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Questions tagged [kpss-test]

Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test is used to analyze time series. The null hypothesis is that the time series is stationary. It is often used to complement an Augmented Dickey Fuller (ADF) test.

Two statistical tests would be used to check the stationarity of a time series – the Augmented Dickey Fuller (ADF) test and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test. Both tests should be used. The ADF test null and alternate hypothesis are:

Null Hypothesis: The series has a unit root.

Alternate Hypothesis: The series has no unit root.

If the null hypothesis in failed to be rejected, this test may provide evidence that the series is non-stationary.

For the KPSS test the null and alternative hypotheses are reversed:

Null Hypothesis: The process is trend stationary.

Alternate Hypothesis: The series has a unit root (series is not stationary).

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What is the difference between a stationary test and a unit root test?

What is the difference between the Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test and the augmented Dickey-Fuller (ADF) test? Are they testing the same thing? Or do we need to use them in different situations?
Flying pig
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How to know if a time series is stationary or non-stationary?

I am using R, I searched on Google and learnt that kpss.test(), PP.test(), and adf.test() are used to know about stationarity of time series. But I am not a statistician, who can interpret their results > PP.test(x) Phillips-Perron Unit Root…
Sagar Nikam
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Contradictory results of ADF and KPSS unit root tests

To check whether the data is stationary or not, I computed KPSS and ADF test and got the following results adf.test(td,alternative = "stationary") Augmented Dickey-Fuller Test data: td Dickey-Fuller = -3.7212, Lag order = 3, p-value =…
Praveen
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Unit root tests and stationarity

Two common methods of testing whether a time series is stationary are the KPSS and ADF tests. If my understanding is correct, these tests essentially work by measuring the residuals of fitting the time-series to an autoregressive model which is…
gamerx
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Best practice for ADF/KPSS unit root testing sequence?

I've been quite confused by the various unit root testing strategies recommended in the literature, so I was hoping others may have some advice on the best way to proceed using ADF and KPSS tests. Pfaff (2008) describes the following procedure using…
dreamon
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What are the assumptions for checking the stationarity of a time series?

I am checking stationarity or non-stationarity of a time series with R and I am using adf.test and kpss.test in tseries package. What are the assumptions for these tests? Is following a Gaussian distribution by the data set one of the…
Fred
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How to interpret KPSS results?

I'm using R to calculate the KPSS to check the stationarity. The library that I'm using is tseries and the function is kpss.test I have done a simple test using cars (a default matrix on R). The code is: > k <- kpss.test(cars$dist,…
Dail
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Bounded dependent variable: can it be unit-root non-stationary?

I have linear time series regression model where the dependent variable Y is bounded between 0 and 1. Using classical unit root tests (dickey-fuller and kpss), results would make you conclude that Y is non-stationary (cannot reject $H_0$ in…
Giuseppe
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Unit root tests ambiguous - is time series stationary?

I am testing a time series (quarterly) for stationarity. However, using the KPSS test, the ADF test and PP test, I get different results (ADF and PP reject non-stationarity, KPSS rejects stationarity, all of them at a 95% significance level). I am…
Lila
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Seasonal data deemed stationary by ADF and KPSS tests

I have got two time series and I want to evaluate a VAR model. For this, it is necessary that both time series are stationary. Using R, I have found periodicity with the function spectrum in the lag 16 and 98 in both time series and lots of others…
T. Beige
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Is there an optmal lag choice in the KPSS test?

Is there an optimal lag choice in the KPSS test in Stata? For instance, in my example below, for some lags (less than 7) you reject the null for any level of significance. But afterwards, that does not happen. How do I interpret this? 10%: 0.119 5%…
John Doe
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How to determine correlation between stationary and non-stationary time series

I have three time series of economic data based on quarterly observations; A, B and C, and I would like to ascertain the correlation (or not) between A and C as well as the correlation between B and S. The 1st order differenced time series of B…
Allan
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Stationarity tests in a regression model

In a model I am trying to justify, a mortgage rate spread is estimated by regression on a swap spread using around 40 monthly data-points. The model fails the assumptions of heteroskedasticity and serial correlation but the coefficients are still…
Des
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How can this time series be stationary?

I have the following irregularly spaced time series. The related autocorrelogram is: and I run the following tests: > adf.test(x) Augmented Dickey-Fuller Test data: x Dickey-Fuller = -70, Lag order = 70, p-value = 0.01 alternative hypothesis:…
stochazesthai
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Interpreting results of KPSS test in R

I've been trying to create an ARIMA model however, I'm not sure how to determine if the data is stationary or not. I preformed a KPSS test in R using kpss.test from package tseries and these are the results: KPSS Level = 1.966, Truncation lag…
jlang
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