Non-Linearities and the Euler Equation: Does Uncertainty Have an Effect on the Approximation Quality?

Abstract

Abstract Deriving a forward-looking Euler equation, this paper compares two fully identified non-linear versions. The difference (or bias) between them stems from an approximation by extracting parameters from the expectation values (Jensen’s inequality) as it is common practice in the literature. Furthermore, the model is completely identified using Consensus Forecasts data for the expectations, inflation-indexed bonds as a proxy for the long-run real interest rate, and estimates for the elasticity of intertemporal substitution. Regression analyses using data for three major economies reveal that the difference between the two Euler versions can be explained by uncertainty in the data itself and external uncertainty measures. The results confirm a connection between theoretical and empirical higher-order moments in economic models.