| purtest {plm} | R Documentation |
purtest implements several testing procedures that have been proposed to test unit root hypotheses with panel data.
purtest(object, data = NULL, index = NULL,
test= c("levinlin", "ips", "madwu", "hadri"),
exo = c("none", "intercept", "trend"),
lags = c("SIC", "AIC", "Hall"), pmax = 10, Hcons = TRUE,
q = NULL, dfcor = FALSE, fixedT = TRUE, ...)
## S3 method for class 'purtest'
print(x, ...)
## S3 method for class 'purtest'
summary(object, ...)
## S3 method for class 'summary.purtest'
print(x, ...)
object, x |
Either a |
data |
a |
index |
the indexes, |
test |
the test to be computed: one of |
exo |
the exogenous variables to introduce in the augmented Dickey-Fuller regressions: this can be nothing ( |
lags |
the number of lags to be used for the augmented Dickey-Fuller regressions: either an integer (the number of lags for all time series), a vector of integers (one for each time series), or a character string for an automatic computation of the number of lags, based on either the AIC ( |
pmax |
maximum number of lags, |
Hcons |
a boolean indicating whether the heteroscedasticity-consistent test of Hadri should be computed, |
q |
the bandwidth for the estimation of the long-run variance, |
dfcor |
should the standard deviation of the regressions be computed using a degrees-of-freedom correction? |
fixedT |
should the different ADF regressions be computed using the same number of observations?, |
... |
further arguments. |
All these tests except 'hadri' are based on the estimation of augmented Dickey-Fuller regressions for each time series. A statistic is then computed using the t-statistic associated with the lagged variable.
The kind of test to be computed can be specified in several ways:
A formula/data interface (if data is a
data.frame, an additional index argument should be
specified); the formula should be of the form: y~0, y~1, or y~trend for a test with no exogenous variables, with an intercept, or with a time trend, respectively.
A data.frame, a matrix, a pseries: in this case, the exogenous variables are specified using the exo argument.
The Hadri statistic is the cross-sectional average of the individual KPSS statistics, standardized by their asymptotic mean and standard deviation.
An object of class 'purtest': a list with the elements 'statistic' (a 'htest' object), 'call', 'args', 'idres' (containing results from the individual regressions), and 'adjval' (containing the simulated means and variances needed to compute the statistics).
Yves Croissant
Hadri K. (2000). “Testing for Unit Roots in Heterogeneous Panel Data”, The Econometrics Journal, 3, pp. 148–161.
Im K.S., Pesaran M.H. and Shin Y. (2003). “Testing for Unit Roots in Heterogeneous Panels”, Journal of Econometrics, 115(1), pp. 53–74.
Levin A., Lin C.F. and Chu C.S.J. (2002). “Unit Root Test in Panel Data: Asymptotic and Finite Sample Properties”, Journal of Econometrics, 108, pp. 1–24.
Maddala G.S. and Wu S. (1999). “A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test”, Oxford Bulletin of Economics and Statistics, 61, Supplement 1, pp. 631–652.
data("Grunfeld", package = "plm")
y <- data.frame(split(Grunfeld$inv, Grunfeld$firm))
purtest(y, pmax = 4, exo = "intercept", test = "madwu")
## same via formula interface
purtest(inv ~ 1, data = Grunfeld, index = "firm", pmax = 4, test = "madwu")