One thing that has bothered me, or at least piqued my interest, are two seemingly contradictory facts:

1) Many regions & nations have seen a resurgence of religion in the past generation (i.e., 1980s to 2010). The post-Communist and Islamic world most prominently. There is quantitative data for the post-Communist world, while for the Islamic world it is more impressionistic (e.g., the shift toward more stark outward "conservatism" in dress among the young).

2) But The World Values Survey does not show a skew toward religiosity among the young for most nations. Very few in fact. This is a bit curious in light of some plausible background assumptions. For example, religious people have more children the world over within each nation (though religiosity at the national level may have a more unpredictable relationship to fertility, as evident in Western Europe).

I decided to present the data which I'm basing the second assertion on. The WVS has several "waves." I decided to look at wave 5, wave 4 and wave 2, which were done during the mid to late 2000s, around 2000 and 1990 respectively. I also looked at the question:

How important is God in your life? Please use this scale to indicate- 10 means very important and 1 means not at all important.

The WVS interface outputs mean values (as well as standard deviations). You can then drill-down and cross with age of the respondents in 3 classes:, 15-29, 30-49, and 50+. I was curious as to age related changes, so I simply put the mean values of the importance of God by age class into the linest function. So, if the mean values were 7, 8 and 9 for the age classes from youngest to oldest, the linest would output a slope of 1 as I omitted x values (so the classes would be recoded implicitly as 1, 2, 3, etc. for x's). If you reversed it, it would output -1. So, negative values indicate that the younger are more religious than the old. Here are some trends in the data.....

Here are some charts ordered by the values generated by linest by wave. The countries at the top exhibit larger differences between the young and old. Observe the large asymmetry in the number with positive vs. negative values (that is, many more nations have more secular young than old). You need to click to see the larger version.





Some of the nations span the waves (many do not). 30 nations span wave 5 and wave 4. Here are the correlations between the same columns across waves:

Mean religiosity = 0.98
Trend of religiosity by age = 0.84

I don't know if the samples are representative (though the developed world ones do seem to be, I've checked with independent surveys and they often match up well), but the two waves seem consistent with each other here.

Now let's compare wave 2 and wave 5. So from from ~1990- to ~2005.

Mean religiosity = 0.92
Trend of religiosity by age = 0.77

How about differences in mean religiosity from wave 2 to wave 5? Here we see a bias toward greater religiosity in the 26 countries found in both waves.



The results match expectation. The nations to the right, those which have seen the most increase in religiosity are post-Communist ones. No surprise there. The nation furthest to the left is Spain, it's gone through the most striking shift toward secularism since 1990. That is in line with what the news reports, the position of the Catholic Church at the center of Spanish life has been collapsing since the 1980s (more accurately, since the end of the Franco regime).

One assumes that the difference in religiosity by age cohort is a feature of less religious societies. If everyone is religious, as is the case in some Muslim and African countries, then there can't be any variance. Merging all 3 waves together, here's a scatter plot which shows the trend:



Now a labelled plot of wave 5.



An interesting point of contrast is China and Spain. In the 1970s Spain was still a pro-clerical right-wing authoritarian regime, while China was an atheist left-wing regime. Political pressures toward conforming to a particular attitude toward religion have abated in both nations over the past generation, and while Spain has become much more secular, China seems to more religious. The mean value of the importance of God in one's life in China is 3.7 in the youngest age group, and 3.5 in the oldest (survey taken in 2007). In 1990 it was 1.5 and 1.8 respectively.

