one of the most important hydrological time series task is to determine if there is any trend in the data and how to achieve stationarity when there is nonstationarity behavior in data. detecting trend and stationarity in hydrological time series may help us to understand the possible links between hydrological processes and global climate changes. in this study yearly, monthly and daily stream...

This paper examines stationarity and cointegration of health expenditure and GDP, for a sample of 21 OECD countries using data for the period 1960-1997, by applying a test battery that allows robust inference to be made on the stationarity and cointegration issue. Trend stationarity and no-cointegration are tested using new country-by-country and panel tests, not previously applied in this sett...

Tests of the null hypothesis of stationarity against the unit root alternative play an increasingly important role in empirical work in macroeconomics and in international finance. We show that the use of conventional asymptotic critical values for stationarity tests may cause extreme size distortions, if the model under the null hypothesis is highly persistent. This fact calls into question th...

sts15 Tests for stationarity of a time series Christopher F. Baum, Boston College, [email protected] Abstract: Implements the Elliott–Rothenberg–Stock (1996) DF-GLS test and the Kwiatkowski–Phillips–Schmidt–Shin (1992) KPSS tests for stationarity of a time series. The DF-GLS test is an improved version of the augmented Dickey–Fuller test. The KPSS test has a null hypothesis of stationarity and may be...

The study at hand concentrates on existing stationarity tests as well as some of their variants and generalizations. It also focuses on the results of applying time series methods to univariate non-stationary data in order to stress the importance that stationarity plays in generating accurate and reliable estimates and forecast models to describe the data. Part A of the study focuses on variou...

We present a test of the null hypothesis of stationarity against unit root alternatives for panel data that allows for arbitrary cross-sectional dependence. We treat the short run time series dynamics non-parametrically and thus avoid the need to fit separate models for the individual series. The statistic is simple to compute and is asymptotically normally distributed, even in the presence of ...