ESTIMATION OF A DISCRETE CHOICE MODEL WHEN INDIVIDUAL CHOICES ARE NOT OBSERVABLE

This paper presents an econometric technique for circumventing the lack of individual choice data in a framework of binary choice model by utilizing aggregate choice data. The probability of observing a certain number of individuals making choice A out of the total number of individuals in a group is presented as a sum of probabilities of disjoint events, in which some individuals are picked to make choice A, and others are not. These probabilities are then used to form a likelihood function. The model, which is estimated using the method of maximum likelihood, performs favorably in an application to real discrete choice data.


Issue Date:
2003
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/22230
Total Pages:
15
Series Statement:
Selected Paper




 Record created 2017-04-01, last modified 2017-08-24

Fulltext:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)