EconPapers    
Economics at your fingertips  
 

A Learning Design for Reducing Hypothetical Bias in the Contingent Valuation Method

David Bjornstad, Ronald Cummings and Laura Osborne ()
Authors registered in the RePEc Author Service: Laura O. Taylor

Environmental & Resource Economics, 1997, vol. 10, issue 3, 207-221

Abstract: Over the last few years a great deal of research has focussed on hypothetical bias in value estimates obtained with the contingent valuation (CV) method and on means for ameliorating if not eliminating such bias. To date, efforts to eliminate hypothetical bias have relied on calibration techniques or on word-smithing of one kind or another to induce subjects to provide responses to hypothetical questions that mimic responses made by subjects facing actual payments in the valuation experiment. This paper introduces a different approach for eliminating hypothetical bias. A design for a CV survey format is presented which provides subjects with the opportunity to “learn” how the CV institution works. Sequential referenda are conducted where respondents gain experience in CV settings by participating in both hypothetical and real referenda. The logic of this Learning Design is a straightforward application of the trials process used in experimental economics. We demonstrate that the Learning Design is effective in eliminating hypothetical bias in surveys concerning donations to two different public goods. Copyright Kluwer Academic Publishers 1997

Keywords: contingent valuation; hypothetical bias; experimental economics (search for similar items in EconPapers)
Date: 1997
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)

Downloads: (external link)
http://hdl.handle.net/10.1023/A:1026423201797 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:enreec:v:10:y:1997:i:3:p:207-221

Ordering information: This journal article can be ordered from
http://www.springer. ... al/journal/10640/PS2

DOI: 10.1023/A:1026423201797

Access Statistics for this article

Environmental & Resource Economics is currently edited by Ian J. Bateman

More articles in Environmental & Resource Economics from Springer, European Association of Environmental and Resource Economists Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-19
Handle: RePEc:kap:enreec:v:10:y:1997:i:3:p:207-221