IDEAS home Printed from https://ideas.repec.org/a/spr/inecre/v58y2023i2d10.1007_s41775-023-00180-1.html
   My bibliography  Save this article

A study of Fisher Effect in India

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41775-023-00180-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s41775-023-00180-1?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. 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.
    2. 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.
    3. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. He, Zonglu & Maekawa, Koichi, 2001. "On spurious Granger causality," Economics Letters, Elsevier, vol. 73(3), pages 307-313, December.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    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. Zheng, Li & Abbasi, Kashif Raza & Salem, Sultan & Irfan, Muhammad & Alvarado, Rafael & Lv, Kangjuan, 2022. "How technological innovation and institutional quality affect sectoral energy consumption in Pakistan? Fresh policy insights from novel econometric approach," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    2. R. Santos Alimi, 2014. "ARDL Bounds Testing Approach to Cointegration: A Re-Examination of Augmented Fisher Hypothesis in an Open Economy," Asian Journal of Economic Modelling, Asian Economic and Social Society, vol. 2(2), pages 103-114, June.
    3. Gerard Bikorimana & Charles Rutikanga & Didier Mwizerwa, 2020. "Linking energy consumption with economic growth: Rwanda as a case study," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2020(2), pages 181-200.
    4. Ekaterini Panopoulou, 2005. "A Resolution of the Fisher Effect Puzzle: A Comparison of Estimators," The Institute for International Integration Studies Discussion Paper Series iiisdp067, IIIS.
    5. Perles-Ribes, José Francisco & Ramón-Rodríguez, Ana Belén & Rubia, Antonio & Moreno-Izquierdo, Luis, 2017. "Is the tourism-led growth hypothesis valid after the global economic and financial crisis? The case of Spain 1957–2014," Tourism Management, Elsevier, vol. 61(C), pages 96-109.
    6. Neeraj, & Panigrahi, Prasanta K., 2017. "Causality and correlations between BSE and NYSE indexes: A Janus faced relationship," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 284-313.
    7. Man-Keun Kim & Kangil Lee, 2015. "Dynamic Interactions between Carbon and Energy Prices in the U.S. Regional Greenhouse Gas Initiative," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 494-501.
    8. Santos, Carlos Filipe & Fuinhas, José Alberto & Marques, António Cardoso, 2014. "O nexus energia-crescimento e o nível da auto-suficiência na produção de petróleo: análise com macro painel [Energy-growth nexus and oil self-sufficiency: macro panel analysis]," MPRA Paper 57008, University Library of Munich, Germany.
    9. Akadiri, Ada Chigozie & Akadiri, Seyi Saint & Gungor, Hasan, 2019. "The role of natural gas consumption in Saudi Arabia's output and its implication for trade and environmental quality," Energy Policy, Elsevier, vol. 129(C), pages 230-238.
    10. Fatma Unlu, 2022. "The Effects of Information and Communication Technologies on Labor Productivity and Employment in Turkiye: The ARDL Bounds Test Approach," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 72(72-2), pages 725-751, December.
    11. Mehmet Balcilar & Gizem Uzuner & Chinazaekpere Nwani & Festus Victor Bekun, 2023. "Boosting Energy Efficiency in Turkey: The Role of Public–Private Partnership Investment," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
    12. Hanan Naser, 2015. "Can Nuclear Energy Stimulates Economic Growth? Evidence from Highly Industrialised Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 164-173.
    13. Litsios, Ioannis & Pilbeam, Keith, 2017. "An empirical analysis of the nexus between investment, fiscal balances and current account balances in Greece, Portugal and Spain," Economic Modelling, Elsevier, vol. 63(C), pages 143-152.
    14. Hénoc Mpongo Mbulo, 2022. "« Impact du dividende démographique sur la croissance économique en République Démocratique du Congo (RDC) ; une approche par la modélisation AutoRegressive Distributed Lag (ARDL) »," Working Papers halshs-03735863, HAL.
    15. Hanson, Daniel & Toru Delibasi, Tuba & Gatti, Matteo & Cohen, Shamai, 2022. "How do changes in economic activity affect air passenger traffic? The use of state-dependent income elasticities to improve aviation forecasts," Journal of Air Transport Management, Elsevier, vol. 98(C).
    16. António Afonso & José Carlos Coelho, 2021. "Current Account Targeting Hypothesis versus Twin Deficit Hypothesis: The EMU Experience of Portugal," EconPol Working Paper 68, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    17. Aitor Ciarreta & Ainhoa Zarraga, 2007. "Electricity Consumption and Economic Growth: Evidence from Spain," Energy and Environmental Modeling 2007 24000009, EcoMod.
    18. Amiri, Arshia & Zibaei, Mansour, 2012. "Granger causality between energy use and economic growth in France with using geostatistical models," MPRA Paper 36357, University Library of Munich, Germany.
    19. Ali, Adnan & Ramakrishnan, Suresh & Faisal,, 2022. "Financial development and natural resources. Is there a stock market resource curse?," Resources Policy, Elsevier, vol. 75(C).
    20. Gritli, Mohamed Ilyes & Rey, Serge, 2019. "Compte capital et développement financier en Tunisie : Causalité et relation de long terme," L'Actualité Economique, Société Canadienne de Science Economique, vol. 95(4), pages 405-428, Décembre.

    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

    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:spr:inecre:v:58:y:2023:i:2:d:10.1007_s41775-023-00180-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.