# Statistical Jokes (48): Life Imprisonment Without Parole

A prisoner had just been sentenced for a heinous crime and was returned to his cell. An inquisitive guard could not wait to ask him about the outcome.

Guard: “What did you get for a sentence?”
Prisoner: “I could choose life or 100 years.”
Guard: “And what did you choose?”
Prisoner: “Well, life, obviously. Statistically speaking that is shorter.”

More on Liwop. More statistical jokes.

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# Statistical Jokes (47): The Odds Are Good But the Goods Are Odd

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Three ladies, formerly roommates at college, met monthly for lunch. This month’s topic of conversation turned to catching husbands. Sue said she was going to take advantage of the upcoming 3-day weekend to fly to Acapulco and scout the pool at Club Med. Julie said she was going to bite the bullet and sign herself up at one of those video dating services. Kate said she was flying to Chicago for the International Conference of Statisticians. Sue and Julie looked puzzled. Kate responded by telling them that 86% of statisticians were single males under the age of 37.

Sue said, “Wow! Odds are good!” Julie said, “Yeah, but the goods are odd”.

More statistical jokes.

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# Lies, Damned Lies, and Statistics (43): Cherry Picking Time Frames

I’ve shown before how misleading it can be to pick a very particular start or end date in a statistical time series for which more data are available than the data you choose to show. Here’s another example: in an effort to whip up some old fashioned hatred of asylum seekers, the French newspaper Le Figaro offered this graph:

###### (source)

A continuous and steep rise in the numbers! 70% increase in 5 years! Take it easy I would say. The increase would have looked a lot less ominous had they chosen to start the y-axis at 0 instead of 30.000. The most important bit of manipulation, however, occurs in the x-axis: go a bit further back in time, and you get this (look at the green line):

But of course they don’t want to take it easy. Angst is precisely the point, and choosing the low-point of 2007 as the cherry-picked starting date of the graph is intended to maximize angst. They don’t want people to realize that the current numbers are nothing more than a return to normal.

With thanks to @jacksometer for the pointer.

Another, more sophisticated way to manipulate the x-axis in a graph is described here. More posts in this series are here.

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# Statistical Jokes (42): Graphs and Axes

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More serious posts about what happens when you forget about or mess with the axis of a graph are here, here and here. More statistical jokes here.

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# Capital Punishment (42): The Stupidity of Deterrent Statistics, Ctd.

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The so-called deterrent effect is one of the main arguments in favor of capital punishment. I’ve argued many times before that the data we have don’t support the existence of this effect. Some of the data even suggest the possibility that instead of a deterrent effect, capital punishment has a brutalization effect (because it sends out the normative message that violent retaliation is the normal response to ill-treatment and that the sanctity of life is a naive moral ideal).

The following quote nicely summarizes the difficulty of proving the deterrent effect:

I would like to know how a statistical study, no matter how sophisticated, can possibly tell us the subjective motives for acts that were never taken and, moreover, how it can do so with the specificity of telling us approximately how many people did not do what they otherwise would have done under different circumstances. Where are these people? And, more importantly, how would we recognize one if we happened across him or her? (source)

Of course, people who want to disprove the deterrent effect also face this difficulty, but I assume we can agree that the burden of proof is on those who want to use the effect as an argument in favor of capital punishment. And that turns out to be a very heavy burden in this case.

Anyway, even if deterrence could be proven and even if we could establish with some certainty that every execution saves n lives – as some have argued, oblivious of the difficulties pointed out in the quote above – then we would still have good reasons to reject capital punishment.

More here.

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# Terrorism and Human Rights (38): Guantanamo by the Numbers

A fine infographic from the ACLU:

gitmo by numbers, ACLU infographic

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The oldest prisoner is 98 years old? Come on people. Nobody can claim with a straight face that this person is a serious threat. I’m sure he can be handled by those manly security guards in a normal US prison where he would find himself serving a sentence imposed on him after a regular trial.

More in this series here.

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# Racism (23): Residential Segregation in the U.S.

A nice illustration complementing this previous post:

residential segregation in the US

###### (source, click image to enlarge)

More on segregation here.

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# Human Rights Maps (157): Homicide in NYC is Primarily a Problem of and for Male African Americans

Apparently, it’s more dangerous to be a male black person in NYC than a person of any other race or gender:

###### (source, where you can find an interactive version of these maps)

African Americans represent only 25% of NYCs population, but 61% of murder victims. The racial distribution of the perpetrators is strikingly similar to the racial distribution of the victims; and men are not only the main victims but also the perpetrators in 92% of cases.

A note of caution: correlation doesn’t imply causation. In this case, this means that the race of most of the perpetrators shouldn’t lead you to the conclusion that black people are more likely to engage in murder because they are black. A third element, hidden in the correlation and more common among blacks, is most probably the cause of the high murder rate (perhaps poverty). In which case, distorted homicide rates may be a symptom of racism and discrimination.

Another note of caution: a common feature of a lot of statistical data in map form is that they exaggerate the prevalence of the phenomenon that is measured, and so it is with these images of murder in NYC. The town is full of it, if you can believe the images. But that’s obviously not true. 500 or so homicides per year, on a total population of 8 million, amounts to one murder per 16.000 people, only slightly higher than the 1 in 18.000 for the US nationwide (it’s not surprising that it’s higher for a densely populated urban area).

