The Metrics of Ruling the World.

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The Metrics of Ruling the World.

Postby Wombaticus Rex » Wed Jul 18, 2012 6:42 pm

The common thread here is my interest in the logistics and science of metrics for world management. "Ruling the world" makes for a stronger title, but this is accounting-level stuff that interests me. Having seen how much numbers get fudged and intelligence gets doctored, I am wondering where, exactly, the ruling class makes any contact with the real world at all.

The initial inspiration was reading this on lunch break:

Via: http://www.nytimes.com/2012/07/17/busin ... -data.html


U.S. Tightens Security for Economic Data
By JOHN H. CUSHMAN Jr.


WASHINGTON — On Tuesday morning at precisely 8:30, after a 10-second countdown synchronized to the Naval Observatory’s atomic clock, a Labor Department official flipped a master switch in the agency’s battened-down pressroom and computers blurted out the monthly Consumer Price Index.

Until that moment, the market-sensitive data was guarded with launch-code secrecy, a precaution against anyone who might try to take advantage of an accidental or a surreptitious leak to gain an insider’s edge in the financial markets, turning milliseconds into millions.

Yet for all the rituals of high security, government officials have become increasingly nervous that their process is vulnerable, and are now overhauling it.

After a yearlong review that included scrutiny by anti-hacking specialists from Sandia National Laboratories, officials at the Labor Department revoked the credentials of a few little-known news organizations that appeared to serve financial clients rather than the public at large.

The government has also ordered other media groups to replace their computers in the lockup room with new computers under tighter controls.

The efforts stem from the newfound importance of high-speed trading, which began to grow significantly in the middle of the last decade and is now a central part of some hedge funds’ investment strategies. By gaining information seconds or minutes before others, high-speed traders — sometimes known as high-frequency or algorithmic traders — can use the computerized nature of modern finance to make quick profits or, if a bet goes wrong, take large losses.

In addition to the inflation numbers, the lockup process, in use at several agencies, covers releases on economic growth, home sales, gas prices, corn yields and the unemployment rate, among other things.

The Labor Department’s overhaul was ignited by inquiries starting in 2007 from the F.B.I., the Securities and Exchange Commission and the department’s own inspector general. Officials did not cite any specific major breach of security, but they had grown concerned that one was possible. Two instances in 2008, when Reuters accidentally released data a few seconds too early, heightened concerns.

The clampdown has strained the Labor Department’s relations with some of the world’s biggest news agencies, including Reuters and Bloomberg News. In negotiations with the department and at a fractious Congressional hearing, the companies suggested the government was taking extreme measures against an imagined threat.

At the center of the Labor Department’s effort was a so-called Red Team from Sandia Labs, a federally financed research group operated by a subsidiary of Lockheed Martin, which has half a century of experience in computer security, including work on the military’s command and control networks.

The “root cause” for the review, the team noted, was the possibility of traders or their agents working inside the lockup.

Acting on the team’s recommendations, Labor Department officials sought a wholesale replacement of the computer equipment in the lockup room. The replacement is scheduled to happen by September, although further steps to shield against surreptitious transmissions are possible later.

At a hearing of the House Committee on Oversight and Government Reform last month, the former Bureau of Labor Statistics commissioner Keith Hall explained the main worry, which is that the growing reliance on high-speed trading had created the potential for participants in the media lockup to give an unfair advantage to traders.

“Lockup participants may now have access to specialized computer equipment and software that links them directly to automated trading models,” he noted. “This effectively allows financial market transactions to be driven from inside lockups.”

Carl Fillichio, the Labor Department official in charge of the overhaul, described a series of malfunctions and violations over the last few years, including the installation of fiber optic cables in the lockup room without permission or the use of BlackBerrys or mobile phone cameras. Media companies themselves have complained about competitors who “may have gained unfair advantage in speed of transmission or have surreptitiously broken embargoes,” Mr. Fillichio added in his testimony.

Some members of the media, however, say the crackdown is unnecessary. (The New York Times does not participate in the Labor Department lockup.)

“What is the problem you think, you imagine that this will prevent?” asked Daniel Moss, an executive editor at Bloomberg News, in an April conference call between Mr. Fillichio and news organizations. Mr. Moss, plainly exasperated, repeated the question several times but got no clear answer.

Government officials consider the potential security problems to be real. After a five-member team from Sandia Labs visited the lockup room last July, it identified “verified vulnerabilities in processes, procedures and systems used to protect” embargoed data, according to the summary of its report.

The team warned about methods of sneaking information out, such as by hidden transmitters, or bypassing the black boxes and master switches that keep the lockup room under electronic quarantine through other means, like wireless Internet. The team noted that “likely adversaries” had the technical and financial resources and possibly the willingness “to bend and potentially violate rules and laws.”

But it said any culprits were unlikely to “employ violent means to meet their goal of exfiltrating embargoed data prior to the official release time.”

At the oversight hearing, Mr. Moss of Bloomberg News argued that traditional media outlets were not the problem and suggested that the Labor Department instead expel those groups connected to algorithmic traders from the lockup.

Ultimately, the Labor Department did pull the credentials of a few organizations — including Need to Know News, a small enterprise owned by the German exchange. Its data goes directly from the lockups to specialized trading programs. Mr. Fillichio explained that they were not “primarily journalistic” and did not “disseminate their information to a wide audience.”

Chris Rhea, chief executive of Need to Know News, referred questions to a spokesman, who did not respond.

In the initial stages of the crackdown, Mr. Fillichio ordered lockup participants to use government computers, transmission lines and even pens and pencils and paper while inside the lockup. Media groups objected.

“This proposal threatens the First Amendment,” Mr. Moss said at the oversight hearing, adding that it would give the government “access to a reporters’ thoughts, drafts or notes as a condition for covering the news.”

After another round of negotiations, the government backed off a bit. For now, some equipment owned by media companies is expected to stay. But over the next few months they will have to deliver new, shrink-wrapped terminals, which will be subject to inspection and maintenance by Labor Department technicians.

One question that is still unresolved is how many seats each organization will be allowed.

Space is tight in the lockup. And paradoxically, all the attention to this obscure room on a drab corridor has brought newcomers knocking, as if at the door of a speakeasy.

This article has been revised to reflect the following correction:

Correction: July 16, 2012

An earlier version of this article misstated Mr. Moss’s title at Bloomberg News as executive director.
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Re: The Metrics of Ruling the World.

Postby Wombaticus Rex » Tue Jul 24, 2012 7:19 pm

via: http://nymag.com/nymetro/news/people/features/14573/

“Ninety-nine percent of the people with Mike’s résumé would have failed dismally at the mayor thing,” Rattner says. “He happens to be the one guy who has come to understand the political system well enough that he can function within it. And Mike didn’t do anything with the money, really, before running for mayor that would have given you any idea he’d be good at being mayor.”

Like Bloomberg, Rattner long ago soared past his parents’ tax bracket. “It gets harder, frankly, to have perspective on what goes on in the real world,” he says, “because your life changes and you operate in a certain way where you’re just not taking your dry cleaning to the cleaners anymore. But it’s true of most public officials, no matter their net worth, that they live in a bubble. They’re not operating in the real world any more than Mike Bloomberg was operating in the real world. But you’re trying to elect a guy who you think has compassion and cares and really wants to be better, even if he can’t possibly imagine how tough it would be to live in Bushwick in some five-story walk-up.”


