interpret the result of the Unit Root Test . Augmented Dickey-Fuller Unit Root T
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Question
interpret the result of the Unit Root Test .
Augmented Dickey-Fuller Unit Root Test on GDP GROWTH_RATE Null Hypothesis: GDPGROWTH_RATE has a unit root Exogenous: Constant Lag Length: 0 (Automatic based on SIC, maxlag-9) t-Statistic Prob.* Augmented Dickey-Fuller test statistic 1% level 5% level 10% level 4.934874 0.0002 -3.581152 2.926622 2.601424 Test critical values MacKinnon (1996) one-sided p-values Augmented Dickey-Fuller Test Equation Dependent Variable: D(GDP GROWTH_RATE) Method: Least Squares Date: 12121/17 Time: 00:20 Sample (adjusted): 1971 2016 Included observations: 46 after adjustments Variable Coefficient Std. Error t-Statistic Prob GDP_GROWTH_RATE(1) -0.699349 0.141716 4.934874 0.0000 2.805557 1.476308 1.900387 0.0639 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.356283 0.341653 9.066665 3616.994 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion 0.285870 11.17429 7.289591 7.369097 7.319374 2.165120 -165.6606 Hannan-Quinn criter 24.35298 Durbin-Watson stat 0.000012Explanation / Answer
Augmented dicky-fuller test is used to test the existence of unit, that is if the model is non stationary.
If the model augmented Dicky-fuller test test statistics is greater than critical statistics then we reject the null hypothesis of presence of unit root and conclude the model is stationary.
We take the absolute value of statistics
From the first table we see that augmented dicky fuller test is greater than critical test statistics at all three levels of significance.
Thus we reject the null hypothesis of unit root. We can interpret that there is no unit root and time series data is stationary.
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