NDLI: Phillips-Perron-type unit root tests in the nonlinear ESTAR framework

Content Provider	Springer Nature Link
Author	Sibbertsen, Philipp Rothe, Christoph
Copyright Year	2006
Abstract	In this paper, we propose Phillips-Perron type, semi-parametric testing procedures to distinguish a unit root process from a mean-reverting exponential smooth transition autoregressive one. The limiting nonstandard distributions are derived under very general conditions and simulation evidence shows that the tests perform better than the standard Phillips-Perron or Dickey-Fuller tests in the region of the null.
Ending Page	456
Page Count	18
Starting Page	439
File Format	PDF
ISSN	00026018
e-ISSN	16140176
Journal	AStA Advances in Statistical Analysis
Issue Number	3
Volume Number	90
Language	English
Publisher	Springer-Verlag
Publisher Date	2006-01-01
Publisher Place	Berlin, Heidelberg
Access Restriction	Subscribed
Subject Keyword	Monte Carlo simulations Statistics for Business/Economics/Mathematical Finance/Insurance unit roots Probability Theory and Stochastic Processes Exponential smooth transition autoregressive model Econometrics purchasing power parity Statistics Hypothesis Testing: General Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability

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Phillips-Perron-type unit root tests in the nonlinear ESTAR framework