Also, the numbers have trended downwards in NYC:

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Apparently the same pattern can be seen in Chicago:

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And Washington DC as well – data are here:

###### (source, where you can find an interactive version)

More maps on violence are here, and more human rights maps in general are here.

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# Why Do Countries Become/Remain Democracies? Or Don’t? (20): Education Again

It’s a common assumption that democracy is driven by levels of education:

• Less educated people are – supposedly – easier to oppress and more willing to accept extreme and simplistic ideologies that authoritarian rulers can exploit. They are also said to be less tolerant, and therefore less willing to accept freedoms and rights that protect outgroups.
• Once people become more educated, they start earning more. And because they earn more, they have more leisure time. And because they have more leisure time, they have more opportunities to engage in various activities. And because they have these opportunities, they start to demand the freedoms they need to take up these opportunities. Better education itself, irrespective of the higher earning potential that goes with it, opens up opportunities to do things, and hence drives the demand for the freedom necessary to do things.
• More educated people are also more aware of the ways in which their governments oppress them and of the liberties enjoyed in other countries, and they are better able to organize and mobilize against their governments.
• Maslow’s theory about the hierarchy of needs also plays a part: when lower needs – such as food, clothing and shelter – are met, then the preconditions are fulfilled for the appearance of higher needs. Higher education levels, because they help to fulfill lower needs, assist the appearance of needs such as self-actualization, self-esteem and belonging, needs that require freedom for their realization.
• Democracy requires a certain level of education among citizens in order to function properly. Of course, it’s not because B requires A that A results in B; claiming that education results in democracy because democracy needs education would mean committing a logical error. However, the fact that democracy needs education does probably increase the likelihood that democracy will follow from more education. At least the absence of some level of education will diminish the chances of democracy.
• And, finally, more education improves the capacity to make rational choices, and democracy is essentially a system of choice. Democracy will therefore intrinsically appeal to the higher educated.

And indeed, there is a correlation – albeit not a very strong one – between levels of education and degrees of democracy:

education and democracy correlation

###### (source)

The correlation may be due to the fact that democracies are better educators, but there are some reasons to believe that part of the causation at least goes the other way. Anecdotal evidence is provided by the recent Arab Spring: education levels in Arab countries have risen sharply in recent decades.

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# What is Democracy? (55): A System For Signaling Disapproval of the Economy

statistics cartoon by R. Crumb

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It’s the economy, stupid“. The famous phrase suggests that economic basics rather than social or cultural issues, politicians’ personal merit, foreign policy successes etc. determine democratic outcomes. People vote against incumbents when unemployment is high and GDP growth low, whatever the causes of the economic downturn. One can accuse George H.W. Bush of many things but he wasn’t by far the sole or main cause of the recession that propelled Clinton to power.

It seems that people use democratic elections – especially high profile one such as presidential elections – to signal disapproval of the economy, whatever the real responsibility of individual politicians for the state of the economy (it’s silly to assume that individual politicians, even American presidents, have the power to dramatically change the unemployment rate, for better or worse).

This graph shows a clear correlation between incumbent margins of victory in US presidential elections and changes in the unemployment rate:

incumbent margin of victory vs change in unemployment rate

###### (source, incumbents running for a second full term won when the unemployment rate was falling and they lost when it was going up)

The unemployment rate in 1980 was 7.2%, up considerably from the year before; Jimmy Carter duly lost his bid for reelection. In 1984, the unemployment rate was actually higher at 7.5%, but was on its way down from the previous year; Ronald Reagan was reelected in a landslide. (source)

Granted, the number of observations is low, too low to be certain about the correlation (and others have expressed doubts about the data).

Some more certainty is given by the fact that it’s not just unemployment but also income that is correlated with election results:

###### (source)

If we assume that the economy does indeed determine democratic outcomes in this way, then we face a problem because some of the traditional justifications of democracy become unavailable. Democracy is supposed to improve the quality of politicians: when a politician has to face popular judgment and has to pass the test of accountability, she will try harder to respect the will of the people, to avoid engaging in corruption and to generally do a good job, because doing so will convince the people that she deserves reelection. Also the freedom of the press is in part justified on this basis. A free press is able to give people the information about politicians necessary to make an informed judgment at the next election. Government transparency combined with accountability as a prerequisite for reelection provides politicians with the necessary incentives to do a good job, or at least a job that is considered good by an informed majority of public opinion.

If, however, democratic election results are determined less by the actual way in which politicians do their job than by the economic basics, then we lose this justification. If a politician won’t be reelected during an economic downturn, even if she does all that’s humanly possible to avoid it or lessen its impact, she has one less reason to do her best. She may still do her best out of a sense of responsibility or public service and remain unconcerned by electoral prospects, but we should not underestimate the motivation provided by the mere fact of having and retaining a position of power.

More posts in this series are here. More on signaling here, and on accountability here.

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# Statistical Jokes (29): Causation-Correlation Again

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Here’s a similar one:

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More on the causation-correlation problem here. More statistical jokes here.

