Imperfect Knowledge

My remarks today will be focused primarily on features of the developed world’s financial system which led to the crisis of 2008 and to the Great Recession that followed, from which we are only slowly and painfully emerging.

In his recent lecture at the Cass Business School, Lord Turner noted that even mentioning the possibility of overt monetary financing was akin to breaking a taboo.

This essay critically evaluates the benefits and costs of the dominant methodology in macroeconomics, the DSGE approach. Although the approach has led to great progress in some areas, it has also created biases and blind spots in the profession that hold back our understanding and our ability to govern the macroeconomy. There is great scope for progress in macroeconomics by judiciously pushing the boundaries of some of the methodological restrictions imposed by the DSGE approach.

Economists discussing the problem of radical uncertainty commonly invoke Frank Knight’s classic definition in Risk, Uncertainty and Profit, but only rarely venture to explore the broader contours of his argument.

We discuss recent work on bounded rationality and learning in relation to Soros’ principle of reflexivity and stress the empirical importance of non-rational, almost self-fulfilling equilibria in positive feedback systems.

This chapter surveys experimental research on networks in economics.

US Military needs during the Cold War induced a mathematical modeling of rational allocation and control processes while simultaneously binding that rationality with computational reality. Modeling strategies to map the optimal to the operational ensued and eventually became a driving force in the development of macroeconomic dynamics.

Tania Singer on the key importance of understanding preferences and behavioral change.

The financial crisis of 2008 was unforeseen to a significant extent. One reason is that the dominant academic theories influencing political decision makers ignore recent advances and instead rely largely on models and decision science dating back to the Second World War.

We call attention to the class of models that serve as the foundation for the rational expectations hypothesis (REH). Models in this class rule out completely any structural change that cannot be fully anticipated with a probabilistic or other quantitative rule. REH models are abstractions of rational decision-making, but only in a hypothetical world in which participants can fully anticipate when and how they might revise their understanding of the process driving outcomes.