Forecasting Interest Rates in India

Author:

Dua Pami1,Raje Nishita2,Sahoo Satyananda3

Affiliation:

1. Pami Dua is Professor, Department of Economics, Delhi School of Economics, University of Delhi, Delhi, India;

2. Nishita Raje is Director, Division of Econometrics, Department of Economic Analysis and Policy, Reserve Bank of India, Mumbai, India;

3. Satyananda Sahoo is Assistant Adviser, Division of Money and Banking, Department of Economic Analysis and Policy, Reserve Bank of India, Mumbai, India;

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.

Publisher

SAGE Publications

Subject

General Economics, Econometrics and Finance,Development

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