EconPapers    
Economics at your fingertips  
 

A Neural Network Demand System

Julien Boelaert ()
Additional contact information
Julien Boelaert: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique

Post-Print from HAL

Abstract: We introduce a new type of demand system using a feedforward artificial neural network. The neural network demand system is a flexible system that requires few hypotheses, has no roots in consumer theory but may be used to test it. We use the system to estimate demand elasticities on micro data of household consumption in Canada between 2004 and 2008, and compare the results to those of the quadratic almost ideal demand system.

Keywords: Estimating demand systems; neural networks; flexible forms; Quadratic Almost Ideal Demand System (QUAIDS); Systèmes de demande; réseaux de neurones artificiels; formes flexibles (search for similar items in EconPapers)
Date: 2013-12
New Economics Papers: this item is included in nep-cmp and nep-ore
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00917810
References: Add references at CitEc
Citations: Track citations by RSS feed

Published in 2013

Downloads: (external link)
https://shs.hal.science/halshs-00917810/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-00917810

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().

 
Page updated 2023-02-13
Handle: RePEc:hal:journl:halshs-00917810