TESTING RESTRICTIONS IN NONPARAMETRIC EFFICIENCY MODELS

Léopold Simar · Paul W. Wilson

106 citations0/0 files storedCommunications in Statistics - Simulation and Computation

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Efficiency Analysis Using DEA Statistical Methods and Inference Advanced Statistical Methods and Models

Abstract

This paper discusses statistical procedures for testing various restrictions in the context of nonparametric models of technical efficiency. In particular, tests for whether inputs or outputs are irrelevant, as well as tests of whether inputs or outputs may be aggregated are formulated. Bootstrap estimation procedures which yield appropriate critical values for the test statistics are also provided. Evidence on the true sizes and power of the proposed tests is obtained from Monte Carlo experiments.

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References

1978Measuring the efficiency of decision making units 1957The Measurement of Productive Efficiency 1959Portfolio Selection: Efficient Diversification of Investments 1962Portfolio Selection: Efficient Diversification of Investments.1979Measuring the efficiency of decision-making units 2015Theory of Cost and Production Functions 1951The Coefficient of Resource Utilization 1998Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models

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2013Comparing Malmquist and Hicks–Moorsteen productivity indices: Exploring the impact of unbalanced vs. balanced panel data 2011Performance of the Bootstrap for DEA Estimators and Iterating the Principle 2009A nonparametric efficiency analysis of German public transport companies 2005Public capital and total factor productivity: New evidence from the Italian regions, 1970–98 2018Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback

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