Saturday, February 13, 2010

The Spirit Level is junk science (updated: Wikinson Responds)

There is a new book called The Spirit Level, which claims to prove that most social problems are directly caused by income inequality. So if people in the U.S are more obese than Swedes, it is because middle class Americans they are stressed because they earn less than rich Americans, and eat more (not joking). The “proof” for this is cross country correlation between inequality and various measures.

As a social science student, I am taught to take causality seriously. If you want to argue that inequality causes obesity, you have to actually prove it. Correlations are not scientific proof.

From a theoretical perspective, social problems cause inequality, or are often both caused by deeper ills. In fact it is difficult to think about a social problem that does not cause inequality! Low level of human capital makes your more likely to not take care of your health and causes low income. Bad norms cause crime and low income. Drug use causes problems and low income. Family disruptions causes social problems and low income. And so on.

If The Spirit Level wants to make extraordinary claims (middle class people become more likely to die if the rich grow richer) they need extraordinary evidence. But they have no evidence at all, just correlations. That is why no one in scientific circles takes this book very seriously. However in Sweden it is making a huge impact.

Blogger Danne Nordling pointed out a strange fact about the book. Its measure of inequality, the most important factor in the book, is not gini, the standard inequality result. They seem to use 20/20 richest and poorest ratio. Why make this strange choice, when their source (UN Human Development Index) has gini? I smell data mining.

First for fun I did a simple regression of life expectancy on income inequality and per capita GDP for all countries the UN has data for. The correlation between inequality and health is not statistically significant.

Second I approximately redid the exercise in their book, I did a regression of inequality as measures by Gini and life expectancy for 28 OECD countries, again from the UN HDI. The result is not only that it again is not statistically significat, income inequality is positively correlated with life expectancy!



If I add per capita GDP to the regression, the p value is 0.29 for a positive relationship between health and inequality.

If a Social Democrat 5 minutes ago was convinced that “inequality kills” based on a cross country correlation, are they now convinced if I claim that I have “proven” than income inequality leads to longer life expectancy? How about my "proof" that income inequality makes you happy?

Swedish Social Democrats do not understand causality. They are excited about a book with a horrible methodological problem to start with (reverse causality), weak evidence (correlations) whose correlations are not even robust to using the standard measure of inequality.

PS. From a personal perspective, this book bothers me. It’s not at all the leftist message, but that they are giving cross country regressions a bad name. This kind of scientific abuse has caused economists to be very dismissive of any use of cross country regressions. Basically, as a rule of thumb, they completely dismiss cross country regressions altogether, because unserious people misuse it so much.

However I think that if you have solid theory and there are no serious endogeneity problems, you should be able to use countries as quasi-experiments, as long as you are careful. Have a solid story about causality, no reverse causality or third factor problems, and don’t push your results too hard, and go ahead and use cross country. For some problems, such as the effect of taxation on long run outcome, there is no other good measure of treatment.

Update:

Richard Wilkinson responds to me, and it is a amazingly week responce.

Wilkinson claims that the relationship between inequality and life expectancy remains if you use Gini. Look at his nice graph. Convincing, isn’t it?

It shouldn’t be. First of all he amazingly does not look at the straightforward measure “Life expectancy”. He uses some index. Here is the exact same graph if we look at the most intuitive measure of health, the standard, straightforward “life expectancy”, with the same countries Wilkinson used:



Not quite as nice, is it? Your eyes are not deceiving you, there is no statistically significant relationship between Gini and Life expectancy in the 21 countries Wilkinson looks at. The p value is 0.46.

That’s really it. End of story. He has written a book about the fact that inequality kills you, even though there is no statistically significant relationship, even a weakly statistically significant relationship (say p 0.1), between life expectancy and inequality.

Second, why are there 21 countries, when the OECD has more members? Out of the OECD countries, Wilkinson excludes 9 nations. I can understand excluding Mexico and Turkey, as they are third world nations. But He also excludes South Korea, Czech Republic, Hungary, Luxemburg, Poland, Slovak Republic and Iceland. I included the full list in my other post, let me put here here is well:



The relationship between Gini and Life expectancy is as you see essentially zero, and no where close to statistically significant, p value 0.78. (At least, unlike the U.N data, with the OECD data the relationship is not the opposite of what Wilkinson claims...)

