Fig. 1. By-production representation with two sub-technologies, one for the good output (Ty) and one for the bad output (Tb). From: Greenhouse gas emissions.

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Presentation transcript:

Fig. 1. By-production representation with two sub-technologies, one for the good output (Ty) and one for the bad output (Tb). From: Greenhouse gas emissions and efficiency in French sheep meat farming: A non-parametric framework of pollution-adjusted technologies Eur Rev Agric Econ. 2016;44(1):33-65. doi:10.1093/erae/jbw013 Eur Rev Agric Econ | © Oxford University Press and Foundation for the European Review of Agricultural Economics 2016; all rights reserved. For permissions, please email journals.permissions@oup.com

Fig. 3. Evolution of yearly averages of pollution adjusted efficiency and its components. From: Greenhouse gas emissions and efficiency in French sheep meat farming: A non-parametric framework of pollution-adjusted technologies Eur Rev Agric Econ. 2016;44(1):33-65. doi:10.1093/erae/jbw013 Eur Rev Agric Econ | © Oxford University Press and Foundation for the European Review of Agricultural Economics 2016; all rights reserved. For permissions, please email journals.permissions@oup.com

Fig. 4. Evolution of yearly averages of good and bad outputs efficiency. From: Greenhouse gas emissions and efficiency in French sheep meat farming: A non-parametric framework of pollution-adjusted technologies Eur Rev Agric Econ. 2016;44(1):33-65. doi:10.1093/erae/jbw013 Eur Rev Agric Econ | © Oxford University Press and Foundation for the European Review of Agricultural Economics 2016; all rights reserved. For permissions, please email journals.permissions@oup.com

Fig. 2. Distributions of bad and good outputs efficiency and pollution-adjusted efficiency (1987–2013). From: Greenhouse gas emissions and efficiency in French sheep meat farming: A non-parametric framework of pollution-adjusted technologies Eur Rev Agric Econ. 2016;44(1):33-65. doi:10.1093/erae/jbw013 Eur Rev Agric Econ | © Oxford University Press and Foundation for the European Review of Agricultural Economics 2016; all rights reserved. For permissions, please email journals.permissions@oup.com

Fig. A1. Evolution of yearly averages of polluting inputs. From: Greenhouse gas emissions and efficiency in French sheep meat farming: A non-parametric framework of pollution-adjusted technologies Eur Rev Agric Econ. 2016;44(1):33-65. doi:10.1093/erae/jbw013 Eur Rev Agric Econ | © Oxford University Press and Foundation for the European Review of Agricultural Economics 2016; all rights reserved. For permissions, please email journals.permissions@oup.com

Fig. A2. Evolution of yearly averages of efficiency of each GHG under assumption A4E in equation (4). From: Greenhouse gas emissions and efficiency in French sheep meat farming: A non-parametric framework of pollution-adjusted technologies Eur Rev Agric Econ. 2016;44(1):33-65. doi:10.1093/erae/jbw013 Eur Rev Agric Econ | © Oxford University Press and Foundation for the European Review of Agricultural Economics 2016; all rights reserved. For permissions, please email journals.permissions@oup.com

Fig. 5. Evolution of yearly averages of shadow price minimums and maximums for each GHG and all GHG taken together. From: Greenhouse gas emissions and efficiency in French sheep meat farming: A non-parametric framework of pollution-adjusted technologies Eur Rev Agric Econ. 2016;44(1):33-65. doi:10.1093/erae/jbw013 Eur Rev Agric Econ | © Oxford University Press and Foundation for the European Review of Agricultural Economics 2016; all rights reserved. For permissions, please email journals.permissions@oup.com