This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Terasvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Terasvirta has had and will continue to have, on the profession.
Preface ; TESTING FOR LINEARITY AND FUNCTIONAL FORM ; 1. Testing for Neglected Nonlinearity Using Twofold Unidentified Models under the Null and Hexic Expansions ; 2. Consistent Testing of Functional Form in Time Series Models ; 3. Linearity Testing for Trending Data with an Application of the Wild Bootstrap ; SMOOTH TRANSITION MODELS ; 4. Common Non-linearities in Multiple Series of Stock Market Volatility ; 5. Balance Sheet Recessions and Time-Varying Coefficients in a Phillips Curve Relationship: An Application to Finnish Data ; 6. Modelling Time-Varying Volatility in Financial Returns: Evidence from Bond Markets ; MODEL SELECTION AND ECONOMETRIC METHODOLOGY ; 7. Semi-automatic Non-linear Model Selection ; 8. Fundamental Problems with Nonfundamental Shocks ; 9. Penalized Estimation of Semi-parametric Additive Time Series Models ; 10. Oracle Efficient Estimation and Forecasting with the Adaptive Lasso and the Adaptive Group Lasso in Vector Autoregressions ; APPLIED FINANCIAL ECONOMETRICS ; 11. Modeling Commodity Prices with Dynamic Conditional Beta ; 12. Bias and Uncertainty in Analyst Earnings Expectations at Different Forecast Horizons ; 13. Asymmetric Dependence Patterns in Financial Returns: An Empirical Investigation Using Local Gaussian Correlation ; 14. Bagging Constrained Equity Premium Predictors
