IDEAS home Printed from https://ideas.repec.org/a/eee/riibaf/v39y2017ipap612-624.html
   My bibliography  Save this article

China’s intervention in the central parity rate: A Bayesian Tobit analysis

Author

Listed:
  • Li, He
  • Zhang, Zhichao
  • Zhang, Chuanjie

Abstract

This paper investigates China’s daily foreign exchange intervention through the setting and adjustment of the central parity rate, using daily data from July 22, 2005 to July 22, 2013. Applying a Bayes Tobit model, we find evidence that China’s daily price intervention decision is driven by market developments regarding the Chinese currency, international currency movements and macroeconomic conditions. The results further suggest that the objectives of China’s daily price intervention change not only over time, but also between high and low interventions.

Suggested Citation

  • Li, He & Zhang, Zhichao & Zhang, Chuanjie, 2017. "China’s intervention in the central parity rate: A Bayesian Tobit analysis," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 612-624.
    • Handle: RePEc:eee:riibaf:v:39:y:2017:i:pa:p:612-624
    DOI: 10.1016/j.ribaf.2016.07.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S027553191630157X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ribaf.2016.07.017?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Peter Brandner & Harald Grech, 2005. "Why Did Central Banks Intervene in ERM I? The Post-1993 Experience," IMF Staff Papers, Palgrave Macmillan, vol. 52(1), pages 120-147, April.
    2. Omori, Yasuhiro & Miyawaki, Koji, 2010. "Tobit model with covariate dependent thresholds," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2736-2752, November.
    3. Humpage, Owen F, 1999. "U.S. Intervention: Assessing the Probability of Success," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 31(4), pages 731-747, November.
    4. Chkili, Walid & Nguyen, Duc Khuong, 2014. "Exchange rate movements and stock market returns in a regime-switching environment: Evidence for BRICS countries," Research in International Business and Finance, Elsevier, vol. 31(C), pages 46-56.
    5. Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
    6. Muhammad Kashif Ali Shah & Zulfiqar Hyder & Muhammad Khalid Pervaiz, 2009. "Central bank intervention and exchange rate volatility in Pakistan: an analysis using GARCH-X model," Applied Financial Economics, Taylor & Francis Journals, vol. 19(18), pages 1497-1508.
    7. Baillie, Richard T. & Osterberg, William P., 1997. "Why do central banks intervene?," Journal of International Money and Finance, Elsevier, vol. 16(6), pages 909-919, December.
    8. Aleem, Abdul & Lahiani, Amine, 2014. "A threshold vector autoregression model of exchange rate pass-through in Mexico," Research in International Business and Finance, Elsevier, vol. 30(C), pages 24-33.
    9. Richard H. Clarida, 2013. "Hot Tip: Nominal Exchange Rates and Inflation Indexed Bond Yields," NBER Working Papers 18726, National Bureau of Economic Research, Inc.
    10. Kitamura, Yoshihiro, 2016. "Does the simple microstructure model tell the time of the FX intervention? A one day analysis of the Japanese FX intervention," Research in International Business and Finance, Elsevier, vol. 36(C), pages 436-446.
    11. Disyatat, Piti & Galati, Gabriele, 2007. "The effectiveness of foreign exchange intervention in emerging market countries: Evidence from the Czech koruna," Journal of International Money and Finance, Elsevier, vol. 26(3), pages 383-402, April.
    12. Almekinders, Geert J. & Eijffinger, Sylvester C. W., 1996. "A friction model of daily Bundesbank and Federal Reserve intervention," Journal of Banking & Finance, Elsevier, vol. 20(8), pages 1365-1380, September.
    13. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    14. Szakmary, Andrew C. & Mathur, Ike, 1997. "Central bank intervention and trading rule profits in foreign exchange markets," Journal of International Money and Finance, Elsevier, vol. 16(4), pages 513-535, August.
    15. Tullio, Giuseppe & Natarov, Vitaly, 1999. "Daily Interventions by the Central Bank of Russia in the Treasury Bill Market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 4(3), pages 229-242, July.
    16. Almekinders, Geert J & Eijffinger, Sylvester C W, 1994. "Daily Bundesbank and Federal Reserve Interventions: Are They a Reaction to Changes in the Level and Volatility of the DM/$-Rate?," Empirical Economics, Springer, vol. 19(1), pages 111-130.
    17. John Williamson, 1994. "Estimating Equilibrium Exchange Rates," Peterson Institute Press: All Books, Peterson Institute for International Economics, number 17, April.
    18. Wang, Yajie & Hui, Xiaofeng & Soofi, Abdol S., 2007. "Estimating renminbi (RMB) equilibrium exchange rate," Journal of Policy Modeling, Elsevier, vol. 29(3), pages 417-429.
    19. Zhang, Zhibai, 2010. "A comparison of the BEER and Penn effect models via their applications on the valuation of the Renminbi," MPRA Paper 40649, University Library of Munich, Germany.
    20. Estrella, Arturo & Hardouvelis, Gikas A, 1991. "The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    21. Harvey, Campbell R., 1988. "The real term structure and consumption growth," Journal of Financial Economics, Elsevier, vol. 22(2), pages 305-333, December.
    22. Rudebusch, Glenn D. & Williams, John C., 2009. "Forecasting Recessions: The Puzzle of the Enduring Power of the Yield Curve," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 492-503.
    23. Pontines, Victor & Rajan, Ramkishen S., 2011. "Foreign exchange market intervention and reserve accumulation in emerging Asia: Is there evidence of fear of appreciation?," Economics Letters, Elsevier, vol. 111(3), pages 252-255, June.
    24. Robert Summers & Alan Heston, 1991. "The Penn World Table (Mark 5): An Expanded Set of International Comparisons, 1950–1988," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(2), pages 327-368.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jia, Fei & Shen, Yao & Ren, Junfan & Xu, Xiangyun, 2021. "The impact of offshore exchange rate expectations on onshore exchange rates: The case of Chinese RMB," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

