A1710
Title: Piecewise linear solutions for non-stationary models
Authors: Inna Tsener - Universitat de les Illes Balears (Spain) [presenting]
Mariano Kulish - University of Sydney (Australia)
Abstract: The aim is to assess the accuracy and efficiency of piecewise linear solutions for non-stationary models with rational expectations. We compare piecewise linear solutions against accurate global solutions. Using the canonical stochastic growth model we show that the piecewise linear solution is accurate when expansion sequences evolve according to the non-stochastic growth path of the non-linear model and when agents anticipate this growth path.
