Comparative numerical analysis of two stock-flow consistent post-Keynesian growth models

Stock-flow-consistent (SFC) models are an active and fruitful area of research in Post-Keynesian economics. However, SFC models become complex and hence rather intractable once they seek to incorporate more features of reality. Thus analytical solutions are difficult to obtain. Solving the model numerically for preselected parameter values can help to overcome this problem. But how should parameters be selected given that there often exists a host of economically plausible values? Picking just one such combination seems rather arbitrary implying that any conclusion derived from the model on the basis of some randomly selected parameter configuration has to be taken with a grain of salt. However, modern computers make it possible to explore the property of models in a much more systematic fashion than hitherto the case. Thus rather than picking specific assumption out of the blue, only very general assumptions about parameters have been made in this paper. We then use 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.

CIUFFO Biagio;  ROSENBAUM Eckehard; 

2015-04-30

Edward Elgar Publishing

JRC86038

2052-7764,   

http://www.elgaronline.com/abstract/journals/ejeep/12-1/ejeep.2015.01.09.xml,    https://publications.jrc.ec.europa.eu/repository/handle/JRC86038,   

10.4337/ejeep.2015.01.09,