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and so for the group of us uh at a very high level we're interested in understanding the relationship between
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the trade-offs people are willing to choose to make and the trade-offs that determine their happiness or a little
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more practically we're interested in thinking about situations where you have
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data on what makes people happy but you don't have data on what people choose
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and you want to try to use this happiness data to forecast things about their their decision- Mak process uh so
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to give you a little bit of background uh there's an increasing practice in economics of trying to use happiness
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data to augment uh typical choice-based analysis uh so to give you a you particular example let's say we were
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trying to think about how we should uh value a public policy and figure out how much a particular person would be
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willing to pay to have that public policy in place so one way of approximating this is by taking uh
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existing happiness data estimating how policies like this affect happiness in the past estimating how money plays into
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determining happiness and then figuring out the trade-off between these two things and we could use that to
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basically determine uh the amount of money a person would be willing to pay to put that policy in place under the
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assumption that choices and happiness are aligned right so that people are choosing whatever makes them most happy
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so that's the practice that's currently being followed uh by by some economists
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and we're basically interested in assessing that trying to figure out if these two trade-offs really do reflect
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one another uh so to get at that we ran a large scale study of medical students as they were participating in the
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medical residency match uh so in case you're unfamiliar with the training of
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doctors in the United States uh after uh young doctors uh graduate from medical school they go through a period of
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several years uh where they get really intensive Hands-On training in their specialty called a medical residency
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they have to go through an elaborate process to match from their medical school to a residency and so at this
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point you're probably asking well why are we talking about medical students now and we were just talking about
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happiness and happiness data and the reason why we're looking at this particular setting is because it has
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these really nice properties that allow us to get really high quality Cho data side by side with really high quality
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happiness data so in order to go through this matching process I just described medical students have to basically uh go
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through a period of interviewing with medical schools and consider really carefully the trade-offs they're willing
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to make about say The Prestige of a school versus a city location or things like this and then determine their
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choice ordering over those schools and say this is my first choice school this is my second choice school and so on and
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actually make a list like that and submit it to a centralized matching agency and that list is to determine the
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final assignment of where everyone will go uh and that mechanism was designed very carefully to make sure that
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students uh it's in their own best interest to report their preferences truthfully so basically we'll be
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piggybacking off of that existing field mechanism we'll be seeing their choice
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ordering uh and pairing that up with excellent survey data about how happy they think they'll be at these different
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options and the trade-offs they're making as they're making this decision
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so to generate that happiness data I just described we ran a large large scale survey of medical students as they
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participated in the 2012 residency match uh so in the leadup to that residency match I contacted basically all the
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medical schools in the United States uh and uh you know due to my uh my my uh requests I got 23 schools to agree to
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participate and at those schools students going through the matching process uh were given the opportunity to
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participate in a web survey where they could uh basically report their top four choices we get to see their choice
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ordering over them we also get to ask them how happy do you think you would be if you went to this res how happy do you
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think you would be if you went to this other residency and also for these residencies we collect all the features
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that they're trading off when they're making this decision things like Prestige or stady quality or how much
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their spouse cares about being in that location things like that so with this data we now have everything we need to
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basic uh to basically put happiness data and choice data side by side and uh kind
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of compare the analysis that you could do with with each of these these types of data so our main results from this uh
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are basically twofold so the first main one is that uh Happy data is actually reasonably useful for forecasting
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choices in this setting uh so if you were to say know that some resident or some future medical Resident was
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considering between two options we don't know which one he chooses but we just
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know that one of them uh he thinks will make him happier 70 to 80% of the time that's the one he will choose um now on
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one hand you know we know that people like to be happy right that's not that
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shouldn't be surprising but on the other hand this is a particular setting where
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we don't really think decisions are are necessarily made just to be happy right
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no one's going to to a medical residency to have fun uh this is a big investment
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and important decision in their lives and even in this situation uh happiness data is very useful for forecasting so
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that's you know a positive uh spin on how to use happiness data in economic settings there's a bit of a negative
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side uh in our data too that's the second main result and that's if you try
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to use happiness data to infer the tradeoffs people are willing to make so again like how how they tradeoff
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Prestige against City quality for example we find that the trade-offs you would estimate from happiness data are
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pretty dramatic rically different than the trade-offs you would estimate from Choice data uh these different factors
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wait very different uh very differently in determining these two things uh and that's a bit of a problem for a lot of
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economic analysis because for uh you know many questions economists are asking understanding tradeoffs is really
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the key thing we're trying to understand how we how we price various things you
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know how we trade off one attribute of a of a good versus another things like that and for these types of questions
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happiness data is not getting us the kind of answers we need um so kind of overall our main goal in this entire
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project was trying to get a better sense of how to how to use happiness data in economic applications and how far you