The big test would be to see how the 15-29 compared to 30-49 between wave 2 and wave 5. I'm a little worn out by this right now, so I'll look at that systematically tomorrow (or the next day), but spot checking Russia seems to show that the rank-order holds, but all age cohorts became more religious (not relevant for the youngest cohort in wave 5 because they weren't surveyed in 1990). In Spain the 15-29 year olds in wave 2 who became 30-49 year olds in wave 5 are invariant. If you want to get a jump ahead of me, here are some raw data file (excel):

religwave2.xls

religwave4.xls

religwave5.xls

Here are two preliminary comments:

* All the post-Communist nations have seen a resurgence in religion (perhaps with the exception of the Czech Republic). But this is a phenomenon which has "lifted all boats," older people who were militant atheists who went on anti-religious rampages in their youth have been swept along, just as generations who barely remember Communism exhibit the nominal culturally grounded religious sensibilities normal in many societies. I've read a fair number of news stories over the years about the generational "God-gap" in the post-Communist states, but I suspect that it makes a punchier story-line than to suggest that there's been a broader societal shift. That it isn't a case of atheistic pensioners vs. youthful churchgoers.

* The Muslim countries are really weird. On most of the religious data in the WVS the only nations which approach or surpass them consistently are the African ones, and these do not exhibit the uniformity of outlook of the Muslim ones, especially the "core" Muslim nations of the Middle East. In some of the surveys for Pakistan no Pakistanis in a sample of 2,000 will admit to not believing in God, and in one survey all the respondents gave the highest value for the importance of God in their life on a 1 to 10 scale. By all, I mean all 2,000. It isn't implausible to me that somehow someone who was really religious just recoded the survey data to make Pakistan seem more religious than it was, but if so that bespeaks a zealous conformity of outlook in the society. But overall many of the Muslim nations are so religious that there isn't variation in belief by age group because there isn't variation much of belief, period. Everyone's on the same page. When you see women donning the hijab or men growing beards I think perhaps we should reconceptualize what's going on, as it isn't renewed orthodoxy (belief) as opposed to a change in orthopraxy. Of course it may be that Muslim nations do exhibit variation in religiosity, but they're just off the scale here. I suspect of the funniest shock-documentary projects would be to have someone run into a public square in the Muslim world screaming that God is dead. Of course, it might be a suicide mission!

Labels: data, Religion

A friend pointed me to this article in Slate which noted:

This size bias may ultimately play out along party lines. The last presidential election revealed a startling overlap between statewide obesity figures and support for the GOP. Despite losing in a landslide, John McCain carried all nine of the fattest states in the union and 16 of the top 20. (Obama prevailed in 17 of the 20 thinnest states, including New Jersey.) In the race for governor of a very blue state, Christie's girth marks him as an outsider-a member of the chunky-monkey Fox News demographic, the kind of guy who rides around in an SUV and eats Double Down sandwiches. If Christie stands in for America's boorish consumer culture, then Corzine-slender, bearded, and bespectacled-represents the cosmopolitan elite.

The issue though is that black Americans are more obese, and extremely black states exhibit a lot of racial polarization whereby McCain actually those states. My friend wondered if I could look on a more granular level. If I could find obesity data on all the counties in the nation, that would be easy, but I didn't find that. But, I did find obesity data for race, so the proportion of each state which are classified as obese who are non-Hispanic white, as well as exit polls of the white vote for McCain. The scatterplot below shows the outcome.



What about individual level data? In 2004 there was a variable which was interviewer perception of weight. Here's what the GSS says:




The 95% confidence intervals are their, including the N's. Not much difference. Perhaps the sample size is too small to tell, or perhaps how interviewers perceived people differed from region to region. I limited the sample to Non-Hispanic whites. Here's the variables:

Row: INTRWGHT(r:1 "Below Average"; 2 "Average"; 3-4 "Above Average")
Col: partyid(r:0-2 "Democrat";3 "Independent"; 4-6 "Republican") polviews(r:1-3 "Liberal";4 "Moderate" ;5-7 "Conservative")

Oh, and about fat people voting for fat candidates. I think the issue is that many fat people imagine that one day they won't be fat, so it's hard to create an identity around something you want to escape, and think you can, with enough hard work, or a miracle drug, or gastric bypass.

