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Actively Learning about Demand and the Dynamics of Price Adjustment

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  • Balvers, Ronald J
  • Cosimano, Thomas F

Abstract

By observing the quantity demanded at particular prices, a firm may learn about the parameters of its demand curve. In such an environment, price changes obstruct the learning process by inducing additional noise. The authors' paper constructs a dynamic model where a price-setting firm endogenously controls the speed of learning. The model provides a possible explanation for price inertia, as a stable pricing policy allows the firm to learn more rapidly, which improves future expected profits. Furthermore, even in the long run, learning continues to affect the firm's optimal price. Copyright 1990 by Royal Economic Society.

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Bibliographic Info

Article provided by Royal Economic Society in its journal The Economic Journal.

Volume (Year): 100 (1990)
Issue (Month): 402 (September)
Pages: 882-98

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Handle: RePEc:ecj:econjl:v:100:y:1990:i:402:p:882-98

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Cited by:
  1. Cosimano, Thomas F., 2008. "Optimal experimentation and the perturbation method in the neighborhood of the augmented linear regulator problem," Journal of Economic Dynamics and Control, Elsevier, vol. 32(6), pages 1857-1894, June.
  2. Wieland, Volker, 2000. "Learning by doing and the value of optimal experimentation," Journal of Economic Dynamics and Control, Elsevier, vol. 24(4), pages 501-534, April.
  3. Aldo Rustichini & Asher Wolinsky, 1992. "Learning about Variable Demand in the Long Run," Discussion Papers 1015, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  4. Christos Koulovatianos, & Leonard J. Mirman & Marc Santugini, . "Optimal Growth and Uncertainty: Learning," Discussion Papers 08/08, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  5. Holmes, James M. & Dowd, Michael R. & Black, David C., 1995. "Ignorance may be optimal? Some welfare implications of rational versus non-rational expectations," Journal of Macroeconomics, Elsevier, vol. 17(3), pages 377-386.
  6. Alexandre X. Carvalho & Martin L. Puterman, 2005. "Dynamic Optimization and Learning: How Should a Manager set Prices when the Demand Function is Unknown ?," Discussion Papers 1117, Instituto de Pesquisa Econômica Aplicada - IPEA.
  7. Leonard J. Mirman & Marc Santugini, 2012. "Learning and Technology Progress in Dynamic Games," Cahiers de recherche 1217, CIRPEE.
  8. Klumpp, Tilman, 2006. "Linear learning in changing environments," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2577-2611, December.
  9. Leonard J. Mirman & Kevin Reffett & Marc Santugini, 2013. "On Learning and Growth," Cahiers de recherche 1336, CIRPEE.
  10. Batlome Janjgava & Sergey Slobodyan, 2011. "Duopoly Competition, Escape Dynamics and Non-cooperative Collusion," CERGE-EI Working Papers wp445, The Center for Economic Research and Graduate Education - Economic Institute, Prague.
  11. Christos Koulovatianos & Leonard J. Mirman & Marc Santugini, 2011. "Investment in a Monopoly with Bayesian Learning," Cahiers de recherche 11-05, HEC Montréal, Institut d'économie appliquée.
  12. Kelly, David L. & Kolstad, Charles D., 1999. "Bayesian learning, growth, and pollution," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 491-518, February.
  13. Tim Willems, 2013. "Actively Learning by Pricing: A Model of an Experimenting Seller," Economics Series Working Papers 687, University of Oxford, Department of Economics.
  14. Mario Tello, 1992. "Precios relativos, producción interna y exportaciones en modelos de competencia imperfecta doméstica y mercados segmentados," Documentos de Trabajo 1992-107, Departamento de Economía - Pontificia Universidad Católica del Perú.
  15. Mason, Robin & Välimäki, Juuso, 2011. "Learning about the arrival of sales," Journal of Economic Theory, Elsevier, vol. 146(4), pages 1699-1711, July.

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