Here artificial neural networks (ANNs) are employed for efficiency purposes. First, the main features of ANNs are … presented. Then, common techniques of the efficiency literature are reviewed: parametric (deterministic and stochastic) and non … advantages and drawbacks in the efficiency context are examined. Finally, these various methodologies are applied to refuse …

neural networks (ANNs) for measuring efficiency and productivity growth for seven East Asian economies at manufacturing level … measure efficiency and productivity under non-linear contexts, with minimum assumptions. …

addressed the productivity and efficiency of the core area of the armed forces, operational units, using Data Envelopment … Analysis (DEA). Introducing a model for the production process of an operational unit, productivity and efficiency are … find that, by using the bootstrap technique to estimate confidence intervals, we can point at the uncertainty of the …

When analyzing what determines the efficiency of production, regressing efficiency scores estimated by DEA on … suffers from severe flaws, that render its results, and in particular statistical inference based on them, questionable. At … the same time they propose a statistically grounded bootstrap based two-stage estimator that eliminates the above …

one input and one output, and previous bootstrap methods proposed for inference have not been proven consistent, making …) provide consistent inference. The smooth bootstrap requires smoothing the irregularly-bounded density of inputs and outputs as … in analyses of productive efficiency. The distributions of these estimators remain unknown except in the simple case of …