We propose new scoring rules based on partial likelihood for assessing the relative out-of-sample predictive accuracy of competing density forecasts over a specific region of interest, such as the left tail in financial risk management. By construction, existing scoring rules based on weighted...

We determine the scoring rule that is most likely to select a high-ability candidate. A major result is that neither the widely used plurality rule nor the inverse-plurality rule are ever optimal, and that the Borda rule is hardly ever optimal. Furthermore, we show that only the...

We determine the scoring rule that is most likely to select a high-ability candidate. A major result is that neither the widely used plurality rule nor the inverse-plurality rule are ever optimal, and that the Borda rule is hardly ever optimal. Furthermore, we show that only the almostplurality,...

We determine the scoring rule that is most likely to select a high-ability candidate. A major result is that neither the widely used plurality rule nor the inverse-plurality rule are ever optimal, and that the Borda rule is hardly ever optimal. Furthermore, we show that only the...

We propose the concept of level r consensus as a useful property of a preference profile which considerably enhances the stability of social choice. This concept involves a weakening of unanimity, the most extreme form of consensus. It is shown that if a preference profile exhibits level r...