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Analyzing China's Consumer Price Index Comparatively with that of United States

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  • Zhenzhong Wang
  • Yundong Tu
  • Song Xi Chen

Abstract

This paper provides a thorough analysis on the dynamic structures and predictability of China's Consumer Price Index (CPI-CN), with a comparison to those of the United States. Despite the differences in the two leading economies, both series can be well modeled by a class of Seasonal Autoregressive Integrated Moving Average Model with Covariates (S-ARIMAX). The CPI-CN series possess regular patterns of dynamics with stable annual cycles and strong Spring Festival effects, with fitting and forecasting errors largely comparable to their US counterparts. Finally, for the CPI-CN, the diffusion index (DI) approach offers improved predictions than the S-ARIMAX models.

Suggested Citation

  • Zhenzhong Wang & Yundong Tu & Song Xi Chen, 2019. "Analyzing China's Consumer Price Index Comparatively with that of United States," Papers 1910.13301, arXiv.org.
    • Handle: RePEc:arx:papers:1910.13301
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    References listed on IDEAS

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    1. Michael W. McCracken & Serena Ng, 2016. "FRED-MD: A Monthly Database for Macroeconomic Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
    2. Zhang, Lingxiang, 2013. "Modeling China's inflation dynamics: An MRSTAR approach," Economic Modelling, Elsevier, vol. 31(C), pages 440-446.
    3. Chow, Gregory C., 1987. "Money and price level determination in China," Journal of Comparative Economics, Elsevier, vol. 11(3), pages 319-333, September.
    4. Chow, Gregory C. & Wang, Peng, 2010. "The empirics of inflation in China," Economics Letters, Elsevier, vol. 109(1), pages 28-30, October.
    5. Wang, Ying & Tu, Yundong & Chen, Song Xi, 2016. "Improving inflation prediction with the quantity theory," Economics Letters, Elsevier, vol. 149(C), pages 112-115.
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