# Searching for Happiness: an Econometric Framework

— written by Yongbin

Being happy is an eternal struggle and if I had an answer to being happy, then the world would be a perfect place.

But I don’t have an answer, no more than the next person, and my guess is that there never will be one. That’s not what my response is about — instead, I want to focus on how to view happiness through what I call the Econometric Framework.

Econometrics is a subfield within Economics that has to do with statistics, data, and modeling. The basic and most elementary economic model is what I’ll be using. This is called the Simple Linear Regression Model or the OLS model:

It’s a very simple model when you break it down. “Y” is what we are looking for, “X” is what we think will make us happy, and “U” is what we call the “error term” or all terms that make us happy but aren’t defined. B0 is our happiness when we have no “units” or rather, we ignore what we think will make us happy. B1 is the degree of which what we think will make us happy (the X value). The most important conclusion we can derive from this model is that we are looking to search for happiness (Y) by measuring how much a certain act, event, person, or thing (X) will make us happy.

For example, if I think that eating hot cheetoes makes me really happy, X =consumed Hot Cheetoes.

Therefore, Happiness = Current Happiness + Hot Cheetoes Consumed + All other factors of our happiness.

We can extend the econometric model so that we have Y = B0 + (B1)(X1) + (B2)(X2) + U. With this new model, I am examining two separate things that make me happy. Let’s say X1 = consumed Hot Cheetoes but X2 = books read. Now I’m looking to find my happiness through this equation. And if eating Hot Cheetoes creates much more joy than reading books, then I’d say B1 > B2.

Therefore, Happiness = Current Happiness + Hot Cheetoes Consumed + Books Read + All other factors of our happiness

Now, the reason why I specify the econometric model from the more commonly known linear model (y = mx+b) is that there is an unique term called the error term. This value changes the way we view this entire concept. In short, it adds variability and uncertainity to our mathematical model. Let’s continue with the above.

We have X1 = consumed Hot Cheetoes and X2 = books read. Let’s say that I realize that I can make myself happier by eating so many hot cheetoes and, briefly suspending notions of becoming full then hating ourselves for eating so many hot cheetoes, therefore I buy fourteen bags of Hot Cheetoes. Brilliant idea? Not so much — because it turns out, it’s not the Cheetoes that I love, it’s the act of spending money on the Cheetoes. Or maybe it’s the specific crunch of the Cheetoes I actually enjoy, and other foods that are healthier also have that crunch. Turns out, I actually hate Hot Cheetoes and I don’t get much happiness from them as I do other things that I end up doing when I eat Hot Cheetoes. I could be so much happier while eating carrots and spending money on Game of Thrones figurines.

What does this all mean? Well, our equation when we dig deeper is plain wrong. Or more accurately, our notions of X causes Y is insufficient. We have to look into the error term, U, and understand that when we try to figure out how much X1 makes us happy, we ignore the infinite number of X’s that are captured by our error term. And sometimes X values overlap or are related — a concept we call covariance — and when our X value and our error term have a lot of shared covariance (i.e. covariance is not 0), we don’t have a very good grasp of how much Hot Cheetoes makes us truly happy.

Let’s say that we thought Y = B0 + (B1)(X) + U where B1 = consumed Hot Cheetoes. For the sake of the argument, let’s say hot cheetoes are, in fact crunchy (maybe because they are stale, oops!)

Initially, because we only tested one value and it turns out Hot Cheetoes make us happy, we end up eating ourselves too many of them.

But now let’s really break down what we enjoy about them. Turns out, the crunch of eating them is our favorite part — in fact, it’s almost the only reason we enjoy our Hot Cheetoes so much. So we have Y = B0 + (B1)(X1) + (B2)(X2) + U where B1 = consumed Hot Cheetoes and B2 = Enjoying crunchy foods. Here, B1 is a tiny, tiny value — almost close to 0 — and B2 is really, really high.

Or in other words: Happiness = Current Happiness + (small value)Hot Cheetoes Consumed + (high value)Crunchy foods + All other factors of our happiness.

Compare this to our original equation: Happiness = Current Happiness + (medium value)Hot Cheetoes Consumed + All other factors of our happiness

When we didn’t account for both, the average value between them was higher. But when we split them, we see where we really get our joy from.

So instead of eating hot cheetoes, we decide to get carrots and end up happier (and healthier) than eating a bunch of hot cheetoes, both in the short and long run.

So what can we conclude?

1 : Finding the “Perfect Equation” (no error term) is impossible.

It’s not easy trying to understand what makes us happy. There is always an error term with infinite number of X’s (or values/things that we think make us happy) and we will never really know our “perfect” equation.

2 : We need to unpack and dissect every “X” value.

We need to really understand every X value. If I said that going to class makes me happy, and maybe it does, does that mean the happiest I will be is in class all the time? Maybe not — maybe it’s the act of learning that makes me truly happy and I actually get unhappy being in a classroom. So let’s reflect and really think about our happiness.

3 : We need to choose the best “X” in determining our happiness.

We have to choose the right values to examine. Maybe one X gives us some happiness, but another X gives us a lot. We are humans with limited time, energy, and capacity — so let’s not waste time on a X with minor happiness if we don’t need to.

4 : Life is more complicated than an equation.

Like I stated in the introduction, I’m not trying to solve this equation to maximize Y (our happiness), find our error term (U), or determine which X gives us the most happiness — because it’s simply not reasonable to put numbers to life when life is priceless, valueless, and indeterminate. Instead, this framework exists as one perspective of happiness rather than as the solution to it.

Happiness is hard to achieve and as self-proclaimed seeker of happiness, I’ve learned that maybe half of finding happiness is learning what makes us happy. The other half is being happy. And both are equally hard — and this framework exists for me to attempt to quantify the unquantifiable and regress the unregressable.

Referring to @Mikaela’s post on happiness and aesthetics — maybe this model is can show how we “try-on” different things to find our happiness. From yoga to EDM, these are just all different values of X that we are trying to plug into our equation to solve our ultimate Y — our happiness. But I don’t think we can actually find our Y, not like this anyway, and trying out many different X’s isn’t as important as maybe unpacking the X’s we choose, because happiness might be something we already have in our lives or have done. We just need to find out what those true values of X are.

One clap, two clap, three clap, forty?

By clapping more or less, you can signal to us which stories really stand out.