Buch, Englisch, 586 Seiten, Paperback, Format (B × H): 156 mm x 234 mm, Gewicht: 878 g
Buch, Englisch, 586 Seiten, Paperback, Format (B × H): 156 mm x 234 mm, Gewicht: 878 g
Reihe: Advanced Texts in Econometrics
ISBN: 978-0-19-958715-5
Verlag: OUP Oxford
Forecasting is a major reason for building time series models, linear or nonlinear. The book contains a discussion on forecasting with nonlinear models, both parametric and nonparametric, and considers numerical techniques necessary for computing multi-period forecasts from them. The main focus of the book is on models of the conditional mean, but models of the conditional variance, mainly those of autoregressive conditional heteroskedasticity, receive attention as well. A separate chapter is devoted to state space models. As a whole, the book is an indispensable tool for researchers interested in nonlinear time series and is also suitable for teaching courses in econometrics and time series analysis.
Zielgruppe
Academics, researchers, graduates and advanced undergraduates of econometrics, particularly academics in time series econometrics.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
1: Concepts, models and definitions
2: Nonlinear models in economic theory
3: Parametric nonlinear models
4: The nonparametric approach
5: Parametric linearity tests
6: Testing parameter constancy
7: Nonparametric specification tests
8: Conditional heteroskedasticity
9: State space models
10: Nonparametric models
11: Nonlinear and nonstationary models
12: Estimating parametric models
13: Basic nonparametric estimates
14: Forecasting from nonlinear models
15: Nonlinear impulse responses
16: Building nonlinear models
17: Other topics