Testing for Non-Stationarity in R

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In the second part of the series, we will be testing for non-stationarity using the Augmented Dickey-Fuller, the Phillips Perron Test, and the KPSS test.

Codes and Dataset are in here:

Created by Justin S. Eloriaga

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You had an oversight on the differenced KPSS test. The result of differenced inflation stationarity test using KPSS shows that inflation is stationary at first difference since the p-value is 0.1 which is 10%. Your videos are quite informative and very useful. Thanks for all you have been doing.

bolajiadedasola

hi, great videos! One question, kpss(dinf) gives a p-value of 0.1, why do you say it's non-stationary?

estaykylyshbek

Thanks for the nice explanation, i get confused sometimes when reporting unit root tests we take absolute value or consider the sign of value for example test that compares calculated t statistics with tabulated value example t calt= -2.56 and t tabulated= -4.63 In this do we reject null or except .

Thanks

bolisolwak

Why does the p value shows 'NA' when I run adf test in R.

meenalchand

Is it not a requirement to transform the data using a log before using KPSS test?

yonasabebe

what if the results of the three test are contradictory??? both adf and kpss shows non stationarity at level however, the pp test shows stationarity. i tried differencing my data and then the adf and pp shows stationarity but my kpss shows non stationarity. it's very confusing

samfisher

Thank you. Your videos are very helpful...

sajidnoor

Mmm one question, does the number of lags to be chosen in the ADF test depend on the data frequency? For example if I have monthly data could I use 12 lags or something like that?

fvc

Hi! Thanks for these videos, which are very helpful. One question: on the last test KPSS for dinf, we see a high p-value supporting the null hypothesis that the series is stationary: it is then agreeing with the rest of the tests to my understanding so why do you say the test indicates that dinf is non-stationary?

dumoncelclemence

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