IDEAS home Printed from https://ideas.repec.org/a/gam/jijfss/v7y2019i2p34-d240702.html
   My bibliography  Save this article

The Predictive Power of the User Cost Spread for Economic Recession in China and the US

Author

Listed:
  • Dongfeng Chang

    (School of Economics, Shandong University, Jinan 250100, Shandong, China)

  • Ryan S. Mattson

    (The Center for Financial Stability, New York, NY 10036, USA)

  • Biyan Tang

    (University of Massachusetts Dartmouth, Economics Department, North Dartmouth, MA 02747-2300, USA)

Abstract

The predictive power of the yield curve slope, or the yield spread is well established in the United States (US) and European Union (EU) countries since 1998. However, there exists a gap in the literature on the predictive power of the yield spread on the Chinese economy. This paper provides a different leading recession indicator using the Chinese and US economy as comparative examples: the user cost spread, being the difference of the opportunity costs of holding government securities of different maturities. We argue that the user cost spread, based on the Divisia monetary aggregate data like the ones produced by the Center for Financial Stability, provides improved predictive ability and a better intuitive explanation based on changes in the user cost price of holding bonds.

Suggested Citation

  • Dongfeng Chang & Ryan S. Mattson & Biyan Tang, 2019. "The Predictive Power of the User Cost Spread for Economic Recession in China and the US," IJFS, MDPI, vol. 7(2), pages 1-12, June.
    • Handle: RePEc:gam:jijfss:v:7:y:2019:i:2:p:34-:d:240702
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7072/7/2/34/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7072/7/2/34/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Barnett, William A., 1980. "Economic monetary aggregates--reply," Journal of Econometrics, Elsevier, vol. 14(1), pages 57-59, September.
    2. William A. Barnett & Shu Wu, 2011. "On User Costs of Risky Monetary Assets," World Scientific Book Chapters, in: Financial Aggregation And Index Number Theory, chapter 3, pages 85-105, World Scientific Publishing Co. Pte. Ltd..
    3. Ryan S. Mattson & Victor J. Valcarcel, 2016. "Compression in monetary user costs in the aftermath of the financial crisis: implications for the Divisia M4 monetary aggregate," Applied Economics Letters, Taylor & Francis Journals, vol. 23(18), pages 1294-1300, December.
    4. Ryan S. Mattson, 2019. "A Divisia User Cost Interpretation of the Yield Spread Recession Prediction," JRFM, MDPI, vol. 12(1), pages 1-9, January.
    5. 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.
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    7. Liu, Weiling & Moench, Emanuel, 2016. "What predicts US recessions?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1138-1150.
    8. 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.
    9. Marcelle Chauvet & Simon Potter, 2005. "Forecasting recessions using the yield curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 77-103.
    10. Tobin, James, 1969. "A General Equilibrium Approach to Monetary Theory," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 1(1), pages 15-29, February.
    11. William Barnett & Jia Liu & Ryan Mattson & Jeff Noort, 2013. "The New CFS Divisia Monetary Aggregates: Design, Construction, and Data Sources," Open Economies Review, Springer, vol. 24(1), pages 101-124, February.
    12. William A. Barnett, 2000. "The User Cost of Money," Contributions to Economic Analysis, in: The Theory of Monetary Aggregation, pages 6-10, Emerald Group Publishing Limited.
    13. Arnaud Mehl, 2009. "The Yield Curve as a Predictor and Emerging Economies," Open Economies Review, Springer, vol. 20(5), pages 683-716, November.
    14. Arturo Estrella & Mary R. Trubin, 2006. "The yield curve as a leading indicator: some practical issues," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 12(Jul).
    15. Michael T. Belongia & Peter N. Ireland, 2015. "Interest Rates and Money in the Measurement of Monetary Policy," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 255-269, April.
    16. Harvey, Campbell R., 1988. "The real term structure and consumption growth," Journal of Financial Economics, Elsevier, vol. 22(2), pages 305-333, December.
    17. Paolo Zagaglia, 2013. "Forecasting Long-Term Interest Rates with a General-Equilibrium Model of the Euro Area: What Role for Liquidity Services of Bonds?," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 20(4), pages 383-430, November.
    18. Henri Nyberg, 2010. "Dynamic probit models and financial variables in recession forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 215-230.
    19. 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.
    20. Massimiliano Marzo & Paolo Zagaglia, 2018. "Macroeconomic Stability in a Model with Bond Transaction Services," IJFS, MDPI, vol. 6(1), pages 1-27, February.
    21. Arturo Estrella & Frederic S. Mishkin, 1996. "The yield curve as a predictor of U.S. recessions," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 2(Jun).
    22. Tsagkanos, Athanasios G., 2007. "A bootstrap-based minimum bias maximum simulated likelihood estimator of Mixed Logit," Economics Letters, Elsevier, vol. 96(2), pages 282-286, August.
    23. Canzoneri, Matthew & Cumby, Robert & Diba, Behzad & López-Salido, David, 2011. "The role of liquid government bonds in the great transformation of American monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 35(3), pages 282-294, March.
    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. Lee, Kiryoung & Jeon, Yoontae, 2020. "Measuring Chinese consumers’ perceived uncertainty," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 51-70.
    2. Viacheslav M. Shavshukov & Natalia A. Zhuravleva, 2020. "Global Economy: New Risks and Leadership Problems," IJFS, MDPI, vol. 8(1), pages 1-17, February.
    3. Yizheng Fu & Zhifang Su & Aihua Lin, 2024. "Functional Cointegration Test for Expectation Hypothesis of the Term Structure of Interest Rates in China," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(4), pages 799-820, December.

