🚀 go-pugleaf

 
> > pcollac@pyrnova.mis.pyramid.com (Paul Collacchi) writes:
>   thompson@atlas.socsci.umn.edu (T. Scott Thompson) writes:
    pcollac@pyrnova.mis.pyramid.com (Paul Collacchi) writes:

> >I'm a little surprised by this.  Aren't there mathematical models which
> >are able, at least, to simulate GDP cycles?  These GDP cycles may not
> >have amplitudes or frequencies which match anything real, but the models
> >themselves may suggest something about the nature of variables at work 
> >needed to produce curves that 'look like' GDP graphs.
> 
> The point is that there are _many_ mathematical models that are able
> to do a pretty good job of simulating business cycle phenomena.  They
> involve quite different causal mechanisms.  So simulation success is
> not enough to resolve the disputes among the competing theories.
> 
> As for prediction...
> 
> I would agree that predictive success is in principle a pretty good
> yardstick for evaluating models,....  The problem is that we can not
> experiment much with the macro economy, so the models are rarely
> tested (through prediction) in situations that are able to sort out
> the differences among them.
> 
> For example, two of the mechanisms (among many) that might explain the
> boom of the 1980s are (1) lower tax rates and (2) deficit spending.
> In order to learn the relative contribution of these two phenomena we
> would have to run some experiments in which we vary tax rates and
> fiscal policies _independently_ holding all other things equal.
> Needless to say, this cannot be done.
> 

This is really the curse of economics, isn't it?  Can't do controlled
experimentation.  Quite possibly, Stupendous Man has simply looked back at
the 200 or so data points on the graph, formulated a theory by selecting
events that coincide with "booms" and now pronounced that the data supports
his theory that [his event] "caused" the boom, and by the way, if you don't
believe him go look at the data.
 
|> For what it's worth: My impression is that most of the formal
|> mathematical models that have been developed have a very poor track
|> record predicting movements of the business cycle more than a few
|> months ahead.

I remember trying to do this with graphs of futures prices.  I'd look back
at the data, find events that I thought were 'significant', correlate those
events to peaks in the data and propose a "theory".  My theories never
predicted very well.  They'd go a little way and then fail.  

Mathematically, it's equivalent to asking which of an infinite number
of possible sequences that begins with these 200 points is the real GDP
sequence?

|> The most successful forecasting models do not attempt
|> to model causal mechanisms directly, and therefore are rather
|> uninformative about what the "fundamental forces" are driving the
|> business cycle.
|> --

I assume then that there are "analytic" models as well -- one's in which
tons of little micro-economic beings are "added up" to form a macro-economic
whole.  You say these don't do too well?

Are other developed economies anecdotally relevant?  Are there ANY examples
of tax cuts which do NOT result in economic growth?  Are there any examples
of tax cuts in our own GDP which did not result in growth?  Questions like
these must be valid as far as 'disproving' hypotheses.  Given what you
said, I don't think its ever possible to prove them.

Paul Collacchi