tag:blogger.com,1999:blog-3813701770708442620.post8640377074252591443..comments2019-10-22T05:09:30.305-07:00Comments on G-FEED: Warming makes people unhappy: evidence from a billion tweets (guest post by Patrick Baylis)solhttp://www.blogger.com/profile/00936469103707728475noreply@blogger.comBlogger3125tag:blogger.com,1999:blog-3813701770708442620.post-76237542897154071962015-12-07T20:00:26.454-08:002015-12-07T20:00:26.454-08:00I always thought that Hawai`i's high happiness...I always thought that Hawai`i's high happiness ranking had something to do with the weather. But maybe it's something else. <br /><br />Michael Robertshttps://www.blogger.com/profile/16455035518968529794noreply@blogger.comtag:blogger.com,1999:blog-3813701770708442620.post-19441115763700292502015-12-07T17:01:31.391-08:002015-12-07T17:01:31.391-08:00Hi Jonas, thanks for reading and for the good ques...Hi Jonas, thanks for reading and for the good questions. <br /><br />Yes, the shaded area is the 95% confidence interval. The graphs are 0 at 65F because I normalize the response function to be 0 at the 60-70F bin. So you can think of the size of the point estimate for, say, 80-90 degrees as representing the difference in hedonic state caused by changing the temperature of a given day from 60-70F to 80-90F.<br /><br />You are correct that 1 = 1SD. 0.01SD seemed small to me as well when I first ran these regressions. But, it turns out that the hedonic difference between a Sunday and Monday is actually only about 0.01SD as well! Also, the hedonic difference between a local football team winning and losing is a little bit over 0.01SD. I take from this that there's quite a bit of variation in the measures I use, which probably both reflects underlying variation in hedonic state along with variation in the measures. Both likely contribute to making the standardized effect sizes appear small, which is why I think it's useful to compare them to other things (like day of week) that we have a clearer intuitive sense for. Thanks for reading!Patrickhttps://www.blogger.com/profile/04195224636252225241noreply@blogger.comtag:blogger.com,1999:blog-3813701770708442620.post-87712317154729194222015-12-07T14:48:29.735-08:002015-12-07T14:48:29.735-08:00Interesting work!
I have a little trouble interpr...Interesting work!<br /><br />I have a little trouble interpreting your graphs. What's the shaded area? A confidence interval or something like that? And why is it 0 at +/- 65F?<br /><br />And what's on the y-axis? Standardized effect size (e.g., 1 = 1 SD)? If so, those strike me as rather small effects, rather than large ones, not really of practical significance. It's still interesting that you can find the differences though.Jonasnoreply@blogger.com