MSTest (version 0.1.5)

DLMCTest: Monte Carlo moment-based test for Markov switching model

Description

This function performs the Local Monte Carlo moment-based test for Markov switching autoregressive models proposed in Dufour & Luger (2017).

Usage

DLMCTest(Y, p, control = list())

Value

List of class DLMCTest (S3 object) with attributes including:

• mdl_h0: List with restricted model attributes. This will be of class ARmdl if p>0 or Nmdl otherwise (S3 objects). See ARmdl or Nmdl.

• theta: Value of nuisance parameters. Specifically, these are the consistent estimates of nuisance parameters as discussed in Dufour & Luger (2017) LMC procedure.

• S0: A (1 x 4)) matrix containing the four moment-based test statistics defined in (11) - (14) in Dufour & Luger (2017).

• F0_min: Test statistic value for min version of Local Monte Carlo moment-based test.

• F0_prod: Test statistic value for prod version of Local Monte Carlo moment-based test.

• FN_min: A (N x 1) vector with simulated test statistics for min version of Local Monte Carlo moment-based test under null hypothesis.

• FN_prod: A (N x 1) vector with simulated test statistics for prod version of Local Monte Carlo moment-based test under null hypothesis.

• pval_min: P-value for min version of Local Monte Carlo moment-based test.

• pval_prod: P-value for prod version of Local Monte Carlo moment-based test.

• FN_min_cv: Vector with 90%, 95%, and 99% Monte Carlo critical values for min version of Local Monte Carlo moment-based test.

• FN_prod_cv: Vector with 90%, 95%, and 99% Monte Carlo critical values for prod version of Local Monte Carlo moment-based test.

• control: List with test procedure options used.

Arguments

Y

Series to be tested

p

Number of autoregressive lags.

control

List with test procedure options including:

• N: Integer determining the number of Monte Carlo simulations. Default is set to 99 as in paper.

• simdist_N: Integer determining the number of simulations for CDF distribution approximation. Default is set to 10000.

• getSE: Boolean indicator. If TRUE, standard errors for restricted model are estimated. If FALSE no standard errors are estimated. Default is TRUE.

References

Dufour, J. M., & Luger, R. 2017. "Identification-robust moment-based tests for Markov switching in autoregressive models." Econometric Reviews, 36(6-9), 713-727.

Examples

set.seed(1234)
# load data used in Hamilton 1989 and extended data used in CHP 2014 
y84 <- as.matrix(hamilton84GNP$GNP_gr)
y10 <- as.matrix(chp10GNP$GNP_gr)

# Set test procedure options
lmc_control = list(N = 99,
                   simdist_N = 10000,
                   getSE = TRUE)

# perform test on Hamilton 1989 data
lmc_gnp84 <- DLMCTest(y84, p = 4, control = lmc_control)
summary(lmc_gnp84)