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 

Teaching Link: Imperial college student webinar, Current economic prospects, 12 May 2020

Imperial college student webinar, Current economic prospects, 12 May 2020

Some of our Imperial College students organised a webinar last night on our current economic prospects. They kindly invited David Shepherd, David Miles, James Sefton and me to participate. Here are some notes on the questions that they set us in advance and a few notes on what was said. Thanks to our talented and interested students for organising this and participating.

Q. How does the current climate compare to previous periods of economic turbulence e.g. Spanish flu of 1918, WW I&II, the great depression? In your opinion what is the optimal fiscal/monetary policy mix to confront the liquidity crunch due to COVID? 

The BBC showed on its website the following graph saying that this was the sharpest annual downturn since 1706. So this is clearly an gigantic recession; historically unparalleled, at least since 1706m and rolling together The Great Depression, the 2008 Financial Crisis and the flu pandemic all in one go. 

Optimal mix.

The optimal mix of money in fiscal policy is a nice question. Perhaps the best way to think about it is the benchmark economics competitive model. In that model economic systems are self-correcting. If there’s a shock to a market, say to the demand for PPE, it becomes more expensive: demand is choked off and supply is increased, as firms rush to enter a more lucrative market. The two forces of falling demand and rising supply raise prices and bring the market back to equilibrium.

The second feature of the benchmark competitive economics model, is that markets are not only self correcting, but they are what economists call complete. By complete this means that goods can be transacted for. And, in particular, future goods can be transacted for via future contracts.  Of course that's exactly what we see in the real world if we're thinking about let us say oil or aluminium. Airlines buy the oil forward . And that's part of prudent business management. But when economists think of a complete market they mean that all items can be traded forward. As John Kay is pointed out, in his book “The Truth About Markets” that would mean that you could buy a futures contract in let us say 1960 for the appearance of an iPad in 1990. The fact is of course that nobody even knew what an iPad was in 1960, let alone were able to sign a contract for it. But had they done so, it would have meant that the contract could have been traded and the forces of supply and demand mentioned above would have equilibrated the market.

Now in an economy where neither of those two conditions hold then we potentially have a room for policy. Let's take the first one. Many markets especially financial markets, seemed to be complete opposite of self equilibrating, especially in periods when market participants are panicking. That is to say uncertainty over the future, which induces panic, often makes sellers of financial assets sell, without demanders coming in to pull up the price (Think of somebody who are forced into crisis to sell some asset, a so called fire sale , even when the market is very depressed). The price of the asset falls and falls, thereby amplifying the original shock.

As for the second condition, nobody knew what COVID19 was and nobody signed a contract on it: in this case nobody insured themselves against its possibility. So we've had a very large adverse shock against which nobody took out insurance.

So the role of the state in this case , is to (1) step in if the market is in chaos and (2) to provide insurance because of the incompleteness in that market.

One important role for monetary policy is to step in when financial markets are in chaos and are dysfunctional. The Monetary Policy Committee did this in the financial crisis.

As for insurance, that is commonly the right role for fiscal policy. The benefit system ensures that workers have unemployment benefits if they were unlucky enough to be unemployed, and the progressivity of the tax system is such that when incomes go down taxes are effectively cut, so-called automatic stabilisers. That provisioning of insurance of course involves borrowing and involves perhaps paying out large amounts of unemployment benefit now, to be funded by the state, but then paid back by future taxing and borrowing once the economy has been restored.  

The right mix of monetary and fiscal policy depends upon institutions that we currently have in place.  The burden of insurance provision should lie with the fiscal authorities. Note however that as part of inflation targeting an independent central bank might want to undertake more expansionary monetary policy than would otherwise be the case if it wanted to avoid scarring; that is to say, if its inflation target would be imperilled if a prolonged recession lowered the potential output in the economy.   See Powell’s speech today (https://www.federalreserve.gov/newsevents/pressreleases/other20200228a.htm).

·         Do you expect a mild recession with a V shape recovery, a greater recession with a U shaped recovery or an L shaped deep depression? What are 'the city' thinking and how are they modelling excess risk/uncertainty into long-term economic models/predictions?

