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A BAYESIAN ANALYSIS OF WEAK IDENTIFICATION IN STOCK PRICE DECOMPOSITIONS

Published online by Cambridge University Press:  07 January 2014

Nathan S. Balke ,
Jun Ma  and
Mark E. Wohar
Nathan S. Balke
Affiliation:
Southern Methodist University and Federal Reserve Bank of Dallas
Jun Ma*
Affiliation:
University of Alabama
Mark E. Wohar
Affiliation:
University of Nebraska at Omaha
*
Address correspondence to: Jun Ma, Department of Economics, Finance and Legal Studies, Culverhouse College of Commerce and Business Administration, University of Alabama, Tuscaloosa, AL 35487-0024, USA; e-mail: jma@cba.ua.edu.
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Abstract

This paper employs the state-space model to reexamine the fundamental issue in finance of whether it is the expected returns or the expected dividends growth that is primarily responsible for stock price variations. We use Bayesian methods to show that there is a substantial uncertainty about the contributions of expected returns and expected dividends to fluctuations in the price–dividend ratio when the aggregate returns and dividends data are used. The substantial uncertainty of the contributions results from the model being weakly identified. Our finding challenges the notion long held in the existing literature that it is the expected returns that contribute most to price–dividend variations.

Keywords

Weak IdentificationBayesian AnalysisStock Price DecompositionState-Space Model
Type
Articles
Information
Macroeconomic Dynamics , Volume 19 , Special Issue 4: Empirical Analysis of Business Cycles, Financial Markets, and Inflation: Essays in Honor of Charles Nelson , June 2015 , pp. 728 - 752
Copyright
Copyright © Cambridge University Press 2014 

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References

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