A longstanding belief in the predictability of market behavior and outcomes has created plenty of fodder for academic theorizing in economics. But firms operating in the real world succeed by recognizing that the future is unknowable – and acting accordingly.
CAMBRIDGE – A central premise of neoclassical economics is that the consequences of the decisions of market participants can be known in advance and quantified as risk-adjusted estimates. As John Kay and Mervyn King showed in their 2020 book, Radical Uncertainty: Decision-Making Beyond the Numbers, such probabilistic reasoning has a long history. As applied in economics, it has operationalized the concept of “expected utility” – the desideratum that rational economic agents are defined to be maximizing.
As the author of a major analysis of the stock market sponsored by the British government (Kay) and a former governor of the Bank of England (King), both men are well equipped to examine the complex interaction between financial markets and markets for “real” things (goods, services, labor, patents, and so forth). In doing so, they have challenged the statistical methodologies and ontological assumptions that lead economists to regard the future as measurable and manageable.
Managing Expectations
From John Maynard Keynes at the University of Cambridge 90 years ago through Robert Lucas at the University of Chicago in the mid-twentieth century, economists have placed expectations at the core of market dynamics. But they differ on how expectations are formed. Are the data we observe the outcome of processes that are as “stationary” as physical laws, like those determining the properties of light and gravity? Or do the social processes that animate markets render future outcomes radically uncertain?
CAMBRIDGE – A central premise of neoclassical economics is that the consequences of the decisions of market participants can be known in advance and quantified as risk-adjusted estimates. As John Kay and Mervyn King showed in their 2020 book, Radical Uncertainty: Decision-Making Beyond the Numbers, such probabilistic reasoning has a long history. As applied in economics, it has operationalized the concept of “expected utility” – the desideratum that rational economic agents are defined to be maximizing.
As the author of a major analysis of the stock market sponsored by the British government (Kay) and a former governor of the Bank of England (King), both men are well equipped to examine the complex interaction between financial markets and markets for “real” things (goods, services, labor, patents, and so forth). In doing so, they have challenged the statistical methodologies and ontological assumptions that lead economists to regard the future as measurable and manageable.
Managing Expectations
From John Maynard Keynes at the University of Cambridge 90 years ago through Robert Lucas at the University of Chicago in the mid-twentieth century, economists have placed expectations at the core of market dynamics. But they differ on how expectations are formed. Are the data we observe the outcome of processes that are as “stationary” as physical laws, like those determining the properties of light and gravity? Or do the social processes that animate markets render future outcomes radically uncertain?