andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-709 knowledge-graph by maker-knowledge-mining
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Introduction: I followed a link from Tyler Cowen to this bit by Daniel Kahneman: Education is an important determinant of income — one of the most important — but it is less important than most people think. If everyone had the same education, the inequality of income would be reduced by less than 10%. When you focus on education you neglect the myriad other factors that determine income. The differences of income among people who have the same education are huge. I think I know what he’s saying–if you regress income on education and other factors, and then you take education out of the model, R-squared decreases by 10%. Or something like that. Not necessarily R-squared, maybe you fit the big model, then get predictions for everyone putting in the mean value for education and look at the sd of incomes or the Gini index or whatever. Or something else along those lines. My problem is with the counterfactual: “If everyone had the same education . . .” I have a couple problems with this
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1 I followed a link from Tyler Cowen to this bit by Daniel Kahneman: Education is an important determinant of income — one of the most important — but it is less important than most people think. [sent-1, score-0.703]
2 If everyone had the same education, the inequality of income would be reduced by less than 10%. [sent-2, score-0.811]
3 When you focus on education you neglect the myriad other factors that determine income. [sent-3, score-1.072]
4 The differences of income among people who have the same education are huge. [sent-4, score-0.905]
5 I think I know what he’s saying–if you regress income on education and other factors, and then you take education out of the model, R-squared decreases by 10%. [sent-5, score-1.741]
6 Not necessarily R-squared, maybe you fit the big model, then get predictions for everyone putting in the mean value for education and look at the sd of incomes or the Gini index or whatever. [sent-7, score-1.142]
7 My problem is with the counterfactual: “If everyone had the same education . [sent-9, score-0.922]
8 First, if everyone had the same education, we’d have a much different world and I don’t see why the regressions on which he’s relying would still be valid. [sent-13, score-0.45]
9 Second, is it even possible for everyone to have the same education? [sent-14, score-0.381]
10 I don’t think it’s possible for everyone to do this. [sent-16, score-0.441]
11 Setting aside budgetary constraints, I don’t think that most college-age kids could handle the MIT physics curriculum (nor do I think I could handle, for example, the courses at a top-ranked music or art college). [sent-17, score-0.931]
12 I suppose you could imagine everyone having the same number of years of education, but that seems like a different thing entirely. [sent-18, score-0.377]
13 As noted, I think I see what Kahneman is getting at–income is determined by lots of other factors than education–but I’m a bit disappointed that he could be so casual with the causality. [sent-19, score-0.495]
14 And without the causal punch, his statement doesn’t seem so impressive to me. [sent-20, score-0.06]
15 Everybody knows that education doesn’t determine income, right? [sent-21, score-0.828]
16 Bill Gates never completed college, and everybody knows the story of humanities graduates who can’t find a job. [sent-22, score-0.468]
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Introduction: I followed a link from Tyler Cowen to this bit by Daniel Kahneman: Education is an important determinant of income — one of the most important — but it is less important than most people think. If everyone had the same education, the inequality of income would be reduced by less than 10%. When you focus on education you neglect the myriad other factors that determine income. The differences of income among people who have the same education are huge. I think I know what he’s saying–if you regress income on education and other factors, and then you take education out of the model, R-squared decreases by 10%. Or something like that. Not necessarily R-squared, maybe you fit the big model, then get predictions for everyone putting in the mean value for education and look at the sd of incomes or the Gini index or whatever. Or something else along those lines. My problem is with the counterfactual: “If everyone had the same education . . .” I have a couple problems with this
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Introduction: These are based on raw Pew data, reweighted to adjust for voter turnout by state, income, and ethnicity. No modeling of vote on age, education, and ethnicity. I think our future estimates based on the 9-way model will be better, but these are basically OK, I think. All but six of the dots in the graph are based on sample sizes greater than 30. I published these last year but they’re still relevant, I think. There’s lots of confusion when it comes to education and voting.
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Introduction: Within any education category, richer people vote more Republican. In contrast, the pattern of education and voting is nonlinear. High school graduates are more Republican than non-HS grads, but after that, the groups with more education tend to vote more Democratic. At the very highest education level tabulated in the survey, voters with post-graduate degrees lean toward the Democrats. Except for the rich post-graduates; they are split 50-50 between the parties. What does this say about America’s elites? If you define elites as high-income non-Hispanic whites, the elites vote strongly Republican. If you define elites as college-educated high-income whites, they vote moderately Republican. There is no plausible way based on these data in which elites can be considered a Democratic voting bloc. To create a group of strongly Democratic-leaning elite whites using these graphs, you would need to consider only postgraduates (no simple college grads included, even if they have achieved s
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Introduction: Tyler Cowen points to this news article by Lauren Sandler: Stunningly, the postponement of marriage and parenting — the factors that shrink the birth rate — is the very best predictor of a person’s politics in the United States, over even income and education levels, a Belgian demographer named Ron Lesthaeghe [and coauthor Lisa Neidert] has discovered . Larger family size in America correlates to early marriage and childbirth, lower women’s employment, and opposition to gay rights — all social factors that lead voters to see red. All the analysis in the linked paper is at the state and county level. That’s fine but this is not going to tell you what is a “predictor of a person’s politics.” Cowen labels his post “Sentences to ponder,” and what I want to ponder is that people are so quick to jump from aggregate to individual patterns. And, yes, I know that aggregate patterns are related to individual patterns but they’re not the same. In particular, from the evidence we’
Introduction: While visiting the education school at the University of Pennsylvania a couple months ago, I had a long conversation with Bob Boruch, a prominent researcher in the field of evidence-based education. We shared Fred Mosteller stories and talked about a lot of other things too. Boruch sent me an article about teaching randomized controlled trials to education students, which gave me the following idea which connects to my longstanding embarrassment (and subject of my next column on ethics, forthcoming in Chance magazine) about the lack of systematic measurement, sampling, or experimentation in our own teaching efforts. Anyway, here’s my idea for experimentation in statistics teaching, an idea that I think could work particularly well in classes with education students. Each class could, as part of the course, design an educational experiment to be performed on next year’s class. Easier said than done, I know, but perhaps ed school students would be particularly motivated to do t
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