Do Markov-switching models capture nonlinearities in the data?: Tests using nonparametric methods

Robert V. Breunig; Adrian R. Pagan

doi:10.1016/S0378-4754(03)00106-X

Do Markov-switching models capture nonlinearities in the data? Tests using nonparametric methods

Robert V. Breunig^*, Adrian R. Pagan

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

6 Citations (Scopus)

Abstract

Markov-switching models have become popular alternatives to linear autoregressive models. Many papers which estimate nonlinear models make little attempt to demonstrate whether the nonlinearities they capture are of interest or if the models differ substantially from the linear option. By simulating the models and nonparametrically estimating functions of the simulated data, we can evaluate if and how the nonlinear and linear models differ.

Original language	English
Pages (from-to)	401-407
Number of pages	7
Journal	Mathematics and Computers in Simulation
Volume	64
Issue number	3-4
DOIs	https://doi.org/10.1016/S0378-4754(03)00106-X
Publication status	Published - 11 Feb 2004
Event	MSSANZ IMACS 14th Biennial Conference on Modelling and Simulations - Canberra, Australia Duration: 1 Dec 2001 → 1 Dec 2001

Access to Document

10.1016/S0378-4754(03)00106-X

Cite this

@article{8fbe6d26e20143d7a65208c445df1708,

title = "Do Markov-switching models capture nonlinearities in the data?: Tests using nonparametric methods",

abstract = "Markov-switching models have become popular alternatives to linear autoregressive models. Many papers which estimate nonlinear models make little attempt to demonstrate whether the nonlinearities they capture are of interest or if the models differ substantially from the linear option. By simulating the models and nonparametrically estimating functions of the simulated data, we can evaluate if and how the nonlinear and linear models differ.",

keywords = "Markov-switching models, Nonparametric estimation, Simulation methods",

author = "Breunig, {Robert V.} and Pagan, {Adrian R.}",

year = "2004",

month = feb,

day = "11",

doi = "10.1016/S0378-4754(03)00106-X",

language = "English",

volume = "64",

pages = "401--407",

journal = "Mathematics and Computers in Simulation",

issn = "0378-4754",

publisher = "Elsevier B.V.",

number = "3-4",

note = "MSSANZ IMACS 14th Biennial Conference on Modelling and Simulations ; Conference date: 01-12-2001 Through 01-12-2001",

}

TY - JOUR

T1 - Do Markov-switching models capture nonlinearities in the data?

T2 - MSSANZ IMACS 14th Biennial Conference on Modelling and Simulations

AU - Breunig, Robert V.

AU - Pagan, Adrian R.

PY - 2004/2/11

Y1 - 2004/2/11

N2 - Markov-switching models have become popular alternatives to linear autoregressive models. Many papers which estimate nonlinear models make little attempt to demonstrate whether the nonlinearities they capture are of interest or if the models differ substantially from the linear option. By simulating the models and nonparametrically estimating functions of the simulated data, we can evaluate if and how the nonlinear and linear models differ.

AB - Markov-switching models have become popular alternatives to linear autoregressive models. Many papers which estimate nonlinear models make little attempt to demonstrate whether the nonlinearities they capture are of interest or if the models differ substantially from the linear option. By simulating the models and nonparametrically estimating functions of the simulated data, we can evaluate if and how the nonlinear and linear models differ.

KW - Markov-switching models

KW - Nonparametric estimation

KW - Simulation methods

UR - http://www.scopus.com/inward/record.url?scp=0942277639&partnerID=8YFLogxK

U2 - 10.1016/S0378-4754(03)00106-X

DO - 10.1016/S0378-4754(03)00106-X

M3 - Conference article

SN - 0378-4754

VL - 64

SP - 401

EP - 407

JO - Mathematics and Computers in Simulation

JF - Mathematics and Computers in Simulation

IS - 3-4

Y2 - 1 December 2001 through 1 December 2001

ER -

Do Markov-switching models capture nonlinearities in the data? Tests using nonparametric methods

Abstract

Access to Document

Other files and links

Fingerprint

Cite this