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# Measuring Human Rights (13): When More Means Less and Vice Versa

I’ve said it a few times before in this blog series: human rights violations can make it difficult to measure human rights violations, and can distort international comparisons of the levels of respect for human rights. Country A, which is generally open and accessible and on average respects basic rights such as speech, movement and press fairly well, may be more in the spotlight of human rights groups than country B which is borderline totalitarian. And not just more in the spotlight: attempts to quantify or measure respect for human rights may in fact yield a score that is worse for A than for B, or at least a score that isn’t much better for A than for B. The reason is of course the openness of A:

• Human rights groups, researchers and statisticians can move and speak relatively freely in A.
• The citizens of A aren’t scared shitless by their government and will speak to outsiders.
• Country A may even have fostered a culture of public discourse, to some extent. Perhaps its citizens are also better educated and better able to analyze political conditions.
• Alexis de Tocqueville

• As Tocqueville has famously argued, the more a society liberates itself from inequalities, the harder it becomes to bear the remaining inequalities. Conversely, people in country B may not know better or may have adapted their ambitions to the rule of oppression. So, citizens of A may have better access to human rights groups to voice their complaints, aren’t afraid to do so, can do so because they are relatively well educated, and will do so because their circumstances seem more outrageous to them even if they really aren’t. Another reason to overestimate rights violations in A and underestimate them in B.
• The government administration of A may also be more developed, which often means better data on living conditions. And better data allow for better human rights measurement. Data in country B may be secret or non-existent.

I called all this the catch 22 of human rights measurement: in order to measure whether countries respect human rights, you already need respect for human rights. Investigators or monitors must have some freedom to control, to engage in fact finding, to enter countries and move around, to investigate “in situ”, to denounce etc., and victims should have the freedom to speak out and to organize themselves in pressure groups. So we assume what we want to establish. (A side-effect of this is that authoritarian leaders may also be unaware of the extent of suffering among their citizens).

A recent example of this catch 22 is here. This is also the reason why people often talk about a new set of human rights, namely the rights of human rights defenders.

You can see the same problem in the common complaints that countries such as the U.S. and Israel get a raw deal from human rights groups:

[W]hy would the watchdogs neglect authoritarians? We asked both Human Rights Watch and Amnesty, and received similar replies. In some cases, staffers said, access to human rights victims in authoritarian countries was impossible, since the country’s borders were sealed or the repression was too harsh (think North Korea or Uzbekistan). In other instances, neglected countries were simply too small, poor, or unnewsworthy to inspire much media interest. With few journalists urgently demanding information about Niger, it made little sense to invest substantial reporting and advocacy resources there. … The watchdogs can and do seek to stimulate demand for information on the forgotten crises, but this is an expensive and high risk endeavor. (source)

So there may also be a problem with the supply and demand curve in media: human rights groups want to influence public opinion, but can only do so with the help of the media. If the media neglect certain countries or problems because they are deemed “unnewsworthy”, then human rights groups will not have an incentive to monitor those countries or problems. They know that what they will be able to tell will fall on deaf ears anyway. So better focus on the things and the countries which will be easier to channel through the media (see also here and here).

Both the catch 22 problem and the problems caused by media supply and demand can be empirically tested by comparing the intensity of attention given by human rights monitoring organizations to certain countries/problems to the intensity of human rights violations (the latter data are assumed to be available, which is a big assumption, but one could use very general measures such as these). It seems that both effects are present but not much:

[W]e subjected the 1986-2000 Amnesty [International] data to a barrage of statistical tests. (Since Human Rights Watch’s early archival procedures seemed spotty, we did not include their data in our models.) Amnesty’s coverage, we found, was driven by multiple factors, but contrary to the dark rumors swirling through the blogosphere, we discovered no master variable at work. Most importantly, we found that the level of actual violations mattered. Statistically speaking, Amnesty reported more heavily on countries with greater levels of abuse. Size also mattered, but not as expected. Although population didn’t impact reporting much, bigger economies did receive more coverage, either because they carried more weight in global politics and economic affairs, or because their abundant social infrastructure produced more accounts of abuse. Finally, we found that countries already covered by the media also received more Amnesty attention. (source)

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# Capital Punishment (32): Use of Death Penalty Continues to Decline in the U.S.

Some fresh data for 2010:

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More on capital punishment is here (more data are here).

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# Measuring Poverty (12): The Experimental Method

###### (source, photo by Richard Sclove)

The so-called experimental method of poverty measurement is akin to the subjective approach. Rather than measuring poverty on the basis of objective economic numbers about income or consumption the experimental method uses people’s subjective evaluation of living standards and living conditions. But contrary to the usual subjective approach it’s aim is not to ask people directly about what poverty means to them, about what they think is a reasonable minimum level of income or consumption or a maximum tolerable level of deprivation in certain specific areas (food, health, education etc.). Instead, it uses experiments to try to gather this information.

For example, you can set up a group of 20 people from widely different social backgrounds and some of them may suffer from different types of deprivation, or from no deprivation at all. The group receives a sum of money and has to decide how to spend it on poverty alleviation (within their test group or outside of the group). The decision as to who will receive which amount of funding targeted at which type of deprivation has to be made after deliberation and possibly even unanimously.

