IDEAS home Printed from https://ideas.repec.org/a/sgh/annals/i40y2016p479-490.html
   My bibliography  Save this article

Przełącznikowe modele Markowa (MS) – charakterystyka i sposoby zastosowań w badaniach ekonomicznych

Author

Listed:
  • Monika Kośko

    (Wyższa Szkoła Informatyki i Ekonomii w Olsztynie)

  • Marta Kwiecień

    (Uniwersytet Warmińsko-Mazurski w Olsztynie)

  • Joanna Stempińska

    (Uniwersytet Warmińsko-Mazurski w Olsztynie)

Abstract

The paper presents the characteristics of Markov switching models (MS), their types, estimation method, and various methods of their application in economic research. MS models are a practical tool that is used in the analysis of economic processes characterised by the occurrence of certain states (regimes). MS models allow to describe series characterised by regular volatility over time, for example series in which there are periods of increased and decreased variability or faster and slower growth. The purpose of this article is to draw attention to the fact that Markov switching models are essential tools in modelling and forecasting such important economic issues as business cycles and time series of the financial market.

Suggested Citation

  • Monika Kośko & Marta Kwiecień & Joanna Stempińska, 2016. "Przełącznikowe modele Markowa (MS) – charakterystyka i sposoby zastosowań w badaniach ekonomicznych," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 40, pages 479-490.
    • Handle: RePEc:sgh:annals:i:40:y:2016:p:479-490
    as

    Download full text from publisher

    File URL: http://rocznikikae.sgh.waw.pl/p/roczniki_kae_z40_35.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hamilton, James D & Gang, Lin, 1996. "Stock Market Volatility and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 573-593, Sept.-Oct.
    2. James D. Hamilton, 2005. "What's real about the business cycle?," Review, Federal Reserve Bank of St. Louis, vol. 87(Jul), pages 435-452.
    3. Dueker, Michael J, 1997. "Markov Switching in GARCH Processes and Mean-Reverting Stock-Market Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 26-34, January.
    4. Sichel, Daniel E, 1994. "Inventories and the Three Phases of the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 269-277, July.
    5. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1.
    6. Hans-Martin Krolzig, 2001. "Markov-Switching Procedures for Dating the Euro-Zone Business Cycle," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 70(3), pages 339-351.
    7. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    8. Joanna Janczura & Rafał Weron, 2012. "Efficient estimation of Markov regime-switching models: An application to electricity spot prices," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(3), pages 385-407, July.
    9. Goldfeld, Stephen M. & Quandt, Richard E., 1973. "A Markov model for switching regressions," Journal of Econometrics, Elsevier, vol. 1(1), pages 3-15, March.
    10. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    11. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    12. Hamilton, James D., 1988. "Rational-expectations econometric analysis of changes in regime : An investigation of the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 385-423.
    13. Weron, Rafal & Janczura, Joanna, 2010. "Efficient estimation of Markov regime-switching models: An application to electricity wholesale market prices," MPRA Paper 26628, University Library of Munich, Germany.
    14. Janczura, Joanna & Weron, Rafal, 2010. "An empirical comparison of alternate regime-switching models for electricity spot prices," Energy Economics, Elsevier, vol. 32(5), pages 1059-1073, September.
    15. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    16. Joanna Janczura, 2014. "Pricing electricity derivatives within a Markov regime-switching model: a risk premium approach," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 79(1), pages 1-30, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    2. Liu, Wen-Hsien & Chyi, Yih-Luan, 2006. "A Markov regime-switching model for the semiconductor industry cycles," Economic Modelling, Elsevier, vol. 23(4), pages 569-578, July.
    3. Chung-Ming Kuan, 2013. "Markov switching model (in Russian)," Quantile, Quantile, issue 11, pages 13-40, December.
    4. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    5. Maddalena Cavicchioli, 2021. "OLS Estimation of Markov switching VAR models: asymptotics and application to energy use," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(3), pages 431-449, September.
    6. Laurent Calvet & Adlai Fisher, 2003. "Regime-Switching and the Estimation of Multifractal Processes," Harvard Institute of Economic Research Working Papers 1999, Harvard - Institute of Economic Research.
    7. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Advances in Econometrics, in: Missing Data Methods: Time-Series Methods and Applications, pages 1-86, Emerald Group Publishing Limited.
    8. Joanna Janczura & Rafal Weron, 2012. "Inference for Markov-regime switching models of electricity spot prices," HSC Research Reports HSC/12/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    9. Hamilton, J.D., 2016. "Macroeconomic Regimes and Regime Shifts," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 163-201, Elsevier.
    10. Liu, Wen-Hsien & Chung, Ching-Fan & Chang, Kuang-Liang, 2013. "Inventory change, capacity utilization and the semiconductor industry cycle," Economic Modelling, Elsevier, vol. 31(C), pages 119-127.
    11. Richard D. F. Harris & Murat Mazibas, 2022. "A component Markov regime‐switching autoregressive conditional range model," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 650-683, April.
    12. Dmitry Kulikov, 2012. "Testing for Rational Speculative Bubbles on the Estonian Stock Market," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 4(1).
    13. Masaru Chiba, 2023. "Robust and efficient specification tests in Markov-switching autoregressive models," Statistical Inference for Stochastic Processes, Springer, vol. 26(1), pages 99-137, April.
    14. Jeremy J. Nalewaik, 2011. "Forecasting recessions using stall speeds," Finance and Economics Discussion Series 2011-24, Board of Governors of the Federal Reserve System (U.S.).
    15. AKA, Bédia F., 2009. "Business Cycle And Sectoral Fluctuations: A Nonlinear Model For Côte D’Ivoire," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 9(1), pages 111-126.
    16. Olivier Darné & Laurent Ferrara, 2011. "Identification of Slowdowns and Accelerations for the Euro Area Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(3), pages 335-364, June.
    17. Baele, Lieven, 2005. "Volatility Spillover Effects in European Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(2), pages 373-401, June.
    18. Psaradakis, Zacharias & Sola, Martin, 1998. "Finite-sample properties of the maximum likelihood estimator in autoregressive models with Markov switching," Journal of Econometrics, Elsevier, vol. 86(2), pages 369-386, June.
    19. Vika Koban, 2017. "The impact of market coupling on Hungarian and Romanian electricity markets: Evidence from the regime-switching model," Energy & Environment, , vol. 28(5-6), pages 621-638, September.
    20. Monica Billio & Laurent Ferrara & Dominique Guegan & Gian Luigi Mazzi, 2009. "Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro," Documents de travail du Centre d'Economie de la Sorbonne 09053, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sgh:annals:i:40:y:2016:p:479-490. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michał Bernardelli (email available below). General contact details of provider: https://edirc.repec.org/data/sgwawpl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.