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Testing for Long Memory Against ESTAR Nonlinearities Author info | Abstract | Publisher info | Download info | Related research | Statistics Kuswanto, Heri
Sibbertsen, Philipp
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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.
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Paper provided by Universität Hannover, Wirtschaftswissenschaftliche Fakultät in its series Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Universität Hannover with number
dp-427.
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Length: 41 pages
Date of creation: Aug 2009Date of revision:
Handle: RePEc:han:dpaper:dp-427Contact details of provider: Postal: Koenigsworther Platz 1, D-30167 Hannover Phone: (0511) 762-5350 Fax: (0511) 762-5665 Web page: http://www.wiwi.uni-hannover.de/ More information through EDIRC
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Keywords: directed-Wald test ; ESTAR ; long memory ; Other versions of this item:
Find related papers by JEL classification: C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
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