The advantage of this experimental approach, compared to simply asking individual survey respondents, is that you get a deliberated choice: people will think together about what poverty means, about which types of deprivation are most important and about the best way to intervene. It’s assumed that such a deliberated choice is better than an individual choice.

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# Racism (14): Race and Consumer Behavior

The iPod family

Some time ago, I’ve cited a study showing evidence of racist sorting by people looking for a job (white job seekers often avoid working for black managers, and white workers quit their jobs more rapidly when a white manager is replaced with a black manager). A similar phenomenon is race discrimination by buyers.

Do buyers discriminate based on race? This column describes an experiment in the US that advertised iPods online from black and white sellers. Black sellers received fewer offers at lower prices, doing better in markets with competition amongst buyers and worse in high-crime markets. The authors find evidence of both statistical and taste-based discrimination. … [I]t appears that discrimination may not “survive” in the presence of significant competition among buyers. Furthermore, black sellers do worst in the most racially isolated markets and markets with high property crime rates, suggesting a role for statistical discrimination in explaining the disparity. (source)

The important question is indeed to what extent this “sorting” on the part of buyers is motivated by statistical discrimination or by taste-based discrimination:

• Statistical discrimination means that race is used as a proxy for unobservable negative characteristics, maybe in this case a judgment about the probability that black sellers will be happy with a marginally lower sales price, given their statistically higher rates of poverty. Or perhaps there’s distrust based on unclear statistical judgments about the risk of buying fake or stolen goods, meeting sellers in an inconvenient or dangerous neighborhoods, or dealing with unreliable sellers who might not complete the transaction.
• Taste-based discrimination occurs when people just don’t like dealing with black people for no particular reason apart from the difference in race.

The study cited above uses a number of clever ways to disentangle these two effects. For instance, the inclusion of white tattooed sellers, who also received fewer and lower purchase offers, suggesting that part of the differences are due to statistical discrimination. Another part, however, is just plain racism. Black sellers are at a significant disadvantage on average, and that’s due to both statistical and taste-based discrimination.

More on statistical discrimination here.

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# Statistical Jokes (17): The Illusion of Precision

Gabriel García Márquez

If you say that there are elephants flying in the sky, people are not going to believe you. But if you say that there are four hundred and twenty-five elephants in the sky, people will probably believe you. Gabriel García Márquez

Statistics give the impression of precision. Giving people a number does indeed make a statement seem more plausible. In reality, of course, statistical numbers often serve to obfuscate or to lie. And even if they don’t we often forget that they are mere estimates and extrapolations with margins of errors, and that they are often based on very messy data collection procedures and a lot of assumptions.

More statistical jokes.

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# Statistical Jokes (16): Statistics on the Skill-Luck Continuum

There’s something to this one, although I wouldn’t say statistics are merely a tiny fraction better than gambling and pure chance (but don’t ask me the size of the real fraction):

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More statistical jokes here. More serious stuff about statistics is here.

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# Human Rights Maps (92): Income Inequality in the U.S., 1969-2007

Income inequality is a human rights issue (if you’re not convinced, go here or here first). Here are a few maps about income inequality in the U.S., in addition to some older posts on the same subject (see here, here, and here).

income inequality in the US, 1969-2007

###### (source, click on the image to enlarge; a higher Gini value means more inequality)

You can clearly see the maps becoming darker over time, and also the shifting of inequality across the country.

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However, if you take the global view and move away from the U.S., income inequality has actually gone down over time. See here. More maps on income inequality are here. Something on the related concept of relative poverty is here. And more human rights maps are here.

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# Why Do Countries Become/Remain Democracies? Or Don’t? (13): Prosperity

I already mentioned in a previous post how democracy is correlated with prosperity. There’s a much higher proportion of democracies among rich countries than among poor countries. The level of national income is the most important factor explaining inter-country variations in the degree of democracy. If we assume from this correlation that there is a causal link from prosperity to democracy, then low income is the most important barrier to democracy. But the causal link probably goes in both directions. Countries aren’t just democratic – or remain so – because they prosper (among other reasons), but it’s also the case that countries prosper to some extent because they are democratic (disproving the often heard claim that economic development requires authoritarian government). I gave an overview of the reasons why prosperity promotes democracy here, and why the opposite is also the case here.

The correlation between democracy and prosperity is obvious from this graph (at least for non-Muslim countries):

###### (source)

The stronger one of the causal links seems to be the one going from prosperity to democracy rather than vice versa. If you accept that, there’s an additional question (it’s one made famous by Przeworski and Limongi): are there more democracies among rich countries than among poor countries

• because economic development increases the likelihood that countries will undergo a transition to democracy (this is often called modernization theory), or
• because economic development makes democracies less likely to fall back into dictatorship?

Przeworski and Limongi found that affluence makes it very unlikely that a shift from democracy to dictatorship occurs, while Boix and Stokes find that there is an effect of affluence on the likelihood of a shift to democracy. Both effects are visible in this graph:

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It’s likely that the economic effect on transition towards democracy is a bit smaller than the effect halting the opposite transition. The reason is probably the fact that the transition from democracy to authoritarianism is in se much easier than the other way around. Some even say that democracy is inherently suicidal. Whatever the merits of that claim, it’s obvious that an authoritarian leader has the resources and the necessary lack of scruples to cling to power. Especially when his country becomes more prosperous. He can then use this prosperity to bribe the population into submission, and buy the arms and security forces when this doesn’t work.

