Examples of using Unit root in English and their translations into Indonesian
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Colloquial
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Ecclesiastic
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Computer
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Ecclesiastic
Result of Unit Root Test.
For the moment we believe there to be a unit root.
Unit Root Tests for Panel Data.
We can't reject the null of a unit root.
Since this has a unit root it is a non-stationary series.
We can't reject the null of a unit root.
Unit root tests and structural breaks: A survey with applications.
In neither period can we reject the null of a unit root.
Our conclusion is that there is a unit root, there is neither trend nor drift.
In this example we fail to reject the null of a unit root.
Unit root test confirms the stationary of all variables at first difference.
The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis.
The unit root test results indicate that all the variables are first difference stationary.
Further evidence of great crash, the oil price shock and unit root hypothesis.
The results of unit root test reveal all variables are stationary after the first difference.
At the formal level,stationarity can be checked by finding out if the time series contains a unit root.
In a higher-order MA model, a unit root exists if the sum of the MA coefficients is exactly equal to 1.
For now we will concern ourselves with determining whetheror not the series{yt} has a unit root.
GLS-Based Unit Root Tests with Multiple Structural Breaks under Both the Null and the Alternative Hypotheses.
A set of such seriesare considered as co-integrated when it contains one unit root I(1) and a linear combination of them is stationary.
In a higher-order AR model, a unit root exists in the AR part of the model if the sum of the AR coefficients is exactly equal to 1.
Unit root tests allowing for a break in the trend function at an unknown time under both the null and alternative hypotheses.
Similarly, an MA(1) model is said to have a unit root if the estimated MA(1) coefficient is exactly equal to 1.
Our results conØrm that panel data unit root tests have greater power as compared with univariate tests.