Archive for the ‘Statistics’ Category
The quote for the day –
Lieutenant General Tommy Franks, who led the invasions of Iraq and Afghanistan during his time as head of US Central Command, once announced, “We don’t do body counts.”
He, of course, had nothing on a certain former first lady:
But back to the story.
… five years after Bush and Tony Blair launched the invasion of Iraq against the wishes of a majority of UN members, no one knows how many Iraqis have died. We do know that more than two million have fled abroad. Another 1.5 million have sought safety elsewhere in Iraq. We know that the combined horror of car bombs, suicide attacks, sectarian killing and disproportionate US counter-insurgency tactics and air strikes have produced the worst humanitarian catastrophe in today’s world. But the exact death toll remains a mystery.
There is no shortage of estimates, but they vary enormously. The Iraqi ministry of health initially tried to keep a count based on morgue records but then stopped releasing figures under pressure from the US-supported government in the Green Zone. The director of the Baghdad morgue, already under stress because of the mounting horror of his work, was threatened with death on the grounds that by publishing statistics he was causing embarrassment. The families of the bereaved wanted him to tell the truth, but like other professionals he came to the view that he had to flee Iraq.
An independent UK-based research group, calling itself the Iraq Body Count (IBC), collates all fatality reports in the media where there are two or more sources as well as figures from hospitals and other official sources. At least four household surveys have been done asking Iraqis to list the family members they have lost. The results have then been extrapolated to Iraq’s total population to give a nationwide estimate.
The results range from just under 100,000 dead to well over a million. Inevitably, the issue has become a political football, with the Bush administration, the British government and other supporters of the US-led occupation seizing on the lowest estimates and opponents on the highest.
It is a long and fantastic article about the trouble involved in trying to get estimates of dead civilians when the corporation making them won’t co-operate. For those of you who’ve not been to the site of the Iraq Body Count, you really should:
247 dead: Last week’s death toll (as counted by Iraq Body Count)
Monday March 10 – 34 dead
Including Dr Khalid Nasir, the only neurosurgeon in Basra; sheikh Thair Ibrahim and his five-year-old niece, killed by a female suicide bomber; 10 people killed by a suicide bomber; and a mother and son killed by gunmen.
Tuesday March 11 – 90 dead
Including a couple kidnapped the week before; 16 members of a family returning from a funeral, killed by a roadside bomb; three killed in a US air strike; and 20 people whose bodies were found in a mass grave.
Wednesday March 12 – 24 dead
Including a 10-year-old girl killed by US forces; five shot and beheaded at a checkpoint; and three truck drivers killed in a roadside bomb.
Thursday March 13 – 39 dead
Including a journalist killed by gunmen; 18 people killed by a car bomb in Baghdad; a 15-year-old girl shot dead by police; and Archbishop Paulos Faraj Rahho.
Friday March 14 – 15 dead
Including ex-footballer Munther Khalaf, killed outside his home by a group of armed men; a street sweeper killed by a roadside bomb; an Iraqi interpreter, killed by a suicide bomber; and the son of the chief of al-Kharaj tribes, killed during a raid by joint forces.
Saturday March 15 – 19 dead
Including Hussein Awda, killed by gunmen; three brothers; and an Iraqi contractor, Athir Ibrahim.
Sunday March 16 – 26 dead
Including two policemen killed in an armed assault and 16 others whose bodies were found, including that of an 11-year-old boy.
icasualties.org is another site worth visiting. Amongst other things, it might just remind you of how many non-civilians have died, also (since surveys here in the US show fewer people than ever know these numbers – rather relevant ones, one would think – 3988 confirmed by the DOD, by the by):
Although I graduated long ago from inmate to guard, I benefit from continued receipt of the American Statistical Society’s student magazine. Well, benefit – when one is more than a decade an Econometrician (of varying skill and/or pedigree) there isn’t much to be had inside.
