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我们应该对效率估计值抱有多大的信心?

How much confidence should we place in efficiency estimates?

作者信息

Street Andrew

机构信息

Centre for Health Economics, University of York, UK.

出版信息

Health Econ. 2003 Nov;12(11):895-907. doi: 10.1002/hec.773.

Abstract

Ordinary least squares (OLS) and stochastic frontier (SF) analyses are commonly used to estimate industry-level and firm-specific efficiency. Using cross-sectional data for English public hospitals, a total cost function based on a specification developed by the English Department of Health is estimated. Confidence intervals are calculated around the OLS residuals and around the inefficiency component of the SF residuals. Sensitivity analysis is conducted to assess whether conclusions about relative performance are robust to choices of error distribution, functional form and model specification. It is concluded that estimates of relative hospital efficiency are sensitive to estimation decisions and that little confidence can be placed in the point estimates for individual hospitals. The use of these techniques to set annual performance targets should be avoided.

摘要

普通最小二乘法(OLS)和随机前沿(SF)分析通常用于估计行业层面和企业特定的效率。利用英国公立医院的横截面数据,基于英国卫生部制定的规范估计了总成本函数。围绕OLS残差和SF残差的无效率成分计算了置信区间。进行了敏感性分析,以评估关于相对绩效的结论对于误差分布、函数形式和模型规范的选择是否稳健。得出的结论是,相对医院效率的估计对估计决策敏感,并且对于个别医院的点估计几乎无法置信。应避免使用这些技术来设定年度绩效目标。

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