Penalizing ordered and multinomial likelihood functions with prior information for discrete choice modeling of consumer demand

Abstract

This research note extends Bayesian discriminant analysis procedures to the ordered and multinomial logistic likelihood functions. Use of the procedure is warranted when the researcher desires to identify the membership of individuals randomly drawn from distinct groups or locations in a population, rather than from a random sample of undifferentiated individuals from a population. An empirical application analyzes consumers’ reasons why they choose to support a beef product produced with enhanced pasture management practices.

Keywords

• C18
• C25
• C51