I wonder if the best defence of the theory that the imposition of the UK National Minimum Wage didn’t hurt anybody much is that there never really was a youth unemployment “crisis”. After all, it would surely look brave to believe both that the Low Pay Commission was “successful” in setting the minimum wage, and that there was a youth unemployment crisis right after a period of imposing higher and higher minimum wages on young people in the labour market.
One way to claim there was never much of a crisis is looking at the data on NEETs – young people Not in Education, Employment or Training, rather than the standard Labour Force Survey measures of unemployment. The ONS break the NEETs data down into the 16-17 and 18-24 age group, which is helpful because being NEET has become much harder in recent years for 16- and 17-year-olds as the school leaving age has risen to 18 in England (although not the rest of the UK).
The rise in the NEET rate for the 18-24 group during the 2008 recession was much less sharp than the rise in the LFS unemployment rate for the same group. Today’s data update suggests the youth unemployment crisis is perhaps over; at 13.8% for 2015 Q3 the 18-24yrs NEET rate is only a whisker above the all time low of 13.7% in 2004.
If you compared two periods:
1) Period One, where nominal asset prices fell 15%, nominal incomes fell 4%, the labour market was contracting sharply … oh, and the CPI rate was usually above 3%.
2) Period Two, where nominal asset prices are at all time highs, rising 5-10% p.a., nominal incomes are rising 3-4%, the labour market is expanding rapidly… oh, and the CPI rate was slightly negative.
… which period would you call “deflation”?
To keep my comment section happy, here is some “productivity scepticism”. I like this theory from Paul Donovan of UBS discussed in a Guardian article, here quoting Donovan:
“In 2000, 32% of UK businesses were employers. By 2014, 24% of UK businesses were employers. This raises the obvious question of what on Earth 76% of UK businesses were doing if they were not employing anyone – and the answer of course is that they were single person businesses where the owner was the sole person ‘on payroll’.
This matters for capital spending, because people setting up as self-employed – for example, as a consultant – may well make little or no upfront investment in kit. Says Donovan:
“If you are a self-employed consultant, you probably already have a laptop, have a car, have an office at home. As the boundaries between home and work blur, we are making better use of the capital we have got.”
“What this means is that investors looking for a “capex recovery” may be missing the point. The secret capex story may be that businesses make better use of non-business assets, and that part of the capex cycle … masquerades under a ‘retail sales’ pseudonym.”
One of the puzzling parts of the UK productivity puzzle is the divergence of employment and output during late 2011 through 2012, when output barely grew and employment soared. If output and employment are both growing we can use the “low-skilled labour supply shock plus composition effect” theory to explain slow average productivity growth, but that doesn’t work well for this period.
We can (partially) resolve this problem by revising up 2011-2 real GDP, and Donovan’s theory could help here. 2011-2 saw a self-employment boom; if capital investment by the self-employed shows up only as consumption, or not at all, then measured GDP was too low. The recovery in household consumption of durable goods has been much stronger than total consumption, up 19% from 2008 Q1 to 2014 Q1 versus 2% for the latter. One of the upcoming ONS methodology changes is to remove a £500 lower bound on what counts as capital spending in the business investment survey, perhaps this will help.
File under “grasping at straws” if you prefer. There are good reasons to be sceptical there is any significant bias in measuring GDP, and other survey indicators (PMIs etc) suggest the 2011-2 quasi-depression was roughly that. Stories about the unemployed being pushed into “false” self-employment could make us doubt the jobs data instead, though again it would be surprising if that was sufficient to explain such a large shift in the labour market surveys.
What do you expect to happen with a 2% inflation target, if productivity growth falls from 2% per annum to 0% per annum? You expect tight money. Nominal wage growth must be pushed down from 4% to 2%. If nominal wages are sticky you’ll need a nasty blast of unemployment to achieve this. But the labour market will adjust eventually to the new equilibrium. This is the EARN08 table which tracks one measure of nominal hourly wages, updated today, steadily tracking below 2% average growth since 2009.
Alternative view using nominal weekly wages, with the arrow highlighting that dangerous inflection point in Britain’s inflationary wage/price spiral which prompted Carney and other MPC members to insist last year that Bank Rate would soon rise:
Of course everybody knows that productivity growth will pick up to 2% per annum again, slash return to the pre-crisis trend, and then wages will rise 4% per annum again, slash soar into the heavens, and everything will be just fine. See also, Bank of England productivity forecasts today.
Welcome to Britain, have a nice day!
The median real GDP forecasts from the Bank are now slightly lower than August last year, when the oil price was above $100. Carney claimed there was an “unambiguously positive” effect of falling oil price… doesn’t look that way. Even if the falling oil price lowered forecast unemployment – not impossible as before, go from lower forecast inflation to less tight monetary policy to jobs – there has been an offsetting negative drag on expected output – maybe losing more jobs in the North Sea?
As usual it doesn’t take long for the OBR employment forecast to look too low. Labour market data covering the three months to March out today:
Employment has hit the OBR’s estimate of trend employment. I’m not sure if this is a first, due to the ONS revision to population estimates last year, the current labour market data is not comparable with old OBR forecasts. Another upward revision to the OBR’s trend seems not unlikely.
Hours worked are slightly weaker than forecast. It’s going to be interesting to see what happens to average hours. The OBR thinks the rise in average hours since 2010 is a cyclical blip in a structural downward trend. We’ll see. If welfare reform is driving up average hours, and is one of the reasons that average productivity is not growing (due to a composition effect), let’s hope the OBR is wrong on this too.
Economist writer H.C. has an interesting Free Exchange post discussing Scott’s “musical chairs” model and British unemployment. Scott also comments. Here is my curve-fitting exercise:
One of the difficulties in working with the UK macro data is that the ONS don’t produce a good quality high frequency time series for hourly wages. Of the available data we have low frequency, high accuracy data in the Annual Survey of Hours and Earnings (ASHE) based on very large sample of employers’ payroll data held by HMRC. At the other end we have high frequency, low accuracy data in the Average Weekly Earnings (AWE) data, produced from a small survey which deliberately excludes a number of workers (notably, I believe, high earners and small employers). I compared the range of various sources at the beginning of last year.
In this post I’ll use the lower quality AWE data, from which we have time series for both regular (ex bonuses) and total weekly pay, and also for average actual hours worked. I’ll also assume that bonus pay is not very sticky. From either pay series we can then calculate average hourly wages by simple division.
The musical chairs model says there is a strong positive correlation between the unemployment rate and the ratio of hourly wages to nominal GDP. I’ll cheat slightly (I did warn you this was a curve-fitting exercise) and use nominal GVA at basic prices instead of NGDP. An increase in nominal GDP which is accounted for entirely by an increase in indirect taxes would not be expected to increase the resources available to hire workers; since we’ve had big VAT shocks in the UK I think this is a reasonable “cheat”.
Here’s the first version of the musical chairs graph, using regular wages to derive hourly wages:
I would say this has done quite well since 2008: though the recovery is predicted slightly too fast, and the correlation is absent for the period prior to 2008.
A second interpretation is to use aggregate employee income instead of nominal GDP/GVA, so changes in the labour share of GDP don’t affect the results:
This is a better fit.
One thing that either of these models will struggle with, if only because of data limitations, is the shift between employment and self-employment. There have been two very large swings in UK self-employment in the period covered above: a 9% rise in 2003 and a 10% rise in 2013/4. We cannot really measure the wages of the self-employed, and as far as I know those workers are entirely excluded from the AWE data – I would not find it surprising that the musical chairs model appears to breaks down for that kind of shock. If there are studies on self-employment and wage stickiness I’d be interested to hear in the comments.