IDEAS home Printed from https://ideas.repec.org/a/bla/chinae/v16y2008i6p1-21.html
   My bibliography  Save this article

What Prompts the People's Bank of China to Change Its Monetary Policy Stance? Evidence from a Discrete Choice Model

Author

Listed:
  • Dong He
  • Laurent L. Pauwels

Abstract

In the present paper, we model the policy stance of the People's Bank of China (PBC) as a latent variable, and the discrete changes in the reserve requirement ratio, policy interest rates, and the scale of open market operations are taken as signals of movement of this latent variable. We run a discrete choice regression that relates these observed indicators of policy stance to major trends of macroeconomic and financial developments, which are represented by common factors extracted from a large number of variables. The predicted value of the estimated model can then be interpreted as the implicit policy stance of the PBC. In a second step, we estimate how much of the variation in the PBC's implicit stance can be explained by measures of its policy objectives on inflation, growth and financial stability. We find that deviations of CPI inflation from an implicit target and deviations of broad money growth from the announced targets, but not output gaps, figure significantly in the PBC's policy changes.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:chinae:v:16:y:2008:i:6:p:1-21
    DOI: 10.1111/j.1749-124X.2008.00134.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1749-124X.2008.00134.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1749-124X.2008.00134.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Joon Y. Park & Peter C. B. Phillips, 2000. "Nonstationary Binary Choice," Econometrica, Econometric Society, vol. 68(5), pages 1249-1280, September.
    2. James D. Hamilton & Oscar Jorda, 2002. "A Model of the Federal Funds Rate Target," Journal of Political Economy, University of Chicago Press, vol. 110(5), pages 1135-1167, October.
    3. Geiger, Michael, 2006. "Monetary Policy in China (1994-2004): Targets, Instruments and their Effectiveness," W.E.P. - Würzburg Economic Papers 68, University of Würzburg, Department of Economics.
    4. Phillips, Peter C.B. & Jin, Sainan & Hu, Ling, 2007. "Nonstationary discrete choice: A corrigendum and addendum," Journal of Econometrics, Elsevier, vol. 141(2), pages 1115-1130, December.
    5. Marvin Goodfriend & Eswar Prasad, 2009. "A Framework for Independent Monetary Policy in China," Chapters, in: Gill Hammond & Ravi Kanbur & Eswar Prasad (ed.), Monetary Policy Frameworks for Emerging Markets, chapter 8, Edward Elgar Publishing.
    6. Michael J. Dueker, 1999. "Measuring monetary policy inertia in target Fed funds rate changes," Review, Federal Reserve Bank of St. Louis, vol. 81(Sep), pages 3-10.
    7. Balduzzi, Pierluigi & Bertola, Giuseppe & Foresi, Silverio, 1997. "A model of target changes and the term structure of interest rates," Journal of Monetary Economics, Elsevier, vol. 39(2), pages 223-249, July.
    8. Phillips, Peter C.B. & Jin, Sainan & Hu, Ling, 2007. "Nonstationary discrete choice: A corrigendum and addendum," Journal of Econometrics, Elsevier, vol. 141(2), pages 1115-1130, December.
    9. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    10. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    11. Li-gang Liu & Wenlang Zhang, 2007. "A New Keynesian Model for Analysing Monetary Policy in Mainland China," Working Papers 0718, Hong Kong Monetary Authority.
    12. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    13. Ling Hu & Peter C.B. Phillips, 2002. "Dynamics of the Federal Funds Target Rate: A Nonstationary Discrete Choice Approach," Cowles Foundation Discussion Papers 1365, Cowles Foundation for Research in Economics, Yale University.
    14. Mr. Bernard J Laurens & Mr. Rodolfo Maino, 2007. "China: Strengthening Monetary Policy Implementation," IMF Working Papers 2007/014, International Monetary Fund.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hyeongwoo Kim & Wen Shi, 2014. "The Determinants of the Benchmark Interest Rates in China: A Discrete Choice Model Approach," Auburn Economics Working Paper Series auwp2014-12, Department of Economics, Auburn University.
    2. Kim, Hyeongwoo & Shi, Wen, 2018. "The determinants of the benchmark interest rates in China," Journal of Policy Modeling, Elsevier, vol. 40(2), pages 395-417.
    3. Rebeca I. Muñoz Torres & David Shepherd, 2014. "Inflation Targeting and the Consistency of Monetary Policy Decisions in Mexico: an Empirical Analysis with Discrete Choice Models," Manchester School, University of Manchester, vol. 82, pages 21-46, December.
    4. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    5. Phillips, Peter C.B. & Jin, Sainan & Hu, Ling, 2007. "Nonstationary discrete choice: A corrigendum and addendum," Journal of Econometrics, Elsevier, vol. 141(2), pages 1115-1130, December.
    6. Hyeongwoo Kim & John Jackson & Richard Saba, 2009. "Forecasting the FOMC's interest rate setting behavior: a further analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(2), pages 145-165.
    7. Ling Hu & Peter C.B. Phillips, 2002. "Dynamics of the Federal Funds Target Rate: A Nonstationary Discrete Choice Approach," Cowles Foundation Discussion Papers 1365, Cowles Foundation for Research in Economics, Yale University.
    8. Hyeongwoo Kim, 2014. "Estimating Interest Rate Setting Behavior in Korea: An Ordered Probit Model Approach," Auburn Economics Working Paper Series auwp2014-02, Department of Economics, Auburn University.
    9. Petreski, Marjan & Jovanovic, Branimir, 2012. "New Approach to Analyzing Monetary Policy in China," MPRA Paper 40497, University Library of Munich, Germany.
    10. Seibert, Armin & Sirchenko, Andrei & Müller, Gernot, 2021. "A model for policy interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 124(C).
    11. Renne, Jean-Paul, 2016. "A tractable interest rate model with explicit monetary policy rates," European Journal of Operational Research, Elsevier, vol. 251(3), pages 873-887.
    12. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
    13. Farvaque, Etienne & Malan, Franck & Stanek, Piotr, 2020. "Misplaced childhood: When recession children grow up as central bankers," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    14. Xu, Peng, 2015. "Testing for joint significance in nonstationary ordered choice model," Economics Letters, Elsevier, vol. 130(C), pages 5-8.
    15. Marcus Kappler, 2009. "Do hours worked contain a unit root? Evidence from panel data," Empirical Economics, Springer, vol. 36(3), pages 531-555, June.
    16. Park, Byeong U. & Simar, Léopold & Zelenyuk, Valentin, 2017. "Nonparametric estimation of dynamic discrete choice models for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 97-120.
    17. Holmes, Mark J. & Otero, Jesús & Panagiotidis, Theodore, 2011. "Investigating regional house price convergence in the United States: Evidence from a pair-wise approach," Economic Modelling, Elsevier, vol. 28(6), pages 2369-2376.
    18. Miguel Carvalho & Paulo Júlio, 2012. "Digging out the PPP hypothesis: an integrated empirical coverage," Empirical Economics, Springer, vol. 42(3), pages 713-744, June.
    19. Christoph Hanck, 2013. "An Intersection Test for Panel Unit Roots," Econometric Reviews, Taylor & Francis Journals, vol. 32(2), pages 183-203, February.
    20. Òscar Jordà & Moritz Schularick & Alan M. Taylor, 2020. "Disasters Everywhere: The Costs of Business Cycles Reconsidered," Staff Reports 925, Federal Reserve Bank of New York.

    More about this item

    JEL classification:

    • 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
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:chinae:v:16:y:2008:i:6:p:1-21. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/iwepacn.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.