nlogit logoVersion 4.0

NLOGIT Version 4.0 is an extension of LIMDEP that provides programs for estimation, model simulation and analysis of multinomial choice data, such as brand choice, transportation mode, and all manner of survey and market data in which consumers choose among a set of competing alternatives. NLOGIT has become the premier package for estimation and simulation of multinomial discrete choice models.

NLOGIT 4.0 is a full information maximum likelihood estimator for, among other models, up to four level nested logit models. Many other formulations are included in NLOGIT, including random parameters (mixed logit), latent class, multinomial probit, many forms of the nested logit model, and several new formulations for panel data.

NLOGIT 4.0 includes all the features and capabilities of LIMDEP 9.0 plus NLOGIT’s FIML estimation programs. With the combination of LIMDEP and NLOGIT, NLOGIT 4.0 is the only large package for discrete choice analysis that contains the full set of features of an integrated econometrics program.

NLOGIT is a Complete Econometrics Package

NLOGIT takes the form of an econometrics studio. Analysis of a data set is done interactively in a set of windows. Program control may be from a 'script' or in an unstructured session of instructions and manipulations. The program is designed to allow easy setup of data for estimation, specification of different forms of the models, experimentation with different specifications, hypothesis testing, analysis of data and model results and construction of special procedures and estimators.

NLOGIT offers a complete set of tools for econometric analysis. In addition to the estimation programs, NLOGIT provides:

  • Data management, including input from all standard sources (such as Excel), all manner of transformations and sample controls
  • Built-in estimation programs plus a programming language, matrix algebra package and scientific calculator that allow you to write your own estimators, test statistics and simulation and analysis programs
  • Random number, vector and matrix capabilities for bootstrapping, Gibbs sampling and Monte Carlo simulation
  • A wide range of graphical and numeric descriptive statistics capabilities
  • Optimization tools that allow you to construct your own likelihood, GMM, or maximum simulated likelihood estimators
  • Analysis tools including graphics, numerical analysis and post estimation tools for specification and hypothesis testing
  • An extensive hard copy documentation set, with over 3,000 pages, containing full reference guides for the programs, background econometrics, and sample applications