Three heuristics of search for a low price when initial information about the market is obsolete
AbstractIn traditional economics, buyer behaviour is usually modelled under the assumption of full information either on prices and their locations within the market or at least on the probability distribution of prices in the market. Neither of these assumptions seems appropriate in some cases such as when the buyer enters the specific market only very infrequently (e.g., markets for durables). This paper studies experimentally the search rules that buyers might use in this case of extreme lack of information on prices. The paper identifies three general search heuristics, derives three specific rules from the heuristics and, using data from a small-scale experiment, estimates parameters of the rules.
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 Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies in its series Working Papers IES with number 2006/17.
Length: 27 pages
Date of creation: Jul 2006
Date of revision: Jul 2006
search; heuristics; aspiration level; experiment;
Find related papers by JEL classification:
- D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-12-09 (All new papers)
- NEP-CBE-2006-12-09 (Cognitive & Behavioural Economics)
- NEP-EXP-2006-12-09 (Experimental Economics)
- NEP-PKE-2006-12-09 (Post Keynesian Economics)
You can help add them by filling out this form.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lenka Herrmannova).
If references are entirely missing, you can add them using this form.