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.

Price Dividend Ratio and Long-Run Stock Returns: A Score-Driven State Space Model

Petrella, Ivan;
2020-01-01

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.
2020
39
4
1054
1065
Equity premium; Present-value models; Score-driven models; State space models; Time-varying parameters
Monache, Davide Delle; Petrella, Ivan; Venditti, Fabrizio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2019776
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