Description Usage Arguments Details Value Note Author(s) References See Also Examples
rank.test.vecm
performs a test for cointegrating rank in VEC models
1 2 3 | rank.test.vecm(Y.ts, etw, p, case, season = NULL, season.start.time = NULL)
rank.test.we(z.ts, etw, p, q = p, n, ex, lex, case)
|
Y.ts,z.ts |
time series data matrix |
etw |
estimation time window, a list of the form |
p |
lag order of the endogenous variables |
q |
lag order of the (weakly) exogenous variables, is set to |
n |
number of endogenous variables |
ex |
number of exogenous variables |
lex |
lag order of the strictly exogenous variables |
case |
intercept and trend options from |
season |
optional seasonal dummies, default value is |
season.start.time |
optional dummy start time, default value is |
Either use rank.test.vecm
or rank.test.we
for VECM and VECM with exogenous I(1) variables respectively.
Values for maximum eigenvalue and trace statistics are returned as well as critical values for the limit distribution of these test statistics.
~~further notes~~
Martin Summer, Klaus Rheinberger, Rainer Puhr
Soeren Johansen. Likelihood-Based Inference in Cointegrated Vector Auto-Regressive Models. Advanced Texts in Econometrics. Oxford University Press, 1995.
Helmut Luetkepohl, Markus Kraetzig. Applied Time Series Econometrics. Cambridge University Press, 2004.
M. Hashem Pesaran, Yongcheol Shin, and Richard J. Smith. Structural analysis of vector error correction models with exogenous I(1) variables. Journal of Econometrics, 97:293-343, 2000.
1 | ##---- Should be DIRECTLY executable !! ----
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