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含不良投入与产出的生产效率推断：潜在价格与最优方向AI 解读

Researchers employ the directional distance function (DDF) to estimate multiple-input and multiple-output production, firm inefficiency, and productivity growth. We relax restrictive assumptions by computing optimal directions subject to profit maximization and cost minimization, correct for the potential endogeneity of inputs and outputs, estimate latent prices for bad outputs, measure firms’ responses to shadow prices rather than actual prices, and introduce an unobserved…

方向距离函数：最优内生方向AI 解读

A substantial literature has dealt with the problem of estimating multiple-input and multiple-output production functions, where inputs and outputs can be good and bad. Numerous studies can be found in the areas of productivity analysis, industrial organization, labor economics, and health economics. While many papers have estimated the more restrictive output- and input-oriented distance functions, here we estimate a more general directional distance function. A seminal…

通过贝叶斯数值方法估计企业特定的配置无效率AI 解读

Abstract Both the theoretical and empirical literature on the estimation of allocative and technical inefficiency has grown enormously. To minimize aggregation bias, ideally one should estimate firm and input‐specific parameters describing allocative inefficiency. However, identifying these parameters has often proven difficult. For a panel of Chilean hydroelectric power plants, we obtain a full set of such parameters using Gibbs sampling, which draws sequentially from…

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讨论：位似可分性对份额方程价格弹性的含义AI 解读

The assumption of homothetically separable utility (HSU) has been widely used in many recent studies of consumer demand. Atkinson (1979,1981), Caves and Christensen (1980), and Lau and Lillard (1979) maintain rather than test HSU in estimating price elasticities for electricity time-of-use pricing experiments, because of the nature of the data collected. Maintaining HSU when it cannot be supported by the structure of consumer preferences may lead to substantial biases in…

多重共线性下联立方程估计量的小样本性质AI 解读

A Monte Carlo simulation is employed to reinvestigate the general disagreement in the literature regarding the small-sample properties of simultaneous equation estimators under widely different levels of multicollinearity. This disagreement has been attributed to the greater use by more complex estimators of information on variables excluded from each equation, producing the advantage in inference of increasing precision at low levels of collinearity, but the disadvantage of…