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.frame' or a matrix containing the time series, a 'pseries' object, a formula, or the name of a column of a 'data.frame' , or a 'pdata.frame' on which the test has to be computed; a'purtest' object for the print and summary methods, |
data |
a 'data.frame' or a 'pdata.frame' object, |
index |
the indexes, |
test |
the test to be computed: one of levinlin for Levin, Lin and Chu (2002), ips for Im, Pesaran and Shin (2003), madwu for Maddala and Wu (1999), and hadri for Hadri (2000), |
exo |
the exogenous variables to introduce in the augmented Dickey-Fuller regressions: this can be nothing ('none' ), individual intercepts ('intercept' ) or individual intercepts and trends ('trend' ), |
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 ('AIC' ), the SIC ('SIC' ) or on Hall's method ('Hall' ), |
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 variable, 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.
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, type = "intercept", test = "madwu")