In spite of perhaps attracting the wrath of Jason Smith, I think it is safe to say that economics is too complicated for there to be one generally applicable model of everything. Because of this, there is a veritable plethora of economic models available to the economic theorist. This simply leaves the question of which one to use in which circumstance.
Simon Wren-Lewis seems to think that economists should select between models in an ex-post manner -- that is, we should seen which model better represents the data and use that model from then on:
This is why context-based validation of theory is superior to empirical validation in the case of economics. The context -- i.e. the sub-field of economics that is being studied -- should inform model choice almost entirely. If the field is business cycles, then the relevant model is a New Keynesian DSGE model and if the field is growth theory, then New Keynesian models are superfluous and should be tabled in favor of neoclassical models -- whose only difference from their New Keynesian counterparts is nominal rigidity, which is irrelevant over a time scale longer than a decade.
Predictions about the economy can now be made based on currently available information: it is possible to determine whether or not, e.g. financial frictions should be present in our business cycle model based on the current state of the economy: we knew by Q3 2008 that financial frictions were relevant, so we should have put them in a model if we were trying to predict the next few years.
Alternatively, the model I should choose to use depends on the kind of thought experiment I choose to embark on. Am I trying to compare PAYGO pensions with Social Security? If so, the obvious model to use is a simple OLG model without a labor-leisure trade-off or sticky prices. Choice of models is equivalent to choice of assumptions, at least when it comes to the DGE approach currently dominant in economics, and assumption choice depends entirely on the question being asked. Nominal rigidity is obviously relevant for business cycle theory, but completely useless when it comes to determining the level effect of a tax increase.
Hopefully this selection mechanism is specific enough to not be "basically feelings," as Jason Smith would suggest is the case for most of economics.
Simon Wren-Lewis seems to think that economists should select between models in an ex-post manner -- that is, we should seen which model better represents the data and use that model from then on:
How do we know if most economic cycles are described by Real Business Cycles (RBC) or Keynesian dynamics. One big clue is layoffs: if employment is fall because workers are choosing not to work, we could have an RBC mechanism, but if workers are being laid off (and are deeply unhappy about is) this is more characteristic of a Keynesian downturn.The issue here is that we can only diagnose events after the fact, we cannot reasonably make predictions because of the impossibility of ex ante empirical validation: it is impossible to determine whether or not a recession is New Keynesian or if it is a Real Business Cycle before data are released.
This is why context-based validation of theory is superior to empirical validation in the case of economics. The context -- i.e. the sub-field of economics that is being studied -- should inform model choice almost entirely. If the field is business cycles, then the relevant model is a New Keynesian DSGE model and if the field is growth theory, then New Keynesian models are superfluous and should be tabled in favor of neoclassical models -- whose only difference from their New Keynesian counterparts is nominal rigidity, which is irrelevant over a time scale longer than a decade.
Predictions about the economy can now be made based on currently available information: it is possible to determine whether or not, e.g. financial frictions should be present in our business cycle model based on the current state of the economy: we knew by Q3 2008 that financial frictions were relevant, so we should have put them in a model if we were trying to predict the next few years.
Alternatively, the model I should choose to use depends on the kind of thought experiment I choose to embark on. Am I trying to compare PAYGO pensions with Social Security? If so, the obvious model to use is a simple OLG model without a labor-leisure trade-off or sticky prices. Choice of models is equivalent to choice of assumptions, at least when it comes to the DGE approach currently dominant in economics, and assumption choice depends entirely on the question being asked. Nominal rigidity is obviously relevant for business cycle theory, but completely useless when it comes to determining the level effect of a tax increase.
Hopefully this selection mechanism is specific enough to not be "basically feelings," as Jason Smith would suggest is the case for most of economics.
