When I wrote about
why the BBC should treat a clear consensus in economics the same way
as it now treated climate science, I got a number of comments about why economics is not a science. A common theme was that
economics couldn’t prove theories ‘beyond doubt’ the same way
as the hard sciences could. A more sophisticated version of this
complaint is that most economic theories cannot be disproved in the
same way that Popper thought scientific theories could be disproved.
All this ignores a
key feature of any social science, which is their inexact nature.
Instead we have accumulations of evidence that confirm the
applicability of some theories and reject the applicability of
others. Economists’ views about what models are applicable change
as this evidence accumulates.
A good example
involves the minimum wage, as Noah Smith suggests.
The basic economic model suggested even a modest minimum wage should
significantly reduce employment, but economists discovered that the
evidence did not show this. As this evidence accumulated, alternative
theories and models (monopsony and search) were thought to be more
relevant. It is this response to evidence that makes
economics a science.
Jo Michell writes
“The scientific method of forming a hypothesis and then testing
that hypothesis against reality can never be the final arbiter of
knowledge, as it can in the physical sciences.” He is right that no
single experiment or regression can kill a theory, but wrong that the
accumulation of evidence is not the final arbiter, because no other
arbiter is available. He links to a post by Noah Smith which talks
about the failures of forecasting. But as that post makes clear, this
is not about data rejecting models, but the inability of models to
predict the future. We would never dream of condemning medics because
they cannot predict the exact time of our death, still less suggest
that this failure indicates they are not doing science.
Of course economics
involves cases where economists appear too reluctant to give up their
favoured models. You can find similar stories in the hard sciences.
There will be more such stories in economics because the inexact
nature of economics makes it easier to discount any single piece of
evidence. What I cannot understand is what leads someone like Russ
Roberts to argue
against the use of evidence, and instead that “economics is
primarily a way of organizing one’s thinking”. Astrology is also
a way of organising one’s thinking, but it fails because evidence
does not back it up.
That comparison is
slightly unfair, because while the theory behind astrology is
obviously implausible, the basic principles of microeconomics are
not. In a class on economic methodology I once drew a huge tree that
showed how most of economics could be derived from principles of
rational choice. But go beyond the basics, and add in complications
involving information and transactions costs (to name but two) and
you very quickly derive competing models. There is no single model
that comes from thinking like an economist, so for that reason alone
we need data to tell us which models are more applicable.
So thinking like an
economist does not tell me at what point raising the minimum wage
will reduce employment. But why would anyone want to keep their
models from being proved relevant or otherwise by data? The only
reason I can think of is that some models give answers that are
ideologically convenient. Of course allowing data to establish the relevance of some models over others does not make economics ideology proof. For example people can always select the one study that suggests that fiscal policy does not influence output and ignore the hundreds that show otherwise. That is why the accumulation of evidence, which includes its replicability, is so important. If you think economics has problems in that respect, have a look at psychology.
This is why
economists views about the long term impact of Brexit should be
treated as knowledge rather than just an opinion. Here knowledge is
shorthand for the accumulation of evidence consistent with plausible
theory. Sometimes the theories are common sense, like making trade
more difficult will reduce trade. Estimates of the size of trade
reduction based on evidence are uncertain, but they are better than
estimates based on wishful thinking. Empirical gravity equations
consistently show that geography still matters a lot in determining
how much is traded. Finally there is clear evidence that trade is
positively associated with productivity growth. To say that all this
has no more worth than some politicians opinion is ultimately to
degrade evidence and the science which interprets it.
