Bayesian Efficiency Analysis With a Flexible Form: The AIM Cost Function
使用吉布斯抽样方法对带有渐近理想价格加总、非恒定规模报酬和复合误差的成本前沿模型进行后验推断，并通过实证例子展示效率度量对前沿函数形式假设的敏感性。
In this article we describe the use of Gibbs sampling methods for drawing posterior inferences in a cost frontier model with an asymptotically ideal price aggregator, nonconstant returns to scale, and composed error. An empirical example illustrates the sensitivity of efficiency measures to assumptions made about the functional form of the frontier. We also examine the consequences of imposing regularity through parametric restrictions alone.