Social Science

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?).

 

 

The Big Man Can't Shoot - Threshold Model

Podcast REVISIONIST HISTORY: ""The Big Man Can't Shoot" - S1 E3

This episode examines Wilt Chamberlain’s 100 point game in 1962 and points out that Wilt (usually a terrible free throw shooter) dramatically improved his free throw performance in this game by using the underhand method (the “granny style” pioneered by Rick Barry in the NBA). Despite the dramatic improvement, Wilt goes back to his standard overhead method soon afterwards and sees his free throw percentage plummet. Why did Wilt go back and why did Barry persist? Gladwell points out that the “granny style” is considered silly or weird or weak by other basketball players. Even though the rational thing to do would be (like Barry) to adopt the more effective underhand method, players do not because they perceive it to be weird, weak and - most importantly, no one else is doing it.

This leads to a discussion of sociologist Granovetter’s threshold model: (from Wikipedia): “the “threshold” is “the number or proportion of others who must make one decision before a given actor does so”. It is necessary to emphasize the determinants of threshold. A threshold is different for individuals, and it may be influenced by many factors: social economic status, education, age, personality, etc. Further, Granovetter relates “threshold” with utility one gets from participating collective behavior or not, using the utility function, each individual will calculate his cost and benefit from undertaking an action. And situation may change the cost and benefit of the behavior, so threshold is situation-specific. The distribution of the thresholds determines the outcome of the aggregate behavior (for example, public opinion).” So Wilt had a high threshold for freethrow shooting style, meaning he needed to see lots of other players go underhand before he would switch. Barry had a lower threshold for this activity.

Here’s the Granovetter paper.

This problem extends into other fields like football where Thaler has shown how first round draft picks are consistently overvalued yet owners continue to trade up for them whenever possible.