Labels: data, politics

The New York Times has a piece, The Divided States of Health Care:

Those who lack health insurance now are far more likely to live in states that usually vote Republican — the states whose senators and representatives are least likely to support a law to extend coverage.

That would seem to indicate that Republican constituents are the ones who would most benefit from passage of universal health insurance coverage. But an analysis of Congressional districts within those states indicates that those without health insurance are much more likely to live in strongly Democratic Congressional districts. Many of those contain large minority populations with relatively low incomes.

This is not a surprising finding. Some of the most Democratic districts due to variables of race & income are in "Red States." The text alludes to more granular analysis, but it doesn't show up in the graphics, which is focused on the state level. But the county level data is freely available from the Census. To the left is a map of uninsured (those 18-64) by county. It does seem to me that state regulations or policies have some influence, look at the Pennsylvania-Ohio border with Kentucky and West Virginia, and Pennsylvania's border with New York. Culturally the Appalachian areas of Pennsylvania are extensions of West Virginia. Or look at the Missouri-Iowa border. But we can do more than just look at maps. Let's compare the county-by-county variation against other metrics. For example, how about voting for this year's Nobel Peace Prize recipient in the fall of 2008. What's the correlation?


I was a little surprised when I got a correlation of -0.33. That is, a negative correlation for voting for Barack Obama and proportion of uninsured on the county level. This assumes a level of linearity which really isn't there when you look more closely. You can see in the scatterplots at the bottom of this post, but let's just go with the linear for the moment so I can stick to correlations; you can correct by looking at the loess curves later on. Here are some other correlations with the proportion uninsured in each county (most of the dta are from the American Community Survey 2005-2007 of the Census, the "Foreign Born Males" data are for males over the age of 18):


-.36 - White (not Latino)
0.07 - Black (not Latino)
0.48 - Latino
0.43 - Foreign Born Males
-.29 - Age
-.24 - Median Household Income (2006)
-.15 - Median Home Value (2006)

I was a little curious about the lack of correlation with health insurance for blacks, but this from the Census clears it up:

At 89.4 percent, non-Hispanic Whites were more likely to have health insurance coverage than any other racial group. Those reporting 'some other race' were the least likely to have coverage, 66.0 percent [most of 'some other race' are probably Latino -Razib]. The health insurance coverage rates for the remaining single-race groups fell in that range - 85.5 percent for Asians, 83.8 percent for Native Hawaiians and Other Pacific Islanders, 82.0 for Blacks, and 68.4 percent for American Indians and Alaska Natives. The health insurance coverage rate for Hispanics was 68.5 percent.

This includes both private health insurance and public health insurance (Medicaid) for those under 65. Look at the map for those at or below 200% of the poverty rate. It looks like Medicaid is covering many people in the Black Belt, while regions in Appalachia which aren't quite as destitute in northern Alabama and Mississippi are relatively underinsured. The Census also reports that those ages 18-24, and 25-34, have coverage rates of 71.4 and 73.3 respectively, before jumping up to nearly 81% in the 35-44 range. For non-citizens the rate is around 50%.

How about limiting the data set to those counties where 90% of the population is white, not hispanic. That leaves 1477 counties in the data set.

-.48 - Obama
-.30 - Income
-.12 - Home Value

As you can see, in very white counties the inverse relationship between proportion uninsured and proportion voting for Barack Obama holds. I played around with limiting geographically. In New England and Tennessee there's no correlation between voting for Obama and insurance rates. But New England had really uniform voting. Tennessee might be a special case where lower insurance coverage rates among blacks are at play. In California and Texas the lack of insurance among Latinos positive correlations between voting for Obama and underinsurance, but only on the order of ~0.10.

I'm a little confused by these results. You can get the original data as a csv and see if I switched the sign or did something wrong. I wouldn't be surprised. My general model though is that this is a case of:

1) The Dems tending to get high and low socioeconomic status groups (not necessarily the super-rich, but the middle and upper-middle class college-educated).