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can go with that and we found some positive results that it is actually useful for just raw forecasting of
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choices uh but some negative results that it doesn't do a great job in answering nuanced questions about how
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you trade off different attributes of a of an option you face so one way or one dimension where
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you can see differences in the way trade-offs are made across happiness data and across Choice data is looking
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at the importance of say considerations about your family's wellbeing or your
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spouse's well-being uh so if we compare how important uh you know say your spouse's happiness is in determining
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your choices it's actually dramatically more important uh in determining your
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choices than it is in determining your predictions about how happy you'll be so
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if we're thinking about trading off say going to a more prestigious residency in
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a location that your spouse likes less you're more likely to choose that and
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you're more likely to wait your spouse's uh your spouse's opinion more heavily in
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your choice then you would in your forecast about how happy you'll be in the future so in some sense this could
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be evidence that people are willing to uh to sacrifice their own happiness uh you know to to benefit their spouse in
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these kind of decisions I came at this problem from the point of view of an economist but it
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does have a lot of implications for how people uh conduct you know General exercises and marketing so uh reasonably
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commonly uh you know both economists and marketers find themselves in situations
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where we have lots of data about say customer satisfaction consumer satisfaction happiness things like that
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and we're trying to infer from that how people you know value different attributes of a product we're trying to
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sell uh how people make trade-offs in various economic environments and the results I was discussing for economists
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translate immediately to the kind of same kind of decisions in marketing environments so basically if you're
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trying to forecast what your consumers will choose or what they will like our results suggest that happiness data can
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help you make those kind of forecasting uh forecasts accurately however uh if you're trying to infer more nuanced
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question questions about how say customers are trading off different attributes of a product you're trying to
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sell our results suggest that happiness data doesn't really get you all the way
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there to estimating those kind of uh tradeoffs so I think this study speaks to uh to to countering misperceptions on
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two ends of a spectrum right on on one end of the spectrum uh some people believe that happiness is basically
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everything that maximizing happiness is the ultimate goal of all of our actions and our research suggests that at least
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when we're thinking about how happiness is currently measured in surveys and
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things like that that's not the case that happiness is something that's very
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important to people and it's an important goal they're pursuing uh but people will explicitly trade off the
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pursuit of happiness against uh you know to to pursue other goals uh now on the other end of the spectrum I think some
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people believe that happiness is not particularly informative for economic analysis uh this is a view held by by
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many economists this is sort of a frivolous psychological variable that isn't really fundamentally related to
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how we make choices and our results actually suggest that's not quite right either um so even in this setting that
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is unambiguously you know a very serious decision a very important decision not made for fun by any by any stretch of
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the imagination uh understanding or having access to happiness data really helps us understand how the decision
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process is made and helps us forecast the choices people will make so there are a few things that set
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my research apart from uh other analysis done looking at the alignment between choice and happiness and I think the
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main thing is we're coming at it from a little bit of a different attitude uh so
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there's a great deal of research out there demonstrating that people don't
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always choose what'll make them happy but the way that's typically discussed
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and the way that's typically presented is as evidence that people are making
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some sort of mistake or or they're bad at forecasting so the idea is that they
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would they're trying to to maximize their happiness and the only thing that's stopping them is either they they
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messed up the decision somehow or they they guessed wrong about what would make them most happy and so on and thus we
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can attribute the entire gap between Choice data and happiness data just to these mispredictions
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we were coming at it from a little bit of a different a different kind of Bas background we were thinking well okay
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you know maybe mispredictions are important but also it could be that people aren't even necessarily trying to
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maximize happiness maybe they could just be thinking of it as one of many goals they're pursuing and explicitly trade
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off that goal uh against other goals and so this led us to look at a situation where people are making uh a decision
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that's very considered very deliberated very high stakes where we're not
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particularly worried about mistakes driving any deviations we see uh and basically trying to see if we
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still see a wedge in that setting uh and of course we did and by by looking in this particular type of environment we
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were better able to get at uh how much of this wedge between choice and happiness is driven by people's initial
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intentions versus just their uh their mispredictions about what actually makes them
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happy in terms of what's next we're thinking about continuing this line of
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research uh by continuing to investigate basically the relationship between happiness data
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uh and choice data which is the more typical object in economic analysis we want to continue to think about uh how
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much you can infer about how choices are made based only on happiness data uh a particular Dimension that I'm interested
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in is in trying to build build happiness data into a more standard price theoretic economic analysis so rather
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than thinking about happiness as just a way of approximating the thing people are trying to maximize think of it as
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this kind of abstract good that people are willing to uh you know in some sense buy and also trade uh and explicitly
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trade off against other goals in their life and uh we're starting to work on a
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theoretical approach to uh to modeling that and thinking about how we can uh better use that type of framework to
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import uh psychological data and happiness data into economic analysis [Music]