This paper demonstrates how a two or three component error structure can be used with seemingly unrelated regressions. Its application may be particularly useful with large panel data sets when the researcher wishes to estimate several equations simultaneously and believes that errors both between and within equations are correlated over time and across units. Relatively simple algorithms are presented for estimation of the error covariance matrix and generalized least squares coefficients.