Again, economic development isn’t a sufficient or even necessary prerequisite for democracy to appear or to survive. Things are more complicated than that and many other factors are in play, including conscious human activity and volition. People can decide to make or destroy a democracy at any level of economic development.

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# Religion and Human Rights (28): Is Religion Particularly Violent?

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9/11 and other terrorist attacks apparently motivated by Islamic beliefs has led to an increased hostility towards Islam, but also towards religion in general. Perhaps in an effort to avoid the charge of islamophobia, many anti-jihadists have taken a new look at the violent history of other religions, particularly Christianity, and concluded that religion per se, because of the concomitant belief in the absolute truth of God’s words and rules, automatically leads to the violent imposition of this belief on unwilling fellow human beings, or – if that doesn’t work – the murderous elimination of persistent sinners. This has given rise to a movement called the new atheists. The charge of fanatical and violent absolutism inherent in religion is of course an old one, but it has been revitalized after 9/11 and the war on terror. I think it’s no coincidence that many of the new atheists are also anti-jihadists (take Christopher Hitchens for example).

There are many things wrong with question in the title of this blogpost. (And – full disclosure – this isn’t part of a self-interested defense of religion, since I’m an agnostic). First of all, it glosses over the fact that there isn’t such a thing as “religion”. There are many religions, and perhaps it can be shown that some of them produce a disproportionate level of violence, but religion as such is a notoriously vague concept. Nobody seems to agree on what it is. Even the God-entity isn’t a required element of the definition of religion, except if you want to take the improbable position that Buddhism isn’t a religion. All sorts of things can reasonably be put in the container concept of “religion” – the Abrahamic religions as well as Wicca and Jediism. The claim that “religion is violent” implies that all or most religions are equally violent, which is demonstrably false.

cartoon by Ares

That leaves the theoretical possibility that some religions are more violent than others. If that claim can be shown to be true, islamophobia may perhaps be a justified opinion, but not the outright rejection of religion inherent in new atheism (which, of course, has other arguments against religion besides religion’s supposed violent character). However, how can it be shown empirically and statistically that a certain religion – say Islam – is relatively more violent than other religions? In order to do so you would need to have data showing that Islam today (or, for that matter, Christianity in the age of the crusades and the inquisition) is the prime or sole motive behind a series of violent attacks. But how do you know that the violent actor was motivated solely or primarily by his religious beliefs? Because he has a Muslim name? Speaks Arabic? Looks a certain way? Professes his religious motivation? All that is not enough to claim that he wasn’t motivated by a combination of religious beliefs and political or economic grievances for instance, or by something completely unconnected to religion, despite his statements to the contrary.

Now let’s assume, arguendo, that this isn’t a problem, and that it is relatively easy and feasible to identify a series of violent attacks that are indisputably motivated solely or primarily by certain religious beliefs. How can you go from such a series to a quantified comparison that says “the religion behind this series of attacks – say again Islam – is particularly violent”? That seems to be an unwarranted generalization based on a sample that is by definition very small (given the long history of most religions and the lack of data on motivations, especially for times that have long since passed). Also, it supposes a comparison with other causes of violence, for example other religions, other non-religious belief systems, character traits, economic circumstances etc. After all, the point of this hypothetical study is not to show that (a) religion can lead to bad things. That’s seldom disputed. Everything can lead to bad things, including fanatical atheism (and don’t tell me communism and fascism were “really” religions; the word “religion” is vague, but probably not as vague as that – which doesn’t mean that there aren’t any religious elements in those two world-views). The claim we’re discussing here is that (a) religion – because of its fanatical absolutism and trust in God’s truth – is particularly violent, i.e. more violent than other belief systems, and hence very dangerous and to be repudiated.

cartoon by Christo Komarnitski

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I think it’s useless, from a purely mathematical and scientific point of view, to engage in such a comparative quantification, given the obvious problems of identifying true motivations, especially for long periods of time in the past. There’s just no way that you can measure religious violence, compare it to “other violence”, and claim it is more (or less) violent. So the question in the title is a nonsensical one, I think, even if you limit it to one particular religion rather than to religion in general. That doesn’t mean it can’t be helpful to know the religious motives of certain particular acts of violence. It’s always good to know the motives of violence if you want to do something about it. What it means is that such knowledge is no reason to generalize on the violent nature of a religion, let alone religion as such. That would not only obscure other motives – which is never helpful – but it would also defy our powers of quantification.

More on religious violence here, here and here. More on violence in general here. Also interesting perhaps is this look at pacifism and anti-violence in religion.

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# Income Inequality (22): Social Mobility in Anglo-Saxon Economies, Ctd.

