Identification-robust moment-based tests for Markov switching in autoregressive models

  title={Identification-robust moment-based tests for Markov switching in autoregressive models},
  author={Jean-Marie Dufour and Richard Luger},
  journal={Econometric Reviews},
  pages={713 - 727}
ABSTRACT This paper develops tests of the null hypothesis of linearity in the context of autoregressive models with Markov-switching means and variances. These tests are robust to the identification failures that plague conventional likelihood-based inference methods. The approach exploits the moments of normal mixtures implied by the regime-switching process and uses Monte Carlo test techniques to deal with the presence of an autoregressive component in the model specification. The proposed… 
5 Citations
Performance of Markov-Switching GARCH Model Forecasting Inflation Uncertainty
This paper seeks to uncover the non-linear characteristics of uncertainty underlying the US inflation rates over the period 1971-2015 within a regime-switching framework. Accordingly, we employ two
Finite-Sample Generalized Confidence Distributions and Sign-Based Robust Estimators In Median Regressions with Heterogeneous Dependent Errors
We study the problem of estimating the parameters of a linear median regression without any assumption on the shape of the error distribution – including no condition on the existence of moments –
Identification-robust inference with simulation-based pseudo-matching*
We develop a general simulation-based inference procedure for partially specified models. Our procedure is based on matching auxiliary statistics to simulated counterparts where nuisance parameters
Relative Nash welfarism
Relative Nash welfarism is a solution to the problem of aggregating von Neumann-Morgenstern preferences over a set of lotteries. It ranks such lotteries according to the product of any collection of
(Il)legal Assignments in School Choice
In public school choice, students with strict preferences are assigned to schools. Schools are endowed with priorities over students. Incorporating constraints from different applications,


Testing for Regression Coefficient Stability with a Stationary AR(1) Alternative
A bstract-We discuss the problem of testing for constant versus time varying regression coefficients. Our alternative hypothesis allows the coefficients to follow a stationary AR(1) process with
Erratum: The likelihood ratio test under nonstandard conditions: Testing the Markov switching model of GNP
SUMMARY A theory of testing under non-standard conditions is developed. By viewing the likelihood as a function of the unknown parameters, empirical process theory enables us to bound the asymptotic
This paper proposes a class of optimal tests for the constancy of parameters in random coefficients models. Our testing procedure covers the class of Hamilton's models, where the parameters vary
Testing for Regime Switching
We analyze use of a quasi-likelihood ratio statistic for a mixture model to test the null hypothesis of one regime versus the alternative of two regimes in a Markov regime-switching context. This
Testing for Regime Switching: A Comment
In Cho and White (2007) "Testing for Regime Switching" the authors obtain the asymptotic null distribution of a quasi-likelihood ratio (QLR) statistic. The statistic is designed to test the null
Simulation-based ! nite-sample tests for heteroskedasticity and ARCH e * ects
Tests for heteroskedasticity in linear regressions are typically based on asymptotic approximations. We show that the size of such tests can be perfectly controlled in !nite samples through Monte
Markov Regime-Switching Tests: Asymptotic Critical Values
A key insight in Cho and White is to expand the null region to guard against false rejection of the null hypothesis due to a small group of extremal values, and to ease the task of calculating critical values, the limit theory and detail how the covariance of the Gaussian process is linked to the specification of both the model and the parameter space.
Multivariate Tests of Mean–Variance Efficiency With Possibly Non-Gaussian Errors
We develop exact mean–variance efficiency tests of the market portfolio in the context of (conditional and unconditional) capital asset pricing models (CAPM), allowing for a wide class of possibly
Asymptotic null distribution of the likelihood ratio test in Markov switching models
Markov switching (MS) models raise a problem known as testing hypotheses when a nuisance parameter is not identified under the null hypothesis. The author shows that the asymptotic distribution