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Regime switching panel data models with interative fixed effects

Author

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  • Tingting Cheng
  • Jiti Gao
  • Yayi Yan

Abstract

In this paper, we introduce a regime switching panel data model with interactive fixed effects. We propose a maximum likelihood estimation method and develop an expectation and conditional maximization algorithm to estimate the unknown parameters. Simulation results show that the algorithm works well in finite samples. The biases of the maximum likelihood estimators are negligible and the root mean squared errors of the maximum likelihood estimators decrease with the increase of either cross-sectional units N or time periods T.

Suggested Citation

  • Tingting Cheng & Jiti Gao & Yayi Yan, 2018. "Regime switching panel data models with interative fixed effects," Monash Econometrics and Business Statistics Working Papers 21/18, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:2018-21
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    File URL: https://www.monash.edu/business/ebs/research/publications/ebs/wp21-2018.pdf
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    References listed on IDEAS

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    1. Patrick Gagliardini & Elisa Ossola & Olivier Scaillet, 2016. "Time‐Varying Risk Premium in Large Cross‐Sectional Equity Data Sets," Econometrica, Econometric Society, vol. 84, pages 985-1046, May.
    2. Hyungsik Roger Moon & Martin Weidner, 2015. "Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects," Econometrica, Econometric Society, vol. 83(4), pages 1543-1579, July.
    3. Laurent Gobillon & Thierry Magnac, 2016. "Regional Policy Evaluation: Interactive Fixed Effects and Synthetic Controls," The Review of Economics and Statistics, MIT Press, vol. 98(3), pages 535-551, July.
    4. Lu, Xun & Su, Liangjun, 2016. "Shrinkage estimation of dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 190(1), pages 148-175.
    5. Sílvia Gonçalves & Benoit Perron & Antoine Djogbenou, 2017. "Bootstrap Prediction Intervals for Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 53-69, January.
    6. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    7. Chang, Yoosoon & Choi, Yongok & Park, Joon Y., 2017. "A new approach to model regime switching," Journal of Econometrics, Elsevier, vol. 196(1), pages 127-143.
    8. Kim, Chang-Jin & Piger, Jeremy & Startz, Richard, 2008. "Estimation of Markov regime-switching regression models with endogenous switching," Journal of Econometrics, Elsevier, vol. 143(2), pages 263-273, April.
    9. Degui Li & Junhui Qian & Liangjun Su, 2016. "Panel Data Models With Interactive Fixed Effects and Multiple Structural Breaks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1804-1819, October.
    10. Marcus Hagedorn & Iourii Manovskii & Kurt Mitman, 2015. "The Impact of Unemployment Benefit Extensions on Employment: The 2014 Employment Miracle?," NBER Working Papers 20884, National Bureau of Economic Research, Inc.
    11. Chen, Shyh-Wei, 2007. "Measuring business cycle turning points in Japan with the Markov Switching Panel model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 76(4), pages 263-270.
    12. Moon, Hyungsik Roger & Weidner, Martin, 2017. "Dynamic Linear Panel Regression Models With Interactive Fixed Effects," Econometric Theory, Cambridge University Press, vol. 33(1), pages 158-195, February.
    13. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
    14. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    15. 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.
    16. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    17. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    18. 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.
    19. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
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    Cited by:

    1. Cheng, Tingting & Xing, Shuo & Yao, Wenying, 2022. "An examination of herding behaviour of the Chinese mutual funds: A time-varying perspective," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    2. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    3. Liu, Hao, 2019. "The communication and European Regional economic growth: The interactive fixed effects approach," Economic Modelling, Elsevier, vol. 83(C), pages 299-311.

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    More about this item

    Keywords

    ECM algorithm; interactive effect; maximum likelihood estimation; panel data model; regime switching.;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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