How important are intangibles in accounting for productivity growth?

1. I was asked today: if intangible capital deepening slows, is that a big effect on productivity growth?  This is part of a broader question; what's the relative importance of intangible assets in accounting for productivity growth (value added per hour growth)?

2. Growth accounting allows a decompositition of labour productivity growth into the contributions of:  

a. reallocation = workers moving between industries of different productivity levels 

b. labour composition = increased skills, age and experience

c.  ICT capital deepening = increased ICT capital (computers, comms equip) per hour 

d.  NonICT capital deepening = increased NonICT capital (buildings, vehicles, non-ICT plant) per hour 

e.  Intangible capital deepening = increased intangible capital (R&D, software, artistic originals, design, marketing, business process, training) per hour 

f. TFP = increased total factor productivity (what's left over, which increased efficiency plus mismeasurement etc.)

Here are some results from our EUKLEMS-INTANProd database, in hopefully obvious notation.  Countries are US, UK, EU (France, Germany, Spain, Italy, Denmark, Holland, Austria, Sweden, Finland). Industries are all ommiting A (agriculture), OPQ (defence, education, health), B (mining), D-E (gas, electricity, water), F (construction).  All these are not well measured, and/or mostly public sector. 

As the results show, intangible capital deepening is much the most important contributor to labour productivity growth in the 2011-19 period (tangible capital deepening contributions is the sum of ICT and NonICT, which is still lower than the intangible contribution).

Table:  of contributions

 

And a picture

As we saw in a recent blog the employment rights bill will very likely lower intangible investment. That will lower intangible capital deepening, other things equal.  This then is a policy measure lowering the major source of UK productivity growth.  Not a good policy if you want growth to increase. 

What is a log point? 100*ln(new/old).

 Nerdy. Often when doing growth in Economics, we use change in natural logs.  For a change to y from x, the log point change = 100*ln(y/x).   So a change of 1 in the natural logs, which we often call "1%" is 100 log points.  

If a dataseries rises from 100 to 100.5, then: 

a. the % change is 0.5%

b. the change in the natural log is 0.0049875

c. the change in log points is 0.49875

If a dataseries rises from 100 to 101, then: 

a. the % change is 1%

b. the change in the natural log is 0.00995

c. the change in log points is 0.995

A basis point is defined as: 1bp is 0.0001 = 1/100th of 1%.  Or 100bps are 0.01 = 1%.  One might be tempted to say 0.995 log points are 99.5 basis points, but that's not often done.

Will building more houses boost growth?

An excellent meeting at the Resolution Foundation this morning discussed this point, following their new report, "The growth mindset: Sizing up the Government’s growth agenda" by Emily Fry & Gregory Thwaites.

1.  The new government is commited to building more houses.  It says this will boost growth, see their note 27.

2. Let's first be clear on levels and growth.  Will building more houses boost the level of GDP?  As Rupert Harrison on the panel said, this is what most people think. 

To most people, building more houses means allowed more people wearing hard hats producing some output. Surely that that must boost GDP?  Part of the job of economists, aside from quantifying things, is to point out unintended consequences. It is of course true that building more houses, with nothing else changing will raise measured GDP. Part of the components of GDP is investment come up and housing is an important share of investment.  So the question is will anything else change? As Rupert Harrison pointed out, All the estimates we have for the current economy is that it is running at full capacity. That means that any additional activity in housing simply transfer's activity away from other parts of the economy. In other words, what one might loosely call unintended consequences, turn out to be the key effect. Thus there is no effect on the level of GDP Via this mechanism.

This mechanism is a demand mechanism. That is to say, the mechanism most people have in mind, of more people wearing hard hats building buildings, is a mechanism whereby there is increased demand for resources in the economy, and that increased demand raises GDP common sense GDP measures the resources that the economy is producing. As is clear in this example, GDP will only rise if the increased demand is matched by supply (Or if there is surplus capacity in the economy set the increased demand does not displace any existing activity).

3. So what is the effect on supply? This is where the resolution foundation report very helpfully does the mathematics.

Their Figure 5 below sets out the data.  

The extra new housing that the report identifies turns out to be around 1.1% of the stock of housing. This in itself is an interesting number and shows the value of undertaking these calculations.  The announced target, of 1.5 million homes over 5 years sounds like a large number. But this is an extra 60,000 homes per year over and above what we are already building. The key point is that there are around 30 million dwellings already existing. Thus the additional building over 5 years is around 0.2% per year of the stock of existing buildings. Thus the question is: what is the additional effect on the supply side of the economy of increasing the stock of existing buildings by 0.2% per year?

