Capabilities
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:
Frontier and Efficiency Analysis
All forms of the stochastic frontier model are provided:
- 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:
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: