Closing the UK productivity gap with better data


Closing the UK productivity gap with better data

By Rebecca Riley

Investment in economic measurement is essential to developing robust statistics to investigate our productivity gap.  New ESRC funding announced today, including for a project by a research group at the  ESCoE and ONS, will greatly help.

The received wisdom based on international productivity comparisons is that labour productivity is (a lot) lower in the UK than in France, Germany and the United States. The implication is that UK living standards, on average, are less than they could be, if only the UK were more like its peers. The most recent data from the UK Office for National Statistics (ONS) on GDP per hour worked suggest that in 2016 labour productivity was around 30% higher in France and the US and 35% higher in Germany than in the UK. Although this UK productivity gap has worsened since the financial crisis of 2008, a gap of this order of magnitude is thought to have persisted for decades in many sectors of the economy (Mason, O’Mahony and Riley (2018)).

Labour productivity is measured as the ratio of GDP to the total number of hours worked in the economy. The ratio of UK labour productivity to the equivalent in, for example, France is then simply the ratio of UK GDP to French GDP multiplied by the ratio of hours worked in France to hours worked in the UK. The overall size of the UK and French economies is similar measured in terms of GDP at purchasing power parity and so labour productivity differences between the UK and France are accounted for by differences in the total number of hours worked to generate GDP. As it is often put, what UK workers produce in a normal working week can be produced by French workers an hour or two before closing time on a Thursday afternoon.

Much current research on economic measurement focusses on the measurement of GDP and its interpretation, prompted by the rise in the digital economy. In contrast, new analysis published towards the end of last year by the Organisation for Economic Co-operation and Development (OECD), instigated by the ONS, focusses on the total number of hours worked. In short, the analysis finds scope for harmonising across countries the way that total hours worked are estimated, with implications for the UK productivity gap and cross-country productivity comparisons more generally. It suggests that the UK productivity gap vis-à-vis its peers may be less spectacular (around a third less spectacular) than previously thought.

Does this new information mean that recent policy focus on increasing UK productivity is somehow less important? No. The OECD study doesn’t overturn the received wisdom that there is plenty of scope for UK productivity levels (and living standards) to catch up with that of many other advanced economies. Rather, at the risk of stating the obvious, the OECD study illustrates the importance of investing in economic measurement, not just so that the statistics that inform policy can keep up with an ever evolving economy, but so that the detailed investigation required to develop robust statistics can take place.

So, what can be done to close the UK productivity gap? The answer to this is multifaceted, because the determinants of productivity are many. One contender is for businesses to improve their management practices. The UK Management and Expectations Survey (MES) conducted in 2017, developed in collaboration between the Economic Statistics Centre of Excellence (ESCoE) and the ONS, revealed significant variation in management practices amongst UK firms that were otherwise similar in terms of workforce composition, industry, age and size (ONS, 2018). It corroborated a growing body of evidence (Sadun, Bloom and Van Reenen (2017)) that suggests better management practices are associated with superior business performance, showing a strong positive correlation between the productivity levels of UK firms and the ‘quality’ of their management practices. But this raises an important question. If the returns to investing in good management practices are as high as indicated by such correlations, then why don’t more firms invest in improving management? Is it simply the case that the positive correlation between good management and productivity reflects a tendency for firms that are already successful to invest in management?

While the associations between business performance and management practices are increasingly well-documented, the factors underlying these associations are not well-understood. This matters, because if policy is to make a difference we need to better understand how and under which circumstances management influences productivity, and whether for some firms there are barriers to adopting good management practices. The starting point for this is better data.

Today the Economic and Social Research Council has announced a new investment in projects to investigate management practices’ effect on productivity. One of these projects has been awarded to a research group* at the ESCoE and ONS. Over the next three years they will develop and analyse new resources to improve understanding of the causes and consequences of differences in management practices across UK businesses. The project will develop a second wave of the MES, providing longitudinal data on management practices that can be matched to data from other sources, as well as new evidence from randomised control trials. These new resources will enable researchers to identify changes in management practices and productivity over time, fundamental to disentangling the linkages between the two. Working with stakeholders including McKinsey, Chartered Management Institute, Be the Business and the Confederation of British Industry the research group will draw from this new evidence base a number of practical lessons for improving UK productivity.

*The research group includes Nicholas Bloom (Stanford University), Paul Mizen (University of Nottingham), Rebecca Riley (National Institute of Economic and Social Research), Tatsuro Senga (Queen Mary University of London), Catherine Sleeman (Nesta) and John Van Reenen (MIT) from the ESCoE and Gaganan Awano, Ted Dolby, Jenny Vyas and Philip Wales from ONS.

ESCoE blogs are published to further debate.  Any views expressed are solely those of the author(s) and so cannot be taken to represent those of the ESCoE, its partner institutions or the Office for National Statistics.

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