Leitura do Dia - A Comment on Econometric Information Recovery and Inference from Indirect Noisy Economic Data

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.

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

JEL Classification: C40, C51