This thesis presents methods for obtaining asymptotically efficient and consistent parameters and variance estimates for simultaneous equations in a forest growth modelling context. Ordinary Least Squares (OLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares (2SLS) and Three- Stage Least Squares (3SLS) are presented for linear models. The variables, model types and transformations are examined for appropriateness in diameter and height growth models in young stands. A basal diameter growth, height growth and static crown ratio model were developed using the methods described. Model performance was measured by the ratio of the standard-errors of the predictions for basal diameter growth, height growth and crown ratio as described by Hasenauer et al. (1998). The 3SLS model performed better than the 2SLS or OLS for the basal diameter growth. The advantages of using 3SLS over 2SLS or OLS for the height growth and crown ratio models were minimal. Finally, a simultaneous equation estimation package was developed for the R (Ihaka and Gentleman, 1996) open-source computer program
