Noise and bias in eliciting preferences
Hey, John D. and Morone, Andrea and Schmidt, Ulrich (2007) Noise and bias in eliciting preferences. [Discussion Paper]. p. 28. Discussion Papers in Economics (No. 07/04).
This is the latest version of this item.
PDF (Full text)
In the context of eliciting preferences for decision making under risk, we ask the question: "which might be the 'best' method for eliciting such preferences?". It is well known that different methods differ in terms of the bias in the elicitation; it is rather less well-known that different methods differ in terms of their noisiness. The optimal trade-off depends upon the relative magnitutdes of these two effects. We examine four different elicitation mechanisms (pairwise choice, willingness-to-pay, willingness-to-accept, and certainty equivalents) and estimate both effect. Our results suggest that economists might be better advised to use what appears to be a relatively inefficient elicitation technique (i.e. pairwise choice) in order to avoid trhe bias in better-known and more widely-used techniques.
|Item Type:||Report / Paper (Discussion Paper)|
|Research documents and activity classification:||Working Papers > Refereed Working Papers / of international relevance|
|Divisions:||Department of Business and Management|
|Additional Information:||The paper has been published as: John Hey & Andrea Morone & Ulrich Schmidt, 2009. "Noise and bias in eliciting preferences," Journal of Risk and Uncertainty, Springer, vol. 39(3), pages 213-235, December.|
|Uncontrolled Keywords:||Pairwise choice; willingness-to-pay; willingness-to-accept; errors; noise; biases.|
|MIUR Scientific Area:||Area 13 - Economics and Statistics > SECS-P/01 Political Economy|
|Deposited by:||Maria Teresa Nistico|
|Date Deposited:||06 Dec 2010 14:57|
|Last Modified:||21 Apr 2015 23:13|
Available Versions of this Item
Noise and bias in eliciting preferences. (deposited 28 Oct 2009 09:57)
- Noise and bias in eliciting preferences. (deposited 06 Dec 2010 14:57) [Currently Displayed]
Downloads per month over past year
Repository Staff Only