Download this Paper Open PDF in Browser

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

18 Pages Posted: 4 Aug 2012  

George Judge

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

Date Written: 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.

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

JEL Classification: C40, C51

Suggested Citation

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

George G. Judge (Contact Author)

University of California, Berkeley - Department of Agricultural & Resource Economics ( email )

207 Giannini Hall
University of California
Berkeley, CA 94720
United States

Paper statistics

Downloads
58
Rank
308,752
Abstract Views
443