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Related to Stationarity: Autocorrelation
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Formal statistical tool for checking stationarity of the time series data is to go for Augumented Dickey Fuller (ADF) test it is used to know when to difference time series data to make it stationary.
At the end of the day, what the unit root wars taught us is that it is very difficult to say anything with much confidence about stationarity.
In order to have a good understanding of the stationarity of the time series, ACF and PACF graphs are depicted in Figures 2 and 3, respectively.
Stationarity is a necessary condition for cointegration but it is not sufficient as cointegration also requires that the elasticity of stock prices with respect to consumer prices be positive: [beta] > 0.
All the models fitted in this analysis required checking for stationarity of the series; which was checked by performing Dickey-Fuller unit root tests.
Therefore, we plot the cointegrating vectors over time and check the stationarity of the cointegrating vectors.
Empirical tests of the sustainability of fiscal policies generally involve stationarity and unit root tests for public debt and deficits, and cointegration tests for government expenditures and tax revenues.
This study mainly examined the efficiency of Asia-Pacific foreign exchange market, in respect of normality, stationarity, and cointegration stability over time.
Kwiatkowski-Phillips-Schmidt-Shin (KPSS 1992) test with constant and trend terms is used for stationarity of data.
The stationarity tests are used to conclude whether the regions have converged, while the unit root tests come in handy to conclude whether the regions are converging.
Recent empirical studies hang on testing for stationarity in the fiscal balance series or cointegration between government expenditure and revenue.
First, the stationarity or a lack thereof of the dependent variable (IU) and the explanatory variables (TEL, INCOME, and RURAL) requires testing.