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Re: The Metrics of Ruling the World.

Postby bks » Wed Jul 25, 2012 7:56 am

Not vouching for the article's silly conclusion, but interesting perhaps in this context.

The psychology of power
Absolutely

Power corrupts, but it corrupts only those who think they deserve it

Jan 21st 2010

REPORTS of politicians who have extramarital affairs while complaining about the death of family values, or who use public funding for private gain despite condemning government waste, have become so common in recent years that they hardly seem surprising anymore. Anecdotally, at least, the connection between power and hypocrisy looks obvious.

Anecdote is not science, though. And, more subtly, even if anecdote is correct, it does not answer the question of whether power tends to corrupt, as Lord Acton's dictum has it, or whether it merely attracts the corruptible. To investigate this question Joris Lammers at Tilburg University, in the Netherlands, and Adam Galinsky at Northwestern University, in Illinois, have conducted a series of experiments which attempted to elicit states of powerfulness and powerlessness in the minds of volunteers. Having done so, as they report in Psychological Science, they tested those volunteers' moral pliability. Lord Acton, they found, was right.

In their first study, Dr Lammers and Dr Galinsky asked 61 university students to write about a moment in their past when they were in a position of high or low power. Previous research has established that this is an effective way to “prime” people into feeling as if they are currently in such a position. Each group (high power and low power) was then split into two further groups. Half were asked to rate, on a nine-point morality scale (with one being highly immoral and nine being highly moral), how objectionable it would be for other people to over-report travel expenses at work. The other half were asked to participate in a game of dice.

The dice players were told to roll two ten-sided dice (one for “tens” and one for “units”) in the privacy of an isolated cubicle, and report the results to a lab assistant. The number they rolled, which would be a value between one and 100 (two zeros), would determine the number of tickets that they would be given in a small lottery that was run at the end of the study.

In the case of the travel expenses—when the question hung on the behaviour of others—participants in the high-power group reckoned, on average, that over-reporting rated as a 5.8 on the nine-point scale. Low-power participants rated it 7.2. The powerful, in other words, claimed to favour the moral course. In the dice game, however, high-power participants reported, on average, that they had rolled 70 while low-power individuals reported an average 59. Though the low-power people were probably cheating a bit (the expected average score would be 50), the high-power volunteers were undoubtedly cheating—perhaps taking the term “high roller” rather too literally.

Taken together, these results do indeed suggest that power tends to corrupt and to promote a hypocritical tendency to hold other people to a higher standard than oneself. To test the point further, though, Dr Lammers and Dr Galinsky explicitly contrasted attitudes to self and other people when the morally questionable activity was the same in each case. Having once again primed two groups of participants to be either high-power or low-power, they then asked some members of each group how acceptable it would be for someone else to break the speed limit when late for an appointment and how acceptable it would be for the participant himself to do so. Others were asked similar questions about tax declarations.

Only the little people pay taxes…

In both cases participants used the same one-to-nine scale employed in the first experiment. The results showed that the powerful do, indeed, behave hypocritically. They felt that others speeding because they were late warranted a 6.3 on the scale whereas speeding themselves warranted a 7.6. Low-power individuals, by contrast, saw everyone as equal. They scored themselves as 7.2 and others at 7.3—a statistically insignificant difference. In the case of tax dodging, the results were even more striking. High-power individuals felt that when others broke tax laws this rated as a 6.6 on the morality scale, but that if they did so themselves this rated as a 7.6. In this case low-power individuals were actually easier on others and harsher on themselves, with values of 7.7 and 6.8 respectively.

These results, then, suggest that the powerful do indeed behave hypocritically, condemning the transgressions of others more than they condemn their own. Which comes as no great surprise, although it is always nice to have everyday observation confirmed by systematic analysis. But another everyday observation is that powerful people who have been caught out often show little sign of contrition. It is not just that they abuse the system; they also seem to feel entitled to abuse it. To investigate this point, Dr Lammers and Dr Galinsky devised a third set of experiments. These were designed to disentangle the concept of power from that of entitlement. To do this, the researchers changed the way they primed people.

A culture of entitlement

Half of 105 participants were asked to write about a past experience in which they had legitimately been given a role of high or low power. The others were asked to write about an experience of high or low power where they did not feel their power (or lack of it) was legitimate. All of the volunteers were then asked to rate how immoral it would be for someone to take an abandoned bicycle rather than report the bicycle to the police. They were also asked, if they were in real need of a bicycle, how likely they would be to take it themselves and not report it.

The “powerful” who had been primed to believe they were entitled to their power readily engaged in acts of moral hypocrisy. They assigned a value of 5.1 to others engaging in the theft of the bicycle while rating the action at 6.9 if they were to do it themselves. Among participants in all of the low-power states, morally hypocritical behaviour inverted itself, as it had in the case of tax fraud. “Legitimate” low-power individuals assigned others a score of 5.1 if they stole a bicycle and gave themselves a 4.3. Those primed to feel that their lack of power was illegitimate behaved similarly, assigning values of 4.7 and 4.4 respectively.

However, an intriguing characteristic emerged among participants in high-power states who felt they did not deserve their elevated positions. These people showed a similar tendency to that found in low-power individuals—to be harsh on themselves and less harsh on others—but the effect was considerably more dramatic. They felt that others warranted a lenient 6.0 on the morality scale when stealing a bike but assigned a highly immoral 3.9 if they took it themselves. Dr Lammers and Dr Galinsky call this reversal “hypercrisy”.

They argue, therefore, that people with power that they think is justified break rules not only because they can get away with it, but also because they feel at some intuitive level that they are entitled to take what they want. This sense of entitlement is crucial to understanding why people misbehave in high office. In its absence, abuses will be less likely. The word “privilege” translates as “private law”. If Dr Lammers and Dr Galinsky are right, the sense which some powerful people seem to have that different rules apply to them is not just a convenient smoke screen. They genuinely believe it.

What explains hypercrisy is less obvious. It is known, though, from experiments on other species that if those at the bottom of a dominance hierarchy show signs of getting uppity, those at the top react both quickly and aggressively. Hypercrisy might thus be a signal of submissiveness—one that is exaggerated in creatures that feel themselves to be in the wrong place in the hierarchy. By applying reverse privileges to themselves, they hope to escape punishment from the real dominants. Perhaps the lesson, then, is that corruption and hypocrisy are the price that societies pay for being led by alpha males (and, in some cases, alpha females). The alternative, though cleaner, is leadership by wimps.
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Re: The Metrics of Ruling the World.

Postby Wombaticus Rex » Wed Jul 25, 2012 2:39 pm

^^Thank you!

via: http://www.theatlantic.com/magazine/arc ... tor/7711/#

Misleading Indicator
Will the Great Recession finally end our misguided obsession with gross domestic product?

Here’s a question no one ever asks about the Great Recession: How do we even know it’s happening? Daily, almost, someone releases employment figures, production estimates, consumer-confidence indexes—almost all of them bad. There’s no need to wonder what’s happening when information about everyone’s problems constantly streams across your TV screen.