Why would he include Portugal, but not Korea and Czech Republic (that are richer than Portugal), or Slovak Republic (that is as rich as Portugal)? One reason he excludes them is that Czech Republic and Slovak Republic have very even distribution of income, but low life expectancy. Portugal fits his story, it is unequal and does bad. Czech Republic and Slovak Republic don’t fit his story, since they are equal and do bad.

Now, if you ask me, I would say that the reason these two nations have low life expectancy is that they have low income. But once we control for income, we have to control for income for every country. In that case the relationship between gini and life expectancy becomes even weaker. As you remember I controlled for income using EVERY country in the U.N list, and the relationship between gini and life expectancy was no longer statistically significant!

This man has very weak evidence, and is data-mining like crazy. He does not use Gini, the standard measure, because it doesn't tell him what he wants. He does not use life expectancy, the standard and intuitive measure, because there is no statistically significant relationship between life expectancy and inequality. He removed 7 out of 28 standard OECD countries, because some of them have low inequality and bad outcomes.

The lesson is: Don’t believe a word Wilkinson says before you have had a chance to verify it by looking at the source data yourself. He is not a objective scientists giving you realible data, he is selling you a story.

Of course the book is full of this type of graph. The central argument, the supposedly solid relationship between health and inequality, was a fraud, an optical trick created by data mining. How reliable do we expect the rest of the graphs in the book to be? The naive Swedish Social Democrats, perhaps desperate for new ideas, have been fooled by these guys. The Social Dems should ask for their money back.

I will give you the data, so you can run your own regressions.



If you see Wilkinson, ask him:

* How can he claim that inequality kills, when there is no statistically significant relationship between the standard measure of inequality (Gini) and the standard measure of health (Life expectancy)?

Remember: This is true regardless if he uses OECD data or UN data. In fact the OECD data is kinder to him than the UN HDI data, according to both sources there is no statistically significant relationship, not even close, and in the UN HDI the relationship between inequality and life expectancy is even mildly positive.

* Why did he use an odd measure of inequality and some index instead of the standard measures?

*When the standard measures refute his story, why does he not mention this to his audience, as a scientist would?

60 comments:

  1. What you are missing in your analysis is that this is a popular science representation of a wider scientific field. The "proof" is not only in the regression he chooses to include in the book; that is just a representation of the science behind.

    There has been a great amount of medicine literature written on the subject. To mention one of the latest very large meta-studies (59,000,000 subjects include) did find "a modest adverse affect of income inequality on health, although the population impact might be larger if the association is truly causal". [Income inequality, mortality and self rated health: meta-analysis of multilevel studies, British Medical Journal].

    There is a serious literature on the subject, and we can see that it is not completely dismissive of Wilkinson's claims (although this report of course expressed a wish to be careful with interpretation of its results).

    What I go against is the notion that you can attack a popular account by a scientist by just deconstructing the plots he includes in the book, and a run a few regressions on your own, instead of taking the approach of looking at the scientific field from which he comes.

    p.s.
    Granted, it probably is true that Wilkinson oversold his case, which is regrettable, but often happens in the popularization of science. One of the book's harshest critics in Sweden, Johan Norberg, for example included a a large number of graphs plotting quintiles of economic freedom against a number of good traits of a countries in his bestseller "In Defence of Global Capitalism". Was he careful about not asserting causality? Well, a sample title: "Economic Freedom Lowers Corruption"….

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  2. "There is a serious literature on the subject, and we can see that it is not completely dismissive of Wilkinson's claims"

    true for the inequality - health relation. But wilkinson and picket also argue that that equality causes a number of other good stuff, including high levels of recucling. it is not serious.

    As for Norberg, for sure he also has a few not so scientific scatterplots in his books.