Except, that is, for the likes of this (click for a larger/readable version):
Very amusing. Fair to say – Diogenes should have invested a little time, first, searching for some decent help with survey design.
My wife sent me this: Understanding America. Sweet Brain-on-crack Jesus, I don’t know where to begin. How ’bout here (The Cost of War)?
Or … here (The Economics of Raising a Child)?
How ’bout some Economy?
It’s as though a small army with AKs for days is tearing up my brain from the inside…
The latest on trust of the media, via thinkprogress.
From their post:
The Harris results reflect the findings of a Harvard University study conducted last year, which found “nearly two-thirds of Americans do not trust campaign coverage by the news media.” A few other recent surveys offer some explanation for the public’s distrust:
– Two thirds of Americans – 67% – believe traditional journalism is out of touch with what Americans want from their news.
– The harshest indictments of the press come from the growing segment that relies on the internet as its main source for news. The internet news audience is particularly likely to criticize news organizations for their lack of empathy, their failure to “stand up for America,” and political bias.
– Democrats, Republicans and independents have decreased confidence in the accuracy of media reports on the war.
Imagine – people not trusting the media! I notice that, as well as being the least-trusted, “the press” has the least uncertainty. It’s quite possible that this is because it has the greatest exposure: not everyone listens to the radio or uses the internet. Television, not so sure (I don’t own one).
Television and Radio are interesting ones, for trust: given the might of Clear Channel and the rightness (political-wing-wise) of talk-back radio, is this such a good thing? Same for Television news. If this is Fox News and CNN viewers, we’re dead.
Methodologically, according to Businesswire, the numbers are “… the results of a nationwide Harris Poll of 2,302 U.S. adults surveyed online between January 15 and 22, 2008.” Now there are nationwide surveys and then there are nationally representative surveys.
Harris’ responses were as follows (click for larger version):
I can’t say that I’m a fan of the web-use question: that is so far from how the average web/news person actually gathers “news” from the internet that it isn’t funny.
Getting back to survey methodology. According to the company itself,
Figures for age, sex, race/ethnicity, education, region and household income were weighted where necessary to bring them into line with their actual proportions in the population. Propensity score weighting was also used to adjust for respondents’ propensity to be online.
All sample surveys and polls, whether or not they use probability sampling, are subject to multiple sources of error which are most often not possible to quantify or estimate, including sampling error, coverage error, error associated with nonresponse, error associated with question wording and response options, and post-survey weighting and adjustments. Therefore, Harris Interactive avoids the words “margin of error” as they are misleading. All that can be calculated are different possible sampling errors with different probabilities for pure, unweighted, random samples with 100% response rates. These are only theoretical because no published polls come close to this ideal.
Which is quite responsible of them.
The missing pieces of information (for me): what were the levels of trust/distrust conditional upon use? I.e. if you’re a Rarely/Never kind of user, should your trust/mistrust be jumbled in with the Often/Occasionally people? While it is, of course, entirely likeky that one rarely or never uses a medium because of mistrust (part of my non-tv-ownership, but only part; my mistrust also of newspapers is, of course, no secret), low use also makes one a poor judge – even ignoring the response bias of a non-user.
Odds are that, given you’re here at this blog, you probably don’t see yourself represented in this survey at all. Which is a shame.
Because they can tell any story you like – just the way economists like it.
On Friday, the government will release the latest employment report, which will help clarify whether the economy is slipping into a recession. Wall Street forecasters are predicting that the February unemployment rate will have inched up to 5 percent, from 4.9 percent in January.
Whatever the survey shows, however, you can be sure of one thing: Politicians will be quick to point out that joblessness remains low by historical standards.
Ed Lazear, the chairman of the Council of Economic Advisers of President George W. Bush, said recently that “5 percent is still a low unemployment rate.” He added: “It’s below the average for the last three decades.”
You will note that “the last three decades” conveniently includes one or so in which employment was crap. Hell, we’d do better to compare today’s numbers to the last five decades.
