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Replication data for: A Test of Racial Bias in Capital Sentencing

Resource Type
  • Alesina, Alberto
  • La Ferrara, Eliana
Publication Date
  • Abstract

    We collect a new dataset on capital punishment in the US and we propose a test of racial bias based upon patterns of sentence reversals. We model the courts as minimizing type I and II errors. If trial courts were unbiased, conditional on defendants race the error rate should be independent of the victims race. Instead we uncover 3 and 9 percentage points higher reversal rates in Direct Appeal and Habeas Corpus cases, respectively, against minority defendants who killed whites. The pattern for white defendants is opposite but not statistically significant. This bias is confined to Southern States.
  • Is supplement to
    DOI: 10.1257/aer.104.11.3397 (Text)
  • Alesina, Alberto, and Eliana La Ferrara. “A Test of Racial Bias in Capital Sentencing.” American Economic Review 104, no. 11 (November 2014): 3397–3433.
    • ID: 10.1257/aer.104.11.3397 (DOI)

Update Metadata: 2020-05-18 | Issue Number: 2 | Registration Date: 2020-03-23

Alesina, Alberto; La Ferrara, Eliana (2014): Replication data for: A Test of Racial Bias in Capital Sentencing. Version: 1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset.