Maximum entropy models are often used to describe supply and demand behavior in urban transportation and land use systems. However, they have been criticized for not representing behavioral rules of system agents and because their parameters seems to adjust only to modeler-imposed constraints. In response, it is demonstrated that the solution to the entropy maximization problem with linear cons...

As datasets capturing human choices grow in richness and scale—particularly in online domains—there is an increasing need for choice models that escape traditional choice-theoretic axioms such as regularity, stochastic transitivity, and Luce’s choice axiom. In this work we introduce the Pairwise Choice Markov Chain (PCMC) model of discrete choice, an inferentially tractable model that does not ...

Logit Kernel is a discrete choice model that has both probit-like disturbances as well as an additive i.i.d. extreme value (or Gumbel) disturbance à la multinomial logit. The result is an intuitive, practical, and powerful model that combines the flexibility of probit (and more) with the tractability of logit. For this reason, logit kernel has been deemed the “model of the future” and is becomi...

Many researchers have used the conditional logit model to examine migration. One common objection to this model is that it carries the independence from irrelevant alternatives (IIA) assumption, which may be too restrictive. This study compares the conditional logit with models that partially relax (nested logit) or fully relax (mixed logit) the IIA assumption. We will begin to learn whether as...

In this paper we develop a two-step survival time approach – a discrete logit model with survival time dummies – that allows for time-varying explanatory variables and interval censored data. Our empirical analysis reveals that the twostep approach outperforms the benchmark logit model with respect to out-ofsample prediction accuracy. Survival time, however, does not play an important role. The...

Empirical studies on household car ownership have used two types of discrete choice modelling structures, the ordered and the unordered. In ordered structures such as the ordered logit and ordered probit models, the choice of the number of household-vehicles arises from a uni-dimensional latent index that reflects the propensity of a household to own vehicles. Unordered response models, on the ...

This study makes use of the results of a postal questionnaire sent to a sample of large private sector companies in Britain and France to address two key issues in the new institutional analysis of the firm. The first is the way the institutional environment supports and constrains the design of firm-level organisational devices and governance mechanisms. The second concerns the relation betwee...

Theory: The spatial model of elections can better be represented by using conditional logit than by multinomial logit. The spatial model, and random utility models in general, suffer from a failure to adequately consider the sub­ stitutability of candidates sharing similar or identical issue positions. Hypotheses: Multinomial logit is not much better than successive applications of binomial log...

We propose 2 related models for the meta-analysis of diagnostic tests. Both models are based on the bivariate normal distribution for transformed sensitivities and false-positive rates. Instead of using the logit as a transformation for these proportions, we employ the tα family of transformations that contains the log, logit, and (approximately) the complementary log. A likelihood ratio test f...

This study analyzes characteristics determining member’s willingness to invest in cooperatives using ordered logit model. The data were collected in a field survey among 122 cooperative members in north-central China. The descriptive analysis of survey evidence suggests that cooperatives in China generally having poor ability to deliver the processing services related to product package, gradin...