Economist Writing Every Day

Lately I have been thinking a lot about rationality and economics. In my Economics of the Family and Religion course I exhort students to take the approach, “crazy is lazy”. Like archeologists that brush away the dust from artifacts we should brush away the dust of human decision-making and find the rationality. This is especially useful when it comes to understanding observed patterns in religious practice across time and space. You don’t get very far with, “people are nuts”.

Humans make decisions on purpose. They weigh the costs and benefits of an action and make the choice that seems best to them given their available opportunities. Some students have struggled to integrate this message with their other classes. At FSU we have a deep bench of experimental and behavioral economists so there are ample opportunities for students to see courses with a more psychological approach.

In one famous study, Khaneman and Tversky manipulate whether there is a positive or negative frame on a treatment for a deadly disease. In the positive frame, there was a 33 percent chance that treatment could save the 600 people with the deadly disease. In the negative frame, there was a 66 percent chance the treatment could kill the 600 people with the deadly disease. Notice that both of those probabilities result in 200 people being saved. However, people were far more favorable to the positive frame (72%) compared to the negative frame (22%).

Then there are numerous other behavioral economics findings about seemingly small things that impact the decisions people make. For example, in research about bidding behavior psychologists Dan Ariely and Drazen Prelec and economist George Loewenstein passed out sheets of paper and had students write the last two digits of their social security number (SSN) at the top before they placed a bid for each item on a sheet. Students with SSN in the top 20 percent of the distribution bid 216 to 346 percent higher for the items compared to those with SSN in the bottom 20 percent.

We could go on. In the face of those kind of results, it is no wonder that students pause to reflect about how these findings fit into the larger corpus of economics. Are they useful observations to the extent they help us improve the predictions of our models? Are they damning demonstrations that cut out the heart of the economic approach?

This is worth a much more extended treatment but I’ll simply make a couple observations. In my last intermediate microeconomics class, we discussed sequential games. Students played the classic “Centipede Game” where two players are paired together for a game with a fixed number of turns. The game starts with Player 1 (P1) having a payoff of 4 and Player 2 (P2) having a payoff of 1. The decision for P1 is whether to “Take” or “Pass”. If “Take” is chosen the game ends. If “Pass” is chosen the joint-payoff doubles but in favor of the other person, so the payoffs would be 8 and 2 but in favor of P2. Then P2 has the same “Take” v. “Pass”, where passing would lead to a payoff of 16 and 4 in favor of Player 1 while taking would end the game.

The equilibrium in this game is solved using backward induction. Player 1 chooses “Take” in the first turn. But, what do people actually do? Each dot in the graph below represents the average number of turns taken (or steps) in each round of play. Students played five rounds. Over time the average number of turns declined. Interestingly, this happened without a single student being able to rattle off the idea of common knowledge of rationality and backward induction. Rather, students felt their way through a game, learned from the disappointment of others choosing “Take”, and behaved as if they understood backward induction.

Then we played the Ultimatum Game. The proposer has an endowment and can offer a split of that endowment to the responder. If the responder accepts, the split goes through. If the responder rejects, then nobody gets anything. The student responders frequently rejected offers of 20 – 30 percent of the endowment. Many cited something like, “That’s not the way you treat people.” So fairness is something people believe is desirable and an economic model that did not include fairness considerations would not predict rejection. But, economics does not require people to be selfish. Anything people care about can be included as an economic good. Fairness is subject to scarcity as the folks over at Economic Forces reminded us yesterday.

In fact, in the newsletter Josh Hendrickson notes that when fairness is a commodity there would be a demand curve for it. When the price of enforcing norms of fairness is high we would expect people to do less of it. This is what Andersen et al. (2011) find in their American Economic Review article titled, “Stakes Matter in Ultimatum Games”,

“Through our stakes treatments, we find that sufficiently high stakes lead responder behavior to converge almost perfectly to full acceptance of low offers, even in the absence of learning … it reveals that the demand curve for punishing unfair offers is downward sloping and provides the first evidence that one of the most basic economic predictions—that people respond predictably to stake changes—arises in this game.”

Demand curves are the most basic manifestation of the economic cornerstone that incentives matter. Even amid these behavioral economics considerations, people are rational and respond to prices. Moreover, what the Centipede data (and other data like it) help illustrate is that predictions can happen without people being able to write down the mathematical solution on a whiteboard.

I told my students that I still struggle to integrate a variety of behavioral economics findings into the economic approach. Then I told them, one thing I do know, I have a strong prior that “crazy is lazy”: feedback and learning opportunities matter for the performance of economic theory and demand curves slope downward. I’ll leave you with this screenshot quote from Daniel Friedman and his American Economic Review article titled, “Monty Hall’s Three Doors: Construction and Deconstruction of a Choice Anomaly”