Interest Rate Forecasting using Regression Analysis

Introduction

• Forecast of interest rates can be done in many different ways, qualitative (surveys, opinion polls) as well as quantitative (reduced form and structural approaches)*
• Example of methods in quantitative approaches
- Regression method
- Univariate method (e.g. ARIMA)
- Vector autogressive models (VAR)
- Single equation approaches
- Structural systems of simultaneous equations

This paper will focus on the structural approach relying mainly on the Regression Model technique

Advantages of the structural approach:
• Rests on economic theory (unlike reduced form methods such as VAR)
• Can trace the effects of changes in macroeconomic variables to interest rates (more likely long rates)

Disadvantages of the structural approach
• Data not always readily available at the required frequency

To forecast interest rates using macroeconomic variables imply the use of a structural approach......

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Title: Interest Rate Forecasting Using Regression Analysis
Approximate Word Count: 1071
Approximate Pages: 5 (250 words per double-spaced page)

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