This article demonstrates how to estimate the parameters of a system of seemingly unrelated regressions when the equations are unbalanced, i.e., when the equations have an unequal number of observations. With estimators that require the data to be in wide format, such as Stata’s sureg, the equations must be balanced. Any additional observations that are available for some equations, but not for all, are discarded, potentially resulting in a loss of efficiency. Reshaping and scaling the data allows us to use Stata’s xtgee command to fit the model and obtain estimates utilizing all the available data. The resulting estimator is potentially more efficient when the equations are unbalanced.