Stochastic Optimization in Econometric Models – A Comparison of GA, SA and RSG
AbstractThis paper shows that, in case of an econometric model with a high sensitivity to data, using stochastic optimization algorithms is better than using classical gradient techniques. In addition, we showed that the Repetitive Stochastic Guesstimation (RSG) algorithm –invented by Charemza-is closer to Simulated Annealing (SA) than to Genetic Algorithms (GAs), so we produced hybrids between RSG and SA to study their joint behavior. The evaluation of all algorithms involved was performed on a short form of the Romanian macro model, derived from Dobrescu (1996). The subject of optimization was the model’s solution, as function of the initial values (in the first stage) and of the objective functions (in the second stage). We proved that a priori information help “elitist “ algorithms (like RSG and SA) to obtain best results; on the other hand, when one has equal believe concerning the choice among different objective functions, GA gives a straight answer. Analyzing the average related bias of the model’s solution proved the efficiency of the stochastic optimization methods presented.
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 Institute for Economic Forecasting in its series Working Papers of Institute for Economic Forecasting with number 080825.
Length: 29 pages
Date of creation: Aug 2008
Date of revision:
Contact details of provider:
Postal: Casa Academiei, Calea 13, Septembrie nr.13, sector 5, Bucureşti 761172
Phone: 004 021 3188148
Fax: 004 021 3188148
Web page: http://www.ipe.ro/
More information through EDIRC
underground economy; Laffer curve; informal activity; fiscal policy; transitionmacroeconomic model; stochastic optimization; evolutionary algorithms; Repetitive Stochastic Guesstimation;
Find related papers by JEL classification:
- E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-08-31 (All new papers)
- NEP-CMP-2008-08-31 (Computational Economics)
- NEP-ECM-2008-08-31 (Econometrics)
- NEP-MAC-2008-08-31 (Macroeconomics)
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.:
- Dobrescu, Emilian, 1996. "Macromodels of the Romanian transition Economy," MPRA Paper 35810, University Library of Munich, Germany.
- Wojciech W. Charemza, 1998.
Discussion Papers in Economics
98/1, Department of Economics, University of Leicester, revised Sep 1998.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Corina Saman).
If references are entirely missing, you can add them using this form.