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Effect of Experimental Design on Choice‐Based Conjoint Valuation Estimates
Author(s) -
Lusk Jayson L.,
Norwood F. Bailey
Publication year - 2005
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.1111/j.1467-8276.2005.00761.x
Subject(s) - valuation (finance) , credibility , monte carlo method , design of experiments , conjoint analysis , computer science , willingness to pay , econometrics , paired comparison , optimal design , mathematical optimization , economics , statistics , mathematics , microeconomics , machine learning , preference , finance , political science , law
In this article, we investigate the effect of several commonly used experimental designs on willingness‐to‐pay in a Monte Carlo environment where true utility parameters are known. All experimental designs considered in this study generated unbiased valuation estimates. However, random designs or designs that explicitly incorporated attribute interactions generated more precise valuation estimates than main effects only designs. A key result of our analysis is that a large sample size can substitute for a poor experimental design. Overall, our results indicate that certain steps can be taken to achieve a manageably sized experimental design without sacrificing the credibility of welfare estimates.