Behavioural economics

Behavioral economics studies the effects of psychological, cognitive, emotional, cultural and social factors in the decisions of individuals or institutions, and how these decisions deviate from those implied by classical economic theory. Behavioral economics is primarily concerned with the bounds of rationality of economic agents. Behavioral models typically integrate insights from psychology, neuroscience and microeconomic theory. The study of behavioral economics includes how market decisions are made and the mechanisms that drive public opinion. Behavioral economics began as a distinct field of study in the 1970s and '80s, but can be traced back to 18th-century economists, such as Adam Smith, who deliberated how the economic behavior of individuals could be influenced by their desires. The status of behavioral economics as a subfield of economics is a fairly recent development; the breakthroughs that laid the foundation for it were published through the last three decades of the 20th century. Behavioral economics is still growing as a field, being used increasingly in research and in teaching. Early classical economists included psychological reasoning in much of their writing, though psychology at the time was not a recognized field of study. In The Theory of Moral Sentiments, Adam Smith wrote on concepts later popularized by modern Behavioral Economic theory, such as loss aversion. Jeremy Bentham, a Utilitarian philosopher in the 1700s conceptualized utility as a product of psychology. Other economists who incorporated psychological explanations in their works included Francis Edgeworth, Vilfredo Pareto and Irving Fisher. A rejection and elimination of psychology from economics in the early 1900s brought on a period defined by a reliance on empiricism. There was a lack of confidence in hedonic theories, which saw pursuance of maximum benefit as an essential aspect in understanding human economic behavior. Hedonic analysis had shown little success in predicting human behavior, leading many to question its viability as a reliable source for prediction.