IDEAS home Printed from https://ideas.repec.org/a/cuf/journl/y2011v12i1p157-181.html
   My bibliography  Save this article

Has China's Economy Become More Stable and Inertial? Nonlinear Investigations Based on Structural Break and Duration Dependent Regime Switching Models

Author

Listed:
  • Angang Hu

    (School of Public Policy and Management, Tsinghua University)

  • Jie Lu

    (School of Public Policy and Management, Tsinghua University)

  • Zhengyan Xiao

    (The Center for Applied Statistics, Renmin University of China)

Abstract

In this study we use both the structural break model and duration dependent transition model to study the characteristics of China's GDP growth from 1953 to 2009. The empirical results show that China's economic growth had become more stable since the economic reform in the end of the 1970s, and had transformed from a "low growth rate, high volatility" state to a "high growth rate, low volatility" state. In contrast to other transitional countries, China's structural break did not happen immediately, but rather it experienced a long transition period (1977-1992) which shows that China's economic development has a strong "growth inertia".

Suggested Citation

  • Angang Hu & Jie Lu & Zhengyan Xiao, 2011. "Has China's Economy Become More Stable and Inertial? Nonlinear Investigations Based on Structural Break and Duration Dependent Regime Switching Models," Annals of Economics and Finance, Society for AEF, vol. 12(1), pages 157-181, May.
    • Handle: RePEc:cuf:journl:y:2011:v:12:i:1:p:157-181
    as

    Download full text from publisher

    File URL: http://www.aeconf.net/Articles/May2011/aef120110.pdf
    Download Restriction: no
    File URL: http://down.aefweb.net/AefArticles/aef120110.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Eric Girardin, 2005. "Growth-cycle features of East Asian countries: are they similar?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(2), pages 143-156.
    3. Pok-sang Lam, 2004. "A Markov-Switching Model Of Gnp Growth With Duration Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(1), pages 175-204, February.
    4. Vadim Marmer, 2008. "Testing the null hypothesis of no regime switching with an application to GDP growth rates," Empirical Economics, Springer, vol. 35(1), pages 101-122, August.
    5. Iiboshi, Hirokuni, 2007. "Duration dependence of the business cycle in Japan: A Bayesian analysis of extended Markov switching model," Japan and the World Economy, Elsevier, vol. 19(1), pages 86-111, January.
    6. Layton, Allan P. & Smith, Daniel R., 2007. "Business cycle dynamics with duration dependence and leading indicators," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 855-875, December.
    7. Krolzig, Hans-Martin, 2001. "Business cycle measurement in the presence of structural change: international evidence," International Journal of Forecasting, Elsevier, vol. 17(3), pages 349-368.
    8. Chang-Jin Kim & Charles R. Nelson, 1999. "Has The U.S. Economy Become More Stable? A Bayesian Approach Based On A Markov-Switching Model Of The Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 608-616, November.
    9. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
    10. Gabriel Perez-Quiros & Margaret M. McConnell, 2000. "Output Fluctuations in the United States: What Has Changed since the Early 1980's?," American Economic Review, American Economic Association, vol. 90(5), pages 1464-1476, December.
    11. Charles R. Nelson, 2000. "Output fluctuations in the United States: what has changed since the early 1980s? comments," Proceedings, Federal Reserve Bank of San Francisco.
    12. Terence C. Mills & Ping Wang, 2003. "Have output growth rates stabilised? evidence from the g‐7 economies," Scottish Journal of Political Economy, Scottish Economic Society, vol. 50(3), pages 232-246, August.
    13. Durland, J Michael & McCurdy, Thomas H, 1994. "Duration-Dependent Transitions in a Markov Model of U.S. GNP Growth," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 279-288, July.
    14. 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.
    15. 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.
    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. Woon Kan Yap & Siong Hock Law & Judhiana Abdul-Ghani, 2019. "Effects of Credit Market Freedom on Output Reallocation in China's Banking Sector Through the Intermediation of Cost X-inefficiency," Annals of Economics and Finance, Society for AEF, vol. 20(2), pages 691-720, November.

    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. Jie Lu & Angang Hu & Yilong Yan, 2012. "Nonlinear investigations of China's agricultural transformation based on the structural break regime switching model," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 4(1), pages 52-68, January.
    2. Iiboshi, Hirokuni, 2007. "Duration dependence of the business cycle in Japan: A Bayesian analysis of extended Markov switching model," Japan and the World Economy, Elsevier, vol. 19(1), pages 86-111, January.
    3. Vitor Castro, 2015. "The Portuguese business cycle: chronology and duration dependence," Empirical Economics, Springer, vol. 49(1), pages 325-342, August.
    4. 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.
    5. Castro, Vítor, 2010. "The duration of economic expansions and recessions: More than duration dependence," Journal of Macroeconomics, Elsevier, vol. 32(1), pages 347-365, March.
    6. 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.
    7. Chevallier, Julien, 2011. "A model of carbon price interactions with macroeconomic and energy dynamics," Energy Economics, Elsevier, vol. 33(6), pages 1295-1312.
    8. Vitor Castro, 2013. "The duration of business cycle expansions and contractions: are there change-points in duration dependence?," Empirical Economics, Springer, vol. 44(2), pages 511-544, April.
    9. Giorgio Canarella & WenShwo Fang & Stephen M. Miller & Stephen K. Pollard, 2008. "Is the Great Moderation Ending? UK and US Evidence," Working Papers 0801, University of Nevada, Las Vegas , Department of Economics.
    10. Huseyin Tastan & Nuri Yildirim, 2008. "Business cycle asymmetries in Turkey: an application of Markov-switching autoregressions," International Economic Journal, Taylor & Francis Journals, vol. 22(3), pages 315-333.
    11. Penelope A. Smith & Peter M. Summers, 2005. "How well do Markov switching models describe actual business cycles? The case of synchronization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 253-274.
    12. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    13. Terence C. Mills & Ping Wang, 2003. "Have output growth rates stabilised? evidence from the g‐7 economies," Scottish Journal of Political Economy, Scottish Economic Society, vol. 50(3), pages 232-246, August.
    14. 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.
    15. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.
    16. Smith Penelope & Summers Peter M, 2009. "Regime Switches in GDP Growth and Volatility: Some International Evidence and Implications for Modeling Business Cycles," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-19, September.
    17. 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.
    18. Mustafa Caglayan & Ozge Kandemir & Kostas Mouratidis, 2011. "Real effects of inflation uncertainty in the US," Working Papers 2011002, The University of Sheffield, Department of Economics, revised Feb 2015.
    19. Owyang, Michael T. & Piger, Jeremy M. & Wall, Howard J. & Wheeler, Christopher H., 2008. "The economic performance of cities: A Markov-switching approach," Journal of Urban Economics, Elsevier, vol. 64(3), pages 538-550, November.
    20. Kamel Helali, 2022. "Markov Switching-Vector AutoRegression Model Analysis of the Economic and Growth Cycles in Tunisia and Its Main European Partners," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 656-686, March.

    More about this item

    Keywords

    Structural break; Duration dependent transition; Growth inertia;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
    • N15 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - Asia including Middle East

    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:cuf:journl:y:2011:v:12:i:1:p:157-181. 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: Qiang Gao (email available below). General contact details of provider: https://edirc.repec.org/data/emcufcn.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.