Joint Hypothesis Specification for Unit Root Tests with a Structural Break

Several tests based on a t-ratio have been proposed in the literature to decide the order of integration of a time series allowing for a structural break. However, another approach based on testing a joint hypothesis of unit root and the irrelevance of some nuisance parameters is also feasible. This paper proposes new unit root tests consistent with the presence of a structural break applying this second perspective. Our approach deals both with the case where the break is not allowed under the null hypothesis, and where it is allowed. Simulations investigate the performance of this proposal compared to the existing tests and show important gains in terms of power. Copyright Royal Economic Society 2006

[1]  Liang-sheng Lu,et al.  [Expression of fusion proteins in beta(2)GP I gene-transfected HEp-2 cells and its clinical application]. , 2002, Zhonghua yi xue za zhi.

[2]  P. Phillips.  Testing for a Unit Root in Time Series Regression , 1988 .

[3]  J. Stock,et al.  Recursive and Sequential Tests of the Unit Root and Trend Break Hypothesis: Theory and International Evidence , 1990 .

[4]  J. Bai,et al.  Estimation of a Change Point in Multiple Regression Models , 1997, Review of Economics and Statistics.

[5]  Michio Hatanaka,et al.  ARE THERE UNIT ROOTS IN REAL ECONOMIC VARIABLES? (AN ENCOMPASSING ANALYSIS OF DIFFERENCE AND TREND STATIONARITY) , 1995 .

[6]  P. Perron,et al.  Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power , 2001 .

[7]  C. Nelson,et al.  Trends and random walks in macroeconmic time series: Some evidence and implications , 1982 .

[8]  P. Perron,et al.  Nonstationarity and Level Shifts With an Application to Purchasing Power Parity , 1992 .

[9]  Pierre Perron,et al.  Structural breaks with deterministic and stochastic trends , 2005 .

[10]  Pierre Perron.  Tests of Joint Hypotheses for Time Series Regression with a Unit Root , 1986 .

[11]  P. Phillips.  Time series regression with a unit root , 1987 .

[12]  P. Perron,et al.  Testing For A Unit Root In A Time Series With A Changing Mean , 1990 .

[13]  W. Fuller,et al.  LIKELIHOOD RATIO STATISTICS FOR AUTOREGRESSIVE TIME SERIES WITH A UNIT ROOT , 1981 .

[14]  Robin L. Lumsdaine,et al.  Multiple Trend Breaks and the Unit-Root Hypothesis , 1997, Review of Economics and Statistics.

[15]  Josep Lluís Carrión i Silvestre.  Integració i estacionarietat de séries temporals amb ruptures estructurals , 1999 .

[16]  In Choi,et al.  TIME-SERIES-BASED ECONOMETRICS , 1998, Econometric Theory.

[17]  J. Bai,et al.  Least squares estimation of a shift in linear processes , 1994 .

[18]  D. Andrews,et al.  Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis , 1992 .

[19]  P. Perron,et al.  Further Evidence on Breaking Trend Functions in Macroeconomic Variables. , 1997 .

[20]  Pierre Perron,et al.  Additional Tests for a Unit Root Allowing for a Break in the Trend Function at an Unknown Time , 1998 .

[21]  Pierre Perron,et al.  Trend, Unit Root and Structural Change in Macroeconomic Time Series , 1994 .

[22]  Serena Ng,et al.  Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag , 1995 .

[23]  Antonio Montañés,et al.  The European Union currencies and the US dollar: from post-Bretton-Woods to the Euro , 2004 .

[24]  Christopher A. Sims,et al.  Advances in Econometrics , 1996 .

[25]  P. Perron,et al.  The Great Crash, The Oil Price Shock And The Unit Root Hypothesis , 1989 .

[26]  Anindya Banerjee,et al.  Recursive and sequential tests for unít roots and structural breaks in long annual GNP series , 1990 .

[27]  H. Luetkepohl,et al.  TESTING FOR A UNIT ROOT IN A TIME SERIES WITH A LEVEL SHIFT AT UNKNOWN TIME , 2002, Econometric Theory.

[28]  Y. Chen.  [The change of serum alpha 1-antitrypsin level in patients with spontaneous pneumothorax]. , 1995, Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases.