Measuring Chinese business cycles with dynamic factor models
AbstractThe Stock-Watson method and the dynamic Markov switching factor (DMSF) model are employed to construct macroeconomic composite coincident indexes for the Chinese economy, January 1990-March 2008. Four coincident indicators, namely, industrial production, investment in fixed assets, sales revenues, and the money supply, M1, are selected to compute the coincident index. Strong asymmetries are found with recent business cycles in China characterized by expansions of longer duration and smaller amplitude relative to the contraction stage. The two models produce similar composite index series, but the DMSF model shows frequent transitions that are difficult to interpret. A comparison of the composite coincident index and other measures of macroeconomic activity provides economic interpretations of the patterns in the index. There are notable differences between the index and GDP growth rates over this period, reflecting its more comprehensive measurement of economic activity. This more comprehensive view of macroeconomic activity increases understanding of changes in China's policies and economic fluctuations that are not shown by GDP growth rates alone.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Asian Economics.
Volume (Year): 20 (2009)
Issue (Month): 2 (March)
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Web page: http://www.elsevier.com/locate/asieco
Business cycles Composite coincident index State space model Markov switching model Dynamic factor model;
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