Measuring Happiness: Literature Review
Measuring the subjective experience of 'happiness' can be challenging due to the broad scope of the term. Several studies have used quantitively-scored happiness data obtained from surveys (e.g. Zhang, et al, 2017b; Sanduijav, et al, 2021; Goetzke & Rave, 2015). However, within these studies, the quantitative ‘happiness’ is defined in different ways. The main split is between 'hedonic' happiness and 'eudaimonic' happiness. The former describes 'moment-to-moment experienced utility and directly links to immediate emotions and affection' and the latter is an evaluation of a person’s happiness across their entire life (Zhang, et al., 2017a, p. 81). This methodological divide makes it significantly more difficult to define happiness as a measurable concept.
Existing studies demonstrate a significant relationship between air quality and happiness: (Zhang, et al., 2017b; Sanduijav, et al., 2021; Goetzke & Rave, 2015), thereby confirming the validity of our proposed exploration of the topic. Additionally, these studies draw on quantitative data from secondary sources: a governmental body (e.g. Houlden, et al., 2019) or NGO (e.g. Sanduijav, et al., 2021), demonstrating the methodical similarities between our approach and previous ones, and perhaps indicating its reliability. Both our approach and previous studies use scored data, taken from individual responses to subjective wellbeing questions where the participants have been asked to place their response on a numerical scale, a method highlighted by the OECD (2013, cited by Sanduijav, et al., 2021, p. 9), as providing a framework for generating nationally representative survey data.
Although approaches to defining happiness by scoring are corroborated in many studies, it is near impossible to define all aspects of the subjective concept and represent it quantitatively. Dambrun, et al.’s 2012 paper discusses the important methodological distinction of measuring ‘authentic-durable’ and ‘fluctuating’ happiness, but notes the current limitations of executing the method. Sanduijav, et al., (2021) and Houlden, et al., (2019) each take a more holistic approach to the idea of ‘happiness’ and emphasise using data that describes a more general picture of mental wellbeing. Conversely, Zhang, et al., (2017b) and Goetzke & Rave (2015) use data on only hedonic happiness and eudaimonic happiness respectively. Zhang, et al.’s happiness data is arguably less precise since the hedonic happiness scale is comprised of 5 points (0-4). This is a smaller scale compared to the range used by Sanduijav, et al. (2021) or the methods proposed by Dambrun, et al. (2012)-- this suggests that the latter studies may access greater nuance in their analysis of happiness trends.
What remains unacknowledged in this literature, however, is the serious potential for bias in evaluating eudaimonic happiness. There is no evidence so far that researchers who measure happiness can account for how an individual’s emotions (hedonic happiness) influence their life evaluation at that one instance. The methodology in the literature discussed relies on a mismatch: using a single, instantaneous method to measure the subjective experience of an entire life. Zhang, et al. (2017b) convincingly claims that measuring eudaimonic and hedonic happiness separately would yield different results, which substantiates concerns about measuring any subjective experience, including hedonic happiness.
Although the Zhang, et al. (2017b), Sanduijav et al. (2021), Houlden, et al. (2019), and Goetzke & Rave (2015) studies each agree that greater concentrations of air pollution generally have negative impacts on happiness, Zhang, et al.’s claim seems to indicate that different definitions of happiness can be varyingly useful to different research questions. Considering this, we believe that, despite its ephemerality, hedonic measurements are the most appropriate tool for a longitudinal study on a national scale.