We consider the incentive characteristics of optimal linear contracts based on relative performance evaluation (RPE) for managers undermoral hazard in imperfectly competitive product markets. Each contract influences the quantity choices of all competing agents causing contract externalities

Using data from China, this paper examines the role of relative performance eval-uation in the turnover decisions made by the central government. We find that the turnover of provincial leaders hinges on provincial economic performance relative to their immediate predecessors.

Relative performance schemes (e.g., tournaments) are commonly used in markets for a variety of livestock and processing commodities, while explicit versions of these schemes are rarely (if ever) used in markets for fresh fruits and vegetables and specialty grains. We show how contracts for each

Abstract not found

, in contrast to the Relative Performance Evaluation hypothesis, but consistent with several empirical studies. 1

detailed analyses of annual bonus plans, executive stock options, and option valuation), international pay differences, the pay-setting process, the relation between CEO pay and firm performance (“pay-performance sensitivities”), the relation between sensitivities and subsequent firm performance, relative

the optimal contract subject to the fund manager’s participation constraint. We find that the impact of relative performance evaluation on the equilibrium equity premium and on portfolio herding critically depends on whether the participation constraint is binding. Simple numerical examples suggest

workload generation tool which mimics a set of real users accessing a server. The tool, called Surge (Scalable URL Reference Generator) generates references matching empirical measurements of 1) server file size distribution; 2) request size distribution; 3) relative file popularity; 4) embedded file

their performance depends on the interest region detector. The descriptors should be distinctive and at the same time robust to changes in viewing conditions as well as to errors of the detector. Our evaluation uses as criterion recall with respect to precision and is carried out for different image transformations

were used as baselines, since they were evaluated on all versions of Reuters that exclude the unlabelled documents. As a global observation, kNN, LLSF and a neural network method had the best performance; except for a Naive Bayes approach, the other learning algorithms also performed relatively well.