Za | R Documentation |
Compute Phillips' (1987) Za and Zt statistics for the null hypothesis that y has a unit root.
Za(y,p=1,v=15,ker_fun="parzen",aband=0,filter=0)
y |
The data of dependent variable in a regression. |
p |
Order of the time polynomial in the cointegrating regressio. |
v |
Number of autocovariance terms to compute the spectrum at frequency zero, default=15. |
ker_fun |
Set kernel function to one of the available kernels, default="parzen". See section |
aband |
Whether to activate the automatic bandwidth selection. |
filter |
Whether to use an AR(1) filter to compute the spectrum at frequency zero. |
alpha |
Estimate of the AR(1) coefficient. |
za |
Za statistic for the series under the null has a unit root. Reject the null hypothesis of a unit root if the test statistic < critical value. |
za_cv |
Critical values of Za. |
zt |
Zt statistic for the series under the null has a unit root. Reject the null hypothesis of a unit root if the test statistic < critical value. |
zt_cv |
Critical values of Zt. |
Ho Tsung-wu <tsungwu@ntnu.edu.tw>, College of Management, National Taiwan Normal University.
Ouliaris, S., J. Y. Park, and P. C. B. Phillips (1989) Testing for a Unit Root in the Presence of a Maintained Trend. Ch. 1 in Baldev Raj (ed.), Advances in Econometrics and Modelling. Netherlands: Kluwer Academic Publishers.
Phillips, P. C. B. (1987) Time Series Regression with a Unit Root. Econometrica, 55, 277-301.
data(macro)
y=macro[,1]
Za(y,p=1,v=10)
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