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vars (version 1.6-1)

BQ: Estimates a Blanchard-Quah type SVAR

Description

This function estimates a SVAR of type Blanchard and Quah. It returns a list object with class attribute ‘svarest’.

Usage

BQ(x)

Value

A list of class ‘svarest’ with the following elements is returned:

A

An identity matrix.

Ase

NULL.

B

The estimated contemporaneous impact matrix.

Bse

NULL.

LRIM

The estimated long-run impact matrix.

Sigma.U

The variance-covariance matrix of the reduced form residuals times 100.

LR

NULL.

opt

NULL.

start

NULL.

type

Character: “Blanchard-Quah”.

var

The ‘varest’ object ‘x’.

call

The call to BQ().

Arguments

x

Object of class ‘varest’; generated by VAR().

Author

Bernhard Pfaff

Details

For a Blanchard-Quah model the matrix \(A\) is set to be an identity matrix with dimension \(K\). The matrix of the long-run effects is assumed to be lower-triangular and is defined as:

$$ (I_K - A_1 - \cdots - A_p)^{-1}B $$

Hence, the residual of the second equation cannot exert a long-run influence on the first variable and likewise the third residual cannot impact the first and second variable. The estimation of the Blanchard-Quah model is achieved by a Choleski decomposition of:

$$ (I_K - \hat{A}_1 - \cdots - \hat{A}_p)^{-1}\hat{\Sigma}_u (I_K - \hat{A}_1' - \cdots - \hat{A}_p')^{-1} $$

The matrices \(\hat{A}_i\) for \(i = 1, \ldots, p\) assign the reduced form estimates. The long-run impact matrix is the lower-triangular Choleski decomposition of the above matrix and the contemporaneous impact matrix is equal to:

$$ (I_K - A_1 - \cdots - A_p)Q $$ where \(Q\) assigns the lower-trinagular Choleski decomposition.

References

Blanchard, O. and D. Quah (1989), The Dynamic Effects of Aggregate Demand and Supply Disturbances, The American Economic Review, 79(4), 655-673.

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

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

See Also

SVAR, VAR

Examples

Run this code
data(Canada)
var.2c <- VAR(Canada, p = 2, type = "const")
BQ(var.2c)

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