References of "Santin, Daniel"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailImposing monotonicity on outputs in parametric distance function estimations
Perelman, Sergio ULg; Santin, Daniel

in Applied Economics (2011)

Detailed reference viewed: 20 (4 ULg)
Full Text
Peer Reviewed
See detailHow to generate regularly behaved production data? A Monte Carlo experimentation on DEA scale efficiency measurement
Santin, Daniel; Perelman, Sergio ULg

in European Journal of Operational Research (2009), (199), 303-310

Monte Carlo experimentation is a well-known approach used to test the performance of alternative methodologies under different hypotheses. In the frontier analysis framework, whatever the parametric or ... [more ▼]

Monte Carlo experimentation is a well-known approach used to test the performance of alternative methodologies under different hypotheses. In the frontier analysis framework, whatever the parametric or non-parametric methods tested, experiments to date have been developed assuming single output multi-input production functions. The data generated have mostly assumed a Cobb–Douglas technology. Among other drawbacks, this simple framework does not allow the evaluation of DEA performance on scale efficiency measurement. The aim of this paper is twofold. On the one hand, we show how reliable two-output two-input production data can be generated using a parametric output distance function approach. A variable returns to scale translog technology satisfying regularity conditions is used for this purpose. On the other hand, we evaluate the accuracy of DEA technical and scale efficiency measurement when sample size and output ratios vary. Our Monte Carlo experiment shows that the correlation between true and estimated scale efficiency is dramatically low when DEA analysis is performed with small samples and wide output ratio variations. [less ▲]

Detailed reference viewed: 20 (5 ULg)