Pavlidis, E., Paya, I. and Peel, D. (2010) Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form. Studies in Nonlinear Dynamics and Econometrics, 14, Article 3.

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.