2) The poor get insurance through Medicaid. And public sector workers and small business people of approximately same incomes are likely to differ in their insurance rates (public sector workers are overwhelmingly insured from what I know).

3) Democratic leaning states have more robust insurance systems for the poor. Take a close look at some of the inter-state differences on the borders; rather stark. In a lot of data county level variation doesn't give you a sense of state borders, especially those dictated by latitude or longitude. Not so here.

Here are the some plots.

Labels: data, Health

A few weeks ago I pointed to a paper which suggested a state-level relationship between teen births and religiosity. I did the calculation, and added in race as a control, as well as breaking out birthrate of the 15-17 age bracket. My results differ a little because 1) I didn't impute states like Rhode Island, 2) I think I used 2000 Census household income numbers, not later American Community Survey numbers (my bad).

	Teen Birth Rate			15-17 Birth Rate
	r	r (control Black)	r (control Household Income)	r	r (control Black)	r (control Household Income)
Black	0.41		0.41	0.39		0.38
Median Household Income	-0.59	-0.59		-0.49	-0.49
Religiosity Index	0.72	0.64	0.55	0.65	0.56	0.49

Race didn't make that big of a difference. Here's a map with the states:



Click it for the big version. But Utah is an outlier now because its 15-17 teen birthrate is way lower than when you include 18-19. The social reason for this is obvious; young marriage among Mormon women.

I'm skeptical of the conclusions or at least the explanatory framework in the model in the paper. I will do an analysis of Hispanics, as there's something there. The states well above the trendline have large Hispanic populations, and Hispanics aren't that much more religious than whites (so they would push a state in the vertical direction, but not to the right). But I think if I can get county level data I might see some interesting correlation with Scotch-Irish ancestry. Some of the states with high teen birthrates, like Oklahoma, have a higher proportion of Non-Hispanic whites than nationally, so there's some other story to be told here.

Addendum: I suspect that a lot of the time when it come to religion and social data the causality is inverted. Both the anti and pro-religious tend to take the efficacy of religion for granted (though their value judgments would be inverted). But in many cases it may be that particular religious "styles" (e.g., low church vs. high church) reflect the state of a given society. There is a body of social science data which shows the strong relationship between socioeconomic status and particular Protestant denominations, and the strongly biased "switching" of those who move up or down the socioeconomic ladder in their lifetimes. A similar effect might be at work on the aggregate social level.

Labels: data

Readers of this weblog might find GALLUP Worldview of interest. It's free, but you have to register. Here's a screenshot:

Labels: data

In the post from a few days ago showing areas where Non-Hispanic white proportions over & under predicted the % for Obama there were some interesting comments. One of the issues is that lumping different regions together obscures some information. Some readers wondered about regional differences, and I did too. So I thought it might be interesting to look at the South as distinct from the non-South. For the purposes of this post the "South" means: Virginia, West Virginia, North & South Carolina, Georgia, Tennessee, Alabama, Mississippi, Louisiana, Texas, Oklahoma, Kentucky and Arkansas. I excluded Maryland, Delaware and Missouri because I don't think these can be considered culturally Southern, especially the first two. In any case, first, scatterplots and loess best fit lines for the South & the non-South. The South is red/black, the non-South is blue/green.




For me the interesting point is that the "upturn" where the % for Obama increases is notable in the South, but not the non-South. That surprised me. What counties are these? Click for the larger image.

Some of the counties are not surprising in terms of being above the trendline, such as the "Research Triangle" region of North Carolina. But Elliott County, Kentucky? Who knew that this was the second-whitest county in the country to vote for Barack Obama. A map illustrating the trendline might be interesting. Blue is above the trendline, red below the trendline. I limited the data to the South here. Click for the larger image.

