Abstract
The aim of the present paper is to attack some of the conceptual problems that arise when the framework of mathematical learning theory is applied to the description of the behavior of the firm, in setting prices and production quotas, in a competitive market. The goal is to depict the process by which the firm fixes prices and production quotas as a stochastic learning process. A solution to such problems is proposed which is based on statistical-decision concepts. The conceptualization of the behavior of the firm by means of concepts pertaining to mathematical learning theory gives rise to certain mathematical problems, which are formulated here in rather precise terms.
Similar content being viewed by others
References
Fuchs, G.: 1979, ‘Is Error Learning Behaviour Stabilizing?’, Journal of Economic Theory 20,
Lange, O.: 1962, Introduction to Econometrics, Pergamon Press, Oxford.
Suppes, P.: 1959, ‘Stimulus Sampling Theory for a Continuum of Responses’, in K. J. Arrow, S. Karlin, and P. Suppes (eds.), Mathematical Methods in the Social Sciences, Stanford University Press, Stanford.
Suppes, P. and Atkinson, R. C.: 1960, Markov Learning Models for Multiperson Interactions, Stanford University Press, Stanford.
Suppes, P. and Carlsmith, J. M.: 1962, ‘Experimental Analysis of a Duopoly Situation from the Standpoint of Mathematical Learning Theory’, International Economic Review 3.
Author information
Authors and Affiliations
Additional information
I am glad to acknowledge the support given to the research project leading to the present paper by the National University of Mexico, through the DGAPA, as well as by Tilburg's Catholic University (Holland). I appreciate also the fruitful comments and suggestions made to me by Dr Gustavo Valencia (Facultad de Ciencias, University of Mexico) in connection with some of the topics presented in this paper.
Rights and permissions
About this article
Cite this article
de la Sienra, A.G. Open problems in the foundations of price formation dynamics. Erkenntnis 30, 87–99 (1989). https://doi.org/10.1007/BF00184817
Received:
Issue Date:
DOI: https://doi.org/10.1007/BF00184817