IDEAS home Printed from https://ideas.repec.org/a/rnd/arjebs/v9y2017i3p163-170.html
   My bibliography  Save this article

Threshold Cointegration and Nonlinear Causality test between Inflation Rate and Repo Rate

Author

Listed:
  • Katleho Makatjane
  • Ntebogang Moroke
  • Diteboho Xaba

Abstract

The current study investigated a cointegration and nonlinear causality relationships between inflation and repo rates of South Africa using the data spanning the period of January 2002 to March 2016. We used a threshold vector error correction model (TVECM) and nonlinear Granger frameworks causality to carry out the analysis. Preliminary analysis of data revealed the expected properties of the data such as nonlinearity, non-stationarity and co-movement of the variables. The two variables confirmed to be moving together in the long-run according to the observed supWald test statistic. Finally, the Diks-Panchenko nonlinear Causality test revealed a strong bidirectional nonlinear causal relationship between repo rate and inflation rate. The results imply that the use of repo rate to target the inflation rate during the target period did not address the financial problem in South Africa. Consequently, the study concluded that repo rate may not be a good measure to use for controlling inflation rates of South Africa.

Suggested Citation

  • Katleho Makatjane & Ntebogang Moroke & Diteboho Xaba, 2017. "Threshold Cointegration and Nonlinear Causality test between Inflation Rate and Repo Rate," Journal of Economics and Behavioral Studies, AMH International, vol. 9(3), pages 163-170.
  • Handle: RePEc:rnd:arjebs:v:9:y:2017:i:3:p:163-170
    DOI: 10.22610/jebs.v9i3.1755.g1453
    as

    Download full text from publisher

    File URL: https://ojs.amhinternational.com/index.php/jebs/article/view/1755/1453
    Download Restriction: no

    File URL: https://ojs.amhinternational.com/index.php/jebs/article/view/1755
    Download Restriction: no

    References listed on IDEAS

    as
    1. Hansen, Bruce E. & Seo, Byeongseon, 2002. "Testing for two-regime threshold cointegration in vector error-correction models," Journal of Econometrics, Elsevier, vol. 110(2), pages 293-318, October.
    2. Ahdi N. Ajmi & Goodness C. Aye & Mehmet Balcilar & Rangan Gupta, 2015. "Causality between exports and economic growth in South Africa: evidence from linear and nonlinear tests," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(2), pages 163-181, April-Jun.
    3. Granger, C W J & Lee, T H, 1989. "Investigation of Production, Sales and Inventory Relationships Using Multicointegration and Non-symmetric Error Correction Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages 145-159, Supplemen.
    4. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415.
    5. Andrew Phiri, 2016. "Tourism and Economic Growth in South Africa: Evidence from Linear and Nonlinear Cointegration Frameworks," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 14(1 (Spring), pages 31-53.
    6. Lo, Ming Chien & Zivot, Eric, 2001. "Threshold Cointegration And Nonlinear Adjustment To The Law Of One Price," Macroeconomic Dynamics, Cambridge University Press, vol. 5(4), pages 533-576, September.
    7. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    8. Baum, Christopher F. & Barkoulas, John T. & Caglayan, Mustafa, 2001. "Nonlinear adjustment to purchasing power parity in the post-Bretton Woods era," Journal of International Money and Finance, Elsevier, vol. 20(3), pages 379-399, June.
    9. Hiemstra, Craig & Jones, Jonathan D, 1994. " Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    10. Enders, Walter & Siklos, Pierre L, 2001. "Cointegration and Threshold Adjustment," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 166-176, April.
    11. Taylor, Alan M, 2001. "Potential Pitfalls for the Purchasing-Power-Parity Puzzle? Sampling and Specification Biases in Mean-Reversion Tests of the Law of One Price," Econometrica, Econometric Society, vol. 69(2), pages 473-498, March.
    12. Esso, Loesse Jacques, 2010. "Threshold cointegration and causality relationship between energy use and growth in seven African countries," Energy Economics, Elsevier, vol. 32(6), pages 1383-1391, November.
    13. Chiou-Wei, Song Zan & Chen, Ching-Fu & Zhu, Zhen, 2008. "Economic growth and energy consumption revisited -- Evidence from linear and nonlinear Granger causality," Energy Economics, Elsevier, vol. 30(6), pages 3063-3076, November.
    14. Rossouw, J.J. & Vermeulen, J.C. & Leshoro, L.A., 2014. "Monetary Economics in South Africa," OUP Catalogue, Oxford University Press, edition 2, number 9780199050703 edited by van der Merwe, Ernie & Mollentze, Sandra.
    15. Seo, Myunghwan, 2006. "Bootstrap testing for the null of no cointegration in a threshold vector error correction model," Journal of Econometrics, Elsevier, vol. 134(1), pages 129-150, September.
    16. Prasad Bal, Debi & Narayan Rath, Badri, 2015. "Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India," Energy Economics, Elsevier, vol. 51(C), pages 149-156.
    17. Hassan Ghassan & Prashanta Banerjee, 2015. "A threshold cointegration analysis of asymmetric adjustment of OPEC and non-OPEC monthly crude oil prices," Empirical Economics, Springer, vol. 49(1), pages 305-323, August.
    18. Yau, Hwey-Yun & Nieh, Chien-Chung, 2009. "Testing for cointegration with threshold effect between stock prices and exchange rates in Japan and Taiwan," Japan and the World Economy, Elsevier, vol. 21(3), pages 292-300, August.
    19. Bonga-Bonga, Lumengo & Kabundi, Alain, 2015. "Monetary Policy Instrument and Inflation in South Africa: Structural Vector Error Correction Model Approach," MPRA Paper 63731, University Library of Munich, Germany.
    20. repec:wly:japmet:v:31:y:2016:i:7:p:1333-1351 is not listed on IDEAS
    21. Cees Diks & Marcin Wolski, 2016. "Nonlinear Granger Causality: Guidelines for Multivariate Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1333-1351, November.
    22. Ghosh, Sajal & Kanjilal, Kakali, 2016. "Co-movement of international crude oil price and Indian stock market: Evidences from nonlinear cointegration tests," Energy Economics, Elsevier, vol. 53(C), pages 111-117.
    Full references (including those not matched with items on IDEAS)

    More about this item

    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:rnd:arjebs:v:9:y:2017:i:3:p:163-170. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Muhammad Tayyab). General contact details of provider: https://ojs.amhinternational.com/index.php/jebs .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.