IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v208y2019i2p442-467.html
   My bibliography  Save this article

Asymptotic properties of the maximum likelihood estimator in regime switching econometric models

Author

Listed:
  • Kasahara, Hiroyuki
  • Shimotsu, Katsumi

Abstract

Markov regime switching models have been widely used in numerous empirical applications in economics and finance. However, the asymptotic distribution of the maximum likelihood estimator (MLE) has not been proven for some empirically popular Markov regime switching models. In particular, the asymptotic distribution of the MLE has been unknown for models in which some elements of the transition probability matrix have the value of zero, as is commonly assumed in empirical applications with models with more than two regimes. This also includes models in which the regime-specific density depends on both the current and the lagged regimes such as the seminal model of Hamilton (1989) and switching ARCH model of Hamilton and Susmel (1994). This paper shows the asymptotic normality of the MLE and consistency of the asymptotic covariance matrix estimate of these models.

Suggested Citation

  • Kasahara, Hiroyuki & Shimotsu, Katsumi, 2019. "Asymptotic properties of the maximum likelihood estimator in regime switching econometric models," Journal of Econometrics, Elsevier, vol. 208(2), pages 442-467.
  • Handle: RePEc:eee:econom:v:208:y:2019:i:2:p:442-467
    DOI: 10.1016/j.jeconom.2018.09.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304407618301970
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jeconom.2018.09.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Leroux, Brian G., 1992. "Maximum-likelihood estimation for hidden Markov models," Stochastic Processes and their Applications, Elsevier, vol. 40(1), pages 127-143, February.
    2. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 61-82, Suppl. De.
    3. Andrew Ang & Allan Timmermann, 2012. "Regime Changes and Financial Markets," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 313-337, October.
    4. Dahlquist, Magnus & Gray, Stephen F., 2000. "Regime-switching and interest rates in the European monetary system," Journal of International Economics, Elsevier, vol. 50(2), pages 399-419, April.
    5. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    6. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521471626.
    7. Qiang Dai & Kenneth J. Singleton & Wei Yang, 2007. "Regime Shifts in a Dynamic Term Structure Model of U.S. Treasury Bond Yields," Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1669-1706, 2007 12.
    8. Maheu, John M & McCurdy, Thomas H, 2000. "Identifying Bull and Bear Markets in Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 100-112, January.
    9. Evans, Martin & Wachtel, Paul, 1993. "Were price changes during the Great Depression anticipated? : Evidence from nominal interest rates," Journal of Monetary Economics, Elsevier, vol. 32(1), pages 3-34, August.
    10. Garcia, Rene & Perron, Pierre, 1996. "An Analysis of the Real Interest Rate under Regime Shifts," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 111-125, February.
    11. Boldin Michael D., 1996. "A Check on the Robustness of Hamilton's Markov Switching Model Approach to the Economic Analysis of the Business Cycle," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(1), pages 1-14, April.
    12. Chang‐Jin Kim & James Morley & Jeremy Piger, 2005. "Nonlinearity and the permanent effects of recessions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 291-309.
    13. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
    14. 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.
    15. Marine Carrasco & Liang Hu & Werner Ploberger, 2014. "Optimal Test for Markov Switching Parameters," Econometrica, Econometric Society, vol. 82(2), pages 765-784, March.
    16. 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.
    17. Camacho Maximo & Perez Quiros Gabriel, 2007. "Jump-and-Rest Effect of U.S. Business Cycles," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(4), pages 1-39, December.
    18. Margaret M. McConnell & Gabriel Perez-Quiros, 2000. "Output fluctuations in the United States: what has changed since the early 1980s?," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
    19. Alexander David & Pietro Veronesi, 2013. "What Ties Return Volatilities to Price Valuations and Fundamentals?," Journal of Political Economy, University of Chicago Press, vol. 121(4), pages 682-746.
    20. 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.
    21. Edwards, Sebastian & Susmel, Raul, 2001. "Volatility dependence and contagion in emerging equity markets," Journal of Development Economics, Elsevier, vol. 66(2), pages 505-532, December.
    22. De Luca Giovanni & Gallo Giampiero M., 2004. "Mixture Processes for Financial Intradaily Durations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-20, May.
    23. Hamilton, James D., 1996. "Specification testing in Markov-switching time-series models," Journal of Econometrics, Elsevier, vol. 70(1), pages 127-157, January.
    24. Okimoto, Tatsuyoshi, 2008. "New Evidence of Asymmetric Dependence Structures in International Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(3), pages 787-815, September.
    25. Jin Seo Cho & Halbert White, 2007. "Testing for Regime Switching," Econometrica, Econometric Society, vol. 75(6), pages 1671-1720, November.
    26. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models 2 volume set," Cambridge Books, Cambridge University Press, number 9780521478373, July.
    27. Hiroyuki Kasahara & Katsumi Shimotsu, 2018. "Testing the Number of Regimes in Markov Regime Switching Models," Papers 1801.06862, arXiv.org, revised Jan 2018.
    28. Inoue, Tomoo & Okimoto, Tatsuyoshi, 2008. "Were there structural breaks in the effects of Japanese monetary policy? Re-evaluating policy effects of the lost decade," Journal of the Japanese and International Economies, Elsevier, vol. 22(3), pages 320-342, September.
    29. J. B. Taylor & Harald Uhlig (ed.), 2016. "Handbook of Macroeconomics," Handbook of Macroeconomics, Elsevier, edition 1, volume 2, number 2.
    30. Garcia, Rene, 1998. "Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(3), pages 763-788, August.
    31. Vikram Krishnamurthy & Tobias Ryden, 1998. "Consistent Estimation of Linear and Non‐linear Autoregressive Models with Markov Regime," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(3), pages 291-307, May.
    32. Ramchand, Latha & Susmel, Raul, 1998. "Volatility and cross correlation across major stock markets," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 397-416, October.
    33. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    34. Goodwin, Thomas H, 1993. "Business-Cycle Analysis with a Markov-Switching Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 331-339, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ruijun Bu & Jie Cheng & Fredj Jawadi, 2022. "A latent‐factor‐driven endogenous regime‐switching non‐Gaussian model: Evidence from simulation and application," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3881-3896, October.
    2. Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2022. "Maximum Likelihood Estimation in Markov Regime‐Switching Models With Covariate‐Dependent Transition Probabilities," Econometrica, Econometric Society, vol. 90(4), pages 1681-1710, July.
    3. Chaojun Li & Yan Liu, 2020. "Asymptotic Properties of the Maximum Likelihood Estimator in Regime-Switching Models with Time-Varying Transition Probabilities," Papers 2010.04930, arXiv.org, revised Dec 2021.

