How to think like an economist (and why it matters)
Presentation by Diane Coyle
at IPEG, University of Manchester, 30 May 2003 PART 1
Let me motivate this talk about
how to think like an economist by describing some eminent
figures who'd make ideal economists. What kind of people
are they? My first candidate isn't, strictly speaking, a
person. Mr Spock, first officer of the starship Enterprise,
is ultra-logical, in contrast to the emotional and
impulsive Captain Kirk. Spock is the ideal rational man, or
rational Vulcan rather, of economic theory. What's more, he
sums up the essence of utility theory as he sacrifices
himself to save The Enterprise in the movie The Wrath of
Khan. Referring to the self-sacrifice of Sydney Carton from
A Tale of Two Cities, he famously explains to Kirk that the
needs of the many outweigh the needs of the few the
greatest happiness of the greatest number.
My second ideal economist is Charles Babbage. Not only did
he open the way to the development of programmable
computers, which are such a vital tool in modern economics,
he also upheld scientific standards of rationality and
accuracy against poetic vagueness. In his poem "The Vision
of Sin" Alfred, Lord Tennyson wrote:
Every minute dies a man, Every minute one is born
Babbage wrote to congratulate him on the poem but added: "I
need hardly point out to you that this calculation would
tend to keep the sum total of the world's population in a
state of perpetual equipoise, whereas it is a well-known
fact that the said sum total is constantly on the increase.
I would therefore take the liberty of suggesting that in
the next edition of your excellent poem the erroneous
calculation to which I refer should be corrected as
follows:
Every minute dies a man, And one and a sixteenth is born
The actual number is much longer but I believe 1-1/16 will
be sufficiently accurate for poetry."
My third example is Hercule Poirot, Agatha Christie's
precise Belgian detective who solves the most puzzling
crimes with a passion for order and a disdain for tangible
evidence. He's a theorist. The purest example of his method
is in The Mystery of Hunter's Lodge, in which he solves a
murder in Derbyshire without leaving his London flat, where
he's laid up with flu. As Poirot says: "The true work, it
is always done from within. The little grey cells--remember
always the little grey cells, mon ami. "
By contrast, we have some evidence that Keynes would have
made a lousy economist by modern academic standards. He
said: "When statistics don't make sense, I find it
generally wiser to prefer sense to statistics." Ambitious
young lecturers wouldn't get many journal articles
published if they took that attitude today. In his Essays
in Persuasion Keynes in fact blows the gaff on one of the
difficulties with economics: "Economists, like other
scientists, have chosen the hypothesis from which they set
out, and which they offer to beginners, because it is the
simplest and not because it is the nearest to the facts." I
think you'll be getting the idea. Economics is based on the
assumption of rational behaviour by standardised
individuals. One of the great merits of this assumption is
that it makes conventional economic models very tractable.
But we know that few human beings live up to the
economist's standard of rationality, as it has been refined
and narrowed in practice. Hence the standard criticism of
economics: it's unreal, divorced from real life.
This isn't only an external critique. Plenty of economists
think it's valid. The University of Notre Dame is splitting
its economics department into two, putting the Spocks and
Poirots, members of the academic mainstream, into an
orthodox department, and all its Marxists, post-Keynesians,
historians of economic thought and feminists into another.
There's a growing "Post-Autistic Economics Network" which
is encouraging alternatives to the mainstream. There's
nothing new about this such criticisms have been voiced
since at least the late 1970s, a significant date I'll
return to later. I'd be sorry to see a schism in my subject
because I believe it's a uniquely important one for public
policy and civic life. I want to put forward two arguments
about it today. One, that there's much merit in criticisms
of the kind of orthodox economics that dominates the
profession, especially in Anglo-Saxon universities. But,
two, none of the criticisms is fatal, and in fact we should
take care not to devalue the real insights of economics. We
need more economic theorising, not less, in public policy.
On the contrary, I believe economics is still a
fantastically fruitful intellectual discipline. The version
of economics that's taught to most students is hugely
flawed. But the version done by economists who make it
through the purgatory of their undergraduate and graduate
courses is much richer, and there's an exciting renaissance
in several areas of the subject.