Consider this: The average unemployment rate in this decade, just above 5 percent, has been lower than in any decade since the 1960s.
Yet the percentage of prime-age men (those 25 to 54 years old) who are not working has been higher than in any decade since World War II.
In January, almost 13 percent of prime-age men did not hold jobs, up from 11 percent in 1998, 11 percent in 1988, 9 percent in 1978 and just 6 percent in 1968.
There are only two possible explanations for this bizarre combination of a falling employment rate and a falling unemployment rate. The first is that there has been a big increase in the number of people not working purely by their own choice. You can think of them as the self-unemployed. They include retirees, as well as stay-at-home parents, people caring for aging parents and others doing unpaid work.
If growth in this group were the reason for the confusing statistics, there should be no to worry. It would be perfectly fair to say that unemployment was historically low.
The second possible explanation – a jump in the number of people who are not working, who are not actively looking but who would, in fact, like to find good jobs – is less comforting. It also appears to be the more accurate explanation.
Why the latter is more accurate, I don’t know. In fact, the author has conflated the two. We went through this (hilariously) in class: suppose you’re in your mid/late-fifties and you get laid off. The economy has been in a jobless recovery since 2001, and is now in a jobless plateau/decline. What do you do?
First, the hilarity: a student raised his hand and said “I’d get a job”. Even re-stating the question did not help. I believe he ended up taking my word for the fact that ‘getting another job’ isn’t really on the cards for Hypothetical Man (my University is seriously middle-class and up – I doubt my students, overall, really understand unemployment as a lived concept).
The answer, for the rest of the group, is retire. Or call yourself retired. Live off savings until Social Security kicks in – maybe try for that sweet deal their offering. In the UK – and, no doubt, similar countries – people are going onto disability pensions, which is essentially becoming a path to early retirement for many (what would you rather be on: a disability pension, or unemployment benefits?).
It is my belief that retirement numbers contain a lot of the missing people, and are helping mightly to keep the unemployment statistics nice and low (relatively speaking). This is where the conflation occurs – calling one’s self retired and being retired are two different things (just ask Michael Jordan or Jay Z).
We should, of course, also bear in mind how dangerous/difficult tracking a macroeconomy in real-time is, but the unemployment rates indicate, reasonably clearly, the drivers of unemployment. From the latest release by the Bureau of Labor Statistics:
The over-55’s are the only group for whom the unemployment rate has declined:
And somehow I don’t think the Births/Deaths jobs are going to that group first.
The advantage being that there are fewer sons of mill-workers – meaning he had a monopoly on the narrative (I don’t know if his father was a flour-mill-worker or not). From The American Journal of Industrial Medicine, via Reuters:
Using data from the Washington State health department, researchers found that the children of men who worked in flour mills were disproportionately female. Of 59 children born to these workers between 1980 and 2002, 37 — or roughly 63 percent — were girls.
In contrast, just over 51 percent of children born in Washington during that period were boys, according to the findings published in the American Journal of Industrial Medicine.
The current study found that, besides the low prevalence of male births, boys born to flour mill workers also weighed significantly less than average. Their average birthweight was 7 pounds, compared with nearly 8 pounds among girls born to flour mill workers, and about 7 pounds, 12 ounces among boys born statewide.
Unfortunately, and despite their false promises, my library either doesn’t have access, or won’t give it to me, off-campus, but from the paper’s abstract:
The Washington State Department of Health has collected and coded parental occupation information on birth certificates since 1980. We used these data to search for possible effects of parental occupational exposures on birth outcomes.
We tabulated sex ratio, birth weight, and proportions of multiple births, still births, and malformations by mothers’ and fathers’ occupations.