And in this dolorous statistical parade, no number is quite so central to public life as the gross domestic product. Political scientists build formulas around it to predict who will win the presidency. The stock market trembles at the approach of new quarterly figures. Other economic statistics, like budget deficits or health-care spending, are quoted as percentages of GDP. It has become the common denominator of economic well-being.

But GDP’s broad dominion has long had its critics. It was never meant to be the measure of our well-being, they say, only the measure of our production—literally, the total value of the goods and services produced within the national borders in a given year. While the quest for some broader measure of progress has been going on for a while (more than a decade ago, for example, The Atlantic was running articles like “If the GDP Is Up, Why Is America Down?”), it may finally be gaining traction at a time when people understand, as never before, how easily GDP and well-being can diverge.

One of the leaders of a huge global effort to build a better statistical yardstick has been Enrico Giovannini, until recently the chief statistician of the Organization for Economic Cooperation and Development. Though the OECD is the global coordinator of the project, its partners represent a who’s who of economic development: the World Bank, various UN programs, the African Development Bank, and the European Commission. They are looking to create more-reliable metrics for measuring change in our health, education, the environment—the many ways that human beings make themselves better off or worse off. This fall, in the wake of the OECD’s third World Forum on Statistics, Knowledge, and Policy, these groups are set to move ahead on a broader, better set of indexes.

Crisis seems to be the mother of statistics. The germ of the idea that eventually became GDP emerged after World War I, when American economists who had been frustrated by the lack of reliable statistics to guide war production founded the National Bureau of Economic Research (despite its name, the NBER is a private organization). Still, not until the Great Depression did we finally get our first national income accounts, which measured the annual income of people, companies, and the government.

It is rare for people to write about that era without taking a swipe at Herbert Hoover, but we might be kinder if we remembered just how little information he had. With no national income accounts, Hoover had to rely on fragmentary indicators such as freight-car loadings, steel production, and the gyrations of the New York Stock Exchange. There weren’t even comprehensive national unemployment statistics, because Congress didn’t authorize the Department of Labor to collect them until the middle of 1930. Forget Hoover’s economic theory, most of which was pretty bad; the man barely had any data.

Beyond newspaper anecdotes and a bunch of unrelated industrial indexes, he had little way of knowing just how awful things were or, more important, exactly where intervention might be needed. It’s as if someone hired you to cater a lavish formal dinner—then gave you no head count, a partial list of available ingredients, and the July 1953 issue of Gourmet magazine to work with.

That started to change in 1932. The legendary progressive Senator Robert La Follette introduced a resolution that directed the secretary of commerce to estimate national income for the prior three years. Unable to find anyone in the department who was up to the task, Commerce hired Simon Kuznets, who had already begun working on the problem at the NBER. He spent the next 14 years creating a system of national accounts that, with constant refinements and additions, we still use today.

It’s almost impossible to overstate what a titanic achievement this was. But here’s something that hints at the magnitude of the difficulties: despite his earlier work, Kuznets didn’t make the first tentative presentation of his figures to Congress until 1934. By 1941, he had expanded the series backward to 1919, and all the way to 1938. Measures of output—the true forerunners of GDP—didn’t follow until 1942, as war production ramped up. (Total mobilization depended on extensive statistics, which is why the Nobel Prize winner Paul Samuelson called World WarII “an economist’s war.”) The Great Depression and World WarII created the modern world in a lot of ways. They also created one of the primary lenses through which we view it.

Unfortunately, that lens is a trifle distorted. It counts the dollar value of our output, but not the actual improvement in our lives, or even in our economic condition.

Think about a house, any of the millions that were constructed during the bubble that burst in 2008. Let’s make it a nice house: four bedrooms, 3.5 baths, with an attached garage and a quarter-acre lot. During its construction, that house did its own little bit to boost GDP. Lumber was purchased and swathed in fluttering robes of Tyvek. Tiles were pressed out of clay and nailed to the roof. Pipe was laid, glass was sealed into the window slots, granite was hewn from a Vermont mountain and shipped all the way to its kitchen counters. All of this output, which swelled GDP (at least to the tune of its purchase price), has ended up in … nothing. The house, in an exurban cul-de-sac, sits empty while bankers, borrowers, and regulators squabble. One of the estimated 2.4million excess homes on the market, its only function right now is to bankrupt its owner.

GDP does not, and cannot, reflect the waste of enormous effort, and precious natural resources, that went into building something that suddenly no one wants. Moreover, it misses many other aspects of our existence. Strip-mining a picturesque mountaintop, or clear-cutting a primeval forest, shows up in GDP only as a boost to output. Meanwhile, in India’s national accounts, all of Mother Teresa’slabors among the poor would have had only the most minimal possible impact. GDP can record how much money we spend on health care or education; it cannot tell us whether the services we are buying are any good.

Consider the housewife, or rather, her modern successor, the stay-at-home mom. There’sevidence that the recession may have forced her back onto the job market. Since the downturn, the labor-force participation rate for working-age men has fallen significantly. But the participation rate of women has actually ticked up. The most likely explanation is that women whose husbands have been laid off or had their income cut are going back into the workplace (at least temporarily) to help make ends meet.

Some feminists might rejoice, but to an economist, or a social conservative, this development is almost certainly a bad thing. Assuming that she and her family both wanted her to stay home, each woman who leaves for the office out of economic necessity represents a loss to the country, a loss of what economists call utility and what we may think of as net national happiness.

As she heads back to the workplace, that mother will be boosting GDP. If her husband has lost not his job but merely some income from sales commissions or a business, she will probably have to pay for child care. She may need to buy new work clothes. Money will be spent on commuting, and the family will probably shift away from homemade meals to costlier prepared foods that save time. All of these transactions further swell the national income accounts. Yet all of them also represent a decrease in life satisfaction.

These are but some of the reasons why analysts on the left and right think we need a better measure of national welfare than GDP. But if Kuznets had a hard time figuring out how to measure all the transactions in our marketplace, how much harder will it be for his multilateral successors to put a number on the things we often call priceless?

There are, broadly speaking, three ways you can try to build a “well-being” index. You can use what economists call “shadow prices,” imputing dollar values to the various things that contribute to our quality of life. But the index usually ends up being incredibly sensitive to your starting assumptions. As the economist Tyler Cowen says, “How much is a fish worth? .00000000000001 cents per fish or .0000000000000000000000000001 cents per fish? It makes a big difference!” He wryly adds, “The point of a GDP statistic is to drain away those sorts of problems. The point is not to commit you to an anti-fish position.”

The second approach is to attach weights to various indicators and use them to build a composite gauge like the Human Development Index. Unfortunately, the weights will always be somewhat arbitrary. That inherent subjectivity makes the accuracy of your index somewhat suspect, and leaves the people who created it open to accusations of bias.

Take the World Health Organization’s infamous ranking of national health systems, which in 2000 put the United States below such health-care luminaries as Oman, Colombia, and Morocco. Would you really rather get sick in Bogotá than in Berkeley? The WHO analysts heavily weighted somewhat murky estimates like equality of access, knocking us down to two places above Cuba, where antibiotics are scarce for everybody. This is so bizarre that conservatives don’t sound entirely crazy when they voice suspicions that the WHO chose its weights to produce just this result. The WHO has since stopped publishing the index.

