NLOGIT

NLOGIT is a statistical software package used for discrete choice modeling. It is developed by Train and McFadden, pioneers in the field of microeconometrics. NLOGIT allows researchers to estimate various models of consumer choice, including logit, probit, and nested logit models. These models are fundamental for understanding how individuals make decisions when faced with a set of mutually exclusive alternatives, such as choosing a mode of transportation, selecting a brand of product, or deciding on a residential location.

The software is particularly well-suited for analyzing data where choices are structured in a hierarchical or nested fashion. For example, a consumer might first decide to buy a car, and then within that decision, choose a specific make and model. Nested logit models, which are a core feature of NLOGIT, can capture such decision hierarchies. The package also supports more advanced model specifications, including mixed logit models, which can account for unobserved heterogeneity in preferences across individuals.

NLOGIT's capabilities extend to handling large datasets and complex sampling designs. It provides robust estimation methods and diagnostic tools to assess model fit and interpret results. Its primary applications are found in econometrics, marketing research, transportation studies, and other fields where understanding and predicting choices are crucial. The software's flexibility makes it a valuable tool for both academic research and practical policy analysis.