Risk Problems Identifying Optimal Pollution Level

  • George E. HalkosEmail author
  • Dimitra C. Kitsou
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 136)


The determination of the optimal pollution level is essential in Environmental Economics. The associated risk in evaluating this optimal pollution level and the related Benefit Area (BA), is based on various factors. At the same time the uncertainty in the model fitting can be reduced by choosing the appropriate approximations for the abatement and damage marginal cost functions. The target of this paper is to identify analytically and empirically the Benefit Area (BA) in the case of quadratic marginal damage and linear marginal abatement cost functions, extending the work of (Halkos and Kitsos, Appl. Econ. 37:1475–1483, 2005, [9]).


Optimal pollution level Risk Benefit area 



This research has been co-financed by the European Union (European Social Fund ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF) - Research Funding Program: Heracleitus II. Investing in knowledge society through the European Social Fund. D.K would like to express its gratitude to Heracleitus II for the financial support.

Thanks are also due to three anonymous reviewers for their helpful and constructive comments in an earlier draft of our paper as well as to the participants in the 5th International Conference on Risk Analysis (Biomedicine, Environmetrics, Economics, Finance & Reliability) in the Polytechnic Institute at Tomar, Portugal (30 May-1 June 2013) for their encouraging comments.

An extended version of this presentation with the consideration of all combinations of linear, quadratic and exponential abatement and damage cost functions as well as the relation to the existing relative literature can be fount in [10].


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Economics (Laboratory of Operations Research)University of ThessalyVolosGreece

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