Abstract
In this paper we propose new panel tests to detect changes in persistence. The test statistics are used to test the null hypothesis of stationarity against the alternative of a change in persistence from I(0) to I(1), from I(1) to I(0), and in an unknown direction. The limiting null distributions of the tests are derived and evaluated in small samples by means of Monte Carlo simulations. An empirical illustration is also provided.
Highlights
Over the last two decades, a vast literature has investigated whether economic and financial time series may be characterized by a change in persistence between separate I(1) and I(0) regimes rather than I(1) or I(0) behavior
In this paper we propose new panel tests to detect changes in persistence
The test statistics are used to test the null hypothesis of stationarity against the alternative of a change in persistence from I(0) to I(1), from I(1) to I(0), and in an unknown direction
Summary
Over the last two decades, a vast literature has investigated whether economic and financial time series may be characterized by a change in persistence between separate I(1) and I(0) regimes rather than I(1) or I(0) behavior. While many data sets are panels of multiple time series, the way that existing tests are constructed requires that the series are tested one at a time. The purpose is to develop tests for changes in persistence that explores the multiplicity of series, and that can be seen as panel extensions of the time series tests of Kim (2000), Kim et al (2002), and Busetti and Taylor (2004).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
