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Reducing size distortions of parametric stationarity tests
Author(s) -
LANNE MARKKU,
SAIKKONEN PENTTI
Publication year - 2003
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/1467-9892.00314
Subject(s) - unit root , autoregressive model , estimator , mathematics , parametric statistics , econometrics , unit root test , inflation (cosmology) , statistical hypothesis testing , parametric model , statistics , cointegration , physics , theoretical physics
The use of asymptotic critical values in stationarity tests against the alternative of a unit root process is known to lead to over‐rejections in finite samples when the considered process is stationary but highly persistent. We claim that, in recent parametric tests, this is caused by estimation errors which result when the autoregressive parameters used to describe the short‐run dynamics of the process are replaced by estimators. We suggest a modification that corrects for these errors. Simulation results show that the modified test works reasonably well when the persistence is moderate and there is no time trend in the model but it is less effective when the model contains a time trend. An empirical illustration with inflation rate data is provided.