Publication Type

Journal Article

Version

acceptedVersion

Publication Date

4-2019

Abstract

This paper studies a continuous time dynamic system with a random persistence parameter. The exact discrete time representation is obtained and related to several discrete time random coefficient models currently in the literature. The model distinguishes various forms of unstable and explosive behavior according to specific regions of the parameter space that open up the potential for testing these forms of extreme behavior. A two-stage approach that employs realized volatility is proposed for the continuous system estimation, asymptotic theory is developed, and test statistics to identify the different forms of extreme sample path behavior are proposed. Simulations show that the proposed estimators work well in empirically realistic settings and that the tests have good size and power properties in discriminating characteristics in the data that differ from typical unit root behavior. The theory is extended to cover models where the random persistence parameter is endogenously determined. An empirical application based on daily real S&P 500 index data over 1928–2018 reveals strong evidence against parameter constancy over the whole sample period leading to a long duration of what the model characterizes as extreme behavior in real stock prices.

Keywords

Bubble testing, Explosive path, Continuous time models, Infill asymptotics, Extreme behavior, Random coefficient autoregression

Discipline

Econometrics

Research Areas

Econometrics

Publication

Journal of Econometrics

Volume

209

Issue

2

First Page

208

Last Page

237

ISSN

0304-4076

Identifier

10.1016/j.jeconom.2019.01.002

Publisher

Elsevier: 24 months

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1016/j.jeconom.2019.01.002

Download

Included in

Econometrics Commons

Share

COinS