“CBS This Morning” reported on a survey done by the University of Vermont in which researchers searched “geo-tagged” twitter messages for words that were either “happy” or “unhappy” words, and then compiled the data by state. Here’s a link to the results: http://www.uvm.edu/storylab/share/papers/mitchell2013a/AppendixB.html.
The colored map caught my population density-sensitive eye. Knowing that the eastern U.S. is more densely populated than the western U.S., I was immediately suspicious that there may be a correlation. It’s something I’ve suspected for a long time – that people living in crowded conditions are more unhappy – but I’ve never come across any hard data, until now. (Although one could question just how “hard” the data is that’s gathered from a twitter survey.)
So I plotted the data state-by-state vs. each state’s population density on a scatter chart to see if any correlation emerges. Here’s the chart: U of Vermont Happiness Index. There’s a lot of scatter in the data but, once a trend line is calculated and plotted by the computer (in this case, a logarithmic trend line gave the best correlation) a relationship does emerge. For this trend line, the correlation coefficient (R2) is 0.13. A correlation coefficient of 1.0 indicates a perfect, straight line relationship while a correlation coefficient of 0.0 indicates that no relationship exists, as you’d find in a shotgun-like scatter of the data. So the relationship is weak, but there’s definitely one there. Densely populated states tend to be more unhappy while more sparsely populated states tend to be happier.
No doubt, there are many other factors involved. Southern states seem to be less happy. Even though Texas is below the average population density, it ranks near the bottom of the happiness index. Perhaps oppressive heat and humidity are factors. Having lived for five years in the Houston area, I can tell you that it was definitely a factor for me. (I felt like I was living in hell for much of the year.) Houston is also among the worst in terms of air pollution and traffic congestion.
California’s happiness index holds up quite well, in spite of its population density being well above average. Perhaps its climate and beautiful geography tend to offset its overcrowding. Lending support to that theory, it should be no surprise that Hawaii is the happiest state in the union.
Alaska, the least densely populated state, falls somewhere around the middle of the happiness scale. Perhaps the happiness that would otherwise be attributed to its sparse population is offset by its bitterly cold and dark climate for much of the year. Or, perhaps the diminished opportunities for social interaction in an extremely sparse population actually becomes a negative factor. That is, perhaps there’s a “sweet spot” in terms of the relationship between population density and happiness.
It also struck me how similar this map was to the electoral college map in the most recent presidential election. Republican states also tended to be western states (with some exceptions, like California), while the Democratic states tended to be eastern states. Does this mean that Republicans are happier than Democrats? Maybe. If you think about it, people who are better off financially tend to be more conservative and tend to vote Republican. The Democratic states tend to be less happy. Does this mean that President Obama was better than George Romney at tapping into unhappy voters? Or do his policies play better to people in densely populated (and less happy) situations, who see more of a role for government in maintaining an orderly society? But, then again, this may also tend to relate back to population density, since unemployment is higher in densely-populated areas.
This is all a bit beyond the scope of my economic theory based on the very real and powerful inverse relationship between population density and per capita consumption, and I don’t want to make too much of what appears to be a weak relationship, but the evidence suggests that we all might be a bit happier if the U.S. was less crowded.