A Test of Racial Bias in Capital Sentencing∗

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 type I and type II errors, namely 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 the race of the defendant, or of the victim, or of the combination of the two. The key prediction of the model is that if the court is unbiased, ex post the error rate should be independent of the race of the defendant and/or the victim. We test this prediction using an original dataset that contains the outcomes of all capital appeals that became final between 1973 and 1995, together with the race of the defendant and of the victim(s). We do not find evidence of bias when looking at the race of the defendant per se. However, in Habeas Corpus cases we find strong and robust evidence of bias against minority defendants who killed white victims: the probability of error in these cases is 15 percentage points higher than for minority defendants who killed minority victims. ∗We thank Abhijit Banerjee, Richard Dieter, Jeffrey Fagan, Hamming Fang, Paola Giuliano and Nicola Persico for helpful discussions. Giulia La Mattina, Lucia Rizzica, Erika Deserranno and Damiano Briguglio provided excellent research assistance. This paper was written while Alesina was visiting IGIER Bocconi. He thanks this institution for hospitality. La Ferrara acknowledges financial support from the European Research Council grant ERC-2007-StG-208661. The usual disclaimer applies.