考博试题

[B]have already suffered loss due to the company’s failure in the bid.

[C] don’t want the company to bid for AT&T Wireless.

[D] don’t like the company to give up its stake in Verizon Wrieless.

Passage 2

Figures lie, as everyone knows, and liars figure. That should make economists especially suspect, since they rely heavily on statistics to try and resolve a wide range of

controversies. For example, does a rise in the minimum wage put people out of work? Are stock market returns predictable? Do taxes influence whether a company pays pidends? In recent years, helped by cheaper, more powerful computers, and egged on by

policy-makers anxious for their views, economists have analyzed reams of statistics to answer such questions. Unfortunately, their guidance may be deeply flawed.

Two economists, Deirdre MeCloskey of the University of Illinois, and Stephen Ziliak of Roosevelt University, think their colleagues do a lousy job of making sense of figures, often falling prey to elementary errors. But their biggest gripe is that, blinded by statistical wizardry, many economists fail to think about the way in which the world really works. To be fair, statistics can be deceptive, especially when explaining human behavior, which is necessarily complicated, and to which iron laws do not apply. Moreover, even if a

relationship exists, the wrong conclusions can be drawn. In medieval Holland, it was noted that there was a correlation between the number of storks living on the roof of house and the number of children born within it. The relationship was so striking that, according to the rules of math’s that govern such things, you could say with great confidence that the results were very unlikely to be merely random. Such a relationship is said to be

“statistically significant”. But the Dutch folklore of the time that storks somehow increased human fertility was clearly wrong.

A failure to separate statistical significance from plausible explanation is all too common in economics, often with harmful consequences. In a past paper Professors McCloskey and Ziliak attacked other economists’ over-reliance on statistical rather than economic reasoning, and focused on one case in particular.

In the 1980s, the American state of Illinois launched a program to keep people off the dole. Economists asked whether its costs outweighed its benefits. One study estimated that the program produced benefits that were more than four times as large as the costs. Although this seemed a good deal for taxpayers---and other tests seem to support this

conclusion---the authors of the study rejected such a finding because they found that their estimate was not statistically significant. In other words, their results fell just short of 90%