Nonparametric Technical Efficiency with K Firms, N Inputs, and M Outputs: A Simulation

Technical efficiency estimation with multiple inputs and multiple outputs using regression analysis

Regression and linear programming provide the basis for popular techniques for estimating technical efficiency. Regression-based approaches are typically parametric and can be both deterministic or stochastic where the later allows for measurement error. In contrast, linear programming models are nonparametric and allow multiple inputs and outputs. The purported disadvantage of the regression-b...

Technical Efficiency Estimation with Multiple Inputs and Multiple Outputs Using Regression Analysis

Regression and linear programming provide the basis for popular techniques for estimating technical efficiency. Regression based approaches are typically parametric and can be both deterministic or stochastic where the later allows for measurement error. In contrast, linear programming models are nonparametric and allow multiple inputs and outputs. The purported disadvantage of the regression b...

DEA Models with Interval Scale Inputs and Outputs

This paper proposes an alternative approach for efficiency analysis when a set of DMUs uses interval scale variables in the productive process. To test the influence of these variables, we present a general approach of deriving DEA models to deal with the variables. We investigate a number of performance measures with unrestricted-in-sign interval and/or interval scale variables.

Basic Block Basic Block Input Multiplexors I inputs Clock N outputs K input LUT FF Inputs

State Dependent M/M/C/K/N Machining System with Mixed Spares and Removable Repairmen