The Economic Analysis of Random Events: Economic Perspectives on Probability Theory, Statistical Inference and the Nature of Chance

This book investigates applications of probability theory to random events from an economic standpoint and considers how economics can deal with uncertainty in today's world. As such the nature of chance and probability will be discussed with examples taken from the theoretical literature in probability and the history of economic thought, as well as real-life events.
Chapters cover the nature of randomness and the element of chance, the concepts of both hidden costs and opportunity costs, the economic effect of human action, the randomness of economic events, random walk hypotheses and observable and unobservable phenomena. It situates the discussion in John Maynard Keynes' and Ronald Fisher's seminal works on probability, as well as introducing key tenets of probability theory and how these can be applied to economic events. The book considers the relationship between artificial intelligence and economic events, the role of big data, and international examples from different economic systems and how these can be evaluated. It also introduces a multidisciplinary exploration of other social sciences and how they deal with uncertainty, to assess the extent to which it is possible to apply probability theory to economic events which are by nature erratic and uncertain.

This book will be of interest to researchers and students in economics, statistics, and those in the social sciences interested in questions of randomness and chance.