While market participants are increasingly likely to treat short-term GDP data with scepticism on the basis the numbers will be revised later, productivity data tends to be viewed with more reverence.
The topic is of key importance right now as economists grapple with the UK's so-called 'productivity problem'.
The general long-term causes of low or declining productivity in an economy are well understood by economists, and usually attributed to demographics, skill and education levels among the working age population, and the level of technological adoption in an economy.
But George Lagarias, chief economist at Mazars Wealth Management, says that in the present age of rapid technological change, with economies still recovering from the after-effects of the pandemic and those economies questioning how the data is compiled, “we can’t really measure productivity very well in the short term”.
He cites the example of smartphones, which many regard as enhancing productivity as they allow workers to operate even when on public transport or between meetings, “but also mean people can check their personal messages in the workplace now in a way that is completely normal. In workplaces pre-smartphones that would not have been the case.”
Gavyn Davies, a former chief economist at Goldman Sachs and current chairman at Fulcrum Asset Management, says that it is particularly difficult to measure output in the public sector and among those who work from home on a permanent basis.
Melanie Baker, senior economist at Royal London Asset Management, agrees that many of the assumptions around productivity presently being made could be erroneous, because “it’s too early” to understand how some of the recent changes to the structure of the economy are impacting productivity.
Another consideration is that some commonly used measures of productivity, such as output per worker per hour, have the unintended consequence of making economies with higher levels of inequality look more productive.
One example of this is that in an economy with high unemployment, only the most productive workers are employed, so the average productivity per worker is high, whereas in an economy with very low unemployment, even those workers that are perceived as least productive are employed, which drags down the average productivity by that widely used measure.
Baker says that this effect may be exaggerated right now because labour market shortages mean that even less productive workers are being “hoarded” by employers, whereas in more normal labour markets, the least productive workers would be fired, and either replaced by someone more productive or not replaced at all.
Lagarias adds that in the US they stop counting a person in the productivity data at the age of 65, whether they are employed or not, but in the UK a person is counted in the data until they are 67, whether they are employed or not, so comparisons are hard to make.
