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MSTest: An R-Package for Testing Markov Switching Models

Gabriel Rodriguez-Rondon, Jean-Marie Dufour

arXiv 12 Nov 2024 · Statistics — Methodology

arXiv:2411.08188 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We present the R package MSTest, which implements hypothesis testing procedures to identify the number of regimes in Markov switching models. These models have wide-ranging applications in economics, finance, and numerous other fields. The MSTest package includes the Monte Carlo likelihood ratio test procedures proposed by Rodriguez-Rondon and Dufour (2024), the moment-based tests of Dufour and Luger (2017), the parameter stability tests of Carrasco, Hu, and Ploberger (2014), and the likelihood ratio test of Hansen (1992). Additionally, the package enables users to simulate and estimate univariate and multivariate Markov switching and hidden Markov processes, using the expectation-maximization (EM) algorithm or maximum likelihood estimation (MLE). We demonstrate the functionality of the MSTest package through both simulation experiments and an application to U.S. GNP growth data.

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87
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237
in-text mentions
87
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Rodriguez-Rondon, G. and Dufour, J.-M (2024) Monte Carlo likelihood ratio tests for Markov switching models self1.000319100%
2Hansen, B. E (1992) The likelihood ratio test under nonstandard conditions: testing the markov switching model of gnp1.000197100%
3Dufour, J.-M. and Luger, R (2017) Identification-robust moment-based tests for markov switching in autoregressive models self1.000196100%
4Carrasco, M., Hu, L., and Ploberger, W (2014) Optimal test for markov switching parameters1.000166100%
5Qu, Z. and Zhuo, F (2021) Likelihood ratio-based tests for markov regime switching1.000154100%
6Kasahara, H. and Shimotsu, K (2018) Testing the number of regimes in markov regime switching models1.000114100%
7Garcia, R (1998) Asymptotic null distribution of the likelihood ratio test in markov switching models1.000104100%
8Cho, J.-S. and White, H (2007) Testing for regime switching1.00073100%
9Hamilton, J. D (1989) A new approach to the economic analysis of nonstationary time series and the business cycle1.00063100%
10Dufour, J.-M (2006) Monte carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics self0.87462100%

Showing the top 10 of 87 scored citations.