Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Principals often operate on misspecified models of their agents’ preferences. When preferences are such that non-local incentive constraints may bind in the optimum, even slight misspecification of the preferences can lead to large and non-vanishing losses. Instead, we propose a two-step scheme whereby the principal: (1) identifies the model-optimal menu; and (2) modifies prices by offering to share with the agent a fixed proportion of the profit she would receive if an item were sold at the model-optimal price. We show that her loss is bounded and vanishes smoothly as the model converges to the truth. Finally, two-step mechanisms without a sharing rule like (2) will not yield a valid approximation.