Labels: data, Election 2008

One of the major issues when you discuss topics with people with whom you disagree is conflicts as to the acceptability of a particular chain of reason or line of analysis. There are usually implicit assumptions within any given analyses which need to be fleshed out, and to do so is usually time consuming. To give an example, I do not agree with the assertion that "IQ has nothing to do with intelligence." This is a very common background assumption for many people, so many analyses simply make no sense when you do, or don't, accept the viability of a concept like IQ. Talking about the issues at hand is a waste of time when there are such differences in the axioms and background structure of the models one holds, and I can understand why the temptation of extreme subjectivism emerges so often. Looking through the glass darkly can obscure the reality that beyond the glass there is a clear and distinct world.

That is why I think it is important to expose and avoid falsity of fact, however trivial. It is often much easier to agree on basic facts, especially quantitative ones. I do not say that it is alway easy, but it is certainly much easier. This is why weblogs such as The Audacious Epigone are so useful, their bread & butter is fact-checking. When blogs first began to make a splash in 2002 the whole idea of "fact checking your ass" was in vogue, but it doesn't seem like it's really worked out. What's really happened is a proliferation of Google Pundits, who know the answers they want, and know how to get those answers out of the slush pile of answers via an appropriate query. Google Punditry is not exploratory data analysis, it's fishing around for data to match your preconceptions.

Many GNXP readers may not agree with the conservative politics of The Inductivist or The Audacious Epigone, but their data-driven blog posts are often formatted such that you don't even need to read the commentary after their tables. Eight months ago Kevin Drum of Mother Jones promised to do more digging through the GSS after I'd pointed him to the resources, but it doesn't seem like it has happened. My GSS and WVS related posts at Secular Right often get picked up by mainstream pundits like Andrew Sullivan, but the utilization of the GSS or WVS interface hasn't spread. Why? One friend suggested that perhaps people fear what they might find out.

I do agree that the GSS (or WVS) aren't oracles which are infallible. There are obvious issues with representativeness in the WVS, and the small N's for some categories in the GSS mean there's a lot of noise. But with that caution aside, these objections are clear and distinct when one begins with these tools and data sets. In fact, with something like the GSS or WVS you can check your intuitions about representativeness by digging a little deeper.

Addendum: When I do GSS posts people often object in the form of "your data doesn't prove that!" Interestingly, this objection comes up even when there's a minimum of commentary. Of course the sort of surface scratches that I do don't definitively disprove or prove much, at least in general. Rather, they should be starting off points for further digging.

Labels: data

The paper Eight Americas: Investigating Mortality Disparities across Races, Counties, and Race-Counties in the United States, has this fascinating map (reformatted a bit):



As you can see there is a great deal of variance in white male life expectancy in the United Sates. Compare to this map:

"American" is probably just Scotch-Irish in this case. It is noticeable it seems on this map that the countries in central Texas where Anglo ancestry is dominated by those of German origin exhibit high life expectancy.

In any case, you can actually look at the county-by-county data set from the above paper in regards to life expectancies. The minimum male life expectancy in any county is 62, with the maximum being 80.30. The median is 73.60 and the mean 73.38 (these data are ~2000). There's a "long tail" of sparsely populated counties with low male life expectancies as evidenced by the lower mean value than the median. The standard deviation across the counties is 2.35 years.

As can be seen on the first map there is a strong geographic component to the interregional differences. Below is a chart which reports the proportion of counties in the 50 states which have a life expectancy at, or above, the Canadian national value as of the year 2000 (again, both these values are for males).




Some states obviously have very few counties. But Kentucky has 120. None of them are at the Canadian level.

Labels: data

One of the "theories" I've had for a long time is that the smaller a proportion of a society's population atheists are, the stranger and more deviant they are going to be. A reason I came to this position is that read an account by an atheist American scientist who had some interactions with Soviet religious dissidents during the Cold War. His position was that in many ways American atheists and Soviet religious dissidents exhibited similarities in terms of personality, likely because they were generally not conformists. One of the peculiarities of the massive re-confessionalization of Russian society after the fall of the Soviet Union is the reality that these Communist era dissidents are now being marginalized in many congregations by recent converts who had a background as apparatchiks in the old regime, and were sometimes even actively involved in persecuting their current coreligionists! In any case, what about my hypothesis? Do I have any evidence for it? Not in any substantive manner. So I thought it might be interesting to look in the World Values Survey, naturally. How do attitudes of atheists and religious people vary within a society as a function of the proportion of each group?

