BOOTSTRAPPED INSIGHTS INTO EMPIRICAL APPLICATIONS OF STOCHASTIC-DOMINANCE

• 成果类型: Article
• 署名作者: NELSON, RD; POPE, RD
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.37.9.1182
• 发表日期: 1991
• 页码: 1182-1194
• 关键词: Bootstrapping; EMPIRICAL DISTRIBUTION FUNCTION; 1ST AND 2ND DEGREE STOCHASTIC DOMINANCE; MONTE-CARLO SIMULATION

摘要

Bootstrapping a very versatile statistical technique, significantly amplifies the understanding and success of empirical applications of stochastic dominance. Its ability to calculate the standard deviations of order statistics reveals the uncertainty of the critical estimates of the tails of cumulative density functions. Understanding this uncertainty reveals why a wide variety of tail shapes all cause a notable loss in power for stochastic dominance tests. Simulations show that the smoothing inherent in bootstrapping can significantly increase the power of the tests when dominance exists in the population.