Delle Monache, Davide, Venditti, Fabrizio and Petrella, Ivan (2020) Price dividend ratio and long-run stock returns : a score driven state space model. Journal of Business and Economic Statistics . doi:10.1080/07350015.2020.1763805 (In Press)

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Abstract

In this article, we develop a general framework to analyze state space models with time-varying system matrices, where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying matrices. We use this method to study the time-varying relationship between the price dividend ratio, expected stock returns and expected dividend growth in the United States since 1880. We find a significant increase in the long-run equilibrium value of the price dividend ratio over time, associated with a fall in the long-run expected rate of return on stocks. The latter can be attributed mainly to a decrease in the natural rate of interest, as the long-run risk premium has only slightly fallen.

Item Type:	Journal Article
Subjects:	H Social Sciences > HA Statistics H Social Sciences > HC Economic History and Conditions H Social Sciences > HG Finance
Divisions:	Faculty of Social Sciences > Warwick Business School > Finance Group Faculty of Social Sciences > Warwick Business School
Library of Congress Subject Headings (LCSH):	State-space methods -- Econometric models, Time-series analysis -- Econometric models, Stock price forecasting -- Econometric models, Rate of return -- Forecasting -- Econometric models
Journal or Publication Title:	Journal of Business and Economic Statistics
Publisher:	Taylor & Francis Inc.
ISSN:	0735-0015
Official Date:	2020
Dates:	Date Event 2020 Published 2 June 2020 Available 4 May 2020 Accepted
DOI:	10.1080/07350015.2020.1763805
Status:	Peer Reviewed
Publication Status:	In Press
Publisher Statement:	This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Business and Economic Statistics on 02/06/2020, available online: http://www.tandfonline.com/10.1080/07350015.2020.1763805
Access rights to Published version:	Restricted or Subscription Access
Related URLs:	Publisher

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