Julian Sanchez has a fantastic piece about the fabrication of a (still used today) statistic about the economic harm caused by “piracy.”
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Meta
Supposing the 250 billion number is true, the whole argument that this is harmful to the economy is false.
It is not as if this 250 billion, that would have gone to content providers, vanishes into thin air. No, the money stays in the consumer’s pocketbook, where it can and will be spent on something else. If I don’t have to spend money on music or video, then I have more left over to spend somewhere else. No harm to the economy there. Content providers may lose, but some other producer gains at their expense. In the short term the economy is a zero sum game. Every time you pick one product over another you are helping one producer and harming another.
It would be perfectly reasonable to make a contrarian, utilitarian argument that every time I pay too much for music or video or Gucci shoes or Louis Vuitton wallets or some other non-essential item, I am harming the economy. When I buy meat and potatoes or tools or a house or a vacation or simply invest my money, I am helping the economy. In the long run, the latter economic activities provide more jobs and distribute income, dollar for dollar, more equitably, than the industries which suffer from rampant piracy.
Jardinero1 is correct that a $250 billion loss of revenue to content providers doesn’t imply a $250 billion cost to the economy, but he is not correct in suggesting that it is merely a transfer. What one ought to ask is what the effect is on how people act. Looking at it that way, there are effects in both direction.
On the one hand, the fact that content providers can’t get money for producing content means that less content is produced. The cost of not producing content is the difference between the value of would have been produced and the cost of producing it, which could be more or less than the loss of revenue.
On the other hand, since the cost to the producer of a consumer using content already produced is essentially zero, any price above zero means some consumers not choosing to use the content even though it is of value to them and their use costs the producer nothing, which is a net loss. In that dimension, piracy produces a net benefit.
This is, I should add, an old argument on the economics of IP protection. As a first approximation, it results in a more efficient level of production of intellectual property, since producers can get a substantial fraction of the value of what they produce, but a less efficient use of intellectual property, since consumers only use it if they are willing to pay the price, even though one more user normally imposes no cost at all.
On another point … .
It occurs to me that it would be interesting for someone to put together an essay, or even a book, on bogus statistics, of which this is only one small example. The pattern seems to be a common one. I gather, for instance, that the commonly cited figure on how many people are homeless is pure invention–someone arguing for something asserted it without evidence and other people repeated it. The figure that used to be widely quoted, to the effect that the U.S. had X% of the world’s population but consumed Y%>>X% of the world’s resources, was, I believe, a real figure from about 1946, when the rest of the developed world had been mostly flattened by WWII. And I am sure there are a lot of other examples out there. The widely cited figures on hunger in the U.S. seem to be someone’s estimate of how many people are hungry “or at risk of hunger,” the latter being a sufficiently vague term to permit almost any estimate one wants.
Part of the point of the more general piece would be to get away from the partisanship associated with any single example. It’s easier to accept the fact that some of the figures used by your side of the argument are bogus if it’s in the context of a collection of bogus figures, many of them used by the other side. Perhaps Larry could get the ball rolling by looking over figures he has from time to time cited and seeing if any of them are in fact baseless.
Of course, I could do the same thing. And probably should.
“It occurs to me that it would be interesting for someone to put together an essay, or even a book, on bogus statistics, of which this is only one small example. The pattern seems to be a common one. I gather, for instance, that the commonly cited figure on how many people are homeless is pure invention–someone arguing for something asserted it without evidence and other people repeated it. “
See the just published book Stat-Spotting: A Field Guide to Identifying Dubious Data
http://www.amazon.com/Stat-Spotting-Field-Guide-Identifying-Dubious/dp/0520257464/ref=sr_1_1?ie=UTF8&s=books&qid=1224382315&sr=1-1
Product Description
Are four million women really battered to death by their husbands or boyfriends each year? Does a young person commit suicide every thirteen minutes in the United States? Is methamphetamine our number one drug problem today? Alarming statistics bombard our daily lives, appearing in the news, on the Web, seemingly everywhere. But all too often, even the most respected publications present numbers that are miscalculated, misinterpreted, hyped, or simply misleading. Following on the heels of his highly acclaimed Damned Lies and Statistics and More Damned Lies and Statistics, Joel Best now offers this practical field guide to help everyone identify questionable statistics. Entertaining, informative, and concise, Stat-Spotting is essential reading for people who want to be more savvy and critical consumers of news and information.
Stat-Spotting features:
* Pertinent examples from today’s news, including the number of deaths reported in Iraq, the threat of secondhand smoke, the increase in the number of overweight Americans, and many more
* A commonsense approach that doesn’t require advanced math or statistics