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The Direction and Intensity of China’s Monetary Policy: A Dynamic Factor Modelling Approach

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  • Michael Funke
  • Andrew Tsang

Abstract

The recent update of the People’s Bank of China’s monetary policy framework establishes a corridor system of interest rates. 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 co‐movements 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 dynamic stochastic general equilibrium (DSGE) model that can be solved analytically and allows tracing of the expansionary and contractionary on‐and‐off phases of Chinese monetary policy.

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  • Michael Funke & Andrew Tsang, 2021. "The Direction and Intensity of China’s Monetary Policy: A Dynamic Factor Modelling Approach," The Economic Record, The Economic Society of Australia, vol. 97(316), pages 100-122, March.
    • Handle: RePEc:bla:ecorec:v:97:y:2021:i:316:p:100-122
    DOI: 10.1111/1475-4932.12576
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    as
    1. 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.
    2. 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.
    3. Sun, Rongrong, 2013. "Does monetary policy matter in China? A narrative approach," China Economic Review, Elsevier, vol. 26(C), pages 56-74.
    4. Dong He & Laurent L. Pauwels, 2008. "What Prompts the People's Bank of China to Change Its Monetary Policy Stance? Evidence from a Discrete Choice Model," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 16(6), pages 1-21, November.
    5. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    6. Kaiji Chen & Jue Ren & Tao Zha, 2018. "The Nexus of Monetary Policy and Shadow Banking in China," American Economic Review, American Economic Association, vol. 108(12), pages 3891-3936, December.
    7. 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.
    8. 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.
    9. Sun, Rongrong, 2015. "What measures Chinese monetary policy?," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 263-286.
    10. 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.
    11. 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.
    12. Peter N. Ireland, 2004. "Technology Shocks in the New Keynesian Model," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 923-936, November.
    13. J. B. Taylor & Harald Uhlig (ed.), 2016. "Handbook of Macroeconomics," Handbook of Macroeconomics, Elsevier, edition 1, volume 2, number 2.
    14. Michael McMahon & Mr. Alfred Schipke & Xiang Li, 2018. "China’s Monetary Policy Communication: Frameworks, Impact, and Recommendations," IMF Working Papers 2018/244, International Monetary Fund.
    15. Mr. Bin Wang & Tao Sun, 2013. "How Effective are Macroprudential Policies in China?," IMF Working Papers 2013/075, International Monetary Fund.
    16. Hongyi Chen & Michael Funke & Ivan Lozev & Andrew Tsang, 2020. "To Guide or Not to Guide? Quantitative Monetary Policy Tools and Macroeconomic Dynamics in China," International Journal of Central Banking, International Journal of Central Banking, vol. 16(5), pages 49-94, October.
    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. Callum Jones & Mariano Kulish, 2016. "A graphical representation of an estimated DSGE model," Applied Economics, Taylor & Francis Journals, vol. 48(6), pages 483-489, February.
    19. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, December.
    20. 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.
    21. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    22. 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.
    23. Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.
    24. Peter N. Ireland, 2011. "A New Keynesian Perspective on the Great Recession," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(1), pages 31-54, February.
    25. 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.
    26. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    27. 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.
    28. Zhang, Wenlang, 2009. "China's monetary policy: Quantity versus price rules," Journal of Macroeconomics, Elsevier, vol. 31(3), pages 473-484, September.
    29. 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.
    30. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    31. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-996, November.
    32. 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.
    33. 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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    Cited by:

    1. Tsang, Andrew, 2021. "Uncovering Heterogeneous Regional Impacts of Chinese Monetary Policy," MPRA Paper 110703, University Library of Munich, Germany.
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    3. Makram El-Shagi & Yishuo Ma, 2021. "Nine blind men and the PBoC," CFDS Discussion Paper Series 2021/2, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
    4. Funke, Michael & Li, Xiang & Zhong, Doudou, 2023. "Household indebtedness, financial frictions and the transmission of monetary policy to consumption: Evidence from China," Emerging Markets Review, Elsevier, vol. 55(C).

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