alphaols | R Documentation |

This functions estimates the `\bold{\alpha}`

matrix of a VECM.
The following OLS regression of the R-form of the VECM is hereby
utilised:

```
\bold{R}_{0t} = \bold{\alpha}\bold{\beta}\prime \bold{R}_{kt} +
\bold{\varepsilon}_t \qquad t=1, \dots, 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{\beta}
```

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))
```

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