Evaluación asimétrica de una red neuronal: aplicación al caso de la inflación en Colombia
AbstractThe objective of the present work is to explore the non-linear relationship between money and inflation in Colombia through an artificial neural network using monthly information for the variation of the consumer price index and the monetary aggregate M3 since January 1982 through February 2005. Artificial neural networks turn up as an excellent alternative for monetary authorities to count on the best models to forecast inflation and guide their policy decisions. This article incorporates some innovations in money and inflation modeling that allow to generate more reliable forecasts given that the model approximates reality with greater accuracy
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 InfoArticle provided by Universidad de Antioquia, Departamento de Economía in its journal LECTURAS DE ECONOMÍA.
Volume (Year): (2006)
Issue (Month): 65 (Julio-Diciembre)
Postal: Lecturas de Economía, Departamento de Economía, Calle 67, 53-108, Medellin 050010, Colombia.
Find related papers by JEL classification:
- D87 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Neuroeconomics
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral 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: (Carlos Andrés Vasco Correa).
If references are entirely missing, you can add them using this form.