    But in this case, it is also true that reserach is not dismissive of the idea that there is a causal relationship from economic freedom to e.g. low corruption.

    oh, and also, norberg is not a researcher himself, whereas Wilkinson relies heavily on his academic credibility. so wilkinson annoys me much more! :-)

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  3. "What I go against is the notion that you can attack a popular account by a scientist by just deconstructing the plots he includes in the book, and a run a few regressions on your own, instead of taking the approach of looking at the scientific field from which he comes."

    The book mostly consists of cross-country linear regressions, and if they are not even robust (for country selection and choice of inequality measures - especially as the authors use a somewhat "quirky" measure of inequality, I.e. not gini) that is certainly a strike against their thesis.

    One instersting aside is that the gini statistics for their perhaps most influential observation (Japan) are wildly different depending on whether one uses world bank data or OECD data. That is an interesting issue in itself.

    When it comes to showing, say, within-country correlations of how the share of income of the highest 10 percent of the population correlates over time with, say, life expectancy they come up short. They even briefly admit as much in the book (sort of), although they proceed to ignore it.

    (I.e. see for instance:

    http://4.bp.blogspot.com/_0uByo4dX5yM/S3WDOwsJfDI/AAAAAAAAAkk/eWWOYg27vnY/s1600-h/Leigh10feb1.JPG

    http://3.bp.blogspot.com/_0uByo4dX5yM/S3WDT9p0wzI/AAAAAAAAAks/lzYobOoXwOI/s1600-h/Leigh10feb2.JPG

    As for the public health literature on the topic, it works (sort of, with the usual caveats attached to epidemiology, especially imperialistic epidemiology) provided one believes that the inequality->stress->health causality chain is more important than the "well ordered life"->higher income //"well ordered life" -> health chain.

    Note: Their thesis isn't really that inequality is bad. They are adamant that it is the wealth of the wealthy, not the poverty of the poor that is bad.

    As for Norberg, he probably has some causality problems as well. Note though that this post is careful not to attack all use of cross-country regressions per se, just this particular instance of cross-country regressions.

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  4. Well I agree with you that to extend the health ideas to every aspect of society is overstretched; one of those exercises where you have a good idea that you try to fit ever more diverse phenomena. Also, researchers should constantly be checked so that they do not violate the trust we hold for them because of their academic credentials.

    But, notably, the reaction has not been that this is a scholar well trained in the social determinants of health, which has an interesting thesis (albeit debated) when it comes to the effect of inequality for health, who, on the downside, tries to stretch his theories beyond his area of expertise.

    Indeed, the health part has been one of the most contested claims.

    And, of course, this is the area in which Wilkinson actually is a researcher: the inequalities in health. Hence it is the area where we are most justified to demand scientific integrity from him.

    I believe that your PM that your wrote on the book addressed some issues with these sorts of correlations, although introducing dummy variables for countries can eliminate the visibility of non-linear and threshold effects (as a dummy variable analysis essential becomes an averaging of the derivative of the response curve over the different levels of inequality..)

    In addition, you referred to a couple of other researchers whom you called "competent (duktiga) and honest" (in implicit contrast to Wilkinson?) which were critical of Wilkinson's conclusion.

    It is good to assess the scientific quality when a researcher makes claims, but as a fellow researcher you also speak with a credibility which demands balance. The reading of your blog entry and PM gave the impression that Wilkinson based his conclusions concerning health on one regression plot, which you could debunk, and that there are "serious researchers" who disagree with him. I don't believe this gives the impression that you now convey, that it is true that there is non-dismissive literature on Wilkinson when it comes to the health-inequality relation.

    The issue is interesting, and there are competing claims being made, and I think an assessment of the merits of Wilkinson's work should focus on what the academic debate in general says, and not just your own analysis plus a number of Wilkinson's critics.

    I do sympathise with your aim of critically scrutinizing the claims made by researchers, but we should all be careful not to skew the debate in an opposite direction instead!:)

    Hannes

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  5. Note: my reply is a reply to berghs entry and not Arvid's, as his was posted while I was writing mine.