There were 59 births (22 boys and 37 girls) where the father’s occupation was specified as flour mill worker. The sex ratio of 0.373 (95% confidence interval [CI]: 0.261-0.500) was lower than the mean sex ratio of 0.512. The mean birth weight for flour mill workers’ boy babies was 3,180 g (95% CI: 2,971-3,389), compared to an overall mean of 3,511 g for all boy babies. The mean birth weight of flour mill workers’ girl babies was 3,602 (95% CI: 3,380-3,824), compared to an overall mean of 3,389 for all girl babies.
The low prevalence of male infants born to fathers of flour mill workers in Washington State suggests that fumigants that they are exposed to are causing testicular dysfunction. The very low birth weight seen in the male infants of flour mill fathers is unprecedented and may be another genotoxic endpoint.
This lack of access is annoying, because I really want to see the paper. Why, you ask? Well I can certainly understand that question, having just asked it myself (hat-tip to Colonel Blake).
This sort of analysis is prone to several statistical problems. The first is what we call “power”. “Power” is a function of sample size: small samples are under-powered. Why? Because a small sample has less information, possibly too little information, with which to establish properly the distribution of the data. Moreover, too-small samples are less and less likely to represent properly a population (meaning your results apply only to your sample – in this case Washington State, say – and not to the population at large). The authors are, above, using confidence intervals, meaning they’re relying upon the Central Limit Theorem. They certainly can do this, although their sample of 59, with p = .373, isn’t all that close to the criteria for textbook statistics (at nearly 50/50 probabilities, one is a lot more assured of underlying normality).
I’m just wary of small samples. I’d like to see what else they did. The proportion of males is statistically significantly less than the population proportion (we can see this because the 95% confidence interval of the proportion of males does not include 0.512), but I’m willing to bet the confidence intervals of each (p = .373 and p* = .512 overlap significantly, and I’d like to see by how much (meaning I’d like to see how the confidence intervals work using the “population” numbers, rather than the mill-worker numbers).
The other problem I’d like to see worked out is Simpson’s Paradox. Simpson’s paradox is an aggregation issue and the classic example of it, in fact, relates to low-birth-weight babies (of smokers). It basically says that, merely by dis-aggregating data, one can draw incorrect conclusions. In the case of this paper, the low-birth-weight problem, once children have been separated by gender, might not have been observed had they not been separated by gender.
Don’t get me wrong – I’m not suggesting that there’s nothing here worth responding to. At the very least it has picked up the workers of Washington State, and Washington State ought to respond – assuming the “population” numbers are also Washington State, rather than national, in which case another set of comparisons would be needed. This is more a stats-geek level of interest.
Oh, I think Edwards’ father worked at a textile mill.
Surprising to whom, I wonder.
Retail sales in the U.S. unexpectedly rose in January, easing concern that the world’s largest economy has already slipped into a recession.
The 0.3 percent increase was led by spending on autos, clothes and gasoline, the Commerce Department said today in Washington. The figure followed a 0.4 percent decrease the previous month. Purchases excluding automobiles and gasoline were unchanged.
“Today’s report will diminish recession anxieties, but it doesn’t dispel them altogether,” said Richard DeKaser, chief economist at National City Corp. in Cleveland, who accurately forecast the sales gain. Federal Reserve Bank of St. Louis President William Poole said yesterday “the best bet” is the U.S. will avoid a recession.
A) Is this volume, is it revenue, what are retail sales? Previously we’ve seen this, discussing volume, and the volume has been on steeply-discounted goods at discount stores. This could very well (and, most likely, will) be the same – meaning there’s no ‘there’ here.
B) This is more likely than not to be inflation-driven, either (i) because prices are up, or (ii) because people expect prices to go up even further, so tomorrow’s consumers are entering today’s markets, trying to save a bit of money (the article specifically mentions gasoline and its appreciating prices at bowsers across the country)
C) This is according to Commerce department. The department whose job it is to sell us the economy, and a department in an administration known for selling many bad goods under fake bills, across the board. Which gets us back to part A).
