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, ...)
"print"(x, ...)
"summary"(object, ...)
"print"(x, ...)
'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.frame'
or a 'pdata.frame'
object,"levinlin"
for Levin, Lin and Chu (2002), "ips"
for Im, Pesaran and Shin (2003), "madwu"
for Maddala and Wu (1999), or "hadri"
for Hadri (2000),"none"
), individual intercepts ("intercept"
), or individual intercepts and trends ("trend"
),"AIC"
), the SIC ("SIC"
), or on Hall's method ("Hall"
),'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 statistic).
"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 individual intercepts and 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.
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 Tests in Panel Data: Asymptotic and Finite Sample Properties'', Journal of Econometrics, 108(1), 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")
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