I limited the sample to males, because men are more secular on average and exhibit more variance between nations. Additionally, because so many nations have very few atheists I put a lower bound of N = 20 for "convinced atheists." I mollified my own concerns about such a low N with the hope that if an N in a society is that low, the atheists may be strange enough indeed that their deviation from the social median may still swamp the noise. As before, the means for a class were calculated. So, the mean political self position of atheists and the religious is on a 1-10 scale. Below are are the charts for the results of a set of questions which exhibit a 1-10 level of agreement along a spectrum. The position is less important than the difference. First is a simple scatterplot which shows the attitudes of both the religious and atheists by nation. The expectation is a strong correlation between the religious and atheists, because most of the variation is naturally between nations. The second chart shows the difference between the two groups, "Religious persons" and "Convinced Atheists." I excluded those who were "Not religious" from the sample (so those who don't consider themselves religious, but neither are they professed atheists). Lastly, I plotted the difference between atheists and the religious as function of the ratio of religious to atheists. So, for example, the ratio of religious to atheists for Iraq is very high, atheists are a small minority (though to my surprise the N was large enough to stay above the threshold I put). In China the number of convinced atheists and religious are at parity, though those who are without religion and are not atheists are a plural majority.


Looking at these results I'm going to withdraw my model.

* For the "justifiable" questions 1 = never, 10 = always.
* Competition is good = 1, competition is harmful = 10.
* 1 = everything determined by fate, 10 = people shape their fates.
* 1 = gov. more responsibility, 10 = individual more responsibility.
* 1 = incomes more equal, 10 = we need larger differences for incentives.
* 1 = private ownership should be increased, gov. ownership should be increased.
* 1 = science makes world worse off, 10 = better off.
* 1 = Left, 10 = Right.

Labels: data, World Values Survey

I was in the bookstore and decided to look through God Is Back: How the Global Revival of Faith Is Changing the World. The authors work at The Economist, so I assumed it was going to be more reportage than a popular distillation of scholarship. I haven't read the whole thing, but that seems about right, skimming through I kept picking up errors or tendentious assertions. The very title is, in my opinion, only tenuously rooted in any factual secular trend. Secularization theory's overreach has given rise to a huge counter-literature which argues for the progressively more fervent religiosity of the world. But much of this has little to do with scholarship. Just as George Lakoff knows his audience, and so tailors his "scientific" message in the interests of getting his ideas out there through book sales, so the popular press knows very well that articles and books about the resurgence of religion will sell well. After all, there are many religious people out there. A few years ago David Aikman published Jesus in Beijing: How Christianity is Transforming China and Changing the Global Balance of Power. The book had a natural base when it came to potential sales. No matter that he tended to push highbound estimates for the number of Christians in China, the business is demand side driven.

We don't need to talk about China. There's a nation where the mainstream media has been hyping religious revival for the past generation that hasn't been happening: the United States. As far back as the 2000 Religious Identification Survey it was clear that the 1990s were a period of major decline in denominational affiliation. Those data have been confirmed over the past decade. The religious revival in the United States was simply in the minds of hopeful evangelicals, and terrified secular liberals who wanted to hype the power of the religious Right so as to elicit a counterresponse from the Left. And of course cover stories on the rise of evangelical America sell copy (again, scared secularists and enthusiastic evangelicals).