In our most recent monthly policy report The Bank of England have felt that the situation is so uncertain, and the historical parallels so difficult to discern, that it is unable to have a definitive forecast . Instead it produced a scenario, being an outlook based on the series of what at the time seem reasonable judgments. That scenario in Chart 1.3 below has a very sharp fall in GDP and then a slow recovery.  So overall UK GDP falls by 14% in 2020. Activity then picks up in the latter part of 2020 and into 2021 as social distancing measures are relaxed. That said GDP doesn't reach the pre covid level until the second half of 2021. So in 2020 GDP falls by 14%, in 2021 it rises by 15% and in 2022 it rises by 3%.

. 

The chart below shows what other forecasters expect for 2020 Q 2. The bank is somewhere in the middle of these averages. 

The report notes a number of downside risks to this scenario. One of course is the position of the world which is currently extremely difficult. A second which other commentators have looked at is the possibility of further waves of the pandemic. This is obviously a matter for epidemiologists but it is of interest to look at the chart below, put together by some London Business School economists pointing out that belief the death rate from Spanish flu came in three waves.  It is perhaps also worth pointing out do we don't yet have a vaccine for AIDS, thus the question of whether we will eventually have a vaccine is still open one .  Still another important point came out in the discussion last night. It is that it's very difficult to know how to interpret the recent fall and death rates because we are so uncertain as to what the level of infection in the community might be. The range of estimates seems to be from 5 to 65%. Of course, if the level of infection is very high, this is potentially extremely good and important news, because it means that the lockdown can be released. We urgently need to know what this number is. Perhaps the proliferation of tracing apps, the national launch of the NHS app, and Professor Tim Spector’s app from Kings College might help us.

Finally, the other sets of sensitivities would be around scarring. As mentioned above this is the possibility that the long-term supply potential of the economy is so damaged that it is difficult for the economy to come back again consistent with low inflation.  A number of scarring mechanisms exist. One is obviously the idea that if there was an extended period of unemployment workers would lose their skills and motivation. The second is that there may be a permanent structural change in the economy such that a number of capital assets (think airports) are simply as not usable and productive in the current economy as before. Of course capital can be reallocated but if that takes a time then the supplies potentially the economy can potentially be disrupted.  And of course it does look like they're going to be need to be some capital assets which will have to be increased: say, hospitals, delivery equipment and social distancing infrastructure.

·         What will be the long term impact of QE/Debt monetisation on interest rates and inflation post-COVID?  How will we pay-off the debt: taxation, austerity, growth, or a combination of the three? How does this marry-up with political decision-making and public opinion?

This raises a number of key questions. Let's go through them one by one .

The first point is what will happen to R*. To recap R*is the neutral rate of interest , that is to say the rate of interest at which resources completely utilised, and  unemployment and inflation are stable. It is indeed the case that central banks can influence short term interest rates but the long term interest rate is something typically beyond their control. So for example the large increase in demographic ageing in the last 30 years and the associated high demand for savings for a longer old age, is widely held to have depressed the equilibrium interest rate. Equally there appears to have been a fall in the demand for capital, perhaps caused by the increase of use of intangible assets which likewise pressed down on the equilibrium long term interest rate. So the key question is what happens to that future interest rate after this crisis?

One possibility is that it will increase as the demand for capital and demand for debt rises in the face of large borrowing by central banks and governments. Against that if there were an outbreak of precautionary savings in the face of the uncertainty around this shock , then there will be strong pressure for the rate to fall even further. We don't know what the balance of these forces is going to be. At least in the short run the amount of saving is strongly correlated with unemployment and the fear of unemployment. If unemployment rises and stays high that would typically drive saving up comma and if that were, common throughout the world that would drive the equilibrium real rate of return down.

So if the equilibrium interest rate falls further or at least stays low, that of course is very good news for what will of course be highly indebted governments. That said, we will need to boost growth in order that even at very low interest rates the economy can grow sufficiently to pay off what will be almost certainly a greatly increased debt burden.  And indeed was a bit of discussion at the session as to what his oral experience can tell us. The debt to GDP ratio was extremely high After World War One World War Two and rather earlier the Napoleonic wars. In the case of the Napoleonic wars in World War One the debt was reduced essentially via growth and low interest rates. That was also the case after World War 2, although inflation did play a role. So there is historical precedent for having high debt burdens and there is historical precedent for their being reduced by the joint forces of economic growth and interest rates.