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  6. According to the Japanese Statistics Bureau the Gini used by the OECD appears far closer to official japanese statistics.

    http://www.stat.go.jp/english/data/zensho/1999/3.htm

    http://www.stat.go.jp/english/data/zensho/2004/hutari/gaiyo18.htm

    "An examination of the disparity in yearly income between households by means of Gini's coefficient reveals a slight rise to 0.301 in 1999."

    "The differentials in yearly income using the Gini coefficient1) in all households consistently rose from 1979 reaching 0.308 in 2004."

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  7. To Arvid:
    I'm not mainly in defense of the book's and its conclusions, but I've become very interested in the issue that the book raises, and wonder to what extent it is true. Clearly the book is somewhat shallow as it is a popular science account, but many debaters seem more concerned with rebutting details in the book than clarify what is actually going on.

    The issue I have with Tino's post is not so much that it is bad to test for robustness, or that it is bad for a regression to not be robust. I dispute that something which is not science can be junk-science. The science is not the book; the book is just a popular science account.

    What has happened though, is that the book has elevated a discussion about inequality and its consequences to an important position in Swedish national debate. The main interest now is what is true with regards to the issue, and criticizing a popular science book's lack of discussion on causal connections is not wrong, but besides the point.

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  8. Correction: I'm in partial defense of some of the conclusions for which there seems to be reasonable support; outside the book that is.

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  9. Sorry Timo, you have to think harder, and read more as well.


    There is a long ongoing debate about the causality between health and inequality where the conclusion is that they reinforce each other.

    Health improvement can reduce inequality, but an unequal distribution can also aggravate ill-health and thus aggravate inequality.

    The solution is to attack both ill-health and inequality. And here Sweden is a successful example.

    To accuse social democrats of not understanding causality is simply foolish.

    Have you read anything about the efficiency of Swedish social policy in reducing inequality and improving health?

    How can you implement an efficient policy if you do not understand causality?

    Bo Malmberg

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  10. "...criticizing a popular science book's lack of discussion on causal connections is not wrong, but besides the point."

    It does discuss the causal connections, but in a very one-sided manner. I.e. it is assumed that Rosengård has high crime and many social problems because of stress amongst Rosengård inhabitants brought on by people in Danderyd making too much money.

    "Sorry Timo(sic), you have to think harder, and read more as well."

    That would be excellent - I have a feeling that the larger "higher ginis brings on stress-induced illness" literature could use a thorough examination.

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  11. "it is assumed that Rosengård has high crime and many social problems because of stress amongst Rosengård inhabitants brought on by people in Danderyd making too much money. "

    However, it would be considerably less need to live in Rosengård if income was more evenly dispersed, given that the general income level of society determines land prices; if the incomes of all inhabitants in my hometown double, it will certainly be harder for me to buy myself a house in that down.

    That means that a high income inequality may well lead to ghettoization as places were rich people prefer to live become unattainably expensive for poor people. Segregation, which you probably admit has a part to play in Rosengård's problems, does certainly have a connection to income inequality...

    I'm certainly no expert on segregation, but a possible causal link is not as outrageous as you make it sound.

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  12. "However, it would be considerably less need to live in Rosengård if income was more evenly dispersed, given that the general income level of society determines land prices; if the incomes of all inhabitants in my hometown double, it will certainly be harder for me to buy myself a house in that down."

    Given the prevalence of housing subsidies and rent control in Sweden, I would be very careful in ascribing social problems in a specific area to the general non-affordability of non-problem-area housing brought on by (too-high) incomes amongst the wealthier segments of the population.

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  13. Dear Arvid,

    'the larger "higher ginis brings on stress-induced illness" literature could use a thorough examination.'

    It is already a cottage industry.There are more than 800 papers in web of science citing Wilkinson 1996.

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  14. Hannes: I should add that your example does not use low-status-induced-stress as the conduit for the worsening of health/BMI/recycling frequency brought on by inequality - hence it is separate from the Wilkinson/Pickett hypothesis.

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  15. "It is already a cottage industry.There are more than 800 papers in web of science citing Wilkinson 1996."

    I was referring to a Tino-conducted examination.

    I am re-reading the causality chapter (p 187-) right now. Good stuff.

