Religion and Life Satisfaction: Evidence from Germany

Elisabeth Sinnewe • Michael A. Kortt • Brian Dollery

Accepted: 7 September 2014� Springer Science+Business Media Dordrecht 2014

Abstract We examined the association between religious involvement and life satis-

faction using data drawn from the 2003, 2007, and 2011 waves of the German Socio-

Economic Panel. Our study provides evidence of an association between attendance at

religious services and life satisfaction for respondents residing in West Germany. While

social networks partially mediate this relationship for West Germany, there appears to be a

remaining direct impact of attendance on life satisfaction. On the contrary, we find no

evidence of an association between attendance at religious services and life satisfaction for

respondents residing in East Germany.

Keywords Germany � Life satisfaction � Religion � Religious participation � Social

networks

1 Introduction

The study of factors influencing subjective well-being (SWB) has traditionally been the

province of psychologists (e.g., Argyle 2001; Diener et al. 1999). However, scholars from

other disciplines like economics and sociology are now also increasingly exploring a wide

range of putative determinants of SWB. Examples include what role religion (e.g., Lim and

Putnam 2010) and rising incomes (Frijters et al. 2004) may exert on SWB. This growing

corpus of empirical research has, in part, been driven by the development of reliable and

valid measures of SWB (Kahneman and Krueger 2006) and the relative ease of access to

E. Sinnewe � M. A. Kortt (&)Southern Cross Business School, Southern Cross University, Coolangatta, QLD, Australiae-mail: michael.kortt@scu.edu.au

B. DolleryUNE Business School, University of New England, Armidale, NSW, Australia

123

Soc Indic ResDOI 10.1007/s11205-014-0763-y

life satisfaction and happiness data in large-scale international surveys such as the Euro-

pean Values Study and the World Values Survey (Frey and Stutzer 2002).

An extensive range of factors can influence SWB including, inter alia, age, sex, edu-

cational attainment, marital status, number of children, employment status, self-reported

health status, personality, and major life events (Argyle 2001; Diener et al. 1999, 2009).

Moreover, a number of studies have also found that attendance at religious services and

religious affiliation are positively related to SWB (e.g., Argyle 2001; Diener et al. 1999,

2009; Ellison 1991; Ellison et al. 2001; Ferris 2002; Francis et al. 2003; Hadaway 1978;

Hadaway and Roof 1978; Inglehart 2010; Maselko and Kubzansky 2006). However, not all

studies have found a connection between religious behaviour and SWB (e.g., Ciarrocchi

and Deneke 2004; Lewis et al. 1997; Lewis 2002; Lewis et al. 2000).

There is, however, a significant on-going debate regarding how religious behaviour may

actually affect SWB. For instance, some scholars stress the importance of social networks

(e.g., Krause 2008) while other researchers concentrate on the personal and inner

dimensions of religion (e.g., Greeley and Hout 2006). In an effort to explain why religion

may affect SWB, two main explanations have been proposed. The first explanation is that

religious organisations such as churches may enhance SWB by providing like-minded

individuals with access to social networks (e.g., Ellison and George 1994; Krause 2008).

The second explanation is that the personal and inner dimensions of religion (such as a

belief in God) may be positively linked to SWB. While it is far from clear which aspect of

religion may play a more dominant role in affecting individual SWB (Lim and Putnam

2010), the current study examines the importance of social networks in German society.

While many studies have examined the link between religious participation and life

satisfaction employing U.S. data (e.g., Koenig, McCullough and Larson 2001), compara-

tively few studies have examined this question using German data. Thus, in an effort to

partially remedy this neglect, our study uses data from the German Socio-Economic Panel

(G-SOEP) to explicitly examine the link between life satisfaction and religion for Germany

and what role, if any, social networks may play in mediating this relationship.

