These are both things that would tend to boost the relative demand for high-skilled labour during a downturn. Differences in labour supply might also play a part. For example, some have argued that those with low wages have less to lose from exiting employment. Their pay is lower relative to unemployment benefit, especially during downturns. They may also have fewer options: when vacancies are scarce, skilled people have the capacity to move into lower-paid jobs while searching for new opportunities (Nickell (1979), Chassamboulli (2011)). Why have compositional effects been less positive during this cycle? These factors can help to explain why employment is more variable for the low paid. It’s possible the same factors have been at work in the most recent cycle in the UK. But the last  6  The regression also includes time dummies so allows for arbitrary variation of pay growth net of the compositional effects. 7  In principle, demand-side factors could still matter. Perhaps, for example, the problems of the financial industry, whose employees are better qualified than average, have pushed employment towards other industries. To that extent, the regression could be picking up effects whose origins are demand-led – a shift in output across sectors – but attributing them to changes in individuals’ characteristics. But this seems unlikely: in truth, shifts in sectoral employment haven’t been big enough to generate such effects.
This might account for the acceleration we’ve seen in average productivity and wages; it could also explain why there’s been a narrowing of the gap between AWE growth and the surveys. So having summarised the main points let me describe in a little more detail where the data comes from and how these effects have been estimated. I’ll then say something, if only tentatively, about why they might have differed from the last cycle – why, in particular, the compositional effects have been more negative during the recovery, and perhaps before that as well (my hands will be waving slightly at that point). A short final section concludes with some remarks about policy. Generating the estimates To understand the results it helps to know something about where the data come from and how they’re constructed. The first and most important point is that the headline measure of wages in the UK, the AWE, is what it says it is – an average. Employers are asked simply to divide their total wage bill by the number of employees. So if – say – a responding firm were to substitute a less experienced, less well-paid person for someone better paid, its submission to the AWE would fall even if no individual’s wage had changed. It is these “compositional effects” that we are trying to measure and account for. We do so using data from a different source – the Labour Force Survey – which is sent out to households.