Multinomial Choice in NLOGIT

NLOGIT has become the standard package for estimation and simulation of multinomial choice models. The most recent developments in multinomial choice modeling, including generalized mixed logit, random regret models, scaled MNL, latent class and WTP space specifications are provided. Among the many other formulations included in NLOGIT Version 6 are: up to four level nested logit models; random parameters (mixed logit) models with nonlinear utility functions; multinomial probit, the generalized nested logit model, and several new formulations for panel data and stated choice experiments. NLOGIT is the only large package for multinomial choice modeling that contains the full set of features of an integrated econometrics and statistics program (LIMDEP).

NLOGIT 6 includes all of LIMDEP 11 plus the full set of features in NLOGIT, including the additional data management features, estimators for many types of multinomial choice models, and the program simulator.

Data Analysis

NLOGIT will typically be used to analyze individual, cross section data on consumer choices and decisions from multiple alternatives. But, the program is equally equipped for market shares or frequency data, data on rankings of alternatives, and, for several of the estimators, panel data from repeated observation of choice situations. There are several data handling procedures for NLOGIT in addition to all those available in LIMDEP. Details

Model Estimation

NLOGIT supports a greater range of models for discrete choice than any other package. These include state of the art estimators for the mixed (random parameters) logit model, WTP space, random regret, and nonlinear utility models. The basic multinomial logit model, nested logit models up to four levels, and the multinomial probit model are also supported.

NLOGIT contains all of the discrete choice estimators supported by LIMDEP, plus the extensions of the discrete choice models which do not appear in LIMDEP. These include:

  • Multinomial logit - many specifications
  • Random effects MNL
  • Generalized mixed logit
  • Random regret logit
  • MNL with nonlinear utility functions
  • WTP space specifications in mixed logit
  • Scaled multinomial logit
  • Nested logit
  • Generalized nested logit
  • Multinomial probit
  • Mixed (random parameters) logit
  • Heteroscedastic extreme value
  • Covariance heterogeneity
  • Latent class
  • Latent class random parameters
  • Nonlinear utilities with random parameters
  • Attribute nonattendance

Model Specification

NLOGIT’s estimation programs are accessed as LIMDEP model commands. Since discrete choice models are often more complicated to specify than other single equation models in LIMDEP, the command setup includes many specifications that are specific to NLOGIT. Details

Inference Tools for Hypothesis Testing

The full set of post estimation and analysis tools in LIMDEP is accessed by NLOGIT. This includes the Wald, likelihood ratio and Lagrange multiplier tests, and all the matrix algebra and scientific calculator tools. NLOGIT also provides tools specific for discrete choice analysis, including built-in procedures for testing the IIA assumption of the multinomial logit model.


Any model estimated by NLOGIT can be used in ‘what if’ analyses using the model simulation package. The base case model produces fitted probabilities data that aggregate to a prediction of the sample shares for the alternatives in the choice set. The simulator is then used, with the estimation data set or any other compatible data set, to recompute these shares under scenarios that you specify, such as a change in the price of a particular alternative or a change in household incomes. Details