In that respect QE is a minor player.  

Q. The Fed was quick and effective to launch stimulus programmes to contain the freefall in markets by providing mass scale liquidity. Warren Buffet recently commented that due to Fed intervention asset prices haven't bottomed out, making investment opportunities less attractive. Do you think the market has bottomed out? What are the asset price implications if lockdowns continue, albeit intermittently, until 2021? i.e. returns on stocks, bond yields, ETFs, safe haven assets such as gold.  Given the flight to safety we're seeing in capital outflows, what are the implications for FX rates between strong currencies (e.g. dollar, euro) and EM currencies? Could the massive scale QE cause the dollar to depreciate?

The session finished with some discussion of the above couple of questions. The difficulty of forecasting interest rates exchange rates made most people rather non-committal, beyond the observation that the US dollar always seems to stay strong in periods of panic , as people seek refuge in the world’s reserve currency. Finally, the future of the housing market. The interesting issue here is whether our experience of working from home, and the possible worries about taking public transport , might get us to a situation in which there is simply much less demand for both offices in general, but also office space,. That fall in demand may well have important effects reducing prices and rendering housing more affordable.  Another example of an equilibrating market? 

Various teaching links

We discussed the role of the state in the last section of class on Wednesday. Here is a typically insightful essay by Tim Taylor on what the state can and cannot do.

What is the Impact of Universities on the UK Economy?

Universities UK alert me to a report, The impact of universities on the UK economy, PDF here, from April 2014.

What does it say?  Here is a quote

The report highlights universities’ increasingly significant impact on the economy in terms of output, contribution to GDP, job creation, and overseas investment. It also estimates the economic activity generated elsewhere in the economy through the knock-on effects of expenditure by universities, their staff, and international students.
The report finds that in 2011–12, the UK higher education sector:
• generated over £73 billion of output – up 24% from £59 billion in 2009
• contributed 2.8% of UK GDP in 2011 – up from 2.3% in 2007
• generated 2.7% of all UK employment and 757,268 full-time-equivalent jobs
• generated £10.7 billion of export earnings for the UK

In the report, P.4 we have some multiplier or rate of return type calculations

For every 100 full-time jobs within the universities themselves, another 117 full-time-equivalent jobs

were generated through knock-on effects. 373,794 full-time-equivalent jobs in other sectors of the

UK economy were dependent on the expenditure of the universities.

• For every £1 million of university

output a further £1.35 million of output was generated in other

sectors of the economy. This meant that anadditional £37.63 billion of output was generated

outside the universities as a result of theirexpenditure.

•For every £1 million of university GVA a further £1.03million of GVA was generated in other industries.

And this enables the website to say

Universities generate more GDP per unit of expenditure than other sectors including health, public administration and construction

What was done to get these estimates? P.6 says

The model used was a purpose designed and specially constructed ‘type II’ input-output model

based on actual UK data derived from the Office forNational Statistics’ input-output tables together with

data from its Blue Book.

And this is in fact a method which is widely used in many other studies, e.g. the impact of tourism.  

 I would think that most economists don't know anything about this method, despite it using Economic data and answering an economic question. And you never read this kind of thing in reputable economics journals.  Indeed, in a review of the method, Siegfried et al say,
The Economic Impact of Colleges and Universities, that this kind of work is damaging to universities

"If these economic impact studies were conducted at the level of accuracy most institutions require of faculty research, their claims of local economic benefits would not be so preposterous, and, as a result, trust in and respect for higher education officials would be enhanced."

 So what is going on?  Siegfried et al have a very good review, which I try to outline here.

1. The basic method in this work uses input/output tables.  All statistical agencies produce such tables.  Suppose the economy consist of dairy farmers, milk bottlers and opera singers.  An input/output table describes the inputs and outputs of industries and products, so for example, the farmers produce milk, which is an input to the bottlers, who then sell to the opera singers.  At the same time, farmers like opera, so the output of the opera industry is an input into farming.  Such a method can therefore tell you the payment flows between sectors. (Wonkish note: such data depends on detailed purchase information, current UK tables use purchase data from 2004).

