Peter Goodridge

Can Intangible Investment Explain the UK Productivity Puzzle

This paper investigates whether intangibles might explain the UK productivity puzzle. We note that since the recession: (a) firms have upskilled faster than before; (b) intangible investment in RD and (c) intangible and telecoms equipment investment slowed in advance of the recession. We have therefore tested to see if: (a) what looks like labour hoarding is actually firms keeping workers who are employed in creating intangible assets; and (b) the current slowdown in TFP growth is due to the spillover effects of the past slowdown in RD and (b) 0.75 per cent per annum of the TFP growth slowdown can be accounted for by the slowdown in intangible and telecoms investment in the early 2000s. Taken together intangible investment can therefore account for around 5 percentage points of the 16 per cent productivity puzzle.

Productivity and Growth in UK Industries: An Intangible Investment Approach

This paper tries to calculate some facts for the “knowledge economy”. Building on the work of Corrado, Hulten and Sichel (CHS, 2005,9), using new data sets and a new micro survey, we (1) document UK intangible investment and (2) see how it contributes to economic growth. Regarding investment in knowledge/intangibles, we find (a) this is now greater than tangible investment at, in 2008, £141bn and £104bn respectively; (b) that RD (d) the most intangible-intensive industry is manufacturing (intangible investment is 20% of value added) and (e) treating intangible expenditure as investment raises market sector value added growth in the 1990s due to the ICT investment boom, but slightly reduces it in the 2000s. Regarding the contribution to growth, for 2000-08, (a) intangible capital deepening accounts for 23% of labour productivity growth, against computer hardware (12%) and TFP (40%); (b) adding intangibles to growth accounting lowers TFP growth by about 15% (c) capitalising R&D adds 0.03% to input growth and reduces lnTFP by 0.03% and (d) manufacturing accounts for just over 40% of intangible capital deepening plus TFP

Constructing a Price Deflator for R&D: Calculating the Price of Knowledge Investments as a Residual

We model the production and use of knowledge investment and show how the model can be used to infer the unknown price of knowledge using two approaches. The first is often used by national accounting offices and is based on costs in the knowledge-producing sector. We show this implicitly assumes no market power and no productivity in the production of knowledge. We set out an alternative approach that focuses on the downstream knowledge-using sector, the final output sector. The science policy practice of using the GDP deflator is a simple variant of this approach, while the full approach allows market power and implies backing out the price of R&D from final output prices, factor costs, and TFP. We estimate a R&D price for the United Kingdom from 1985 to 2005 using the full approach. The index falls strongly relative to the GDP deflator suggesting conventionally-measured real R&D is substantially understated.

Accounting for the UK productivity puzzle: a decomposition and predictions

This paper revisits the UK productivity puzzle using new data on outputs and inputs and clarifying the role of output mismeasurement, input growth and industry effects. Our data indicate an implied labour productivity gap of 13 percentage points in 2011 relative to the productivity level on pre‐recession trends. We find that: (a) the labour productivity puzzle is a TFP puzzle, since it is not explained by the contributions of labour or capital services; (b) the reallocation of labour between industries deepens rather than explains the puzzle (i.e. there has been a reallocation of hours away from low‐productivity industries and toward high productivity industries); (c) capitalization of RD (d) assuming increased scrapping rates since the recession, a 25% (50%) increase in depreciation rates post‐2009 can potentially explain 15% (31%) of the productivity puzzle; (e) industry data show that 35% of the TFP puzzle can be explained by weak TFP growth in the oil & gas and finance sectors; and (f) cyclical effects via factor utilization could potentially explain 17% of the productivity puzzle. Continued weakness in finance would suggest a future lowering of TFP growth to around 0.8% p.a. from a baseline of 0.9% p.a. (This abstract was borrowed from another version of this item.)

How important are mobile broadband networks for global economic development

Since the beginning of the 21st century mobile broadband has diffused very rapidly in many countries around the world. This paper investigates to what extent the diffusion of mobile broadband has impacted economic development in terms of GDP. The study is based on data for 135 countries (90 countries once controlling for capital, employment and human capital) for the period 2002–2014. The results show that there is a statistically significant effect from mobile broadband on GDP both when mobile broadband is first introduced and gradually as mobile broadband diffuses throughout different economies. Based on a two stage model we are able to conclude that on average a 10 percent increase of mobile broadband adoption causes a 0.8 percent increase in GDP. Moreover, once we control for the years since mobile broadband was introduced, we find that the economic effect gradually decreases over time. For the country with median average growth of mobile broadband penetration, this implies that the economic effect has disappeared 6 years after introduction (if introduction is defined as a mobile penetration of 1 percent).

A Response to Bill Martin and Robert Rowthorn

This note responds to a critique of our recent paper, “Can Intangible Investment Explain the UK Productivity Puzzle?†. In that critique Martin and Rowthorn (MR) present a re-working of data on labour composition which they feel refutes an element of our argument. In this response we argue that the data are still in support of our original position. Essentially, the puzzle is that measured labour productivity has been falling, but labour quality is rising, so, at least on this measure, changes in labour quality cannot explain falling productivity.