Panel Data Models

Nearly all of the models in LIMDEP may be analyzed with special tools for panel data.  A partial list of the panel data models supported in LIMDEP includes:

• Linear regression model, OLS, GLS, IV
• Probit, logit, Gompertz, complementary log log binary choice
• Tobit, truncated regression, categorical data
• Survival models: exponential, Weibull, lognormal, loglogistic
• Loglinear models: Weibull, gamma, exponential, inverse Gauss
• Stochastic frontier
• Bivariate probit, partial observability
• Ordered probit, ordered logit, ordered Gompertz, ordered complementary log log
• Sample selection
• Poisson, negative binomial, zero inflated Poisson
• Conditional logit (multinomial logit - discrete choice)
  

The panel data models include fixed and random effects, random parameters and latent class models for almost all nonlinear models supported by the package. There are also numerous special estimators for the linear model, such as Arellano and Bond's GMM estimator for dynamic panels and Hausman and Taylor's estimator for random effects models. No panel data operation anywhere in the program requires that the data set be balanced. Most estimators place no limit on the number of groups in the panel - the data set is already 'in the program' so it must already fit in memory. Many tools in addition to the estimation programs are also provided. For example, you can bootstrap sample groups in your panel data set, a feature we have not seen anywhere else.