解耦(概率)
道德风险
逆向选择
计算机科学
简单(哲学)
校长(计算机安全)
选择(遗传算法)
危害
风险分析(工程)
人工智能
精算学
经济
微观经济学
认识论
激励
业务
计算机安全
工程类
哲学
控制工程
生态学
生物
作者
Henrique Castro-Pires,Héctor Chade,Jeroen M. Swinkels
摘要
While many real-world principal-agent problems have both moral hazard and adverse selection, existing tools largely analyze only one at a time. Do the insights from the separate analyses survive when the frictions are combined? We develop a simple method—decoupling—to study both problems at once. When decoupling works, everything we know from the separate analyses carries over, but interesting interactions also arise. We provide simple tests for whether decoupling is valid. We develop and numerically implement an algorithm to calculate the decoupled solution and check its validity. We also provide primitives for decoupling to work and analyze several extensions. (JEL D82, D86)
科研通智能强力驱动
Strongly Powered by AbleSci AI