To complicate matters, there are criticisms of economics
that are valid, and criticisms that are not. I want to
start by dismissing the unimportant ones. A lot of the
unpopularity of economics outside the citadel is the price
of intellectual integrity. Unpopularity is almost the
raison d'etre of economists, who are the dirty realists of
the social sciences. Economists are the only people who
warn, constantly, about difficult choices and trade-off -
summed up in the catch-phrase 'there's no such thing as a
free lunch'. Choosing one course of action means closing
off another.
Indeed, economics is essentially intelligent skepticism,
applied to human society and politics. It's a subject born
out of the Enlightenment's elevation of the power of
reason. David Hume described the approach as "an attempt to
introduce the experimental method of reasoning into moral
subjects", to quote the subtitle of the 'Treatise of Human
Nature'. Good economics is inspired by what Hume described
as "the spirit of accuracy", which takes all the sciences
"nearer their perfection, and renders them more subservient
to the interests of society."
I think this gets to the heart of the suspicion with which
people from other disciplines regard economics. It
contradicts cherished beliefs, and does so in an
aggressively rigorous way that is often difficult to
challenge - difficult because the logic and evidence go the
economists' way. For example, great insights in economics
can amount to saying that accounting identities must add up
(as Thomas Schelling argued). The current and capital
accounts of the balance of payments must sum to zero. If
you're a net importer of foreign capital, you've got a
trade deficit. That makes it impossible for a country to be
simultaneously flooded with cheap goods and yet exporting
jobs to low wage countries - but protectionists can never
get the point.
Some critics of economics simply reject the idea that human
society is amenable to the scientific method at all, rather
than cultural analysis, (and this kind of chasm isn't
confined to economics - hence the nature versus nurture
wars). I don't have much to say about this rather sterile
dualism. Some are just innumerate, suspicious of anything
at all involving addition, subtraction, multiplication or
division (or as the Mock Turtle in Alice in Wonderland
renamed them, ambition, distraction, uglification and
derision). It's easier for the critics to attack the entire
subject and its intellectual approach. These kinds of
critics aren't worth taking seriously.
Unfortunately, other criticisms of economics have more
substance. The idea we're taught as students, that the
positive and the normative can be kept strictly separate,
is nonsense, as many of the people teaching it will
recognise. But to our cost as a profession, most
practitioners of economics - especially in universities
have taken an extreme and ultimately unsustainable view
about what it means to be scientific.
The pretence by economists, that it was possible to isolate
purely positive questions, has rebounded in the form of a
reaction inside the fortress of economics, as well as
outside, against the assumption of maximising behaviour by
rational individuals. The assumption of rational behaviour
gets taken to extremes.
Needless to say, it is a powerful working assumption. Vito
Volterra compared it to simplifying assumptions in physics,
such as frictionless surfaces and non-extendable lines.
People are certainly not totally rational in real life, but
if you are going to argue that they consistently behave in
ways that are not in their best interests, you¹d better
have a convincing explanation for it.
So, for example, whenever the stockmarket crashes
economists are widely mocked - often by people who should
know better - for assuming investors behave rationally and
the financial markets are 'efficient'. In that case, why
was a dot.com company worth $10 billion one day worth only
a few hundred million the next? There is no question that
psychology and sociology have a crucial role to play in
explaining what goes on in the stockmarket .
However, it is always worth pointing out to the generally
(but not always) innumerate critics, that share prices are
supposed to value the entire future profitability of a
company at today's values. Although the observed volatility
is indeed "excessive", a small change in expectations of
profits growth in 10 or 20 years' time can, as a matter of
arithmetic, have a big impact on today's valuation. What's
more, there is also a deep truth in the economists'
argument that investors are rational and will therefore
compete away any lasting profit opportunities. For very few
investors manage to beat the market for any length of time.
