Certainty Equivalence and the Non-Vertical Long Run Phillips-Curve

The certainty equivalence principle states that only the mean of a random variable is relevant to a decision maker facing uncertainty. This principle simplifies the application of the idea of rational expectations considerably. Yet, certainty equivalence does not in general apply outside of the special case of quadratic objective function subject to linear constraints. I use the standard augmented Phillips-Curve to demonstrate the significant effects that occur with the breakdown of certainty equivalence