
A Nobel for a Real-World Economist - akg_67
http://www.bloombergview.com/articles/2015-10-12/a-nobel-for-a-real-world-economist
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bsbechtel
While trying to use empirical evidence to evaluate theories is an important
way to advance knowledge in a given domain, I worry about how much weight is
given to early empirical results found in fields that study chaotic systems.
Case in point, look at the past 100 years of study in nutrition science. An
entire generation was taught that fats are bad, food policy was designed
around this premise, and now we are learning this may not have necessarily
been the case. I don't have a solution to this, because studying empirical
evidence allows us to identify what variables are missing, expand our scope of
study, and evaluate what variables are/aren't relevant. However, designing
policies based on empirical evidence from a field that is in its infancy when
it comes to data collection is dangerous.

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overdrivetg
I can understand your point, but isn't the answer just "more science"? We want
to have a theory based on early data (since there _will_ be a policy, whether
explicit or not, so better to base it on our best ideas to date), but it's
early and we don't really know what we're doing. Then we get better data and
better theories and voila! New consensus, better theory, better policies (in
theory ;-).

Maybe advocate more open-mindedness so paradigm shifts don't require
extinction of the proponents of the previous theory? Or strive for more policy
responsiveness to scientific discoveries (I guess it's pretty clear this would
be a Good Thing)?

I think structurally encouraging policies to be built around actual scientific
consensus and data (and to keep up with the field) could go a long way.

~~~
bsbechtel
In general I agree that yes, the answer is "more science", although my
intuition tells me that some domains are too complex to ever be modeled
accurately by humans...meaning writing and managing the codebase to accurately
model some domains, even with infinite computing power, would be impossible
due to humans limited mental capacities. What those domains are, however, I
don't know and don't want to guess. I just suspect they exist.

In regards to your point about policy, if it is implicit (as in findings
reported by the media), that's fine. However, as soon as policy is made
explicit, either through law, or through national policies such as the food
nutrition pyramid, interest groups immediately begin forming to protect said
explicit policy. The rules our policymakers have to follow were explicitly
designed in a way that makes changing policy a slow, arduous process to
protect swift changes that could have dangerous, unknown side effects that
every citizen would have to deal with. When we prematurely start explicitly
making policies based on empirical results in domains of chaotic systems
(i.e., those domains where unknown, new variables appear often and change the
course of things), those policies have a higher chance of being wrong, and it
becomes (by design) very hard to change those policies later on. This is where
my concern is rooted.

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dimitar
Please read his 'Letters from America' column:
[http://scholar.princeton.edu/deaton/letters-
america](http://scholar.princeton.edu/deaton/letters-america)

His articles are very approachable and written with a lot of wit and vision
for where new research is taking economics.

For example see his take on new research on minimum wage at a time when most
economists were very sceptical:
[http://scholar.princeton.edu/sites/default/files/deaton/file...](http://scholar.princeton.edu/sites/default/files/deaton/files/letterfromamerica_oct1996.pdf)