In studying contemporary German society we are provided with the unique opportunity

to investigate separately the relationship between religion and life satisfaction for West and

East Germany. This stratification can be justified on the grounds that: (1) prior to the fall of

the Berlin Wall in 1989 two large neighbouring German populations—with a shared

history and language—were residing under starkly different economic and political cir-

cumstances (Easterlin and Plagnol 2008); (2) within a relatively short period of time, West

Germany and East Germany were integrated into a single market-based economy under

democratic law, with East Germany effectively ‘converting’ from socialism to capitalism

(Easterlin and Plagnol 2008); (3) the vast majority of non-religious people live in East

Germany (Religionen in Deutschland 2009); and (4) even after reunification, differences in

the beliefs about God in West and East Germany continue to persist and, in some cases,

widen (Smith 2012).

Thus, while there is evidence that the ‘post-unification story of life satisfaction in East

and West Germany is largely one of convergence’ (Easterlin and Plagnol 2008: 435)

differences in religious beliefs continue to persist (Smith 2012), which is probably due—at

least in part—to the former communist party’s suppression of religion in East Germany

(e.g., Froese and Pfaff 2005). Furthermore, the consistently higher rates of attendance at

religious services in West Germany compared to those in East Germany suggests that

attendance is most likely a chosen activity as opposed to a matter of social compliance

(e.g., Headey et al. 2010).

E. Sinnewe et al.

123

2 Theoretical and Empirical Background

2.1 Conceptual Considerations

An individual assesses his or her own level of SWB in relation to their current circum-

stances (and comparison with other people), previous experience, and future aspirations

(Frey and Stutzer 2002). The concept of SWB consists of both an ‘affective’ and ‘cog-

nitive’ domain (Diener et al. 1999). The ‘affective’ domain is a label used to describe the

emotions of an individual’s instantaneous reaction (i.e., a pleasant or unpleasant response)

to events happening in their life. On the other hand, the ‘cognitive’ dimension refers to the

‘intellectual’ aspect of SWB and it is typically evaluated by measures of life satisfaction

(Diener et al. 1999; Frey and Stutzer 2002).

Traditionally, economists have inferred ‘well-being’ from ‘objective’ measures like

educational attainment, GDP per capita, and life expectancy. However, increasing attention

has been devoted to measuring ‘subjective’ well-being (SWB) using responses to questions

on life satisfaction in major social science surveys. Consequently, there is now a sizable

body of literature that has investigated the reliability and validity of responses to these

kinds of questions (e.g., Clark et al. 2008; Di Tella and MacCulloch 2006; Frey and Stutzer

2002). The general agreement in the literature is that SWB measures of this kind represents

a meaningful measure of an individual’s well-being. Thus, our interest falls squarely on

examining how attendance at religious services in Germany influences the cognitive

dimension of subjective life satisfaction.

2.2 The Impact of Religion on SWB

Koenig, McCullough and Larson (2001) have conducted one of the most wide-ranging

reviews on the association between religious behaviour and life satisfaction. The authors

reviewed 100 studies that examined the statistical association between life satisfaction and

religion and established that: (1) 79 studies reported a positive association, (2) 13 studies

found no association, (3) seven studies were inconclusive, and (4) one study found a

negative association. The main conclusions drawn from this corpus of empirical research

were that religious belief and attendance at religious services were predictive of life

satisfaction.

However, it is worth noting that in those empirical studies which detected a positive

association between religion and life satisfaction, the strength of this relationship is sig-

nificant (Inglehart 2010). For example, in a meta-analysis, Witter et al. (1985) estimated

that religious involvement accounted for between 2 and 6 % of the variation in SWB.

Similarly, Ellison (1991) has reported that religious variables account for between 5 and

7 % of the variation in life satisfaction but only between 2 and 3 % of this variable can be

ascribed to the affective domains of SWB. This suggests that the purported benefits

bestowed by religion are, for the most part, largely ‘cognitive’, and accordingly offers

individuals an interpretative framework to support them in making sense of life (Diener

et al. 1999).