So what's the data around the world? Let's look at the World Vaues Survey. There are five "waves" to the WVS, and of these the last four have had a question of the form: For each of the following aspects, indicate how important it is in your life. Religion. The answers are:

1 Very important
2 Important
3 Not at all important

Below the fold I've the data from waves 2, 3, 4 and 5 for all the nations. Some obviously don't have data for a particular wave. Wave 2 is from around 1990 (some are as early 1989, with a few as late as 1993). Wave 3 is from around 1995-1998. Wave 4 around 2000. And wave 5 is from 2005-2008. The numbers represent the proportion who agreed that religion was "very important."

	WVS 2	WVS 3	WVS 4	WVS 5
Albania		24.8	28
Algeria			91.5
Andorra				8
Argentina		35.2	46.5	33.4
Armenia		26.6
Australia		23.3		19.5
Austria	24.4		20.2
Azerbaijan		29.9
Bangladesh		82.4	87.8
Belarus	12.3	21.8	12.2
Belgium	15.3		18
Bosnia		35.1	34.4
Brazil	57	64.6		50.6
Bulgaria	11.6	15.5	16.5	18.9
Burkina Faso				84.3
Canada	30.7		30.2	32
Chile	51.4	42.8	46.6	39.9
China	1.4	4.3	2.7	6.7
Colombia		49.1
Croatia		25.6	25.8
Cyprus				54.1
Czech Republic	9	9.3	7.3
Denmark	8.5		7.9
Egypt			97.3	95.4
El Salvador		86.9
Estonia	4.5	8.1	5.5
Ethiopia				81
Finland	14.5	13.4	13.8	17.6
France	13.9		10.9	13
Georgia		49.4		80.2
Germany	12.7	10.9	7.2	11.2
Ghana				90.4
Great Britain	16.2		12.6	21
Greece			32.9
Hong Kong				5.3
Hungary	23.2	21.6	19.8
Iceland	23.8		33.4
India	49.3	48.9		51.4
Indonesia				94.7
Iran				78.5
Iraq			94	96.1
Ireland			33.4
Italy	34.3		33	34.4
Japan	5.8	6.8	7.3	6.5
Jordan			96	94.5
Kyrgyzstan			31.9
Latvia	6.8	12.8	10.7
Lithuania	15.7	13.5	14.3
Macedonia		35.2	47.6
Malta	71.2		66
Malaysia				80.5
Mali				90.2
Mexico	34.3	43.5	68	59
Moldova		30.7	35.2	31.8
Morocco			94.3	90.6
Netherlands	22.1		16.7	12.5
New Zealand		20		17.3
Nigeria	85.3	91.8	92.9
Northern Ireland	34.2		27.7
Norway	15.2	12.1
Pakistan		80.5	81.8
Peru		55	52.6	49.6
Philippines		78.5	86.8
Poland	51.6	46.9	44.7	47.8
Portugal	17.1		27.3
Puerto Rico		71.4	75.6
Romania	41.8	38.4	51.3	58
Russia	11.8	14.4	12.1	13.7
Rwanda				38.9
Saudi Arabia			89
Singapore			35.9
Serbia		25.8	24.5	25.7
Slovakia	24.6	24.2	27.2
Slovenia	17.4		12.3	15.3
South Africa	66.2	68.2	69.8	70.3
South Korea	25.6	20	23.3	21.2
Spain	23.1	25.4	18.5	14.9
Sweden	9.9	9.6		9.3
Switzerland	23.8	14.7		17.2
Taiwan		12.8		12.4
Tanzania			85.1
Thailand				56.3
Trinidad				76.8
Turkey	61.2	83.4	80.8	74.7
Uganda			73.6
Ukraine		20.9	21.6	18.3
Uruguay		23.1
USA	52.9	56.1	57.1	47.4
Venezuela		61.2	64
Vietnam			10	7.2
Zambia				77.5
Zimbabwe			77.7

Yes, there are almost certainly issues about representativeness across these samples over the years. And the data are spotty. But in any case, there a few cases where we have other sources which confirm the trend line. Spain has become notably more secular over the past 20 years. China has seen an increase in religion over the past 20 years. But I don't see a very strong trend in either direction on a worldwide basis, and I assume a lot of the jumping around individually probably has to do with the nature of the sample . The point is that there hasn't been a massive secular trend in increased religiosity. But who cares? John Micklethwait and Adrian Wooldridge will sell a lot of copies of their book predicated on a likely moronic axiom (judging by the elementary errors that I quickly spotted they don't know much about the topic besides what they read in newspapers).

