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...

The cigarette market is of ongoing interest to competition authorities as it features a small number of rms selling di erentiated though similar products. However, the extent of market power and the response of competition authorities to mergers in this industry has not been recently analysed. In this paper we estimate a nested logit model of demand for cigarettes in Australia using a dataset o...

Nested logit is increasingly advocated as a tool of recreational demand and benefit estimation. The intent of this short monograph is to lay out, in a simple fashion, the theory behind the nested-logit model of site choice and the nested-logit model of participation and site choice. Rigorous but straightforward derivations of the properties of nested-logit models are provided, including the pro...

A Iogit vector model and a logit ideal point model are presented for external analysis of paired comparison preference judgments aggregated over a homogeneous group. The logit vector model is hierarchically nested within the logit ideal point model so that statistical tests are available to distinguish between these two models. Generalized least squares estimation procedures are developed to ac...

The emergence of Intelligent Transportation Systems and the associated technologies has increased the need for complex models and algorithms. Namely, real-time information systems, directly influencing transportation demand, must be supported by detailed behavioral models capturing travel and driving decisions. Discrete choice models methodology provide an appropriate framework to capture such ...

In a recent paper in this journal, Wojcik (2000) argues that the nested logit model “is likely to be superior” to alternative random coefficients logit specifications, like those we and many others have used in recent work (e.g. Berry, Levinsohn, and Pakes (1995), henceforth BLP). Her conclusion is based on a within sample “prediction” exercise. We would like to raise several issues about her c...

We develop a method for estimating the rivalness of tax bases using the structures of the conditional logit, Poisson and nested logit models. As an illustration, we apply this method to estimate the e↵ect of state-level capital taxation on U.S. inward foreign direct investment. The assumption of perfect non-rivalenss can in some cases be rejected, but the assumption of perfect rivalness cannot....