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2004•RePEc: Research Papers in EconomicsRequires access

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

Xiaoming Li

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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.

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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.

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Available 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.

Key concepts: Productivity, Econometrics, Bayesian probability, Economics, Series (stratigraphy), China, Bayesian information criterion, Maximum likelihood

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