Panel Data Models
All of the linear and nonlinear models may be analyzed with special forms of panel data, including:

Fixed and random effects
Multilevel random effects
Latent class models
Random parameters (mixed) models
Unbalanced panels for all models
Unlimited panel data set size
Arellano/Bond DPD with many variations
IV and GMM estimators

Model Estimation and Analysis
Over 100 model formulations for continuous, discrete, limited and censored dependent variables are provided, including:

Linear and nonlinear regression
Robust estimation
Binary choice
Ordered choice models
Unordered multinomial choice
Censoring and truncation
Sample selection models
Count data
Loglinear models
Stochastic frontier and DEA
Survival analysis
Time series models
Panel data models

Data Description and Graphics
Descriptive statistics and graphical analysis tools include:

Descriptive statistics for cross sections and panels
Tables of means and quantiles
Time series
Graphics tools
Discriminant analysis

Count Data
The widest range of specifications for count data of any package is provided, including several newly developed models:

Poisson and negative binomial models
New specifications for NB models
Gamma, generalized Poisson, Polya
Aeppli
Zero inflation and hurdle
Fixed and random effects
Latent class

Statistical Analysis
Programming language allows extension of supported estimators:

Nonlinear estimation
Delta method for functions of parameters
Simulation: Krinsky and Robb
Testing and restrictions
Post estimation analysis
Predictions
Marginal effects

Data Environments
Nearly every model may be extended to a variety of frameworks including:

Data transformations
Cross section
Panel data
Time series manipulation

Programming and Numerical Analysis
Programming language including matrix and data manipulation commands is provided for building new estimators:

MAXIMIZE/MINIMIZE for user supplied functions
Matrix programming with LIMDEP
Scientific calculator
Numerical analysis tools, integration and differentiation
Simulation based estimation
Program Gibbs samplers

Fixed and random effects
Battese and Coelli
Heteroscedasticity
Technical inefficiency estimation
This is the only package with both SFA and DEA.

Discrete Choice Models in LIMDEP
Discrete choice estimators for binary, multinomial, ordered, count and multivariate discrete data are provided:

Binary choice - dozens of specifications
Ordered choice
Hierarchical ordered choice
Panel data
Multinomial logit
Count data models

Modeling Individual Choice with NLOGIT
NLOGIT contains all of LIMDEP plus numerous extensions of the multinomial choice models that do not appear in LIMDEP, including:

Nested logit model
Generalized nested logit model
Multinomial probit model
Mixed (random parameters) logit model
Latent class model
Error components (RE) logit model
Dynamic random effects MNL model
General utility specifications
Partial effects and elasticities
Model simulation
(These features do not appear in LIMDEP.)

Time Series Analysis
A range of estimators for time series are provides including:

ARMAX models
GARCH and GARCH-in-mean models
Spectral density estimation
ACF and PACF
Phillips-Perron tests
Newey-West estimator

Accuracy
Extremely accurate computational methods are employed throughout. High marks are earned on all National Institute of Standards and Technology test problems, including:

Descriptive statistics
Analysis of variance
Linear regression
Nonlinear least squares

Post Estimation
Extensive tools for post estimation enable manipulation of model results along with other statistics and procedures.

Data Management
Data management tools are provided for input of data or internal generation with the random number generators, including:

Data transformations
Sampling and bootstrapping
Bootstrap cross section observations or panel groups
Weighted data
Random number generation
Cluster sampling and stratification