Eger, R. J., & Maridal, J. H., (2015). A statistical meta-analysis of the wellbeing literature. International 

Journal of Wellbeing, 5(2), 45-74. doi:10.5502/ijw.v5i2.4 

 

Robert J. Eger 

Naval Postgraduate School 

rjeger@nps.edu 
 

Copyright belongs to the author(s) 

www.internationaljournalofwellbeing.org 

45 

ARTICLE  

 

A statistical meta-analysis of the wellbeing literature 
 

Robert J. Eger  ·  J. Haavard Maridal 
 
 

Abstract:  This study employs an empirical meta-analysis to examine the livability factors of 

wellbeing and assess each precursor’s relative significance. The effect size results of individual 

studies of existing academic work are pooled by the use of a variety of statistical techniques to 

determine a meta-effect that yields statistically more significant conclusions and is a more 

powerful measure in that it has the ability to identify results closer to the true outcomes. The meta-

analysis in this paper covers 164 studies and 560 observations published prior to September 2013. 

After articulating definitions of the central concepts and tenets of the scholarly research on 

wellbeing, the analysis continues with a literature review identifying recurring factors of 

wellbeing and the associated correlation. To address the variation in the type of analysis that 

underlies each study, all studies are converted to an effect size using Fischer’s z and then analyzed 

under the DerSimonian-Laird random-effects model. The results largely confirm the findings in 

the literature but also reveal some surprises and suggest avenues for future research. The meta-

analysis finds empirical support for the dimensions of living standard, health, freedom, personal 

and community relationships, peace, and security as significant livability factors of wellbeing. 

 

Keywords: philosophy, public policy, eudaimonia, life satisfaction 

 

1. Introduction 

The scholarly literature identifies a number of elements as contributors to wellbeing. The purpose 

of this study, which uses an empirical meta-analysis approach, is to assess the relative 

significance of the main factors of wellbeing discussed in the literature. The paper begins with a 

brief introduction to the history of the concept of wellbeing and then articulates definitions of 

the central concepts and tenets of the scholarly research in the field. A review of the academic 

literature in this area helps both to explain the dimensions associated with wellbeing and to 

identify the main components of wellbeing. The paper then describes the meta-analytic 

techniques employed and identifies methodological limitations before turning its attention to the 

meta-analysis itself, looking at each livability factor and its associated correlations. The paper 

ends with a discussion and implications. 

 

1.1 Brief history of the concept of wellbeing   

In the past, happiness denoted a concept comparable to the term ‘objective wellbeing’ used today. 

In ancient Greece, and in both Christian and Eastern wisdom and religious literature, happiness 

signified a life worth living and the truly happy person pursued virtue over the course of a 

lifespan. Happiness was a holistic concept in the vein of the Greek poet Hesiod’s and the 

historian Herodotus’ eudaimonia (a virtuous and flourishing life), the Roman philosopher 

Cicero’s summum bonum (the highest good), and the medieval philosopher and theologian 

Thomas Aquinas’ sublime beatitudo (the Godly life). Historically, happiness had also been 

associated with luck, fortune, or divine favor. In this way, it was seen by some as being beyond 

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a person’s control to a certain extent (McMahon, 2006). Traditional perceptions of happiness 

began to change on two fronts during the Age of Enlightenment in the 18th century. First, the 

emphasis on virtue as a necessary path to flourishing and wellbeing was diminished in favor of 

a focus on pleasure and the absence of pain, something most strongly evident in Jeremy 

Bentham’s (1789) philosophy of Utilitarianism. Second, the pursuit of this new form of happiness 

was elevated as the principal purpose of human life. As a consequence of these ideas, happiness 

came to be defined more narrowly—not as wellbeing in a broad and inclusive sense but rather, 

as in Bentham, as a good feeling. 

This relatively new conception of happiness has given rise to a growing body of popular and 

academic literature seeking to discover how happiness, life satisfaction, and wellbeing are 

achieved. The academic literature focuses primarily on positive psychology, studying how 

individuals can feel better, and on economics, trying to understand how people and governments 

can make welfare-enhancing choices. Despite these focus areas, happiness research is becoming 

increasingly important in most of the social sciences. Academia and popular literature are not 

the only clusters of society concerned with wellbeing, however; attempts are increasingly being 

made by agencies in the governmental sphere to use research on wellbeing to inform policy, with 

the aim of increasing overall societal wellbeing. An example of this is the United Kingdom’s 

recent efforts in measuring national and personal wellbeing through the Office for National 

Statistics (Office for National Statistics, 2014). 

 

1.2 Theoretical background 

A universal definition of wellbeing has somewhat eluded scholars. In the academic and popular 

literature, the terms quality of life, happiness, life satisfaction, and prosperity are often used 

interchangeably with wellbeing. However, as statistical analysis of population surveys and 

dictionary definitions suggest,  these terms differ in their nuances. Happiness is increasingly used 

to describe momentary pleasant emotions, while life satisfaction is used to refer to long-term 

cognitive evaluation of life as a whole, a sort of deeper happiness. Prosperity, on the other hand, 

tends to be used in discussions of tangible economic conditions. Sociologist Ruut Veenhoven, 

considered by some to be the father of happiness studies, has argued that wellbeing should be 

used to denote quality of life overall (Frisch, 2013). 

This study defines wellbeing as a composite of the two underlying concepts of happiness and 

life satisfaction. Although this definition has roots in ancient literature, as exemplified by Thomas 

Aquinas’ delineation of sublime beatitudo (McMahon, 2006), Bradburn and Noll (1969) may have 

been the first modern scholarly work to emphasize the idea that wellbeing is composed of both 

evaluative and joy- or pleasure-based effects. Campbell, Converse, and Rodgers (1976) drew a 

contrast between life satisfaction and happiness, describing the former as “a judgmental or 

cognitive experience” and the latter as “an experience or feeling of affect” (p. 8). In this vein, Lane 

(2000) argued that happiness represented a marginal emotional change. Further support for this 

distinction can be found in Diener, Kahneman, Tov, and Arora (2010); Helliwell, Barrington-

Leigh, Harris, and Huang (2009); Kahneman (1999); and Lucas, Diener, and Suh (1996). A quick 

analysis of self-report surveys supports the distinction between happiness and life satisfaction: 

the correlation between the two concepts in the World Values Survey (1981–2005) is only .47, for 

example, signifying that the two are different, albeit related, concepts. Along these lines, as the 

terms are used in this study life satisfaction describes a cognitive judgment and happiness refers 

to an emotional state. 



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1.3 Evaluative wellbeing and affective wellbeing 

Scholarly research increasingly uses the terms evaluative wellbeing (EWB) and hedonic wellbeing 

(HWB). In Kahneman and Deaton (2010) and Graham (2010), EWB is defined as a global, 

contemplative, long-term assessment, a state of wellbeing that is reflective of one’s sense of 

quality of life—not at a given point in time but rather over the course of one’s life. HWB refers to 

a person’s present, and potentially more transient, state of wellbeing as measured by the positive 

or negative affects experienced immediately or daily. 

In this study, however, preference is given to the term affective wellbeing (AWB) in place of 

HWB to describe a person’s present or experienced state of wellbeing. The concern is that hedonic 

is not an accurate descriptor for experienced wellbeing because one’s momentary, experienced 

feelings and emotions are not necessarily concerned solely with pleasure. Rather, it is possible 

for them to stem instead from a deep inner joy as explained by the Greek concept of eudaimonia, 

Cicero’s expression of the summum bonum, or Thomas Aquinas’ sublime beatitudo. According to 

this understanding, one’s present wellbeing derives not only from bodily pleasures but also from 

personality traits and temperaments, including prudence (according to Aristotle’s Ethics, book 9 

and 10) (Rackham, 1934), personal choice (Seligman, 2002a, 2002b), and states of mood that may 

be hereditary or genetically determined (Lykken, 1999). 

As depicted in Figure 1 below, EWB and AWB can be imagined as a continuum, with EWB 

on the pure cognitive, evaluative end and AWB on the pure immediacy, affective end. Life 

satisfaction is more closely aligned with the former and immediate or experienced happiness 

with the latter. 

 

 

EWB and AWB both emanate from two primary categories of sources: livability and lifeability. 

Livability denotes environmental, societal factors, in which a person finds himself or herself, and 

lifeability describes the internal, personal dynamics that enable this person to benefit from his or 

her environment. 

Scholarly literature distinguishes between subjective and objective wellbeing (Arneson, 1999; 

Parfit, 1984; Scanlon, 1993; Sumner, 2003). Subjective wellbeing (SWB) refers to a person’s 

particular experience of his or her own life and can be measured through self-report methods 

such as population surveys. Objective wellbeing (OWB) consists of a list of quantifiable social or 

economic indicators that a scholar theorizes are determinants of quality of life (Sen, 1999). 

In SWB surveys, questions can range from the very long-term and evaluative (EWB) to the 

very immediate and emotional (AWB). Responses to questions like those in Cantril’s self-

anchoring ladder (1965) fall on the extreme EWB side of the EWB-AWB continuum and are more 

strongly correlated with life satisfaction.1 AWB questionnaires measure respondents’ present 

affects. These questions may use a positive and negative affect schedule (Watson, Clark, & 

                                                 
1 A typical question measuring life satisfaction might ask: “All things considered, how satisfied are you with your life 

as a whole these days? Use a scale from 1–10 where 1 means you are ‘completely dissatisfied’ and 10 means you are 

‘completely satisfied.’” 

Evaluative 

Wellbeing (EWB)

Affective 

Wellbeing (AWB)

Pure Cognition Pure AffectHappiness Life Satisfaction 

Figure 1: Wellbeing—Life Satisfaction and Happiness on the EWB—AWB 

Continuum 

 



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Tellegen, 1988), which falls on the extreme AWB side of the continuum and responses correlate 

more strongly with happiness.2 Table 1 below presents a classification of the concepts introduced 

thus far. 

 

Table 1: Classification of Wellbeing Concepts 

Subjective Variables Of Wellbeing (SWB) 

Underlying Concept Life Satisfaction (EWB) Happiness (AWB) 

Level Of Perception 
Cognitive, evaluative, reflective, 

long term 

Emotional, mood or affect-

based, sensory, short term 

Potential Measurements 
Cantril’s self-anchoring ladder, 

questionnaire (scale from 1–10) 

Day reconstruction method, 

positive and negative affect 

schedule (PANAS) 

Objective Variables Of Wellbeing (OWB) 

Concept 
Livability dimensions 

(environmental, external factors) 

Lifeability dimensions 

(individual, internal factors) 

Elements 

Friends, family, peace, freedom, 

health, income, wealth, 

opportunity, etc. 

Degree of purpose and meaning 

to life, attitudes, life choices, 

heredity3 

Potential Measurements  
Numerical indicators of income, 

health, family, crime, etc. 

Brain-scanning, revealed 

preferences, questionnaires 

 

2. Literature review 

Using the theoretical classification, this study’s focus is on factors of wellbeing that stem from 

livability. To explore the extant literature on the factors of livability, six groupings are identified 

through a review of the academic literature on wellbeing. These groupings are living standard; 

health and environment; freedom; community and relationships; peace and security; and 

opportunity. 

 

2.1 Living standard 

The factor ‘Living standard’ is concerned with the material resources available to people in a 

society and is often measured through economic and financial indicators. The living standard effect 

is at the center of Jeremy Bentham’s (1789) economic utility theory and a substantive component 

of Maslow’s (1943) hierarchy of needs. Economic utility theory suggests that as individuals gain 

income and wealth, they gain purchasing power, which expands the bundle of goods they can 

afford, leading to increased consumption and, ultimately, improved wellbeing. Considerable 

disagreements exist in the literature regarding the degree to which income and wealth contribute 

to wellbeing. Currently, the science seems to have settled on an understanding that the cognitive 

evaluation of one’s life (i.e., one’s life satisfaction) is considerably and positively impacted by 

increases in living standard, while happiness is impacted only up to medium income levels 

(approximately $75,000 according to Kahneman and Deaton (2010)). Increased financial 

                                                 
2 It is important to emphasize that the difference between happiness and life-satisfaction is also determined by the 

way questions are framed in the surveys. A question measuring happiness that would fall closer to the AWB side of 

the continuum is: “Presently, would you describe yourself as: (1) Very happy, (2) Rather happy, (3) Not very happy, 

or (4) Not at all happy?” 
3 Determined by genetic factors and therefore able to be passed on from parents to their offspring or descendants. 

  



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resources can, however, impact people’s wellbeing through means other than direct 

consumption. Dunn, Aknin, and Norton (2008) found that spending money on other people 

created more happiness than did spending money on oneself, a finding supported by Zak (2011). 

Income is also highly correlated with health and, to a certain degree, with opportunity. 

 

2.2 Health and environment 

The factor ‘health and environment’, as related to wellbeing, deals with the prevailing physical, 

mental, and environmental conditions for individuals in a society. Although Graham (2008) and 

others have pointed out that people adjust surprisingly well to both negative and positive 

changes in their health, research has found wellbeing is greater for people who enjoy good 

physical and mental health. Research supporting this hypothesis includes Bee and Bjorklund 

(2000); Dolan and White (2007); Heylighen (1999); Katsaiti (2012) and Kushner and Foster (2000). 

Research, however, has found health and wellbeing is a non-recursive system. Blakeslee and 

Grossarth-Maticek (1996) showed that wellbeing is highly predictive of future good health. Some 

of the objective indicators of health identified in the literature include life expectancy, 

undernourishment, suicide rates, positive experiences, mental and physical suffering, and air, 

water, and sanitation quality. 

 

2.3 Freedom 

Freedom concerns the extent to which people are in control of their own lives. Sen (1999) was 

among the first to propose that freedom is a “bundled commodity” consisting of political, 

economic, civil, and religious categories. The magnitude of freedom can be measured by the 

degree to which there is respect for political, civil, religious, and economic freedoms in a society 

as well as by people’s perceptions of these freedoms. Triandis and Gelfand (1998) say that 

although absolute freedom in all areas may be counterproductive, dynamic social systems and 

cultures have a tendency to combine a sense of social responsibility and solidarity with a high 

degree of freedom for people to follow their personal moral compasses to make key choices for 

themselves. Gundelach and Kreiner (2004) and Verme (2007) find freedom to be the component 

possessing the overall strongest correlation to wellbeing. Other research supporting the 

correlation between increased wellbeing and freedom in general includes Heylighen (1999), 

Brooks (2008a, 2008b), and (Veenhoven, 2008, 2012). More specifically, Diener, Diener, and 

Diener (1995) found that political freedom and civil liberties enhance wellbeing, while Gropper, 

Lawson, and Thorne (2011) found that economic freedom augments wellbeing. 

