FCVARlagSelect {FCVAR}

Select Lag Order

Description

FCVARlagSelect takes a matrix of variables and performs lag selection on it by using the likelihood ratio test. Output and test results are printed to the screen.

Usage

FCVARlagSelect(x, kmax, r, order, opt)

Arguments

x

A matrix of variables to be included in the system.

kmax

The maximum number of lags in the system.

r

The cointegrating rank.This is often set equal to p, the number of variables in the system, since it is better to overspecify than underspecify the model.

order

The order of serial correlation for white noise tests.

opt

An S3 object of class FCVAR_opt that stores the chosen estimation options, generated from FCVARoptions().

Value

An S3 object of type FCVAR_lags containing the results from repeated estimation of the FCVAR model with different orders of the autoregressive lag length. Note that row j of each of the vectors in the FCVAR_lags object contains the associated results for lag length j+1. The FCVAR_lags object includes the following parameters:

D

A (kmax + 1) x 2 vector of estimates of d and b.

loglik

A (kmax + 1) x 1 vector of log-likelihood values.

LRtest

A (kmax + 1) x 1 vector of likelihood ratio test statistics for tests of significance of \Gamma_{j+1}.

pvLRtest

A (kmax + 1) x 1 vector of P-values for the likelihood ratio tests of significance of \Gamma_{j+1}.

i_aic

The lag corresponding to the minimum value of the Akaike information criteria.

aic

A (kmax + 1) x 1 vector of values of the Akaike information criterion.

i_bic

The lag corresponding to the minimum value of the Bayesian information criteria.

bic

A (kmax + 1) x 1 vector of values of the Bayesian information criterion.

pvMVq

A scalar P-value for the Q-test for multivariate residual white noise.

pvWNQ

A (kmax + 1) x 1 vector of P-values for the Q-tests for univariate residual white noise.

pvWNLM

A (kmax + 1) x 1 vector of P-values for the LM-tests for univariate residual white noise.

kmax

The maximum number of lags in the system.

r

The cointegrating rank. This is often set equal to p, the number of variables in the system, since it is better to overspecify than underspecify the model.

p

The number of variables in the system.

cap_T

The sample size.

order

The order of serial correlation for white noise tests.

opt

An S3 object of class FCVAR_opt that stores the chosen estimation options, generated from FCVARoptions().

See Also

FCVARoptions to set default estimation options. FCVARestn is called repeatedly within this function for each candidate lag order. summary.FCVAR_lags prints a summary of the output of FCVARlagSelect to screen.

Other FCVAR specification functions: FCVARbootRank(), FCVARrankTests(), summary.FCVAR_lags(), summary.FCVAR_ranks()

Examples

opt <- FCVARoptions()
opt$gridSearch   <- 0 # Disable grid search in optimization.
opt$dbMin        <- c(0.01, 0.01) # Set lower bound for d,b.
opt$dbMax        <- c(2.00, 2.00) # Set upper bound for d,b.
opt$constrained  <- 0 # Impose restriction dbMax >= d >= b >= dbMin ? 1 <- yes, 0 <- no.
x <- votingJNP2014[, c("lib", "ir_can", "un_can")]
FCVARlagSelectStats <- FCVARlagSelect(x, kmax = 3, r = 3, order = 12, opt)