Wednesday, 20 May 2015

How UK employment changes just deepen the UK productivity puzzle

John Kay in today's FT on the employment growth at the same time as falling productivity kindly refers to our paper on this

"What have these additional workers been doing? Professor Jonathan Haskel and his colleagues at Imperial College London argue that they have not been employed in low-productivity industries, nor have they been particularly low skilled. Yet the BoE’s analysis is that — especially in the past three years — an increasing proportion of employment growth has been in low-skilled jobs.
In case people think there is a contradiction, the bottom line is that there is not.  First, the  data in our paper goes to 2011, and the effect the Bank talk about is only in the last few years.  Second,it is possible that high skilled individuals are in low skilled jobs, but even if they were, it is only a recent effect and would still leave much of the puzzle unexplained.

Here are some more details. 

The May 2015 Bank of England Inflation report, Chapter 3, has this graph.

If you look closely at it you see that from 2010 to end 2013, the blue lines are the highest, that is, employment growth was predominantly in high-skilled occupations.  It is true that since then there has been more growth in the low skilled, but that is only recent.  If you download the data underlying the chart which the Bank helpfully provides, you see the following: employment growth since 2010Q1 to 2014Q1 in high skilled = 1m, medium skilled = 0.5m, low skilled = 0.3m.  That is, employment growth over the whole period is in the high skilled groups. But John and the Bank are quite right to point out that in the most recent year there is faster growth in the low skilled.

Our paper that John kindly refers to looks at the productivity consequences of this (here, summarised on page 1, more detail in sections 5 and 6) .  There are a number of points.

First, our data only goes to 2011, and we also have much more growth in the high skilled, agreeing then with the Bank.

Second,  the effect on productivity can occur, as John points out, in two ways. 

  1. productivity can change in all industries as the "mix" of worker types employed changes.  Since the mix of types has changed to be high skilled, then this would tend to raise productivity, deepening the puzzle
  2. productivity can change if workers move from industries that are high productivity on average to those that are low productivity on average.  We find this is not the case, in fact, since 2008 it has been the opposite, namely workers moving to high productivity industries.  This again deepens the puzzle.
Is it possible that these high skilled workers are in low skilled jobs?   It is quite possible, but if that is the case, then we would expect them to be paid less than if they were in high skilled jobs. We weight the various types of labour by their wage, so if this effect were occuring then we  would expect changes in the weights would account for it.  We have no data on this in recent years, but don't see an effect in the period up to 2011.  So we don't think that labour composition, at least at this level of aggregation, will explain the puzzle.

Monday, 20 April 2015

The UK Productivity Puzzle

We have a new paper on this:

Haskel J, Goodridge P, Wallis G, 2015, Accounting for the UK productivity puzzle: a decomposition and predictions, Publisher: Imperial College Business School

This paper is featured in the FT today:
Weighing up four theories on the UK’s productivity gap:

Abstract is

This paper revisits the UK productivity puzzle using a new set of data on outputs and inputs and clarifying the role of output mismeasurement, input growth and industry effects. Our data indicates an implied productivity gap of 12.6% in 2011 relative to the productivity level on pre-recession trends. We find (a) the labour productivity puzzle is a TFP puzzle, since it is not explained by the contributions of labour or capital services (b) the re-allocation of labour between industries deepens rather than explains the puzzle (i.e. there has been actually been a re-allocation of hours away from low-productivity industries and toward high productivity industries (c) capitalisation of R&D does not explain the puzzle (d) assuming increased scrapping rates since the recession, a 25% (50%) increase in depreciation rates post-2009 can potentially explain 16%(33%) of the puzzle (e) industry data shows 33% of the TFP puzzle can be explained by weak TFP growth in the oil and gas and financial services sectors and (f) cyclical effects via factor utilisation could potentially explain 14% of the puzzle. Continued weakness in finance would suggest a future lowering of TFP growth to around 1% pa from a baseline of 1.2% pa. 

(Apologies to those who logged into an earlier blog version under this title that linked to a paper on science)

Spending on Science, new paper

We have a new paper on this: Goodridge, P., Haskel, J., Hughes, A., and Wallis, G., (2015). The contribution of public and private R&D to UK productivity growth, Imperial College Discussion Paper, 2015/03, March 2015,   available at

The abstract  is

We estimate the contribution of public and private R&D to UK productivity growth on industry data, 1992-2007. R&D affects productivity growth via (1) R&D input, valued at competitive factor shares and (2) (Domar-Hulten weighted) industry TFP growth if there are (a) within-industry spillovers (b) between-industry spillovers and (c) spillovers from public-sector R&D to the market sector. Thus effects depend upon factor shares, spillovers and industrial structure. We estimate all these effects and perform counter-factual experiments such as e.g. additional government spending on the science budget, increased manufacturing R&D spending and the effects of such changes with a different industrial structure.

Our central estimate of the rate of return to public spending on science is  20%.

This the article behind my interview in the FT this weekend,

Friday, 17 April 2015

Interview in the FT

I very kindly get an interview in the FT this weekend:

Should national accounts stick close to business accounts?

My friend and co-author @carolcorrado makes a very valuable point.  
  1. People say that national accounts should stick close to business accounts.  So national accounts should not capitalise intangibles since business accounts don't do so.
  2. But, that's not so clear. When companies merge, and intangible value is realised in e.g. pricing goodwill, that is put on the balance sheet.  So, in fact, the treatment of intangibles in business accounts is inconsistent between merging and non-merging companies.  
  3. Thus to say that national accounts should stick to business accounts could mean capitalising intangibles but equally not capitalising them.

Knowledge workers demystified


Wednesday, 25 March 2015

Behavioural economics
Asymmetric bayesiansim or why people are so tribal. 

Sunday, 22 March 2015

Rationality in Economics

At an Economics conference last week, Alan Kirman made the point that when economists say "rational", they don't mean rational as most people think i.e. fully optimising, relentlessly all-knowing calculating.  They mean "consistent".

Lots of psychology looks at individual motivations, what should economics do with all these studies?  Here is Peter Abel in a paper I have not seen before.

Psychologists and, indeed, many sociologists often allege that economists adopt
an over-simple model of the individual (i.e. usually rational, calculating and self-
interested). Maybe they do, but the important point is, nevertheless, that the social
sciences should only adopt the simplest model of the individual consistent with
validated psychology theory, which can in turn contribute to an account of the sys-
tem state. This being the case, the social sciences will not always, or even usually,
shift with changing fashions in our understanding of individual psychology. Unfor-
tunately many sociologists have not taken this lesson to heart, with the result that
a type of literature has evolved which tries to locate ever more refined ways of
understanding individuals and their interactions. Social scientists have very little to
learn from this literature.

Sunday, 15 March 2015

Monday, 9 March 2015

How many firms are innovating without doing R&D?

Innovation findings from the 2013 Survey.
a. From table 1 we find that in 2013, 45% of firms are innovation active, that is, they product or process innovate, or introduce new processes etc. 
b. From figure 1, we find that 15% of firms are doing R&D.
c. That means, that assuming those 15% of firms report they are innovation active, 66% or 2/3rds of firms are innovating without any R&D.