Interest Rate Forecasting Using Regression Analysis
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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 – of which 2 processes are involved: 1) model building, and 2) forecasting
Model building: model the relationship between interest rate and relevant macro variables as prescribed by economic theories and quantify (estimate) the relationships using an econometric technique
Forecasting – use the estimated model and assumptions on explanatory variables to project future values of the interest rate
Literature Review
A Structural approach to interest rate forecasting
Model building
Economic theories: which economic variables could cause interest rate to deviate from equilibrium
Econometric estimation: at which magnitudes would interest rates be affected by changes in economic variables (quantification of economic relationships)
Economic Theory
What is an interest rate?
Cost of capital (price of borrowing money)
Could be different among various players and uses: Thus different measures of interest rate (short-term, long-term, risk-free etc.)
Example of various types of interest rates
Short-term
Interbank overnight call rates
1-day, 7-day, 14-day, 1-month repurchase rates
3-month, 6 month, 12 months deposit rates
Long-term (more than 1 year)
Government/corporate bond rates
Bank lending rates
Trend determinants of real interest rates
Saving and Investment
Demographic factors
Returns to capital
International financial integration
Country specific risk premium
Saving and Investment
Higher investment demand (public and/or private) relative to saving Ðo higher interest rates
Slower productivity growth and/or slower population growth Ðo lower returns to capital Ðo lower investment demand
Higher consumption (public and/or private) Ðo less saving Ðo higher interest rates
Demographic factors
Aging populations Ðo “baby boomers” in the saving phase of life cycles Ðo push up savings Ðo but once retired Ðo will have negative impacts on government budget and national savings
Returns to capital
Debt competes with equity Ðo an expected rise in return on equity will push up real interest rates
Rising productivity, economic reform, trade liberalization, lower inflation should push up business profits (at least theoretically) and thus interest rates
International financial integration
Will lead to similar risk-adjusted returns on similar assets across countries (yet way to go)
Country specific risk premium
To compensate for such factors as default risk, market volatility, inflation variability, etc.
Government debt
Higher government debt relative to GDP Ðo similar effects on long term real rates as higher current account deficit
Higher government debt relative to GDP Ðo crowding out private investment Ðo reduction in saving Ðo push up long rates
Higher government debt relative to GDP Ðo expectation of future tax increases Ðo higher risk premium
International risk premium
Higher risk premium Ðo higher uncertainty Ðo higher real interest rates
Can be proxied by beta of the countrys bond returns to a world bond portfolio or by government bond spread
Relative bond and equity risk
Higher riskiness of bonds relative to equities Ðo higher long rates
Constant