‘lying with Numbers’ in International Arbitration against States
| DOI | 10.1093/jnlids/idae007 |
| Date | 12 March 2024 |
| Pages | 5-34 |
| Year | 2024 |
| Published By | Oxford University Press |
In late 2023, the High Court of Justice in London ruled that the award in the arbitration case
In the
The picture that emerged from the High Court proceedings was radically different: P&ID had never been anywhere ready to perform, and a P&ID expert witness confirmed that the extent of the company’s preparatory work amounted to no more than one crude hand-drawn sketch.8 And as for the ‘materials’ underlying the DCF model, it turned out that ‘[t]he
The degree to which the P&ID tribunal’s determinations were at variance with the true facts, together with a keen awareness of “how readily the outcome [of Nigeria’s challenge to the award] could have been different”,10 prompted the court to suggest that those involved in international arbitration might wish
to consider whether the arbitration process, which is of outstanding importance and value in the world, needs further attention where the value involved is so large and where a state is involved [… lest] arbitration as a process becomes less reliable, less able to find difficult but important new legal ground, and more vulnerable to fraud.11
This suggestion has been greeted without much enthusiasm by the international arbitration community at large, however, and the sheer egregiousness of abuse of the arbitral process which this case put in evidence has been cited as a good reason why not too much should be read into it: ‘[b]y any standards, the facts of P&ID are extreme. Is it right that such an extreme case should lead to questions being asked of the long-established and well-trusted system of arbitration?’12
The answer to this question is ‘yes’, because the notion that ‘[i]t is best that P&ID …[be] viewed as an exceptional case’13 is untenable in so far as valuation matters are concerned. The sole factor which makes
Taken together, these cases are a testament to the considerable success that ‘the new industry of testifying quantum experts [who] earn their keep, [by] propounding detailed analyses that many lawyers and tribunals are simply untrained to digest’15 has had in turning this digestive inadequacy of lawyers and tribunals into the cornerstone of a lucrative rent-seeking
As JM Keynes observed in the
If we speak frankly, we have to admit that our basis of knowledge for estimating the yield ten years hence of a railway, a copper mine, a textile factory, the goodwill of a patent medicine, an Atlantic liner, a building in the City of London amounts to little and sometimes to nothing; or even five years hence.23
Today, despite exponential increases in computational power relative to Keynes’ time, it remains the case that ‘
Among the many consequences of this precariousness is that while
people can forecast certain events—such as GDP growth, macroeconomic policies, business cycles, technological advances, and geopolitical conflicts—with some accuracy over periods of up to one year … [a]fter that … accuracy declines rapidly, and beyond a time horizon of three to five years, it disappears into the mists of randomness.25
One telling manifestation of the inaccuracy of business forecasting is the poor record of large investment projects in terms of delivering on the expectations held out for them (not least in terms of profitability):
approximately one out of ten megaprojects is on budget, one out of ten is on schedule, and one out of ten delivers the promised benefits … [so] approximately one in one thousand projects is a success, defined as ‘on target’ for all three … This serves to illustrate what may be called the ‘iron law of megaprojects’: Over budget, over time, over and over again. Best practice is an outlier, average practice a disaster.26
Furthermore, as Bent Flyvbjerg noted in a 2022 public hearing about another project gone wrong, this is not a recent phenomenon:
[w]e have data going back more than 80 years. There’s no change in this over the 80 years for which we have data for, which is pretty interesting if you think about it. Most things we do, we get better at over time, but not delivering big projects.27
These sobering empirical findings are grounded on the ‘world’s largest database of its kind, with information regarding sixteen thousand–plus projects’.28 Admittedly, every once in a while, projects do materialize which deliver on all three of schedule, costs and benefits/profits. On the whole, though, these are outliers in the context of a secular trend pointing very much in the wrong direction.
Back in the early 1980s, Martin Wachs looked at the disappointing track record of big project delivery and identified a key factor behind it; namely, that those entrusted with the quantitative spadework for such projects were (to paraphrase Keynes) not prepared to speak frankly about the impact of the ‘precariousness of their knowledge’ on ‘the likelihood of our best forecast turning out quite wrong’.29 Instead, these experts were wont to attach an unwarranted degree of confidence to their estimates. This gave rise to those ‘gaps between...
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