    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. Hiroyuki Kasahara & Katsumi Shimotsu, 2017. "Asymptotic Properties of the Maximum Likelihood Estimator in Regime Switching Econometric Models," CIRJE F-Series CIRJE-F-1049, CIRJE, Faculty of Economics, University of Tokyo.
    2. 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.
    3. Jean-Marie Dufour & Richard Luger, 2017. "Identification-robust moment-based tests for Markov switching in autoregressive models," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 713-727, October.
    4. 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.
    5. Chevallier, Julien, 2011. "Evaluating the carbon-macroeconomy relationship: Evidence from threshold vector error-correction and Markov-switching VAR models," Economic Modelling, Elsevier, vol. 28(6), pages 2634-2656.
    6. Hiroyuki Kasahara & Katsumi Shimotsu, 2018. "Testing the Number of Regimes in Markov Regime Switching Models," Papers 1801.06862, arXiv.org, revised Jan 2018.
    7. Andrew Ang & Allan Timmermann, 2012. "Regime Changes and Financial Markets," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 313-337, October.
    8. Giovanna Bua & Carmine Trecroci, 2019. "International equity markets interdependence: bigger shocks or contagion in the 21st century?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 155(1), pages 43-69, February.
    9. King, Daniel & Botha, Ferdi, 2015. "Modelling stock return volatility dynamics in selected African markets," Economic Modelling, Elsevier, vol. 45(C), pages 50-73.
    10. Shaw, Charles, 2018. "Regime-Switching And Levy Jump Dynamics In Option-Adjusted Spreads," MPRA Paper 94154, University Library of Munich, Germany, revised 27 May 2019.
    11. Hiroyuki Kasahara & Tatsuyoshi Okimoto & Katsumi Shimotsu, 2014. "Modified Quasi-Likelihood Ratio Test for Regime Switching," The Japanese Economic Review, Japanese Economic Association, vol. 65(1), pages 25-41, March.
    12. Chung-Ming Kuan, 2013. "Markov switching model (in Russian)," Quantile, Quantile, issue 11, pages 13-40, December.
    13. Chevallier, Julien, 2011. "A model of carbon price interactions with macroeconomic and energy dynamics," Energy Economics, Elsevier, vol. 33(6), pages 1295-1312.
    14. Smith, Aaron & Naik, Prasad A. & Tsai, Chih-Ling, 2006. "Markov-switching model selection using Kullback-Leibler divergence," Journal of Econometrics, Elsevier, vol. 134(2), pages 553-577, October.
    15. Meitz, Mika & Saikkonen, Pentti, 2021. "Testing for observation-dependent regime switching in mixture autoregressive models," Journal of Econometrics, Elsevier, vol. 222(1), pages 601-624.
    16. Zeng, Songlin & Bec, Frédérique, 2015. "Do stock returns rebound after bear markets? An empirical analysis from five OECD countries," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 50-61.
    17. Sean D. Campbell, 2002. "Specification Testing and Semiparametric Estimation of Regime Switching Models: An Examination of the US Short Term Interest Rate," Working Papers 2002-26, Brown University, Department of Economics.
    18. Chevallier, Julien, 2012. "Global imbalances, cross-market linkages, and the financial crisis: A multivariate Markov-switching analysis," Economic Modelling, Elsevier, vol. 29(3), pages 943-973.
    19. 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.
    20. Morley James & Piger Jeremy & Tien Pao-Lin, 2013. "Reproducing business cycle features: are nonlinear dynamics a proxy for multivariate information?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 483-498, December.

    More about this item

    Keywords

    Asymptotic distribution; Autoregressive conditional heteroscedasticity; Maximum likelihood estimator; Markov regime switching;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    Statistics

    Access and download statistics

    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:eee:econom:v:208:y:2019:i:2:p:442-467. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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.