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

    for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Omori, Yasuhiro & Miyawaki, Koji, 2010. "Tobit model with covariate dependent thresholds," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2736-2752, November.
    8. 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.
    9. 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.
    10. Donald W. K. Andrews, 2003. "Tests for Parameter Instability and Structural Change with Unknown Change Point: A Corrigendum," Econometrica, Econometric Society, vol. 71(1), pages 395-397, January.
    11. 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.
    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. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. John Williamson, 1994. "Estimating Equilibrium Exchange Rates," Peterson Institute Press: All Books, Peterson Institute for International Economics, number 17, April.
    19. 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.
    20. 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.
    21. 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.
    22. Harvey, Campbell R., 1988. "The real term structure and consumption growth," Journal of Financial Economics, Elsevier, vol. 22(2), pages 305-333, December.
    23. 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.
    24. Richard H. Clarida, 2013. "Hot Tip: Nominal Exchange Rates and Inflation Indexed Bond Yields," NBER Working Papers 18726, National Bureau of Economic Research, Inc.
    25. 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.
    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. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.).
    10. Ito, Takatoshi & Yabu, Tomoyoshi, 2007. "What prompts Japan to intervene in the Forex market? A new approach to a reaction function," Journal of International Money and Finance, Elsevier, vol. 26(2), pages 193-212, March.
    11. Kathryn Dominguez & Rasmus Fatum & Pavel Vacek, 2010. "Does foreign exchange reserve decumulation lead to currency appreciation?," Globalization Institute Working Papers 48, Federal Reserve Bank of Dallas.
    12. 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.
    13. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2003. "How Stable is the Predictive Power of the Yield Curve? Evidence from Germany and the United States," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 629-644, August.
    14. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    15. 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.
    16. 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.
    17. 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..
    18. Javier Gómez, 2007. "Changes in the Informational Content of the Spread: Is Monetary Policy Becoming Less Effective?," Faculty Working Papers 05/07, School of Economics and Business Administration, University of Navarra.
    19. Duarte, Agustin & Venetis, Ioannis A. & Paya, Ivan, 2005. "Predicting real growth and the probability of recession in the Euro area using the yield spread," International Journal of Forecasting, Elsevier, vol. 21(2), pages 261-277.
    20. Fatum, Rasmus & Pedersen, Jesper, 2009. "Real-time effects of central bank intervention in the euro market," Journal of International Economics, Elsevier, vol. 78(1), pages 11-20, June.

    More about this item

    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.