    They simply will not discuss the possibility of society-wide social weaknesses (I.e. in norms and institutions) both increasing inequality and social problems in a serious way. Instead they discuss:

    a) The possibility of direct reverse causality (murders reduce incomes - not the more reasonable alternative, I.e. social dysfunction increases both inequality and murders.)

    b) How holding individual incomes constant still show individuals with the same income having worse outcomes in more unequal countries.

    c) The possibility of "neo-liberalism" being the real culprit.

    After that experiments, etc. are discussed, relating to:

    -Indian casteless.

    -US African-American test performance.

    -The good ol´ "Blue eyes" experiment.

    Plus some Macaques, of course.

    I especially like this part:

    "Although we know of no experiments confirming the causality of the relation between inequality and violence, we invite anyone to go into a poor part of time and try randomly insulting a few people."

    Well, that settles the matter!

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  16. Well, Wilkinson does not have a geographical theory to explain the connection between inequality and stress. But it could certainly be stressful to live in a segregated areas:

    Do perceived neighbourhood cohesion and safety contribute to neighbourhood differences in health?

    Is an article discussing this question.

    Think:
    Inequality -> Segregation -> Stress

    As to whether inequality causes segregation, Biterman & Franzén comments this in "Residential Segregation" in International Journal of Social Welfare with "Whichever theoretical model is used to explain seg- regation, the uneven distribution of financial resources between people appears to be an important factor in its development."

    They do also mention a number of other reasons, but to establish some sort of causal chain, that it is an important factor shoud suffice.

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  17. Hannes: I agree that having a significant part of the population being so poor that they cannot afford housing in a non run-down neighborhood would probably be socially destructive. But I really don't see that being a major issue in Sweden.

    Nor is Inequality -> Segregation -> Social problems / Stress (there is really no need to bring stress into the equation) a very good fit with the thrust of Wilkinson and Pickett's theory, which is that helping the poor is bad policy - it is the rich that must be brought down (not stated explicitly in the book, but in interviews, I.e. se: http://www.sr.se/sida/artikel.aspx?programid=503&artikel=3373753
    )

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  18. 1. The burden of evidence is on the people making the claim, not me. The evidence you have presented so far is a scatterplot that is not even robust. In two straightforward specifications I did it fell apart.

    2. If you want to be taken seriously, find me a paper that meets the identification requirements in current economics. That means a good instrument for inequality, regression discontinuity, or some exogenous shock. The fact that you have written so much and not offered that reinforces my point: Social Democrats do not understand causality.

    3. The fact that you attribute Swedish good health to Social Democrats is an example of this. Sweden had the highest life expectancy in the known world in 1860. In 1900 Swedes lived 5 years longer than Americans. Did Social Democracy do that?

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  19. 1. I'm questioning your claim that Wilkinson is wrong, as I believe you cannot judge the truth of a scientific position based on a graph from a popular science account.

    You claim that this is the only evidence which has been presented, but there is a scientific literature on the subject which I asked you to review instead. For example the study "Income inequality, mortality and self rated health: meta-analysis of multilevel studies, British Medical Journal", was one of the ones I referred to.

    2. I do not know if there is a paper fitting that description. However, in the scientific community there are significantly more thorough analyses of how the correlations look than in the book.

    Should we then choose not to even look at the research which has been done, and instead relying on you bashing a single chart?

    I believe this goes against your own postscriptum.

    The research available is the best we have. It should be one of those situations where you yourself believe mere correlations to be useful (if treated more carefully than in the graph, of course).

    Or do you have higher standards of truth to prove adverse effects of inequality, compared to adverse effects of taxes?

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  20. Tino: ”The burden of evidence is on the people making the claim, not me. The evidence you have presented so far is a scatterplot that is not even robust. In two straightforward specifications I did it fell apart.”

    Bo: You make the claim that Wilkinson is wrong. You should substantiate that claim with a review of the literature, if you want to convince me.

