Economics Department

Working Papers in Economics

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TITLE:
Nearest-Neighbor Forecasts of U.S. Interest Rates

AUTHOR(S):
John Barkoulas, Boston College
Christopher F. Baum, Boston College
Atreya Chakraborty, Boston College

DOCUMENT TYPE: Article

ABSTRACT:
We employ a nonlinear, nonparametric method to model the stochastic behavior of changes in several short and long term U.S. interest rates. We apply a nonlinear autoregression to the series using the locally weighted regression (LWR) estimation method, a nearest-neighbor method, and evaluate the forecasting performance with a measure of root mean square error. We compare the forecasting performance of the nonparametric fit to the performance of two benchmark linear models: an autoregressive model and a random-walk-with-drift model. The nonparametric model exhibits greater out-of-sample forecast accuracy than that of the linear predictors for most U.S. interest rate series. The improvements in forecasting accuracy are statistically significant and robust. This evidence establishes the presence of significant nonlinear mean predictability in U.S. interest rates, as well as the usefulness of the LWR method as a modeling strategy for these benchmark series.

Publication Status: published in International Journal of Banking and Finance, 1:1, 119- 135, 2003.