2. Does this answer the question "what is the Impact of Opera Singing on the Economy"?  In a some sense it does.   The farmers want to listen to opera and so that is a first pass estimate of the impact on the economy.  But the opera input into farming is then an indirect input into bottling.  So one can calculate the indirect contributions as well.

3. So this is commonly how the impact of universities or football stadia or making movies is calculated.  The university is in location X.   Students pay £100 to attend.  The university buys £20 of goods and employs £80 worth of workers, say 80 workers. P.15 of the UK report therefore sets out primary and secondary or "knock-on" effects.

• The primary effect is the university spending and employment itself, (here £100 and 80 workers), the actual UK figure being £26.68bn in 2011-2. 
• the secondary effect is two types which the report calls
• indirect effects: purchasing of goods and services by the university who then buy from others e.g. buying paper, but the paper industry then buys machines etc.
• induced effects: the 80 workers buy goods, which then employs other workers etc. e.g. if a worker buys a bottle of milk, this supports farmers and opera singers via the input/output relations set out above).  

This is how the report can claim that (p.16)

"Universities spent some £26.68 billion in 2011–12. This expenditure generated £37.63 billion of output in other UK industries"

4. All this sounds very plausible.  However, but a moment's thought will show that falls prey to a key objection: what is the counterfactual? Whilst this sounds abstract it is important. As Siefried et al say

The key question posed in studies designed to measure the local impact of a

college is how much better off are area residents with the institution there than they

would be in its absence. “Better off” is usually defined as higher employment, per capita

income or local tax revenue. Both common sense and standard regional economic

analysis say the proper procedure is to compare economic indicators in the presence of

the institution with predictions of those same indicators “but for” the college – that is,

compare actual to “counterfactual” outcomes.

They continue with a key point

From this perspective that portion of an institution’s economic activity that would remain in the local area even if the institution were not there is not a contribution to the local economy. Few studies of the local economic impact of colleges and universities explicitly articulate such a counterfactual.

Take then the contribution of  college X in London.  It employs, say Y cleaners.  Is the contribution to include those cleaners?  The correct counterfactual is to ask "would those cleaners be employed without college X?"  Or take students.  The correct counterfactual is to ask "would students be students without college X?" If the answer is that cleaners would anyway be cleaners and students anyway students, then the college is making no additional contribution.

Or, take a university hospital.  Without the university, would there be no hospital?

So, the method in principle traces through the network of payments currently existing (if the data are correct etc. etc. ).  But if the question is: what would those payments be if the university did not exist, the method cannot answer that without additional assumptions.

5.  Let us make an assumption then.  In an economy operating at full employment we might then, on this measure, score the university additional contribution, that is, the contribution relative to its not being there, as, well, zero. Sure the university buys cleaning services, books and electricity (who then spend out of their sectors).  But if it were not there then in a full employment economy by assumption cleaners, books and electricity would be bought anyway.



6. Even if one wants to use the input/output method, Siegfried have some very useful points (suppose you think about a rural university, which if disappeared, would not be replaced).

• studies often count spending by students and also the college. Be careful of double counting.  When a student spends on fees that then leads to spending by the college, so counting both is wrong (counting a student spend on haircuts is ok)
• be careful if a student would have gone elsewhere in the area.  The additional contribution to London of a university in London should not include a student who would have gone to another college in London.  
• In practice many University hospitals spending dominates spend.  These should not be included.  They say "
  
  The revenues and expenditures of university hospitals usually dwarf the rest of the institution. Seldom
  do medical center expenditures contribute much to local economic development, however. Teaching
  hospitals usually are surrounded by other acute care medical facilities. In such circumstances, were the
  university hospital to evaporate, most of the medical services provided by it would be assumed by other
  local hospitals. Only patients with specialized medical problems would likely turn to hospitals outside the
  area. Thus, most university hospital expenditures should not be included in the first-round of expenditures,
  perhaps an exception being isolated university hospitals that serve broad geographic areas in the plains and
  mountain states". 

