A0445
Title: Identification of DSGE models: The effect of higher-order approximation and pruning
Authors: Willi Mutschler - TU Dortmund (Germany) [presenting]
Abstract: The aim is to show how to check rank criteria for a local identification of nonlinear DSGE models, given higher-order approximations and pruning. This approach imposes additional restrictions on (higher-order) moments and polyspectra, which can be used to identify parameters that are unidentified in a first-order approximation. The identification procedures are demonstrated by means of previous models. Both models are identifiable with a second-order approximation. Furthermore, analytical derivatives of unconditional moments, cumulants and corresponding polyspectra up to fourth order are derived for the pruned state-space.