    Tino: 

”If you want to be taken seriously, find me a paper that meets the identification requirements in current economics. That means a good instrument for inequality, regression discontinuity, or some exogenous shock. The fact that you have written so much and not offered that reinforces my point: Social Democrats do not understand causality.”

    Bo: This is a view that serves to privilege theoretical analysis above empirical results. You seem to indicate that the empirical literature in this field is not worth reading. I do not share this view. Empirical results show us what to expect from different policies. Economist sometimes think that a model result is directly useful, but since it is based on specific assumptions we will never now if model based advice will work in practice. Social democrats acknowledge that our knowledge of reality never can be perfect. That is why they use piecemeal reformism to reach their goals. This gives policymakers time to observe if reforms really lead in the right direction.


    Tino: ”The fact that you attribute Swedish good health to Social Democrats is an example of this. Sweden had the highest life expectancy in the known world in 1860. In 1900 Swedes lived 5 years longer than Americans. Did Social Democracy do that?

    Bo: Should I answer to this? In 1932, life expectancy in Sweden was 63.95. In 2006 it was 80.95. Did Social Democratic policies contribute to this increase? Without doubt. The Swedish Gini coeficient is 0.23, compared to 0.34 in UK and 0.45 in the US. Has Swedish welfare state policies contributed to this low level of inequality? The answer given by current research is again yes.

    Bo: You claim that ”Swedish Social Democrats do not understand causality”. That is, a fully random policy would have generated the same result. Prove that if you can!

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  21. Is that the gini before or after taxes?

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  22. I mean the Gini you (Tino) are using in you calculation showing that ''inequality is positively correlated with life expectancy!'', is it the gini after taxes?

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  24. Hannes:

    1. I read the the study you refer to: is just a summary of other correlation studies (as a side note it only makes modest claims, unlike this book,) I asked you specifically for a study that uses methodology that gets around endogeneity.

    2. “I do not know if there is a paper fitting that description.”

    And you don’t think this is a problem?!? If a causal relationship from inequality to health existed, why can’t you identify it? (and if they have, please show me, and I will believe your). The endogeneity problem is massive, and yet you are not even trying to solve it?

    3. “Should we then choose not to even look at the research which has been done”

    Not if you understand that the methodology is flawed! 100 meaningless studies are not better than 1.

    4. “and instead relying on you bashing a single chart?”

    No, I did both. I pointed out the junk methodology, and that the relationship didn’t even hold for using Gini. Of course, I would not have cared about the chart if the authors had not relied strongly on charts in marketing their arguments.

    5. “Or do you have higher standards of truth to prove adverse effects of inequality, compared to adverse effects of taxes?”

    I have the same standard. These are not my standards, it is the standards of the field, that I follow and uphold.

    On variables where there is an endogeneity between taxes, such as GDP growth rate, economists indeed do not accept correlations. For this reason the general consensus is that we have not identified the effect of taxes on long run growth. I would therefore never write that science has shown taxes reduce long run growth, even if you did 500 correlations.

    Taxes and hours worked do not have quite the same endogeneity problem, although even here it has been pointed out that countries with high taxes also have high unionization, so we cannot be sure the effect is due to taxes. Economists give much more weight to studies that look at quasi-experiments, such as tax reforms where some people have more change in taxes than others, to identify the effect of taxes on taxable income. They don’t accept correlations as evidence in out of itself.

    Bo: You don't seem to understand, I don't want theory, I want empirics done in correctly. When you have endogeneity it is not enough to just use simple correlations.

    Swedish life expectancy has not grown faster than other countries since 1932. Sweden already was ahead of other nations in life expectancy before 1932. Why do you attribute something to Social Democrats that every other western country experienced?

    August:

    I am glad you asked. This morning I looked up after-tax gini data from the OECD, I will make a post tomorrow.

    PS. In case you wonder, I don’t have a strong belief about inequality. It suits my ideology find to find bad effects from inequality, I think homogenous societies work better. But they have to be evidence, not empty claims. This is about junk methodology and making a mockery of science.

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  25. http://augusttorngrenwartin.blogspot.com/2010/02/wilkinson-ger-norberg-och-nordling-svar.html

    Jag har nu publicerat Wilkinsons svar på ditt påstående om att ''inequality is positively correlated with life expectancy!''. Han svarade även på Norbergs och Nordlings kritik.

