How much confidence should we place in efficiency estimates?
How much confidence should we place in efficiency estimates?
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我们应该对效率估算有多大的信心？
作者：
A. Street
普通最小二乘(OLS)和随机前沿(SF)分析通常被用来估计行业水平和公司特定的效率。使用英国公立医院的横断面数据，估算了基于英国卫生部制定的规范的总成本函数。可信区间是围绕OLS残差和SF残差的无效分量来计算的。通过灵敏度分析来评估相对性能的结论对误差分布、函数形式和模型规格的选择是否具有稳健性。结论是，相对医院效率的估计对估计决策很敏感，对个别医院的点估计几乎没有可信度。应避免使用这些技术来设定年度业绩目标。
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.