Am I a cynic and a pessimist? No – this counts merely has having pulled-wool-proof eyes. When oh when will we learn not to believe the hype? Back at Bloomberg:
Department-store sales dropped 1.1 percent. Stores selling building materials showed a 1.7 percent decrease in sales, after falling 2.5 percent. Sales also fell at electronics, appliance and sporting goods stores.
Excluding autos, gasoline and building materials, the retail group the government uses to calculate gross domestic product figures for consumer spending, sales rose 0.2 percent, after a 0.1 percent decrease the prior month. The government uses data from other sources to calculate the contribution from the three categories excluded.
Today’s Commerce Department report on retail sales also runs counter to industry figures that show January sales fell at stores from Target to Nordstrom Inc. even as some retailers slashed prices by as much as 75 percent. Sales at stores open at least a year rose 0.5 percent from a year earlier, the worst January since 1970, according to the International Council of Shopping Centers.
D) Month-by-month data isn’t all that relevant. So what if January sales did increase .3% on December sales – by what percentage have previous Januaries out-done their Decembers? That’s the yard-stick.
Popping over to the Census Bureau:
Very non-sexy graphics, I’m afraid. What does it mean? Nothing, really. January’s CPI figures are due February 20th. PPI figures too, probably – although December’s were down which, in a soft economy, may also not mean much.
Don’t get me wrong – I’m not poo-pooing potentially good news. We’ve already seen only recently, however, how foolish it is to try to capture the macroeconomy in real-time. I don’t know why we persist.
Yes, yes, I know – shouldn’t all mortality be excess? No – this refers to the mortality rates that the invasion/occupation hath wrought, above and beyond the ‘ordinary’ rates of mortality in Iraq. The New England Journal of Medicine is sporting two papers on the subject: Violence-Related Mortality in Iraq from 2002 to 2006, by the Iraq Family Health Survey Study Group; and Estimating Excess Mortality in Post-Invasion Iraq, by Browstein, Catherine A. and John S.
Mortality in Iraq by cause, from the Iraq Family Health Survey Study Group (click for larger version):
It’s Iraq: it’s not suprising to see mortality escalate – but, honestly, Road Accidents and Unintentional? Surely that’s a bit much.
Excess mortality (per 100,000 population), same:
The Iraq Family Health Study Group are fairly open about their measurement issues (recall bias is always a problem in household surveys, with or without holistically-debilitating armed conflicts). The Brownstein and Brownstein paper is survey methodological, and says much the same:
There is no set formula for accurately tallying deaths from humanitarian crises. When a population becomes destabilized, estimation of mortality is likely to be severely challenged. In the case of a sudden traumatic event, such as a natural disaster affecting an otherwise stable population, health and human service agencies, though compromised, may well be able to facilitate an accurate assessment of deaths through the use of prospective registries of vital events.
In the event of a military invasion and ongoing war, however, the likelihood of obtaining good demographic data plummets. A death registry is unlikely to be developed or maintained, and as conditions deteriorate, it may become increasingly unlikely that bodies can be counted at all. In Iraq, there is also a strong cultural imperative that bodies be put to rest quickly, which may affect the ability to arrive at accurate estimates.
Although sentinel populations are commonly monitored to rapidly estimate mortality in developing countries when a registry is not available, the impossibility of finding reliably representative populations in countries engaged in armed conflict and the absence of an accurate population count make it difficult to extrapolate from the rates at sentinel sites to produce reliable national estimates.
They – and the IFHS – discuss the clear variation in mortality estimates between this article, the numbers from the Iraq Body Count people and the widely-publicised results from the paper Mortality after the 2003 invasion of Iraq: a cross-sectional cluster sample survey (Burnham G, Lafta R, Doocy S, Roberts L. Lancet 2006;368:1421-1428). Wikipedia too has an excellent page concerning the Lancet mortality studies.
