The Wealth of Nature. John Michael Greer

Чтение книги онлайн.

СКАЧАТЬ and Statistics

      An economy is a system for exchanging goods and services, with all the irreducible variability that this involves. How many potatoes are equal in value to one haircut, for example, varies a good deal, because no two potatoes and no two haircuts are exactly the same, and no two people can be counted on to place quite the same value on either one. The science of economics, however, is mostly about numbers that measure, in abstract terms, the exchange of potatoes and haircuts (and, of course, everything else).

      Economists rely implicitly on the claim that those numbers have some meaningful relationship with what’s actually going on when potato farmers get their hair cut and hairdressers order potato salad for lunch. As with any abstraction, a lot gets lost in the process, and sometimes what gets left out proves to be important enough to render the abstraction hopelessly misleading. That risk is hardwired into any process of mathematical modeling, of course, but there are at least two factors that can make it much worse.

      The first is that the numbers can be deliberately juggled to support some agenda that has nothing to do with accurate portrayal of the underlying reality. The second, subtler and even more misleading, is that the presuppositions underlying the model can shape the choice of what’s measured in ways that suppress what’s actually going on in the underlying reality. Combine these two and what you get might best be described as speculative fiction mislabeled as useful data — and the combination is exactly what has happened to economic statistics.

      For decades now, to begin with, the US government, like that of most other nations, has tinkered with economic figures to make unemployment look lower, inflation milder and the country more prosperous. The tinkerings in question are perhaps the most enthusiastically bipartisan program in recent memory, encouraged by administrations and congress people from both sides of the aisle, and for good reason: life is easier for politicians of every stripe if they can claim to have made the economy work better. As Bertram Gross predicted back in the 1970s,¹⁶ economic indicators have been turned into “economic vindicators” that subordinate information to public relations, and the massaging of economic figures Gross foresaw has turned into cosmetic surgery on a scale that would have made the late Michael Jackson gulp in disbelief.¹⁷

      When choices are guided by numbers, and the numbers are all going the right way, it takes a degree of insight unusual in contemporary life to remember that the numbers may not reflect what is actually going on in the real world. You might think that this wouldn’t be the case if the people making the decisions know that the numbers are being fiddled with to make them more politically palatable, as economic statistics in the United States and elsewhere generally are.

      It’s important, therefore, to remember that we’ve gone a long way past the simplistic tampering with data practiced in, say, the Lyndon Johnson administration. With characteristic Texan straightforwardness, Johnson didn’t leave statistics to chance; he was well known in Washington politics for sending any unwelcome number back to the bureau that produced it, as many times as necessary, until he got a figure he liked.

      Nowadays nothing so crude is involved. The president — any president, of any party, or for that matter of any nation — simply expresses a hope that next quarter’s numbers will improve; the head of the bureau in question takes that instruction back to the office; it goes down the bureaucratic food chain, and some anonymous staffer figures out a plausible reason why the way of calculating the numbers should be changed; the new formula is approved by the bureau’s tame academics, rubberstamped by the appropriate officials, and goes into effect in time to boost the next quarter’s numbers. It’s all very professional and aboveboard, and the only sign that anything untoward is involved is that for the last 30 years, every new formulation of official economic statistics has made the numbers look rosier than the one it replaced.

      It’s entirely possible, for that matter, that a good many of those changes took place without any overt pressure from the top at all. Hagbard’s Law is a massive factor in modern societies. Coined by Robert Shea and Robert Anton Wilson in their tremendous satire Illuminatus!, Hagbard’s Law states that communication is only possible between equals. In a hierarchy, those in inferior positions face very strong incentives to tell their superiors what the superiors want to hear rather than ‘fessing up to the truth. The more levels of hierarchy between those who gather information and those who make decisions, the more communication tends to be blocked by Hagbard’s Law. In today’s governments and corporations, the disconnect between the reality visible on the ground and the numbers viewed from the corner offices is as often as not total.

      Whether deliberate or generated by Hagbard’s Law, the manipulation of economic data by the government has been duly pilloried in the blogosphere, as well as the handful of print media willing to tread on such unpopular ground. Still, I’m not at all sure these deliberate falsifications are as misleading as another set of distortions. When unemployment figures hold steady or sink modestly, but you and everyone you know are out of a job, it’s at least obvious that something has gone haywire. Far more subtle, because less noticeable, are the biases that creep in because people are watching the wrong set of numbers entirely.

      Consider the fuss made in economic circles about productivity. When productivity goes up, politicians and executives preen themselves; when it goes down, or even when it doesn’t increase as fast as current theory says it should, the cry goes up for more government largesse to get it rising again. Everyone wants the economy to be more productive, right? The devil, though, has his usual residence among the details, because the statistic used to measure productivity doesn’t actually measure how productive the economy is.

      By productivity, economists mean labor productivity — that is, how much value is created per unit of labor. Thus anything that cuts the number of employee hours needed to produce a given quantity of goods and services counts as an increase in productivity, whether or not it is efficient or productive in any other sense. Here’s what A Concise Guide to Macroeconomics by Harvard Business School professor David A. Moss, as mainstream a book on economics as you’ll find anywhere, has to say about it: “The word [productivity] is commonly used as a shorthand for labor productivity, defined as output per worker hour (or, in some cases, as output per worker).”¹⁸

      Output, here as always, is measured in money — usually, though not always, corrected for inflation — so what “productivity” means in practice is income per worker hour. Are there ways for a business to cut down on the employee hours per unit of income without actually becoming more productive in any meaningful sense? Of course, and most of them have been aggressively pursued in the hope of parading the magic number of a productivity increase before stockholders and the public.

      Driving the fixation on labor productivity is the simple fact that in the industrial world, for the last century or so, labor costs have been the single largest expense for most business enterprises, in large part because of the upward pressure on living standards caused by the impact of cheap abundant energy on the economy. The result is a close parallel to Liebig’s law of the minimum, one of the core principles of ecology. Liebig’s law holds that the nutrient in shortest supply puts a ceiling on the growth of living things, irrespective of the availability of anything more abundant. In the same way, our economic thinking has evolved to treat the costliest resource to hand, human labor, as the main limitation to economic growth, and to treat anything that decreases the amount of labor as an economic gain.

      Yet if productivity is treated purely as a matter of income per worker hour, the simplest way to increase productivity is to change over from products that require high inputs of labor per dollar of value to those that require less. As a very rough generalization, manufacturing goods requires more labor input overall than providing services, and the biggest payoff per worker hour of all is in financial services — how much labor does it take, for example, to produce a credit swap with a face value of ten million dollars?

      An economy that produces more credit СКАЧАТЬ