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Some Empirical Evidence on Models of the Fisher Relation: Post-Data Comparison

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  • KIM, Jae-Young
  • PARK, Woong Yong

Abstract

The Fisher relation, describing a one-for-one relation between the nominal interest rate and the expected inflation, underlies many important results in economics and finance. Although it is a conceptually simple relation, the Fisher relation has more or less complicated with mixed results. There are several alternative models proposed in the empirical literature for the Fisher relation that have different implications. We evaluate those alternative models for the Fisher relation based on a post-data model determination method. Our results for data from the U.S. Japan and Korea show that models with both regimes/periods, a regime with nonstationary fluctuations and the other with stationary fluctuations, fit data best for the Fisher relation.

Suggested Citation

  • KIM, Jae-Young & PARK, Woong Yong, 2018. "Some Empirical Evidence on Models of the Fisher Relation: Post-Data Comparison," Discussion paper series HIAS-E-68, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
  • Handle: RePEc:hit:hiasdp:hias-e-68
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    References listed on IDEAS

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    1. Frederic S. Mishkin, 1984. "The Real Interest Rate: A Multi-Country Empirical Study," Canadian Journal of Economics, Canadian Economics Association, vol. 17(2), pages 283-311, May.
    2. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August.
    3. Mishkin, Frederic S., 1990. "What does the term structure tell us about future inflation?," Journal of Monetary Economics, Elsevier, vol. 25(1), pages 77-95, January.
    4. Garcia, Rene & Perron, Pierre, 1996. "An Analysis of the Real Interest Rate under Regime Shifts," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 111-125, February.
    5. Andrews, Donald W.K. & Kim, Jae-Young, 2006. "Tests for Cointegration Breakdown Over a Short Time Period," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 379-394, October.
    6. Seo, Myung Hwan, 2008. "Unit Root Test In A Threshold Autoregression: Asymptotic Theory And Residual-Based Block Bootstrap," Econometric Theory, Cambridge University Press, vol. 24(06), pages 1699-1716, December.
    7. Fama, Eugene F, 1975. "Short-Term Interest Rates as Predictors of Inflation," American Economic Review, American Economic Association, vol. 65(3), pages 269-282, June.
    8. Nelson, Charles R & Schwert, G William, 1977. "Short-Term Interest Rates as Predictors of Inflation: On Testing the Hypothesis That the Real Rate of Interest is Constant," American Economic Review, American Economic Association, vol. 67(3), pages 478-486, June.
    9. Rose, Andrew Kenan, 1988. " Is the Real Interest Rate Stable?," Journal of Finance, American Finance Association, vol. 43(5), pages 1095-1112, December.
    10. Garbade, Kenneth & Wachtel, Paul, 1978. "Time variation in the relationship between inflation and interest rates," Journal of Monetary Economics, Elsevier, vol. 4(4), pages 755-765, November.
    11. Fama, Eugene F. & Gibbons, Michael R., 1982. "Inflation, real returns and capital investment," Journal of Monetary Economics, Elsevier, vol. 9(3), pages 297-323.
    12. V. Vance Roley, 1986. "The Response of Interest Rates to Money Announcements under Alternative Operating Prosedures and Reserve Requirement Systems," NBER Working Papers 1812, National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    Fisher relation; nonlinear behavior; post-data model determination;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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