Perry M. writes:
>... I'm making the point that what you're doing is not based in the
>methods of science.
I am taking well-established well-tested equations and seeing what they
imply in a new hard-to-test context. I claim this is standard practice
in all science and engineering fields I am familiar with. For example,
this is the essense of all engineering feasibility analyses.
>Well, as an honest experimentalist in another field who, say, claimed
>to have a model that predicted earthquakes, one might hold off on
>announcing for a couple of years to document one's claim based on
>future events.
If one had theories that predicted earthquakes well in the U.S., one
might reasonably look at what those theories predict for earthquakes in
China. Sure there is no guarentee that China isn't different somehow,
but one could easily publish such an analysis, and is would certainly
be considered "science".
>You could also, conceivably, have tried to apply your model
>retrospectively to reasonably accurate data in order to see if the
>model at least fits past behavior.
The equations I combined *have* been applied ad nausium to historical data,
and to experiments. It is just that I don't have experimental results
testing this exact combination of equations in the exact area I'm applying
them to.
>I hate to use vulgarity, but the claim that an economist can't be held
>to the same standards as a medical researcher is pure bull.
It seems to me that you are imposing different standards on economics than
are usually applied elsewhere.
>medical studies take twenty years. Five year studies are bloody well
>routine. The scientists in question don't sit back and say "well, it
>would take too long to determine if our model of heart disease is
>correct, so we are going to just publish right now and pretend we are
>exempt from the rules of science."
But if that heart disease model is built from pieces that have strong
support in other contexts, they *do* publish their analysis before that
twenty year test is done. The idea that they must never mention their
theoretical model to anyone before the twenty year test is up is complete
lunacy, and completely at odds with existing practice.
>I've simply asked you for scientific evidence for your claims. ...
>Sure, you are allowed to use a THEORY to exrapolate beyond your
>current data. However, what we have here is a *hypothesis* -- a
>potential theory. That is to say, you do not yet have a demonstrated
>model -- you only have a model for which you have yet to gather
>evidence of predictive power. ...
>Simply noting that components of your hypothesis have some evidence
>for them isn't sufficient. What if you completely ignored an important
>factor? That is why people do EXPERIMENTS.
I provided evidence, which you ignored. When a model is made of parts,
evidence in support of a part is evidence in support of the whole, even
when that evidence is from the context of some other whole. Yes,
confidence in a model increases when it is more directly tested. But to
insist that theorists be silent until there is evidence specific to a
particular combination of parts is contrary to all standard practice.
That standard would, for example, end the theoretical subspecialty
of any field.
>Now, as it turns out, I've spent quite a lot of time with people who
>produce hypotheses about the future near-term price trends of various
>securities and commodities. These individuals, in general, do not
>attempt to risk money on their hypotheses until they have considerable
>bodies of data backing them up. They collect time series data going
>back a century or more, and carefully check their hypotheses against
>historical data and make predictions and see whether or not these
>predictions come true BEFORE risking capital on them.
I'll bet they do not, however, always stay silent about their theories
until tests back them up. And do they always insist on years of experiments,
rather than just tests on historical data, before risking capital?
Robin Hanson
hanson@econ.berkeley.edu http://hanson.berkeley.edu/
RWJF Health Policy Scholar, Sch. of Public Health 510-643-1884
140 Warren Hall, UC Berkeley, CA 94720-7360 FAX: 510-643-8614
Received on Mon May 4 16:43:21 1998
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