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Monetary Policy Effectiveness in China: Evidence from a FAVAR Model

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  • John G. Fernald
  • Mark M. Spiegel
  • Eric T. Swanson

Abstract

We use a broad set of Chinese economic indicators and a dynamic factor model framework to estimate Chinese economic activity and inflation as latent variables. We incorporate these latent variables into a factor-augmented vector autoregression (FAVAR) to estimate the effects of Chinese monetary policy on the Chinese economy. A FAVAR approach is particularly well-suited to this analysis due to concerns about Chinese data quality, a lack of a long history for many series, and the rapid institutional and structural changes that China has undergone. We find that increases in bank reserve requirements reduce economic activity and inflation, consistent with previous studies. In contrast to much of the literature, however, we find that changes in Chinese interest rates also have substantial impacts on economic activity and inflation, while other measures of changes in credit conditions, such as shocks to M2 or lending levels, do not once other policy variables are taken into account. Overall, our results indicate that the monetary policy transmission channels in China have moved closer to those of Western market economies.

Suggested Citation

  • John G. Fernald & Mark M. Spiegel & Eric T. Swanson, 2014. "Monetary Policy Effectiveness in China: Evidence from a FAVAR Model," Working Paper Series 2014-7, Federal Reserve Bank of San Francisco.
  • Handle: RePEc:fip:fedfwp:2014-07
    DOI: 10.24148/wp2014-07
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    More about this item

    Keywords

    Measuring China’s economy; dynamic factor models; factor-augmented VARs; monetary policy;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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