Estimation of Heuristic Switching in Behavioral Macroeconomic Models

Abstract

This paper offers a simulation-based method for the estimation of heuristic switching in nonlinear macroeconomic models. Heuristic switching is an important feature of modeling strategy since it uses simple decision rules of boundedly rational heterogeneous agents. The simulation study shows that the proposed simulated maximum likelihood method identifies the behavioral effects that stay hidden for standard econometric approaches. In the empirical application, we estimate the structural and behavioral parameters of the US economy. We are especially able to reliably identify the intensity of choice that governs the models’ nonlinear dynamics.