How Comparable are the Gallup World Poll Life Satisfaction Data?


This paper explores the degree to which the new data on life satisfaction from the Gallup World Poll are comparable to those used in previous empirical studies, predominantly those from the World Values Survey. Differences might arise due to the timing and anchoring of questions in the Gallup data. The paper identifies a set of large outlier countries, and estimates suggest that the two datasets tend to generate rather different results, questioning the degree to which they measure the same concept.

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Fig. 1


  1. 1.

    The only other surveys that provide cross-country data are the International Social Survey Programme, which unfortunately includes only a small number of countries, all covered by the WVS, and the European, Latin American, African and Asian Barometers, that have so far been used in very few studies on specific regions.

  2. 2.

    For a broader discussion of issues related to comparing different surveys and survey designs, see Veenhoven (2006, ch. 7) for an optimist view and Ormerod and Johns (2007) for a corresponding negative view.

  3. 3.

    The data employed in Bjørnskov et al. (2008c), available twice a year for most years since 1973 for the EU-15 and distributed from one to four, serve to illustrate the stability of the scores over time. Even though the difference between the least happy and the happiest European country is almost one point on the four-point scale, the intra-country variance over time is only .007.

  4. 4.

    The difficulty in translating the concept arises out of at least two problems. First, the Russian and French translations of ‘happy’ both mean happy and lucky, implying that the word can have multiple meanings that make the scores less comparable across countries. Second, the word may carry more or less weight. Even while Denmark has the world’s happiest population in most surveys, the Danish translation ‘lykkelig’ is a stronger concept than the parallel notion of ‘happy’ in English and would arguably require more to achieve.

  5. 5.

    Bjørnskov (2003), relying on WVS data, finds that not only do the Latin American countries score higher on life satisfaction than one would expect, but failing to control for this effect biases coefficients on income inequality, and potentially other institutional factors, upwards.

  6. 6.

    An additional simple test is to replace GDP per capita with the level of private consumption, as indicated by Fischer’s (2008) recent critique of Easterlin’s work. However, the logarithm to private consumption fairs worse than GDP when using the GWP data (not shown). Yet, given the vast differences in taxes across the world, which the data do not take into account, it remains an open question which is the most relevant measure of income in happiness studies.

  7. 7.

    One of the referees of this journal suggested that the GWP data might not measure life satisfaction at all, but instead capture individuals’ attempts at objectively classifying their lives on a ‘good life’ dimension. While the present analysis cannot be used to draw such conclusions, it certainly remains a likely possibility.


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Correspondence to Christian Bjørnskov.



Table A1 Data sources and studies
Table A2 Descriptive statistics
Table A3 Data definitions
Table A4 Testing prior hypotheses of determinants of national average satisfaction—using WDH data

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Bjørnskov, C. How Comparable are the Gallup World Poll Life Satisfaction Data?. J Happiness Stud 11, 41–60 (2010).

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  • Life satisfaction
  • Data comparability
  • Validity