REVERSE SHOOTING IN A MULTI-DIMENSIONAL SETTING

This paper investigates the properties of dynamic solutions that have been derived using the well-known reverse-shooting algorithm. Given an arbitrary large-scale model about which we have limited information, how successful is the algorithm likely to be in solving this model? We address this question using a range of investment models, both linear and non-linear. By extending the investment models to allow for multidimensional specifications of the capital stock, we are able to examine the computational efficiency of the reverse shooting algorithm as the dimensionality of the capital stock is allowed to increase. Our approach provides insights into how the complexity of the solutions to a broad range of macroeconomic models increases with the dimensionality of the models.