By Kevin DeLuca
Opportunity Cost of Reading this ThoughtBurner post: $1.46
You can hear the call coming from inside the gated frat house parties across college campuses every Friday night. The Lonely Island called it “the battle cry of a generation.”[i] Even in everyday conversation, hesitation, prudence, and caution are all greeted with a new, four-letter challenge: YOLO.
The expression “you only live once” (YOLO) is often meant to serve as a justification for risky or unwise behavior. The idea behind the message, however, is stronger than that. Because we only have one life to live – you only live once – we should not give up current opportunities. We should do what we want to do, when we want it, because you might not have the same options later as you do now (since we only live once). Similar phrases have captured this idea throughout history; “carpe diem”, “live life to the fullest”, and “live like there’s no tomorrow.”
Before I speak of the YOLO effect, I’ll introduce the common idea (in economics) of “discounting the future” in choice models. The basic concept behind discounting is that people value the present more than the future. Easy example: would you rather have $10 right now or $10 in 5 years? Most people say $10 right now, since $10 right now is more valuable than $10 in 5 years; you might need that $10 now and it’s not clear that the $10 will be as useful in 5 years. (see here[ii] for more). In order to account for this phenomenon, economists often place some discount factor on future payoffs in optimization problems.
In a very broad and abstract sense then, our total life happiness can be modeled as:
Where each subscript (1, 2, …, T) indicates our happiness in some time period (until we die at period T), and where β is a discount factor between 0 and 1.
A β of 1 would mean that we value each period’s happiness exactly the same ($10 in 5 years is just as good as $10 right now), whereas a β of 0 would indicate that we don’t care at all about future happiness ($10 in 5 years doesn’t make you happy in the slightest).
Everyone is trying to maximize their total happiness – we are people and everyone wants to be happy. How do we do it? It looks like a straightforward problem, but the tricky part is that happiness in one period often affects happiness in future periods. Binge watching Netflix might make you extremely happy in period 1, but in period 2 (the next day, right before your exam) your happiness will could be very low (as you cram for your test). Maybe you can’t pull it off either, and you end up failing your test during period 3, and maybe eventually even failing out of school months later (period 100 or something). Your total happiness would have been much higher if you had suffered in period 1 and 2 – studying instead of watching Sons of Anarchy – and then receiving much higher payoffs in future periods.
How does this relate to only living once? In a sense, the phrase YOLO is an attempt to alter the value of discounting. It suggests that we make the present value of opportunities and payoffs much greater than any future payoffs. Another way to say this is that it places an inappropriate (as in non-optimal) discount factor on future payoffs (and consequences). To an extreme, it suggests using a β of 0 (in other words, discount the future completely). This is “The YOLO Effect.” Rather than basing you decisions on some objective function that takes into account present payoffs and future payoffs, The YOLO Effect changes your optimization problem to the form:
Since β = 0, which simply becomes:
This makes the maximization problem very easy; in order to maximize happiness, simply maximize happiness in the current period, period 1 (H1). Though it may be true that in certain periods, the solution to your lifetime happiness problem is the same as the solution to the current-period maximization problem, it seems unlikely that this would happen very often. The more likely scenario is that you end up getting high payoffs in the current period (high H1) and get lower payoffs in the future (low H2 or even low H100). While it is true that, if you are lucky, the YOLO mentality can lead to extremely high payoffs ( could end up being really, really high), strictly speaking the resulting cumulative amount of happiness from YOLO-based decisions will not be higher than the cumulative lifetime happiness derived from decisions based on appropriate future discounting (which is not the case if β = 0). In other words, the YOLO effect is causing people all over the world to be cumulatively less happy over their lifetime.
In order to counteract the YOLO effect, I propose a new catch phrase: “Live like you’ll live an average lifespan conditional on your particular demographic characteristics!” Not as catchy, I admit, and unfortunately the acronym is a bit complicated (“LLYLAALCOYPDC” doesn’t exactly roll off the tongue). But, if you keep this phrase in mind whenever you make choices, and if you practice saying it enough to yell it quickly at parties and then proceed to do something responsible, you can ensure that you and your friends are maximizing your expected cumulative lifetime happiness – even when the YOLO effect is at its strongest.
(A bit of an aside – The Lonely Island song referenced at the beginning of the article actually takes YOLO to mean something like “Be extra careful with your life, because YOLO.” They meant this sarcastically of course – that is not how the term is used colloquially. Their interpretation, however, implies that you should instead maximize your expected life time. Notice that this is not the same as maximizing your happiness and is, in fact, also a suboptimal strategy (even though you may live longer). A longer life is not always a better life. It does not necessarily lead to inappropriate discounting of future happiness as I’ve described above, but it does cause suboptimal decision making, if your intention is to be as cumulatively happy as possible.)