After completing my older post on the subject – in which I argued that Anglo-Saxon economies don’t do a very good job promoting social mobility despite the focus on individual responsibility and policies that (should) reward merit (e.g. relatively low tax rates) – I found this graph which I thought would illustrate my point:

###### (source)

Although the US and other Anglo-Saxon countries aren’t in the graph, the UK is. And the effect of parental education on child earnings in the UK is particularly large. The children of the well-off and well-educated earn more and learn more than their less fortunate peers in all countries in the world, and that’s hardly surprising given the importance of a head start, both financially and intellectually. What is surprising is that this is less the case in countries which pride themselves on their systems that offer people incentives to do well (low taxes, minimal safety nets etc.).

So one wonders which fact-free parallel universe David Cameron, the new UK Prime Minister, inhabits:

The differences in child outcomes between a child born in poverty and a child born in wealth are no longer statistically significant when both have been raised by “confident and able” parents… What matters most to a child’s life chances is not the wealth of their upbringing but the warmth of their parenting. (source, my emphasis)

Extolling the virtues of good parenting can never hurt, except if you have a low boredom threshold because it’s so goddamn obvious. But making it sound like parents’ wealth or education are “insignificant” is truly grotesque and an insult to those poor parents who have children that aren’t doing very well. And even for those living in the alternative reality where only bad parents keep children back, the Conservative leader’s position in fact, and unwittingly, should lead to left-wing policies, as Chris Dillow points out:

Because of bad parenting – which begins in the womb – some people do badly in school and therefore in later life; they are less likely to be in work, and earn less even if they are. However, we can’t choose our parents; they are a matter of luck. It’s quite reasonable to compensate people for bad luck, so there’s a case for redistributing income to the relatively poor, as this is a roundabout way of compensating them for the bad luck of having a bad upbringing.

High levels of social mobility can compensate for high levels of income inequality: if people can be socially mobile, and if their earnings and education levels don’t depend on who their parents are but on their own efforts and talents, one can plausibly claim that the existing inequalities are caused by some people’s lack of effort and merit. However, the UK and the US combine two evils: low mobility and high inequality, making it seem that whatever effort you invest in your life, you’ll never get ahead of those rich lazy dumb asses. So why would you even try? Low mobility solidifies high inequality.

Just to show that the U.S. isn’t better than the U.K.:

Parental income is a better predictor of a child’s future in America than in much of Europe, implying that social mobility is less powerful. Different groups of Americans have different levels of opportunity. Those born to the middle class have about an equal chance of moving up or down the income ladder, according to the Economic Mobility Project. But those born to black middle-class families are much more likely than their white counterparts to fall in rank. The children of the rich and poor, meanwhile, are less mobile than the middle class’s. More than 40% of those Americans born in the bottom quintile remain stuck there as adults. (source)

More on social mobility.

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# Human Rights Quote (78): Prison Abuse

I often discuss the human rights implications of incarceration: prison rape, overpopulation in prisons, juvenile incarceration, racism in incarceration rates, the social cost of incarceration, voting rights for felons and other related issues regularly make an appearance here.

Here are two other fine quotes admonishing the violence that occurs in prisons, even in so-called developed countries, and the high incarceration rates in the U.S.:

Prison will always be prison: Every society has to live with some level of institutional violence in the worlds it builds to confine its most dangerous elements, and there’s an inherent cruelty to incarceration that cannot be refined away. But there has to be a limit, as well. And what Americans have learned to tolerate (or rather, ignore) inside the walls of jails and prisons ought to churn our stomachs, shock our consciences, and produce not only outrage, but action. Ross Douthat (source)

Sentences in the United States are eight times longer than those handed out in Europe, Justice Kennedy said. California has 185,000 people in prison at a cost of \$32,500 each per year, he said. He urged voters and elected officials to compare taxpayer spending on prisons with spending on elementary education. Justice Kennedy took special aim at the three-strikes law, which puts people behind bars for 25 years to life if they commit a third felony, even a nonviolent one. The law’s sponsor, he said, is the correctional officers’ union, “and that is sick.” (source)

Some prison statistics here (not only for the U.S.).

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# Gender Discrimination (22): Gendercide

The Economist has a front page story this week on “gendercide”, the millions of girls missing in the world, especially in India and China. Perhaps as many as 100 million girls have disappeared in the last decades because of

• selective abortions encouraged by new medical technology (ultrasounds and fertility technology)
• childhood neglect of girls (nutritional, educational neglect and neglect in health care)
• prejudice, preference for male offspring and
• population policies such as the “one child policy” in China.

I’ve written about this several times before (see here, here and here), and even called it a “boomerang human rights violation“: the skewed sex ratios that result from gendercide (in some areas of China, 130 boys are being born for every 100 girls) are coming back to haunt the men that are responsible (although many mothers probably aren’t without fault either). Because of their relative scarcity, women have found an unlikely source of power. They have a competitive advantage in the marriage market, and can demand more in marriage negotiations, or at least be more selective when choosing a mate.

#### Causes

In my view, the word “gendercide” is somewhat overwrought because, contrary to genocide, the word that inspired the neologism of gendercide, there’s no centralized plan to exterminate women. Femicide would be a better term since it’s obviously only one of two genders that’s targeted, but it still sounds like a government organized campaign of extermination. Gendercide is the result of a combination of causes:

• individual choices based on
• plain prejudice against girls
• cultural and legal traditions, or
• economic incentives that have been formed by historical prejudice.

