Linear extrapolations are widely suspected of being unreliable, but maybe not widely enough. Stated differently, it’s a category error to engage in static, not dynamic, analysis.

Stated yet differently, the interesting challenge is almost never to ask, “What can we do to solve this problem?” but instead, “What happens after we take this approach to solving the problem?”

Let me give you a couple of specific examples.

A long-running contributor to structural disequilibrium in the metropolitan New York traffic congestion pattern is that bridges across the East River are toll-free whereas almost all other bridges and tunnels in the area carry tolls as high as $12 one-way. Not surprisingly, the East River bridges are chronically congested and “over capacity.” (The experts’ knowing diagnosis that they’re “over capacity” always amuses me; drivers are paying in time, not money: The “capacity” of the bridges is what it always has been.) So periodically proposals are floated to impose tolls on these bridges, with seemingly reliable projections of how much revenue would be collected based on today’s vehicle traffic multiplied by the average toll.

This is a linear extrapolation, a static analysis, and it’s wrong. It overlooks the question, “How will people alter their behavior in light of the tolls?” Obviously, the answer is that some will carpool, some will take mass transit, some telecommute more often, others use different combinations of bridges and tunnels. Whatever happens, toll revenue will fall short of {[today’s traffic volume] x [proposed toll]}.

Now, in our own backyard, we have a stunning example of market dynamics at work.

The Wall Street Journal reports “First-Year Law School Enrollment at 1977 Levels,” and here are the numbers:

  • the number of 1L’s fell 11% this year, down nearly 5,000 from 2012, at 39,675 students
  • 1977’s number was precisely one more, 39,676
  • 1975 was the previous low, at 39,038
  • in 1975 there were 163 ABA-approved law schools; today there are 202

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