Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/230760
Authors: 
Guo, Shaojun
Li, Dong
Li, Muyi
Year of Publication: 
2018
Series/Report no.: 
IRTG 1792 Discussion Paper No. 2018-049
Abstract: 
In this article we develop a tractable procedure for testing strict stationarity in a double autoregressive model and formulate the problem as testing if the top Lyapunov exponent is negative. Without strict stationarity assumption, we construct a consistent estimator of the associated top Lyapunov exponent and employ a random weighting approach for its variance estimation, which in turn are used in a t-type test. We also propose a GLAD estimation for parameters of interest, relaxing key assumptions on the commonly used QMLE. All estimators, except for the intercept, are shown to be consistent and asymptotically normal in both stationary and explosive situations. The nite-sample performance of the proposed procedures is evaluated via Monte Carlo simulation studies and a real dataset of interest rates is analyzed.
Subjects: 
DAR model
GLAD estimation
Nonstationarity
Random weighting
Strict stationarity testing
JEL: 
C15
C22
Document Type: 
Working Paper

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