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.
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References in zbMATH (referenced in 12 articles )
Showing results 1 to 12 of 12.
- Sandberg, Rickard: M-estimator based unit root tests in the ESTAR framework (2015)
- Kapetanios, George; Shin, Yongcheol: Testing the null hypothesis of nonstationary long memory against the alternative hypothesis of a nonlinear ergodic model (2011)
- Kılıç, Rehim: Testing for a unit root in a stationary ESTAR process (2011)
- Kruse, Robinson: A new unit root test against ESTAR based on a class of modified statistics (2011)
- Nicolau, João: Purchasing power parity analyzed through a continuous-time version of the ESTAR model (2011)
- Maki, Daiki: An alternative procedure to test for cointegration in STAR models (2010)
- Psaradakis, Zacharjas; Sola, Martin; Spagnolo, Fabio; Spagnolo, Nicola: Selecting nonlinear time series models using information criteria (2009)
- Ucar, Nuri; Omay, Tolga: Testing for unit root in nonlinear heterogeneous panels (2009)
- Xie, Ai-Gen; Li, Chuan-Qi; Wang, Tie-Bang; Pei, Yuan-Ji: The formulas for the secondary electron yield at high incident electron energy from gold and aluminum (2009)
- Adebile, O.A.; Shangodoyin, D.K.; Arnab, R.: Forecasting performance of logistic STAR model: an alternative version to the original LSTAR models (2006)
- Rothe, Christoph; Sibbertsen, Philipp: Phillips-Perron-type unit root tests in the nonlinear ESTAR framework (2006)
- Saunders, E.S.; Naylor, T.; Allan, A.: Metrics for agent observers (2006)