 

2.4 Community and relationships 

The factor ‘community and relationships’ relates to the quality of the community, family life, and 

friendships in a society. According to social causation theory (Joung, 1997; Mastekaasa, 1992), 

community and family relations increase wellbeing by providing emotional and financial 

support to the individual. This support serves as a buffer against the travails of life, thereby 

preserving or increasing wellbeing. The empirical literature has found that deep human 

interactions are directly beneficial to the individual’s emotional state and feeling of wellbeing. 

There is also an indirect effect through higher social capital and lower transaction costs that leads 

to economic growth and an increased standard of living. Empirical support for the importance 

of close-knit community interaction for wellbeing can be found in Stolle (1998), Putnam (2000), 

Guiso, Sapienza, and Zingales (2006), and Zak (2011). Religious engagement as a precursor for 

higher wellbeing has been identified by Lim and Putnam (2010), Winkelmann and Winkelmann 



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(1998), Ellison and Levin (1998), Diener and Suh (1997), Veenhoven (1996), Wilson (1967), 

Helliwell (2008), and Inglehart (2010). Drummond (2000), Plagnol and Easterlin (2008), Helliwell 

and Putnam (2004), Diener, Gohm, Suh, and Oishi (2000), Kahneman and Krueger (2006), and 

Veenhoven (2012) provide support for marriage and family life as important aspects of people’s 

wellbeing. 

 

2.5 Peace and security 

The factor ‘peace and security’ relates to sources of instability in a society such as the level of 

violence and crime; and also to trust, transparency, corruption, and bureaucratic quality, or 

efficiency. In addition to community and freedom, peace is one of those factors humans need in 

order to thrive. Competent governance, in the sense of the minimization of violence, crime, 

corruption, and cronyism, fosters a peaceful society. Research that has found some of the 

foregoing impact wellbeing includes Oishi (2012), Oishi and Roth (2009), Inglehart (1990), Frey 

and Stutzer (2000), Inglehart and Klingemann (2000), and Diener, Inglehart, and Tay (2013). 

 

2.6 Opportunity 

Opportunity is concerned with people’s access to things like community basics (i.e. workable 

infrastructure) education, employment, and entrepreneurship that enables them to live satisfying 

and happy lives. The link between opportunity and wellbeing on a societal level is a highly 

mobile economic and social environment. A society with high levels of opportunity is an 

environment that does not discriminate. It is one that allows equal prospects for all when it comes 

to pursuing the good life. As such, the factor ‘opportunity’ is closely related to the factors 

‘freedom’ and ‘living standard’. The opportunity to work, satisfaction with one’s job, and the 

prospect of pursuing entrepreneurial undertakings have been found to be strong explanatory 

factors of wellbeing according to Frankl (1963), Brooks (2008a, 2008b), and Murray (1988), among 

others. Opportunity is especially important to the underprivileged, and poverty sometimes 

results from a lack of opportunity. Research supporting the link between poverty and wellbeing 

includes Biswas-Diener and Patterson (2011), Marshall et al. (2001) and Oishi, Kesebir, and 

Diener (2011). According to Meulemann (2001), education might also be an important driver of 

opportunity. 

 

3. Methodology 

The theoretical background and scholarly literature support the operationalization of these six 

categories. The review of the scholarly literature introduced the reader to the most recurring 

findings based on these groupings. It provides an opportunity to explore and test, through a 

meta-analysis, the linkage of these livability aspects with wellbeing. 

By offering the opportunity to combine evidence from retrospectively accumulated or 

prospectively generated data, meta-analysis is an important research tool that increases statistical 

power by combining results from studies that have similar or related research hypotheses. The 

effect size results of individual studies are pooled by use of a variety of statistical techniques to 

determine a meta-effect, which is a more powerful measure of the outcome. In addition to 

increased statistical power, other advantages include greater generalizability and increased 

ability to do multifactor analyses. Using meta-analysis shifts the focus from an individual study’s 

statistical significance towards the true effect size. 

The meta-analysis in this paper was performed by first asking whether the factors identified 

in the literature impact wellbeing. A systematic literature search was performed based on the 



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specified factors. Several search techniques were used to retrieve studies for inclusion. Articles 

written in a language other than English were considered if they had been translated into English. 

Identification was achieved through electronic library databases including JSTOR, ProQuest, 

Web of knowledge, and Dissertation Abstracts International, the Web-based search engine 

Google Scholar, and the Web-based World Database of Happiness (Veenhoven, 2013). 

Computerized searches involved multiple combinations of terms reflecting wellbeing (life 

satisfaction, satisfaction with life, happiness, quality of life, emotional wellbeing, subjective 

wellbeing, and wellbeing).  

The studies identified as relevant were then reviewed and, when inclusion/exclusion criteria 

were deemed similar, graded for quality. Judgments about the quality of studies was based on 

design, follow-up, and outcome assessments. The inclusion/exclusion criteria for the selection 

process were as follows: 

1. The study must involve participants of working age who reside within the geographic 

location investigated; 

2. The study must include a nationally representative sample; 

3. A measure of wellbeing must be clearly defined; 

4. An objective measure of at least one of the proposed factors within the literature on 

livability must be present; and 

5. The study must be publically available with results presented in a correlation or a 

convertible metric that is conducive to computational conversion into an effect size. 

 

Meta-analysis is particularly influenced by the external validity of each of the examined studies. 

Here, external validity refers to the generalization of research findings either from a sample to a 

larger population or to settings and populations other than those studied. To address external 

validity, assessment is based on (1) the extent to which empirical measures accurately reflect the 

stated theoretical constructs, (2) whether the research setting conforms to the scope of the theory 

under test, (3) a subjective assessment regarding confidence that the findings presented may be 

repeated under identical conditions, and (4) the confirmatory status of the theory under test. In 

these ways, external validity is principally seen as a theoretical issue and can be addressed only 

by an examination of the interplay between theory and methods. 

All potentially relevant studies published or posted through September of 2013 were 

considered for inclusion. Every attempt was made to be inclusive; however, the criteria for 

inclusion and exclusion does not guarantee that every relevant study is identified using these 

criteria. Selected articles were then abstracted. 

 

3.1 Fixed effects (FE) vs. random effects (RE) 

Given that meta-analysis is the focus of this study, the distinction between fixed effects (FE) and 

random effects (RE) models is a critically important topic because there is a strange anomaly in 

the behavioral and social sciences today. The anomaly is the fact that although the FE models are 

almost never appropriate, the majority of published meta-analyses in social science in general 

and some related areas have been based on FE models. This is not the case in either the industrial 

and organizational psychology literature and certain other literatures such as management 

studies, organizational behavior, and business strategy (Hunter & Schmidt, 2000). 

Inference under a meta-analysis framework indicates that if there is real variation in 

population parameters across studies, the FE model not only cannot detect this variation, but 

also produces confidence intervals (CIs) that are erroneously narrow. That is, the FE model 

greatly underestimates the amount of uncertainty in the estimated mean value. Of course, the FE 



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model produces accurate results when there is zero variance across studies in the population 

values. The problem is that there are few if any study sets that meet this condition (Hunter & 

Schmidt, 2000). On the other hand, RE models produce accurate results in both cases: when there 

is and is not variation in study population values. 

Evidence of the anomaly and of the use of FE models is explored in (Schmidt, Oh, & Hayes, 

2009). Using two different RE methods to reanalyze the data from five FE-based meta-analysis 

publications in Psychological Bulletin that included a total of 54 separate meta-analyses, they 

found that the average level of underestimation of the width of the CIs by the FE models was 

55%. That is, the FE CIs are, on average, less than half as wide as the actual CIs. This amounts to 

a very serious overestimation of the degree of certainty of the mean effect sizes. Hence, the use 

of FE models instead of RE models does not lead to merely technical anomalies. It leads to major 

errors. 

Hedges and Vevea (1998) and Overton (1998) point to a possible reason for the use of FE 

methods. They suggest that the choice of a FE or RE model depends on the type of inference that 

is the goal of the meta-analysis. If the goal is to draw conclusions that are limited to the set of 

studies at hand, and there is no desire to generalize beyond the particular set of studies included 

in the analysis, the FE model can be used when population parameters vary and when they do 

not. Hedges and Vevea (1998) refer to this as conditional inference. The usual goal of research, 

however, is generalizable knowledge (Toulmin, 1961), which requires generalization beyond the 

current set of studies to other similar studies that have been or might be conducted. Hedges and 

Vevea (1998) refer to this as unconditional inference. 

The objective of this meta-analysis is to make unconditional inferences about a wide 

population of studies; that is, to draw conclusions that can be generalized beyond the specific set 

of studies included in the presented meta-analysis. The methodological purpose, therefore, is to 

reach conclusions that are not limited to the specific set of studies in the meta-analysis, because 

the set of studies at hand is viewed as a sample of a larger number of studies that might exist or 

could be conducted (Hedges & Vevea, 1998; Hunter & Schmidt, 2000; Overton, 1998; Murray et 

al., 1994). In this case, generalization of conclusions is an important aspect of the study and the 

RE model is offered in the analysis, i.e., the inference of cumulative knowledge (Field, 2005; 

Hedges & Vevea, 1998; Murray et al., 1994). 

To address variation in the type of analysis that underlies each study, all studies are 

converted to an effect size using Fischer’s z and then analyzed under the DerSimonian-Laird 

random-effects model. This model assumes heterogeneity between the studies; that is, it assumes 

that the true effect can be different for each study. The model assumes that the true effects of 

individual studies are distributed with a variance 
2

  around an overall true effect, but the model 

makes no assumptions about the form of the distribution of either the within-study or the 

between-studies effects. 

 

3.2 Addressing publication bias  

Once a study included in this meta-analysis has been subjectively assessed for external validity, 

based on both statistical methods and theory, the results and implications of that study are 

assessed for publication bias. Publication bias is the term for what occurs whenever the research 

that appears in the published literature is systematically unrepresentative of the population of 

completed studies. Simply put, when the research that is readily available differs in its results 

from the results of all the research that has been done in an area, readers and reviewers of that 

research are in danger of drawing the wrong conclusion about what that body of research shows. 



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Although publication bias has likely been around for as long as research has been conducted 

and reported, it has come to prominence in recent years largely with the introduction and 

widespread adoption of the use of systematic review and meta-analytic methods to summarize 

research. In part, this is because, as methods of reviewing have become more scientific and 

quantitative, the process of reviewing (and synthesizing) research has been increasingly seen as 

paralleling the process of primary research. Parallels to the threats to the validity of primary 

research have been uncovered at every step of the systematic review process (Cooper, 1998; 

Shadish, Cook, & Campbell, 2002). Publication bias is a non-trivial issue. Evidence that 

publication bias has had an impact on meta-analyses has been firmly established by several lines 

of research (Rothstein, Sutton, & Borenstein, 2005). Thus, a problem that was viewed hazily 

through the looking glass of traditional reviews came into sharp focus under the lens of meta-

analysis. 

To address the threat of publication bias, this study uses the Egger, Smith, Schneider, and 

Minder (1997) regression method, which tests for a linear association between the intervention 

effect and its standard error. Alternative methods, such as that of Begg and Mazumdar (1994), 

which proposed testing the interdependence of variance and effect size using Kendall's method, 

may also be applicable in testing for publication bias. Although Begg and Mazumdar (1994) make 

fewer assumptions than do Egger et al. (1997), the method of Begg and Mazumdar (1994) is 

insensitive to many types of bias to which the test of Egger et al. (1997) is sensitive. As suggested 

by Sterne, Gavaghan, and Egger (2000), in cases where the number of studies in the meta-analysis 

is small, the Begg and Mazumdar (1994) method has very low power to detect bias. Given the 

number of studies available for several of the livability factors in this meta-analysis, the Egger et 

al. (1997) test for publication bias was used. 

 

3.3 Descriptive results 

Table 2 below reports the descriptive count of the studies meeting the criteria of inclusion in the 

meta-analysis. The total count of observation is 560 with 164 unique studies identified. This 

indicates that on average each study contributed about 3.4 observations. In the meta-analysis, 

each country or geographical area that is uniquely identified is considered an observation. This 

is not to say that each unique study provides information on a single geographical entity; in fact, 

many of the uniquely identified studies may offer generalizable information. Unique studies may 

also offer multiple components or factors that are independently assessed. 

 

Table 2: Study count 

Number of Observations 560 

Number of Unique Studies 164 

 

Table 3 below reports the tests for validity based on publication bias using Egger et al. (1997). 

Using p-values, the results indicate the presence of potential publication bias for one of the 

components, GDP per capita, at the conventional p = 0.05 level. This analysis is presented to assist 

in formulating overall inferences for each of the livability factors presented above. 

  



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Table 3: Publication Bias Test using Egger et al. (1997) 

 

Publication 

Bias (p-value) 

Living standard 

 Current living standards 

GDP per capita (PPP adjusted, real, and logged) p = 0.03 

Are you satisfied or dissatisfied with your standard of living, all the 

things you can buy or do? p = 0.10 

Improvement in living standards  

5-year growth rate of GDP per capita p = 0.89 

Right now, do you feel your economic situation is getting better or 

getting worse? p = 0.28 

Freedom  

Political rights p = 0.21 

Civil liberties p = 0.35 

Economic freedom  p = 0.19 

Overall perception of freedom: Are you satisfied or dissatisfied with 

your freedom to choose what to do with your life?  p = 0.99 

Health and environment  

Physical health  

Life expectancy at birth  p = 0.33 

Infant mortality rate p = 0.07 

Mental and emotional health  

Suicide rate p = 0.21 

Environmental health  

Air quality p = 0.67 

Community and relationships  

Community life  

Religious engagement p = 0.75 

Family life  

Are you married? p = 0.10 

Peace, stability and security  

Political and ethnic violence  

Violence and ethnic warfare p = 0.09 

Human rights violations p = 0.33 

Trust in national institutions  p = 0.89 

Corruption in business and government  

Control of corruption p = 0.42 

World indexes: Corruption index p = 0.58 

Bureaucratic quality p = 0.23 

Opportunity  

Unemployment p = 0.80 

 

The concern in Table 3 above is the component GDP per capita, which is one of the underlying 

components of the factor of livability, ‘Living standard’. GDP per capita has 50 studies associated 

with it, as offered in Figure 2 below. The visual assessment of these 50 studies identifies an 

asymmetric outcome. The asymmetry indicates strong evidence that studies with a one-sided 



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www.internationaljournalofwellbeing.org 55 

significance test are suppressed and those with a two-sided significance test are not. This adds 

further credence to the possibility that the asymmetry observed in the contour plot offered in 

Figure 2 below is caused by publication bias. 

