A couple of days ago, I blogged about time spent watching television and video by different age groups in Norway. Of course the issue of internet immediately popped up, so I made this graph showing both time spent watching television and time spent on the internet:
With regards to total screen time, note that these graphs leave out time spent watching video tapes and dvds and time spent on computers, electronic games and mobile phones without using the internet.
Inspired by a tweet by Gray Kimbrough graphing changes in television and video watching in the US between the mid-2000s and the mid-2010s for various age groups, I decided to follow up with a similar figure with Norwegian data. Gray showed that in the US, people aged 45 and older increased their watching substantially, while younger people decreased it at least to some extent. In Norway the picture was somewhat different – there was very little change for the oldest groups, but the youngest ones reduced their watching by much more than in the US.
Part of the reason for making the graph was to learn how to use the pcarrow option in Stata, which I accomplished, however, I found that in this case with only five groups, a simple line chart may actually provide more information and be preferable:
The recent “empirical” turn in economics should be known as an “applied” one and it is just one in a long series of related developments. Moreover, it is a move towards the historical roots of the discipline. Those are some lessons from Beatrice Cherrier‘s essay “Is there really an empirical turn in economics?“. Based on research conducted together with Roger Backhouse, she takes issue with the idea that there has been a revolution in economic research involving empirics. Some points I liked:
H/t: Erwin Dekker.
Who Will Debunk The Debunkers? Daniel Engber asks in a fascinating piece at fivethirtyeight. He tells the story of “meta-skeptic” Dave Sutton, who has made it his specialty to doubt other doubters’ explanations. The first few paragraphs, about iron, prove the point that a good debunking is often too clever. Likewise with Semmelweis – the received version is probably too simple. Finally, Sutton comes off as somewhat of a megalomaniac when it comes to his work about Darwin, providing yet another layer to the story.
A silly proposal to spend public money on giving everyone a type of sports equipment that in average can be used around one quarter of the year got me wondering how many Norwegian actually do ski. So I looked up some data from Statistics Norway’s survey on living conditions:
Source: Statistics Norway
More than half the population skis at all, skiing (on the extensive margin) is clearly on a downwards sloping trend, but is free skis to everyone the solution? Given that skis can be obtained nearly for free already, perhaps interest is just not that high. Better to build out opportunities for all-year activity close to where people live, restrict time spent watching television, raise sugar taxes, and get more physical activity into school.
I have started listening to a new podcast called What’s The Point, produced by Nate Silver’s fivethirtyeight team. The show “is a short weekly conversation (tag line: “Big Data. Small Interviews.”) that highlights data’s growing influence and brings in the people who are using it in surprising ways.” I have enjoyed the first few episodes and will continue to listen to the show on a regular basis. In the second episode, the guest was astrophysicist Neil deGrasse Tyson, and when talking about his multiple interests and obligations, he said something I liked very much about having too much to do: “When something is out of balance you can get quite innovative in your attempts to resolve that fact.” Anyway, the podcast is recommended.
Since I am doing some work using intelligence test data, I wanted to read something introductory material on that topic. Enter Intelligence: A Very Short Introduction
Deary takes the test collection called Wechsler Adult Intelligence Scale III as a starting point. WAIS-III consists of 13 different tests, and strikingly,
“every single one of those 13 tests in the WAIS-III has a positive correlation with every other one. People who are better at any one test tend to be better at all of the others. There are 78 correlations when we look at all the pairings among the 13 tests. Every single correlation is positive – a good score on one of the tests tends to bring with it a good score on the others. There are no tests unrelated to any other one, i.e. there are noe near-to-zero correlations. There are no tests that are negatively related with other ones. Even the lowest correlation between any two tests is still a modest 0.3 (between picture completion and digit span). […]
The first substantial fact, then, is that all of these different tests show positive associations – people good at one tend to be good at all of the others. […]
The second important fact is that some sub-groups of tests in the WAIS-III collection associate higher among themselves than with others. For example, the tests of vocabulary, information, similarities, and comprehension all have especially high associations with each other. So, although they relate quite strongly to every test in the WAIS-III collection, they form a little pool of tests that are especially highly related among themselves. The same thing occurs with digit span, arithmetic, and letter-number sequencing. They relate positively with all of the other tests in the collection, but they relate especially highly with each other (pp. 7-8).”
