Better the Devil You Know: Improved Forecasts from Imperfect Models

<ns2:p>Many important economic decisions are based on a parametric forecasting model that is known to be good but imperfect. We propose methods to improve out-of-sample forecasts from a mis-specified model by estimating its parameters using a form of local M estimation (thereby nesting local OLS and local MLE), drawing on information from a state variable that is correlated with the misspecification of the model. We theoretically consider the forecast environments in which our approach is likely to o¤er improvements over standard methods, and we find significant fore- cast improvements from applying the proposed method across distinct empirical analyses including volatility forecasting, risk management, and yield curve forecasting.</ns2:p>

Duke Scholars

Author Andrew J. Patton Economics