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Economists have offered many explanations. They are often seen as
re¬‚ecting different schools of thought: Keynesian, new-Keynesian,
Classical, new-Classical, Real Business Cycle theories, and so on;
which is as it should be, because it would be most odd if all slumps
were the same. Throughout the 1990s that post-war economic
miracle, Japan, experienced an economic slump that has only now
begun to show signs of ending. Over the past decade the of¬cial
unemployment rate in France and that other post-war economic

miracle, Germany, has been about 10%, while in the UK it has been
4“5%. The unemployment rate in the US has been in the region of
6% for a number of years. As you might expect, the countries differ
in regard to labour laws, taxation, unemployment bene¬ts, and
social security; and Germany reuni¬ed at the beginning of the
1990s. Countries in Becky™s world differ also in the mundane matter
of what criteria to use for registering someone as unemployed. We
should be astonished if one account could cover all slumps.
Limitations of space forbid that we discuss macroeconomic
¬‚uctuations and the government™s potential role in smoothing them
at a high level of economic activity. That™s a subject deserving of its
own very short introduction. Nevertheless, it will be instructive to
sketch a model that shows how that ubiquitous mental state,
expectations, can play a role in bringing about slumps in the market

So consider a situation where, for one reason or other (perhaps
because of rumours: Chapter 2), producers believe demand for their
products will be low. It would then be in each producer™s interest to

cut back production, run down inventories, and reduce the demand
for labour. If the supply of labour is constant, there would be excess
labour in the market place. If adjustments occur quickly, wages
would fall. But if wages fall, then incomes fall, which then leads to a
decline in the demand for goods and services at the level of prices
with which we began our account. That decline in turn causes the
price level to fall. But lower prices lead employers to lower their
demand for labour, so that the original short-run expectations on
the part of employers are con¬rmed. To put it another way, when
producers expect prices and wages to move together, aggregate
output doesn™t respond much to a change in the price level. Each
producer heaves a sigh of relief that he hadn™t made a mistake in his
(short-run) economic forecast, but would be justi¬ably anxious that
times were bad.

In contrast, suppose for one reason or other producers believe
demand for their products will be high. Then it would be in each

producer™s interest to maintain (even raise) production and build
up inventories. An analogous piece of reasoning suggests that such
beliefs could be self-con¬rming in the short run. Each producer
would heave a sigh of relief that he hadn™t made a mistake in his
economic forecast, and would feel justi¬ably jubilant that times
were good.

Problems are exacerbated if prices or wages are sticky. The
economist Joseph Stiglitz has shown that the phenomena of moral
hazard and adverse selection in the labour market can create
conditions where real wages are rigid in the downward direction. If
the real wage for a particular type of work is downwardly rigid and
the demand for workers at that wage is less than the supply,
obviously some workers will fail to get hired. Those who are
fortunate to be hired are better off than those who are rejected.
Economists call that state of affairs involuntary unemployment, to
distinguish the situation from one where, say, someone is
temporarily unemployed because he is searching for a better job
than the one he had earlier. That wage rigidity will not bite if

producers, buoyed by high expectations, demand lots of labour.
which is why exuberant expectations can lift an economy by their
own bootstraps to full employment.

John Maynard Keynes, Michal Kalecki, and Bertil Ohlin were
prominent among those economists who, in the 1930s,
recommended active government engagement for reviving
depressed economies. Their ideas were extended greatly by the
economists James Meade, Paul Samuelson, and James Tobin,
among others. One way to interpret the need for ¬scal and
monetary policies during severe slumps (taxes and subsidies, public
investment, interest rates, credit facilities) is that they help to
change the expectations people hold about the future. But ¬nding
the right combination of public policies can be a nightmare:
different slumps require different palliatives, which is why
macroeconomic stabilization continues to be a controversial


Chapter 5
Science and Technology
as institutions

Institutions are public goods. The problem facing a society is to
unearth what combination is likely to work best for it. In the rest of
this book we explore how institutions interact with one another. To
see what issues are involved, it will pay to begin by studying the
institutions that have been created to produce a commodity that
any reader of books would ¬nd interesting: knowledge.

Knowledge is a public good par excellence. It is non-rivalrous in
use (when someone applies the calculus to a problem, no one else
is prevented from applying the calculus to his or her problems).
Unless the producer of a piece of knowledge is secretive, it is also
non-excludable. Knowledge is a durable commodity, in that the
same piece of knowledge can be used over and over again. If
someone was to invent the wheel today, we would observe that he
had merely ˜reinvented the wheel™; he wouldn™t contribute
anything of value. Moreover, as no additional cost is involved
when someone dips into a piece of knowledge, he shouldn™t be
charged for it.

These observations are truisms today, but they raise a problem. If
knowledge is freely available to all, the only way discoverers and
inventors could obtain a return on their efforts would be by being
secretive or by earning pro¬ts from the head start they have with
their ideas. Which means that the private incentives to produce

knowledge would be low. The trick is to ¬nd more reliable ways to
reward people who discover and invent.

