Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form
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Efthymios G Pavlidis
The specification of Smooth Transition Regression models consists of a sequence of tests, which are typically based on the assumption of i.i.d. errors. In this paper we examine the impact of conditional heteroskedasticity and investigate the performance of several heteroskedasticity robust versions. Simulation evidence indicates that conventional tests can frequently result in finding spurious nonlinearity. Conversely, when the true process is nonlinear in mean, the tests appear to have low size adjusted power and can lead to the selection of misspecified models. The above deficiencies also hold for tests based on Heteroskedasticity Consistent Covariance Matrix Estimators but not for the Fixed Design Wild Bootstrap. We highlight the importance of robust inference through empirical applications.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Articles in the same Issue
- Article
- Estimation of Parameters in the Presence of Model Misspecification and Measurement Error
- An Alternative Maximum Entropy Model for Time-Varying Moments with Application to Financial Returns
- Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form
- First and Second Order Asymptotic Bias Correction of Nonlinear Estimators in a Non-Parametric Setting and an Application to the Smoothed Maximum Score Estimator
- Conditional Skewness, Kurtosis, and Density Specification Testing: Moment-Based versus Nonparametric Tests
Articles in the same Issue
- Article
- Estimation of Parameters in the Presence of Model Misspecification and Measurement Error
- An Alternative Maximum Entropy Model for Time-Varying Moments with Application to Financial Returns
- Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form
- First and Second Order Asymptotic Bias Correction of Nonlinear Estimators in a Non-Parametric Setting and an Application to the Smoothed Maximum Score Estimator
- Conditional Skewness, Kurtosis, and Density Specification Testing: Moment-Based versus Nonparametric Tests
