출처: The Economist, Nov 23, 1996. Vol. 341, Iss. 7993, pp. 85-86 (2 pp.)
※ 발췌 (excerpt):
Economic statistics can cause governments to lose elections or wipe billions off share prices. Unfortunately, many of the numbers are wrong.
THERE are three kinds of economists: those who can count and those who can't." That old joke gets a good laugh at economics conferences, yet it cuts dangerously close to the bone. Economists spend much time churning statistics through computer models or using them to justify policy, but few worry about the reliability of those numbers. They ought to: traditional measures of economic performance are becoming increasingly dodgy.
Number-crunching is not just an academic issue. Important questions, such as why all the billions of dollars invested in computers have failed to boost productivity growth, rest upon the accuracy of official statistics. Faulty figures distort people's vision. America's economic debate, for example, has been shaped partly by official numbers showing that productivity growth has slowed-from an annual rate of 2.6% in 1960-73 to 0.9% in 1980-95-and that real wages have stagnated. Calculate those figures correctly, however, and America's true rate of productivity growth in the 1990s could be almost as high as in the
1960s, while real wages could be rising at a respectable pace. ( ... ... )