Embedding Preference Uncertainty for Environmental Amenities in Climate Change Economic Assessments: A “Random” Step Forward

Michalis Skourtos, Dimitris Damigos, Areti Kontogianni, Christos Tourkolias and Alistair Hunt
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Michalis Skourtos: Department of Agricultural Economics & Rural Development, Agricultural University of Athens, 11855 Athens, Greece
Dimitris Damigos: Department of Mining, National Technical University of Athens, 15780 Zografou, Greece
Areti Kontogianni: Department of Mechanical Engineering, University of Western Macedonia, 50100 Kozani, Greece
Christos Tourkolias: Center for Renewable Energy Sources, 19009 Pikermi, Greece
Alistair Hunt: Department of Economics, University of Bath, Bath BA2 7AY, UK

Economies, 2019, vol. 7, issue 4, 1-22

Abstract: While there is a considerable debate regarding the choice of proper discount rates for assessing climate change projects and policies, only a tiny body of literature emphasizes “what to discount”. Usually, climate change economic assessments rely on tools and methods that employ strong simplifications, assuming, among others, given and fixed preferences about the values of man-made and environmental goods. Aiming to fill a gap in the literature, this paper leaves aside the issue of discounting and focuses on the nature and impact of preference uncertainty on the economic estimates of future climate change damages on ecosystem non-market goods and services. To this end, a general random walk-based stochastic model is proposed, combining a number of parameters, e.g., the growth of income, depletion of environmental assets, the elasticity of income and demand, and the change in preferences towards the environment. The illustrative application of the model shows that the value of environmental losses is significantly affected by the change in preferences. By doing so, the model allows the analyst to visualize future paths of preference evolutions and to bring future values of damaged environmental assets realistically to the fore. If these elements are neglected when estimating climate change-related future damages to environmental goods and services, the results may be too narrow from a policy perspective.

Keywords: future preferences; ecosystem values; random walk modeling; climate change impact assessment (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2019
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