Trends in Post-Judgment Interest Awarded in Investment Arbitration - Journal of Damages in International Arbitration, Vol.4, No.1
Originally from Journal of Damages in International Arbitration
Beyond all the interesting legal discussions related to domestic or international law in investment arbitrations under the aegis of a Bilateral Investment Treaty (BIT) or another relevant treaty, an investment arbitration arose because one party is claiming compensation from another. At the end of the arbitration if a party is found at fault, damages are estimated and a compensation amount from a party to the other is determined. An arbitral tribunal not only determines if there will be an amount of compensation owed to a party, but also decides on how the costs of the arbitration will be shared and establishes a post-judgment interest rate from the date that the amount of compensation is due.
The determination of the right level of post-judgment interest to preserve the value of the amount of compensation that is determined by a tribunal at a specific date and will be paid at a later date must follow basic financial principles. The underlying principle in an award calculation, including discount rates and post-judgment interest, is the time value of money. The time value of money principle means that a dollar today is more valuable than a dollar tomorrow. According to this principle, the purchasing power of a dollar in the past is higher than the purchasing power of that same dollar today.
In this article, we focus on the observed practice in investment arbitration related to the determination of the post-judgment interest rate in arbitration awards by reviewing all available investment arbitrations awards in the International Centre for Settlement of Investment Disputes (ICSID) and the Permanent Court of Arbitration (PCA) websites and from two websites that compile information on investment arbitrations awards of the United Nations Commission on International Trade Law (UNCITRAL). In analyzing all these published awards, we identify commonalities and trends through statistical tabulations.