Ultimately the problem won’t go away – this section, from the Brownstein’s paper, is brilliant:
Under the current conditions in Iraq, it is difficult to envision a study that would not have substantial limitations. The circumstances that are required to produce high-quality public health statistics contrast starkly with those under which the IFHS study group worked. Indeed, it must be mentioned that one of the authors of the survey was shot and killed on his way to work
It’s certainly worth having more studies. More information is always going to help stabilise estimates in the face of such uncertainty as this.
While I work through a re-jig of my Cost-Benefit Analysis syllabus (actually it’s really Cost-Effectiveness Analysis, but the University calls it Cost-Benefit Analysis and never comes into the classroom to check, so. The differences between Cost-Benefit, Cost-Effectiveness and Cost-Utility Analysis are not problematic to navigate CEA is a better umbrella). I will take your time up with some of it.
This is going to go into a discussion that we have, early on, concerning key issues “going forward”. Methodological, social, ethical, etc. It’s a graduate class, but the students usually have not had any real exposure to things like proper analysis, research, research papers, dissemination – which is to be expected, at that level. We take the first few weeks to give them a feel for (a) what’s out there, and what’s important, and (b) the aesthetic, the structure, of applied research. It’s well-worth the time spent.
Uninsured near-elderly adults, particularly those with cardiovascular disease or diabetes, experience worse health outcomes and use more health services as Medicare beneficiaries after age 65 years than insured near-elderly adults. Because chronic diseases are prevalent and insurance coverage is often unaffordable for older uninsured adults, the impact of near-universal Medicare coverage at age 65 years on the health of previously uninsured adults may be substantial.
Most studies assessing the health consequences of lacking coverage have relied on cross-sectional data and study designs that have not allowed coverage effects to be distinguished from unobserved differences between insured and uninsured persons. A few studies have used cross-sectional data that span multiple years or ages to conduct more rigorous comparisons. For example, an assessment of the introduction of Medicare in 1965 found no discernible impact on mortality for beneficiaries,15 but subsequent medical advances may have improved the effectiveness of health care for elderly Americans.16 A recent cross-sectional analysis of age profiles found that Medicare eligibility at age 65 years was associated with modest gains in self-reported general health status for less-educated adults and minority groups, but uninsured adults and those with specific conditions could not be longitudinally followed as they became eligible for Medicare.
The objective of our study was to assess the effect of Medicare coverage at age 65 years on trends in self-reported health outcomes from ages 55 through 72 years for previously uninsured adults, particularly those with cardiovascular disease or diabetes. We compared cohorts of insured and uninsured near-elderly adults using a quasi-experimental design and longitudinal data on a broad array of general, physical, and mental health measures from the nationally representative Health and Retirement Study. We hypothesized that acquiring Medicare coverage would attenuate adverse health trends for previously uninsured adults relative to previously insured adults, as improved access to care, greater use of beneficial medications and procedures, and more effective management of chronic conditions helped to alleviate symptoms, maintain functioning, and prevent or postpone complications.
You will find it is familiar to a lot of what was written here, concerning SCHIP: give people insurance, and you give them access to health care. Give them access to health care, and you improve their health. This does not include the argument that it is not the absence of insurance but the high cost of care that is the problem – this, too, will be a defining issue for the our retiree Boomer self-interest.
Back with McWilliams et al, some results (click for large version):
Among 5766 adults (79.7%) who completed at least 1 survey after age 65 years, previously uninsured adults were less likely to report coverage for prescribed medications after age 65 years (62.7% vs 77.9%; P < .001). Among the study cohort, 4443 adults (61.4%) reported diagnoses of hypertension, heart disease, stroke, or diabetes before age 65 years, of whom 3103 (69.8%) were insured and 1340 (30.2%) were uninsured. Among 838 adults with diabetes in our study cohort who were also surveyed in 2003, 541 (64.6%) underwent HbA1c testing.
