| pssbounds | R Documentation |
Perform Pesaran, Shin, and Smith (2001) cointegration test
pssbounds( data = list(), obs = NULL, fstat = NULL, tstat = NULL, case = NULL, k = NULL, restriction = FALSE, digits = 3, object.out = FALSE )
data |
an optional |
obs |
number of observations |
fstat |
F-statistic of the joint test that variables in first lags are equal to zero: the specific restriction tested
is |
tstat |
t-statistic of the lagged dependent variable |
case |
The case of the test, as per Pesaran, Shin, and Smith (2001). Case I: no intercept or trend; case II: restricted intercept, no trend; case III: unrestricted intercept with no trend; case IV: unrestricted intercept and restricted trend; case V: unrestricted intercept and trend. Case III is most frequently specified |
k |
number of regressors appearing in levels in the estimated model, not including the lagged dependent variable |
restriction |
if you design to test case II or IV of pssbounds, where it is assumed that the constant (case 2) or trend (case 4) are restricted in the resulting F-test, indicate that restriction = |
digits |
the number of digits to round to when showing output. The default is |
object.out |
if |
pssbounds performs post-estimation cointegration testing using the bounds testing procedure from Pesaran, Shin, and Smith (2001). Since test statistics vary based on the number of k regressors, length of the series, these are required, in addition to F- and t-statistics
Soren Jordan and Andrew Q. Philips
# Using the ineq data from dynamac
# We can get all the values by hand
ardl.model <- dynardl(concern ~ incshare10 + urate, data = ineq,
lags = list("concern" = 1, "incshare10" = 1),
diffs = c("incshare10", "urate"),
lagdiffs = list("concern" = 1),
ec = TRUE, simulate = FALSE)
summary(ardl.model)
pssbounds(obs = 47, fstat = 7.01578, tstat = -3.223, case = 3, k = 1)
# Or just pass a dynardl model.
pssbounds(ardl.model)
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