 

Figure 2: Contour funnel plot for GDP per capita 

 

4. Meta-analysis results 

Based on this study’s theoretical discussion, there are three effect sizes offered in these meta-

analyses. The first effect size, WB, is a measure of the correlation with wellbeing ignoring 

differences associated with affective wellbeing represented by happiness (AWB) and evaluative 

wellbeing represented by life satisfaction (EWB). The second measure of correlation uses affective 

wellbeing (AWB) alone. As discussed, AWB is closely related to an immediate state of wellbeing 

that is reflected in one’s current emotional state. The data show that 132 of the 560 observations 

can be considered AWB studies. The third effect size offered in the meta-analysis is articulated as 

evaluative wellbeing (EWB). EWB is advanced as a cognitive, reflective state where individuals 

evaluate their wellbeing over longer periods of time. In the data, 428 observations are categorized 

as EWB. In addition to the three effect sizes, the 95% confidence intervals (CI) and the observation 

counts are reported. Appendix A provides a listing of all the studies associated with the meta-

analyses. 

 

4.1 Living standard 

The analysis for the first factor of livability, ‘Living standard’, is presented in Table 4. From a 

wellbeing perspective, several components underlie ‘Living standard’ in the literature. Two of 

these are Current living standard and Improvement in living standard. Within Current living 

0

5

10

15

20

25

S
ta

n
d

a
rd

 e
rr

o
r

-100 -50 0 50 100
Effect estimate

GDP Per Capita

p < 1%

1% < p < 5%

5% < p < 10%

p > 10%

 
0 

5 

10 

15 

20 

25 

S
ta

n
d

a
rd

 e
rr

o
r 

  -100 -50 0                                 50      100 

Effect estimate 

GDP Per Capita 

P < 1% 

1% < p < 5% 

5% < p < 10% 

P > 10% 

 



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standard, an objective measure and two subjective measures are offered in the literature. The 

objective measure, GDP per capita, has 50 observations in the prior literature. Measures of GDP 

per capita include adjusted and real; for example, Samanni and Holmberg (2010) and Fahey and 

Smyth (2004), respectively. The effect size for all 50 observations is a correlation of 0.53 with 

wellbeing and is statistically significant with a CI lower limit of 0.47 and an upper limit of 0.58. 

When considering AWB and EWB, the correlation is stronger with EWB and the CI is narrower, 

providing some evidence that the effect of income and wealth is stronger when the individual 

considers his or her life satisfaction (wellbeing over time) than it is for happiness (one’s emotional 

state), a result supporting Kahneman and Deaton (2010). For Current living standard, the prior 

literature has measured only the subjective question, “Are you satisfied or dissatisfied with your 

standard of living, all the things you can buy or do?” as a component. Examples in the prior 

literature include Andrews and Withey (1976) and Headey, Veenhoven, and Wearing (1991). 

Sixty-four observations are found for this subjective component with a mean correlation of 0.34, 

a weaker correlation than found for the objective measure, GDP per capita. The results indicate 

that EWB has a stronger correlation than is found with AWB, with EWB having a narrower CI. 

 

Table 4: Livability Factor—Living standard 

 
Average Effect Size 

(correlation) 
95% Confidence Interval 

Number of 

Observations 

 WB AWB EWB WB AWB EWB WB AWB EWB 

Current living standards 

GDP per 

capita (PPP 

adjusted, real, 

and logged) 

0.53 0.39 0.58 0.47, 0.58 0.28, 0.48 0.51, 0.64 50 14 36 

Are you 

satisfied or 

dissatisfied 

with your 

standard of 

living, all the 

things you can 

buy or do?  

0.34 0.24 0.37 0.31, 0.36 0.17, 0.30 0.33, 0.40 64 16 48 

Improvement in living standards 

5-year growth 

rate of GDP 

per capita. 

0.03 -0.14 0.09 -0.04, 0.10 -0.26, -0.0 0.02, 0.16 41 10 31 

Right 

now, do you 

feel your 

economic 

situation is 

getting better 

or getting 

worse?  

0.09 0.17 0.00 0.01, 0.17 0.09, 0.24 -0.09, 0.10 8 4 4 

 

Within Improvement in living standard, an objective measure and two subjective measures are 

offered. The objective measure, 5-year growth rate of GDP per capita, which is the chosen proxy 

for Improvement in living standard, contains 41 observations in the prior literature. Statistical 



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significance is found for both AWB and EWB, although the correlations are in opposite directions. 

For AWB the 5-year growth rate is negatively associated with immediate happiness, which is 

quite possible given that the 5-year growth rate is measuring a reflective aspect of wellbeing. The 

finding, however, may support Graham’s (2010) thesis of short-run “unhappy growth.” The 

same observation holds true for the positive correlation between EWB and the 5-year growth rate, 

which signals that the reflective measure is positively correlated with the reflective measure of 

wellbeing. The effect size for wellbeing is a statistically insignificant correlation of 0.03. This is 

most likely due to the reflective nature of the 5-year growth rate in which AWB and EWB are 

pulling the wellbeing outcome in different directions. For Improvement in living standard, the prior 

literature has measured only the subjective question, “Right now, do you feel your economic 

situation is getting better or getting worse?” as a component. Eight observations are found for 

this subjective component with a mean correlation of 0.09, a stronger correlation than found with 

the 5-year growth rate of GDP per capita. The results indicate that AWB has a stronger correlation 

than is found with EWB, with EWB found to be statistically insignificant. The result is to be 

expected as the variable addresses people’s personal changes in income. 

 

4.2 Freedom 

The analysis for the livability factor, ‘Freedom’, is presented in Table 5. Four components are 

identified and used in the prior literature. Within ‘Freedom’, Political rights is offered in the prior 

literature. The effect size for all 28 observations for Political rights is a correlation of 0.16 with 

wellbeing. This correlation is statistically significant with a CI lower limit of 0.08 and an upper 

limit of 0.24. When considering AWB and EWB, the correlation is weaker with EWB, providing 

some evidence that Political rights is stronger when individual wellbeing is considered as 

happiness. 

 

Table 5: Livability Factor—Freedom 

 

Average Effect Size 

(correlation) 
95% Confidence Interval 

Number of 

Observations 

 WB AWB EWB WB AWB EWB WB AWB EWB 

Political rights 0.16 0.22 0.14 0.08, 0.24 0.08, 0.34 0.05, 0.24 28 6 22 

Civil liberties 0.23 0.28 0.22 0.14, 0.32 0.11, 0.43 0.11,0.31 23 6 17 

Economic 

freedom  
0.35 0.35 0.35 0.26, 0.42 0.16, 0.52 0.24, 0.43 28 4 24 

Overall 

perception of 

freedom: Are you 

satisfied or 

dissatisfied with 

your freedom to 

choose what to do 

with your life? 

0.24 0.19 0.28 0.18, 0.28 0.14, 0.24 0.20, 0.35 21 10 11 

 

The next component of ‘Freedom’ is Civil liberties. Twenty-three observations are found for Civil 

liberties with a mean correlation of 0.23. The results indicate that EWB has a weaker correlation 

than is found with AWB based on magnitude, although EWB has a narrower CI. The component 

Economic freedom has an average correlation with wellbeing of 0.35. The correlation is consistent 

across both AWB and EWB, with EWB and wellbeing reflecting similar CIs. The final component 



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of ‘Freedom’ that is observed in the prior literature is Overall perception of freedom. The average 

correlation for Overall perception of freedom is 0.24 with EWB showing the strongest correlation. In 

the literature, limitations exist on the correlation between wellbeing and religious freedom due 

to a lack of longitudinal data on religious freedom. 

 

4.3 Health and environment 

Three components are identified as underlying the third livability factor, ‘Health and 

environment’. Beginning with Physical health, two sub-components are present in the extant 

literature. Life expectancy at birth, in Table 6, shows a statistically significant average correlation 

of 0.11 with wellbeing. The strongest correlation for Life expectancy at birth is found with AWB, 

with an average correlation of 0.27. The reported correlation for Infant mortality rate is -0.14, 

indicating that as infant mortality increases wellbeing decreases. All studies found in the extant 

literature using the criteria offer only EWB when estimating the effect of wellbeing and infant 

mortality. Studies measuring the relationship between overall Mental and emotional health in a 

society and its overall wellbeing are sparse in the existing literature. The empirical findings focus 

on Suicide rate. This component has the fewest studies meeting the inclusion criteria of all the 

components found in the literature reviewed for this meta-analysis. The negative correlation of 

0.14 is bolstered by a single study associated with EWB that shows a correlation of -0.25. If that 

study is ignored, as shown in the AWB column, the resulting correlation of Suicide rate with 

wellbeing is statistically insignificant. The final component underlying the livability factor 

‘Health and environment’ is Environmental health. Of the three sub-components of health 

identified in academic works, only one sub-component, Air quality, is measured in the extant 

literature. Although the correlation for this sub-component is -0.03, the outcome is a statistically 

insignificant correlation. 

 

Table 6: Livability Factor—Health and environment 

 

Average Effect Size 

(correlation) 
95% Confidence Interval 

Number of 

Observations 

 WB AWB EWB WB AWB EWB WB AWB EWB 

Physical health 

Life 

expectancy    

at birth  

0.11 0.27 -0.02 -0.07, 0.16 0.012, .041 0.01, 0.04 15 5 10 

Infant 

mortality rate 
-0.14  -0.14 -0.24, -0.02  -0.24, -0.02  06 0 06 

Mental and emotional health 

Suicide rate -0.14 -0.11 -0.25 -0.04, -0.23 00.00, -0.22  05 4 01 

Environmental health 

Air quality -0.03  -0.03 -0.15, 0.09  -0.15, 0.09 06 0 06 

 

4.4 Community and relationships 

The analysis for the fourth livability factor, ‘Community and relationships’, is presented in Table 

7. In academic works two major components are identified that relate to ‘Community and 

relationships’, Community life and Family life. Table 7 presents both components, noting that 

Community life contains Religious engagement only. Unfortunately, longitudinal data does not 

exist for secular community engagement in the literature used in the meta-analysis. Religious 

engagement is significantly positively correlated with wellbeing for EWB. The effect size of 



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Religious engagement is insignificant for the AWB studies. Given the relatively small number of 

observations from AWB studies, the statistically significant correlation for wellbeing results is 

dominated by the EWB studies overall. The component Family life has one sub-component, Are 

you Married?, which meets the criteria for this study. Are you Married? is positively correlated 

with all the wellbeing measures, with a correlation of about 0.06 (WB) and a CI lower limit of 

0.03 and an upper limit of 0.08. 

 

Table 7: Livability Factor—Community and relationships 

 

Average Effect Size 

(correlation) 95% Confidence Interval 

Number of 

Observations 

 WB AWB EWB WB AWB EWB WB AWB EWB 

Community Life 

Religious 

Engagement 
0.07 -0.02 0.07 0.03, 0.11 -0.08, 0.04 0.03, 0.12 87 6 81 

Family Life 

Are you                        

Married? 
0.06 0.07 0.05 0.03, 0.08 0.05, 0.10 0.02, 0.08 73 21 52 

 

4.5 Peace, stability, and security 

The analysis for the livability factor ‘Peace, stability, and security’ is presented in Table 8. The 

major components observed in the literature that underlie ‘Peace, stability, and security’ are 

identified as Political and ethnic violence, Human rights violations, Law and order, Trust in national 

institutions, Corruption in business and government, and Bureaucratic quality. The results for Political 

and ethnic violence indicate that wellbeing is negatively correlated with Political and ethnic violence 

for AWB, a correlation of -0.28, showing that in the immediacy associated with AWB increases in 

Political and ethnic violence reduce wellbeing. The correlation with wellbeing is not statistically 

significant with either WB or EWB. The Human rights violations component shows a positive 

correlation of -0.20 with wellbeing. When considering AWB and EWB, the correlation is stronger 

with AWB, providing some evidence that Human rights violations is stronger when the individual 

considers his or her immediate wellbeing. The next component is Trust in national institutions. No 

statistically significant correlation is found for Trust in national institutions and wellbeing. 

Corruption in Business and Government is composed of two sub-components, both of which have 

been used in prior studies that meet the inclusion criteria. The sub-component Control of 

corruption is positively correlated with all three measures of wellbeing. A correlation of 0.40 is 

associated with wellbeing, which is similar to both the AWB and EWB correlations. AWB has the 

strongest correlation with Control of corruption at an average of 0.47. The Corruption index 

shows a negative correlation with wellbeing as measured in the WB and AWB measurements. 

The Corruption index is statistically correlated with the EWB measure of wellbeing. The results 

for Bureaucratic quality, or efficiency, indicate a positive correlation across all measures of 

wellbeing. 

