EconPapers    
Economics at your fingertips  
 

Information Recovery in a Dynamic Statistical Markov Model

Douglas J. Miller () and George Judge ()
Additional contact information
Douglas J. Miller: Economics and Management of Agrobiotechnology Center, University of Missouri, Columbia, MO 65211, USA
George Judge: Graduate School, 207 Giannini Hall, University of California, Berkeley, Berkeley, CA 94720, USA

Econometrics, 2015, vol. 3, issue 2, 1-12

Abstract: Although economic processes and systems are in general simple in nature, the underlying dynamics are complicated and seldom understood. Recognizing this, in this paper we use a nonstationary-conditional Markov process model of observed aggregate data to learn about and recover causal influence information associated with the underlying dynamic micro-behavior. Estimating equations are used as a link to the data and to model the dynamic conditional Markov process. To recover the unknown transition probabilities, we use an information theoretic approach to model the data and derive a new class of conditional Markov models. A quadratic loss function is used as a basis for selecting the optimal member from the family of possible likelihood-entropy functional(s). The asymptotic properties of the resulting estimators are demonstrated, and a range of potential applications is discussed.

Keywords: conditional moment equations; controlled stochastic process; first-order Markov process; Cressie-Read power divergence criterion; quadratic loss; adaptive behavior (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
https://www.mdpi.com/2225-1146/3/2/187/pdf (application/pdf)
https://www.mdpi.com/2225-1146/3/2/187/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:3:y:2015:i:2:p:187-198:d:47332

Access Statistics for this article

Econometrics is currently edited by Prof. Dr. Kerry Patterson

More articles in Econometrics from MDPI, Open Access Journal
Bibliographic data for series maintained by XML Conversion Team ().

 
Page updated 2018-10-02
Handle: RePEc:gam:jecnmx:v:3:y:2015:i:2:p:187-198:d:47332