We Know What You Choose! External Validity of Discrete Choice Models
For over the last thirty years the multinomial logit model has been the standard in choice modeling. Development in econometrics and computational algorithms has led to the increasing tendency to opt for more flexible models able to depict more realistically choice behavior. This study compares three discrete choice models, the standard multinomial logit, the error components logit, and the random parameters logit. Data were obtained from two choice experiments conducted to investigate consumers’ preferences for fresh pears receiving several postharvest treatments. Model comparisons consisted of in-sample and holdout sample evaluations. Results show that product characteristics hence, datasets, influence model performance. We also found that the multinomial logit model outperformed in at least one of three evaluations in both datasets. Overall, findings signal the need for further studies controlling for context and dataset to have more conclusive cues for discrete choice models capabilities.
|Date of creation:||Apr 2010|
|Contact details of provider:|| Postal: PO Box 646210, Pullman, WA 99164-646210|
Web page: http://faculty.ses.wsu.edu/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:wsu:wpaper:gallardo-6. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Danielle Engelhardt)
If references are entirely missing, you can add them using this form.