Solved – How to interpret the result of Fisher’s unit root test

Following are the results from Fisher-type unit-root test for RDI (dependent variable). How do you interpret it?

Based on Phillips-Perron tests:  Ho: All panels contain unit roots           Number of panels       =    100 Ha: At least one panel is stationary        Avg. number of periods =  10.74  AR parameter:    Panel-specific             Asymptotics: T -> Infinity Panel means:     Included Time trend:      Included Newey-West lags: 1 lag                                       Statistic               p-value  Inverse chi-squared(196)     P       207.1519                 0.2788 Inverse normal               Z        2.0005                  0.9773 Inverse logit t(389)         L*        0.5211                0.6987 Modified inv. chi-squared    Pm        0.5633                 0.2866  P statistic requires number of panels to be finite. Other statistics are suitable for finite or infinite number of panels. 

So in the upper left you see which hypothesis you are testing. In this case your null is that all of your panels contain a unit root. In the lower half of your output you see the outcome of the test statistics (P,Z,L*,Pm) to test this hypothesis and their associated p-value. All of the p-values are relatively large. If we were to use a 10% level of statistical significance (5% is more commonly used), you can see that all of your p-values exceed this threshold. So on the basis of this we cannot reject the null hypothesis. Which means that your panel data contains a unit root.

Similar Posts:

Rate this post

Leave a Comment