Perhaps girls still need a dowry, and poor parents may find it difficult to save enough and hence prefer a boy. Or perhaps they prefer a boy because the law of their country or tribe – inspired by age-old prejudice – says that only boys can inherit land or the family business. Again, the parents may prefer a boy for this reason, not because they dislike girls. Or perhaps tradition holds that girls marry off into their husbands families, and parents simply want to be sure to have someone in their home to care for them when they are old (“raising a daughter is like watering your neighbor’s garden”, is a Hindu saying).

#### Consequences

The consequences of gendercide are mixed. It’s obviously horrible to the girls that are aborted or neglected to death. But, as in the “boomerang” case cited above, gendercide may ultimately empower women. However, the skewed sex ratios also spell trouble: the presence of armies of men who can’t find wives and have children (“bare branches” or “guanggun” they are called in China) may result in more sexual violence, depression, suicide, human trafficking etc. It’s estimated that in 10 years time, one in five young Chinese men won’t be able to find a bride. On the other hand, a shortage of women will encourage immigration, and immigration may help some women escape poverty, and perhaps will also result in more intercultural tolerance.

#### Solutions

Economic development won’t stop it. In China and India, the regions with the worst sex ratios are wealthy ones, with educated populations. Even in some population strata in the U.S. sex ratios are skewed. When people escape poverty, fertility rates drop, and when families have fewer children, the need to select for sex only becomes more important in order to realize their son preference. In poor societies with high fertility rates, families are almost destined to have a boy at some point. Female children will suffer relative neglect and may die more often and more rapidly (skewing the sex ratios), but selective abortions aren’t much of a risk: families don’t really feel the need to limit the number of children (on the contrary often, because children are a workforce), and ultrasound technology for sex determination of fetuses isn’t as readily available as in rich countries or regions. When families want few children – as they do in more developed regions – or are forced by the government to limit their number of children (as in China), they will abort female fetuses in pursuit of a son.

Ultimately, only a cultural change will help. The son preference has to die out. Education probably will help, as it always does. Ending pernicious policies such as the one child policy will also help, but then overpopulation hysterics will have to be dealt with. This policy didn’t help stop population growth anyway. Other East Asian countries reduced population pressure as much as China without brutal policies.

Old customs and discriminating laws should also be abolished. Think of the dowry system, or inheritance rights. Stigmatizing abortion, especially sex selective abortion, will also help.

More on gender discrimination, on prejudice, on India, and on China.

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# Measuring Poverty (5b): Poverty in Africa

Here‘s an interesting paper by Sala-i-Martin and Pinkovskiy on the evolution of poverty in Africa, and it contains exciting news: African poverty is falling and is falling rapidly since 1995 (this contradicts some older research). Moreover, this evolution is remarkably general across African countries, and not just explained by good news in a few large countries. Poverty is falling even in countries which are believed to burdened by geography, bad agricultural prospects, a history of slave trade, war, or lack of natural resources. And, to make the good news complete: income inequality has also decreased, and the Millennium Development Goal of halving the proportion of people earning less than \$1 a day will be achieved on time.

You can see the reduction of the poverty rate in Africa in the graph below. From a “high point” of almost 45% of the population surviving on less than \$1 dollar day in the late 1980s, that rate has fallen to 32% in 2006. How come? As you can also see in the graph, at the time poverty began to decline around 1995, GDP began to grow (after three decades of zero or negative growth). The graph shows a striking correlation between poverty reduction and economic growth, something I have written about before in another context, see here and here).

###### (source)

Of course, poverty reduction isn’t the automatic result of GDP growth only. Other factors are at work as well, but the paper is silent about those.

What’s interesting is that this African growth spurt since 1995 (probably briefly interrupted by the current recession) isn’t just caused by growing oil prices. If that had been the case, we would have seen increasing income inequality, since revenues from the oil industry are typically appropriated by elites. But that’s not the case. Poverty reduction has gone hand in hand with a reduction in income inequality. You can see the extent of this reduction in the following two graphs from the paper:

###### (source)

This means that growth has benefited the poor. However, although the reduction in poverty is impressive, it’s not quite as impressive as poverty reduction in China.

More on poverty measurement. More poverty statistics. More on Africa.

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# Political Jokes & Funny Quotes (75): The Importance of Race

This is not about how important race actually is in the minds and behavior of many, but about how important it should be. On a more serious note, here are some data on how people really think about race.

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# Statistical Jokes (8): Polls Messed Up By Self-Selection

###### (source)

I think point 3 in this cartoon is extremely relevant. A lot of polls, especially internet polls, are completely ruined by self-selection. I explained here why that’s a problem and what the consequences can be (for instance, political polarization and “gladiator politics“).

More statistical jokes here. More serious discussion of statistics here.

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human rights maps

# Human Rights Maps (79): Numbers of Firearm Deaths in the U.S.

number of firearms deaths in the US

###### (source)

And this is the map for 2007:

number of deaths due to injury by firearms US

###### (source, these include accidental shootings, suicides, acts of self-defense, as well as crimes)

Here are some numbers for the rest of the world:

###### (source)

homicide by firearm, rate per 100000 population

percentage of homicides by firearm

###### (source)

More maps on violence. View all human rights maps. More textual information on violence here and here. Statistics on violence are here. Something on gun control and the arms trade.

