The PANEL procedure deals with panel data sets that consist of time series observations on each of several cross-sectional units. The PANEL procedure includes the following features:
one-way and two-way fixed effects
one-way and two-way random effects
variance component estimation by the following methods:
Fuller and Battese method (variance component model)
Wansbeek and Kapteyn method
Wallace and Hussain method
Nerlove method
Parks method (autoregressive model)
Da Silva method (mixed variance component moving-average model)
Hausman-Taylor and Amemiya-MaCurdy estimation
dynamic-panel estimation one-step, two-step, or iterative generalized method of moments (GMM)
support for unbalanced panel data for all methods
model specification tests
panel data unit-root tests
automatic generation of lagged variables
model comparison tables
model specification tests
variety of estimates and statistics, including the following:
underlying error components estimates
regression parameter estimates
standard errors of estimates
t tests
R-square statistic
correlation matrix of estimates
covariance matrix of estimates
autoregressive parameter estimate
cross-sectional components estimates
autocovariance estimates
F tests of linear hypotheses about the regression parameters
specification tests, including the Hausman test