So I am reading perloff/karp/golan's book on estimating market power. They approach the estimation from the standpoint of IT estimation in particular maximum entropy estimation. This seems like a very unpopular approach as google scholar did not turn up much in the econometrics literature.
Is there a reason for the unpopularity? Seems quite consistent with bayesian approaches and ET Jaynes was an advocate of the approach.
Schennach has successfully used information theory in a lot of her work - google schennach and etel, betel, elvis, even a working paper on machine learning with Gunsilius. Imbens and Kitamura have also done work on exponential tilting - which is an estimator based on information theory. So I really wouldn't say it's unpopular.
Schennach has successfully used information theory in a lot of her work - google schennach and etel, betel, elvis, even a working paper on machine learning with Gunsilius. Imbens and Kitamura have also done work on exponential tilting - which is an estimator based on information theory. So I really wouldn't say it's unpopular.
cool thanks for the pointers.
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Schennach has successfully used information theory in a lot of her work - google schennach and etel, betel, elvis, even a working paper on machine learning with Gunsilius. Imbens and Kitamura have also done work on exponential tilting - which is an estimator based on information theory. So I really wouldn't say it's unpopular.
minimal description length estimators are based on information theory as well, there was a special issue of the JoE on this stuff years ago, might have fallen out of fashion for a while, sounds like its back.
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Hi,
I hope you are doing well.
I want to contribute a guest post article to your website that may interest your readers.
It would be of high quality and free of cost. You can choose the topic of the article from the topic ideas that I'll send you in my next email once you approve this offer.
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