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Policing carbon markets

Calel, Raphael, Dechezlepretre, Antoine and Venmans, Frank ORCID: 0000-0002-4264-6606 (2023) Policing carbon markets. Grantham Research Institute on Climate Change and the Environment Working Paper (400). Grantham Research Institute on Climate Change and the Environment, London School of Economics and Political Science, London, UK.

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Abstract

Carbon markets have emerged in recent decades as one of the most important tools for curbing industrial greenhouse gas emissions, but they present a number of novel enforcement challenges as compared to more conventional pollution regulations—new regulators with narrow authority, lack of legal precedent, and more. To shed light on the practical issues involved in policing carbon markets, we present the first comprehensive analysis of the EU Emissions Trading System, a single program that was policed by 31 different national regulators. We find generally high rates of compliance coupled with low rates of enforcement, a pattern that is known in the literature as ‘Harrington’s paradox.’ Variation in the probability and severity of fines explain just one tenth of the variation in compliance rates. Meanwhile, other enforcement strategies that have been pointed to as resolutions to Harrington’s paradox in other applications, such as ‘naming and shaming,’ appear to have had little discernible effect.

Item Type: Monograph (Working Paper)
Official URL: https://www.lse.ac.uk/granthaminstitute/publicatio...
Additional Information: © 2023 The Author(s)
Divisions: Grantham Research Institute
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
H Social Sciences > HC Economic History and Conditions
JEL classification: Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics > Q5 - Environmental Economics > Q50 - General
Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics > Q5 - Environmental Economics > Q52 - Pollution Control Costs; Distributional Effects; Employment Effects
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods
Date Deposited: 30 Oct 2023 14:36
Last Modified: 14 Sep 2024 04:39
URI: http://eprints.lse.ac.uk/id/eprint/120565

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