Estimating the hyperbolic distance function: A directional distance function approach

The influence of public subsidies on farm technical efficiency: A robust conditional nonparametric approach

“…In this line, further research should focus on new approaches for subsidy allocation as in Amores and Contreras (2009) and on multicriteria analyses for better resource management (Hayashi, 2000). It is also recommended that further research uses advanced modeling approaches which allow a simultaneous contraction of inputs and bad outputs, and expansion of good outputs including environmental outputs (Halkos and Tzeremes, 2013;Daraio and Simar, 2014;Tzeremes, 2015;Färe et al, 2016;Latruffe and Desjeux, 2016;Dakpo et al, 2016), for a full picture of the effects of subsidies on production decisions.…”

Lexicographic hyperbolic DEA

“…without the convexity constraint on the intensity variables) can be linearised and it is equivalent to the classical radial DEA model of Charnes et al (1978). As regards model (1), Färe et al (2016) have proposed an ingenious iterative solution approach that only needs to solve a finite sequence of linear programming (LP) models of DDF type. They present numerical results on real-world and simulated data confirming that the iterative DDF approach computes the exact HDF scores and it is rather fast, requiring most of the times at most two iterations to converge.…”

“…Finally, note that the reduced hyperbolic DEA model (6) is non-linear. However, the iterative DDF-based algorithm of Färe et al (2016) can be appropriately extended to solve (6) using only LP models. Alternatively, a non-linear optimization solver can be used to directly solve (6).…”

“…For completeness and for correctness checking, the extension of the iterative DDF-based algorithm of Färe et al (2016) to this situation is also presented in Appendix B. Table 3 shows the observed inputs and outputs as well as the corresponding GDF target and efficiency score.…”

“…In this paper, the multi-stage methodology is used to enhance the hyperbolic distance function (HDF) proposed in Färe et al (1985). Färe et al (2016) enumerates a number of areas in which HDF has been used. One of the advantages of HDF over other approaches like DDF is that the projection path is based only on the inputs and outputs of the DMU being projected and therefore it does not require subjective information about the projection direction.…”