How do firms grow as they age?

Marko Melolinna and Patrick Schneider.

Firm age is a main determinant of firm growth and survival. For example, older firms are likely to be larger and grow more slowly than younger ones (see Audretsch & Mata, 1995; Coad et al, 2013). They are also more likely to survive (see Audretsch & Mahmood, 1995, Manjón-Antolín & Arauzo-Carod, 2008). This is why, in this blog post, we look at how firms’ lifecycles – firms being born, aging and dying – are linked to how firms grow. The results show that, as they age, firms in the United Kingdom grow mainly by employing more people, rather than by generating more turnover per employee. And while firms are on average less likely to die the older they get, the cohort of firms that were born since the financial crisis are more resilient than older firms.

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Tight labour markets and self-service beer: is the productivity slowdown about to reverse?

Will Holman and Tim Pike

Firms are increasingly investing in automation, substituting capital for labour, as workers become more scarce and costly. We are seeing multiple examples, from automation in food processing to increasingly-common self-service tills. This push for productivity growth is one of the key themes from our meetings with businesses in the past year, which we think suggests a reversal of a decade-long trend.

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Is the economy suffering from the crisis of attention?

Dan Nixon

Smartphone apps and newsfeeds are designed to constantly grab our attention. And research suggests we’re distracted nearly 50% of the time. Could this be weighing down on productivity? And why is the crisis of attention particularly concerning in the context of the rise of AI and the need, therefore, to cultivate distinctively human qualities?

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Does productivity drive wages? Evidence from sectoral data

Alex Tuckett

Since 2008, aggregate productivity performance in the UK has been substantially worse than in the preceding eight years. Over the same period, aggregate real wage growth has also been significantly lower – it has averaged -0.4% per annum from 2009-16, compared with 2.3% per annum from 2000-08. The MPC, and others, have drawn a link between these two phenomena, arguing that low productivity growth has been a major cause – if not the major cause – of weak wage growth. The logic is simple – if workers produce less output for firms, then in a competitive market firms will only be willing to employ them at a lower wage.

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Bitesize: Exploring UK sectoral productivity

Ian Billett and Patrick Schneider.

As time goes to infinity, the probability that a productivity analyst will wonder ‘which sectors are driving these trends?’ goes to one. We present an interactive sectoral productivity tool to help you explore this question without any fuss.

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The world trade slowdown (redux)

Gene Kindberg-Hanlon and David Young.

The volume of world trade is now 17% below where it would be had it grown at pre-crisis trend after 2011.  This post argues that most of this gap can be explained by weakness in world GDP, but stalling expansion in global value chains (GVCs) is playing an increasingly important role.  We also argue that this shortfall can’t be explained by shifts in the geographical or the expenditure split of global GDP growth. While world trade grew twice as quickly as world GDP pre-crisis, it is likely to grow at about the same rate as world GDP in the future.  This matters: weak trade could explain half of the 1pp fall in annual global productivity growth since the crisis.

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There are two productivity puzzles

Patrick Schneider.

Much has been written about the productivity puzzle. But there are actually two puzzles apparent in the data – one in the level that hit at the crisis and the other in the growth rate, which is a more recent phenomenon – and they could be driven by completely different sources. Distinguishing between the two puzzles is important precisely because of these potential differences – if anyone analyses the puzzle as a whole looking for the force driving it, the actual underlying variety will confound our estimates of the relative importance of these drivers.

In this post I discuss:

  1. what people mean by the productivity puzzle, usually a percent deviation from the pre-crisis trend;
  2. how I think of it as actually two puzzles: one in the level and the other in the growth rate; and
  3. why this distinction can be important, using the example of a simple growth accounting decomposition of productivity growth into capital deepening and technological advancement.

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Fish and (micro)chips: Why I’m relatively relaxed about robots

John Lewis.

My earlier post arguing that robotisation wouldn’t destroy jobs, slash wages or drastically shorten the working week prompted many thoughtful responses. Richard Serlin and others countered, arguing that if automation affects all sectors, then displaced workers may have nowhere to go.  Others asked if the sheer scale, speed and scope of robotisation might make it much more disruptive.  Or if wages fall, who will be able to buy the extra output? And Noah Smith raised the prospect that robotisation might eventually differ from earlier waves of innovation by replacing rather than complementing human labour.  This post attempts to respond to those points, expand on the original post and explain why I’m still relatively relaxed about robots.

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Robot Macroeconomics: What can theory and several centuries of economic history teach us?

John Lewis.

Advances in machine learning and mobile robotics mean that robots could do your job better than you.  That’s led to some radical predictions of mass unemployment, much more leisure or a work free future.   But labour saving innovations and the debates around them aren’t really anything new.  Queen Elizabeth I denied a patent for a knitting machine over fears it would create unemployment, Ricardo thought technology would lower wages and Keynes famously predicted a 15 hour working week by 2030.   Understanding why these beliefs proved to be wrong gives us important insights into why similar claims about robotisation might be incorrect.  But automation could nevertheless have sizeable distributional implications and ramifications well beyond the industries in which it’s deployed.

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