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We Are Happier than We Realize: Underestimation and Conflation in Measuring Happiness

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The study evaluates a very common question designed to measure happiness: “Taken all together, how would you say things are these days–would you say that you are very happy, pretty happy, or not too happy?” Through five representative survey experiments, we show that (1) this survey item underestimates the level of happiness with one’s life; (2) this is because the measure is more likely to reflect satisfaction with the state of the world rather than personal life; (3) this measures is more susceptible to priming; (4) the addition of three words “in your life” to the item greatly reduces priming and question order effects; and (5) the addition of these three words produces results that are very similar to life satisfaction measures that include “in your life” and are more positively associated with income. These results provide evidence that a simple correction better measures personal happiness. Furthermore, our findings reassess the foundation of a considerable volume of scholarship about how politics and income is associated happiness.

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Fig. 1

Source: University Poll

Fig. 2

Source: Elon University Poll, Feb. 2013. N = 886

Fig. 3

Similar content being viewed by others

Notes

  1. http://www.federalreserve.gov/newsevents/speech/bernanke20100508a.htm---It should be noted that in this speech Bernanke specifically cites the survey item we evaluate in this study.

  2. The advantage of using external evaluations of happiness is that one can avoid problems stemming from common-source bias. Researchers have observed that when two self-reported measures are obtained from the same source, such as a single survey, the association between the two measures is often inflated (Favero and Bullock 2015; Meier and O’Toole 2010).

  3. Additionally, Smith (1979) investigated the slight difference between the National Opinion Research Center (NORC) wording and the Survey Research Center, University of Michigan (SRC) wording of a single item happiness question and finds noticeable differences in responses but suggests that much of this may be due to question ordering in the two surveys.

  4. GSS variable name HAPPY. A Google Scholar search of the exact question revealed 628 results. Document counts accessed on 9/19/2015.

  5. Mutz (2011) argues that “population-based survey experiments provide a means of establishing causality that is unmatched by any large-scale survey data collection effort, no matter how extensive.”

  6. Details of each survey is presented in Table 5 in the Online Supporting Materials.

  7. See Nicholson-Crotty and Meier (2002) for a defense of single-state studies.

  8. The results were also consistent across survey mode. In an online, web-based survey we found that the modified happiness question produced happier responses than the standard question wording.

  9. To assess accuracy of coding, we coded responses with multiple coders. Intercoder reliability was 0.71. Other scales could be used for this coding.

  10. We estimate a parsimonious model. However, results are consistent with additional right-hand side variables.

  11. A content analysis of the February 2013 open-ended responses to the questions asking why a respondent was happy or unhappy found that 8 percent of respondents mentioned "government" when "in your life" wasn't in the wording. This is compared to only 1 percent when "in your life" was included in question. In addition, only 3 respondents mentioned the president or his name in the "in your life" survey item, while 14 referenced the president when those words were dropped from the question.

  12. For example, the World Values Survey; European Social Survey, and European Quality of Life Survey use such a measure.

  13. Although Fry and Stutzer (2005) question the causal direction of this relationship and find that for some age groups happy people are more likely to get married.

  14. We replicated the analysis with each of the four telephone surveys containing the 4 category income measure and found in every case our modified happiness measure was more strongly correlated with income than the standard happiness measure.

  15. We estimate a parsimonious model. However, results are consistent with additional right-hand side variables.

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Authors and Affiliations

  1. Elon University, Elon, NC, USA

    Jason A. Husser

  2. College of Southern Nevada, Las Vegas, NV, USA

    Kenneth E. Fernandez

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Husser, J.A., Fernandez, K.E. We Are Happier than We Realize: Underestimation and Conflation in Measuring Happiness. J Happiness Stud 19, 587–606 (2018). https://doi.org/10.1007/s10902-016-9831-0

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