But maybe a phrase meant to counteract the YOLO effect doesn’t actually help anyone to make decisions (other than to, potentially, stop them from doing something that is obviously suboptimal). The information you need, you might be thinking, is really 1) how long you are expected to live and 2) how much you should discount the future – the ‘appropriate’ discount rate.
Let’s start with the first bit. Using the Social Security website life expectancy calculator[iii], you can enter some information and it will predict how long you’ll live (it predicted that I would live an additional 59.2 years, not bad I guess). The U.S. Census Bureau has some interesting tables[iv] as well to help you figure out how much longer you can expect to live. This[v] website also has a bunch of different life expectancy stats, though I’m not sure how reputable it is based on its underground-esque appearance. Of course there is a lot of uncertainty, so I won’t claim that the ‘average age’ or ‘life expectancy’ is at all close to your expected lifetime – especially if you say “YOLO” a lot. In terms of estimating your expected lifespan, it might be best to ‘start’ at the average life expectancy, which is 78.8 years (for the United States[vi]), and then adjust from there based on your healthy/unhealthy habits, your family history, medical conditions, your ability to make wise decisions and so on.
Once you have a good idea of how long you have left to live, and have come to terms with your own mortality, you now need to figure out how much you ought to discount the future. This, as you may imagine, is not an easy question to answer. There have been studies that empirically try to estimate how people discount the future, and much of the data fits a hyperbolic discounting model (see this[vii] paper, section 4.1 and 5.1) where, generally:
With t being time and being some constant indicating the strength of the discounting. The implication of hyperbolic discounting is that your discounting factor becomes smaller as you consider different situations that are further away in the future. For example, suppose you are comparing the current period (say t = 0) with the next (t = 1) (also assume that = 1 for simplicity). You would discount today’s happiness by = 1 (so, not at all) and the next period’s happiness by = 0.5, or half! So if you receive $100 today you value it at $100, and if you receive $100 tomorrow you value it at only $50 (in current value). In other words, $100 tomorrow would only make you $50-worth happier today. But now let’s compare t = 100 to t = 101. This gives 0.0099 for day 100 and about 0.0098 for day 101. So if you receive $100 on day 100 you value it at about $0.99 (in current value), and if you receive $100 on day 101 you value it at about $0.98. The difference between the two times is the same as the first example – just 1 day – but the difference in your valuation is only $0.01, rather than $50.
Now, we don’t know that these empirical studies necessarily reveal anything about the “best” way to discount the future – the people studied may not have been acting optimally. At this point, however, there is no consensus among economists as to which model of future discounting is optimal, or even which is most accurate. We don’t know whether these people were maximizing their lifetime happiness or whether they were following some other behavioral strategy, but if they were acting optimally then that’s good news for hyperbolic discounting models. Hyperbolic discounting seems to work well to explain the observed data in general, and may be a good, easy approximation.
I’m usually against using rules of thumb or heuristics to solve these sorts of problems, but I actually think that using my anti-YOLO prescribed saying, “Live like you’ll live an average lifespan conditional on your particular demographic characteristics!”, actually works pretty well. It essentially prompts you to consider the cumulative lifetime happiness maximization problem rather than the current-period maximizing problem (which is usually suboptimal). When you say this in your head or out loud, you should be considering:
-The potential for tradeoff in payoffs between time periods
-Your expected lifespan
-How payoffs may affect total lifespan
-How your preferences may change in the future (anticipate your future needs and try to predict how happy certain things will make you in the future as you grow older)
-How to appropriately discount the future, and
-The amount of uncertainty and risk surrounding each of your estimations (how wrong you could be and the consequences of being wrong)
Unfortunately, many of these things are person and preference dependent, so it is hard to give answers or advice that is any more specific. Ultimately, I am leaving you to figure out the solution to your own lifetime happiness maximization problem. Your success depends on how well you can accurately and optimally incorporate all of the things I mentioned above into your optimization problem formation, in addition to how well you can resist the allure of the instant gratification offered by the YOLO effect. For this problem, you are in the best position to estimate the maximizing solution, since you have the most information about yourself and how it might affect the form of the problem.
Essentially what I am saying – and I think that this creed is one that many economists would adopt in problems that rely so heavily on the individual – is one thing: “You do you.”