Here's a line graph where I placed all the nations with at least 3 data points. See if you can discern anything from the noise....



I invite readers to weight the data by the populations of these nations and see if, for example, the likely enormous relative increase in religiosity in China from hardly anyone being religious to a small minority being religious is making a worldwide difference. Doing a scatter of wave 2 on wave 5 for those nations which had those two gave an incredible slope of 1.01!

Labels: data, Demographics, Religion

Below when I compared the Nordic countries and Italy on a host of variables, I noted in the comments that it was rather amusing that 99% of the people in Bangladesh asserted that bribery was never justifiable, while only 69% of Swedes did. More specifically, the World Values Survey simply asked if bribery was ever justifiable, and there 10 options, with 0 = never justifiable and 10 = always justifiable. So 99% of the Bangladeshis chose 0, while only 69% of Swedes did. Plotting the 2008 Corruptions Perceptions Index scores from Transparency International against the proportion who chose 0, bribery is never justifiable, resulted in this:





Here's the raw data:

	Bribery Never Justifiable	CPI
Sweden	68.5	9.3
Singapore	76.6	9.2
Denmark	92.9	9.2
Finland	79.7	9
Netherlands	72.6	8.9
Iceland	87.1	8.9
Canada	80.3	8.7
Luxembourg	70.8	8.3
Austria	72.3	8.1
Germany	64.6	7.9
Great Britain	67.4	7.7
USA	80	7.3
Japan	83	7.3
Belgium	67.7	7.3
Chile	70.9	6.9
France	67.1	6.9
Slovenia	73.5	6.7
Estonia	66.9	6.6
Spain	71.9	6.5
Portugal	73.7	6.1
Israel	86.1	6
Malta	94.2	5.8
Puerto Rico	89.8	5.8
Korea	80.2	5.6
Czech Republic	51.4	5.2
Jordan	96.4	5.1
Hungary	53.3	5.1
Slovakia	39.4	5
Latvia	74.4	5
South Africa	61.1	4.9
Lithuania	66.7	4.8
Italy	79.3	4.8
Greece	64.4	4.7
Poland	76.8	4.6
Turkey	93.7	4.6
Croatia	79.1	4.4
Romania	80.2	3.8
Bulgaria	77.6	3.6
Peru	72.7	3.6
Mexico	72.5	3.6
China	83.4	3.6
Macedonia	86.7	3.6
Saudi Arabia	77	3.5
Morocco	97.7	3.5
Serbia	85.4	3.4
Albania	53	3.4
India	85	3.4
Algeria	88.6	3.2
Bosnia	85.5	3.2
Tanzania	92.1	3
Argentina	92	2.9
Nigeria	63.3	2.9
Moldova	49.2	2.9
Egypt	94	2.8
Vietnam	93.5	2.7
Uganda	72.6	2.6
Indonesia	82.5	2.6
Pakistan	91.9	2.5
Ukraine	64.1	2.5
Iran	93.3	2.3
Philippines	39.5	2.3
Russia	70.3	2.1
Bangladesh	99	2.1
Belarus	39.3	2
Venezuela	75.1	1.9
Kyrgyzstan	73.4	1.8
Zimbabwe	91.9	1.8
Iraq	84.6	1.3

Eastern Europeans and Filipinos are at least honest about their "pragmatism."

Labels: culture, data, World Values Survey

In the spirit of Gapminder, I've noticed three data visualization sites which present user-generated content:
* Many Eyes (does maps!!!)
* Swivel
* Data360

Labels: data, graph, map, visualization, web