I assert that the sunken cost “fallacy” is actually a quite sophisticated mechanism of human reasoning. People who take into account sunken costs in everyday decisions will make better decisions on average.
My argument relies on the proposition that a person’s estimate of his own utility function is highly noisy. In other words, you don’t really know if going to the movie will make you happy or not, until you actually do it.
So if you’re in this movie-going situation, then you have at least two pieces of data. Your current self has produced an estimate that says the utility of going to the movie is negative. But your former self produced an estimate that says the utility is substantially positive—enough so that he was willing to fork over $10. So maybe you average out the estimates: if you currently value the movie at -$5, then the average value is still positive and you should go. The real question is how confident you are in your current estimate, and whether that confidence is justified by real new information.
Your utility estimates at any given time should already take into account all of the data available to you at that time, including your previous estimates.
In other words, if you decide you don’t want to go to a movie you’ve already purchased a ticket for, that decision has already been influenced by the knowledge that you did want to go to the movie at some point, so there’s no reason to slide your estimate again.
It should have been, but you get pretty much the same result from the sunk cost fallacy, so people do that instead. We didn’t evolve to be rational. We evolved to succeed.
You give no examples as to which situations you actually come out ahead from believing in the sunk cost fallacy, and your justification for it amounts to no more than the fallacy itself. “You thought at some point this was a good idea, so you should probably keep doing it.”
New information should not be averaged with ignorance. When you did not know how you would feel that night, you thought it likely you would want to see the movie. but now you KNOW you don’t feel like seeing it. This should have a much stronger effect on your decision than the prior data you had. You’re not averaging two relatively similar pieces of data, you’re putting together more accurate information with information that’s basically a guess.
I assert that the sunken cost “fallacy” is actually a quite sophisticated mechanism of human reasoning. People who take into account sunken costs in everyday decisions will make better decisions on average.
My argument relies on the proposition that a person’s estimate of his own utility function is highly noisy. In other words, you don’t really know if going to the movie will make you happy or not, until you actually do it.
So if you’re in this movie-going situation, then you have at least two pieces of data. Your current self has produced an estimate that says the utility of going to the movie is negative. But your former self produced an estimate that says the utility is substantially positive—enough so that he was willing to fork over $10. So maybe you average out the estimates: if you currently value the movie at -$5, then the average value is still positive and you should go. The real question is how confident you are in your current estimate, and whether that confidence is justified by real new information.
Your utility estimates at any given time should already take into account all of the data available to you at that time, including your previous estimates.
In other words, if you decide you don’t want to go to a movie you’ve already purchased a ticket for, that decision has already been influenced by the knowledge that you did want to go to the movie at some point, so there’s no reason to slide your estimate again.
It should have been, but you get pretty much the same result from the sunk cost fallacy, so people do that instead. We didn’t evolve to be rational. We evolved to succeed.
You give no examples as to which situations you actually come out ahead from believing in the sunk cost fallacy, and your justification for it amounts to no more than the fallacy itself. “You thought at some point this was a good idea, so you should probably keep doing it.”
New information should not be averaged with ignorance. When you did not know how you would feel that night, you thought it likely you would want to see the movie. but now you KNOW you don’t feel like seeing it. This should have a much stronger effect on your decision than the prior data you had. You’re not averaging two relatively similar pieces of data, you’re putting together more accurate information with information that’s basically a guess.