Transcript pptx

Basic research and economic growth
With some reflections on the impact of
astronomy, its large facilities and
educational efforts
Paper at http://hdl.handle.net/1887/18636
Overview
• Astronomy’s four economic roles
• Research and growth literature
• Modeling technology and applied R&D
• Modeling basic research.
• Return on applied R and D and basic research
• Science policy implications
• Astronomy’s four economic roles revisited
Astronomy’s four economic roles
• Economic impact of astronomical results
• Knowledge spin-offs of instrument building
• People spin-offs
• Civilizing influence of astronomical knowledge
3
Economic impact of astronomical results
• Copernicus observed, Newton explained and
communication satellites make money
• Mercury anomaly, Eddington’s starlight bending,
Einstein, and car navigation systems
• Today: dark energy, high energy accelerators in
the sky, astronomical work like that of George
Miley; tomorrow new basic physics, next century
new industries?
• Insurance: Near Earth Objects, communication
disruption warnings
4
Knowledge and people spin-offs
• Old paper by Ben Martin and John Irvine (1981)
• Cutting edge instrumentation leads to spin-off
results in other industries (cf. examples on the
internet; George Miley’s LOFAR ground based
sensor network).
• Both instrument building and pure astronomy
lead to excellently trained young people, popular
elsewhere in research and in industry.
5
Civilizing influence
• Steven Pinker (2011): why has violence declined? Both
violent crime and war. Refers to Elias: the civilizing process
• Knowledge is a civilizing force (p. 174): “[…] people […] had
more to read about. The Scientific Revolution had revealed that everyday
experience is a narrow slice of a vast continuum of scales from the
microscopic to the astronomical, and that our abode is a rock orbiting a
star rather than the centre of creation.”
• This broadening of horizons adds a dose of humanitarianism
to peoples minds, increasing empathy and reducing violence.
• George Miley’s Universe Awareness perfectly fits the bill of
the civilizing process
• Economic impact of lower rates of violent crime and of war
needs no arguing
6
Quantifying economic impact of research
• Empirical macro case studies: discoveries (‘One half of our
GDP is based on quantum mechanics’)
• Empirical regional studies: spin-offs from facilities,
calculations of regional science based employment and
business (Silicon valley, bio-science parks)
• Empirical innovation studies based on innovation surveys
(what are the sources of knowledge and ideas in innovative
businesses), patent data bases and cooperation patterns in
scientific publications by people from business
• Empirical econometric studies: higher growth in countries
that spend more on R& D ?
7
Doubts
• Dutch CPB (Government institute for economic policy
analysis) said last week that they neglect impact of science
funding on economy because they don´t know how to put it
in a model.
• Empirical literature inconclusive because the attributions of
economic effects to R&D are debatable: what would have
happened if the money would have been spend directly on
productive engineering projects or on applied R&D?
• Therefore let’s start at the other side: how does economic
growth occur and what are the relative roles of capital,
applied R&D and basic research.
• This means turning to the macro-economic theory of
economic growth
8
Research and growth literature
9
Growth literature: production function
Y GDP
A Constant
f Linear homogeneous, K Capital stock, L Labor force
•
•
•
A is called ‘Total factor productivity’
If A grows exponentially: constant rate growth of
factor productivity
Also called ‘technological progress’
Neoclassical growth: Robert Solow (1960)
• Production function plus capital accumulation (based
on saving)  sustained per capita growth
• Technological progress needed
• This result earned Solow the 1987 Nobel and caused
more attention for innovation
• But: until 1990 technological progress was
exogenous (“Manna from heaven”).
• Then endogenous growth theory
11
Endogenous growth: basic model
• A seen as stock of knowledge, produced by R&D: research
labor using the existing stock of knowledge.
• Then technological progress proportional to amount spent on
R&D
• Constant level of R&D = constant rate of economic growth.
• More R&D: higher rate of economic growth.
• But there is a ‘scale problem’: large country spends more on
R&D and must have higher growth rate.
• And: GDP growth means more money for R&D, thus more
technological progress, yet more money for R&D, ……….
• Economy explodes
Taming the scale problem
Diminishing returns
• Knowledge accumulation progressively more difficult
• Then growth of A no longer proportional to amount of R&D
• Explosion vanishes, but growth too. Only some very slow
growth if population grows
Need for knowledge scale dependent
• Most used mechanism: product diversity increases with scale,
equal knowledge needed for all products
• Growing number of products plus fixed amounts of R&D per
product total R&D grows
•
Growth rate depends on level of R&D again
BUT
• Extreme fine-tuning of unknown parameters needed
• Measurement tough and inconclusive (Donselaar)
• Relation between country size and product diversity?
• Disaggregation of R&D extremely difficult.
• Therefore almost no policy conclusions
• Policy (such as top-sectors) more hype and fashion
than solid theory
Modeling technology and applied R&D
Trial and error
• Technological progress is not accumulation but trial and error
discovery (Kortum, 1997)
• Solutions, ideas, possibilities tried out all the time, the best are
retained and replace current practice:
• Repeated sampling and selection from random distribution of
technological possibilities, the technology function.
