Some Thoughts on Econometric Information Recovery

George Judge ()

Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series from Department of Agricultural & Resource Economics, UC Berkeley

Abstract: This paper is concerned with the problem of information recovery and measuring evidence that involves uncontrolled indirect noisy effects data and stochastic ill posed inverse problems in economics-econometrics. Information theoretic methods based on a multi parametric family of power divergence measures are suggested as an estimation and inference framework for dealing with these problems, analyzing questions of a causal nature and learning about hidden dynamic economic processes and systems that may or may not be in equilibrium. The paper concludes with some comments on the implications for information recovery of continuing to use traditional economic-econometric models and methods.

Keywords: Social and Behavioral Sciences; Information theoretic methods; First order Markov processes; Inverse problems; Dynamic economic systems; Information Recovery (search for similar items in EconPapers)
Date: 2013-08-21
New Economics Papers: this item is included in nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:cdl:agrebk:qt5h048626

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