Reverse-Shooting versus Forward-Shooting over a Range of Dimensionalities
AbstractThis paper investigates the properties of dynamic solutions that have been derived using the well-known reverse-shooting and forwardshooting algorithms. Given an arbitrary large-scale model about which we have limited information, how successful are the algorithms 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 multi-dimensional specifications of the capital stock, we are able to examine the computational efficiency of the competing algorithms 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by The University of Melbourne in its series Department of Economics - Working Papers Series with number 921.
Length: 21 pages
Date of creation: 2004
Date of revision:
Contact details of provider:
Postal: Department of Economics, The University of Melbourne, 5th Floor, Economics and Commerce Building, Victoria, 3010, Australia
Phone: +61 3 8344 5289
Fax: +61 3 8344 6899
Web page: http://www.economics.unimelb.edu.au
More information through EDIRC
Macroeconomics; Reverse-shooting; Forward-shooting; Saddlepath instability; Computational techniques; Investment models.;
Find related papers by JEL classification:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- E27 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Fumio Hayashi, 1981.
"Tobin's Marginal q and Average a : A Neoclassical Interpretation,"
457, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Hayashi, Fumio, 1982. "Tobin's Marginal q and Average q: A Neoclassical Interpretation," Econometrica, Econometric Society, vol. 50(1), pages 213-24, January.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marisa Cerantola).
If references are entirely missing, you can add them using this form.