Hernández, Juan R. (2016): Unit Root Testing in ARMA Models: A Likelihood Ratio Approach.

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Abstract
Abstract: In this paper I propose a Likelihood Ratio test for a unit root (LR) with a localtounity 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 smallsample properties. The asymptotic distribution of the test is shown to be independent of the shortrun 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.
Item Type:  MPRA Paper 

Original Title:  Unit Root Testing in ARMA Models: A Likelihood Ratio Approach 
Language:  English 
Keywords:  Likelihood ratio test; ARMA model; Unit root test. 
Subjects:  C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C22  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes 
Item ID:  100857 
Depositing User:  PhD Juan R. Hernandez 
Date Deposited:  05 Jun 2020 10:25 
Last Modified:  05 Jun 2020 10:25 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/100857 