 17, 2017 by notayesmanseconomics

Today gives us an opportunity to look at the latest data on what is the key economic number these days which is wages growth. After yesterday’s inflation data we will be able to look at both nominal and real or inflation adjusted wages growth. The reason it has become a key number is that in countries like the UK ( and US and Japan..) is that the employment situation is strong and recorded unemployment has improved considerably but wages growth has been weak. In the extreme case of Japan there has so often been no wages growth.
An associated influence on this has been problems with productivity as of course it has helped drive wages growth in the past. Whereas according to Bank of England Chief Economist Andy Haldane that happy situation has been replaced by this.

Productivity growth has consistently underperformed relative to expectations, since at least the global financial crisis. This tale of productivity disappointment, in forecasting and in performance, has been extensively debated and analysed over recent years. Some have called it the “productivity puzzle”.

Indeed we have been on something of a road to nowhere.

For the past decade, average productivity growth has been negative. This is unusual, if not unique, historically. You would have to go right back to the 18th century to see a similarly lengthy period of stagnant productivity.

In case you were wondering it compares to this.

there has been a near-monotonic rise in UK productivity. UK TFP growth since 1750 has averaged 0.8% per year. Since the Industrial Revolution, GDP per capita has doubled roughly every 65 years and productivity roughly every 85 years.

Actually some of Andy’s numbers are a little contradictory as he suddenly agrees with the theme on here that things were deteriorating even before the credit crunch.

From 1950 to 1970, median global productivity growth averaged 1.9% per year. Since 1980, it has averaged 0.3% per year.

I find that fascinating because is not that the same period where we saw the influence of increasing globalisation and internationalisation which were badged as bring significant economic benefits?

The United States

The international scale of the issue has been highlighted by the Financial Times today.

US productivity is set to grow this year at around a third of the pace prevailing before the financial crash………..

US labour productivity — a driver of the economy’s fortunes — is forecast to expand 1 per cent this year, an improvement on the 0.5 per cent recorded for 2016 but far shy of the 2.9 per cent growth seen from 1999 to 2006, according to Conference Board projections shared with the Financial Times.

This is true of others as well.

The EU will see 1 per cent growth in GDP per hour, an improvement on last year’s 0.8 per cent but short of the 1.9 per cent seen in 1999-2006.  Japan is on course for 1.1 per cent productivity growth, up sharply from 0.5 per cent in 2016 but still well shy of the 2.2 per cent pace seen before the crisis.

I cannot move on without pointing out that the pre credit crunch figures were inflated in many places by booming housing and banking sectors which then went bust.

the figures lag far behind the 4.9 per cent pace in 1999-2006.

Is it the service sector?

To my mind a large factor in the productivity puzzle has been the switch from actual things being produced to more intangible types of economic growth. If we look at it in a stereotypical sense we see output of cars replaced by output of haircuts or teaching or nursing. The latter is much harder to measure in productivity terms as who wants teachers to be more productive via larger class sizes? It is even worse for nurses as who would want to be in a hospital ward with fewer nurses? The problem here is we need a measure of quality of the output and we struggle to define and measure that. Even worse some areas of production face a future of possible enormous gains in labour productivity by the use of robotics and artificial intelligence but where does that leave the labour? Can we have too much of something that is usually considered to be good.
Looking forwards as Sarah O’Connor points out we are likely to see more growth in the service sector.

The undramatic truth is that many of the jobs of the future are also those of the present. Prime among them are jobs that involve humans looking after other humans. The US Bureau of Labor Statistics has predicted the top 30 fastest-growing occupations for the next 10 years; more than half are some variety of nurse, therapist, healthcare worker or carer. This feels like a safe bet — and not just in the US.

She also points out that this growth will be in jobs that we tend to not value.

Social care jobs, for example, are defined by economists everywhere as low-skilled or unskilled…….Personal care and home health aides in the US make roughly $23,000 a year on average. In Britain, a prolonged squeeze on public spending has had knock-on effects on care workers, many of whom work for private companies that rely on public sector contracts. In England last year, 43 per cent of care workers earned less than £7.50 an hour.

There are plenty of thought-provoking issues here as raising productivity here would involve paying them more as that is the only measure of output we have here. Indeed both GDP and productivity fail us when we cannot measure economic output. On this road no wonder both metrics have problems. If a service sector producer gets more efficient and reduces its price then as money is often the only measure we record lower productivity when in fact things have improved. In other words we are in a something of a mess of our own making.

Today’s data

Not the cheeriest I am afraid to say.

Output per hour – our main measure of labour productivity – fell by 0.5% in Quarter 1 (January to March) 2017. This compares with growth of 0.4% in Quarter 4 (October to December) 2016.

My explanation given above may well work though.

was a result of hours worked growing faster than output;

What about wages?

Growth has been pretty consistent at what seems to be something of a new normal.

Between January to March 2016 and January to March 2017, in nominal terms, total pay increased by 2.4%

It is in fact marginally higher but as we look for real wage growth and note that nominal growth in March was 2.4% we see that it was a mere 0.1% and should it remain the same in April then wage growth will be negative. Of course if we use the RPI then annual wage growth was negative again in March at -0.7%. Sadly such numbers come on the back of a credit crunch era decline.

The Resolution Foundation has a somewhat enduring if increasingly lonely faith in officialdom so it still takes the forecasts of the OBR seriously and has switched to the CPIH inflation measure. I think though like so many places today it was so revved up to say real wages were falling again that it has used the regular rather than total pay data.
Comment
There is much to consider here as we find yet another set of statistics that are failing us in the credit crunch era. Our outdated concept of productivity needs to change and it is being challenged at both ends of the spectrum. At one extreme we have the sort of situation covered by Skynet in the Terminator series of firms where robots rule and at the other we have what we might call 100% human occupations. Do we really want to say that one provides a sort of 100% productivity and the other 0% because that is where we are heading right now?
Let me add in another sector which is the self-employed which these days is 15% of our workforce or 4.78 million people. For those in the service sector our main measure of output and hence productivity will be their pay. The very pay numbers that are ignored by the official average earnings data. What could go wrong?