    Mvh
    August

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  26. August: Thanks a lot!

    (P.S I know the OECD this year accepted some new members, but they have not added much data for them yet).

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  27. I have now updated my blog with a brief response from Wilkinson.

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  28. Hi again! I've now sent what you wrote in the comments field at my blog further to Wilkinson. It will be interesting to hear his response.

    The reason why he gave me a long answer on sunday was probably because it was during a weekend.

    ''Please don't waste my time more with wild goose chases, and answer the direct questions: Why is life expectancy not related in a statistically significant way to inequality, if inequality is a major killer?''

    Good question. As I wrote before: Wilkinsons Gini-index showed in my post is, as you can see, an index of health AND social problems in relation to inequality. It may be totally true that the relationship is different (not statistically significant) if you're measuring only life-expectancy, and it would be very interesting to hear Wilkinsons comment on that.

    well, check out http://augusttorngrenwartin.blogspot.com/2010/02/wilkinson-ger-norberg-och-nordling-svar.html
    in the coming days for more answers from Wilkinson

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  29. ''Notice that the United States is one of the least innovative countries according to "The Spirit Level". Now, no matter how dogmatically leftists you are, it is hard to claim that the U.S., the most technologically advanced country in the world, winner of 60% of scientific Nobel prizes in the post war period, is one of the least innovative advanced nations on earth, no more innovative than Portugal.''

    You have to measure patents PER CAPITA (of course!). The US is, according to what I have reda, not very innovative per capita.

    Come on, you know yourself you have to measure patents per capita Tino, right?

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  30. If Wilkinson answers tomorrow I'll publish it on my blog.

    Again: Patents per capita is the only way you can measure how innovative a country is.

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  31. I'm sorry, I was reading the post very fast and missed the following: ''They had themselves calculated a measure of patents adjusted for population''.

    Very interesting that you get a very different relationship than Wilkinson on this.

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  32. August:

    It took a bit longer, since they had not done it themselves, but I also looked at patents granted country by country (of course per capita, also here). No statistically significant relationship to gini.

    As an example, in 2008 Americans got 485 patents per million people, and the people of Portugal, acountry with virtually no high-tech industry, 23 per million.

    It strains credulity to sell us a measure that claims that Portugal is as innovative as the U.S.

    In 2008 the E.U 15 on average had 344 patents per million, slighly less than the U.S.

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  33. I'm all aboard on your claims that the book is full of junk science, but I would like to point out that:

    "Swedish life expectancy has not grown faster than other countries since 1932. Sweden already was ahead of other nations in life expectancy before 1932. Why do you attribute something to Social Democrats that every other western country experienced? "

    this comment was made about the absolute level of US GDP vs EURO GDP and the growth rate and there you attributed the equal growth rate, but higher level of US to better policies. Why not now?

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  36. Excellent question. I think I have a good answer though:

    The U.S had more capitalistic institutions than Europe in 1900 and in 2009. If it did not have a systematic advantage Europe would have closed the gap, which it didn't.

    Krugman essentially was saying "Europe does not have worse institutions, because it grew almost as fast in a certain period." However I argue that if it had as good institutions convergence would have taken place, they would have *closed* the gap, which they did not.

    The health care equivalent of Krugman's argument would have been me writing that the U.S. is not doing worse than Sweden in health, because life expectancy grew as fast between 1932-2009 (which is in fact the case).

    However I would not claim that, because Sweden maintained its advantage in levels, which means it must have maintained some systematic advantage. Otherwise the U.S would have *closed* the gap.

    My point was not that we should ignore levels, or that Sweden does not have an advantage in health compared to the U.S. It was that the systematic advantage Sweden has cannot be Social Democratic policy, as Bo claimed.

    In the first example policy is a candidate, since the U.S had more capitalistic policies and higher level in period 1 and more capitalistic policies and higher level period 2.

    In the second case Sweden did NOT have Social Democratic policies in period 1 (1932), only in period 2 (now).