  



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Table 8: Livability Factor—Peace, stability, and security 

 
Correlation 95% Confidence Interval 

Number of 

Observations 

 WB AWB EWB WB AWB EWB WB AWB EWB 

Political and 

Ethnic 

Violence 

0.14 -0.28 0.27 -0.16, 0.41 -0.43, -0.13 -0.02, 0.52 08 02 06 

Human rights 

violations 
-0.20 -0.33 -0.13 -0.11, -0.29 -0.19, -0.45 -0.03, -0.24 27 10 17 

Trust in 

national 

institutions  

0.10 0.02 0.12 -0.01, 0.20 -0.07, 0.12 -0.01, 0.24 09 02 07 

Corruption in business and government       

Control of 

corruption 
0.40 0.47 0.39 0.30, 0.50 0.01, 0.76 0.29, 0.48 11 02 09 

Corruption 

index 
-0.27 -0.54 -0.14 -0.47, -0.05 -0.71, -0.30 -0.37, 0.10 10 03 07 

Bureaucratic 

quality 
0.37 0.40 0.37 0.29, 0.45 0.14, 0.62 0.28, 0.44 19 04 15 

 

4.6 Opportunity 

The analysis for the final livability factor, ‘Opportunity’, is presented in Table 9. In the literature, 

there are at least four components that underlie ‘Opportunity’. These are entrepreneurship, 

community basics, education, and employment. Although the literature has four major 

components for ‘Opportunity’, the inclusion criteria limit the analysis to Employment. Table 9 

presents the results for Employment. The objective measure, Unemployment, has 21 observations 

assessed from the prior literature. The effect size for all 21 observations is a correlation of 0.04 

with wellbeing and is statistically insignificant, with a CI lower limit of -0.04 and an upper limit 

of 0.11. When considering AWB and EWB, the correlation is statistically insignificant with EWB, 

but it is statistically significant for AWB with a correlation of 0.19; thereby leading to an 

assessment that individuals consider their immediate wellbeing when considering employment. 

This finding may seem surprising, but the outcome is intuitive if we consider that unemployment 

is a temporary individual effect that can change in a very short period of time. 

 

Table 9: Livability Factor—Opportunity 

 

Average Effect Size 

(correlation) 
95% Confidence Interval 

Number of 

Observations 

 WB AWB EWB WB AWB EWB WB AWB EWB 

Employment 

Unemployment 0.04 0.19 0.01 -0.04, 0.11 0.01, 0.35 -0.06, 0.09 21 3 18 

 

5. Conclusion 

This study has investigated, through a meta-analysis, the livability factors and associated 

components identified in the literature as contributors to wellbeing. Using the theoretical 

background associated with wellbeing, two constructs observed in the literature underpin 

wellbeing: happiness and life satisfaction. Using the meta-analysis, the findings support the 

underlying constructs associated with wellbeing—happiness, which is identified as AWB in the 



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analysis; and EWB, the identifier for life satisfaction. The meta-analysis of the prior empirical 

literature shows that the two constructs differ in regard to the magnitude and statistical 

significance of their correlations as they relate to wellbeing, supporting the hypothesized 

continuum derived through the synthesis of the theoretical literature. 

The main findings of the analyses are that all six livability factors are present within the prior 

literature, although the frequency with which the components of these factors are used varies. 

The livability factor identified as ‘Living standard’ has strong representation in the empirical 

literature, with dozens of studies using this factor. The results for ‘Living standard’ show that 

the underlying components are all positively related to wellbeing, with variability in magnitude 

found with both AWB and EWB. The results for ‘Living standard’ are indicative of those found 

with the livability factors ‘Freedom’ and ‘Community and relationships,’ although ‘Freedom’ has 

correlation coefficients approximately 50% smaller than those found with ‘Living standard’. 

Correlations of ‘Community and relationships’ are approximately 50% smaller than those found 

with ‘Freedom’. The implication for these three livability factors is that all three are important 

when investigating the implications of wellbeing, but that the magnitudes of the impacts are 

different. 

For the other three livability factors, ‘Health and environment,’ ‘Peace, stability, and 

security,’ and ‘Opportunity,’ the results show that these three factors are correlated with 

wellbeing although their representation in the literature is substantially lower than that the other 

three livability factors. One reason may be the difficulty in measuring these livability factors, in 

addition to the possibility that these factors have become of interest rather recently within the 

literature. The importance of these livability factors is quite apparent, with many of the 

correlations with wellbeing at around a modest magnitude of 0.15. This leads to the conclusion 

that ignoring these three livability factors might produce erroneous assumptions about 

wellbeing—in particular, about each underlying construct of wellbeing, happiness, and life 

satisfaction. 

This meta-analysis is used to answer questions not posed by the individual studies. The 

selection of studies based on the criteria laid down for this meta-analysis is focused on providing 

estimates that may help improve or settle controversies arising from apparently conflicting 

studies regarding the factors of wellbeing. Statistical analysis of findings allows the degree of 

conflict to be formally assessed and reasons for different results to be explored and quantified as 

social science assessments of wellbeing advance in the literature. The meta-analysis has also 

discovered the need for further studies of wellbeing that include multiple dimensions of 

wellbeing simultaneously in order to capture indirect relationships, spurious effects, and other 

matters of interest. 

The empirical value of this meta-analysis is to increase statistical power and improve 

precision, since significance level and the estimation of effect-size can be improved when they 

are based on more information. Some of the components have a small number of prior studies 

associated with them, which directly impacts the value of the meta-analysis for those variables. 

The results for some of the components and sub-components in small studies should encourage 

researchers to continue to explore the influence of these components and sub-components on 

wellbeing. 

This study explores the effects of all the research found to date regarding AWB, EWB, and 

wellbeing. The promise of enhancing our understanding of the role of wellbeing in the world 

encourages future research, as wellbeing and its underlying constructs continue to provide 

important information to policy-makers throughout the world. 

 



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Acknowledgments 

This research was sponsored by a grant from the Charles Koch Institute. 

 

Authors 

Robert J. Eger 

Naval Postgraduate School 

rjeger@nps.edu 

 

J. Haavard Maridal 

Baylor University 

 

Publishing Timeline 

Received 11 August 2014 

Accepted 27 March 2015  

Published 21 June 2015  

 

References 

Andrews, F. M., & Withey, S. B. (1976). Social indicators of well-being: Americans' perceptions of life quality. 

New York: Plenum Press. http://dx.doi.org/10.1007/978-1-4684-2253-5 

Arneson, R. J. (1999). Human flourishing versus desire satisfaction. Social Philosophy and Policy, 16(01), 

113–142. http://dx.doi.org/10.1017/S0265052500002272 

Bee, H. L., & Bjorklund, B. R. (2000). The journey of adulthood (4th ed.). Upper Saddle River, NJ: Prentice 

Hall. 

Begg, C. B., & Mazumdar, M. (1994). Operating characteristics of a rank correlation test for publication 

bias. Biometrics, 50(4), 1088–1101. http://dx.doi.org/10.2307/2533446 

Bentham, J. (1789). An introduction to the principles of morals and legislation. Oxford: Clarendon Press. 

Biswas-Diener, R., & Patterson, L. (2011). Positive psychology and poverty. In R. Biswas-Diener (Ed.), 

Positive psychology as social change (125–140). Dordrecht, The Netherlands: Springer. 

Blakeslee, T. R., & Grossarth-Maticek, R. (1996). Feelings of pleasure and well-being as predictors of 

health status 21 years later. http://www.attitudefactor.com/PWItecharticle.htm  

Bradburn, N. M. & Noll, C. E. (1969). The structure of psychological well-being. Chicago: Aldine Pub. Co. 

Brooks, A. C. (2008a). Free people are happy people—Especially when strong personal morality guides 

their choices. City Journal 18(2), 31. 

Brooks, A. C. (2008b). Gross national happiness: Why happiness matters for America—And how we can get more 

of it. New York: Basic Books. 

Campbell, A., Converse, P. E., & Rodgers, W. L. (1976). The quality of American life: Perceptions, evaluations, 

and satisfactions. New York: Russell Sage Foundation. 

Cantril, H. M. (1965). Pattern of human concerns. New Brunswick, NJ: Rutgers University Press. 

Cooper, H. M. (1998). Synthesizing research: A guide for literature reviews (Applied Social Research 

Methods, Vol. 2). Thousand Oaks, CA: Sage Publications. 

Diener, E., Diener, M., & Diener, C. (1995). Factors predicting the subjective well-being of nations. Journal 

of Personality and Social Psychology, 69(5), 851–864. http://dx.doi.org/10.1037/0022-3514.69.5.851 

Diener, E., Gohm, C. L., Suh, E., & Oishi, S. (2000). Similarity of the relations between marital status and 

subjective well-being across cultures. Journal of Cross-cultural Psychology, 31(4), 419–436. 

http://dx.doi.org/10.1177/0022022100031004001 

Diener, E., Inglehart, R., & Tay, L. (2013). Theory and validity of life satisfaction measures. Social 

Indicators Research, 112(3), 497–527. http://dx.doi.org/10.1007/s11205-012-0076-y 

Diener, E., Kahneman, D., Tov, W., & Arora, R. (2010). Income’s association with judgments of life versus 

feelings. In E. Diener, D. Kahneman, & J. F. Helliwell (Eds.), International differences in well-being (3–

15). Oxford, United Kingdom: Oxford University Press. 

mailto:rjeger@nps.edu
http://dx.doi.org/10.1007/978-1-4684-2253-5
http://dx.doi.org/10.1017/S0265052500002272
http://dx.doi.org/10.2307/2533446
http://www.attitudefactor.com/PWItecharticle.htm
http://dx.doi.org/10.1037/0022-3514.69.5.851
http://dx.doi.org/10.1177/0022022100031004001
http://dx.doi.org/10.1007/s11205-012-0076-y


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 63 

Diener, E., & Suh, E. (1997). Measuring quality of life: Economic, social, and subjective indicators. Social 

Indicators Research, 40(1–2), 189–216. http://dx.doi.org/10.1023/A:1006859511756 

Dolan, P., & White, M. P. (2007). How can measures of subjective well-being be used to inform public 

policy? Perspectives on Psychological Science, 2(1), 71–85. http://dx.doi.org/10.1111/j.1745-

6916.2007.00030.x 

Drummond, N. (2000). Quality of life with asthma: The existential and the aesthetic. Sociology of Health & 

Illness, 22(2), 235–253. http://dx.doi.org/10.1111/1467-9566.00201 

Dunn, E. W., Aknin, L. B., & Norton, M. I. (2008). Spending money on others promotes happiness. 

Science, 319(5870), 1687–1688. http://dx.doi.org/10.1126/science.1150952 

Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, 

graphical test. BMJ, 315(7109), 6. http://dx.doi.org/10.1136/bmj.315.7109.629 

Ellison, C. G., & Levin, J. S. (1998). The religion-health connection: Evidence, theory, and future 

directions. Health Education & Behavior, 25(6), 700–720. http://dx.doi.org/10.1177/109019819802500603 

Fahey, T., & Smyth, E. (2004). The link between subjective well-being and objective conditions in 

European societies. In W. A. Arts, & L. Halman (Eds.), European values at the turn of the millennium 

(Vol. 7), 57–80. Leiden, The Netherlands: Koninklijke Brill NV. 

Field, A. (2005). Discovering statistics using SPSS (2nd ed.). London: Sage. 

Frankl, V. E. (1963). Man’s search for meaning (I. Lasch, Trans.). (Original work published 1946). New 

York: Pocketbooks.  

Frey, B. S., & Stutzer, A. (2000). Happiness, economy and institutions. The Economic Journal, 110(466), 

918–938. http://dx.doi.org/10.1111/1468-0297.00570 

Frisch, M. B. (2013). Ruut Veenhoven: Pioneer on empirical fresearch on happiness. 

http://www2.eur.nl/fsw/research/veenhoven/interviews/AppliedResearchQOL_2013.pdf 

Graham, C. (2008). Happiness and health: Lessons—and questions—for public policy. Health Affairs, 

27(1), 72–87. http://dx.doi.org/10.1377/hlthaff.27.1.72 

Graham, C. (2010). The challenges of incorporating empowerment into the HDI: Some lessons from 

happiness economics and quality of life research. Human Development Reports Research Paper, 

Documento de investigación, 2010/13, 1–54. New York: United Nations Development Programme. 

Gropper, D. M., Lawson, R. A., & Thorne, J. T., Jr. (2011). Economic freedom and happiness. The Cato 

Journal, 31, 237–255.  

Guiso, L., Sapienza, P., & Zingales, L. (2006). Does culture affect economic outcomes? The Journal of 

Economic Perspectives, 20(2), 1–48. http://dx.doi.org/10.1257/jep.20.2.23 

Gundelach, P., & Kreiner, S. (2004). Happiness and life satisfaction in advanced European countries. 

Cross-Cultural Research: Official journal of the Society for Cross-Cultural Research, Sponsored by the Human 

Relations Area Files, Inc, 38(4), 359. http://dx.doi.org/10.1177/1069397104267483 

Headey, B., Veenhoven, R., & Wearing, A. (1991). Top-down versus bottom-up theories of subjective 

well-being. Social Indicators Research, 24(1), 81–100. http://dx.doi.org/10.1007/BF00292652 

Hedges, L. V., & Vevea, J. L. (1998). Fixed- and random-effects models in meta-analysis. Psychological 

Methods, 3(4), 486–504. http://dx.doi.org/10.1037/1082-989X.3.4.486 

Helliwell, J. F. (2008). Life satisfaction and quality of development (Working paper 14507). Cambridge, MA: 

National Bureau of Economic Research. http://dx.doi.org/10.3386/w14507 

Helliwell, J. F., Barrington-Leigh, C. P., Harris, A., & Huang, H. (2009). International evidence on the social 

context of well-being (Working paper 14720). Cambridge, MA: National Bureau of Economic Research. 

http://dx.doi.org/10.3386/w14720 

Helliwell, J. F., & Putnam, R. D. (2004). The social context of well-being. Philosophical Transactions of the 

Royal Society of London Series B Biological Sciences, 359(1449), 1435–1446. 

http://dx.doi.org/10.1098/rstb.2004.1522 

Heylighen, F. (1999). Happiness. In F. Heylighen, C. Joslyn & V. Turchin (Eds.) Principia Cybernetica Web. 

Brussels, Belgium. 

