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’ Principle 2: Consider behavioral biases when designing prescriptive solutions. Over the years I have learned (sometimes the hard way) that if one does not take into account the way individuals process information and make choices, strategies that appear to be reasonable to economists may not work well in practice. As an illustration of this point, consider the National Flood Insurance Program. When enacted in 1968, it provided highly subsidized premiums for existing homes so as to maintain property values and to encourage individuals to purchase policies. But very few homeowners in flood-prone areas voluntarily bought coverage, even though they were getting a bargain with respect to price. As my colleagues and I later discovered when interviewing these individuals, many believed the probability of a flood in the near future was so low as to justify a lack of concern with protecting themselves. Eventually, Congress passed legislation requiring flood insurance as a condition for a federally insured mortgage.

Researchers’ Principle 3: Start with a simple problem before trying to solve a more complex one. This point was driven home when Geoff Heal and I were tackling the interdependent security (IDS) problem described above. We first looked at the simplest case we could think of: two identical individuals, each of whom had a chance of suffering damage to their apartment unit from a fire. If the fire occurred in Person 1’s apartment it was certain to spread to Person 2’s unit even if Person 2 had invested in a fire sprinkler system. The same scenario would occur if Person 2 had a fire: It would spread to Person 1’s apartment. For this two-player game we discovered that two Nash equilibria were possible: Either both individuals would want to invest in a sprinkler system or neither of them would want to adopt this protective measure.

This was an Aha moment for us! We both recognized that we would have had a hard time uncovering this feature of the solution if we’d started with a more complicated problem structure such as having the two individuals differ from each other or considering three or more apartment owners, each deciding whether or not to invest in a fire sprinkler system. Later we added these and other features to make the problem more realistic.

Researchers’ Principle 4: As a neutral party, do not advocate a specific program. Rather than lobbying for a specific program, it is often more appropriate to point out the pros and cons of alternative strategies. In this way, one will be viewed more objectively by the interested parties. My colleagues and I learned this lesson firsthand more than thirty years ago while circulating a draft of the final chapter of our book Disaster Insurance Protection: Public Policy Lessons2 to some insurance executives who were working with us on the study. The chapter made a strong pitch for a comprehensive disaster insurance program without noting its advantages and disadvantages relative to other options. One of our insurance colleagues pointed this out to us. We modified the final chapter by providing an assessment of such an insurance program in the context of other strategies, rather than focusing solely on this option.

Researchers’ Principle 5: Be aware of loaded words when developing prescriptive solutions. A few years ago I designed a game as part of a presentation I was giving to practitioners interested in the challenges associated with siting potentially noxious facilities such as landfills. Each person had to determine the amount of compensation he or she would require in order to accept a landfill in his or her community. The person stating the lowest amount had the facility sited in his or her backyard; each of the other n participants paid 1/n of this dollar figure to the lowest bidder. In other words, if the lowest bid was $200 by Player 1 and there were 11 players (each representing a community) then the 10 higher bidders would each pay $20 (i.e., $200/10) to Player 1 in return for having the landfill in his or her backyard.

After I explained the rules of the