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Time-Varying Parameters of Inflation Model in Nepal: State Space Modeling

Author

Listed:
  • T.P.Koirala, Ph.D.

    (Nepal Rastra Bank, Research Department)

Abstract

This paper attempts to investigate the stability of time-varying parameters of the random walk model of inflation in Nepal. This study has been motivated with the Lucas Critique (1976) that the monetary/fiscal policy that is exposed to change over time affect the expectations of forward looking economic agents which hence lead to non-constant time-varying parameters of the model. Monthly time series of inflation ranging from August, 1997 to July, 2012 has been utilized for the analysis. Applying the Kalman Filter technique for the estimation of coefficients of random walk model, we found non-constant time varying parameters of both the constant and autoregressive of order one AR(1) coefficient of inflation over the long run. The changes in the expectations of rational economic agents on macroeconomic policies as a result of the problems of policy commitment, credibility and dynamic consistency might have attributed such non-constant time-varying parameters. Therefore, in addition to supply smoothing policies to control inflation in Nepal, consistent and credible policies that are not exposed to change over time may reduce the gap of actual inflation from its targets and hence trigger inflation into desired level.

Suggested Citation

  • T.P.Koirala, Ph.D., 2013. "Time-Varying Parameters of Inflation Model in Nepal: State Space Modeling," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, vol. 25(2), pages 66-77, October.
  • Handle: RePEc:nrb:journl:v:25:y:2013:i:2:p:66
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    References listed on IDEAS

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    1. R. H. Shumway & D. S. Stoffer, 1982. "An Approach To Time Series Smoothing And Forecasting Using The Em Algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(4), pages 253-264, July.
    2. Roberts John M., 2005. "How Well Does the New Keynesian Sticky-Price Model Fit the Data?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 5(1), pages 1-39, September.
    3. T. R. Bishnoi & T. P. Koirala, 2006. "Stability and Robustness of Inflation Model of Nepal: An Econometric Analysis," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 4(2), pages 114-129, July.
    4. Hamilton, James D., 1988. "Rational-expectations econometric analysis of changes in regime : An investigation of the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 385-423.
    5. James H. Stock & Mark W. Watson, 1993. "Introduction to "Business Cycles, Indicators and Forecasting"," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 1-10, National Bureau of Economic Research, Inc.
    6. Friedman, Benjamin M., 1979. "Optimal expectations and the extreme information assumptions of `rational expectations' macromodels," Journal of Monetary Economics, Elsevier, vol. 5(1), pages 23-41, January.
    7. Taylor, John B, 1975. "Monetary Policy during a Transition to Rational Expectations," Journal of Political Economy, University of Chicago Press, vol. 83(5), pages 1009-1021, October.
    8. Fuhrer, Jeffrey C, 1997. "The (Un)Importance of Forward-Looking Behavior in Price Specifications," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(3), pages 338-350, August.
    9. Shanken, Jay, 1990. "Intertemporal asset pricing : An Empirical Investigation," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 99-120.
    10. James H. Stock & Mark W. Watson, 1993. "Business Cycles, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number stoc93-1, September.
    11. Stock, James H. & Watson, Mark W. (ed.), 1993. "Business Cycles, Indicators, and Forecasting," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226774886.
    12. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
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    Keywords

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    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

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