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Supersizing the Incentive
ОглавлениеI should probably tell you now that we didn’t start out running our experiments in the way I just described. Initially, we set about to place some extra stress on our participants. Given our limited research budget, we wanted to create the strongest incentive we could with the fixed amount of money we had. We chose to do this by adding the force of loss aversion to the mix.* Loss aversion is the simple idea that the misery produced by losing something that we feel is ours—say, money—outweighs the happiness of gaining the same amount of money. For example, think about how happy you would be if one day you discovered that due to a very lucky investment, your portfolio had increased by 5 percent. Contrast that fortunate feeling to the misery that you would feel if, on another day, you discovered that due to a very unlucky investment, your portfolio had decreased by 5 percent. If your unhappiness with the loss would be higher than the happiness with the gain, you are susceptible to loss aversion. (Don’t worry; most of us are.)
To introduce loss aversion into our experiment, we prepaid participants in the small-bonus condition 24 rupees (6 times 4). Participants in the medium-bonus condition received 240 rupees (6 times 40), and participants in the very-large-bonus condition were prepaid 2,400 rupees (6 times 400). We told them that if they got to the very good level of performance, we would let them keep all of the payment for that game; if they got to the good level of performance, we would take back half of the amount per game; and if they did not even reach the good level of performance, we would take back the entire amount per game. We thought that our participants would feel more motivated to avoid losing the money than they would by just trying to earn it.
Ramesh carried out this version of the experiment in a different village with two participants. But he went no further because this approach presented us with a unique experimental challenge. When the first participant stepped into the community center, we gave him all the money he could conceivably make from the experiment—2,400 rupees, equivalent to about five months’ salary—in advance. He didn’t manage to do any task well, and, unfortunately for him, he had to return all the money. At that point we looked forward to seeing if the rest of the participants would exhibit a similar pattern. Lo and behold, the next participant couldn’t manage any of the tasks either. The poor fellow was so nervous that he shook the whole time and couldn’t concentrate. But this guy did not play according to our rules, and at the end of the session he ran away with all of our money. Ramesh didn’t have the heart to chase him. After all, who could blame the poor guy? This incident made us realize that including loss aversion might not work in this experiment, so we switched to paying people at the end.
There was another reason why we wanted to prepay participants: we wanted to try to capture the psychological reality of bonuses in the marketplace. We thought that paying up front was analogous to the way many professionals think about their expected bonuses every year. They come to think of the bonuses as largely given and as a standard part of their compensation. They often even make plans for spending it. Perhaps they eye a new house with a mortgage that would otherwise be out of reach or plan a trip around the world. Once they start making such plans, I suspect that they might be in the same loss aversion mind-set as the prepaid participants.