Comparative numerical analysis of two stock-flow consistent post-Keynesian growth models
Stock-flow consistent (SFC) models become complex and hence rather intractable once they seek to incorporate more features of reality. Solving such models numerically for preselected parameter values can help to overcome this problem. But how should the parameters be selected given that there often exists a host of economically plausible values?
In order to address this problem, this paper suggests using a Monte Carlo approach to examine which combinations of parameters and starting values (feasibility regions) produce economically meaningful equilibria for the short and long run, and whether the long-term equilibria thus identified are in fact stable. In addition, we undertake a sensitivity analysis for all parameters which allows us to gauge the extent to which model results are driven by certain parameters and starting values.