International Real Business Cycles and Increasing Returns to Scale: A Formal Analysis using Likelihood Methods
One of the more common methods used to model international real business cycles is through the use of a dynamic stochastic general equilibrium (DSGE) model. Guo and Sturzenegger (1998) argue that an increasing returns to scale production technology can improve the performance of such a model. They also argue that if increasing returns are strong enough, then sunspot equilibria are possible. In this paper, we formally test the increasing returns to scale assumption and find that a model with a constant returns to scale technology has a superior out-of-sample prediction performance over a model with an increasing returns to scale production technology. Moreover, this result is robust to the degree of returns to scale and to the persistence and variance of the shocks in the model.
|Date of creation:||18 Jun 2002|
|Contact details of provider:|| Postal: New Jersey Hall - 75 Hamilton Street, New Brunswick, NJ 08901-1248|
Phone: (732) 932-7363
Fax: (732) 932-7416
Web page: http://economics.rutgers.edu/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:rut:rutres:200212. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()
If references are entirely missing, you can add them using this form.