Author(s): Alberto Alesina and Eliana La Ferrara
This paper proposes a test of racial bias in capital sentencing based upon patterns of judicial errors in lower courts. We model the behavior of the trial court as minimizing a weighted sum of the probability of sentencing an innocent and that of letting a guilty defendant free. We define racial bias as a situation where the relative weight on the two types of errors is a function of defendant and/or victim race. The key prediction of the model is that if the court is unbiased, ex post the error rate should be independent of the combination of defendant and victim race. We test this prediction using an original dataset that contains the the race of the defendant and of the victim(s) for all capital appeals that became final between 1973 and 1995. We find robust evidence of bias against minority defendants who killed white victims: in Direct Appeal and Habeas Corpus the probability of error in these cases is 3 and 9 percentage points higher, respectively, than for minority defendants who killed minority victims.