Applied Economics Workshop
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چکیده
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 de ne 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 nal between 1973 and 1995. We nd 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. We thank Shamena Anwar, Abhijit Banerjee, Katherine Barnes, Francesco Corielli, Richard Dieter, John Donohue, Je¤rey Fagan, James MacKinnon, Nicola Persico, Andrei Shleifer and seminar participants at CIAR, Duke, Warwick, Royal Holloway, IIES Stockholm University, Queens University, NBER Political Economy Conference, CEPR Public Policy Conference and Villa La Pietra Conference on New Directions in Applied Microeconomics for helpful comments. Giulia La Mattina, Lucia Rizzica, Erika Deserranno, Mariagiovanna Di Feo, Damiano Briguglio, Giovanni Rizzo, Matteo Fiorini and Marta Barazzetta provided excellent research assistance. This paper was written while Alesina was visiting IGIER Bocconi. He thanks this institution for hospitality. La Ferrara acknowledges nancial support from the European Research Council grant ERC-2007-StG-208661. The usual disclaimer applies.
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تاریخ انتشار 2011