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The direction and intensity of China's monetary policy conduct: A dynamic factor modelling approach

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  • Funke, Michael
  • Tsang, Andrew

Abstract

The recent upgrade of the People's Bank of China's monetary policy framework establishes a corridor system of interest rates. As the revamped policy arrangement now features a multiple-instrument mix of liquidity tools and pricing signals, we employ a dynamic factor modelling approach to derive an indicator of China's monetary policy stance. The approach is based on the notion that comovements in several monetary policy instruments have a common element that can be captured by a single underlying, unobserved component. To clarify and interpret the derived index, we employ a baseline DSGE model that can be solved analytically and allows tracing of the expansionary and contractionary on-and-off phases of Chinese monetary policy.

Suggested Citation

  • Funke, Michael & Tsang, Andrew, 2019. "The direction and intensity of China's monetary policy conduct: A dynamic factor modelling approach," BOFIT Discussion Papers 8/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
    • Handle: RePEc:zbw:bofitp:bdp2019_008
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    References listed on IDEAS

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    1. Sun, Rongrong, 2013. "Does monetary policy matter in China? A narrative approach," China Economic Review, Elsevier, vol. 26(C), pages 56-74.
    2. Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
    3. Hélène Rey, 2016. "International Channels of Transmission of Monetary Policy and the Mundellian Trilemma," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 64(1), pages 6-35, May.
    4. Fernald, John G. & Spiegel, Mark M. & Swanson, Eric T., 2014. "Monetary policy effectiveness in China: Evidence from a FAVAR model," Journal of International Money and Finance, Elsevier, vol. 49(PA), pages 83-103.
    5. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
    6. Mr. Bin Wang & Tao Sun, 2013. "How Effective are Macroprudential Policies in China?," IMF Working Papers 2013/075, International Monetary Fund.
    7. Greg Kaplan & Benjamin Moll & Giovanni L. Violante, 2018. "Monetary Policy According to HANK," American Economic Review, American Economic Association, vol. 108(3), pages 697-743, March.
    8. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    9. Christina D. Romer & David H. Romer, 1989. "Does Monetary Policy Matter? A New Test in the Spirit of Friedman and Schwartz," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 121-184, National Bureau of Economic Research, Inc.
    10. Güneş Kamber & Madhusudan Mohanty, 2018. "Do interest rates play a major role in monetary policy transmission in China?," BIS Working Papers 714, Bank for International Settlements.
    11. Chen, Hongyi & Chow, Kenneth & Tillmann, Peter, 2017. "The effectiveness of monetary policy in China: Evidence from a Qual VAR," China Economic Review, Elsevier, vol. 43(C), pages 216-231.
    12. Mario Forni & Lucrezia Reichlin, 1998. "Let's Get Real: A Factor Analytical Approach to Disaggregated Business Cycle Dynamics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 453-473.
    13. Eric Girardin & Sandrine Lunven & Guonan Ma, 2017. "China's evolving monetary policy rule: from inflation-accommodating to anti-inflation policy," BIS Working Papers 641, Bank for International Settlements.
    14. Eickmeier, Sandra, 2007. "Business cycle transmission from the US to Germany--A structural factor approach," European Economic Review, Elsevier, vol. 51(3), pages 521-551, April.
    15. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
    16. Sun, Rongrong, 2015. "What measures Chinese monetary policy?," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 263-286.
    17. Rongrong Sun, 2018. "A Narrative indicator of Monetary Conditions in China," International Journal of Central Banking, International Journal of Central Banking, vol. 14(4), pages 1-42, September.
    18. Alexei Onatski, 2010. "Determining the Number of Factors from Empirical Distribution of Eigenvalues," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1004-1016, November.
    19. Olivier Blanchard, 2018. "On the future of macroeconomic models," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 34(1-2), pages 43-54.
    20. Xiong, Weibo, 2012. "Measuring the monetary policy stance of the People's bank of china: An ordered probit analysis," China Economic Review, Elsevier, vol. 23(3), pages 512-533.
    21. Shuai Chen & Paulina Oliva & Peng Zhang, 2017. "The Effect of Air Pollution on Migration: Evidence from China," NBER Working Papers 24036, National Bureau of Economic Research, Inc.
    22. Jushan Bai & Peng Wang, 2015. "Identification and Bayesian Estimation of Dynamic Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 221-240, April.
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    More about this item

    Keywords

    China; monetary policy stance; dynamic factor model; DSGE model;
    All these keywords.

    JEL classification:

    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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