An increasing interest with maximum entropy estimation in stochastic frontier analysis has recently emerged in the literature. This is largely due to the fact that empirical production frontier models are usually ill-posed and traditional estimation techniques require strong dis- tributional assumptions. A discussion on the role of some maximum entropy estimators in stochastic frontier analysis is accomplished in this seminar. An eco-efficiency analysis of Eu- ropean countries and a benchmarking approach for electricity utility regulation are used to illustrate the performance of maximum entropy and maximum likelihood estimators.
 Macedo, P. and Scotto, M. (2014), Cross-entropy estimation in technical efficiency anal- ysis, Journal of Mathematical Economics, 54, 124–130.
 Macedo, P., Silva, E. and Scotto, M. (2014), Technical efficiency with state-contingent production frontiers using maximum entropy estimators, Journal of Productivity Anal- ysis, 41(1), 131–140.
 Robaina Alves, M., Moutinho, V. and Macedo, P. (2015), A new frontier approach to model the eco-efficiency in European countries, Journal of Cleaner Production, 103, 562– 573.
 Silva, E., Macedo, P. and Soares, I. (2016), An alternative benchmarking approach for electricity utility regulation using maximum entropy, Proceedings of the 13th Interna- tional Conference on the European Energy Market, IEEE, June 06–09, Porto.