Central Limit Theorems for Aggregate Efficiency
为聚合效率估计（如行业效率）建立了完整的渐近理论，填补了该领域缺乏理论支撑的空白，使研究者能基于数据包络分析等方法进行更准确的统计推断。
Applied researchers in the field of efficiency and productivity analysis often need to estimate and make inference about aggregate efficiency, such as industry efficiency or aggregate efficiency of a group of distinct firms within an industry (e.g., public versus private firms, regulated versus unregulated firms, etc.). While there are approaches to obtain point estimates for such important measures, no asymptotic theory has been derived for it. This is the gap in the literature we fill with this paper. Specifically, we develop full asymptotic theory for aggregate efficiency measures when the individual true efficiency scores being aggregated are observed as well as when they are unobserved and estimated via the data envelopment analysis or the free disposal hull. As a result, the developed theory opens a path for more accurate and theoretically better grounded statistical inference (e.g., estimation of confidence intervals and conducting statistical tests) on aggregate efficiency estimates such as industry efficiency, etc.