Is that we need to know how much extra output we get from a certain percentage change in the capital stock. Such extra output comes from the fact that increased capital stock raises the flow of capital services that are available for people to use in the economy.

The answer to that question sounds like an engineering answer. But this is where the economics of growth accounting comes in useful. If firms are behaving in any way rationally, they will equate the marginal product of capital to the real cost of capital. So for example if it costs British Airways $20 million to rent a Boeing 737 for a year they wouldn't bother to rent it unless they could make at least 20 million dollars per year in revenue.  But the real cost of capital is, in turn, the rate of return to capital which is something that statistical authorities calculate, for the UK, non-Continental Shelf firms, this is about 10%.

So there are two ways of getting to the percentage change in GDP: either the rate of return times the change in capital per unit of output, or the rate of return, expressed as a percentage of the baseline Y/K ratio, times the percentage change in capital.  For the latter, the Y/K ratio for the economy as a whole is around 3.3, with the housing share of the total economy capital stock of 40%.  So that the rate of return as a percentage of the baseline Y/K is 0.1*3.3*0.4 = 0.132.  If we then multiply that by the %change, of 0.2% per year, we get an increase in the growth of 0.0264 percentage points per year.  

Update.

Another method is this (see Frontier economics, note 6 and the note to Table 3).  The elasticity is the rate of return times the K/Y ratio.  In the steady state, I=deltaK.  So K/Y is (I/Y)*(1/delta).  I/Y is about 0.2.  Delta is about 0.07.  This gives an elasticity of about 0.3 

Long run economic growth in the UK

 A fascinating new paper by Stephen Broadberry,The Industrial Revolution and the Great Divergence: Recent Findings from Historical National Accounting, looks at new long run data for the UK.  It takes up the point that much pre-1870 data e.g. in Maddison's database was based on guesstimation and we now have improved data.  Here is my reading of some of the key points.

1. Their figure 1 below shows some long run trends.

 

 

 

 As they say, some of the key findings already were that economic growth was slower in the Industrial Revolutoin than previously thought, which means the UK must have entered the Industrial Revolution richer than previously thought, to get to the same agreed final level of GDP per head.  

"Figure 1 shows the long run evolution of real GDP, population and real GDP per capita over the long period 1270-1870. GDP per capita stagnated during 1270-1348, before increasing sharply between 1348 and 1400, as population declined more sharply than GDP following the shock of the Black Death. GDP per capita then remained on a plateau between c.1400 and 1650 as population at first continued to fall and then began to recover from the late fifteenth century. A new GDP per capita growth phase started around 1650, as population stagnated and then declined slightly. Although GDP per capita growth slowed down after 1700 as population growth resumed, it remained positive and became increasingly stable, with fewer and milder years of negative GDP per capita growth. It seems, then, that the Industrial Revolution was less about growing faster and more about avoiding periods of negative growth or shrinking, than has previously been realised (Broadberry and Wallis, 2017)"

 

2. Table 2 

 "Table 2 presents the average annual growth rates for the same three series: GDP, population and GDP per capita. Notice how the growth rate of GDP per capita after 1800 was actually slightly slower than after the Black Death (1350s-1400s) and after the Civil War (1650s-1700), despite the fact that GDP growth was much faster. The reason for this was the very different paths of population in these three periods. Whereas population declined very sharply after the Black Death, and still declined slightly after the Civil War, it grew very rapidly during the first two-thirds of the nineteenth century. This points to a major difference between modern economic growth and pre-industrial growth, as highlighted by Kuznets (1966). Preindustrial growth required falling population, and this led to an increase in land per capita and capital per capita, which in turn led to higher output per capita. However, this was clearly not a route to sustained growth. For Kuznets, sustained or modern economic growth required rising output per capita together with a growing population."