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# Racism (10): Race and Health

In a previous post, I highlighted the fact that African Americans in the U.S. are more likely to die of cancer. It seems that a similar disparity exists for strokes and lead poisoning.

Many ethnic groups have a higher death rate from stroke than non-Hispanic whites. Although the death rate from stroke nationwide dropped 70% between 1950 and 1996, minorities the decline was greatest in non-Hispanic whites. The greatest number of stroke deaths compared to whites occurred in African-Americans and Asians/Pacific Islanders. Excess deaths among racial/ethnic groups could be a result of a greater frequency of stroke risk factors, including obesity, hypertension, physical inactivity, poor nutrition, diabetes, smoking and socioeconomic factors such as lack of health insurance. (source)

###### (source)

Lead poisoning causes, i.a., cognitive delay, hyperactivity, and antisocial behavior.

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# Human Rights Maps (75): Military Spending Worldwide, as Percentage of GDP and of World Total

Some data for the year 2008:

Military Spending Worldwide as Percentage of GDP and of World Total

###### (click on the image to enlarge)

And this is for the year 2010:

military spending as percentage of GDP

military spending, total

###### (source)

More on military spending (or “defense” spending) here. Some statistics here. More maps here.

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# The Causes of Poverty (30): Lack of Economic Growth

As stated in a previous post on the same subject, when a country achieves a certain level of economic growth – or, more precisely, rising levels of GDP per capita because economic growth as such can be the result of rising population levels – it is assumed that this reflects a higher average standard of living for its citizens. Economic growth is therefore seen as an important tool in the struggle against poverty (if you wonder why poverty is a human rights issue, go here). If a country is richer in general, the population will also be richer on average. On average meaning that GDP growth isn’t necessarily equally distributed over every member of the population. That is why GDP growth isn’t sufficient proof of poverty reduction. Separate measurements of poverty and inequality are necessary.

So in theory, you can have GDP growth and increasing levels of poverty, on the condition that GDP growth is concentrated in the hands of a few. However, that’s generally not the case. GDP growth benefits to some extent many of the poor as well as the wealthy, which is shown by the strong correlation between poverty reduction and levels of GDP growth (always per capita of course). It’s no coincidence that a country such as China, which has seen strong GDP growth over the last decades, is also a country that has managed to reduce poverty levels substantially.

Unfortunately, growth isn’t a silver bullet. Poverty is a complex problem, requiring many types of solutions. Promoting economic growth will do a lot of the work, but something more is required. In a new paper, Martin Ravaillon gives the example of China, Brazil and India. The levels of poverty reduction in these three countries, although impressive, do not simply mirror the levels of economic growth. Although half of the world’s poor live in these three countries, in the last 25 years China has reduced its poverty level from 84% of the population in 1981 to just 16% in 2005 (see chart below). China is exceptional, but Brazil also did well, cutting its rate in half over the same period (8% of Brazilians still live on less than \$1.25 a day). Regarding India, there are some problems with its statistics, but whichever statistic you use, there’s a clear reduction.

poverty reduction in China, India and Brazil

###### (source)

Ravaillon points out that the intensity of poverty reduction was higher in Brazil than in India and China, despite lower GDP growth rates.

Per unit of growth, Brazil reduced its proportional poverty rate five times more than China or India did. How did it do so well? The main explanation has to do with inequality. This (as measured by the Gini index, also marked on the chart) has fallen sharply in Brazil since 1993, while it has soared in China and risen in India. Greater inequality dampens the poverty-reducing effect of growth. (source)

Which is rather obvious: higher levels of income equality means a better distribution of the benefits of growth. So the “pro-growth strategy” against poverty is important but not enough, and should be combined with Brazilian type anti-inequality measures (focus on education, healthcare and redistribution).

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# Capital Punishment (24): The Probability of Capital Punishment in the U.S., by Race

The U.S. population is about 300,000,000. Whites represent about 80%, or roughly 240,000,000. If you check the numbers of executions in the U.S., you’ll see that there were about 1,000 in the period from 1977 to 2005. 584 of those executions were of whites. That’s about 20 executions per year on average, meaning that whites have a chance of 1 in 12,000,000 of being executed.

There are about 40,000,000 African Americans, representing roughly 13 % of the U.S. population. 339 executions in the 1977-2005 period were of African Americans. That’s about 12 a year, meaning that blacks have a chance of 1 in 3,300,000 of being executed.

A black person in the U.S. is therefore almost 4 times more likely to be executed. Even if we assume that this higher probability of being executed correctly reflects a higher probability of being involved in crime that comes with capital punishment – and that’s something we shouldn’t assume, because it’s likely that there are injustices involved, e.g. inadequate legal representation and such – that shouldn’t put our minds at ease. We then still have to ask the question: why are blacks more likely to be involved in capital offences? Surely not because of their race. Something happens in society that leads to this outcome, and it’s likely that there are injustices involved: for example, inadequate education, poverty levels, discrimination etc.

More statistics on capital punishment are here. More statistics on racism are here. My opinion on capital punishment is here.

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