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Van Dijk, D., Franses, P.H. and Lucas, A. (1999) Testing for Smooth Transition Nonlinearity in the Presence of Outliers. Journal of Business and Economic Statistics, 17, 217-235.

has been cited by the following article:

• TITLE: Properties of Time-Varying Causality Tests in the Presence of Multivariate Stochastic Volatility

  AUTHORS: Daiki Maki

  KEYWORDS: Time-Varying Causality Tests, Wild Bootstrap, Multivariate Stochastic Volatility

  JOURNAL NAME: Open Journal of Statistics, Vol.6 No.5, October 8, 2016

  ABSTRACT: This paper compares the statistical properties of time-varying causality tests when errors of variables have multivariate stochastic volatility (SV). The time-varying causal-ity tests in this paper are based on a logistic smooth transition autoregressive model. The compared time-varying causality tests include asymptotic tests, heteroskedasticity-robust tests, and tests using wild bootstrap. Our simulation results show that asymptotic tests and heteroskedasticity-robust counterparts have size distortions under multivariate SV, whereas tests using wild bootstrap have better size properties regardless of type of error. In particular, the time-varying causality test with first-order Taylor approximation using wild bootstrap has better statistical properties.