andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-649 knowledge-graph by maker-knowledge-mining
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Introduction: Some thoughts on the implausibility of Paul Ryan’s 2.8% unemployment forecast. Some general issues arise. P.S. Yes, Democrats also have been known to promote optimistic forecasts!
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same-blog 1 1.0 649 andrew gelman stats-2011-04-05-Internal and external forecasting
Introduction: Some thoughts on the implausibility of Paul Ryan’s 2.8% unemployment forecast. Some general issues arise. P.S. Yes, Democrats also have been known to promote optimistic forecasts!
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Introduction: Bob Erikson, one of my colleagues at Columbia who knows much more about American politics than I do, sent in the following screed. I’ll post Bob’s note, followed by my comments. Bob writes: Monday morning many of us were startled by the following headline: White House strenuously denies NYT report that it is considering getting aggressive about winning the midterm elections. At first I [Bob] thought I was reading the Onion, but no, it was a sarcastic comment on the blog Talking Points Memo. But the gist of the headline appears to be correct. Indeed, the New York Times reported that White House advisers denied that a national ad campaign was being planned. ‘There’s been no discussion of such a thing at the White House’ What do we make of this? Is there some hidden downside to actually running a national campaign? Of course, money spent nationally is not spent on targeted local campaigns. But that is always the case. What explains the Democrats’ trepidation abou
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Introduction: I was recently rereading and enjoying Bill James’s Historical Baseball Abstract (the second edition, from 2001). But even the Master is not perfect. Here he is, in the context of the all-time 20th-greatest shortstop (in his reckoning): Are athletes special people? In general, no, but occasionally, yes. Johnny Pesky at 75 was trim, youthful, optimistic, and practically exploding with energy. You rarely meet anybody like that who isn’t an ex-athlete–and that makes athletes seem special. [italics in the original] Hey, I’ve met 75-year-olds like that–and none of them are ex-athletes! That’s probably because I don’t know a lot of ex-athletes. But Bill James . . . he knows a lot of athletes. He went to the bathroom with Tim Raines once! The most I can say is that I saw Rickey Henderson steal a couple bases when he was playing against the Orioles once. Cognitive psychologists talk about the base-rate fallacy , which is the mistake of estimating probabilities without accou
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Introduction: Nick Obradovich saw our graphs and regressions showing that the most popular governors tended to come from small states and suggested looking at unemployment rates. (I’d used change in per-capita income as my economic predictor, following the usual practice in political science.) Here’s the graph that got things started: And here’s what Obradovich wrote: It seems that average unemployment rate is more strongly negatively correlated with positive governor approval ratings than is population. The unemployment rate and state size is positively correlated. Anyway, when I include state unemployment rate in the regressions, it pulls the significance away from state population. I do economic data work much of the day, so when I read your post this morning and looked at your charts, state unemployment rates jumped right out at me as a potential confound. I passed this suggestion on to Hanfei, who ran some regressions: lm (popularity ~ c.log.statepop + c.unemployment)
5 0.10189509 2343 andrew gelman stats-2014-05-22-Big Data needs Big Model
Introduction: Gary Marcus and Ernest Davis wrote this useful news article on the promise and limitations of “big data.” And let me add this related point: Big data are typically not random samples, hence the need for “big model” to map from sample to population. Here’s an example (with Wei Wang, David Rothschild, and Sharad Goel): Election forecasts have traditionally been based on representative polls, in which randomly sampled individuals are asked for whom they intend to vote. While representative polling has historically proven to be quite effective, it comes at considerable financial and time costs. Moreover, as response rates have declined over the past several decades, the statistical ben- efits of representative sampling have diminished. In this paper, we show that with proper statistical adjustment, non-representative polls can be used to generate accurate election forecasts, and often faster and at less expense than traditional survey methods. We demon- strate this approach
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Introduction: Some thoughts on the implausibility of Paul Ryan’s 2.8% unemployment forecast. Some general issues arise. P.S. Yes, Democrats also have been known to promote optimistic forecasts!
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Introduction: Bob Erikson, one of my colleagues at Columbia who knows much more about American politics than I do, sent in the following screed. I’ll post Bob’s note, followed by my comments. Bob writes: Monday morning many of us were startled by the following headline: White House strenuously denies NYT report that it is considering getting aggressive about winning the midterm elections. At first I [Bob] thought I was reading the Onion, but no, it was a sarcastic comment on the blog Talking Points Memo. But the gist of the headline appears to be correct. Indeed, the New York Times reported that White House advisers denied that a national ad campaign was being planned. ‘There’s been no discussion of such a thing at the White House’ What do we make of this? Is there some hidden downside to actually running a national campaign? Of course, money spent nationally is not spent on targeted local campaigns. But that is always the case. What explains the Democrats’ trepidation abou
Introduction: A few years ago Larry Bartels presented this graph, a version of which latter appeared in his book Unequal Democracy: Larry looked at the data in a number of ways, and the evidence seemed convincing that, at least in the short term, the Democrats were better than Republicans for the economy. This is consistent with Democrats’ general policies of lowering unemployment, as compared to Republicans lowering inflation, and, by comparing first-term to second-term presidents, he found that the result couldn’t simply be explained as a rebound or alternation pattern. The question then arose, why have the Republicans won so many elections? Why aren’t the Democrats consistently dominating? Non-economic issues are part of the story, of course, but lots of evidence shows the economy to be a key concern for voters, so it’s still hard to see how, with a pattern such as shown above, the Republicans could keep winning. Larry had some explanations, largely having to do with timing: under De
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Introduction: Political campaigns are commonly understood as random walks, during which, at any point in time, the level of support for any party or candidate is equally likely to go up or down. Each shift in the polls is then interpreted as the result of some combination of news and campaign strategies. A completely different story of campaigns is the mean reversion model in which the elections are determined by fundamental factors of the economy and partisanship; the role of the campaign is to give voters a chance to reach their predetermined positions. The popularity of the random walk model for polls may be partially explained via analogy to the widespread idea that stock prices reflect all available information, as popularized in Burton Malkiel’s book, A Random Walk Down Wall Street. Once the idea has sunk in that short-term changes in the stock market are inherently unpredictable, it is natural for journalists to think the same of polls. For example, political analyst Nate Silver wrote
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Introduction: Some thoughts on the implausibility of Paul Ryan’s 2.8% unemployment forecast. Some general issues arise. P.S. Yes, Democrats also have been known to promote optimistic forecasts!
Introduction: Thomas Basbøll points to this ten-year-old article from Anne-Wil Harzing on the consequences of sloppy citations. Harzing tells the story of an unsupported claim that is contradicted by published data but has been presented as fact in a particular area of the academic literature. She writes that “high expatriate failure rates [with "expatriate failure" defined as "the expatriate returning home before his/her contractual period of employment abroad expires"] were in fact a myth created by massive misquotations and careless copying of references.” Many papers claimed an expatriate failure rate of 25-40% (according to Harzing, this is much higher than the actual rate as estimated from empirical data), with this overly-high rate supported by a complicated link of references leading to . . . no real data. Hartzing reports the following published claims: Harvey (1996: 103): `The rate of failure of expatriate managers relocating overseas from United States based MNCs has been estima
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Introduction: Our downstairs neighbor hates us. She looks away from us when we see them on the street, if we’re coming into the building at the same time she doesn’t hold open the door, and if we’re in the elevator when it stops on her floor, she refuses to get on. On the other hand, if you’re a sociology professor in Chicago, one of your colleagues might try to run you over in a parking lot. So I guess I’m getting off easy.
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