Markov-switching quantile autoregression: a Gibbs sampling approach
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DOI: 10.1515/snde-2016-0078
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Cited by:
- Yunmi Kim & Lijuan Huo & Tae-Hwan Kim, 2020. "Dealing with Markov-Switching Parameters in Quantile Regression Models," Working papers 2020rwp-166, Yonsei University, Yonsei Economics Research Institute.
- Xiaochun Liu, 2016.
"Markov switching quantile autoregression,"
Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 356-395, November.
- Liu, Xiaochun, 2013. "Markov-Switching Quantile Autoregression," MPRA Paper 55800, University Library of Munich, Germany.
- Donald Lien & Ziling Wang & Xiaojian Yu, 2021. "Optimal quantile hedging under Markov regime switching," Empirical Economics, Springer, vol. 60(5), pages 2177-2201, May.
- Maruotti, Antonello & Petrella, Lea & Sposito, Luca, 2021. "Hidden semi-Markov-switching quantile regression for time series," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
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More about this item
Keywords
asymmetric Laplace distribution; Gibbs sampler; non-crossing quantiles; quantile regression; regime changes;All these keywords.
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
Statistics
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