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.