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生产率效率得分的自由处置包络估计量AI 解读

In productivity analysis, the free disposal hull (FDH) is a nonparametric estimator for the production set, the set of inputs and outputs that are technically feasible. It is defined as the smallest free disposal set containing all observations in a sample of production units. One can then derive the production frontier and efficiency scores from the FDH. In the literature the method is used as if the FDH estimator were the true feasible set. However, assuming that…

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单调边界的有效估计AI 解读

Let $g: \lbrack 0, 1\rbrack \rightarrow \lbrack 0, 1\rbrack$ be a monotone nondecreasing function and let $G$ be the closure of the set $\{(x, y) \in \lbrack 0, 1\rbrack \times \lbrack 0, 1\rbrack: 0 \leq y \leq g (x)\}$. We consider the problem of estimating the set $G$ from a sample of i.i.d. observations uniformly distributed in $G$. The estimation error is measured in the Hausdorff metric. We propose the estimator which is asymptotically efficient in the minimax sense.

随机前沿模型中的有效半参数估计AI 解读

Abstract This article considers the semiparametric stochastic frontier model with panel data that arises in the problem of measuring technical inefficiency in production processes. We assume a parametric form for the frontier function, which is linear in production inputs. The density of the individual firm-specific effects is considered to be unknown. We construct an efficient estimator of the slope parameters in the frontier function. We also give an estimator of the level…

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回归模型贝叶斯分析中的最小二乘近似AI 解读

SUMMARY Least-Squares approximation of the parameters in a regression model are worked out in a Bayesian framework and shown to provide, at a low computational cost, a setup to handle non-normal models and/or non-natural conjugate prior distributions. This allows one to balance an approximate solution to a reasonable model against an exact solution to a simplified model.