    So the systematic advantage that maintained higher Swedish levels must have been something different than policy (such as lifestyle).

    I never claimed levels do not matter, only that the explanation for higher levels cannot have been Social Democratic rule.

    (It is logically possible that Sweden had some advantage that went away and was replaced by an equally large Social Democratic advantage)

    ReplyDelete
  37. Okay, now Wilkinson have sent me new gini-correlations:

    http://augusttorngrenwartin.blogspot.com/2010/02/wilkinson-ger-norberg-och-nordling-svar.html

    Think you will find it interesting!

    ReplyDelete
  38. Let's assume that there was a causal relationship, e.g. some people who are poor eat their heart out thinking that some other people make a lot more money than they do.

    SO WHAT?

    Does that mean that "redistribution" is justified, because it allows such miserable, envious creatures to live a few years more?

    NOT AT ALL!

    It would be the utmost insult, trampling the rights and feelings of every honest person.

    Redistribution probably leads to a REVERSE health risk: those who are gifted, highly motivated, work hard and are of above average intelligence naturally SHOULD earn substantially more than those who are less gifted, less motivated, work less hard and are of lower intelligence.

    If redistribution takes the money of the gifted, hard working and gives it to the lazy, not so hard working, that might very well affect the health of the former adversely and if THEY die, the country will suffer substantially}

    ReplyDelete
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  42. Pro Libertate: I don't think anyone feels that hardworking gifted people shouldn't be able make money and keep it. The question is, how can we justify radical inequality, say, when 400 Americans own more than 150 million (hardworking middle class) Americans combined? Although there is a good statistical brawl to investigate, there is still the reality that having increased financial power begets greater financial power. Governments of, by and for the corporate / financial sector, where the money is held, spells, by default, only greater inequality. There is some basic social compact in which empathy for fellow citizens and economic justice must be the floor under society. Too consider it mere fluff or mere fodder for statistical rumination, misses the non-statistical, ethical and important considerations of the value of economic and social justice to a society. You're not opposed to that entire idea are you?

    ReplyDelete
  43. Take a look at this which is very interesting in assessing motivational bias in data selection supporting old fashioned notions that Markets and consumption levels measured by GDP actually is of itselfself justification as more growth means its all going swimmingly.
    http://www.green.maryland.gov/mdgpi/pdfs/GDP%20Paradox.pdf
    Wilkinsons Work is not as disingenuous as the original post suggests Economics is flawed in a lot of its assumptions GDP being one of many.

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  46. The Gini Coefficient is a weighted measured of overall population equality. Since the question is about the effects of minimising inequality, it is perfectly valid to select an extremising comparative index. This would ensure that the effects can be visualised effectively with maximum fidelity.
    If you would like to test this theory then I invite you to publish the same figures using income inequality as defined by:
    Top 10% divided by bottom 10%
    and
    Top 1% divided by bottom 1%

    I am also very interested in analysing the source of outliers such as
    -US states ND, MT, CT, NY trust polling is above the trend-lines among the states, while MS, NC, AL, and AR so low?
    -Denmark, Norway, Sweden, Finland, Netherlands, New Zealand, Australia, and USA that seems to give a higher trust polling trend-line than that including most of Europe, Japan, and Israel?
    -Netherlands has high child welfare, while Japan, Israel, New Zealand and especially the UK fall so far below the trend-line?
    -The USA is so much worse deviating strongly from the trend-line on the Index of Health and Social Problems?
    -Homicide rates in USA/Canada from Can J. Crim 2001, 43, 219-236 for paneling of trend points__________________________
    -Homicide rates for Finland and USA deviate high from the trend-line while Singapore, New Zealand, Ireland, and Spain deviate low from the trend-line?
    -USA has excessive prison population while Greece has so little, strongly deviating from the trend-line on both accounts.
    -USA state high school drop-out rate in MA, CT, NY improved versus the  trend-line while AR, SC, KY, MS are so much worse.
    -Denmark and Australia having such high social mobility deviating from the trend-line (and to a lesser extent Canada)?

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