No Regulation Is Unbeatable: People Always Respond to Incentives

February 2006 ChinaEconomic PolicyEveryday Economics

Economists have long emphasized that people respond to incentives. Given sufficient motivation, individuals and businesses reliably find ways around regulations—sometimes through bribery, sometimes through entirely legal ingenuity. The people being regulated are almost always more motivated than the employees of the regulatory agencies trying to stop them.

A striking example emerged in China in early 2006. Shanghai’s main pediatric hospital reported 90 births of twins or triplets in a single year—up from an average of 20 in previous years. The explanation: Chinese women were increasingly using fertility treatments to produce multiple births in a single pregnancy, thus technically complying with the one-child policy while having more than one child. AP reported the story under the headline “Drug Bid to Beat Child Ban.”

The method is entirely legal. Fertility clinics benefit commercially. Parents get the children they want. The regulation is circumvented without anyone formally breaking it. From a purely economic standpoint, the ingenuity is admirable—even if the broader question of whether people should face this constraint at all remains a separate matter.

The general principle extends far beyond China. The U.S. tax code has accumulated to tens of thousands of pages precisely because every new rule generates new avoidance strategies, which generate new rules. Americans spend tens of billions of dollars annually on tax compliance and avoidance—resources that produce no economic value. The tax code is a monument to the failure of regulations to achieve their stated goals without generating enormous collateral waste.

The lesson is not that regulation is always wrong. It is that regulatory design must account for the incentive response. A regulation that ignores how motivated, creative, and well-resourced the regulated parties are will be evaded—at a cost to everyone. The question is not whether to regulate, but how to design rules that are robust to the predictable human responses they will generate.