In using the terms ˜discoverers™ and ˜inventors™, I don™t mean to
restrict the use of the word ˜knowledge™ to the products of science
and technology; I want to include innovations in the arts, crafts,
music, and literature. Nevertheless, in offering an account of the
two overlapping institutions that have emerged in the modern era
for producing knowledge, I shall rely on examples drawn from
science and technology, conventionally de¬ned. Along the way, we
will discover that our analysis applies also to other forms of creative

By scienti¬c and technological knowledge I mean, roughly

Science and Technology as institutions
speaking, what the classical Greeks meant by them, namely,
episteme (speculative, theoretical, or abstract knowledge) and
techne (art or practical knowledge), respectively. As far as I can tell,
Aristotle regarded it impolite to discuss techne, even to enumerate
achievements in that sphere. His discourses focused on episteme. In
contrast, modern economists have attended to techne, which is
evident from our frequent use of the term ˜technological progress™
when we offer reasons for continued economic growth in Becky™s
world (Chapter 1).

Research and development (R&D) are inputs in the production of
knowledge. Publicly funded R&D is the Wicksell-Samuelson
solution (Chapter 2) to the problem of incentives in knowledge
production. For reasons that will become clear presently, I shall call
the institution of publicly funded R&D, Science (with upper case S).
For concreteness, the agency that funds R&D will be taken to be the
state, even though private foundations and large corporations in
Becky™s world augment the resources that ¬‚ow into Science from
the state.

So that the knowledge that is produced with public funds is freely
available to all, employment contracts include the condition that

discoveries and inventions are to be disclosed publicly. But
knowledge often involves technical material. How is the state to
prevent quacks and charlatans from muddying the enterprise?
Modern societies have solved this adverse selection problem by
insisting that public disclosure involves publication in peer-
reviewed journals. Vetting by peers greatly reduces a problem
society faces, namely, its inability to distinguish good products from
bad products.

But there are further problems in Science. As a good deal of
creative work is conducted in the head and success in R&D is
chancy, it isn™t possible to verify whether someone has complied
with the agreement to work hard. How is the paymaster to know
that scientists are thinking, not day-dreaming? After all, even lazy
scientists could claim that they were unlucky, not lazy. Society
therefore faces a moral hazard, implying that payment should not
be based on time or effort. An alternative is a ¬xed payment for

practising science, but that too has a problem. If scientists could
collect the fee irrespective of whether they produced anything of
interest, the incentive to work hard would be blunted; which is
yet another moral hazard. If each of these hazards is to be
reduced, payment has to be based in some way on performance.
Such forms of payment are called piece rate. In the present
context, ˜piece rate™ means payment on the basis of the quality of
the product of R&D.

For reasons similar to the ones I have just enumerated, piece rates
used to be a commonplace for casual labour in agricultural harvest.
Today, machines set the pace, which means that human effort is
veri¬able. That is why piece rates have become less common even in
agriculture. But performance bonuses, often in the form of stock
options, are today a commonplace in large corporations, for reasons
of the moral hazards facing shareholders (Chapter 6). In the
knowledge sector, a special version of piece rate payment is alive
and well and has played an enormously signi¬cant role in the
economic transformations that have led to Becky™s world.

In order to understand the version of piece rates prevalent in
Science, let us recall that a piece of knowledge need not be produced
more than once. If we were to interpret this literally, it would mean
that those who produce a piece of knowledge after it has already
been made public by someone else contribute nothing of value. That
in turn implies that only the ¬rst with a discovery or invention
should be rewarded. So as to encourage scientists to make fruitful
discoveries, the payment schedule also needs to have the feature
that, the better the discovery, the bigger is the reward. The idea
therefore is to transform research into contests.

It can be argued that, in order to encourage entry into scienti¬c
contests, losers ought to be rewarded too. The problem is that losers
could make in¬‚ated claims about their own progress once the

Science and Technology as institutions
winner discloses his or her ¬nding. This possibility would create
another moral hazard for the paymaster. The scheme that avoids
each of these problems and has been adopted by Science is the rule
of priority. Under that rule, the winner takes all that the paymaster
has on offer. Science doesn™t pay runners-up.

What I have just written isn™t literally true of course. First,
scientists are inevitably a garrulous lot, which means that
colleagues usually know roughly how far behind the winner the
losers were at the time the discovery was made public. Second, no
two scientists follow exactly the same trail, which means that losers
also produce material of interest. So, losers are rewarded too. The
˜winner takes all™ version of the rule of priority is simply a stylized
way of saying that in Science, winners are rewarded

The rule of priority is ingenious, in that it elicits public disclosure of
new ¬ndings by creating a private asset from the very moment a
scientist relinquishes exclusive possession of the discovery. In
Science, priority is the prize. In the words of the biologist Peter
Medawar, it awards moral possession of discoveries to winners,
even though no one obtains legal possession of them.

