Estimating Long-Run Risks in Developed and Developing Countries: A Particle MCMC Approach
45 Pages Posted: 19 Dec 2018 Last revised: 11 Jan 2019
Date Written: December 1, 2018
Abstract
We estimate a generalized version of the Long-Run Risk model in a panel of developed and developing countries using consumption, dividend growth, and asset returns data by utilizing the particle filter, while allowing for measurement errors in consumption data at quarterly and annual frequencies. We extend the exercise by Schorfheide et al (2018) to non-U.S. countries. Our estimations provide further evidence in support of the Long-Run Risk model and in the existence of a common small persistent component in consumption growth, dividend growth, and cash-flow growth. In certain developing countries with a short data series such as Malaysia, it is important to include asset return data to generate a large posterior estimate on the persistence parameter ρ. Our results thus further challenge the view that consumption growth is an iid process with international evidence. The estimated model can produce asset-pricing moments consistent with data.
Keywords: Long-Run Risk, Bayesian Estimation, International Finance
JEL Classification: C11, C58, G12, F30, E21
Suggested Citation: Suggested Citation