Hunter, J. E., & Schmidt, F. L. (2000). Fixed effects vs. random effects meta-analysis models: Implications 

for cumulative research knowledge. International Journal of Selection and Assessment, 8(4), 275–292. 

http://dx.doi.org/10.1111/1468-2389.00156 

http://dx.doi.org/10.1023/A:1006859511756
http://dx.doi.org/10.1111/j.1745-6916.2007.00030.x
http://dx.doi.org/10.1111/j.1745-6916.2007.00030.x
http://dx.doi.org/10.1111/1467-9566.00201
http://dx.doi.org/10.1126/science.1150952
http://dx.doi.org/10.1136/bmj.315.7109.629
http://dx.doi.org/10.1177/109019819802500603
http://dx.doi.org/10.1111/1468-0297.00570
http://www2.eur.nl/fsw/research/veenhoven/interviews/AppliedResearchQOL_2013.pdf
http://dx.doi.org/10.1377/hlthaff.27.1.72
http://dx.doi.org/10.1257/jep.20.2.23
http://dx.doi.org/10.1177/1069397104267483
http://dx.doi.org/10.1007/BF00292652
http://dx.doi.org/10.1037/1082-989X.3.4.486
http://dx.doi.org/10.3386/w14507
http://dx.doi.org/10.3386/w14720
http://dx.doi.org/10.1098/rstb.2004.1522
http://dx.doi.org/10.1111/1468-2389.00156


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 64 

Inglehart, R. (1990). Culture shift in advanced industrial society. European Sociological Review, 8(1), 95–98.  

Inglehart, R. (2010). Faith and freedom: Traditional and modern ways to happiness. In E. Diener, D. 

Kahneman & J. F. Helliwell (Eds.), International differences in well-being (351–397). New York: Oxford 

University Press. 

Inglehart, R., & Klingemann, H.-D. (2000). Genes, culture, democracy, and happiness. In E. Diener & E. 

M. Suh (Eds.), Culture and subjective well-being (165–183). Cambridge, MA: MIT Press. 

Joung, I. M. (1997). The relationship between marital status and health. Nederlands tijdschrift voor 

geneeskunde, 141(6), 277–282.  

Kahneman, D. (1999). Objective happiness. In D. Kahneman, E. Diener & N. Schwarz (Eds.), Well-being: 

Foundations of hedonic psychology (3–25). New York: Russell Sage Foundation Press. 

Kahneman, D., & Deaton, A. (2010). High income improves evaluation of life but not emotional well-

being. Proceedings of the National Academy of Sciences, 107(38), 16489–16493. 

http://dx.doi.org/10.1073/pnas.1011492107 

Kahneman, D., & Krueger, A. B. (2006). Developments in the measurement of subjective well-being. 

Journal of Economic Perspectives, 20(1), 3–24. http://dx.doi.org/10.1257/089533006776526030 

Katsaiti, M.-S. (2012). Obesity and happiness. Applied Economics, 44(31/33), 4101–4114. 

http://dx.doi.org/10.1080/00036846.2011.587779 

Kushner, R. F., & Foster, G. D. (2000). Obesity and quality of life. Nutrition, 16(10), 947–952. 

http://dx.doi.org/10.1016/S0899-9007(00)00404-4 

Lane, R. E. (2000). The loss of happiness in market democracies. New Haven, CT: Yale University Press. 

Lim, C., & Putnam, R. D. (2010). Religion, social networks, and life satisfaction. American Sociological 

Review, 75(6), 914–933. http://dx.doi.org/10.1177/0003122410386686 

Lucas, R. E., Diener, E., & Suh, E. (1996). Discriminant validity of well-being measures. Journal of 

Personality and Social Psychology, 71(3), 616–628. http://dx.doi.org/10.1037/0022-3514.71.3.616 

Lykken, D. T. (1999). Happiness: What studies on twins show us about nature, nurture, and the happiness set-

point. New York: Golden Books. 

Marshall, R. D., Olfson, M., Hellman, F., Blanco, C., Guardino, M., & Struening, E. L. (2001). 

Comorbidity, impairment, and suicidality in subthreshold PTSD. The American Journal of Psychiatry, 

158(9), 1467–1473. http://dx.doi.org/10.1176/appi.ajp.158.9.1467 

Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370–396. 

http://dx.doi.org/10.1037/h0054346 

Mastekaasa, A. (1992). Marriage and psychological well-being: Some evidence on selection into marriage. 

Journal of Marriage and Family, 54(4), 901–911. http://dx.doi.org/10.2307/353171 

McMahon, D. M. (2006). Happiness : A history (1st ed.). New York: Atlantic Monthly Press. 

Meulemann, H. (2001). Life satisfaction from late adolescence to mid-life: the impact of life success and 

success evaluation on the life satisfaction of former gymnasium students between ages 30 and 43. 

Journal of Happiness Studies, 2(4), 445–465. http://dx.doi.org/10.1023/A:1013990011655 

Murray, C. A. (1988). In pursuit: Of happiness and good government. New York: Simon and Schuster. 

Murray, D. M., McKinlay, S. M., Martin, D., Donner, A. P., Dwyer, J. H., Raudenbush, S. W., & Graubard, 

B. I. (1994). Design and Analysis Issues in Community Trials. Evaluation Review, 18(4), 493-514. 

http://dx.doi.org/10.1177/0193841X9401800407 

Office for National Statistics. (2014). Statistical bulletin: Personal well-being in the UK, 2013/14. 

http://www.ons.gov.uk/ons/rel/wellbeing/measuring-national-well-being/personal-well-being-in-

the-uk--2013-14/sb-personal-well-being-in-the-uk--2013-14.html 

Oishi, S. (2012). The psychological wealth of nations: Do happy people make a happy society? Chichester, 

England: Wiley-Blackwell. http://dx.doi.org/10.1002/9781444354447 

Oishi, S., Kesebir, S., & Diener, E. (2011). Income inequality and happiness. Psychological Science, 22(9), 

1095–1100. http://dx.doi.org/10.1177/0956797611417262 

Oishi, S., & Roth, D. P. (2009). The role of self-reports in culture and personality research: It is too early to 

give up on self-reports. Journal of Research in Personality, 43(1), 107–109. 

http://dx.doi.org/10.1016/j.jrp.2008.11.002 

http://dx.doi.org/10.1073/pnas.1011492107
http://dx.doi.org/10.1257/089533006776526030
http://dx.doi.org/10.1080/00036846.2011.587779
http://dx.doi.org/10.1016/S0899-9007%2800%2900404-4
http://dx.doi.org/10.1177/0003122410386686
http://dx.doi.org/10.1037/0022-3514.71.3.616
http://dx.doi.org/10.1176/appi.ajp.158.9.1467
http://dx.doi.org/10.1037/h0054346
http://dx.doi.org/10.2307/353171
http://dx.doi.org/10.1023/A:1013990011655
http://dx.doi.org/10.1177/0193841X9401800407
http://www.ons.gov.uk/ons/rel/wellbeing/measuring-national-well-being/personal-well-being-in-the-uk--2013-14/sb-personal-well-being-in-the-uk--2013-14.html
http://www.ons.gov.uk/ons/rel/wellbeing/measuring-national-well-being/personal-well-being-in-the-uk--2013-14/sb-personal-well-being-in-the-uk--2013-14.html
http://dx.doi.org/10.1002/9781444354447
http://dx.doi.org/10.1177/0956797611417262
http://dx.doi.org/10.1016/j.jrp.2008.11.002


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 65 

Overton, R. C. (1998). A comparison of fixed-effects and mixed (random-effects) models for meta-

analysis tests of moderator variable effects. Psychological Methods, 3(3), 354–379. 

http://dx.doi.org/10.1037/1082-989X.3.3.354  

Parfit, D. (1984). Reasons and persons. Oxford, England: Oxford University Press. 

Plagnol, A. C., & Easterlin, R. A. (2008). Aspirations, attainments, and satisfaction: Life cycle differences 

between American women and men. Journal of Happiness Studies, 9(4), 601–619. 

http://dx.doi.org/10.1007/s10902-008-9106-5 

Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. New York: Simon & 

Schuster. http://dx.doi.org/10.1145/358916.361990 

Rackham, H. (1934). Aristotle in 23 Volumes, Vol. 19, translated by H. Rackham. Cambridge, MA: Harvard 

University Press; London: William Heinemann Ltd. 

Rothstein, H. R., Sutton, A. J., & Borenstein, M. (2005). Publication bias in Meta-Analysis. In H.R. 

Rothstein, A.J. Sutton, & M. Borenstein (Eds.), Publication bias in Meta-Analysis- Prevention, assessment 

and adjustments (2-3). West Sussex, England: John Wiley & Sons, Ltd. 

http://dx.doi.org/10.1002/0470870168 

Samanni, M., & Holmberg, S. (2010). Quality of government makes people happy. QoG Working Paper 

Series, 1–36. The QOG Institute: University of Gothenburg. 

Scanlon, T. (1993). Value, desire, and quality of life. In M. Nussbaum & A. Sen (Eds.), The quality of life 

(185–200). Oxford, United Kingdom: Clarendon Press/Oxford University Press. 

Schmidt, F. L., Oh, I.-S., & Hayes, T. L. (2009). Fixed-versus random-effects models in meta-analysis: 

Model properties and an empirical comparison of differences in results. British Journal of Mathematical 

& Statistical Psychology, 62(1), 97–128. http://dx.doi.org/10.1348/000711007X255327 

Seligman, M. E. P. (2002a). Authentic happiness: Using the new positive psychology to realize your potential for 

lasting fulfillment. New York: The Free Press. 

Seligman, M. E. P. (2002b). Positive psychology, positive prevention, and positive therapy. In C. R. 

Snyder & S. J. Lopez (Eds.), Handbook of positive psychology, 2, 3–12. New York: Oxford University 

Press. 

Sen, A. K. (1999). Commodities and capabilities. Delhi; New York: Oxford University Press. 

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for 

generalized causal inference. Boston, MA: Wadsworth Cengage Learning. 

Sterne, J. A., Gavaghan, D., & Egger, M. (2000). Publication and related bias in meta-analysis: Power of 

statistical tests and prevalence in the literature. Journal of Clinical Epidemiology, 53(11), 1119–1129. 

http://dx.doi.org/10.1016/S0895-4356(00)00242-0 

Stolle, D. (1998). Bowling together, bowling alone: The development of generalized trust in voluntary 

associations. Political Psychology, 19(3), 497–525.  

Sumner, L. W. (2003). Welfare, happiness, and ethics (Reprint. ed.). New York: Oxford University Press. 

Toulmin, S. E. (1961). Foresight and understanding: An inquiry into the aims of science. Bloomington, IN: 

Indiana University Press. 

Triandis, H. C., & Gelfand, M. J. (1998). Converging measurement of horizontal and vertical 

individualism and collectivism. Journal of Personality and Social Psychology, 74(1), 118–128. 

http://dx.doi.org/10.1037/0022-3514.74.1.118 

Veenhoven, R. (1996). Developments in satisfaction-research. Social Indicators Research, 37(1), 1–46. 

http://dx.doi.org/10.1007/BF00300268 

Veenhoven, R. (2008). Sociological theories of subjective well-being. In M. Eid & R. J. Larsen (Eds.), The 

science of subjective well-being: A tribute to Ed Diener (44–61). New York: The Guilford Press. 

Veenhoven, R. (2012). Evidence based pursuit of happiness: What should we know, do we know and can we get to 

know?(MRPA paper 41924). Rotterdam, The Netherlands: Erasmus Happiness Economics Research 

Organization. 

Veenhoven, R. (2013). World database of happiness. http://worlddatabaseofhappiness.eur.nl/  

Verme, P. (2007). Happiness and freedom in a world of heterogeneous values. Paper presented at the 

International Conference on Happiness and Public Policy, Bangkok, Thailand. 

http://dx.doi.org/10.1037/1082-989X.3.3.354
http://dx.doi.org/10.1007/s10902-008-9106-5
http://dx.doi.org/10.1145/358916.361990
http://dx.doi.org/10.1002/0470870168
http://dx.doi.org/10.1348/000711007X255327
http://dx.doi.org/10.1016/S0895-4356%2800%2900242-0
http://dx.doi.org/10.1037/0022-3514.74.1.118
http://dx.doi.org/10.1007/BF00300268
http://worlddatabaseofhappiness.eur.nl/


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 66 

Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive 

and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. 

http://dx.doi.org/10.1037/0022-3514.54.6.1063 

Wilson, W. R. (1967). Correlates of avowed happiness. Psychological Bulletin, 67(4), 294–306. 

http://dx.doi.org/10.1037/h0024431 

Winkelmann, L., & Winkelmann, R. (1998). Why are the unemployed so unhappy? Evidence from panel 

data. Economica, 65(257), 1–15. http://dx.doi.org/10.1111/1468-0335.00111 

World Values Survey (1981–2005). World Values Survey. http://www.worldvaluessurvey.org  

Zak, P. J. (2011). Moral markets. Journal of Economic Behavior & Organization, 77(2), 212–233. 

http://dx.doi.org/10.1016/j.jebo.2010.09.004 

  

http://dx.doi.org/10.1037/0022-3514.54.6.1063
http://dx.doi.org/10.1037/h0024431
http://dx.doi.org/10.1111/1468-0335.00111
http://www.worldvaluessurvey.org/
http://dx.doi.org/10.1016/j.jebo.2010.09.004


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 67 

Appendix A 

Abrams, M., Gerard, D., & Timms, N. (Ed.) (1985). Values and social change in Britain. London: Macmillan 

in association with the European Value Systems Study Group. 

Abramson, M., Angers, W., Cherepon, J., Kohut, M., & Lalouch, H. (1981). Pilot analysis of a happiness 

questionnaire. Psychological Reports, 48(2), 570. http://dx.doi.org/10.2466/pr0.1981.48.2.570 

Alesina, A., Di Tella, R., & MacCulloch, R. (2004). Inequality and happiness: Are Europeans and 

Americans different? Journal of Public Economics, 88(9–10), 2009–2042. 

http://dx.doi.org/10.1016/j.jpubeco.2003.07.006 

Allardt, E. (1976). Dimensions of welfare in a comparative Scandinavian study. Acta Sociologica, 19(3), 

227–239. http://dx.doi.org/10.1177/000169937601900302 

Allardt, E. (1981). Experiences from the comparative Scandinavian welfare study, with a bibliography of 

the project. European Journal of Political Research, 9(1), 101–113. http://dx.doi.org/10.1111/j.1475-

6765.1981.tb00591.x 

Andrews, F. M. (1991). Stability and change in levels and structure of subjective well-being: USA 1972 

and 1988. Social Indicators Research, 25(1), 1–30. http://dx.doi.org/10.1007/BF00727649 

Andrews, F. M., & Withey, S. B. (1976). Social indicators of well-being: Americans' perceptions of life quality. 

