In this article we show how to implement merger simulation in Stata after estimating an aggregate nested logit demand system with a linear regression model. We also show how to implement merger simulation when the demand parameters are not estimated, but instead calibrated to be consistent with outside information on average price elasticities and pro…t margins.

There is a known connection between the multinomial and the Poisson likelihoods. This, in turn, means that a Poisson regression may be transformed into a logit model and vice versa. In this paper, I show the data transformations required to implement this transformation. Several examples are used as illustrations.

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 with the tractability of logit. For this reason, logit kernel has been deemed the “model of the future” and is becoming extremel...

Multiple linear regression with special properties of its coefficients parameterized by exponent, logit, and multinomial functions is considered. To obtain always positive coefficients the exponential parameterization is applied. To get coefficients in an assigned range, the logistic parameterization is used. Such coefficients permit us to evaluate the impact of individual predictors in the mod...

There have been many studies that have documented the application of crash severity models to explore the relationship between accident severity and its contributing factors. Although a large amount of work has been done on different types of models, no research has been conducted about quantifying the sample size requirements for crash severity modeling. Similar to count data models, small dat...

The functional logit regression model was proposed by [@Escabias04] with the objective of modeling a scalar binary response variable from predictor. estimation in that case performed subspace $L^2(T)$ squared integrable functions finite dimension, generated set basis functions. For it assumed curves predictor and parameter belong to same subspace. so obtained affected high multicollinearity pro...

This paper uses data on automobile purchases to compare two alternatives to the multinomial logit model. The results indicate that the nested logit model is likely to be superior to the more general Berry–Levinsohn–Pakes model for applications using aggregate-level data.  2000 Elsevier Science S.A. All rights reserved.