• The number of technological possibilities falls off with
increasing productivity: distribution is skewed, with a long tail
• I use inverse power law (= Pareto distribution), common in
scientometrics but also in income distribution
Pure trial and error (pre-industrial)
• Before scientific revolution: a-select trial and error until
something better than current practice is found
• The higher the level achieved, the more additional
experimentation needed for further progress
• Thus no growth; or very slow growth if means for
experimentation grow by population growth.
• As diminishing returns case, but with historical
interpretation; agrees with very long term growth data.
Experimental learning
• Suppose there is enough basic knowledge so that by
experimentation, you not just find better technologies, but
also learn to experiment with greater chance of success.
• Technology function the same, but lower boundary shifts
upward as a consequence of the experiments
China and other transitionals
• This is the situation of transitional countries such as China,
India, Brasil, Japan until 1980.
• Applications of experiments (including “ experiments” with
licensed and copied technologies) generate ever more means
for further experiments
• and render those successful too, as the lower boundary shifts
upwards.
• Easy to prove that this generates double digit, explosive
growth
• Until catching up with the advanced economies and running
into lack of basic knowledge. Cf. Japan from 1980 on.
• Newton spent half his life on alchemist experiments that we
now know, from basic knowledge, to be fruitless
Modeling basic research
The hypothesis function
• Basic research is: developing hypotheses, testing whether they explain
the experimental results, retain the best, and continue.
• At any level of technology basic research is needed until experimental
results are explained and further experiments with lesser results can be
avoided. Thus:
• The hypothesis function: the distribution of basic research hypotheses
• Trial and error of hypotheses until their explanatory power exceeds the
minimum level of the technology function.
• Then the technology level increases and the process repeats at a higher
level.
• Again let the shape of the hypothesis function be Pareto with the same
shape as the technology function
• How fast can hypotheses be developed and tested? I assume:
• proportionality with amount of basic R and D labor/spending;
• fixed rate of learning. In every field the first hypothesis requires
the same amount of work as in earlier fields, the next one a bit
less, and so on.
Modern economic growth
• This yields a nice and globally stable rate of long term
growth.
• Its value depends on two opposing forces: the downward
slope of the technology/ hypothesis function (‘how difficult
is further innovation?’) and the rate of learning in basic
research.
• If further innovation is more difficult, growth is lower.
• If the rate of learning is high, growth is higher.
• Growth depends a bit on labor growth, but if that is zero, per
capita income still grows, due to the learning in basic
research.
• Thus this is a theory of basic and applied research that
explains actual historical developments
Return on applied R&D and basic research
spending
23
Level of income and spending proportions
• The growth rate does not depend on the proportions of income that are
spent on physical capital, applied R&D and basic research
• Similar to a long standing result (Solow, 1956) in growth theory: the rate
of saving does not influence the growth rate.
• But it does influence the level of income and consumption. This is the
same for research.
• Surprisingly easy to derive the rates of return once you have the model.
• They depend on the two parameters (slope of technology/hypothesis
distributions and rate of learning in basic research) we do not yet know.
• But they are not very sensitive to these unknown parameters.
• Rather, they are very sensitive to the current levels of spending: the rate
saving, the applied R& D intensity and the basic research intensity.
• These we know from OECD statistics
Rates of return
• For the rate of saving we may use 15 %, for applied R and 1.5
% and for basic research at most 0.5%.
• Then the return on applied R&D spending is about ten times
that on physical capital investment and that on basic research
about three times higher still
• One euro extra applied R&D generates about 15 euro national
income.
• One euro extra basic research generates about 50 euro extra
national income.
Incubation time
• Great rates of return, but how long does it take?
• Time between start of new fields and application in
actual economy increases monotonously
• But average time between basic research and
applications constant
• Large and constant proportion of all spending on
basic research leads to applications within short
period
• Therefore if a country has insufficient basic research
it will be too late in picking up the useful results
26
Policy implications
Rate of learning: facilities
• Rate of learning in basic research fundamentally
determines economic growth. Main aim of science
policy should be to raise this rate of learning. Thus:
• Open access to publications and data
• Excellent high speed research networks
• Ample research facilities (small and big), and easy
access to them
Rate of learning: human resources
• Excellent training for young researchers (PhD’s)
• Reduction of learning losses by massive outflow of
PhD’s and Post Docs: much earlier up or out
decisions (tenure track selection)
• Stimulation of independence of young talent (they
learn faster and are quicker to choose the new
approaches)
• Defragmentation within universities, much easier
multidisciplinary collaboration; reduction of within
university invoice culture
Astronomy again
• Spending on large facilities such as George Miley’s LOFAR
is at least as profitable as spending on the physical
infrastructure
• Training young people in an interdisciplinary field such as
astronomy and spinning the out to other fields increases the
rate of learning in basic research in general.
• Opening children’s minds and hence societies’ minds as in
Universe awareness creates the culture needed for basic
research
• And thus lays the groundwork for sustained economic growth
and prosperity
30
Thank you for your attention!