But there are problems with the rule of priority. It places all the
risks that are inevitable in R&D ¬rmly on the shoulders of
scientists. This can™t be an ef¬cient system if scientists, like lesser
mortals, are risk-averse. It would seem, after all, that in order to
encourage entry into Science, scientists should be paid something
whether or not they are successful in the contests they choose to
enter. It is in this light that Kenneth Arrow™s remark, that ˜the
complementarity between teaching and research is, from the point
of view of the economy, something of a lucky accident™, assumes its
full signi¬cance. That ˜complementarity™ explains why so many
scientists are employed in universities, and it explains why in recent
centuries universities have been the place where some of the
greatest advances in science have been made. Tenure in university
appointments, a much debated feature of employment contracts, is
a way society ties its hands not to interfere when a scientist has
reasons to follow one research lead rather than another and other
people have reasons to disagree with the scientist.

Although the reasoning I have deployed in arriving at the rule of
priority draws on the language of modern economics, the rule itself
became established much earlier than my discipline. (Societies are
usually a lot cleverer than social thinkers.) The Royal Society of
London (chartered in 1662) and similar Academies in Paris, Rome,
and Berlin were established in order to facilitate the exchange of
scienti¬c knowledge and to con¬rm new discoveries and inventions.
Those Academies also legitimized the rule of priority, administered
it, and became the arena for struggles over con¬‚icting claims to
priority. The dispute between Newton and Leibnitz over moral
possession of the calculus is only the most famous example.

But neither the rule of priority nor the Academies appeared in a
vacuum. The economic historian Paul A. David has traced their
origins to a problem rulers in the late Renaissance Italy faced
increasingly: how to choose men of science who would adorn their
courts. No doubt the evolution of institutions doesn™t follow the
dictates of analytical reasoning, but it is analytical reasoning that

explains what evolutions amount to. Even the notion of moral
ownership of creative works predates the Academies. For example,
it was common practice among bards in medieval India to refer to
themselves in their poems by name in the third person. By doing
that, the poet left a signature on his creation (mostly they were
men) “ the better the poet, the greater his fame, the larger his
audiences, and so, the greater his pecuniary bene¬ts. Scribes,
philosophers, and scholars in Eurasia had practised the open
transfer of knowledge even earlier. The anthropologist, Jack
Goody, has uncovered the ingenious ways in which creators even
in pre-literate societies left markers on their works so as to be
remembered. But those earlier practices were haphazard. What
the rule of priority did was to put the stamp of an institutional
imprimatur on creative works.

Science and Technology as institutions
There are limitations to Science. An exclusive dependence on the
public purse to ¬nance R&D is problematic, because knowledge has
two further properties: no one truly knows what the commodity to
be produced is until it has been produced; nor does anyone really
know in advance how to produce it. Of course, experts are likely to
have a better idea than others of which problems are solvable, by
what means. If society wants to ensure that a wide portfolio of
scienti¬c and technological problems is on the table, it ought to
encourage R&D activity not only in Science, but also in a parallel
institution, where discoveries and inventions are privatized. Let us
call that institution, Technology (with an upper case T).

One way to keep knowledge from being used by others is to keep it
secret. In earlier times practitioners of alchemy, witchcraft, magic,
and the material crafts (glass-making, metallurgy, the manufacture
of precision instruments), and experts at solving complex
accounting problems for merchants and businessmen (for example,
the cossists of 16th-century Germany) kept their knowledge and
skills secret. In the age of maritime discoveries, maps of trade routes
were carefully guarded. Holders of secrets were able to earn pro¬ts
from their knowledge, which is why secrecy was practised mostly

over techne. But secrecy isn™t reliable. Reverse engineering, to use a
modern term, is a danger in the crafts, as is the possibility that rivals
will make the same inventions. Monopoly rights to knowledge, or
patents, is a remedy for that problem. The patent system “ and
relatedly, copyright for images and expressions “ allows people to
disclose their ¬ndings without obliging them to share the pro¬ts
from those ¬ndings. It is a legal means of making a piece of
knowledge an excludable commodity. The system offers a private
reward for disclosure and makes the award on the basis of priority
of disclosure. Like the rule of priority in Science, the patent system
encourages contests in Technology.

The systematic use of patents began in Venice in 1474, when the
Republic promised privileges of ten years to inventors of new arts
and machines. But the forerunner of present day patent laws was
the English Statute of Monopolies in 1623. This enunciated the
general principle that only the ˜¬rst and true™ inventor of a new

11. An 18th-century patent for tuning harpsichords

manufacture should be granted a monopoly patent “ in the case of
the 1623 statute, for a period of 14 years. Even the forerunners of
modern patent laws made it impossible to patent a ˜fact of nature™,
which is why it is customary to regard patents as belonging to the
realm of techne. But recent litigations over patents in biotechnology
have shown that it isn™t always easy to agree on what is a fact
of nature.

Let me sum up in the language that was developed in earlier
chapters: behaviour in Technology is market-driven and thus
enforced by the law; whereas in Science, behaviour is community-
ridden and thus enforced by norms. Both institutions produce
knowledge; but in the former, it is regarded as a private good,
whereas in the latter, it is viewed as a public good. The incentives in

Science and Technology as institutions
Science and Technology differ in ways that encourage scientists and
technologists to regard their products in accordance with the mores
of the institution to which they belong. It should then be no surprise
that the character of what is produced also differs. The traditional
distinction between Science and Technology, which sees the former
as being concerned with basic research (whose output is an input in

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