Optimal Contracting Of New Experience Goods
AbstractWe model new experience goods in the context of dynamic mechanism design. These are goods for which an agent is unsure of her valuation but can learn it through consumption experience. We consider a dynamic environment with a single buyer and seller in which contracting occurs over T periods, where each time the agent consumes the object, she receives a signal which allows her to revise her valuation. In this setting, experimentation with the product is strategic both for the buyer and seller. We derive the efficient and seller optimal contracts and compare them. We present a simple two period example which highlights some of the key features of the model. Finally, the methodology developed in the paper can be used to design efficient and optimal contracts in a multi-buyer setting with learning, where each buyer has single unit demand and there is a single object for sale in each period.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 9880.
Date of creation: 04 Aug 2008
Date of revision:
Dynamic mechanism design; new experience goods; bandit problems;
Find related papers by JEL classification:
- D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law
- D44 - Microeconomics - - Market Structure and Pricing - - - Auctions
- D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-08-14 (All new papers)
- NEP-CTA-2008-08-14 (Contract Theory & Applications)
- NEP-MIC-2008-08-14 (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.:
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