 7. Note that ascribing benefits of educated workers, which is often done, is not clear either.  Educated workers get some of the benefits from themselves in terms of higher earnings, but they might move from the area and might be in the area anyway even if there was no college (and such local benefits might just be capitalised in local house prices).  If there are spillover benefits to lower crime etc. that might be included however, again, as long as those graduates would not have been in the area.

8.  Finally, a note from my time at the Treasury.  One week an official might get this kind of report, suggesting universities support 10% of GDP.  Next week, movies support 15% of GDP and the following week the car industry supports 25% of GDP.  Pretty soon, these reports account for 150% of GDP.  This tells you there is a fallacy of composition, which is again a consequence of the counterfactual: all these reports typically assume that particular industry in question would not exist at all and no other indirect effects would occur.  So reports like this will not convince officials in the Treasury at least.

These are the main objections to these types of methods and suggest different methods might be used that properly show the additional contributions.  One such is the point that university knowledge spillovers to firms are often local and specific to the university: our work on spillovers from the science base for example. 

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 https://spiral.imperial.ac.uk:8443/bitstream/10044/1/21171/2/Haskel%202015-03.pdf

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, http://www.ft.com/intl/cms/s/2/7da2852c-e3af-11e4-9a82-00144feab7de.html#axzz3XZSthOA9

More on the public science base

Here's a new report

The economic impact of Russell Group universities

http://www.russellgroup.ac.uk/uploads/Economic-impact-of-the-Russell-Group_1.pdf.

It's an example of the kind of work that HM Treasury will not be convinced by.  Some of the work, see Chapter 8, takes spending on universities and multiplies it by a rate of return.  For medical research, this rate of return is poorly estimated. Other parts of the work take  e.g spend on construction by employment in construction plus employment supported by constructoin workers buying cups of tea etc. But what is the counterfactual?  Would all those workers and tea-makers be unemployed if these projects did not go ahead?

Various teaching links

1. Economics: the biggest fraud ever perpetrated on the world?

Via Pereia we have this question:Economics: the biggest fraud ever perpetrated on the world?

People outside Chemistry would never go round saying that Organic Chemistry was the biggest fraud ever in the world.  They would not have the knowledge to judge.  I find it disappointing that non-economists seem to be able to make these assertions not knowing about Economics.  Or, more accurately, they seem to have a view of  the kind of Economics poorly taught to them in the dim past.  I hope they come to Imperial to study it and get a different view.

2. The Age of Edison by Ernest Freeberg
As a piece of technology history, I like this book and a nice review here.

3. More on the history of technology

Is ICT like electricity?  Chad Syverson paper
Is ICT like steam? Nick Crafts paper.

4.  Don Boudreaux 

On the perennial topic http://cafehayek.com/2013/10/on-the-relatively-low-salaries-of-relatively-essential-workers.html. Why are essential workers, like firefighters, so poorly paid relative to inessential workers like football players?  I do wonder however if the logic is right, about bankers. Are their skills really in such short supply?  The additional ingredient is, I think, the too big to fail subsidy. 

Teaching links

A hostile report on evidence-based policy by Jamie Whyte from IEA gives a nice example of adjustment along many margins:

Seeking to improve the diets of its pupils, a school in Northamptonshire
banished vending machines in 2006. William
Guntrip, an enterprising thirteen-year-old pupil of the school,
spotted the profit opportunity this created. He started buying
large quantities of sweets and soft drinks and resold them in the
playground, making a profit of £50 a day.  (School bans boy’s snack empire’, Metro, 4 July 2006). 

Innovation Matters: Reviving the Growth Engine

I have had the pleasure of working with McKinsey who have done  a report that was presented at the G8 innovation summit 14th June 2013 last week.

The webpage is here.
The report is here.
The YouTube video presentation is here and the program of presenters, including David Willetts and the PM is here. 

Infrastructure

To those who think that infrastructure spending will solve our problems, today's FT suggests, to me at least, how hard the politics around this are. Here's then minister Peter Mandelson,

"In 2010, when the then Labour government decided to back HS2...We were focusing on the coming electoral battle, not on the detailed facts and figures"

Even then the facts and figures are pretty hard to sort out:

" The cost-benefit analysis for the rail scheme assumes that faster trains will produce £21bn of economic benefits simply because passengers will spend less unproductive time.

