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Abstract

In this article we propose a quick, efficient, and easymethod to detect whether a time series Yt possesses any nonlinear feature. The advantage of our proposed nonlinearity test is that it is not required to know the exact nonlinear features and the detailed nonlinear forms of Yt. Our proposed test could also be used to test whether the model, including linear and nonlinear, hypothesized to be used for the variable is appropriate as long as the residuals of the model being used could be estimated. Oursimulation results show that our proposed test is stable andpowerful while our illustration on Wolf-s sunspots numbers is consistent with the findings from existing literature.



Item Type: MPRA Paper -

Original Title: New Non-Linearity Test to Circumvent the Limitation of Volterra Expansion-

Language: English-

Keywords: linearity; nonlinearity; U-statistics; Volterra expansion-

Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space ModelsC - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: GeneralC - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics-





Autor: Bai, Zhidong

Fuente: https://mpra.ub.uni-muenchen.de/41872/







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