Modeling the Firm as an Artificial Neural Network
AbstractThe purpose of this chapter is two-fold: (1) to make the case that a standard backward propagation artificial neural network (ANN) can be used as a general model of the information processing activities of the firm, and (2) to present a synthesis of Barr and Saraceno (BS) (2002, 2004, 2005), who offer various models of the firm as an artificial neural network.
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 Department of Economics, Rutgers University, Newark in its series Working Papers Rutgers University, Newark with number 2005-011.
Length: 30 pages
Date of creation: Oct 2005
Date of revision:
neural networks; information processing; firm learning; agent-based;
Find related papers by JEL classification:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-11-12 (All new papers)
- NEP-CBE-2005-11-12 (Cognitive & Behavioural Economics)
- NEP-CMP-2005-11-12 (Computational Economics)
- NEP-ICT-2005-11-12 (Information & Communication Technologies)
- NEP-MIC-2005-11-12 (Microeconomics)
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.:
- Jason Barr & Francesco Saraceno, 2004.
"Organization, Learning and Cooperation,"
- Myong-Hun Chang & Joseph E Harrington Jr, 2004.
"Agent-Based Models of Organizations,"
Economics Working Paper Archive
515, The Johns Hopkins University,Department of Economics.
- Barr, Jason & Saraceno, Francesco, 2005. "Cournot competition, organization and learning," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 277-295, January.
- Chung-Ming Kuan, 2006. "Artificial Neural Networks," IEAS Working Paper : academic research 06-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Sgroi, D., 2003. "Using Neural Networks to Model Bounded Rationality in Interactive Decision-Making," Cambridge Working Papers in Economics 0339, Faculty of Economics, University of Cambridge.
- Guido Fioretti, 2002.
"Recognizing Investment Opportunities at the Onset of Recoveries,"
- Fioretti, Guido, 2006. "Recognising investment opportunities at the onset of recoveries," Research in Economics, Elsevier, vol. 60(2), pages 69-84, June.
- Guido Fioretti, . "Recognizing Investment Opportunities at the Onset of Recoveries," Modeling, Computing, and Mastering Complexity 2003 07, Society for Computational Economics.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Vlad Manole).
If references are entirely missing, you can add them using this form.