 Hilary Wharf, director of the HS2 Action Alliance, said £21bn of the £48bn of forecast economic benefits from HS2 depended on the assumption that people did not work on trains.

Philip Rutnam, permanent secretary at the Department for Transport, admitted that the modelling was based on a survey that was now “a decade old” – before the era of handheld devices.

A report for the DfT in 2009 found train journeys had become much more productive. “The obvious causes of this trend are in the general availability and use of mobile phones and laptop computers,” it said.  Yet the HS2 analysis has not taken this change into account. “We are seeking to revise that,” Mr Rutnam told the public accounts committee of MPs, revealing that an altered business case would be published in the autumn.

Can governments use procurement to boost innovation? The US story.

Many have argued that governments can improve growth by procuring “well”, that is to say, in such a fashion that will promote innovation.  In Europe there is a lot of romance about some US examples like DARPA or the SBIF or Apollo/Manhattan programs.   But what are the facts?  David Mowery gave a wonderful presentation today on lessons of procurement from the US. Here is my take on it.

1.     1.  US public procurement is separated in the data from R&D. Federal procurement is actually 63% military.  The non-defense part of procurement is mostly energy, federal housing and veterans admin (mostly drugs and hospital equipment).

2.      2. Note that DARPA and SBIR are not, in the data, procuring.  They are under separate accounts, but besides the accounting point, the important point is that there is an R&D and a procurement program i.e. two instruments.  The former might be used for R&D and the latter for buying the cheapest regardless of innovation.  Or the latter might be used to complement the former.   But with two instruments its not necessarily the case that not using procurement for innovation is missing a trick.

3.      3. The Apollo and Manhattan projects were designed deliberately not to be adopted in the private sector.  So that is very different to e.g. using procurement to trying to find a solution to a grand challenge, like health.   

4.      4. Procurement can take many firms

a.      Paying just for the prototype.   That might encourage innovation just up to an early stage.

b.      Requiring, as in the case of semiconductors, more than one supplier when procuring.  That helps competition and information sharing between the two suppliers.

c.       Paying for the whole project but not promising to then buy the final product.

d.      Paying for the whole project and also buying the final product perhaps from one supplier

5.      some practical details.

a.      Most procurement can be thought of as demand pull.  It procures a product for a particular government missions.

b.      Less common are policies to specifically encourage particular new technologies e.g. deliberately buying innovative energy products to push a green agenda.

6.      How might benefits to innovation from procurement come via the demand pull mechanism?

a.      A lead customer who buys the product might helps firms learn, give them scale economies etc.

b.      Procurement contracts might require new suppliers  or might legitimize standards.

7.      Perhaps most interesting are some cases.  

a.      The big success is IT.  In the 1950s the US military procured  a lot of e.g. software and semiconductors.  This helped Texas Instruments for example to develop semiconductors and seems to have crowded in other suppliers.  Note that one provision of this program was that more than one supplier was needed and this made sharing of information and common standards in the industry a common practice. But note that by the late 1960s, the military was buying a very small share of IT products, so exit by the public sector was important.  In addition, the projects were, in fact, highly complementary to private sector needs.  Indeed, they are the victims of their own success: the military now buys software from the private sector since it’s more advanced.   An attempt by the military in the 1980s to have its own software was a failure.  So ultimately the success was to develop something that was very complementary to private sector needs and the private sector just took over the lead.

b.      Perhaps less well known are some failures.  For example, in the 1970s/80s the USAF tired to develop CNC machine tools but they were a failure: the Japanese did much better.  Another example was civilian nuclear power.  This program focused on PWRs since they were going to be used by nuclear subs.  They were a failure, unsafe and became unused etc.