When all else fails, of course, you can just ask people: Are you better off now than you were three years ago? Even this approach poses problems. As any marketing expert can tell you, the difference between what people say they want, and what they actually want, can be large. Their memories of years past are quite poor, and often highly selective. Survey respondents are vulnerable to all sorts of influences, from how the question is framed to a desire to impress the interviewers. That’s why polls often find substantial majorities against raising taxes and against cutting any major programs—and for reducing the deficit. Surveys also show that heterosexual men on average have many more sexual partners than heterosexual women do, which is mathematically impossible.

Besides, much of the progress in important areas of life is invisible to most people. You are indisputably better off having the option of getting a liver transplant if you should need one. But unless your skin actually starts turning yellow, you probably never think about it.

The OECD project’s daunting task is to find better ways to handle these kinds of obstacles. One possible approach is to focus on hard indicators that we can measure in a fairly standard way. But these are scarce for some aspects of life, and even when they exist, can be tricky to interpret. Life expectancy, for example, seems pretty objective. It’s a metric on which the United States does relatively poorly, causing us endless consternation. A few years ago, however, the health-care economists Robert Ohsfeldt and John Schneider recalculated the numbers after controlling for deaths from homicides and traffic accidents. Because these things tend to strike very young people, they can have an outsize impact on mortality statistics. Those deaths reflect America’s crime policy and its driving habits more than the effectiveness of its health-care system. And if you remove them from the picture, say Ohsfeldt and Schneider, America jumps to the top of the life-expectancy tables. Assuming they’re correct, does America have good health, or bad? Neither answer is the obviously right one. Such conundrums will vex analysts long into the future.

But of course, measurement problems also bedevil GDP, which is why the U.S. Bureau of Economic Analysis employs economists and statisticians rather than bookkeepers. Whatever the difficulties, the OECD project’s leaders, like their forebears during the Great Depression, are convinced of the urgent need to get a better handle on the progress our societies are making.

That sense of urgency doesn’t mean we should look for speedy results. Even though his staff had to tabulate the results without the aid of computers, Kuznets and his team produced the first national accounts more rapidly than his successors will create the newer, better set of statistics they aspire to. For all the burdens under which Kuznets labored, he had one advantage: the absence of an existing economic establishment. He did not have to convene working groups and seminars to make sure that academics around the world and the staffs of dozens of institutions felt included. Nor, once he was finished, did he have to convince governments that they should care. Giovannini describes today’s next step as developing “a framework that at least lists the domains that outline what this project should look like.” That’s several nouns away from any sort of working model.

It doesn’t help that Giovannini has left the OECD to head Italy’s statistics authority. But efforts like these have always been larger than one person. When our grandchildren face their financial Waterloo, they may have Giovannini’s brainchildren to help guide them through it. But we will have to muddle through with the legacy of Kuznets and the generations of economists who expanded and improved on his remarkable achievement.
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Re: The Metrics of Ruling the World.

Postby Aurataur » Fri Jul 27, 2012 2:30 pm

I'm sure you're familiar with this quote, but it seems appropriate in response to the above article.

"Too much and for too long, we seemed to have surrendered personal excellence and community values in the mere accumulation of material things. Our Gross National Product, now, is over $800 billion dollars a year, but that Gross National Product - if we judge the United States of America by that - that Gross National Product counts air pollution and cigarette advertising, and ambulances to clear our highways of carnage. It counts special locks for our doors and the jails for the people who break them. It counts the destruction of the redwood and the loss of our natural wonder in chaotic sprawl. It counts napalm and counts nuclear warheads and armored cars for the police to fight the riots in our cities. It counts Whitman's rifle and Speck's knife, and the television programs which glorify violence in order to sell toys to our children. Yet the gross national product does not allow for the health of our children, the quality of their education or the joy of their play. It does not include the beauty of our poetry or the strength of our marriages, the intelligence of our public debate or the integrity of our public officials. It measures neither our wit nor our courage, neither our wisdom nor our learning, neither our compassion nor our devotion to our country, it measures everything in short, except that which makes life worthwhile. And it can tell us everything about America except why we are proud that we are Americans."


- Robert F. Kennedy, at the University of Kansas March 18, 1968
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Re: The Metrics of Ruling the World.

Postby Wombaticus Rex » Sat Aug 04, 2012 1:22 pm

Via: http://finance.yahoo.com/blogs/breakout ... 37674.html

It is widely regarded as the most important barometer of them all, and fittingly, the monthly jobs report gets more attention and more coverage than almost all other economic data combined. Unfortunately, it is also broken.

That's right. For all its stature, the payroll report (which will be released Friday) has a major flaw — and it's a doozy. The headline unemployment rate is essentially a bunch of bunk.

The current 8.2% figure you hear about so often is wildly inaccurate and doesn't fairly reflect the true state of the nation's labor force. It's a deficiency that Wall Street-types have long adjusted for with a wink-wink sort of acceptance, knowing full well that the so-called "U-3" headline number is actually a quagmire of exclusions and adjustments that under-reports the real situation by as much as 50%.

"It's simply a matter of Congress saying, 'We're not going to use this number. We're going to use the other numbers that you've calculated that we think are more representative of what the unemployment situation really looks like in this country,'" says Congressman Duncan Hunter in the attached video. He points out that changing the calculation wouldn't cost a thing, since the data is already available.

It's a problem that he and a growing number of lawmakers want to fix, and it's why the California Republican has sponsored the Real Unemployment Calculation Act — a legislative fix that would require the Department of Labor to get real about what it tells the American people.

In fact, unbeknownst to most people, the Bureau of Labor Statistics (BLS) tabulates not one but six different unemployment rates, ranging from U-1 to U6 (4.2% to 14.9%).

Hunter's bill would make the U5 result the new official unemployment rate through what he calls "a little magic along with the math." According to the BLS website, the U-5 rate includes "discouraged workers, plus all other persons marginally attached to the labor force." Other carve-outs include categories such as "underemployed" and "part-time for economic reasons," as well as the roughly 87 million people who have dropped out of the labor force altogether. That final fact alone has cut the so-called labor participation rate to 63.8% — the lowest it has been in 30 years.

"It makes everybody look bad," Hunter says. "This isn't about the President or the Republican Party or the Democratic Party. It's about the American people knowing what the number is, and it being a true representation of what we see in everyday life."

While Hunter is the first to admit there's no perfect method or number, he argues that we at least ought to "ballpark it right, and I think we're pretty far off."
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Re: The Metrics of Ruling the World.

Postby Wombaticus Rex » Fri Jan 04, 2013 10:52 am

Via: http://www.imf.org/external/pubs/ft/fan ... cs/gdp.htm

Gross Domestic Product: An Economy’s All

Tim Callen

When it is growing, especially if inflation is not a problem, workers and businesses are generally better off than when it is not

Many professions commonly use abbreviations. To doctors, accountants, and baseball players, the letters MRI (magnetic resonance imaging), GAAP (generally accepted accounting principles), and ERA (earned run average), respectively, need no explanation. To someone unfamiliar with these fields, however, without an explanation these initialisms are a stumbling block to a better understanding of the subject at hand.

Economics is no different. Economists use many abbreviations. One of the most common is GDP, which stands for gross domestic product. It is often cited in newspapers, on the television news, and in reports by governments, central banks, and the business community. It has become widely used as a reference point for the health of national and global economies. When GDP is growing, especially if inflation is not a problem, workers and businesses are generally better off than when it is not.

