New Multinomial Choice Models

NLOGIT 6 includes many new commands and extension of the random parameters model and latent class models:

• Fixed effects in multinomial logit models
• Random effects multinomial logit models
• Random regret logit model
• Best/worst outcome data
• Berry, Levinsohn and Pakes random parameters logit model
• Latent classes with random parameters
• Generalized mixed logit

Model Extensions

• Willingness to pay
• Attribute nonattendance (explicit and implicit)
• Individual specific expected parameters
• Model simulation
• Estimated elasticities and partial effects
• Robust covariance matrix
• Random data generators
• Posterior estimates from latent class models
• Coefficients in random parameters models
• Simplified WALD command

More NLOGIT  Features

NLOGIT  includes all of LIMDEP  plus the full set of features in NLOGIT, including the additional data management features, estimators for many types of discrete 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.
• 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, 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
• 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.
• 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.
• Simulation
  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.