Happiness Inequality #2: Differences Between Groups

Yesterday I showed that happiness inequality has fallen since the 1970′s. The natural question is: Why?

To answer this, we ran an analysis that simultaneously estimated the evolution of happiness through time, by education, race, gender, age, marital status, and region. Here are a few graphs summarizing these findings.

(To think about the units on these graphs, we basically convert each person’s happiness level into a “z-score”; for instance, my happiness z-score is about 1.2, indicating that I’m 1.2 standard deviations happier than the average person.)

First, we find that the rising wage gap between college graduates and high school graduates (and high school dropouts) has been paralleled by a rising happiness gap by education:

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(The year-to-year bumps largely reflect statistical noise, as we are asking a smallish dataset to speak to a range of issues.)

Second, just as racial wage gaps have declined, so too has the racial happiness gap. In fact, the declining significance of race is quite striking:

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Turning to gender, Betsey and I have previously written about the “Paradox of Declining Female Happiness,” and our finding that women are becoming less happy shows up again:

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Thus, happiness trends by race and gender point to declining happiness inequality, while the trends by education point to rising inequality. We have also analyzed trends by region, age group, and marital status, although I’ll leave you to read the full paper to see them. (Hint: Turn to Figure 6.)

How important are these trends in the overall scheme of things? That’s the topic I’ll return to in tomorrow’s post.

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COMMENTS: 37

  1. Gina Marie says:

    How can I calculate my happiness z-score? I want to know where I stand in this!!

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  2. doug says:

    I’ll say it again. Women are becoming more unhappy because they are working outside the home and are incurring all that goes with it.

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  3. Mike says:

    Hold up. While the proportions of men and women are expected to remain largely the same, what about the other groups?

    For instance, if in 1972 there were relatively FEW non-whites, but they were quite unhappy, and now there are MANY non-whites wouldn’t that data just be showing a regression to the mean due to an increasing sample size? Or, are there more or less college grads now than in 1972?

    I think it would be interesting to see how your group happiness is effected by the size of your group. Isn’t it harder to be happy when you feel socially isolated, as opposed to when you have a lot of people to identify with?

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  4. Tom says:

    Using the GSS question, you have to choose one of three answers: not too happy (1), pretty happy (2), or very happy (3). In 2006 the GSS average was 2.17, and the sd was .64. So to get a rough estimate (comparing yourself to the 2006 sample), find the difference between your answer and the mean, then divide by the sd, and you get your z-score.

    PS I’m working on the GSS (only through 2006) right now. I didn’t actually download the dataset to find this out…

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  5. Matt says:

    Funny how in the last 20 years, the pattern for male happiness lags about a year behind female happiness.

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  6. kpg44 says:

    Matt and Doug. great observations. that is all

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  7. Black Political Analysis says:

    Americans tend to lead stressful lives, which personal economics exacerbates.

    Yet, it’s all relative. As a whole, Americans aren’t as happy as many in Western Europe. Why? Some will expectations. I remember a 60 Minutes segment on this with Morley Safer. The Danes led the world in happiness and part of the explanation was that they don’t expect very much to begin with. I’m not saying Americans should lower their expectations, but we’re often disappointed if we don’t drive the fancy car, or live in biggest home, or take the greatest vacations.

    http://blackpoliticalanalysis.com

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  8. iampriteshdesai says:

    The reason for this is the declining cost of entertaining electronics products like iPod etc. Previously only the rich could have access to best things in life. Now pretty much every one has/. All have PC’s , internet they watch movies.

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