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A study of Fisher Effect in India

Author

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  • Swapnil Suryavanshi

    (University of Mumbai)

Abstract

In this paper, the relationship between nominal interest rate and inflation is analyzed based on Fisher Effect (FE) theory. As per FE theory, the difference between nominal interest rate and expected inflation is equal to real interest rate. The theory proposes that a rise in expected inflation can lead to positive impact on nominal interest rate when the real interest rate is constant. For analyzing FE, the inflation rate measures based on Core index, Wholesale Price Index (WPI) and Consumer Price Index (CPI) are considered. As per rational expectation hypothesis, the one-period-ahead inflation rate is considered as expected inflation (eInf). The interest rates (IR) associated with call money, treasury bills of 91- and 364-day maturities are considered. The study uses ARDL bounds testing approach and Granger causality test for analyzing the long-run relationship between eInf and IR. The study finds evidence for presence of cointegrating relationship between eInf and IR in India. Contrary to FE theory, the long-run relation between eInf and IR is found to be negative. The extent and significance of long-run relationship varies depending on measures of eInf and IR considered. Along with cointegration, the expected WPI inflation and interest rate measures also exhibit Granger causality in at least one direction. Although, the cointegration is not observed between expected CPI and IR, there exists Granger causality between these variables. This increasing disconnect between eInf and IR could be attributed to adoption of flexible inflation targeting framework, pursual of additional objectives by monetary authority, different sources and types of inflation, etc.

Suggested Citation

  • Swapnil Suryavanshi, 2023. "A study of Fisher Effect in India," Indian Economic Review, Springer, vol. 58(2), pages 485-503, September.
  • Handle: RePEc:spr:inecre:v:58:y:2023:i:2:d:10.1007_s41775-023-00180-1
    DOI: 10.1007/s41775-023-00180-1
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    References listed on IDEAS

    as
    1. Frederic S. Mishkin & John Simon, 1995. "An Empirical Examination of the Fisher Effect in Australia," The Economic Record, The Economic Society of Australia, vol. 71(3), pages 217-229, September.
    2. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    3. Mishkin, Frederic S., 1992. "Is the Fisher effect for real? : A reexamination of the relationship between inflation and interest rates," Journal of Monetary Economics, Elsevier, vol. 30(2), pages 195-215, November.
    4. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    5. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    6. Cukierman Alex & Muscatelli Anton, 2008. "Nonlinear Taylor Rules and Asymmetric Preferences in Central Banking: Evidence from the United Kingdom and the United States," The B.E. Journal of Macroeconomics, De Gruyter, vol. 8(1), pages 1-31, February.
    7. Masudul Hasan Adil & Shadab Danish & Sajad Ahmad Bhat & Bandi Kamaiah, 2020. "Fisher Effect: An Empirical Re-examination in Case of India," Economics Bulletin, AccessEcon, vol. 40(1), pages 262-276.
    8. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    9. Jamaladeen Abubakar & K. Jothi Sivagnanam, 2017. "Fisher’s Effect: An Empirical Examination Using India’s Time Series Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(3), pages 611-628, September.
    10. He, Zonglu & Maekawa, Koichi, 2001. "On spurious Granger causality," Economics Letters, Elsevier, vol. 73(3), pages 307-313, December.
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    More about this item

    Keywords

    Fisher Effect; Inflation; Interest rate; ARDL models; Granger causality;
    All these keywords.

    JEL classification:

    • 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
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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