dot-covCUBS: computes the unconditional variance of the cubs equation with...

In RGAP: Production Function Output Gap Estimation

computes the unconditional variance of the cubs equation with p lags of cubs and k additional lags of the cycle. The cycle follows an AR process of order l.

Description

computes the unconditional variance of the cubs equation with p lags of cubs and k additional lags of the cycle. The cycle follows an AR process of order l.

Usage

.covCUBS(mu, phi, beta, sigma, phiC, sigmaC)

Arguments

mu	constant.
phi	p x 1 vector of parameters for cubs lags.
beta	k x 1 vector of parameters for contemporaneous cycle and cycle lags.
sigma	the innovation variance of the cubs process.
phiC	l x 1 vector of cycle process parameters.
sigmaC	the innovation variance of the cycle process.

Value

A list with a two covariance matrices; the first one depicts the covariance between the cycle and cubs and the second onf the covariance of cubs.

RGAP documentation built on Nov. 2, 2023, 6:02 p.m.