Jul 31

A. Old measures hide new productivity?

Nowadays, the constant media refrain is: “G7 productivity growth has slowed right down – living standards will fall – inequality will rise – it’s a puzzle why”

Some experts say we couldn’t keep on growing at 2% plus per annum – we’re in an era of ‘secular stagnation’ according to Larry Summers, Harvard economics professor

Goldman Sachs have noted that rich nation productivity has grown at an average pace of just ¾% since 2008, down from 2% in the three decades before

Others like Robert Gordon, another economics professor, say it’s all because no major new productivity enhancing  inventions/ innovations are appearing, or indeed are possible, so productivity growth rates have long since peaked and will continue to struggle from now on

But all these experts base their thinking on available national measures of:

  • Outputs = GDPs = measures prone to considerable error, full of dubious assumptions and estimates, and becoming increasingly flawed given much output value goes uncounted as we move from an era of materialism to mentalism

  • Inputs = Labour hours or numbers only = more flawed measures because they ignore labour quality and other capital and knowledge inputs

In fact, there’s a growing gap between the prices paid for goods and services clocked by GDP and the extra value obtained from those same goods or services, including freebies offered by the likes of Google, Facebook and Skype are included

Add a value for this so-called consumer surplus and maybe, just maybe, GDP and so (labour) productivity has been growing just as fast, if not faster, than in apparent better years before the 2008 financial crisis

Indeed, one estimate has it that some 30% of actual GDP now goes unmeasured/ uncounted – if so, this would make a mockery of the accuracy assumed by experts before they recommend action needed or by the media when one reads their headlines of doom announcing ‘GDP has fallen by 0.3%’

The problem is we don’t know what extra value to add to current GDP levels, even if they were reasonably accurate

Equally, there’s significant labour substitution ongoing with the use of more IT, automation, robotics and Artificial Intelligence – this has a big impact on national productivity by increasing output and making labour productivity look better – however, it does not flag the impact on the productive use of all a nation’s costly input resources, not just labour, because we do not have any good way to value them all together

Hence, the conclusion is nations might well be better off ignoring current national productivity measures and looking to others to build a credible national economic picture – otherwise, they could be steered to take wrong actions in some areas and overlook right actions in others



What extra % on GDP if measure/ value this surplus?

What extra % growth rate

What % prody gaps v others then?

Current measures are relevant to the old days when economies were based on making physical goods – as productivity improved, so unit costs fell, so unit prices also fell in real terms, enabling many more people able to afford them same – so demand and output volumes greatly increased, even as quality of those units also rose by quantum leaps

Trade i.e. exports now need to rise – and can only do so if the demand from abroad nations can afford the units on offer – so first get the prices right ie get the unit costs right

Indeed, when quality also became important as that was also reflected in prices and so GDP – new technology even has a deflationary effect putting a brake on GDP growth and so standards of living/ wages

We don’t want another complex solution like MFP or TFP – Multi Factor Productivity or Total Factor Productivity – to solve the problem

We do want something most government ministers and business managers can understand and will find useful

Clearly, any new major inventions – e.g. Artificial Intelligence or, Internet of Things – takes time to achieve widespread use, not least because there are usually many rough edges to be ironed out and much education of potential users before all are confident in how to use them to best effect – hence they can take many years before they show up in official statistics

However, this applies to stuff bought to remove/ reduce drudgery, dull or dangerous work – work which has to be done, work which needs people to complete it, and so requires them to be paid, work they wouldn’t do if they won the lottery say – materialism in other words

But there’s other stuff they now seek – the 21st century, is the start of the mentalism era – the age of leisure and pleasure, meeting and greeting – work will be activities we want to do, not have to do, to earn ways of exchanging goods and services with each other

Real need is not nec extreme accuracy but a true and fair pic which gives a good idea of trends, gaps and scope

before we start moaning, headlining productivity puzzles and offering hosts of different expert solutions

 Current concerns:

    1. But do these positional fixes provide a ‘true and fair picture’ given they’re based on GDP and labour input measurements

    2. GDP:

      1. No mst of welfare

      2. What of outsourced work abroad

      3. What of public sector output assumed to be its total cost – so if you pour more in, productivity goes up? – public sector services are/ should be vital services the private sector will not or cannot  afford as too little profit in them

      4. No msr of the value people obtain from stuff offered free

  • No msr of £ benefits from living longer and healthier lives

  1. No msr of value from feeling safer or happier/ more contented

  2. No msr of the value/ benefits they offer the community – “socially useless”

    No msr of increases in quality for same price of h/w, s/w, apps, cars, TVs, TV progs

  3. (Flaws of aggregation) We aggregate and so miss much of the important things to see e.g. Most highlight productivity gaps between the UK and the USA, France or Germany – they ignore the publicised data claiming productivity of Japan is worse than the UK, and so never question this oddity:

    1. France reason = ???????????????

    2. Japan reason = Mix of highly productive mfg sector and cottage service/ agricultural industries so, overall, poor – simple arithmetic produces nonsense

    3. You cannot measure productivity at national level – for you get such mixed-up nonsense results – but we always do, governments included

  4. Widespread slowdown in productivity improvement = ‘The productivity puzzle’ – causes offered being:

    1. Lack of diffusion of transformational (digital) technology to most orgs within each sector – it always takes time, often many years, if it’s truly ‘general purpose’ like electricity or computers – perhaps caused by lack of cash, awareness, interest, skills to apply it, or what?

    2. Prototypes, trial and error, build profits first – only then do others pile in? – 30% of all individual items are said to eit the market each and every year – but that still adds up to a massive cumulative gain in totals on offer and so choice/ competition – and so to prody increases expected
    3. Some sectors have more scope to improve than others – Baumol???
    4. Need for increased use of mobile technology, cloud services, artificial intelligence to aid doctors and lawyers, big data analytics for retail and drug discoveries, wearable sensors to monitor blood pressure and health conditions, robots for surgery and eldercare, 3D printing for complex manufacturing such as bespoke hip joints or gas turbine blades, 5G wireless connections

  • Lack of mgt educn

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