In the WAIS-II tests, there are four groups of tests that correlate particularly strongly (called “group factors”), labelled: Verbal comprehension, Perceptual organization, Working memory, and Processing speed, ref. the figure below (p. 3).
Positive correlations between the four group factors are high. This has often been taken to imply that the skills required to do well on each have some common source, which has traditionally been called g (“general factor”). Strictly speaking, the fact that the different test scores are positively correlated does not imply that they have something in common or that “g” corresponds to anything real. Deary is at one point fairly clear about this, writing: “The rectangles in Figure 1 are actual mental tests – the 13 sub-tests – that make up the Wechsler collection. The four circles that represent the ‘group factors’ and the circle that contains g are optimal ways of representing the statistical associations among the tests contained in the rectangles. The things in the circles, the specific/group factor abilities and ‘g’, do not equate to things in the human mind – they are not bits of the brain (p. 11).”
Though he muddles it somewhat when continuing with “The names we pencil into the circles are our common-sense guesses about what seems to be common to the sub-groups of tests that associate closely. The circles themselves emerged from the statistical procedures and the data, not from intuition about the tests’ similarities, but the labels we give the circles have to be decided by common sense (p.11),” and later much more by going on to treat ‘g’ as a valid stand-alone explanatory concept, and writing e.g. “We already know from Chapter 1 that there is general ability and there are […] specific types of mental ability (p. 85).”
Nevertheless, the book seems to be a good exposition of intelligence testing and how psychologists have viewed and continue to view the results of these tests.
I have always liked time use surveys and would love to use them more, for example to write posts like this one at Vox. Now I have recently begun working a little with some such Norwegian surveys, so here is a little about recent developments in how young Norwegians spend their leisure time.
(Apologies for the unsatisfying look of some of the graphs, they are simply lifted from an online resource.)
Percent spending time on various leisure activites an average day, 1970-2010.
In short, since 1970 fewer of us are reading an average day (turquoise), while more area watching television (light blue), and recently using internet (included in “Other” (dark brown)).
A bit more detailed look on average time for 1991-2005 confirms that television time is increasing; 
and although there might be somewhat of a Harry Potter effect for the youngest in the beginning of the 2000’s, time spent reading is quite consistently going down, 
including time spent on newspapers,
magazines, 
and even cartoons. 
Is that a bad thing? Well, that depends, but if it is passive television entertainment that crowds out reading, I would not be surprised if that had some long term consequences.
Via Andrew Gelman, a great slideshow about “How Americans Die” from Bloomberg. We see the development of American mortality 1968-2010 broken down in several different ways. It was new to me how important AIDS was as a mortality factor on the population level between the mid-80’s until the mid-90’s and that it affected black men the most. Also, “suicide […] has recently become the number one violent cause of death.” Go have a look.
Now I have done my share to make Capital in the Twenty-First Century
What I will write here will be the notes I took while reading the book, edited for clarity. It is well known now that the book is thick and contains very much information, Piketty explicitly wants to consider both big and small phenomena, both long and short term changes, hence disclaimer: There will inevitably be much that I will not have caught or write about, and there may also be things that I have misunderstood. But maybe these notes will be helpful for those who have themselves read parts of the book or know a little bit and are trying to understand more. Many others have written better proper reviews.
Conclusion: Much great empirics to learn from. Inequality is an important topic. Good figures. Good at using qualifications and caveats, necessary when writing such a broad book. Good that also tries to explain. Objections by others that the recent rise in inequality is caused by human capital, etc. are misguided. Fundamentals of and cause and effect relationships in theoretical framework should have been clearer, and objections often relevant. Recommended.
-Much entrepreneurial wealth on Forbes list, but probably more inherited. And entrepreneurs and their children in any case turn into rentiers. Comments on Gates and Slim on pp. 444-445 with footnote, (individual) merit not so straightforward. (Gates wrote a positive review nevertheless.)
Ø-blog 