• Media type: E-Book
  • Title: Testing for long memory against ESTAR nonlinearities
  • Contributor: Kuswanto, Heri [Author]; Sibbertsen, Philipp [Author]
  • Published: Hannover: Fachbereich Wirtschaftswiss., Univ., 2009
  • Published in: Universität Hannover: Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät ; 42700
  • Extent: Online-Ressource (41 S.)
  • Language: English
  • Identifier:
  • Keywords: Autokorrelation ; Zeitreihenanalyse ; Nichtlineare Regression ; Statistischer Test ; Theorie ; Arbeitspapier ; Graue Literatur
  • Origination:
  • Footnote: ESTAR = Exponential Smooth Transition Autoregressive
    Systemvoraussetzungen: Acrobat Reader
  • Description: We develop a Wald type test to distinguish between long memory and ESTAR nonlinearity by using a directed-Wald statistic to overcome the problem of restricted parameters under the alternative. The test is derived from two basic model specifications where the first is the standard model based on an auxiliary regression and the second allows the parameter to appear as a nuisance parameter in the transition function. A simulation study indicates that both approaches lead to tests with good size and power properties to distinguish between stationary long memory and ESTAR. Moreover, the second approach is shown to have more power. -- directed-Wald test ; ESTAR ; long memory
  • Access State: Open Access