Social Science

Motivated reasoning 6/10/17

Source: "Free exchange: How to be wrong"           

Human thought is not always (or even usually) rational. Humans don’t use new information to update their beliefs - instead, they cling to their beliefs in the face of contradictory evidence. Jean Tirole and Roland Benabou wrote a landmark paper in 2016 that looks at beliefs as consumption goods. This new perspective yields interesting insights and predictions.

Beliefs are goods, in the sense that people spend resources acquiring them and developing them and they derive value and benefits from their beliefs. A typical value involves signaling membership in a group. A less common belief value would be the way believing in a religion can shape your behavior (if I believe I am a good salesman, I can use the confidence generated by my belief to close more sales; if I accept an ascetic religion, my beliefs can help me avoid unhealthy behaviors).

Benabou and Tirole believe people engage in motivated reasoning to protect their hard-won beliefs from contradictory evidence. The first stage of motivated reasoning is strategic ignorance: here, the believer simply ignores the evidence. In stage two, reality denial, the believer acknowledges the new evidence but refuses to accept it as coming from a credible source. Finally, in self-signalling, the evidence is accepted as credible but the believer interprets it as actually strengthening their belief, not contradicting it (example: an unhealthy person might decide that their ability to still run a few miles is proof that they are indeed healthy).

Other work by Benabou suggests that “groupthink” is highest when people within a group share the same fate if their briefs are discredited. If a politicians fortunes are linked to his party’s performance, they will have little incentive to speak out against the group. Such groups become partisan and polarized. Such groups try to delegitimize independent voices (like research groups or watchdog groups).

Book review: Everybody Lies 5/27/17

Article (book review): Everybody Lies  

 The book Everybody Lies by Seth Stephens-Davidowitz looks at the use of search data as a way to find previously invisible correlations and connections. Example: the prevalence of the term “n*gger” in search results was the best variable in predicting whether or not the voters in that region would vote for Trump in the 2016 GOP primaries. Search data is a game-changer because it gets at what people actually believe, not what they are willing to admit to a stranger with a clipboard.

From the review: ‘Modern microeconomics, sociology, political science and quantitative psychology all depend to a large extent on surveys of at most a few thousand respondents. In contrast, he says, there are “four unique powers of Big Data”: it provides new sources of information, such as pornographic searches; it captures what people actually do or think, rather than what they choose to tell pollsters; it enables researchers to home in on and compare demographic or geographic subsets; and it allows for speedy randomized controlled trials that demonstrate not just correlation but causality. As a result, he predicts, “the days of academics devoting months to recruiting a small number of undergraduates to perform a single test will come to an end.” In their place, “the social and behavioural sciences are most definitely going to scale,” and the conclusions researchers will be able to reach are “the stuff of science, not pseudoscience”.’

Governments embrace behavioral economics 5/20/17

Article: "When nudge comes to shove   

 The Behavioral Insights Team was created by the British government under the advisement of economist Richard Thaler in 2010. (Thaler, along with Cass Sunstein wrote Nudge in 2008). Its mission was to use psychology and behavioral economics to modify government policy and “nudge” people towards better outcomes. For example, organ donation might become opt-out instead of opt-in (the default becomes the desired behavior). Such a small tweak can greatly increase opt-in rates. In the case of the BIT, if they failed to return in savings ten times their operating budget, they would be disbanded. Instead, they returned savings equivalent to twenty times their annual budget.

> Other examples: connecting the FAFSA website for student loans to the IRS website allows FAFSA applications to be pre-filled. This has increased successful applications by 25%.

> Asking voters to write down when they plan to vote increases voter turnout - not just in the upcoming election, but in all subsequent elections.

> “Nudging” can be weaponized. North Carolina enacted a suite of laws (voter ID, reduced polling times, no voting outside of your precinct etc.) all designed to make voting more difficult for low-income voters. It depressed turnout. Fortunately, these laws were found to be unconstitutional in 2016.

 

Carlos Doesn't Remember - American Meritocracy

Podcast REVISIONIST HISTORY: ""Carlos Doesn't Remember" - S1 E4

Here we are looking at the widespread belief that America is a meritocracy, that our capitalization rates (the number of people who achieve their full potential) are very high. Gladwell believes they are very low. Carlos is an example: a high-achieving student from a poor family, he is unable to go to Choate because of his mother going to jail. Gladwell argues that poor kids just don’t get as many chances as their wealthier classmates do. One mistake, one misstep and they are finished.

Evidence: Harvard makes itself essentially free to any poor child who can qualify. Fewer than 15 a year take them up on it. Hoxby study shows that there are 35,000 children per year who come from poor families and score in the top ten percent of all SAT/ACT testers. Gladwell believes that this number is low (how many smart but poor kids drop out or lose interest in school after puberty?).