Time Series Cross-Sectional Regression Analysis

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