Description Usage Arguments Details Value Author(s) References See Also Examples

Use the `fevd`

function from package vars to tompute the impulse response coefficients
of a VAR(p) (or transformed VECM to VAR(p)) for `n.ahead`

steps.

1 2 3 4 |

`x` |
Object of class ‘ |

`impulse` |
A character vector of the impulses, default is all variables. |

`response` |
A character vector of the responses, default is all variables. |

`n.ahead` |
Integer specifying the steps. |

`ortho` |
Logical, if |

`cumulative` |
Logical, if |

`boot` |
Logical, if |

`ci` |
Numeric, the confidence interval for the bootstrapped errors bands. |

`runs` |
An integer, specifying the runs for the bootstrap. |

`seed` |
An integer, specifying the seed for the |

`...` |
Currently not used. |

The function converts the VAR or VECM computed by package tsDyn into
an object of class ‘`vec2var`

’, on which then the `irf`

method is applied. For details, see the relevant package.

A list of class ‘`varirf`

’ with the following elements is
returned:

`irf` |
A list with matrices for each of the impulse variables containing the impulse response coefficients. |

`Lower` |
If |

`Upper` |
If |

`response` |
Character vector holding the names of the response variables. |

`impulse` |
Character vector holding the names of the impulse variables. |

`ortho` |
Logical, if |

`cumulative` |
Logical, if |

`runs` |
An integer, specifying the number of bootstrap runs. |

`ci` |
Numeric, defining the confidence level. |

`boot` |
Logical, if |

`model` |
Character, containing ‘ |

Bernhard Pfaff

Efron, B. and R. J. Tibshirani (1993), *An Introduction to the
Bootstrap*, Chapman \& Hall, New York.

Hamilton, J. (1994), *Time Series Analysis*, Princeton
University Press, Princeton.

LÃ¼tkepohl, H. (2006), *New Introduction to Multiple Time Series
Analysis*, Springer, New York.

`plot`

for the plot method. `lineVar`

, `VECM`

for the models.

1 2 3 4 5 6 7 8 9 10 11 | ```
data(barry)
## For VAR
mod_var <- lineVar(barry, lag = 2)
irf(mod_var, impulse = "dolcan", response = c("dolcan", "cpiUSA", "cpiCAN"), boot =
FALSE)
## For VECM
mod_VECM <- VECM(barry, lag = 2, estim="ML", r=2)
irf(mod_VECM, impulse = "dolcan", response = c("dolcan", "cpiUSA", "cpiCAN"), boot =
FALSE)
``` |

```
Impulse response coefficients
$dolcan
dolcan cpiUSA cpiCAN
[1,] 0.01263041 -0.0048261838 -0.0123959584
[2,] 0.01442056 -0.0003017074 -0.0089117109
[3,] 0.01439029 0.0018221283 -0.0050181633
[4,] 0.01407837 0.0017585360 -0.0023138114
[5,] 0.01373609 0.0005588836 -0.0003808992
[6,] 0.01339939 -0.0011470315 0.0011612521
[7,] 0.01307097 -0.0030532930 0.0025146740
[8,] 0.01274968 -0.0050206825 0.0037743835
[9,] 0.01243458 -0.0069875398 0.0049833475
[10,] 0.01212512 -0.0089270518 0.0061607665
[11,] 0.01182103 -0.0108278553 0.0073152342
Warning messages:
1: In x/sqrt(t(x) %*% S11 %*% x) :
Recycling array of length 1 in vector-array arithmetic is deprecated.
Use c() or as.vector() instead.
2: In x/sqrt(t(x) %*% S11 %*% x) :
Recycling array of length 1 in vector-array arithmetic is deprecated.
Use c() or as.vector() instead.
3: In x/sqrt(t(x) %*% S11 %*% x) :
Recycling array of length 1 in vector-array arithmetic is deprecated.
Use c() or as.vector() instead.
Impulse response coefficients
$dolcan
dolcan cpiUSA cpiCAN
[1,] 0.01254489 -0.0029302360 -7.383446e-03
[2,] 0.01434484 0.0035655133 -2.087037e-03
[3,] 0.01398363 -0.0006891768 -3.406078e-03
[4,] 0.01356168 -0.0043964840 -2.535065e-03
[5,] 0.01324901 -0.0069522987 -2.187395e-03
[6,] 0.01294200 -0.0086735230 -1.091890e-03
[7,] 0.01263782 -0.0101398959 8.207361e-05
[8,] 0.01233276 -0.0114414225 1.432537e-03
[9,] 0.01203124 -0.0126614792 2.808676e-03
[10,] 0.01173367 -0.0138198949 4.209197e-03
[11,] 0.01144100 -0.0149378777 5.600684e-03
```

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