 3. Structural change

"Another important aspect of modern economic growth is structural change. It has long been noted that economic development is associated with a shift in the structure of the economy away from dependence on agriculture. This has traditionally been seen as a process of industrialisation, although recent research suggests that this understates the role of services. Broadberry, Campbell, Klein, Overton and van Leeuwen (2015) note that the British economy diversified away from agriculture over a longer time span than was once believed by economic historians. Agriculture was less important and services more important earlier than widely perceived, with important consequences for sectoral productivity performance. Labour productivity growth was faster in industry than in agriculture during the Industrial Revolution rather than the reverse, as early quantification of the Industrial Revolution had appeared to suggest. The quantitative dimensions of the structural shift away from agriculture in the British economy are set out in Table 3. The first point to note is that agriculture’s share of output and employment declined in importance over time, while the shares of industry and services increased, as would be expected for a developing nation. Second, however, note that even as early as 1381, agriculture accounted for less than 60 per cent of employment and less than 50 per cent of nominal GDP, so that even in the fourteenth century, industry and services accounted for a substantial share of economic activity. Third, although agriculture accounted for a smaller share of output than employment for most of the period under consideration here, thus making agriculture a low productivity sector, this had ceased to be the case by 1801, a point first noted by Crafts (1985). Fourth, although industry increased its share of nominal GDP more rapidly than services until 1700, this ceased to be the case during the Industrial Revolution period. This may at first sight seem surprising, but can be explained by a decline in the relative price of industrial goods, as technological progress increased productivity and drove down prices. By contrast, the more modest productivity improvement in services led to an increase in their relative price, so that the share of services in nominal GDP increased more rapidly than the share of industry after 1700.

 

A fifth striking feature of Table 3 is that much of the shift of labour from agriculture to industry occurred before 1759, which has important implications for the pattern of labour productivity growth before and during the Industrial Revolution. (my italics) If, as was once believed, the shift of labour from agriculture to industry had taken place at the same time as the Industrial Revolution, then much of the growth of industrial output could be explained by increased labour input rather than by productivity growth. This counter-intuitive result was implicit in the work of Deane and Cole (1962), and also confronted more explicitly by Crafts and Harley (1992). With much of the shift of labour from agriculture to industry occurring between 1522 and 1759, there was a period of labour-intensive industrialisation (or proto-industrialisation) without dramatic industrial productivity growth, which can be tracked in Table 4. This was then followed by an Industrial Revolution, where capital deepening and technological progress raised industrial labour productivity rapidly after 1759.

 

4. Comparative growth

 

Finally, they have fascinating conclusions on comparative growth, addressing the argument about just when Europe got ahead of Asia.

 New estimates of GDP per capita during the period 1000-1870 have recently been produced in a number of European and Asian economies, making use of historical data collected at the time. These estimates show reversals of fortune within as well as between the two continents. First, they show a much clearer Little Divergence within Europe between the northwest and the rest of the continent than had been suggested by Maddison (2001), with Britain and the Netherlands overtaking Italy and Spain. Second, these estimates also show a much clearer Asian Little Divergence, with Japan overtaking China and India. And third, they show a later Great Divergence between Europe and Asia than suggested by Maddison, taking account of regional variation within the two continents. Although individual European nations or small regions were ahead of the whole of China as early as 1300, the leading Chinese region did not fall decisively behind the leading European nation until the eighteenth century. This is a lot later than suggested by earlier western economic historians such as Weber (1930), Landes (1969),or North and Thomas (1971), although not quite as late as suggested by Pomeranz (2000), who argued for parity until the early nineteenth century. However, Pomeranz (2011; 2017) has more recently accepted that his earlier claims were exaggerated and now sees the Great Divergence as dating from the eighteenth century.

 

 

Finally, some lessons for process.  

"One of the most interesting developments of the recent wave of research in historical national accounting has been the construction of annual estimates of GDP per capita reaching back to the thirteenth or fourteenth century for a number of countries. Using these data, a radically new picture of the Little and Great Divergences has appeared. Northwestern Europe forged ahead of the rest of Europe and also diverged from Asia not by growing faster during periods of positive growth, but rather by reducing the frequency and rate of shrinking during periods of negative growth (Broadberry and Wallis, 2017)....

 "Explaining the Industrial Revolution has more in common with solving the problem of development today than is usually acknowledged. Getting growth going in the first place, the traditional focus of analysis, is only part of the story. Just as important is ensuring that periods of positive growth are not followed by periods of negative growth, or shrinking. This has been highlighted in the case of developing economies today by Easterly, Kremer, Pritchett and Summers (1993) and Pritchett (2000). For the transition to modern economic growth in Britain during the Industrial Revolution, it means paying as much attention to the absence of negative trend growth after the gains of the post-Black Death growth episode as to the innovations that started episodes of positive growth during the eighteenth century."

". One way to think about Europe’s Little Divergence, and also the Great Divergence, is therefore not so much the beginning of growth, but rather the weakening and ending of periods of shrinking"