Measuring GDP
GDP measures the monetary value of final goods and services—that is, those that are bought by the final user—produced in a country in a given period of time (say a quarter or a year). It counts all of the output generated within the borders of a country. GDP is composed of goods and services produced for sale in the market and also includes some nonmarket production, such as defense or education services provided by the government. An alternative concept, gross national product, or GNP, counts all the output of the residents of a country. So if a German-owned company has a factory in the United States, the output of this factory would be included in U.S. GDP, but in German GNP.

Not all productive activity is included in GDP. For example, unpaid work (such as that performed in the home or by volunteers) and black-market activities are not included because they are difficult to measure and value accurately. That means, for example, that a baker who produces a loaf of bread for a customer would contribute to GDP, but would not contribute to GDP if he baked the same loaf for his family (although the ingredients he purchased would be counted).

Moreover, “gross” domestic product takes no account of the “wear and tear” on the machinery, buildings, and so on (the so-called capital stock) that are used in producing the output. If this depletion of the capital stock, called depreciation, is subtracted from GDP we get net domestic product.

Theoretically, GDP can be viewed in three different ways:

● The production approach sums the “value-added” at each stage of production, where value-added is defined as total sales less the value of intermediate inputs into the production process. For example, flour would be an intermediate input and bread the final product; or an architect’s services would be an intermediate input and the building the final product.

● The expenditure approach adds up the value of purchases made by final users—for example, the consumption of food, televisions, and medical services by households; the investments in machinery by companies; and the purchases of goods and services by the government and foreigners.

● The income approach sums the incomes generated by production—for example, the compensation employees receive and the operating surplus of companies (roughly sales less costs).

GDP in a country is usually calculated by the national statistical agency, which compiles the information from a large number of sources. In making the calculations, however, most countries follow established international standards. The international standard for measuring GDP is contained in the System of National Accounts, 1993, compiled by the International Monetary Fund, the European Commission, the Organization for Economic Cooperation and Development, the United Nations, and the World Bank.

Real GDP
One thing people want to know about an economy is whether its total output of goods and services is growing or shrinking. But because GDP is collected at current, or nominal, prices, one cannot compare two periods without making adjustments for inflation. To determine “real” GDP, its nominal value must be adjusted to take into account price changes to allow us to see whether the value of output has gone up because more is being produced or simply because prices have increased. A statistical tool called the price deflator is used to adjust GDP from nominal to constant prices.

GDP is important because it gives information about the size of the economy and how an economy is performing. The growth rate of real GDP is often used as an indicator of the general health of the economy. In broad terms, an increase in real GDP is interpreted as a sign that the economy is doing well. When real GDP is growing strongly, employment is likely to be increasing as companies hire more workers for their factories and people have more money in their pockets. When GDP is shrinking, as it did in many countries during the recent global economic crisis, employment often declines. In some cases, GDP may be growing, but not fast enough to create a sufficient number of jobs for those seeking them. But real GDP growth does move in cycles over time. Economies are sometimes in periods of boom, and sometimes in periods of slow growth or even recession (with the latter often defined as two consecutive quarters during which output declines). In the United States, for example, there were six recessions of varying length and severity between 1950 and 2011. The National Bureau of Economic Research makes the call on the dates of U.S. business cycles.

Comparing GDPs of two countries
GDP is measured in the currency of the country in question. That requires adjustment when trying to compare the value of output in two countries using different currencies. The usual method is to convert the value of GDP of each country into U.S. dollars and then compare them. Conversion to dollars can be done either using market exchange rates—those that prevail in the foreign exchange market—or purchasing power parity (PPP) exchange rates. The PPP exchange rate is the rate at which the currency of one country would have to be converted into that of another to purchase the same amount of goods and services in each country. There is a large gap between market and PPP-based exchange rates in emerging market and developing countries. For most emerging market and developing countries, the ratio of the market and PPP U.S. dollar exchange rates is between 2 and 4. This is because nontraded goods and services tend to be cheaper in low-income than in high-income countries—for example, a haircut in New York is more expensive than in Bishkek—even when the cost of making tradable goods, such as machinery, across two countries is the same. For advanced economies, market and PPP exchange rates tend to be much closer. These differences mean that emerging market and developing countries have a higher estimated dollar GDP when the PPP exchange rate is used.

The IMF publishes an array of GDP data on its website (www.imf.org). International institutions such as the IMF also calculate global and regional real GDP growth. These give an idea of how quickly or slowly the world economy or the economies in a particular region of the world are growing. The aggregates are constructed as weighted averages of the GDP in individual countries, with weights reflecting each country’s share of GDP in the group (with PPP exchange rates used to determine the appropriate weights).

What GDP does not reveal
It is also important to understand what GDP cannot tell us. GDP is not a measure of the overall standard of living or well-being of a country. Although changes in the output of goods and services per person (GDP per capita) are often used as a measure of whether the average citizen in a country is better or worse off, it does not capture things that may be deemed important to general well-being. So, for example, increased output may come at the cost of environmental damage or other external costs such as noise. Or it might involve the reduction of leisure time or the depletion of nonrenewable natural resources. The quality of life may also depend on the distribution of GDP among the residents of a country, not just the overall level. To try to account for such factors, the United Nations computes a Human Development Index, which ranks countries not only based on GDP per capita, but on other factors, such as life expectancy, literacy, and school enrollment. Other attempts have been made to account for some of the shortcomings of GDP, such as the Genuine Progress Indicator and the Gross National Happiness Index, but these too have their critics.
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Re: The Metrics of Ruling the World.

Postby Wombaticus Rex » Tue Jul 29, 2014 11:58 am

When it comes to discussing money, incomprehension is a form of consent.

Via: http://www.newyorker.com/magazine/2014/ ... ey-talks-6

Money Talks: Learning the language of finance.

By John Lanchester

The most important mystery of ancient Egypt concerned the annual inundation of the Nile floodplain. The calendar was divided into three seasons linked to the river and the agricultural cycle it determined: akhet, or the inundation; peret, the growing season; and shemu, the harvest. The size of the harvest depended on the size of the flood: too little water, and there would be famine; too much, and there would be catastrophe; just the right amount, and the whole country would bloom and prosper. Every detail of Egyptian life was shaped by the flood. Even the tax system was based on the level of the water, which dictated how successful farmers would be in the subsequent season. Priests performed complicated rituals to divine the nature of that year’s flood and the resulting harvest. The religious élite had at their disposal a rich, emotionally satisfying mythological system; a subtle language of symbols which drew on that mythology; and a position of unchallenged power at the center of their extraordinarily stable society, one that remained in an essentially static condition for thousands of years.

But the priests were cheating, because they had something else, too: Nilometers. These were devices that consisted of large, permanent measuring stations, with lines and markers to predict the level of the annual flood, situated in temples to which only priests and rulers were granted access. Added to accurate records of flood patterns dating back for centuries, Nilometers were a necessary tool for control of Egypt. They helped give the priests and the ruling class much of their authority.