Similarly, people do not often get married for purely
economic reasons. Yet economists' models in which people
choose, or ditch, their partners in order to maximize their
financial gains can illuminate trends like single
motherhood. Welfare payments and the low potential earning
power of inner city fathers go a long way to explain how it
became a financially sensible choice as well as consistent
with changing social norms. The economic insight
illuminates the sociological, and vice versa. The economic
explanation is never the only one, but it puts the backbone
into the political and sociological explanations.
It's often argued that the emphasis on formal models of
rational behaviour means that the use of complicated
mathematical techniques has gone too far. And that the
formalisation now required to get anywhere in academic
economics is not only spurious when it comes to
understanding the world, but also simply puts off many
potential students. The figures suggest that students
increasingly prefer the realism of business schools, the
intellectual interest of cross-disciplinary courses or the
genuine technicalities of one of the natural sciences.
For the professional economist, working through the
mathematics of a simplified model that isolates a
particular issue is still the best way to gain new
insights. Edgeworth of the Edgeworth box diagram fame
compared the use of mathematical formalism to scaffolding.
You need the scaffolding to build the house, but then you
need to take it down when the structure's complete.
That's a big 'but' - the economist has to be able to work
out what the solution to the equations means. Paul Krugman
has argued that many of the critics of mathematical
formalism in the subject are criticising bad economics, and
that it's unfair to criticise any subject because of what
its bad practitioners, rather than its good ones, do. That
may be true up to a point.
But as somebody who has spent many years trying to
communicate economics to a wider audience, I think that the
scale of meaningless formalism, bad writing and lack of
real thought about the nature of the world in academic
economics, does constitute a deep institutional problem in
our subject (as indeed in other academic disciplines,
especially the social sciences). Economists must be able to
explain their results to a wider audience, or there has to
be a suspicion they don't actually understand it
themselves. It is, after all, a social science whose
findings have a social meaning.
This is why Deirdre McCloskey is right to highlight the
"rhetoric" of economics. Every subject offers a narrative
framework within which the world is to be interpreted. Our
profession has developed an extremely unappealing framework
or set of metaphors. It is therefore losing the competitive
struggle with other intellectual disciplines as a result.
This is why some of the most exciting economics being
practiced in universities now is at a slight angle to the
mainstream, in economic history or geography, urban
studies, or in behavioural finance or experimental
economics, for example (although this is also just the way
the tides of fashion have flowed in the subject).
There are still far too many pointless papers, which fail
the 'so what?' test that ought to inform any discipline and
inflict atrocious econometrics on their readers, by authors
encouraged by the career structures and perverse incentives
of a creaking university system. The widely understood fact
amongst economists, that probably the majority of the
empirical work published in professional journals is flawed
to the point of uselessness, is our dirty little secret,
not often acknowledged to outsiders. A 1996 study by
McCloskey and Ziliak of 10 years' worth of articles in the
American Economic Review, perhaps the premier journal,
found that a large majority had used statistical inference
incorrectly. Even if you think their standards are too
demanding, it's still true that computers have made it too
easy to access data the researcher never bothers to
understand, or plot, or even check for errors, and too easy
to run too many regressions. Many researchers seem to
regard their computers as a substitute for thinking, not as
a complement. Not surprisingly, they publish results that
are silly, or even damaging.
So I do believe that too much actually-existing economics
is unecessarily formalistic, over-reliant on a narrowly
positivistic philosophy, and stuffed with really bad
econometrics.
How did we get into this mess? I'd pinpoint post-war
macroeconomics as being where it all started to go wrong
and particularly the ideological clashes that marked the
1970s and early 1980s.
Macro is certainly what gives economists such a bad general
press - it's about Gordon Brown's forecasts going wrong or
Denis Healey turning back from the airport because the IMF
had to step in in 1979. The humiliation of macroeconomists
by events has cast a long shadow. As a result many of
today's professional economists are very uneasy about
making sweeping pronouncements on the future of capitalism
or the nature of class struggle in modern societies. They
know there is no decisive empirical evidence, no refutable
facts, to back up many pronouncements on the macro scale.
