Should We Be Measuring Happiness As An Economic Measure?
from the this-makes-me-sad dept
A lot of people have finally realized that traditional economic measures have all sorts of problems. Things like GDP mismeasure a ton of things, and by presenting an aggregate set of data, often obscure lots of issues. Also, things like GDP don’t handle disruption very well. I’ve discussed in the past how you could argue that, purely on a GDP basis, something like Craigslist has been horrible. It effectively undercut newspaper classifieds, which was a multi-billion dollar business, and turned it into a much smaller business. If you measured such things purely by GDP, you’d say that it was bad. But, of course, Craigslist also created tons of value, enabling people to make transactions that couldn’t have been made before, while also allowing other transactions to be made more efficiently and with less friction. Much of that will never show up in GDP, even if, intrinsically, most people recognize that something like Craigslist provided a lot more value to the world than it took away.
In trying to deal with that, we’ve started to see new forms of economic measurements pop up. One popular one is “happiness.” There’s even been some talk about using “Gross National Happiness” as a key economic measure. There’s a great book from a couple of years ago by Nobel-prize winning economist Joseph Stiglitz, with Amartya Sen and Jean-Paul Fitoussi, called Mismeasuring Our Lives: Why GDP Doesn’t Add Up. It was actually the result of a request from then French President Nicolas Sarkozy to explore how useful (or not) GDP was, including looking into alternate measurements, such as this idea of Gross National Happiness. If you haven’t read the book, I highly recommend it.
Recently, the folks at Planet Money also did a report on the growing interest in measuring happiness, particularly as an official stat for American economic health. There appears to be growing interest in establishing a happiness index for the US, not unlike the unemployment index. Of course, you can think of the immediate problem. Just how do you measure happiness:
But once you get into the details, there’s a lot of debate over the happiness data. One big divide: Should you ask people how they’re feeling right now, or how they feel about their life in general?
You get different answers depending on what you ask. Which one is more important is a squishy, philosophical question.
The difference between asking about “right now” or “their life in general” can be massive. It shows up clearly in the data about how happy parents are vs. non-parents. There are tons of studies that suggest parents are miserable compared to non-parents. But nearly all of those studies are based on questions about “how happy are you now” type questions. Not surprisingly, the parent changing a diaper is probably going to report slightly less current happiness compared to the non-parent who’s out at the bar with some friends, for example. But… it’s not that simple. When other studies are done that ask parents and non-parents about how happy their overall lives are or how fulfilled their lives are, parents frequently report much higher feelings of fulfillment/happiness on a grand scale, while non-parents often report more regret. In other words: time frame makes a huge difference.
Of course, as the Planet Money report points out, just because something is difficult to measure, or involves highly subjective concepts, doesn’t mean it can’t be done. For example, unemployment data. You might think that this involves a nice, simple objective question, but when you look at the details, it’s actually pretty subjective as well.
In the U.S, in order to be counted as unemployed, you have to be out of a job and looking for work. But what counts as looking for work? Checking Craigslist? Sending out three resumes a week? Five?
“It’s actually kind of a hard question,” says Justin Wolfers, an economist at the University of Michigan. “It’s very subjective.”
Yet every month, a single unemployment number is released.
So, you could see why a “Happiness Index” might be a compelling bit of economic data — especially if you believe (as I do) that GDP is misleading. After all, if people are happier, isn’t that a pretty important thing? Well, yes and no. Even as I find the topic interesting, I also worry a lot about the embrace of “Happiness” as an economic measure beyond the reasons laid out in the Planet Money report. Yes, it’s difficult to calculate, but perhaps you can get past that so long as the calculation is done the same way over time. The real problem, for me, is that when you choose to make something a key economic number like that, you are guaranteed to start optimizing for it. That’s what happens when you create metrics. Whether they’re important or not, whether they’re accurate or not, once you have a number, you naturally try to optimize for it.
It shouldn’t be difficult, then, to quickly come up with scenarios for why a National Happiness Index could create significant problems as people optimize for it. First off, you encourage the kinds of short-term rewards that lead people to say they’re happier, even if that creates massive costs down the road. Want to see governments leverage the present and put the costs on the future? Start using a happiness index. Second, if the focus is on maximizing present-day happiness, then you just focus on drugging the population. Yes, that’s an extreme example, but hopefully it gets the point across. In economics, you need to measure the costs and benefits to things. You can “maximize happiness” in all sorts of ways if you ignore the costs to it. Put happy drugs in the water, and let everyone be thrilled. The Happiness index fails to take into account all of the consequences of doing something like that.
So while it’s encouraging to see more of an exploration into alternative metrics, and getting beyond some of the older metrics that clearly “mismeasure” important aspects of our lives, we need to be careful to not just leap to the “next great thing” without realizing that it, too, likely has downsides.