The world is full of priesthoods. On the one hand, there are the calculations that the pros make in private; on the other, elaborate ritual and language, designed to bamboozle and mystify and intimidate. To the outsider, the realm of finance looks a lot like the old Nile game. In The Economist, not long ago, I read about a German bank that had some observers worried. The journalist thought that the bank would be O.K., and that “holdings of peripheral euro-zone government bonds can be gently unwound by letting them run off.” What might that mean? There’s something kooky about the way the metaphor mixes unwinding and holding and running off, like the plot of a screwball comedy.

It’s the same when you hear money people talk about the effect of QE2 on M3, or the supply-side impact of some policy or other, or the effects of bond-yield retardation or of a scandal involving forward-settling E.T.F.s, or M.B.S.s, or subprime loans and REITs and C.D.O.s and C.D.S.s. You are left wondering whether somebody is trying to con you, or to obfuscate and blather so that you can’t tell what’s being talked about. During the recent credit crunch, many suspected that the terms for the products involved were deliberately obscure: it was hard to take in the fact that C.D.S.s were on the verge of bringing down the entire global financial system when you’d never even heard of them until about two minutes before.

Sometimes the language of finance really is obscure, and does hide the truth. The 2008 implosion featured many such terms, epitomized by financial instruments with names like “mezzanine R.M.B.S. synthetic C.D.O.” More often, though, it’s complicated because the underlying realities are complicated. The lack of transparency isn’t necessarily sinister, and has its parallel in other fields—in the world of food and wine, for instance. The French word baveuse means, literally, “drooling,” which, in the context of food, we would all agree, is not a good look. Baveuse, though, is also used to describe the texture of a perfect omelette, where the outside is cooked and the inside is set but still faintly runny. It’s a useful term to know, because it helps you to recognize the thing more easily, but the cost is that you can talk about it only with other people who also know the term.

The language of money works like that, too. It is potent and efficient, but also exclusive and excluding. Explanations are hard to hold on to, because an entire series of them may be compressed into a phrase, or even a single word.

When I was growing up, my father worked for the Hongkong and Shanghai Banking Corporation. His kind of banking wasn’t at all the fancy go-go modern investment banking that wrecked the global financial system in 2008. It involved lending to small businesses to get them started. At home, my father couldn’t bear to talk about money; his own father had been the type of control freak who uses money to express that control. If I brought up the question of my allowance, it appeared to cause him actual physical pain. On the other hand, when the subject was at one remove, he was vivacious and funny at telling stories and explaining how things worked, so much so that, forty years later, some of the things he said still make me smile. When he first joined the bank, it had a telegraphic codebook for communicating with the head office, in Hong Kong. The codebook quoted a typical message: “The marketplace is dominated by small Manchurian bears.” Dad explained that the message indicated the influence of pessimistic small-scale investors who were either based in Manchuria or had made investments there. What I liked was the image of those bears, which I imagined were like the small bears in a Tintin book, causing the market stallholders to flee in terror as they rampaged among the carts and awnings, on a furious quest for nuts and honey. Even as a child, I was struck by the fact that the decoded phrase itself was in need of further decoding. But the fact that my father worked in the world of money gave me a sense that it was, and is, comprehensible.

Many people don’t have that advantage. They feel put off or defeated by anything having to do with money and economics. It’s almost as if they didn’t have permission to understand it. I did have permission to understand it, if I wanted to, and ten or so years ago, while working on a novel about contemporary London, I began to teach myself how. One of the things that happens to you—or, at any rate, happened to me—as a novelist is that you become increasingly preoccupied with this question: What’s the story behind the evident story? In my case, the story behind the story turned out to concern money. I realized that you can’t really write a novel about London and ignore the City—London’s financial center—because finance is so integral to the place that London has become. I started to grow more curious about the economic forces behind the surface realities of life. I wrote articles on Microsoft, on Walmart, and on Rupert Murdoch. I came to think that there was a gap in the culture: most of the writing on these subjects was done either by business journalists who thought that everything about the world of business was great or by furious opponents from the left who thought that everything about it was so terrible that all that was needed was rageful denunciation. Both sides missed the complexities, and therefore the interest, of the story.

That was how I ended up getting my education in the language of money—by following the subject in order to write about it. It wasn’t a crash course. For years, I read the financial papers and pages, and kept up with the economic news. Every time I didn’t understand a term, I’d Google it or turn to one of the books I was accumulating on the subject.

Take the earlier example of the German bank and The Economist ’s analysis that “holdings of peripheral euro-zone government bonds can be gently unwound by letting them run off.” What that phrase really means is this: the bank owns too much debt from euro-zone countries like Greece, Italy, Spain, Portugal, and Ireland, but, rather than sell it off, the bank waits for the loan period of the debt to come to an end, and then doesn’t buy any more of it. In this way, the amount of debt owned by the bank gradually decreases over time, instead of shrinking quickly after a selloff. In short, the holdings will be gently unwound by letting them run off.

Money people don’t need to explain that terminology to themselves, or to anyone to whom they’re in the habit of speaking. As for everyone else—you’ve already lost them.

...

Using the language of money does not imply acceptance of any particular moral or ideological framework. Money person A and money person B, talking about the effect of, for instance, quantitative easing, may have different economic philosophies. Person A might be a free-spending Keynesian who thinks that quantitative easing—the government’s buying back its own debt from banks, companies, and sometimes individuals in order to increase the money supply—is the only thing saving the economy from an apocalyptic meltdown. Person B might think that it’s a formula for ruin, is already wreaking havoc on savers, and is on course to turn the United States into a version of Weimar Germany. They completely disagree about everything they’re discussing, and yet they have a shared language that enables them to discuss it with concision and force. A shared language doesn’t necessarily imply a shared viewpoint; what it does is make a certain kind of conversation possible.

This kind of conversation is worth having. The neoliberal consensus in economics presents itself as a set of self-evident laws. Low tax rates, a smaller state, a business-friendly climate, free markets in international trade, rising levels of inequality and an ever-bigger gap between the rich, especially the super-rich, and the rest—supposedly, these are just the facts of economic life if you want your economy to grow and your society to become richer. Many people are eager to tell us that there is no alternative to the existing economic order, that we have to accept things as they are. That isn’t true. Marx was right when he said that “men make their own history, but not under circumstances of their own choosing.” We didn’t create the world that we inherited, but we don’t have to leave it the way we found it.

My father once told me about the first colleague he ever knew to go to jail. This was in the fifties, in Calcutta, where Dad was his bank’s accountant, a rank roughly equivalent to deputy. A junior banker was found to have been stealing. He did it not to be rich but to fund a life style that was slightly more lavish than he could afford, so that he could have parties at which he served imported spirits and cigarettes, and slapped his guests on the back, and said, “Only the best for my friends, none of that Indian rubbish.”

“Every case I’ve known of people stealing from the bank has been like that,” my father said. “People wanting the thing they can’t quite have—that causes more trouble than anything else.” I think he’d have said that this phenomenon was now operating across entire societies, as people tried to cure rising income inequality by taking on debt. That life you can’t quite have? Borrow, and it shall be yours. My father, who had his generation’s horror of debt, would have shaken his head at that. He would have pointed out that when the finance industry says “credit,” what it really means is “debt.” If you don’t know that, you are likely to get into trouble.

