European Journal of Law and Economics

, Volume 41, Issue 3, pp 621–639 | Cite as

Measuring gross disproportion in environmental precaution to establish regulatory expropriation and quantum of compensation in international investment arbitration

  • David Collins
  • Philip Thomas


This article applies a new methodology for the assessment of environmental risk prevention expenditure to the adjudication process of international investment arbitration. The Disproportion Factor Model can be implemented by investment arbitration tribunals to evaluate the reasonableness of environmental regulations imposed by host states that have a damaging impact upon foreign investment activity, such as would be the subject for a claim of indirect or regulatory expropriation. In this setting the Disproportion Factor Model can help illustrate whether a host state measure is unreasonable and in that sense should engage the investor’s entitlement to compensation under international law. It also acts as an objective guide to the setting of an appropriate quantum of compensation for the injured investor by reference to the environmental benefits that the regulation aimed to achieve relative to their costs, as evaluated by a rational decision-maker. The formula should be consequently viewed as a useful tool in judicial analysis by international investment tribunals.


Risk Cost benefit analysis International investment law International arbitration Investor state dispute settlement Judicial decision making Environmental damage Safety precaution 

JEL Classification

K330 K410 



The authors acknowledge gratefully the support of the Engineering and Physical Sciences Research Council (EPSRC). The views expressed in the paper are those of the authors and not necessarily those of the NREFS project. The authors would like to thank Dr Ian Waddington (Ross Technologies Ltd.) for assistance with calculations.

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.City Law SchoolCity University LondonLondonUK
  2. 2.Systems Analytics Group, School of Engineering and Mathematical SciencesCity University LondonLondonUK

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