The lack of confidence is justified. For all of my
professional lifetime there have been competing schools of
thought about how the macroeconomy works, a sure sign that
nobody actually knows. Thus the clash of Keynesians versus
Monetarists, which the Keynesians ultimately lost as it
became blatantly obvious that they could not fix growth and
inflation as they had been confidently proclaiming up to
the late 1970s. But the battle was bitter because it mapped
into the protagonists' political views.
Next came the schism between 'real business cycle' or 'new
classical' or 'rational expectations' theorists and the
former Keynesians. The first group argued that as people
are rational, fluctuations in the level of demand in the
economy must reflect supply side changes such as a sudden
improvement in technology to which everybody was reacting
rationally. The presumption at the heart of the rational
expectations idea, that people will not be so foolish as to
consistently ignore opportunities to profit or increase
their incomes, has something going for it. The marriage of
the tools and insight of rational expectations (why would
people consistently believe something that's false?) to a
study of the imperfections and market failures of the real
world has produced some very fruitful research.
Macroeconomics is now as close to consensus as I can
remember it being, and real policy lessons have emerged
witness the greater stability since around 1995 of growth
and inflation.
Whatever the merits of one school or another, though, the
point is that if there is scope for distinct schools of
thought at all, this is not hard science.
That's not surprising when you're grappling to keep on top
of whatever happens to be going on right now in the world,
whether that's recession, a technology-driven boom, high
inflation, or deflation, or globalisation. Sorting out
cause and effect is intrinsically challenging in a complex
and changing world, in which events are often
over-determined. The data with which we are working are
unfolding in real time. The analysis of what is in the
public interest often involves trade-offs between specific
groups of people and is therefore politically fraught.
What's more, the empirical evidence can hardly ever be
decisive. There isn't all that much data available to test
competing theories: the economy changes so much it doesn't
make much sense to take what happened before 1980, say, as
good evidence for what might happen in 2005. At best an
economist has perhaps 20 years' worth of statistics, some
available monthly, or almost continuously in the financial
markets, but some only quarterly or annual. Given that one
month's price level is really very similar to the next
month's, or one year's GDP much like the next's, there
isn't even all that much information in the separate pieces
of data.
Macroeconomic forecasting in particular - that is, what the
general public thinks economists do - is very tricky,
essentially because where the economy gets to in future
depends on what millions of us do between now and then. In
general, aggregation introduces all sorts of
self-fulfilling phenomena. This isn't a new idea. In a very
famous passage in The General Theory Keynes, who was
himself a successful investor, said investing in shares was
like picking the winner in a beauty contest. You wanted to
choose the contestant most likely to appeal to most judges.
This applies not only to stockmarket bubbles but also to
booms and recessions. A recession is a collective outcome
that can feed on itself in a vicious spiral. It emerges in
the way a storm does, if you're think about the weather as
an analogy. Macroeconomic forecasting is really quite like
weather forecasting. You can spot short-term tendencies and
possibilities, might even be able to predict rain ahead
with great confidence, but any greater precision in the
forecast will be spurious.
Many forecasters are entirely comfortable with this
conclusion, and indeed would quite like to educate the
general public that sensible forecasts would be something
like: "There's a 75% chance inflation will be above 2% by
the end of next year." But we seem to prefer the appearance
of confidence: "Consumer prices will be rising by 2.4% in
18 months' time."
Unfortunately, as models capture a 20-year average
experience, and therefore inevitably predict the future
will be a lot like the average of the past 20 years, unless
the forecaster deliberately overrides the predictions using
his or her skill and judgement. So models produce bland
pictures of the future. They are very bad at forecasting
extreme events like recessions. They are pretty bad anyway
whenever the economy changes because what's new is not
incorporated into the estimated equations and just
compare the economy of 2000 with 1980 or 1970.
And so over the past two centuries, GDP per capita in the
leading economies has grown by about 2% a year - but the
standard errors in forecasting this growth are about 2.5%,
or in other words in excess of the thing being forecast.
The trouble is that events, 'structural breaks', keep
butting in. Events like the Industrial Revolution, fascism,
feminism, and world wars, or innovations like electricity,
the internal combustion engine, and the computer.