    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. Ibarra-Ramírez Raúl, 2021. "The Yield Curve as a Predictor of Economic Activity in Mexico: The Role of the Term Premium," Working Papers 2021-07, Banco de México.
    2. Fernandez-Perez, Adrian & Fernández-Rodríguez, Fernando & Sosvilla-Rivero, Simón, 2014. "The term structure of interest rates as predictor of stock returns: Evidence for the IBEX 35 during a bear market," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 21-33.
    3. He Li & Zhixiang Yu & Chuanjie Zhang & Zhuang Zhang, 2017. "Determination of China’s foreign exchange intervention: evidence from the Yuan/Dollar market," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 34(1), pages 62-81, March.
    4. Pontines, Victor, 2018. "Self-selection and treatment effects: Revisiting the effectiveness of foreign exchange intervention," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 299-316.
    5. Chen, Ho-Chyuan & Chang, Kuang-Liang & Yu, Shih-Ti, 2012. "Application of the Tobit model with autoregressive conditional heteroscedasticity for foreign exchange market interventions," Japan and the World Economy, Elsevier, vol. 24(4), pages 274-282.
    6. Michael D. Bordo & Owen F. Humpage & Anna J. Schwartz, 2016. "On the Evolution of US Foreign-Exchange-Market Intervention: Thesis, Theory, and Institutions," NBER Chapters, in: Strained Relations: US Foreign-Exchange Operations and Monetary Policy in the Twentieth Century, pages 1-26, National Bureau of Economic Research, Inc.
    7. Brandner, Peter & Grech, Harald & Stix, Helmut, 2006. "The effectiveness of central bank intervention in the EMS: The post 1993 experience," Journal of International Money and Finance, Elsevier, vol. 25(4), pages 580-597, June.
    8. Hasse, Jean-Baptiste & Lajaunie, Quentin, 2022. "Does the yield curve signal recessions? New evidence from an international panel data analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 9-22.
    9. Christiansen, Charlotte, 2013. "Predicting severe simultaneous recessions using yield spreads as leading indicators," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1032-1043.
    10. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2012. "The yield curve and the macro-economy across time and frequencies," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1950-1970.
    11. Shuping Shi & Peter C. B. Phillips & Stan Hurn, 2018. "Change Detection and the Causal Impact of the Yield Curve," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 966-987, November.
    12. Ng, Eric C.Y., 2012. "Forecasting US recessions with various risk factors and dynamic probit models," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 112-125.
    13. Vasilios Plakandaras & Juncal Cunado & Rangan Gupta & Mark E. Wohar, 2016. "Do Leading Indicators Forecast U.S. Recessions? A Nonlinear Re-Evaluation Using Historical Data," Working Papers 201685, University of Pretoria, Department of Economics.
    14. Suk-Joong Kim & Jeffrey Sheen, 2018. "The Determinants of Foreign Exchange Intervention by Central Banks: Evidence from Australia," World Scientific Book Chapters, in: Information Spillovers and Market Integration in International Finance Empirical Analyses, chapter 1, pages 3-41, World Scientific Publishing Co. Pte. Ltd..
    15. Chatterjee, Ujjal K., 2016. "Do stock market trading activities forecast recessions?," Economic Modelling, Elsevier, vol. 59(C), pages 370-386.
    16. Chauvet, Marcelle & Senyuz, Zeynep, 2008. "A Joint Dynamic Bi-Factor Model of the Yield Curve and the Economy as a Predictor of Business Cycles," MPRA Paper 15076, University Library of Munich, Germany, revised Apr 2009.
    17. Chatterjee, Ujjal K., 2018. "Bank liquidity creation and recessions," Journal of Banking & Finance, Elsevier, vol. 90(C), pages 64-75.
    18. Chauvet, Marcelle & Senyuz, Zeynep, 2016. "A dynamic factor model of the yield curve components as a predictor of the economy," International Journal of Forecasting, Elsevier, vol. 32(2), pages 324-343.
    19. Jean-Baptiste Hasse & Quentin Lajaunie, 2020. "Does the Yield Curve Signal Recessions? New Evidence from an International Panel Data Analysis," AMSE Working Papers 2013, Aix-Marseille School of Economics, France.
    20. Marcelle Chauvet & Zeynep Senyuz, 2012. "A Dynamic Factor Model of the Yield Curve as a Predictor of the Economy," Finance and Economics Discussion Series 2012-32, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    Keywords

    Foreign exchange intervention; Exchange rate policy; China; Tobit models; Gibbs sampling;
    All these keywords.

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • F31 - International Economics - - International Finance - - - Foreign Exchange

    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:eee:riibaf:v:39:y:2017:i:pa:p:612-624. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ribaf .

    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.