In this study we evaluate the economic usefulness of oil price forecasts by means of conditional forecasting of three US core macroeconomic indicators that policy makers are predicting, using assumptions about the future path of the oil prices. The chosen indicators are the core inflation rate, industrial production and producer price index. We further consider two more indicators, namely inflation expectation and monetary policy uncertainty. To do so, we initially forecast oil prices using a MIDAS framework and subsequently we use regression-based models for our conditional forecasts. Overall, there is diminishing importance of oil price forecasts for macroeconomic projections and policy formulation. An array of arguments is presented as to why this might be the case, which relate to the improved energy efficiency in the US, the contemporary monetary policy tools and the financialisation of the oil market. Our findings remain robust to alternative oil price forecasting frameworks and model specifications.
Oil price forecasts and macroeconomic projections
See also
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Machine learning for EU macroeconomic forecasting
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A Consolidation of the Macroeconomic Neoclassical General Equilibrium Theory via Keynesianism
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Input-Biased Technical Progress and the Aggregate Elasticity of Substitution: Evidence from 14 EU Member States
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Production Structure, International Trade and Carbon Footprint
