The TSCSREG procedure provides combined time series cross-sectional regression analysis. The TSCSREG procedure includes the following features:
estimation of the regression parameters under several common error structures:
Fuller and Battese method (variance component model)
Wansbeek-Kapteyn method
Parks method (autoregressive model)
Da Silva method (mixed variance component moving-average model)
one-way fixed effects
two-way fixed effects
one-way random effects
two-way random effects
any number of model specifications
unbalanced panel data for the fixed or random-effects models
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