USING BOOTSTRAPPED CONFIDENCE-INTERVALS FOR IMPROVED INFERENCES WITH SEEMINGLY UNRELATED REGRESSION EQUATIONS

The usual standard errors for the regression coefficients in a seeming ly unrelated regression model have a substantial downward bias, Bootst rapping the standard errors does not seem to improve inferences, In th is paper, Monte Carlo evidence is reported which indicates that bootst rapping can result in substantially better inferences when applied to t-ratios rather than to standard errors.