The language of money is a powerful tool, and it is also a tool of power. Incomprehension is a form of consent. If we allow ourselves not to understand this language, we are signing off on the way the world works today—in particular, we are signing off on the prospect of an ever-widening gap between the rich and everyone else, a world in which everything about your life is determined by the accident of who your parents are. Those of us who are interested in stopping that from happening need to learn how to measure the level of the Nile for ourselves.
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Re: The Metrics of Ruling the World.

Postby Wombaticus Rex » Wed Feb 18, 2015 3:31 pm

We reach the point of diminishing marginal predictive returns for knowledge disconcertingly quickly. In this age of academic hyperspecialization, there is no reason for supposing that contributors to top journals—distinguished political scientists, area study specialists, economists, and so on—are any better than journalists or attentive readers of the New York Times in ‘reading’ emerging situations.”


Via: http://www.newyorker.com/magazine/2005/ ... -an-expert

“Expert Political Judgment” is not a work of media criticism. Tetlock is a psychologist—he teaches at Berkeley—and his conclusions are based on a long-term study that he began twenty years ago. He picked two hundred and eighty-four people who made their living “commenting or offering advice on political and economic trends,” and he started asking them to assess the probability that various things would or would not come to pass, both in the areas of the world in which they specialized and in areas about which they were not expert. Would there be a nonviolent end to apartheid in South Africa? Would Gorbachev be ousted in a coup? Would the United States go to war in the Persian Gulf? Would Canada disintegrate? (Many experts believed that it would, on the ground that Quebec would succeed in seceding.) And so on. By the end of the study, in 2003, the experts had made 82,361 forecasts. Tetlock also asked questions designed to determine how they reached their judgments, how they reacted when their predictions proved to be wrong, how they evaluated new information that did not support their views, and how they assessed the probability that rival theories and predictions were accurate.

Tetlock got a statistical handle on his task by putting most of the forecasting questions into a “three possible futures” form. The respondents were asked to rate the probability of three alternative outcomes: the persistence of the status quo, more of something (political freedom, economic growth), or less of something (repression, recession). And he measured his experts on two dimensions: how good they were at guessing probabilities (did all the things they said had an x per cent chance of happening happen x per cent of the time?), and how accurate they were at predicting specific outcomes. The results were unimpressive. On the first scale, the experts performed worse than they would have if they had simply assigned an equal probability to all three outcomes—if they had given each possible future a thirty-three-per-cent chance of occurring. Human beings who spend their lives studying the state of the world, in other words, are poorer forecasters than dart-throwing monkeys, who would have distributed their picks evenly over the three choices.

Tetlock also found that specialists are not significantly more reliable than non-specialists in guessing what is going to happen in the region they study. Knowing a little might make someone a more reliable forecaster, but Tetlock found that knowing a lot can actually make a person less reliable. “We reach the point of diminishing marginal predictive returns for knowledge disconcertingly quickly,” he reports. “In this age of academic hyperspecialization, there is no reason for supposing that contributors to top journals—distinguished political scientists, area study specialists, economists, and so on—are any better than journalists or attentive readers of the New York Times in ‘reading’ emerging situations.” And the more famous the forecaster the more overblown the forecasts. “Experts in demand,” Tetlock says, “were more overconfident than their colleagues who eked out existences far from the limelight.”

People who are not experts in the psychology of expertise are likely (I predict) to find Tetlock’s results a surprise and a matter for concern. For psychologists, though, nothing could be less surprising. “Expert Political Judgment” is just one of more than a hundred studies that have pitted experts against statistical or actuarial formulas, and in almost all of those studies the people either do no better than the formulas or do worse. In one study, college counsellors were given information about a group of high-school students and asked to predict their freshman grades in college. The counsellors had access to test scores, grades, the results of personality and vocational tests, and personal statements from the students, whom they were also permitted to interview. Predictions that were produced by a formula using just test scores and grades were more accurate. There are also many studies showing that expertise and experience do not make someone a better reader of the evidence. In one, data from a test used to diagnose brain damage were given to a group of clinical psychologists and their secretaries. The psychologists’ diagnoses were no better than the secretaries’.

The experts’ trouble in Tetlock’s study is exactly the trouble that all human beings have: we fall in love with our hunches, and we really, really hate to be wrong. Tetlock describes an experiment that he witnessed thirty years ago in a Yale classroom. A rat was put in a T-shaped maze. Food was placed in either the right or the left transept of the T in a random sequence such that, over the long run, the food was on the left sixty per cent of the time and on the right forty per cent. Neither the students nor (needless to say) the rat was told these frequencies. The students were asked to predict on which side of the T the food would appear each time. The rat eventually figured out that the food was on the left side more often than the right, and it therefore nearly always went to the left, scoring roughly sixty per cent—D, but a passing grade. The students looked for patterns of left-right placement, and ended up scoring only fifty-two per cent, an F. The rat, having no reputation to begin with, was not embarrassed about being wrong two out of every five tries. But Yale students, who do have reputations, searched for a hidden order in the sequence. They couldn’t deal with forty-per-cent error, so they ended up with almost fifty-per-cent error.

The expert-prediction game is not much different. When television pundits make predictions, the more ingenious their forecasts the greater their cachet. An arresting new prediction means that the expert has discovered a set of interlocking causes that no one else has spotted, and that could lead to an outcome that the conventional wisdom is ignoring. On shows like “The McLaughlin Group,” these experts never lose their reputations, or their jobs, because long shots are their business. More serious commentators differ from the pundits only in the degree of showmanship. These serious experts—the think tankers and area-studies professors—are not entirely out to entertain, but they are a little out to entertain, and both their status as experts and their appeal as performers require them to predict futures that are not obvious to the viewer. The producer of the show does not want you and me to sit there listening to an expert and thinking, I could have said that. The expert also suffers from knowing too much: the more facts an expert has, the more information is available to be enlisted in support of his or her pet theories, and the more chains of causation he or she can find beguiling. This helps explain why specialists fail to outguess non-specialists. The odds tend to be with the obvious.


Much more discussion at this Edge.org conversation between Prof. Tetlock and Daniel Kahneman.
http://edge.org/conversation/win-at-forecasting

"From a sociological point of view, it's a minor miracle that this forecasting tournament is even occurring. Government agencies are not supposed to sponsor exercises that have the potential to embarrass them. It would be embarrassing if it turns out that thousands of amateurs working on relatively small budgets are able to outperform professionals within a multibillion-dollar bureaucracy. That would be destabilizing. If it turns out that junior analysts within that multibillion-dollar bureaucracy can perform better than people high up in the bureaucracy that would be destabilizing. If it turns out that the CEO is not nearly as good as people two or three tiers down in perceiving strategic threats to the business, that's destabilizing."

Thirty years ago we started running some very simple forecasting tournaments and they gradually expanded. We were interested in answering a very simple question, and that is what, if anything, distinguishes political analysts who are more accurate from those who are less accurate on various categories of issues? We looked hard for correlates of accuracy. We were also interested in the prior question of whether political analysts can do appreciably better than chance.

We found two things. One, it's very hard for political analysts to do appreciably better than chance when you move beyond about one year. Second, political analysts think they know a lot more about the future than they actually do. When they say they're 80 or 90 percent confident they're often right only 60 or 70 percent of the time.