New York: Plenum Press. http://dx.doi.org/10.1007/978-1-4684-2253-5 

Ball, R., & Chernova, K. (2008). Absolute income, relative income, and happiness. Social Indicators 

Research, 88(3), 497–529. http://dx.doi.org/10.1007/s11205-007-9217-0 

Baltatescu, S. (2011). Subjective well-being and satisfaction with places of residence in the counties at the 

cross-border between Hungary and Romania. Eurolimes (Supplement), 395–403. 

Beja, E., & Yap, D. (2013). Counting happiness from the individual level to the group level. Social 

Indicators Research, 114(2), 621–637. http://dx.doi.org/10.1007/s11205-012-0165-y 

Bergan, A., & McConatha, J. T. (2001). Religiosity and life satisfaction. Activities, Adaptation & Aging, 

24(3), 23–34. http://dx.doi.org/10.1300/J016v24n03_02 

Bergin, A. E. (1983). Religiosity and mental health: A critical reevaluation and meta-analysis. Professional 

Psychology: Research and Practice, 14(2), 170–184. http://dx.doi.org/10.1037/0735-7028.14.2.170 

Bharadwaj, L., & Wilkening, E. A. (1977). The prediction of perceived well-being. Social Indicators 

Research, 4(4), 421–439. http://dx.doi.org/10.1007/BF00353143 

Binder, M. (2013). Innovativeness and subjective well-being. Social Indicators Research, 111(2), 561–578. 

http://dx.doi.org/10.1007/s11205-012-0020-1 

Binder, M., & Ward, F. (2013). The structure of subjective well-being: A vector autoregressive approach. 

Metroeconomica, 64(2), 361–400. http://dx.doi.org/10.1111/meca.12011 

Bjørnskov, C. (2006). The multiple facets of social capital. European Journal of Political Economy, 22(1), 22–

40. http://dx.doi.org/10.1016/j.ejpoleco.2005.05.006 

Bjørnskov, C., Dreher, A., & Fischer, J. A. (2007). Cross-country determinants of life satisfaction: 

Exploring different determinants across groups in society. Social Choice and Welfare, 30(1), 119–173. 

http://dx.doi.org/10.1007/s00355-007-0225-4 

Bjørnskov, C., Dreher, A., & Fischer, J. A. V. (2007). The bigger the better? Evidence of the effect of 

government size on life satisfaction around the world. Public Choice, 130(3/4), 267–292. 

http://dx.doi.org/10.1007/s11127-006-9081-5 

Bjørnskov, C., Dreher, A., & Fischer, J. A. V. (2010). Formal institutions and subjective well-being: 

Revisiting the cross-country evidence. European Journal of Political Economy, 26(4), 419–430. 

http://dx.doi.org/10.1016/j.ejpoleco.2010.03.001 

Bjørnskov, C., Gupta, N., & Pedersen, P. (2008). Analyzing trends in subjective well-being in 15 European 

countries, 1973–2002. Journal of Happiness Studies, 9(2), 317–330. http://dx.doi.org/10.1007/s10902-007-

9055-4 

Böhnke, P. (2008). Does society matter? Life satisfaction in the enlarged Europe. Social Indicators Research, 

87(2), 189–210. http://dx.doi.org/10.1007/s11205-007-9169-4 

Böhnke, P., & Kohler, U. (2010). Well-being and inequality. In S. Immerfall & G. Therborn (Eds.), 

Handbook of European societies (629–666). New York: Springer. 

http://dx.doi.org/10.2466/pr0.1981.48.2.570
http://dx.doi.org/10.1016/j.jpubeco.2003.07.006
http://dx.doi.org/10.1177/000169937601900302
http://dx.doi.org/10.1111/j.1475-6765.1981.tb00591.x
http://dx.doi.org/10.1111/j.1475-6765.1981.tb00591.x
http://dx.doi.org/10.1007/BF00727649
http://dx.doi.org/10.1007/978-1-4684-2253-5
http://dx.doi.org/10.1007/s11205-007-9217-0
http://dx.doi.org/10.1007/s11205-012-0165-y
http://dx.doi.org/10.1300/J016v24n03_02
http://dx.doi.org/10.1037/0735-7028.14.2.170
http://dx.doi.org/10.1007/BF00353143
http://dx.doi.org/10.1007/s11205-012-0020-1
http://dx.doi.org/10.1111/meca.12011
http://dx.doi.org/10.1016/j.ejpoleco.2005.05.006
http://dx.doi.org/10.1007/s00355-007-0225-4
http://dx.doi.org/10.1007/s11127-006-9081-5
http://dx.doi.org/10.1016/j.ejpoleco.2010.03.001
http://dx.doi.org/10.1007/s10902-007-9055-4
http://dx.doi.org/10.1007/s10902-007-9055-4
http://dx.doi.org/10.1007/s11205-007-9169-4


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 68 

Bond, M. H., Lun, V. M. -C., & Li, L. M. W. (2012). Religion and the life satisfaction of young persons 

around the world: Personal values and societal context. In G. Trommsdorff & X. Chen (Eds.), Values, 

religion, and culture in adolescent development (123–145). Cambridge, England: Cambridge University 

Press. 

Bortner, R. W., & Hultsch, D. F. (1970). A multivariate analysis of correlates of life satisfaction in 

adulthood. Journal of Gerontology, 25(1), 41–47. http://dx.doi.org/10.1093/geronj/25.1.41 

Bray, I., & Gunnell, D. (2006). Suicide rates, life satisfaction and happiness as markers for population 

mental health. Social Psychiatry and Psychiatric Epidemiology, 41(5), 333–337. 

http://dx.doi.org/10.1007/s00127-006-0049-z 

Brooks, A. C. (2008). Gross national happiness: Why happiness matters for America—And how we can get more 

of it. New York: Basic Books. 

Bruni, L., & Porta, P. L. (2005). Economics and happiness framing the analysis. Oxford: Oxford University 

Press. http://dx.doi.org/10.1093/0199286280.001.0001 

Bruni, L., & Stanca, L. (2008). Watching alone: Relational goods, television and happiness. Journal of 

Economic Behavior & Organization, 65(3–4), 506–528. http://dx.doi.org/10.1016/j.jebo.2005.12.005 

Buttel, F. H., Wilkening, E. A., & Martinson, O. B. (1977). Ideology and social indicators of the quality of 

life. Social Indicators Research, 4(3), 353–369. http://dx.doi.org/10.1007/BF00353138 

Camfield, L., Guillen-Royo, M., & Velazco, J. (2010). Does needs satisfaction matter for psychological and 

subjective wellbeing in developing countries: A mixed-methods illustration from Bangladesh and 

Thailand. Journal of Happiness Studies, 11(4), 497–516. http://dx.doi.org/10.1007/s10902-009-9154-5 

Campbell, A., Converse, P. E., & Rodgers, W. L. (1976). The quality of American life: Perceptions, evaluations, 

and satisfactions. New York: Russell Sage Foundation. 

Campbell, A., & University of Michigan Institute for Social, R. (1981). The sense of well-being in America: 

Recent patterns and trends. New York: McGraw-Hill. 

Cantril, H. (1965). Pattern of human concerns. New Brunswick, NJ: Rutgers University Press. 

Cantril, H. (1977). The pattern of human concerns (ICPSR ed. ed.). Ann Arbor, MI: Inter-University 

Consortium for Political and Social Research. 

Chang, W.-C. (2009). Religious attendance and subjective well-being in an Eastern-culture country: 

Empirical Evidence from Taiwan. Marburg Journal of Religion, 14(1), 30.  

Cohn, M. A., Fredrickson, B. L., Brown, S. L., Mikels, J. A., & Conway, A. M. (2009). Happiness 

unpacked: Positive emotions increase life satisfaction by building resilience. Emotion, 9(3), 361–368. 

http://dx.doi.org/10.1037/a0015952 

Costa, F. M., Donovan, J. E., & Jessor, R. (1992). Beyond adolescence: Problem behaviour and young adult 

development. Cambridge, England: Cambridge University Press. 

Cummins, R. A., Eckersley, R., Pallant, J., Vugt, J. V., & Misajon, R. (2003). Developing a national index of 

subjective wellbeing: The Australian Unity Wellbeing Index. Social Indicators Research, 64(2), 159–190. 

http://dx.doi.org/10.1023/A:1024704320683 

Deaton, A. (2008). Income, health, and well-being around the world: Evidence from the Gallup World 

Poll. The Journal of Economic Perspectives, 22(2), 53–72. http://dx.doi.org/10.1257/jep.22.2.53 

Debnath, R. M., & Shankar, R. (2014). Does good governance enhance happiness: A cross nation study. 

Social Indicators Research, 116(1), 235–253. http://dx.doi.org/10.1007/s11205-013-0275-1 

Diener, E. (1994). Assessing subjective well-being: Progress and opportunities. Social Indicators Research, 

31(2), 103–157. http://dx.doi.org/10.1007/BF01207052 

Diener, E. (1996). Subjective well-being in cross-cultural perspective. In H. Grad, A. Blanco, & J. Georgas 

(Eds.), Key issues in cross-cultural psychology (319–330). Liese, The Netherlands: Swets & Zeitlinger 

Publishers. 

Diener, E. (2009). Culture and well-being: The collected works of Ed Diener (Social Indicators Research Series). 

Springer. http://dx.doi.org/10.1007/978-90-481-2352-0 

Diener, E., Ng, W., Harter, J., & Arora, R. (2010). Wealth and happiness across the world: Material 

prosperity predicts life evaluation, whereas psychosocial prosperity predicts positive feeling. Journal 

of Personality and Social Psychology, 99(1), 52–61. http://dx.doi.org/10.1037/a0018066 

http://dx.doi.org/10.1093/geronj/25.1.41
http://dx.doi.org/10.1007/s00127-006-0049-z
http://dx.doi.org/10.1093/0199286280.001.0001
http://dx.doi.org/10.1016/j.jebo.2005.12.005
http://dx.doi.org/10.1007/BF00353138
http://dx.doi.org/10.1007/s10902-009-9154-5
http://dx.doi.org/10.1037/a0015952
http://dx.doi.org/10.1023/A:1024704320683
http://dx.doi.org/10.1257/jep.22.2.53
http://dx.doi.org/10.1007/s11205-013-0275-1
http://dx.doi.org/10.1007/BF01207052
http://dx.doi.org/10.1007/978-90-481-2352-0
http://dx.doi.org/10.1037/a0018066


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 69 

Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of 

progress. Psychological Bulletin, 125(2), 276–302. http://dx.doi.org/10.1037/0033-2909.125.2.276 

Diener, E., & Tov, W. (2007). Subjective well-being and peace. Journal of Social Issues, 63(2), 421–440. 

http://dx.doi.org/10.1111/j.1540-4560.2007.00517.x 

Distante, R. (2013). Subjective well-being, income and relative concerns in the UK. Social Indicators 

Research, 113(1), 81–105. http://dx.doi.org/10.1007/s11205-012-0083-z 

Di Tella, R., & MacCulloch, R. (2006). Some uses of happiness data in economics. Journal of Economic 

Perspectives, 20(1), 25–46. http://dx.doi.org/10.1257/089533006776526111 

Dorahy, M. J., Lewis, C. A., Schumaker, J. F., Akuamoah-Boateng, R., Duze, M. C., & Sibiya, T. E. (1998). 

A cross-cultural analysis of religion and life satisfaction. Mental Health, Religion & Culture, 1(1), 37–43. 

http://dx.doi.org/10.1080/13674679808406496 

Dowley, K. M., & Silver, B. D. (2005). Crossnational survey research and subnational pluralism. 

International Journal of Public Opinion Research, 17(2), 226–238. http://dx.doi.org/10.1093/ijpor/edh052 

Drobnic, S., Beham, B., & Präg, P. (2010). Good job, good life? Working conditions and quality of life in 

Europe. Social Indicators Research, 99(2), 205–225. http://dx.doi.org/10.1007/s11205-010-9586-7 

Dush, C. M. K., & Amato, P. R. (2005). Consequences of relationship status and quality for subjective 

well-being. Journal of Social and Personal Relationships, 22(5), 607–627. 

http://dx.doi.org/10.1177/0265407505056438 

Easterlin, R. A., McVey, L. A., Switek, M., Sawangfa, O., & Zweig, J. S. (2010). The happiness–income 

paradox revisited. Proceedings of the National Academy of Sciences, 107(52), 22463-22468. 

http://dx.doi.org/10.1073/pnas.1015962107 

Easterlin, R. A., Morgan, R., Switek, M., & Wang, F. (2012). China’s life satisfaction, 1990–2010. 

Proceedings of the National Academy of Sciences, 109(25), 9775–9780. 

http://dx.doi.org/10.1073/pnas.1205672109 

Fahey, T., & Smyth, E. (2004). The link between subjective well-being and objective conditions in 

European societies. In W. A. Arts, & L. Halman (Eds.), European values at the turn of the millennium 

(Vol. 7), 57–80. Leiden, The Netherlands: Koninklijke Brill NV. 

Fernandez, R. M., & Kulik, J. C. (1981). A multilevel model of life satisfaction: Effects of individual 

characteristics and neighborhood composition. American Sociological Review, 46(6), 840–850. 

http://dx.doi.org/10.2307/2095082 

Ferriss, A. L. (2002). Religion and the quality of life. Journal of Happiness Studies, 3(3), 199–215. 

http://dx.doi.org/10.1023/A:1020684404438 

Frey, B. S., Luechinger, S., & Stutzer, A. (2009). The life satisfaction approach to valuing public goods: 

The case of terrorism. Public Choice, 138(3–4), 317–345. http://dx.doi.org/10.1007/s11127-008-9361-3 

Gainer, M. (2013). Assessing happiness inequality in the welfare state: Self-reported happiness and the 

Rawlsian Difference Principle. Social Indicators Research, 114(2), 453–464. 

http://dx.doi.org/10.1007/s11205-012-0155-0 

Ganglmair‐Wooliscroft, A., Croft, A. G.-W., & Lawson, R. (2008). Applying the international wellbeing 

index to investigate subjective wellbeing of New Zealanders with European and with Maori 

heritage. Ko ̄tuitui, 3(1), 57–72. http://dx.doi.org/10.1080/1177083x.2008.9522432 

Georgellis, Y., Tsitsianis, N., & Yin, Y. P. (2009). Personal values as mitigating factors in the link between 

income and life satisfaction: Evidence from the European Social Survey. Social Indicators Research, 

91(3), 329–344. http://dx.doi.org/10.1007/s11205-008-9344-2 

Glenn, N. D. (1975). The contribution of marriage to the psychological well-being of males and females. 

