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A Quasi-Bayesian Analysis of Structural Breaks: China's Output and Productivity Series

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  • Xiao-Ming Li

    (Department of Commerce, Massey University-Albany, New Zealand)

Abstract

A quasi-Bayesian model selection approach is employed to detect the number and dates of structural changes in China's GDP and labour productivity data. It is shown that the predictive likelihood information criterion is valid only among models with well-behaved residuals.

Suggested Citation

  • Xiao-Ming Li, 2004. "A Quasi-Bayesian Analysis of Structural Breaks: China's Output and Productivity Series," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 3(1), pages 57-65, April.
    • Handle: RePEc:ijb:journl:v:3:y:2004:i:1:p:57-65
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    References listed on IDEAS

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    Cited by:

    1. Agiwal Varun & Kumar Jitendra & Shangodoyin Dahud Kehinde, 2018. "A Bayesian Inference Of Multiple Structural Breaks In Mean And Error Variance In Panelar (1) Model," Statistics in Transition New Series, Polish Statistical Association, vol. 19(1), pages 7-23, March.
    2. Varun Agiwal & Jitendra Kumar & Dahud Kehinde Shangodoyin, 2018. "A Bayesian Inference Of Multiple Structural Breaks In Mean And Error Variance In Panel Ar (1) Model," Statistics in Transition New Series, Polish Statistical Association, vol. 19(1), pages 7-23, March.

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    More about this item

    Keywords

    structural change; predictive likelihood; GDP; labour productivity; China;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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