There was systematic overconfidence. Moreover, political analysts were disinclined to change their minds when they get it wrong. When they made strong predictions that something was going to happen and it didn’t, they were inclined to argue something along the lines of, "Well, I predicted that the Soviet Union would continue and it would have if the coup plotters against Gorbachev had been more organized," or "I predicted the Canada would disintegrate or Nigeria would disintegrate and it's still, but it's just a matter of time before it disappears," or "I predicted that the Dow would be down 36,000 by the year 2000 and it's going to get there eventually, but it will just take a bit longer."

So, we found three basic things: many pundits were hardpressed to do better than chance, were overconfident, and were reluctant to change their minds in response to new evidence. That combination doesn't exactly make for a flattering portrait of the punditocracy.

...

One of the reactions to my work on expert political judgment was that it was politically naïve; I was assuming that political analysts were in the business of making accurate predictions, whereas they're really in a different line of business altogether. They're in the business of flattering the prejudices of their base audience and they're in the business of entertaining their base audience and accuracy is a side constraint. They don't want to be caught in making an overt mistake so they generally are pretty skillful in avoiding being caught by using vague verbiage to disguise their predictions. They don't say there's a .7 likelihood of a terrorist attack within this span of time. They don't say there's a 1.0 likelihood of recession by the third quarter of 2013. They don't make predictions like that. What they say is if we go ahead with the administration's proposed tax increase there could be a devastating recession in the next six months. "There could be."

The word "could" is notoriously ambiguous. When you ask research subjects what "could" means it depends enormously on the context. "We could be struck by an asteroid in the next 25 seconds," which people might interpret as something like a .0000001 probability, or "this really could happen," which people might interpret as a .6 or .7 probability. It depends a lot on the context. Pundits have been able to insulate themselves from accountability for accuracy by relying on vague verbiage. They can often be wrong, but never in error.
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Re: The Metrics of Ruling the World.

Postby Grizzly » Wed Feb 18, 2015 7:27 pm

Experts know more than you do...
“The more we do to you, the less you seem to believe we are doing it.”

― Joseph mengele
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Re: The Metrics of Ruling the World.

Postby Iamwhomiam » Tue Mar 10, 2015 1:37 pm

The Euro is nearly par with the dollar, so a visit to europe this summer will afford you the privilege of gawking at the uber riche.
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Re: The Metrics of Ruling the World.

Postby Wombaticus Rex » Tue Jul 07, 2015 1:35 pm

Via: http://www.govexec.com/oversight/2015/0 ... ee/117019/

One of those moments where I'm glad I have a data dump thread to place something quite interesting.

The Reports Most Lawmakers Don’t Want You to See

A long-simmering debate continues over whether the in-depth reports prepared for lawmakers by the Congressional Research Service should be published -- just as reports by the Government Accountability Office and Congressional Budget Office are made public.

On June 17, The New York Times revived the issue in an editorial titled “Congressional Research Belongs to the Public.” It cited the nonpartisan high quality of reports written in plain English, which Congress—since the CRS’s founding in 1952—has reserved for itself in what the Times calls “an in-house think tank for lawmakers.”

“Some of these reports are made available to people who know where to look, like diplomats, lobbyists and reporters,” the editorialists wrote. “Constituents can get them from congressional offices if they know what to ask for. Some private groups, like The Federation of American Scientists, post a selection on their websites. But access is very haphazard.” Several private businesses offer the reports at a steep price.

Reps. Leonard Lance, R-N.J., and Mike Quigley, D-Ill., in January introduced a bill to require CRS to publicly release its wares, which drew backing from an array of library groups and transparency advocates.

Steven Aftergood, the blogger on secrecy issues at the Federation of American Scientists, noted that CRS’ staff of 600 (with a $107 million budget) receives 62,000 requests for custom analysis and research for individual members or committees.

He pointed out that a switch to open publication of CRS’s work is backed by the nonprofit Project on Government Oversight, even though its recently retired military analyst Winslow Wheeler warned of a downside. “Officially writing for public consumption can . . . mean that the sometimes technical nature of CRS work will likely be dumbed-down for public consumption,” Wheeler wrote. “It could also mean thickening the bureaucracy at CRS if managers there get the notion they are writing for the public, not directly for staff in Congress.”

On July 2, retired CRS staffer Bob Lyke published a letter in the Times warning that publishing the reports for all comers would do more harm than good while adding to the time it takes staff to produce them. CRS “analysts consult with members of Congress and staff of both parties, conservatives and liberals alike, sometimes with short notice,” he wrote. “Protecting that relationship, which is not perfect but better than outsiders imagine, should be the principal consideration in deciding whether reports are made public.”

Others familiar with CRS note that the agency is not staffed to respond to public inquiries and it would need additional funding to redesign its website to bring the reports out from behind a firewall that currently is accessible only to House and Senate members and staff. What’s more, CRS researchers pay to subscribe to many commercial publications and databases that charge fees based on site licenses for limited numbers of users—costs that would rise if the general public were factored in.

Still, the cordoned-off and “risk-averse” CRS team, as alumni Lyke put it, would hop to if Congress were to change its own policy and let a thousand CRS reports bloom in the public square. The agency takes no public position on the question.


What does it say about concepts like Democracy when the general public are considered dumber than the dumbshits in Congress?

And that's all just noise compared to the bigger question: Why is objective analysis of reality considered dangerous information?
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Re: The Metrics of Ruling the World.

Postby jingofever » Tue Jul 07, 2015 3:26 pm

Wikileaks published a ton of their reports back in 2009: https://wikileaks.org/wiki/Congressiona ... ch_Service
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Re: The Metrics of Ruling the World.

Postby coffin_dodger » Thu Jul 09, 2015 12:26 pm

Womby:
And that's all just noise compared to the bigger question: Why is objective analysis of reality considered dangerous information?


Gosh, it may appear that I'm being a little testy with you today, Mr Wombat - but isn't the biggest question of all "To whom" rather than "Why"?
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Re: The Metrics of Ruling the World.

Postby Wombaticus Rex » Thu Jul 09, 2015 2:37 pm

coffin_dodger » Thu Jul 09, 2015 11:26 am wrote:Gosh, it may appear that I'm being a little testy with you today, Mr Wombat - but isn't the biggest question of all "To whom" rather than "Why"?


Not really, because you're posting that question in a Data Dump thread that clearly identifies "To whom" in the first post to establish the context for the entire thread.

The "Why" is of interest to me because I think most world governments are operating with Napoleon-era concepts and beliefs about the utility of secrecy which are hugely counter-productive to their own strategic goals.

An OSINT approach that was active / participatory instead of passive / obscure would yield a modern day co-op version of Bucky Fuller's World Game, still the most important educational idea that has never been implemented in any seriousness. I don't expect the Deep State (anywhere) to provide this; I do expect to see the hacker community continue to enable & eventually realize it.

Hans Rosling is a great, living example of how many surprises get unveiled by taking a fresh look at massive data sets.

"Very few politically consequential facts are subject to direct, personal verification." (PDF) These vast information gaps create huge systemic problems and destroy anything resembling community/national/cultural "fabric" -- the result is Fear, Uncertainty and Doubt ... reversion to primary loyalties, fragmentation into collapse. The strategic advantage that paradigm-wide secrecy conveys has, in recent decades, been increasingly overwhelmed by the maintenance costs. Classic diminishing returns, and I think we're living through the pivot point nowabouts.
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