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Forecasting Interest Rates in India

Author

Listed:
  • Pami Dua

    (Pami Dua is Professor, Department of Economics, Delhi School of Economics, University of Delhi, Delhi, India; e-mail: dua@econdse.org)

  • Nishita Raje

    (Nishita Raje is Director, Division of Econometrics, Department of Economic Analysis and Policy, Reserve Bank of India, Mumbai, India; e-mail: nbraje@rbi.org.in)

  • Satyananda Sahoo

    (Satyananda Sahoo is Assistant Adviser, Division of Money and Banking, Department of Economic Analysis and Policy, Reserve Bank of India, Mumbai, India; e-mail: ssahoo@rbi.org.in)

Abstract

This paper develops univariate (ARIMA and ARCH/GARCH) and multivariate models (VAR, VECM and Bayesian VAR) to forecast short- and long-term rates, viz., call money rate, 15–91 days Treasury Bill rates and interest rates on Government securities with (residual) maturities of one year, five years and 10 years. Multivariate models consider factors such as liquidity, repo rate, yield spread, inflation rate, foreign interest rates and forward premium. The paper finds that multivariate models generally outperform univariate ones over longer forecast horizons. Overall, the paper concludes that the forecasting performance of Bayesian VAR models is satisfactory for most interest rates and their superiority in performance is marked at longer forecast horizons.

Suggested Citation

  • Pami Dua & Nishita Raje & Satyananda Sahoo, 2008. "Forecasting Interest Rates in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 2(1), pages 1-41, March.
  • Handle: RePEc:sae:mareco:v:2:y:2008:i:1:p:1-41
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    Cited by:

    1. Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2013. "Forecasting the US Real Private Residential Fixed Investment Using Large Number of Predictors," Working Papers 201348, University of Pretoria, Department of Economics.
    2. repec:ipg:wpaper:2014-465 is not listed on IDEAS
    3. Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2016. "Forecasting US real private residential fixed investment using a large number of predictors," Empirical Economics, Springer, pages 1557-1580.
    4. Goodness C. Aye & Rangan Gupta, 2013. "Forecasting Real House Price of the U.S.: An Analysis Covering 1890 to 2012," Working Papers 201362, University of Pretoria, Department of Economics.
    5. repec:spr:jqecon:v:15:y:2017:i:2:d:10.1007_s40953-017-0077-4 is not listed on IDEAS
    6. Naik, Prasad A., 2015. "Marketing Dynamics: A Primer on Estimation and Control," Foundations and Trends(R) in Marketing, now publishers, pages 175-266.
    7. Nicholas Apergis & Ghassen El Montasser & Emmanuel Owusu-Sekyere & Ahdi N. Ajmi & Rangan Gupta, 2014. "Dutch Disease Effect of Oil Rents on Agriculture Value Added in MENA Countries," Working Papers 201408, University of Pretoria, Department of Economics.
    8. Nombulelo Gumata, Alain Kabundi and Eliphas Ndou, 2013. "Important Channels of Transmission Monetary Policy Shock in South Africa," Working Papers 375, Economic Research Southern Africa.

    More about this item

    Keywords

    Bayesian VAR Models; Forecasting; Interest Rate Modelling; JEL Classification: C11; JEL Classification: C32; JEL Classification: C53; JEL Classification: E54;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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