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A Bayesian Approach to Testing for Markov-Switching in Univariate and Dynamic Factor Models

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  • Kim, Chang-Jin
  • Nelson, Charles R

Abstract

Though Hamilton's (1989) Markov-switching model has been widely estimated in various contexts, formal testing for Markov-switching is not straightforward. Univariate tests in the classical framework by Hansen (1992) and Garcia (1998) do not reject the linear model for GDP. We present Bayesian tests for Markov-switching in both univariate and multivariate settings based on sensitivity of the posterior probability to the prior. We find that evidence for Markov-switching, and thus the business cycle asymmetry, is stronger in a switching version of the dynamic factor model of Stock and Watson (1991) than it is for GDP by itself.

Suggested Citation

  • Kim, Chang-Jin & Nelson, Charles R, 2001. "A Bayesian Approach to Testing for Markov-Switching in Univariate and Dynamic Factor Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(4), pages 989-1013, November.
    • Handle: RePEc:ier:iecrev:v:42:y:2001:i:4:p:989-1013
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    Cited by:

    1. Jacob Boudoukh & Matthew Richardson & Tom Smith & Robert Whitelaw, 1999. "Regime Shifts and Bond Returns," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-010, New York University, Leonard N. Stern School of Business-.
    2. Kim, Chang-Jin & Piger, Jeremy, 2002. "Common stochastic trends, common cycles, and asymmetry in economic fluctuations," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1189-1211, September.
    3. Sugita, Katsuhiro, 2008. "Bayesian analysis of a Markov switching temporal cointegration model," Japan and the World Economy, Elsevier, vol. 20(2), pages 257-274, March.
    4. Issler, João Victor & Notini, Hilton Hostalacio, 2016. "Estimating Brazilian Monthly GDP: a State-Space Approach," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 70(1), March.
    5. Wang, Hong & Forbes, Catherine S. & Fenech, Jean-Pierre & Vaz, John, 2020. "The determinants of bank loan recovery rates in good times and bad – New evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 875-897.
    6. Chang-Jin Kim & Jeremy M. Piger & Richard Startz, 2001. "Permanent and transitory components of business cycles: their relative importance and dynamic relationship," International Finance Discussion Papers 703, Board of Governors of the Federal Reserve System (U.S.).
    7. Chang‐Jin Kim & Jeremy M. Piger & Richard Startz, 2007. "The Dynamic Relationship between Permanent and Transitory Components of U.S. Business Cycles," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(1), pages 187-204, February.
    8. Kagraoka, Yusho & Moussa, Zakaria, 2013. "Quantitative easing, credibility and the time-varying dynamics of the term structure of interest rate in Japan," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 25(C), pages 181-201.
    9. Andrew Binning & Junior Maih, 2015. "Sigma point filters for dynamic nonlinear regime switching models," Working Paper 2015/10, Norges Bank.
    10. Raslan Alzubi & Mustafa Caglayan & Kostas Mouratidis, 2017. "The Risk-Taking Channel in the US: A GVAR Approach," Working Papers 2017009, The University of Sheffield, Department of Economics.
    11. Zhiqiang HU & Yizhu WANG, 2013. "The IPO Cycles in China's A-share IPO Market: Detection Based on a Three Regimes Markov Switching Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 115-131, October.
    12. Rafael Ravnik, 2014. "Short-Term Forecasting of GDP under Structural Changes," Working Papers 40, The Croatian National Bank, Croatia.
    13. López-Herrera, Francisco & Ortiz-Arango, Francisco & Venegas-Martínez, Francisco, 2011. "Modelado de la volatilidad del Índice de Precios y Cotizaciones de la Bolsa Mexicana de Valores con cambios markovianos de régimen," Sección de Estudios de Posgrado e Investigación de la Escuela Superios de Economía del Instituto Politécnico Nacional, in: Perrotini-Hernández, Ignacio (ed.), Crecimiento y Desarrollo Económico en México, volume 1, chapter 10, pages 153-164, Escuela Superior de Economía, Instituto Politécnico Nacional.
    14. Panagiotis Petris & George Dotsis & Panayotis Alexakis, 2022. "Bubble tests in the London housing market: A borough level analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1044-1063, January.
    15. Wahyudi, Imam & Luxianto, Rizky & Iwani, Niken & Sulung, Liyu Adhika Sari, 2008. "Early Warning System in ASEAN Countries Using Capital Market Index Return: Modified Markov Regime Switching Model," MPRA Paper 59723, University Library of Munich, Germany, revised 16 Jul 2010.
    16. Geweke, John, 2007. "Interpretation and inference in mixture models: Simple MCMC works," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3529-3550, April.
    17. Zakaria Moussa, 2016. "How big is the comeback? Japanese exchange rate pass-through assessed by Time-Varying FAVAR," Working Papers hal-01282811, HAL.
    18. Zakaria Moussa, 2016. "How big is the comeback? Japanese exchange rate pass-through assessed by time-varying FAVAR," Post-Print hal-03714934, HAL.
    19. Raslan Alzuabi & Mustafa Caglayan & Kostas Mouratidis, 2021. "The risk‐taking channel in the United States: A GVAR approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5826-5849, October.
    20. de Mello, Luiz & Moccero, Diego, 2011. "Monetary policy and macroeconomic stability in Latin America: The cases of Brazil, Chile, Colombia and Mexico," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 229-245, February.
    21. Tan, Siow-Hooi & Habibullah, Muzafar Shah, 2007. "Business cycles and monetary policy asymmetry: An investigation using Markov-switching models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 297-306.
    22. Xiongfeng Pan & Jing Zhang & Changyu Li & Rong Quan & Bin Li, 2018. "Exploring Dynamic Impact of Foreign Direct Investment on China’s CO $$_{2}$$ 2 Emissions Using Markov-Switching Vector Error Correction Model," Computational Economics, Springer;Society for Computational Economics, vol. 52(4), pages 1139-1151, December.

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