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