nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2011‒09‒05
two papers chosen by
Philip Yu
Hong Kong University

  1. Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model By Filip Matejka; Alisdair McKay
  2. Partial Identification of Heterogeneity in Preference Orderings Over Discrete Choices By Itai Sher; Jeremy T. Fox; Kyoo il Kim; Patrick Bajari

  1. By: Filip Matejka; Alisdair McKay
    Abstract: Often, individuals must choose among discrete alternatives with imperfect information about their values, such as selecting a job candidate, a vehicle or a university. Before choosing, they may have an opportunity to study the options, but doing so is costly. This costly information acquisition creates new choices such as the number of and types of questions to ask the job candidates. We model these situations using the tools of the rational inattention approach to information frictions (Sims, 2003). We find that the decision maker's optimal strategy results in choosing probabilistically exactly in line with the multinomial logit model. This provides a new interpretation for a workhorse model of discrete choice theory. We also study cases for which the multinomial logit is not applicable, in particular when two options are duplicates. In such cases, our model generates a generalization of the logit formula, which is free of the limitations of the standard logit.
    Keywords: rational inattention; discrete choice; logit model
    JEL: D81 D83 D01
    Date: 2011–06
    URL: http://d.repec.org/n?u=RePEc:cer:papers:wp442&r=dcm
  2. By: Itai Sher; Jeremy T. Fox; Kyoo il Kim; Patrick Bajari
    Abstract: We study a variant of a random utility model that takes a probability distribution over preference relations as its primitive. We do not model products using a space of observed characteristics. The distribution of preferences is only partially identified using cross-sectional data on varying budget sets. Imposing monotonicity in product characteristics does not restore full identification. Using a linear programming approach to partial identification, we show how to obtain bounds on probabilities of any ordering relation. We also do constructively point identify the proportion of consumers who prefer one budget set over one or two others. This result is useful for welfare. Panel data and special regressors are two ways to gain full point identification.
    JEL: C25 L0
    Date: 2011–08
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:17346&r=dcm

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