Forecasting Interest Rates in India

Pami Dua, Nishita Raje and Satyananda Sahoo
Additional contact information
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

Margin: The Journal of Applied Economic Research, 2008, vol. 2, issue 1, 1-41

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.

Keywords: Bayesian VAR Models; Forecasting; Interest Rate Modelling; JEL Classification: C11; JEL Classification: C32; JEL Classification: C53; JEL Classification: E54 (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/097380100700200101 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:mareco:v:2:y:2008:i:1:p:1-41

DOI: 10.1177/097380100700200101

Access Statistics for this article

More articles in Margin: The Journal of Applied Economic Research from National Council of Applied Economic Research
Bibliographic data for series maintained by SAGE Publications ().