Journal of Marriage and Family, 37(3), 594–600. http://dx.doi.org/10.2307/350523 

Glenn, N. D., & McLanahan, S. (1981). The effects of offspring on the psychological well-being of older 

adults. Journal of Marriage and Family, 43(2), 409–421. http://dx.doi.org/10.2307/351391 

Glenn, N. D., & Weaver, C. N. (1979). A note on family situation and global happiness. Social Forces, 

57(3), 960–967. http://dx.doi.org/10.1093/sf/57.3.960 

Graham, C., & Crown, S. (2014). Religion and wellbeing around the world: Social purpose, social time, or 

social insurance? International Journal of Wellbeing, 4(1), 1-27. http://dx.doi.org/10.5502/ijw.v4i1.1 

http://dx.doi.org/10.1037/0033-2909.125.2.276
http://dx.doi.org/10.1111/j.1540-4560.2007.00517.x
http://dx.doi.org/10.1007/s11205-012-0083-z
http://dx.doi.org/10.1257/089533006776526111
http://dx.doi.org/10.1080/13674679808406496
http://dx.doi.org/10.1093/ijpor/edh052
http://dx.doi.org/10.1007/s11205-010-9586-7
http://dx.doi.org/10.1177/0265407505056438
http://dx.doi.org/10.1073/pnas.1015962107
http://dx.doi.org/10.1073/pnas.1205672109
http://dx.doi.org/10.2307/2095082
http://dx.doi.org/10.1023/A:1020684404438
http://dx.doi.org/10.1007/s11127-008-9361-3
http://dx.doi.org/10.1007/s11205-012-0155-0
http://dx.doi.org/10.1080/1177083x.2008.9522432
http://dx.doi.org/10.1007/s11205-008-9344-2
http://dx.doi.org/10.2307/350523
http://dx.doi.org/10.2307/351391
http://dx.doi.org/10.1093/sf/57.3.960
http://dx.doi.org/10.5502/ijw.v4i1.1


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 70 

Graham, C., Eggers, A., & Sukhtankar, S. (2004). Does happiness pay? An exploration based on panel 

data from Russia. Journal of Economic Behavior & Organization, 55(3), 319–342. 

http://dx.doi.org/10.1016/s0167-2681(04)00047-2 

Graham, C., Inter American Development, B., & Lora, E. (Eds.) (2009). Paradox and perception: Measuring 

quality of life in Latin America. Washington, DC: Brookings Institution Press. 

Gropper, D. M., Lawson, R. A., & Thorne, J. T., Jr. (2011). Economic freedom and happiness. The Cato 

Journal, 31, 237-255. 

Grün, C., & Klasen, S. (2003). Growth, inequality, and well-being: Intertemporal and global comparisons. 

CESifo Economic Studies, 49(4), 617–659. http://dx.doi.org/10.1093/cesifo/49.4.617 

Gundelach, P., & Kreiner, S. (2004). Happiness and life satisfaction in advanced European countries. 

Cross-Cultural Research: Official journal of the Society for Cross-Cultural Research, Sponsored by the Human 

Relations Area Files, Inc, 38(4), 359–386. http://dx.doi.org/10.1177/1069397104267483 

Gurin, G. (1960). Americans view their mental health: A nationwide interview survey; A report to the staff 

director, Jack E. Ewal, 1960. New York: Basic Books. 

Gurin, G., Veroff, J., & Feld, S. (1984). Americans view their mental health, 1957. 

http://doi.org/10.3886/ICPSR03503.v1 

Hackney, C. H., & Sanders, G. S. (2003). Religiosity and mental health: A meta-analysis of recent studies. 

Journal for the Scientific Study of Religion, 42(1), 43–56. http://dx.doi.org/10.1111/1468-5906.t01-1-00160 

Hadaway, C. K. (1978). Life satisfaction and religion: A reanalysis. Social Forces, 57(2), 636–643. 

http://dx.doi.org/10.1093/sf/57.2.636 

Hall, J. F. (1973). Measuring the quality of life using sample surveys. Technology Assessment and Quality of 

Life, 93–101.  

Hall, J. F. (1976). Subjective measures of quality of life in Britain: 1971 to 1975: Some developments and 

trends. Social Trends, 7(48), 14. 

Halman, L. (1987). Traditie, secularisatie en individualisering: een studie naar de waarden van de Nederlanders in 

een Europese context. Tillburg, The Netherlands: University Press. 

Hasegawa, H., & Ueda, K. (2011). Measuring inequality of subjective well-being: A Bayesian approach. 

The Journal of Socio-Economics, 40(5), 700–708. http://dx.doi.org/10.1016/j.socec.2011.05.009 

Hayo, B. (2007). Happiness in transition: An empirical study on Eastern Europe. Economic Systems, 31(2), 

204–221. http://dx.doi.org/10.1016/j.ecosys.2006.08.003 

Headey, B. (1981). The quality of life in Australia. Social Indicators Research, 9(2), 155–181. 

http://dx.doi.org/10.1007/BF00286195 

Headey, B., Muffels, R., & Wagner, G. G. (2010). Long-running German panel survey shows that personal 

and economic choices, not just genes, matter for happiness. Proceedings of the National Academy of 

Sciences, 107(42), 17922–17926. http://dx.doi.org/10.1073/pnas.1008612107 

Headey, B., Muffels, R., & Wagner, G. G. (2013). Choices which change life satisfaction: Similar results for 

Australia, Britain and Germany. Social Indicators Research, 112(3), 725–748. 

http://dx.doi.org/10.1007/s11205-012-0079-8 

Headey, B., Schupp, J., Tucci, I., & Wagner, G. G. (2010). Authentic happiness theory supported by 

impact of religion on life satisfaction: A longitudinal analysis with data for Germany. The Journal of 

Positive Psychology, 5(1), 73–82. http://dx.doi.org/10.1080/17439760903435232 

Headey, B., Veenhoven, R., & Wearing, A. (1991). Top-down versus bottom-up theories of subjective 

well-being. Social Indicators Research, 24(1), 81–100. http://dx.doi.org/10.1007/BF00292652 

Herzog, A. R., Rodgers, W. L., & Woodworth, J. (1982). Subjective well-being among different age groups 

(Research Report Series). Ann Arbor, MI: Institute for Social Research. 

Heukamp, F. H., & Ariño, M. A. (2011). Does country matter for subjective well-being? Social Indicators 

Research, 100(1), 155–170. http://dx.doi.org/10.1007/s11205-010-9610-y 

Hoverd, W. J., & Sibley, C. G. (2013). Religion, deprivation and subjective wellbeing: Testing a religious 

buffering hypothesis. International Journal of Wellbeing, 3(2), 182-196.  

Howell, R. T., & Howell, C. J. (2008). The relation of economic status to subjective well-being in 

developing countries: A meta-analysis. Psychological Bulletin, 134(4), 536–60. 

http://dx.doi.org/10.1037/0033-2909.134.4.536 

http://dx.doi.org/10.1016/s0167-2681%2804%2900047-2
http://dx.doi.org/10.1093/cesifo/49.4.617
http://dx.doi.org/10.1177/1069397104267483
http://doi.org/10.3886/ICPSR03503.v1
http://dx.doi.org/10.1111/1468-5906.t01-1-00160
http://dx.doi.org/10.1093/sf/57.2.636
http://dx.doi.org/10.1016/j.socec.2011.05.009
http://dx.doi.org/10.1016/j.ecosys.2006.08.003
http://dx.doi.org/10.1007/BF00286195
http://dx.doi.org/10.1073/pnas.1008612107
http://dx.doi.org/10.1007/s11205-012-0079-8
http://dx.doi.org/10.1080/17439760903435232
http://dx.doi.org/10.1007/BF00292652
http://dx.doi.org/10.1007/s11205-010-9610-y
http://dx.doi.org/10.1037/0033-2909.134.4.536


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 71 

Inglehart, R., Foa, R., Peterson, C., & Welzel, C. (2008). Development, freedom, and rising happiness: A 

global perspective (1981–2007). Perspectives on Psychological Science, 3(4), 264–285. 

http://dx.doi.org/10.1111/j.1745-6924.2008.00078.x 

Jorm, A. F., & Ryan, S. M. (2014). Cross-national and historical differences in subjective well-being. 

International Journal of Epidemiology, 43(2), 330–340. http://dx.doi.org/10.1093/ije/dyt188 

Kaliterna Lipovčan, L., & Prizmić-Larsen, Z. (2006). What makes Croats happy? Predictors of happiness 

in a representative sample. In A. Delle Fave (Ed.), Dimensions of well-being research: Research and 

intervention (60–74). Milano, Italy: FrancoAngeli. 

Karabegovic, A., & Amela, K. (2006). Economic freedom [Institutions and the impact of investment on 

growth] [Economic policy and the level of self-perceived well-being: An international comparison]. 

Fraser Forum, 28. 

Kennedy, L. W., & Mehra, N. (1985). Effects of social change on well-being: Boom and bust in a Western 

Canadian city. Social Indicators Research, 17(2), 101–113. http://dx.doi.org/10.1007/BF00302416 

Kennedy, L. W., Northcott, H. C., & Kinzel, C. (1978). Subjective evaluation of well-being: Problems and 

prospects. Social Indicators Research, 5(1–4), 457–474. http://dx.doi.org/10.1007/BF00352943 

Koralewicz, J., & Zagorski, K. (2009). Living conditions and optimistic orientation of Poles. International 

Journal of Sociology, 39(4), 10–44. http://dx.doi.org/10.2753/IJS0020-7659390401 

Lemel, Y., & Noll, H. H. (2002). Changing structures of inequality: A comparative perspective. Montréal: 

McGill-Queen's University Press. 

Lim, C., & Putnam, R. D. (2010). Religion, social networks, and life satisfaction. American Sociological 

Review, 75(6), 914–933. http://dx.doi.org/10.1177/0003122410386686 

Luechinger, S., Meier, S., & Stutzer, A. (2010). Why does unemployment hurt the employed? Evidence 

from the life satisfaction gap between the public and the private sector. Journal of Human Resources, 

45(4), 998–1045. http://dx.doi.org/10.1353/jhr.2010.0024 

Matlin, N. (1966). The demography of happiness: Master sample survey of health and welfare. Office of Research, 

Department of Health and Research Unit, School of Public Health. 

McBride, M. (2001). Relative-income effects on subjective well-being in the cross-section. Journal of 

Economic Behavior & Organization, 45(3), 251–278. http://dx.doi.org/10.1016/S0167-2681(01)00145-7 

McGillivray, M., & Markova, N. (2009). Global inequality in well-being dimensions. The Journal of 

Development Studies, 46(2), 371–378. http://dx.doi.org/10.1080/00220380903033280 

McNamara, P. H., & St. George, A. (1978). Blessed are the downtrodden? An empirical test. Sociological 

Analysis, 39(4), 303–320. http://dx.doi.org/10.2307/3709974 

Mookherjee, H. N. (1992). A comparative assessment of life satisfaction in the United States: 1978–1988. 

The Journal of Social Psychology, 132(3), 407–409. http://dx.doi.org/10.1080/00224545.1992.9924717 

Mookherjee, H. N. (1994). Effects of religiosity and selected variables on the perception of well-being. The 

Journal of Social Psychology, 134(3), 403–405. http://dx.doi.org/10.1080/00224545.1994.9711748 

Noelle-Neumann, E. (1974). Lebensfreude–Kein Thema für die Kirche? Fragen zu einem Test über 

Bewegungs-und Mienenspiel von Katholiken. Herder Korrespondenz, 28(1), 41–47.  

OECD. Statistics, Knowledge and Policy 2007: Measuring and fostering the progress of societies. Paris: OECD 

Publishing. 

Okulicz-Kozaryn, A. (2009). Religiosity and life satisfaction across nations. Mental Health, Religion & 

Culture, 13(2), 155–169. http://dx.doi.org/10.1080/13674670903273801 

Ott, J. (2005). Level and inequality of happiness in nations: Does greater happiness of a greater number 

imply greater inequality in happiness? Journal of Happiness Studies, 6(4), 397–420. 

http://dx.doi.org/10.1007/s10902-005-8856-6 

Ouweneel, P. (1987). Geluk volgt welvaart. Economische Statistische Berichten, 3622, 840–842.  

