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Unit root tests for ESTAR models

Journal Article


Abstract


  • Since the introduction of augmented Dickey-Fuller unit root tests, many new types of unit root tests have been developed. Developments in nonlinear unit root tests occurred to overcome poor performance of standard linear unit root tests for nonlinear processes. Venetis et al. (2009) developed a unit root test for the k-ESTAR(p) model where k is the number of equilibrium levels and p is the order of autoregressive terms. Their approach may cause singularity problem because some of the regressors might be collinear. To overcome the problem, they move collinear regressors into the error term. This paper extends the work of Venetis et al. (2009). Using a new approach given in this paper, the singularity problem can be avoided without worrying the issue of collinearity. For some cases, simulation results show that our approach is better than other unit root tests.

Publication Date


  • 2013

Citation


  • Puspaningrum, H., Lin, Y. & Gulati, C. (2013). Unit root tests for ESTAR models. Journal of Statistical Theory and Practice, 7 (3), 558-595.

Scopus Eid


  • 2-s2.0-84879351140

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/2575

Number Of Pages


  • 37

Start Page


  • 558

End Page


  • 595

Volume


  • 7

Issue


  • 3

Abstract


  • Since the introduction of augmented Dickey-Fuller unit root tests, many new types of unit root tests have been developed. Developments in nonlinear unit root tests occurred to overcome poor performance of standard linear unit root tests for nonlinear processes. Venetis et al. (2009) developed a unit root test for the k-ESTAR(p) model where k is the number of equilibrium levels and p is the order of autoregressive terms. Their approach may cause singularity problem because some of the regressors might be collinear. To overcome the problem, they move collinear regressors into the error term. This paper extends the work of Venetis et al. (2009). Using a new approach given in this paper, the singularity problem can be avoided without worrying the issue of collinearity. For some cases, simulation results show that our approach is better than other unit root tests.

Publication Date


  • 2013

Citation


  • Puspaningrum, H., Lin, Y. & Gulati, C. (2013). Unit root tests for ESTAR models. Journal of Statistical Theory and Practice, 7 (3), 558-595.

Scopus Eid


  • 2-s2.0-84879351140

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/2575

Number Of Pages


  • 37

Start Page


  • 558

End Page


  • 595

Volume


  • 7

Issue


  • 3