specify_identification_bsvars function

R6 Class Representing IdentificationBSVARs

The class IdentificationBSVARs presents the identifying restrictions for the bsvar models.

Examples

specify_identification_bsvars$new(N = 3) # recursive specification for a 3-variable system

B = matrix(c(TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE), 3, 3); B
specify_identification_bsvars$new(N = 3, B = B) # an alternative identification pattern

## ------------------------------------------------
## Method `specify_identification_bsvars$get_identification`
## ------------------------------------------------

B    = matrix(c(TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE), 3, 3); B
spec = specify_identification_bsvars$new(N = 3, B = B)
spec$get_identification()

## ------------------------------------------------
## Method `specify_identification_bsvars$set_identification`
## ------------------------------------------------

spec = specify_identification_bsvars$new(N = 3) # specify a model with the default option
B    = matrix(c(TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE), 3, 3); B
spec$set_identification(N = 3, B = B)  # modify an existing specification
spec$get_identification()              # check the outcome

Public fields

• VB: a list of N matrices determining the unrestricted elements of matrix $B$.

Methods

Public methods

• list("specify_identification_bsvars$new()")

• list("specify_identification_bsvars$get_identification()")

• list("specify_identification_bsvars$set_identification()")

• list("specify_identification_bsvars$clone()")

Method new()

Create new identifying restrictions IdentificationBSVARs.

Usage

specify_identification_bsvars$new(N, B)

Arguments

• N: a positive integer - the number of dependent variables in the model.

• B: a logical NxN matrix containing value TRUE for the elements of the structural matrix $B$ to be estimated and value FALSE for exclusion restrictions to be set to zero.

Returns

Identifying restrictions IdentificationBSVARs.

Method get_identification()

Returns the elements of the identification pattern IdentificationBSVARs as a list.

Usage

specify_identification_bsvars$get_identification()

Examples

B    = matrix(c(TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE), 3, 3); B
spec = specify_identification_bsvars$new(N = 3, B = B)
spec$get_identification()

Method set_identification()

Set new starting values StartingValuesBSVAR.

Usage

specify_identification_bsvars$set_identification(N, B)

Arguments

• N: a positive integer - the number of dependent variables in the model.

• B: a logical NxN matrix containing value TRUE for the elements of the structural matrix $B$ to be estimated and value FALSE for exclusion restrictions to be set to zero.

Examples

spec = specify_identification_bsvars$new(N = 3) # specify a model with the default option
B    = matrix(c(TRUE,TRUE,TRUE,FALSE,FALSE,TRUE,FALSE,TRUE,TRUE), 3, 3); B
spec$set_identification(N = 3, B = B)  # modify an existing specification
spec$get_identification()              # check the outcome

Method clone()

The objects of this class are cloneable with this method.

Usage

specify_identification_bsvars$clone(deep = FALSE)

Arguments

• deep: Whether to make a deep clone.