Ouweneel, P. (2002). Social security and well-being of the unemployed in 42 nations. Journal of Happiness 

Studies, 3(2), 167–192. http://dx.doi.org/10.1023/A:1019619324661 

Ovaska, T., & Takashima, R. (2006). Economic policy and the level of self-perceived well-being: An 

international comparison. The Journal of Socio-Economics, 35(2), 308–325. 

http://dx.doi.org/10.1016/j.socec.2005.11.054 

http://dx.doi.org/10.1111/j.1745-6924.2008.00078.x
http://dx.doi.org/10.1093/ije/dyt188
http://dx.doi.org/10.1007/BF00302416
http://dx.doi.org/10.1007/BF00352943
http://dx.doi.org/10.2753/IJS0020-7659390401
http://dx.doi.org/10.1177/0003122410386686
http://dx.doi.org/10.1353/jhr.2010.0024
http://dx.doi.org/10.1016/S0167-2681%2801%2900145-7
http://dx.doi.org/10.1080/00220380903033280
http://dx.doi.org/10.2307/3709974
http://dx.doi.org/10.1080/00224545.1992.9924717
http://dx.doi.org/10.1080/00224545.1994.9711748
http://dx.doi.org/10.1080/13674670903273801
http://dx.doi.org/10.1007/s10902-005-8856-6
http://dx.doi.org/10.1023/A:1019619324661
http://dx.doi.org/10.1016/j.socec.2005.11.054


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 72 

Palisi, B. J., & Canning, F. C. (1983). Urbanism and social psychological well-being: A cross-cultural test 

of three theories. The Sociological Quarterly, 24(4), 527–543. http://dx.doi.org/10.1111/j.1533-

8525.1983.tb00717.x 

Peacock, J. R., & Poloma, M. M. (1999). Religiosity and life satisfaction across the life course. Social 

Indicators Research, 48(3), 319–343. http://dx.doi.org/10.1023/A:1006928028270 

Pontin, E., Schwannauer, M., Tai, S., & Kinderman, P. (2013). A UK validation of a general measure of 

subjective well-being: The modified BBC subjective well-being scale (BBC-SWB). Health and Quality of 

Life Outcomes, 11, 150–159. http://dx.doi.org/10.1186/1477-7525-11-150 

Rojas, M. (2005). A conceptual-referent theory of happiness: Heterogeneity and its consequences. Social 

Indicators Research, 74(2), 261–294. http://dx.doi.org/10.1007/s11205-004-4643-8 

Rojas, M. (2007). Heterogeneity in the relationship between income and happiness: A conceptual-

referent-theory explanation. Journal of Economic Psychology, 28(1), 1–14. 

http://dx.doi.org/10.1016/j.joep.2005.10.002 

Rojas, M., & Veenhoven, R. (2013). Contentment and affect in the estimation of happiness. Social 

Indicators Research, 110(2), 415–431. http://dx.doi.org/10.1007/s11205-011-9952-0 

Rule, S. (2007). Religiosity and quality of life in South Africa. Social Indicators Research, 81(2), 417–434. 

http://dx.doi.org/10.1007/s11205-006-9005-2  

Samanni, M., & Holmberg, S. (2010). Quality of government makes people happy. QoG Working Paper 

Series, 1–36. The QOG Institute: University of Gothenburg. 

Schubert, C. (2012). Pursuing happiness. Kyklos, 65(2), 245–261. http://dx.doi.org/10.1111/j.1467-

6435.2012.00537.x 

Schütz, E., Sailer, U., Al Nima, A., Rosenberg, P., Andersson, A. A., Archer, T., & Garcia, D. (2013). The 

affective profiles in the USA: Happiness, depression, life satisfaction, and happiness-increasing 

strategies. PeerJ (San Francisco, CA), 1(8), e156. http://dx.doi.org/10.7717/peerj.156 

Schyns, P. (1998). Crossnational differences in happiness: Economic and cultural factors explored. Social 

Indicators Research, 43(1–2), 3–26. http://dx.doi.org/10.1023/A:1006814424293 

Selim, S. (2008). Life satisfaction and happiness in Turkey. Social Indicators Research, 88(3), 531–562. 

http://dx.doi.org/10.1007/s11205-007-9218-z 

Shemyakina, O. N., & Plagnol, A. C. (2013). Subjective well-being and armed conflict: Evidence from 

Bosnia-Herzegovina. Social Indicators Research, 113(3), 1129–1152. http://dx.doi.org/10.1007/s11205-

012-0131-8 

Sigelman, L. (1981). Is ignorance bliss? A reconsideration of the folk wisdom. Human Relations, 34(11), 

965–974. http://dx.doi.org/10.1177/001872678103401104 

Snoep, L. (2008). Religiousness and happiness in three nations: A research note. Journal of Happiness 

Studies, 9(2), 207–211. http://dx.doi.org/10.1007/s10902-007-9045-6 

Spreitzer, E., Snyder, E. E., & Larson, D. (1975). Age, marital status, and labor force participation as 

related to life satisfaction. Sex Roles, 1(3), 235–247. http://dx.doi.org/10.1007/BF00287372 

Stevenson, B., & Wolfers, J. (2008). Economic growth and subjective well-being: Reassessing the Easterlin 

paradox. Brookings Papers on Economic Activity, 2008, 1–102. http://dx.doi.org/10.1353/eca.0.0001 

Tavits, M. (2008). Representation, corruption, and subjective well-being. Comparative Political Studies, 

41(12), 1607–1630. http://dx.doi.org/10.1177/0010414007308537 

Taylor, P. (2008). Republicans-still happy campers (S. Trends, Trans.) Pew Research Social & Demographic 

Trends (1–15). 

Thoits, P. A., & Hewitt, L. N. (2001). Volunteer work and well-being. Journal of Health and Social Behavior, 

42(2), 115–131. http://dx.doi.org/10.2307/3090173 

Toulmin, S. E. (1961). Foresight and understanding: An inquiry into the aims of science. Bloomington, IN: 

Indiana University Press. 

Uglanova, E. A. (2014). Gender dimensions of subjective well-being in Russia. In E. Eckermann (Ed.), 

Gender, lifespan and quality of life, Social Indicators Research Series, 53, 135–155. Netherlands: Springer. 

http://dx.doi.org/10.1007/978-94-007-7829-0_9 

http://dx.doi.org/10.1111/j.1533-8525.1983.tb00717.x
http://dx.doi.org/10.1111/j.1533-8525.1983.tb00717.x
http://dx.doi.org/10.1023/A:1006928028270
http://dx.doi.org/10.1186/1477-7525-11-150
http://dx.doi.org/10.1007/s11205-004-4643-8
http://dx.doi.org/10.1016/j.joep.2005.10.002
http://dx.doi.org/10.1007/s11205-011-9952-0
http://dx.doi.org/10.1007/s11205-006-9005-2
http://dx.doi.org/10.1111/j.1467-6435.2012.00537.x
http://dx.doi.org/10.1111/j.1467-6435.2012.00537.x
http://dx.doi.org/10.7717/peerj.156
http://dx.doi.org/10.1023/A:1006814424293
http://dx.doi.org/10.1007/s11205-007-9218-z
http://dx.doi.org/10.1007/s11205-012-0131-8
http://dx.doi.org/10.1007/s11205-012-0131-8
http://dx.doi.org/10.1177/001872678103401104
http://dx.doi.org/10.1007/s10902-007-9045-6
http://dx.doi.org/10.1007/BF00287372
http://dx.doi.org/10.1353/eca.0.0001
http://dx.doi.org/10.1177/0010414007308537
http://dx.doi.org/10.2307/3090173
http://dx.doi.org/10.1007/978-94-007-7829-0_9


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 73 

Uglanova, E. A., & Staudinger, U. M. (2013). Zooming in on life events: Is Hedonic adaptation sensiti ve 

to the temporal distance from the event? Social Indicators Research, 111(1), 265–286. 

http://dx.doi.org/10.1007/s11205-012-0004-1 

van Hemert, D. A., van de Vijver, F. J. R., & Poortinga, Y. H. (2002). The Beck Depression inventory as a 

measure of subjective well-being: A cross-national study. Journal of Happiness Studies, 3(3), 257–286. 

http://dx.doi.org/10.1023/A:1020601806080 

van Praag, B. M. S., Frijters, P., & Ferrer-i-Carbonell, A. (2003). The anatomy of subjective well-being. 

Journal of Economic Behavior & Organization, 51(1), 29–49. http://dx.doi.org/10.1016/S0167-

2681(02)00140-3 

Veenhoven, R. (1984). Conditions of happiness. Dordrecht, Holland; Hingham, MA: D. Reidel. Sold and 

distributed in the U.S.A. and Canada by Kluwer Boston Academic Publishers. 

http://dx.doi.org/10.1007/978-94-009-6432-7 

Veenhoven, R. (1989). National wealth and individual happiness. In Gruert, K.G. & Olander, M. (Eds.) 

Understanding economic behavior, 9-32. Netherlands: Springer. http://dx.doi.org/10.1007/978-94-009-

2470-3_2 

Veenhoven, R. (1993). Happiness in nations. Studies in Socio-Cultural Transformation. Rotterdam, 

Netherlands: Erasmus University. 

Veenhoven, R. (1996). Leefbaarheid van landen. Universiteit Utrecht. 

Veenhoven, R. (1999). Op zoek naar een menselijke maat. Leefbaarheid van de individualistische 

samenleving. Rekenschap, 46(2), 83–95.  

Veenhoven, R. (1999). Quality-of-life in individualistic society: A comparison of 43 nations in the early 

1990s. Social Indicators Research, 48(2), 157–186. http://dx.doi.org/10.1023/A:1006923418502 

Veenhoven, R. (2000). Freedom and happiness: A comparative study in forty-four nations in the early 

1990s. In E. Diener & E. M. Suh (Eds.), Culture and subjective well-being (257–288). Cambridge, MA: 

MIT Press. 

Veenhoven, R. (2001). What do we know about happiness. Paper presented at the Dialogue on Gross 

National Happiness, Woudschoten, Zeist, The Netherlands. 

Veenhoven, R. (2004). Happiness as a public policy aim: The greatest happiness principle. Positive 

Psychology in Practice (658–678). Hoboken, NJ: John Wiley & Sons, Inc. 

Veenhoven, R. (2004). Veiligheid en Geluk. In E. R. Muller (Ed.), Veiligheid studies over inhoud, organisatie 

en maatregelen. The Netherlands: Kluwer. 

Veenhoven, R. (2005). Apparent quality-of-life in nations: How long and happy people live. Social 

Indicators Research, 71(1–3), 61–86. http://dx.doi.org/10.1007/1-4020-3602-7_3 

Veenhoven, R. (2005). Inequality of happiness in nations. Journal of Happiness Studies, 6(4), 351–355. 

http://dx.doi.org/10.1007/s10902-005-0003-x  

Veenhoven, R. (2005). Is life getting better?: How long and happily do people live in modern society? 

European Psychologist, 10(4), 330–343. http://dx.doi.org/10.1027/1016-9040.10.4.330  

Veenhoven, R. (2005). Return of inequality in modern society? Test by dispersion of life-satisfaction 

across time and nations. Journal of Happiness Studies, 6(4), 457–487. http://dx.doi.org/10.1007/s10902-

005-8858-4 

Veenhoven, R. (2007). Greater happiness for a greater number. Journal of Happiness Studies, 11(5), 605-629. 

http://dx.doi.org/10.1007/s10902-010-9204-z 

Veenhoven, R. (2008). Healthy happiness: effects of happiness on physical health and the consequences 

for preventive health care. Journal of Happiness Studies, 9(3), 449–469. http://dx.doi.org/10.1007/s10902-

006-9042-1 

Veenhoven, R. (2009). Well-being in nations and well-being of nations: Is there a conflict between 

individual and society? Social Indicators Research, 91(1), 5–21. http://dx.doi.org/10.1007/s11205-008-

9323-7 

Veenhoven, R. (2010). Life is getting better: Societal evolution and fit with human nature. Social Indicators 

Research, 97(1), 105–122. http://dx.doi.org/10.1007/s11205-009-9556-0 

Veenhoven, R., & Ouweneel, P. (1989). Het Rendement van de Verzorgingsstaat (The revenues of the 

welfare state). Economisch Statistische Berichten (April 26), 419–420.  

http://dx.doi.org/10.1007/s11205-012-0004-1
http://dx.doi.org/10.1023/A:1020601806080
http://dx.doi.org/10.1016/S0167-2681%2802%2900140-3
http://dx.doi.org/10.1016/S0167-2681%2802%2900140-3
http://dx.doi.org/10.1007/978-94-009-6432-7
http://dx.doi.org/10.1007/978-94-009-2470-3_2
http://dx.doi.org/10.1007/978-94-009-2470-3_2
http://dx.doi.org/10.1023/A:1006923418502
http://dx.doi.org/10.1007/1-4020-3602-7_3
http://dx.doi.org/10.1007/s10902-005-0003-x
http://dx.doi.org/10.1027/1016-9040.10.4.330
http://dx.doi.org/10.1007/s10902-005-8858-4
http://dx.doi.org/10.1007/s10902-005-8858-4
http://dx.doi.org/10.1007/s10902-010-9204-z
http://dx.doi.org/10.1007/s10902-006-9042-1
http://dx.doi.org/10.1007/s10902-006-9042-1
http://dx.doi.org/10.1007/s11205-008-9323-7
http://dx.doi.org/10.1007/s11205-008-9323-7
http://dx.doi.org/10.1007/s11205-009-9556-0


A meta-analysis of wellbeing  

Eger & Maridal 

 

www.internationaljournalofwellbeing.org 74 

Veenhoven, R., & Ouweneel, P. (1995). Livability of the welfare-state: Appreciation-of-life and length-of-

life in nations varying in state-welfare-effort. Social Indicators Research, 36(1), 1–48. 

http://dx.doi.org/10.1007/BF01079395 

Veroff, J., Douvan, E. A. M., & Kulka, R. A. (1981). The inner American: A self-portrait from 1957 to 1976. 

New York: Basic Books. 

Welsch, H. (2002). Preferences over prosperity and pollution: Environmental valuation based on 

happiness surveys. Kyklos, 55(4), 473–494. http://dx.doi.org/10.1111/1467-6435.00198 

Wessman, A. E. (1956). A psychological inquiry into satisfactions and happiness. Princeton, NJ: Princeton 

University. 

Wilkening, E. A., & McGranahan, D. (1978). Correlates of subjective well-being in Northern Wisconsin. 

Social Indicators Research, 5(1–4), 211–234. http://dx.doi.org/10.1007/BF00352930 

Williams, K. (2003). Has the future of marriage arrived? A contemporary examination of gender, 

marriage, and psychological well-being. Journal of Health and Social Behavior, 44(4), 470–487. 

http://dx.doi.org/10.2307/1519794 

Wilson, W. R. (1967). Correlates of avowed happiness. Psychological Bulletin, 67(4), 294–306. 

http://dx.doi.org/10.1037/h0024431 

Winkelmann, L., & Winkelmann, R. (1998). Why are the unemployed so unhappy? Evidence from panel 

data. Economica, 65(257), 1–15. http://dx.doi.org/10.1111/1468-0335.00111 

Wooden, M., & Li, N. (2014). Panel conditioning and subjective well-being. Social Indicators Research, 

117(1), 235–255. http://dx.doi.org/10.1007/s11205-013-0348-1 

 

http://dx.doi.org/10.1007/BF01079395
http://dx.doi.org/10.1111/1467-6435.00198
http://dx.doi.org/10.1007/BF00352930
http://dx.doi.org/10.2307/1519794
http://dx.doi.org/10.1037/h0024431
http://dx.doi.org/10.1111/1468-0335.00111
http://dx.doi.org/10.1007/s11205-013-0348-1