Abstract

http://ssrn.com/abstract=2122592
 
 

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A Comment on Econometric Information Recovery and Inference from Indirect Noisy Economic Data


George Judge


University of California, Berkeley - Department of Agricultural & Resource Economics

August 2, 2012


Abstract:     
The focus of this paper is on starting a critical discussion on the state of econometrics. The problem of information recovery in economics is discussed, and information theoretic methods are suggested as an estimation and inference framework for analyzing questions of a causal nature and learning about hidden dynamic micro and macro processes and systems, that may not be in equilibrium.

Number of Pages in PDF File: 18

Keywords: Information theoretic methods, State space models, First order Markov processes, Inverse problems, Dynamic economic systems

JEL Classification: C40, C51

working papers series


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Date posted: August 4, 2012  

Suggested Citation

Judge, George, A Comment on Econometric Information Recovery and Inference from Indirect Noisy Economic Data (August 2, 2012). Available at SSRN: http://ssrn.com/abstract=2122592 or http://dx.doi.org/10.2139/ssrn.2122592

Contact Information

George G. Judge (Contact Author)
University of California, Berkeley - Department of Agricultural & Resource Economics ( email )
Berkeley, CA 94720
United States
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References:  27

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