Dr. William H. Janeway, Vice Chairman, Warburg Pincus, received his doctorate in economics from Cambridge University where he was a Marshall Scholar. He was Valedictorian of the Class of 1965 at Princeton University. Prior to joining Warburg Pincus in 1988, where he was responsible for building the Information Technology practice, he was Executive Vice President and Director at Eberstadt Fleming. Dr. Janeway is a director of BEA Systems, Manugistics, Scansoft and UGS. He is also a member of the board of directors of the Social Science Research Council and a member of the board of Trustees of Cambridge in America, University of Cambridge. He is a Founder Member of the Board of Managers of the Cambridge Endowment for Research in Finance (CERF).
“…there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns—the ones we don’t know we don’t know.”—Donald Rumsfeld
“Ah, what a dusty answer gets the soul, When hot for certainties in this our life”—George Meredith
Donald Rumsfeld’s characteristically idiosyncratic gloss on George Meredith’s existential meditation attracted derision across many constituencies. But Rumsfeld summarized a way of structuring our understanding of the world that has profound and immediate relevance. Most particularly, over the past generation, the application of increasingly powerful and sophisticated computerized statistical analysis has interacted with the work of theoreticians of finance to transform the capital markets in the U.S. and around the world. Our mastery of “known unknowns”—i.e., well-defined probabilities—has increased enormously, transformationally. The measurement and management of “risk” has become a major concern of all financial institutions and their regulators, especially since the collapse of Long Term Capital Management (LTCM) in 1998. At the same time, proposals to privatize Social Security and, more generally, to rely on “risk-managed” financial markets for economic security find their theoretical rationalization in the teachings of “modern” finance. And yet, as Rumsfeld and Meredith assert in their very different ways, there is another category of the world’s possible outcomes that lies beyond the reach of modern, market-based, risk management techniques.
More than eighty years ago, Frank Knight set out to parse the difference between risk and uncertainty and the significance of that difference. In Risk, Uncertainty and Profit, Knight distinguished between three different types of probability, which he termed: “a priori probability”; “statistical probability” and “estimates”. The first type “is on the same logical plane as the propositions of mathematics”; the canonical example is the odds of rolling any number on a die. “Statistical probability” depends upon the “empirical evaluation of the frequency of association between predicates” and on “the empirical classification of instances”. When “there is no valid basis of any kind for classifying instances”, only “estimates” can be made.1 In contemporary Bayesian parlance, in the first case, the probability distribution of the prior and all its moments are known definitionally; in the second case they are specified by statistical analysis of well-defined empirical data; in the third case such data as exists do not lend themselves to statistical analysis. Continue reading