| alphaols {urca} | R Documentation |
This functions estimates the \bold{α} matrix of a VECM. The following OLS regression of the R-form of the VECM is hereby utilised:
\bold{R}_{0t} = \bold{α}\bold{β}\prime \bold{R}_{kt} + \bold{\varepsilon}_t \qquad t=1, …, T
alphaols(z, reg.number = NULL)
z |
An object of class |
reg.number |
The number of the equation in the R-form that should
be estimated or if set to |
The cointegrating relations, i.e. \bold{R}_{kt}\prime
\bold{β} are calculated by using z@RK and z@V.
Returns an object of class lm.
Bernhard Pfaff
Johansen, S. (1988), Statistical Analysis of Cointegration Vectors, Journal of Economic Dynamics and Control, 12, 231–254.
Johansen, S. and Juselius, K. (1990), Maximum Likelihood Estimation and Inference on Cointegration – with Applications to the Demand for Money, Oxford Bulletin of Economics and Statistics, 52, 2, 169–210.
Johansen, S. (1991), Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models, Econometrica, Vol. 59, No. 6, 1551–1580.
ca.jo, lm, ca.jo-class
and urca-class.
data(denmark)
sjd <- denmark[, c("LRM", "LRY", "IBO", "IDE")]
sjd.vecm1 <- ca.jo(sjd, ecdet = "const", type="eigen", K=2, spec="longrun",
season=4)
summary(alphaols(sjd.vecm1))
summary(alphaols(sjd.vecm1, reg.number=1))