Before age 65 years, summary health scores worsened at a greater rate for uninsured adults than for insured adults (mean annual trend, –0.23 vs –0.15; P = .002) and were significantly worse at age 65 years (mean score, 20.75 vs 22.29; P < .001) (Table 2). After age 65 years, however, this adverse trend differentially improved for previously uninsured adults (differential change in annual trend, +0.20; P = .002) such that summary scores after age 65 years indicated near maintenance of health for previously uninsured adults but continued deterioration for previously insured adults (mean annual trend after age 65 years, –0.07 vs –0.19; P = .049 [test not shown]). In comparisons of component health trends before and after age 65 years, previously uninsured adults reported significant improvements relative to previously insured adults in change in general health, agility, and depressive symptoms (Table 2). Persistently uninsured adults reported greater declines before age 65 years than intermittently uninsured adults and worse summary health scores at age 65 years (mean difference, –0.69; P = .07 [data not shown]), but changes in health trends after age 65 years were similar for these 2 groups of previously uninsured adults (P = .81).
Which is, more or less, what one would expect. Near-elderly non-insured (since I’m sure the survey did not specifically find people, give them insurance, then take it away again) are going to be in just-plain-shit health, relative to their peers. They are more likely to have lower incomes, more likely to have avoided preventive (or even early palliative or curative) physician care, less likely to have had any sort of access to medication (particularly in the US) – you name it, they didn’t get it or didn’t do it. Meaning when the retire and hit Medicare, they do.
This means two things: first, as this article shows, we observe health-gains from people having this access – indicating similar gains, probably greater gains, exist if they had such access all along. Meaning expanded health care/insurance, one way or the other.
Second, as per the SCHIP plaint, an ounce of prevention, etc. – particularly now, as Boomers retire. Every individual will invest in their health, to the extent that they believe they can afford to do so (this is also why insurance, coupled with rapidly appreciating care costs, is a recipe for serious problems). As this enormous lump of people retire, the burden that they place upon Medicare is going to be substantial. Couple that with moves by companies to get people off their books and onto government books, and the problem only becomes worse.
The issue for us will be pretty much this: the increasing importance of access to care, as more people retire. Of follow-up importance is the cost: as more people retire, will price-rationing hold, as an ideal? If not, how will the US system expand their use of non-price rationing? Will America soon need a US NICE or PBS, to hold back the tide? At what point (at what age, and what severity, at what condition) do we decide that it is “worth it” to help people? We cannot just help everyone via Medicare: put more people on it, and – in the US – it will be able to do less. With limited health care resources, how do we decide who gets the resources when an increasing bulk of the electorate transition to fixed-income retirees?
I don’t yet know the make-up of my students for CBA. I’m considering brining in some climate change/Bjorn Lomberg stuff, too. As well as agricultural problems.
Statistical update on the previous Iraqi fatalities post.
According to figures released Monday by the Iraqi government, 16,232 civilians, 432 soldiers and about 1,300 Iraqi policeman died in 2007. The previous year, according to the figures compiled by the health, defense and interior ministries, 12,371 civilians, 603 soldiers and 1,224 policeman were killed.
The government’s figures were roughly in line with a count kept by The Associated Press, which found that 18,610 Iraqis were killed in 2007. In 2006, the only other full year an AP count has been tallied, 13,813 died.
Bollocks. Of course, I’m left-wing: according to the freaks that sent us to Iraq, I love the body-count (three cheers for those people getting jobs at the New York Times. Formerly known as the Newspaper Of Record. Now, any dead fish with any self-respect at all would reject it).
So, Iraqi civilians and police fatalities up for the year, troop fatalities down. Domestically, I would expect this one to be called a win. To be fair, and this was the same caveat I entered last time, also: the numbers do appear to be trending downwards (weakly – bear in mind we don’t have much with which to work. I wouldn’t start insisting things like surges are or are not working):
Click for larger versions. All the data comes from icasualties.org.
It is a trend matched in the unconscionably forgotten theatre of this foolish also, Operation Enduring Freedom. Or enduring something, at any rate.