This all leaves macroeconomic theory in an uncomfortable
position. Any textbook will reveal it still rests on formal
models of fixed equations - some of which capture genuine
insights, but which don't add up to a tool for usefully
analysing or forecasting the economy as a whole because
they're metaphors. Unfortunately, there is nothing to put
in its place which would aggregate the behavior of millions
of people who are not fully rational, who don't have
complete information about everything, who make
short-sighted decisions, who are all different, who sway
each other's behavior, and who live in economies where
there are all sorts of obstacles to free and competitive
markets.
Since the ideological clashes of the 1970s and 80s, there
has been a welcome appreciation amongst economists that it
might be a good idea to make far more modest claims to be
able to understand and predict on the macro front. There is
a greater degree of consensus now about what constitutes
bad macro-economic policy, thanks in large part to the
disastrous results of putting once-fashionable economic
theories into practice.
The professional consensus now can be summed up as: don't
make dumb mistakes. Keep inflation low , because it's
economically damaging, unfair, and voters hate it. Get
central bankers, who hate inflation too, to keep it low. A
high rate of growth is good, but so is a steady rate of
growth. The voters hate boom and bust, or at any rate the
bust part of it. That means making sure government
borrowing isn't too high or the government surplus isn't
too big, because the government's not the point of the
economy, businesses and consumers are. There are still
heated arguments, of course, about whether interest rates
or tax and spending have been set at the right levels. But
the argument covers a much narrower range of options than
before.
Indeed, expectations of economic forecasts are
simultaneously extraordinarily high and very low, for
economists are expected to foretell the future with a
degree of authority we would never demand of a
meteorologist or biologist, and not surprisingly are
held in low esteem for often getting it badly wrong. Many
forecasts are extremely bad - perhaps inevitably so. But as
David Hendry at Nuffield has complained: "When weather
forecasts go awry, meteorologists get a new supercomputer;
when economists mis-forecast, we get our budgets cut."
But things are getting better. Modern macroeconometrics
does offer techniques for coping, for narrowing the
inevitable range of uncertainty attached to any forecast.
Some of it is quite simple. First, forecast growth rates,
not levels (first difference the data). That makes it less
important to get the absolute level right, so any mistake
you make here will show up as a one-off 'blip' error in the
forecast. Secondly, if go one step further (second
difference the data), so you are forecasting rate of
acceleration, you can similarly neutralise any linear time
trend in the series.
Two simple steps can therefore tackle the most basic
misspecifications of an econometric equation, getting the
wrong intercept and the wrong trend. Another tip is to
update estimated equations pretty often, using the most
recent data. Many forecasts are in practice based on very
old computer models, and the economists driving them deal
with forecasts that are obviously going adrift by
over-riding the predictions with their own judgement. In
the trade, it's known as adjusting the 'residuals' or
'add-factors'. The variable being forecast can be sorted
into two parts, the bit that is actually produced by the
equation for that variable, and the residual. In creaky old
models the residual can easily be the most important
component of a forecast value. Forecasters can also learn
from their errors. If an equation turns out to have
produced a big error last quarter, the error can be added
to the intercept term in the equation for forecasting the
next quarter.
In short, economic forecasters have to stop believing or
allowing the rest of the world to believe that what they
do is set down a simplified but essentially true version of
the structure of the economy. Most of them don't do this
yet but best practice will improve over time.
At the theoretical rather than practical level there are
also some interesting applications of complexity theory. It
just says people (like or ants or molecules) influence each
other in the many choices they make.
Fans of complexity theory overdo their claims about
undermining all of past economics. Actually, economic
thinking can easily take account of many of the phenomena
beloved of complexity theorists. For example, increasing
returns to scale in certain industries that arise from
'network effects' (the price I pay depends on how many of
you have already purchased the item), certainly don¹t
undermine economics. Respected, and conventional, academic
economists are doing a lot of research along these lines,
especially in finance, trade theory, economic geography,
and industrial organization. CONTINUED IN PART 2