Happiness is a relative concept. Specifically, how happy you are depends on what your aspirations are, or how high you set the bar. For instance, if you are a blue-collar worker with a relatively low salary, and your current goal is to go on a camping trip to the Rockies, and you can do it, then, ceteris paribus, you are probably happier than a rich investment banker whose goal is to buy a private island but cannot do it because his bonus wasn’t as high as expected.
Of course an economist might ask, does the probability that one’s aspirations are fulfilled vary with income? One would expect that the answer is yes. But actually, it is not always the case. Indeed, if you assume aspirations don’t differ much by socioeconomic status, then of course higher income individuals should be in a better position to fulfill them.
We all know sleep is essential to ensure we have enough energy during the day. Yet a lot of people suffer from sleep deprivation. This can be a huge issue as it can lead to lower productivity and lack of alertness, which may even culminate in lower economic growth.
But forget about economic growth for the moment, let’s concentrate on something that individuals may care much more about: life satisfaction. Does sleep duration affect life satisfaction? You bet. In fact, it turns out the average individual sleeps about an hour less than what would maximize their life satisfaction.
Self-reported well-being as measured in surveys is the metric most often used by economists to measure happiness. This post examines the spatial distribution of happiness in U.S. metropolitan and rural areas. We’ll see which are the most and least happy areas in the country.
Furthermore, the post will look at the reasons of the geographical variation in happiness, its long-term trends, and finally some philosophizing about whether happiness and utility are the same thing.