Does people’s life satisfaction adapt to material improvements? In a recent paper (gated), Galiani, Gertler and Undurraga find that it does, even in a case of very poor people receiving a really basic service (housing). In a large-scale experiment, some poor households in El Salvador, Mexico and Uruguay were randomly selected to receive a ready-made small house. Receiving such housing increased the share of households reporting to be “satsfied” or “very satisfied” with the quality of their life by around around 40 %, from 0.53 to 0.73, thus confirming that it was something these households really needed. What about the effect in the long term? Eight months later, more than half of the gain had disappeared, highly consistent with the hedonic treadmill hypothesis.
Thursday May 28 I defended my Ph.D. thesis in economics at the EUI in Florence. As for most people, the defence marked the end of a journey through many ups and downs and unexpected turns. The most significant development for me, and one I was very happy with, was a switch from theory to empirics, in particular from conflict theory to applied (micro)econometrics.
The thesis itself consisted of three chapters – on television and cognitive development, terrorism and work effort, and voting habits in turnout. Three very different papers bound together by using modern empirical methods to discover causal effects.
The defence was a taxing, but also very useful experience. I was lucky to have a committee that had taken their job seriously, and that provided extensive and thorough comments that will lead to large improvements to the papers; papers which I look forward to blog about when I get them out as working papers. Perseus was the proper venue for finishing everything off.
Two papers in The Economic Journal November 2014 deal with how childhood information may predict adult outcomes.
Frijters, Johnston and Shields consider the question Does Childhood Predict Adult Life Satisfaction? Using repeated surveys of people born in the UK in 1958, they are able to explain only 7 % of people’s adult life satisfaction with a very wide range of family and childhood variables. Interestingly, exploiting the panel dimension, they estimate that around 40 % of adult life satisfaction is a trait (i.e. fixed), so it is surprising that their first number is so low. It is as if type of childhood almost does not matter. Education and wages are predicted much better.
I do not know if information on time preferences would have helped, but Golsteyn, Grönqvist and Lindahl at least claim that Adolescent Time Preferences Predict Lifetime Outcomes in their article in the same issue. They find that Swedes who were future-oriented (had low discount rates) as children went on to obtain more education, better grades, higher incomes, and better health (obesity and mortality) as adults than their more impatient peers. The authors are admirably clear that they are not estimating causal effects.
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 (2001) by Ian J. Deary. I found this a useful introduction to how psychologists/psychometricians have thought about these things. What I was really after was the foundational stuff in chapter 1, and that is what I will focus on here. (Though chapter 6 on the Flynn effect is also solid, and taught me that American SAT scores have been declining in the same period as IQ scores have been rising.)
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.
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.)
Much of the discussion about Thomas Piketty’s Capital in the Twenty-First Century has been concerned with his “law” of the relationship between the rate of return on capital (r) and the rate of economic growth (g), known as r > g. To such an extent that the Initiative on Global Markets at University of Chicago asked its panel of economic experts whether they agreed or not with the statement:
The experts overwhelmingly disagreed.
Piketty’s reply in Slate was:
“I think the book makes pretty clear that the powerful force behind rising income and wealth inequality in the US since the 1970s is the rise of the inequality of labor earnings, itself due to a mixture of rising inequality in access to skills and higher education, and of exploding top managerial compensation (itself probably stimulated by large cuts in top tax rates), So this indeed has little to do with r>g.”
And he did indeed write e.g.:
“In short, two distinct phenomena have been at work in recent decades. First, the wage gap between college graduates and those who go no further than high school has increased, as Goldin and Katz showed. In addition, the top 1 percent (and even more the top 0.1 percent) have seen their remuneration take off. This is a very specific phenomenon, which occurs within the group of college graduates and in many cases separates individuals who have pursued their studies at elite universities for many years. Quantitatively, the second phenomenon is more important than the first. In particular, as shown in the previous chapter, the overperformance of the top centile explains most (nearly three quarters) of the increase in the top decile’s share of US national income since 1970. (p. 315)”
So why did the IGM ask this question in the first place? And why have so many economists been concerned with it? It is of course possible that they have not read the book. However it might also be the case that Piketty must take some of the blame and that in general it was not so clear in the book. At least the back cover text (on Amazon) is pretty ambiguous (though I hope the critics read more than that).
I should maybe disclose at this point that I have not read Capital in the Twenty-First Century either, although now I might have to.
The telling figure below from an NBER paper (wp) by Allen, Dechov, Pope and Wu has been shared by several people this summer. From data on almost 10 million marathon finishing times, they show how people use their prospective finishing time as motivation to provide more effort and bunch at every 30 min. interval.
“The law, in its majestic equality, forbids the rich as well as the poor to sleep under bridges, to beg in the streets, and to steal bread.” Anatole France, 1894.
Tyler Cowen refers to the great great quote by Anatole France in a discussion of “anti-homeless spikes” in the UK. It is highly relevant also in Norway, as the government recently struck a deal in parliament to ban begging, and also here we are trying the “raise the cost of being homeless” approach to homelessness.
John M. Keynes thus criticized an excessive preoccupation with the future in his essay Economic possibilities for our grandchildren (1930). I was a bit puzzled by this, and the full quote does not really help:
The “purposive” man is always trying to secure a spurious and delusive immortality for his acts by pushing his interest in them forward into time. He does not love his cat, but his cat’s kittens; nor, in truth, the kittens, but only the kittens’ kittens, and so on forward forever to the end of cat-dom. For him jam is not jam unless it is a case of jam to-morrow and never jam to-day. Thus by pushing his jam always forward into the future, he strives to secure for his act of boiling it an immortality.
Helpfully, there is a Wikipedia page on the “jam tomorrow“. It turns out that the jam reference comes from Lewis Carroll’s Through the Looking Glass (1871), in which the White Queen offers Alice to work in exchange for jam that she (Alice) will always receive tomorrow, i.e. never. Back to Keynes: Such forward-looking behavior is helping to solve the economic problem, but as soon as that is done (it will take at least 100 years), we can stop pushing the jam into the future.
(And presumably start eating it, though Alice says she does not care for jam, but perhaps that is another story.)