
Forecasting with Econometric Methods: Folklore versus Fact (1978) [pdf] - henning
https://repository.upenn.edu/cgi/viewcontent.cgi?article=1008&context=marketing_papers
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zwaps
Interesting article, but heavily biased approach.

1\. Econometrics, as defined here, would include anything regression or
classification. Indeed, Machine Learning would be included as "Econometrics"
by the author's definition. I think everyone, including econometricians, would
say that Machine Learning is doing a pretty decent job at forecasting. The
authors are thinking of classical regression, but maybe this is simply because
it's an article from 1978? The answer may be: Perhaps we just weren't there
yet?

2\. The primary goal of econometrics aka statistical inference is not
forecasting. It is separating effects from confounders, in a multitude of
fashions. Modern approaches are bad at forecasting, and this is almost by
design. One tries to approximate experiments, in a sense, and experiments by
definition do not forecast real, complex situations: They try to get rid of
everything that makes reality complex.

3\. The definitions survey question can be understood as

\- Statistics vs. qualitative research

\- Econometrics vs. time-series econometrics

\- Economics vs. other social sciences

\- Regression vs. other statistical techniques

\- ...

In other words, the survey is designed to get the maximum agreement from
economists. The "test", however basically evaluates the success of early
simple linear regression studies.

This is, essentially, what we call a biased research/survey design, to the
degree that I'd suspect there is some sort of agenda at play!

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bachmeier
> The primary goal of econometrics aka statistical inference is not
> forecasting.

There are some in the economics community that agree with you. Believers in
the Freakonomics/Josh Angrist tradition largely agree with this view.

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dvfjsdhgfv
The big question is: if forecasting with econometrics doesn't work, what other
methods can we use?

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bachmeier
Please note that this paper is 40 years old and there is no reason for anyone
to read it, with the possible exception of someone working on a history
project.

