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Feb

2012

Counting deaths: war as a statistical problem | plus.maths.org

How many people died? It's one of the first questions asked in a war or violent conflict but it's one of the hardest to answer. In the chaos of war many deaths go unrecorded and all sides have an interest in distorting the figures.

The best we can do is come up with estimates but the trouble is that different statistical methods for doing this can produce vastly different results — see the Plus article Body count which reported on controversy surrounding the death toll of the last Iraq war. Statisticians know how well different methods do in theory and under ideal assumptions, but wars rarely adhere to these. And we can't concoct a war in the lab to see which method does best.

But recently a unique document has helped throw some light on the question of how to count the dead.

plus.maths.org/...g-dead-war-statistical-probelm

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War Death Model Assumption Statistics Facts Uncertainty

two methods that are commonly used. One is based on household surveys: a random sample of households from around the region are asked to name their dead and statisticians estimate the total figure from the responses, much like an opinion poll gauges the mood of the nation from the opinions of a random sample of people.

The other involves taking two independent samples of deaths recorded throughout the region and comparing them. If the overlap between the two samples is large — if many deaths appear in both — then chances are that the overall number is relatively small, as you've managed to "catch" many deaths twice. Conversely, if the overlap is small, then the overall number is probably large. There are mathematical equations that make this intuition rigorous and give you an estimate of the total number. The method was initially developed for ecologists trying to estimate the number of animals that live in an area. It's called capture/recapture, as in this case the method works by capturing a number of animals, tagging them, releasing them back, and then capturing another sample to see how many animals got caught twice.
numbers are essential in establishing truth. It's important to get them right. Exhaustive approaches like the Kosovo Memory Book take years to complete and, in the absence of complete information, all you're left with is a statistical approach.
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- There can be few applications of statistics that present as many difficulties as this one. Simply collecting information on the ground is hampered by all sorts of problems. How do you make sure you get a good sample of households for your survey when many homes are not listed anywhere and areas may be too remote or dangerous to venture into? How do you know whether William Smith, Bill Smith and Will Smith are different people or one and the same? How do you account for the fact that the deaths of people with a large surviving family are more likely to be recorded than the deaths in the massacre of a whole village, which leaves no witnesses?
- These aren't just practical problems to do with how information is collected. Statistical methods depend on assumptions — in the capture/recapture method for example, a basic approach assumes that each death has the same probability of being recorded. If these assumptions aren't met, then you need to tweak your theory to match reality. So this is a challenge not just to the people on the ground, but also for the statisticians who analyse the data.
- Politicians, the media and the public want hard figures, but hard figures are something that even the best statisticians can't deliver. And neither do they pretend that they can. In addition to a single number estimate statisticians always give a range of values, a confidence interval, together with a percentage reflecting their confidence that the true number they're trying to estimate lies within that range
- Such intervals aren't very satisfying and they rarely get reported. Even when they are people are easily stumped by their meaning and quick to suspect foul play. This is what happened in controversies surrounding the death toll of the last war in Iraq.
- Statistics can indeed be treacherous and parts of it hard to understand when you first come across them. But so are many other concepts that are part of public discourse. If we're going to make the best of the power of statistics and protect ourselves against its misuses, then it's time that the public are trusted to come to grips with the subtler issues surrounding uncertainty.

Dec

2011

Nobel Winners in Economics - The Reluctant Celebrities - NYTimes.com

www.nytimes.com/...the-reluctant-celebrities.html

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Model Assumption Economics Mathematics Politics

