Unit root testing in ARMA models: A likelihood ratio approach

Arbeitspapier

In this paper I propose a Likelihood Ratio test for a unit root (LR) with a local-to-unity Autoregressive parameter embedded in ARMA(1,1) models. By dealing explicitly with dependence in a time series through the Moving Average, as opposed to the long Autorregresive lag approximation, the test shows gains in power and has good small-sample properties. The asymptotic distribution of the test is shown to be independent of the short-run parameters. The Monte Carlo experiments show that the LR test has higher power than the Augmented Dickey Fuller test for several sample sizes and true values of the Moving Average parameter. The exception is the case when this parameter is very close to -1 with a considerably small sample size.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Papers ; No. 2016-03

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
• Subject: Likelihood ratio test ; ARMA model ; Unit root test

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Hernández González, Juan Ramón
• Event: Veröffentlichung
• (who): Banco de México
• (where): Ciudad de México
• (when): 2016

Further information

• Handle: http://hdl.handle.net/10419/174433
• Last update: 10.03.2025, 11:42 AM CET