    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. Ryan S. Mattson, 2019. "A Divisia User Cost Interpretation of the Yield Spread Recession Prediction," JRFM, MDPI, vol. 12(1), pages 1-9, January.
    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. 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.
    4. Liu, Weiling & Moench, Emanuel, 2016. "What predicts US recessions?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1138-1150.
    5. Pawel Dlotko & Simon Rudkin, 2019. "The Topology of Time Series: Improving Recession Forecasting from Yield Spreads," Working Papers 2019-02, Swansea University, School of Management.
    6. 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.
    7. Döpke, Jörg & Fritsche, Ulrich & Pierdzioch, Christian, 2017. "Predicting recessions with boosted regression trees," International Journal of Forecasting, Elsevier, vol. 33(4), pages 745-759.
    8. B. De Backer & M. Deroose & Ch. Van Nieuwenhuyze, 2019. "Is a recession imminent? The signal of the yield curve," Economic Review, National Bank of Belgium, issue i, pages 69-93, June.
    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. Kuosmanen, Petri & Vataja, Juuso, 2014. "Forecasting GDP growth with financial market data in Finland: Revisiting stylized facts in a small open economy during the financial crisis," Review of Financial Economics, Elsevier, vol. 23(2), pages 90-97.
    11. Stijn Claessens & M Ayhan Kose, 2017. "Asset prices and macroeconomic outcomes: a survey," BIS Working Papers 676, Bank for International Settlements.
    12. 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.
    13. 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.
    14. Hwang, Youngjin, 2019. "Forecasting recessions with time-varying models," Journal of Macroeconomics, Elsevier, vol. 62(C).
    15. 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.
    16. Knut Lehre Seip & Dan Zhang, 2021. "The Yield Curve as a Leading Indicator: Accuracy and Timing of a Parsimonious Forecasting Model," Forecasting, MDPI, vol. 3(2), pages 1-16, May.
    17. Chatterjee, Ujjal K. & Zirgulis, Aras & Hüttinger, Maik & French, Joseph J., 2024. "Reassessing the inversion of the Treasury yield curve as a sign of U.S. recessions: Insights from the housing and credit markets," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    18. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    19. Kajal Lahiri & Cheng Yang, 2022. "ROC approach to forecasting recessions using daily yield spreads," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 57(4), pages 191-203, October.
    20. Bellégo, C. & Ferrara, L., 2009. "Forecasting Euro-area recessions using time-varying binary response models for financial," Working papers 259, Banque de France.

    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:gam:jijfss:v:7:y:2019:i:2:p:34-:d:240702. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.