Final thoughts on Adam Smith and the psychology of probability

I began this series of blog posts on 22 August by asking whether Adam Smith was a closet Bayesian. Today, I draw this series to a close by concluding that Adam Smith was a closet behavioral economist who made several significant contributions to what I like to call the “psychology of probability”. Although Smith’s insights are non-mathematical in nature, they are nevertheless important and original:

LOTTERY METAPHOR

To begin, Adam Smith can be considered the first out of a long line of future Anglo-American philosophers — Rawls 1971, Williams 1981, Taleb 2001, Hawthorne 2004, Binmore 2005, and Stone 2011, just to name a few — who have explored how chance applies to various domains of our lives! On this note, see my posts “Adam Smith’s allegory: the lottery of life” and “Adam Smith on self-deception“.

OPTIMISM BIAS

In addition to initiating an entirely new field of philosophy, the Scottish philosopher-economist made an important contribution to this new field, for he explains how optimism bias clouds and distorts our ability to rationally calculate the expected value of certain types of bets (e.g. choice of profession, lottery prizes, insurance risks). See my posts “Adam Smith: father of behavioral economics” and “Adam Smith on the paradox of insurance“.

RISK-TAKING, CRIME, AND AGE

Smith also identifies a direct connection between age and risk-seeking behavior and correctly concludes that risk-taking is most pronounced among young people, and he also extends his optimism bias model to criminal conduct. See my posts on “Adam Smith on the risks of youth” and “Adam Smith explains why crime does not pay“.

THE “WHO DECIDES?” QUESTION

Last but not least, Smith not only recognizes the role that chance can play in our lives and how our self-confidence can distort our perception of these probabilities; he also highlights (though only in passing) the importance of what I like to call the “who decides?” question. That is, in any given situation, Who is in the best position to calculate what the relevant probabilities are? Who decides? See my post “Politics and probability“.