Forecasting the real prices of crude oil under economic and statistical constraints

• We impose three types of parameter restrictions on predictive regressions.
• Parameter restriction can improve the predictive ability.
• The predictability is significant for longer horizons.
• The revealed predictability is robust to alternative benchmark models.

Forecasting the real oil prices is important but notoriously difficult. In this paper, we apply both economic and statistical restrictions to parameters of predictive regressions of real oil prices. We employ two popular criteria, mean predictive error (MSPE) and success ratio, to evaluate forecasting accuracy. Our out-of-sample results show that the benchmark of no-change model can be significantly outperformed by a model selection strategy with restricted models for longer horizons. The revealed predictability is further demonstrated to be robust to the adjustment of estimation windows and to an alternative benchmark model.