8.      so what are the lessons?

a.      If the project is aligned with civilian needs, then more chance to be widely adopted.  Very hard to say ex ante: indeed totally impossible.   Components will have more chance rather than a whole system perhaps.   Or maybe the link is endogenous, maybe procurement can try to encourage sharing etc.

b.      There’s a natural tension between wanting to get the lowest price and wanting to support innovative products which might be expensive.   But when there are two targets you need two instruments and you have this: an R&D and a procurement budget.

c.       The Apollo and Manhattan projects highlight that the purpose of the project has to be clear: they were never intended for public use, so aren’t good examples of encouraginginnovation.  Indeed, that is case where the procurement project was a different instrument to the R&D budget.

d.      Supporting prototypes might be good since they don’t mean lock into a whole project. But prototypes are impossible in some technologies e.g. nuclear submarines.

Finally, in the discussion, David Mowery made some other very interesting points.  My interpretation of them are:

1.              the romance with SBIR is misplaced.  There are very few rigorous studies of its effectiveness and what studies there are show very mixed results

2.              Much of venture capital in the US does not just supply money.  It also provides managers, help with business plans etc. that’s why some of them are very local, since they are tailor to local labor market needs.   So it may not be something that the EU can imitate by just providing money if the EU cannot also supply the other skills and advice.

3.              Regarding tech transfer, everyone seems to concentrate on the gross return that universities make from ownership of IP.  The net return, aside from some very few top universities, is very modest, because it costs a lot of money to run the office and do the work.  In particular, it costs a lot for patent attorneys (although these costs might be reduced by universities sharing facilities).

Is there a relation between growth and R&D? And why it doesn’t matter

 
A lot of interesting tweets last night from the Royal Society Innovation Debate. (Twitter mark: #innovationdebate). I couldn't go, so I am relying on the tweets I received that raised some interesting points on R&D and innovation. (There were some annoying and, IMHO opinion wrong, comments about economists which I shall return to at the end of this post).

 

 
One point raised was by @JackStilgoe "Annoyingly, national R&D spending does not correlate with economic growth. See Edgerton, http://www.historyandpolicy.org/papers/policy-paper-88.html). To which I replied "well yes, but growth is determined by other things than R&D. Taking those into account there is a correlation IMHO". And @GordonBrianR chimed in with "R&D also needed for absorptive capacity - to stay on the knowledge frontier. There is a Red Queen effect here too.".

 
So what do economists know about all this?

 
The assertion of the non-relation between growth and R&D refers to the article by David Edgerton. Now, I consider myself a friend of David and his books and expertise in this area are unmatched. On this issue however, I beg slightly to differ. Actually, I think he's mostly talking about the correlation between growth and public R&D. So let's break it down.

 
There is of course no simple bivariate correlation between growth and R&D since, as mentioned above, one has to control for other things, R&D takes time to come through etc. etc. One very thorough study on this at the company level is Foray, Hall and Mairesse, Cemi-Working paper-2007-003. They criticize the assertion of no relationship made by Booz Allen Hamilton, Winter 2006, issue 45, "Strategy and Business" and show there is just such a relation at firm level as long as one is careful with data construction, accounts for the correct lags etc. An study at the country level is Griffith, Redding and van Reenen.

 
But let me put out another thought. Who cares if there is no relation?

 
To be fair, many economists are interested in the correlation between R&D in country/industry/firm A and growth in country/industry/firm A. But most are interested in an even more interesting correlation: the relation between R&D in country/industry/firm A and growth in firm B. That is to say, one might not find any correlation at all between one entity's R&D and its growth, for it might all be relying on using R&D from another place. Indeed, part of the Royal Society's honourable tradition is to foster that very information flow, by encouraging open science and communication. And if there is such a relation then we are off to the races, for the free market might under-provide research, there might be role for subsidies and public provision, mobility of scientists and absorbtive capacity might affect such transfer etc. etc. So the lack of a relation actually makes the policy issues more urgent and not less.

 
So, I shouldn't really say that the lack of relation does not matter, but that its not right to cite that lack of relation as an indication that policy is impotent.

 
If interested, here are some additional comments from an earlier post, "Innovation: A guide for the Perplexed".
Additional comment
There were some rather negative tweets about economics which may or may not have accurately recorded what the participants said. I can only say economists never sit around at Economics conferences and complain that scientists just spend their time watching apples fall from trees. Let's base criticism of other disciplines on what they actually do, not what people seem to think they do.