fiscal and monetary policy are inextricably linked, and their research reflects the broad shift in economics from words to numbers — toward a level of empirical analysis that few outside the profession can readily grasp. But it contains a kernel of skepticism appropriate for these troubled times. In a world of uncertainty and constraint, cause and effect may not be what they seem. As a result, we must test and retest our assumptions — and try to prepare for the unexpected.
“The most impressive thing about them as scholars,” says David Easley, an economist at Cornell University, “is that in recent years they have questioned the assumptions of the models they helped to create, and they have been at the vanguard of the efforts to go beyond them.”
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- Mr. Sargent says his most important work is spoken “in the beautiful language of math.” He knows it’s not widely understood.
- Mr. Sims wrote his undergraduate thesis on information theory, a subject to which he has returned over the years. In his senior year, he says, he wanted “something more practical” and switched to economics.
- “There isn’t much political coloration in my economic writing,” Mr. Sims said one afternoon in his Princeton office, looking very much like an older version of the Greenwich boy he was, in a blue oxford button-down shirt, black slacks and moccasins. “It’s not surprising that few people know my political views. They really aren’t very important.”
- AS Mr. Sargent tells it, Mr. Sims changed his life. In 1972, Mr. Sims published an article titled “Money, Income, and Causality.” Mr. Sargent says he recognized its importance but couldn’t follow all of it.
  “I spent the next two years learning enough math so that I could make sense of it,” he says. “From there, having learned that language, I was able to start asking some questions of my own and to go in my own direction. That paper really got me started.”
- the idea of rational expectations is that in many economic situations, the outcome depends on what people expect to happen.
- “rational expectations approach” and the techniques he has helped to pioneer don’t yet capture economic reality. How do people really think, as individuals and in a market? How should we account for changes in expectations as people learn? How should we incorporate human thinking more realistically into economic models? He’s grappling with such questions, seeking more sophisticated techniques that incorporate what he calls the theory of “adaptive learning.”
  His own assumptions need to be continually re-examined “to capture a fundamentally uncertain, constrained, complicated world,” he says.

Jul

2011

Green Bootleggers and Baptists - Bjørn Lomborg - Project Syndicate

In May, the United Nations’ International Panel on Climate Change made media waves with a new report on renewable energy. As in the past, the IPCC first issued a short summary; only later would it reveal all of the data. So it was left up to the IPCC’s spin-doctors to present the take-home message for journalists.

The first line of the IPCC’s press release declared, “Close to 80% of the world‘s energy supply could be met by renewables by mid-century if backed by the right enabling public policies.” That story was repeated by media organizations worldwide.

Last month, the IPCC released the full report, together with the data behind this startlingly optimistic claim. Only then did it emerge that it was based solely on the most optimistic of 164 modeling scenarios that researchers investigated. And this single scenario stemmed from a single study that was traced back to a report by the environmental organization Greenpeace. The author of that report – a Greenpeace staff member – was one of the IPCC’s lead authors.

The claim rested on the assumption of a large reduction in global energy use. Given the number of people climbing out of poverty in China and India, that is a deeply implausible scenario.

www.project-syndicate.org/...English

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Green Energy Assumption Model Optimism Poverty Economy

This sort of behavior – with activists and big energy companies uniting to applaud anything that suggests a need for increased subsidies to alternative energy – was famously captured by the so-called “bootleggers and Baptists” theory of politics.

The theory grew out of the experience of the southern United States, where many jurisdictions required stores to close on Sunday, thus preventing the sale of alcohol. The regulation was supported by religious groups for moral reasons, but also by bootleggers, because they had the market to themselves on Sundays. Politicians would adopt the Baptists’ pious rhetoric, while quietly taking campaign contributions from the criminals.
Of course, today’s climate-change “bootleggers” are not engaged in any illegal behavior. But the self-interest of energy companies, biofuel producers, insurance firms, lobbyists, and others in supporting “green” policies is a point that is often missed.
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- Dubious claims by faithful activists gave rise to the biofuels industry (with supporting lobbyists). Biofuel production likely increases atmospheric carbon, owing to the massive deforestation that it requires, while crop diversion increases food prices and contributes to global hunger. While environmentalists have started to acknowledge this, the industry received a lot of activist support when it began – and neither agribusiness nor green-energy producers have any interest in changing course now.
- private firms are motivated by self-interest, and that is not necessarily a bad thing. But, too often, we hear commentators suggest that when Greenpeace and Big Business agree on something, it must be a sensible option. Business support for expensive policies such as the Kyoto Protocol – which would have done very little for climate change – indicate otherwise.
- Unfortunately, this convergence of interests can push us to focus on ineffective, expensive responses to climate change. Whenever opposite political forces attract, as activists and big business have in the case of global warming, there is a high risk that the public interest will be caught in the middle.