Optimism Bias
http://seekingalpha.com/article/3984796-optimism-bias?page=1
In this June 28th, 2016 article, the author examines the the role of optimism bias and other psychological factors of behavioral economics. The scope of this article zooms in on two events: Leicester City Football Club shocking the world by claiming the English Premier League Title and the United Kingdom’s referendum vote in which 51.9% of voters elected to withdraw from the European Union. However, in more recent times the concept could never be more relevant as just days ago the concept of optimism bias shocked American media and pollsters when Donald Trump became the 45th President-elect of the United States. But what many still do not understand is what exactly happened? How was everyone so off in their predictions of huge political events? The answer to this question lies in chapter 16 of Professor Easly and Professor Kleinberg’s book “Networks, Crowds, and Markets: Reasoning about a Highly Connected World” in which they discuss information cascades.
The article cites herd mentality, information cascades, and optimism bias as the three key behavioral concepts to understanding how everyone could go wrong so many times. However, I would argue that each example cited in the article is just a variation or effect of information cascades. The herd mentality is described in the article as “People are influenced by their peers to adopt certain behaviors, follow trends, and/or purchase items.” This is seen frequently in media and pollsters. No one wants to report falsely. This causes the organization to lose credibility and viewership. As an effect, some pollsters have been known to alter their “methodology” in the event that their results differ from the aggregate. This summer, Reuters/Ipsos changed their method after a 17 point swing in favor of Trump. This is the same concept illustrated in problem four of problem set six. Reuters thought that other polls had better information and made a change. This leads to the second topic, and creates an information cascade. Just a week ago people mocked Adam Silver and fivethirtyeight for having Donald Trump so high in the polls, but on November 9th, they were hailed as the most accurate. Had they been wrong, they would be a laughing stock, and just like Brexit, almost everyone else reported against it. This creates a scenario where reporting cold hard facts may be acting against the cascade, but as the book notes so tersely, “cascades can be wrong.” The last behavior, optimism bias can be particularly damaging in elections. Optimism bias and information cascades differ, though as the author argues, information cascades often trigger optimism bias. This concept particularly hurt Hillary Clinton. This psychological concept is defined as the event when, “Many tend to overestimate the likelihood of positive events, and underestimate the likelihood of negative events.” Because of the information cascade from media and polls, everyone had thought that Hillary Clinton would win and the UK would remain in the EU. Though, this is textbook optimism bias which led millions to not vote. Why vote in Pennsylvania? Clinton was up 11 points they day before the election. Many political scientists are citing areas that Clinton won as the beginning of her demise. This is because even the counties clinton won, the voter turnout was so low, it failed to balance other areas in the state. CNN reports that this election cycle was the lowest voter turnout in 20 years.
The article advocates for extreme measures to protect against optimism bias. He claims that had there been a “pessimism bias”, campaign officials may have locked up enough votes to sway the election. In decision making one should always choose a rational method, and sometimes following a cascade is statistically rational. The author however, remains weary and prefers his own information.