Specification Testing in Parametric Trending Models with Unknown Errors
This paper considers a class of parametric models with nonparametric autoregressive errors. A new test is established and studied to deal with the parametric specification of the nonparametric autoregressive errors with either stationarity or nonstationarity. Such a test procedure can initially avoid misspecification through the need to parametrically specify the form of the errors. In other words, we estimate the form of the errors and test for stationarity or nonstationarity simultaneously. We establish asymptotic distributions of the proposed test. Both the setting and the results differ from earlier work on testing for unit roots in parametric time series regression. We provide both simulated and real-data examples to show that the proposed nonparametric unit root test works in practice.
Year of publication: |
2014
|
---|---|
Authors: | Gao, Jiti ; King, Maxwell |
Subject: | Zeitreihenanalyse | Time series analysis | Modellierung | Scientific modelling | Schätztheorie | Estimation theory | Regressionsanalyse | Regression analysis | Statistische Methodenlehre | Statistical theory |
Saved in:
Saved in favorites
Similar items by subject
-
Specification testing in parametric trending models with unknown errors
Gao, Jiti, (2014)
-
Applied Statistics and Econometrics : Basic Topics and Tools with Gretl and R
Kivedal, Bjørnar Karlsen, (2024)
-
Multivariate Autocontours for Specification Testing in Multivariate GARCH Models
González-Rivera, Gloria, (2011)
- More ...
Similar items by person