In many empirical studies, attendance at religious services is commonly reported as

being a strong predictor of SWB (e.g., Argyle 2001; Diener et al. 1999; Ellison et al. 2001;

Ferris 2002; Francis et al. 2003), although other studies have found that the personal and

inner dimensions of religion are also positively associated with SWB (e.g., Argyle 2001;

Ellison 1991; Greeley and Hout 2006; Pollner 1989).

Religion and Life Satisfaction

123

While most studies which have examined the association between religion and SWB

have used cross-sectional datasets (Ellison and Levin 1998) it needs to be borne in mind

that a number of panel studies have been able to provide a stronger investigation into the

possible causal impact of various religious aspects on SWB (Krause 2006; Krause and

Ellison 2009; Levin and Taylor 1998; Lim and Putnam 2010).

One of the most recent and comprehensive panel studies to examine the influence of

religious involvement and life satisfaction was conducted by Lim and Putnam (2010).

Drawing on data collected in 2006 and 2007 as part of the Faith Matters Study, Lim and

Putnam (2010) provide robust empirical evidence that most of the relationship between life

satisfaction and religious involvement is mediated by friendship networks which church-

goers build in their congregations.

2.3 The Importance of Religion

In exploring the association between religion and SWB, the following question naturally

arises: why should individuals who participate in religious activities—notably attendance

at religious services—report higher levels of SWB? One potential explanation is that

religion offers social networks. This theory, which has its origins in the seminal work by

Durkheim (1951), contends that religious organisations like churches afford like-minded

individuals: (1) the opportunity to develop friendships and social networks; (2) a regular

meeting place to partake in social exchange; and (3) the opportunity to draw on these social

networks in times of need (Argyle 2001; Ellison 1991; George et al. 2002; Krause 2008).

In essence, this theory suggests that attendance at religious services will improve an

individual’s social network, which, in turn, will bolster their life satisfaction. Put differ-

ently, the impact of attendance on life satisfaction operates through one’s social network.

However, although this theoretical explanation is intrinsically appealing, it has limited

empirical support (Lim and Putnam 2010). For example, Ellison et al. (1989) and Greeley

and Hout (2006) have reported that the association between religion and SWB remains

statistically significant despite considerable efforts to control for social networks. More-

over, Lim and Putnam (2010) have also noted that the majority of these studies do not draw

the distinction between ‘secular social networks’ and ‘religious social networks’ and have

consequently made a case that this difference should be made in order to determine

whether religious social networks directly affect SWB.

A second possible explanation rests on how the personal and inner dimensions of

religion heighten individual SWB (Argyle 2001; Ellison 1991; Ellison et al. 1989; Greeley

and Hout 2006). Pollner (1989) has also put forth a case that individuals may build a

personal relationship with a deity in an effort to secure spiritual direction and security.

Moreover, interaction with these deities by way of individual prayer may also assist in

enhancing an individual’s self-esteem (Ellison 1991). Pollner (1989: 93) also proposes that

a belief in a deity may, in turn, bolster individual SWB by contributing to the ‘perceptions

of orderliness and predictability of events’ and may even provide an interpretive structure

for ‘explaining problematic occurrences’.

In investigating these relationships, Ellison (1991) found that the inclusion of personal

and subjective religious dimensions attenuated the association between life satisfaction and

attendance at religious services to a statistically insignificant level. Conversely, Pollner

(1989) found that attendance at religious services was still statistically significant even

after controlling for the possible influence of personal of subjective religious dimensions

on life satisfaction. Even if these variables are deemed to be mitigating factors, there may

E. Sinnewe et al.

123

still be a need to identify any ‘remaining direct influence of attendance’ on life satisfaction

(Lim and Putnam 2010: 917).

2.4 Religion in Germany

Given the analysis in this article takes place within the context of Germany society, it is

instructive to consider a number of key characteristics. According to 2011 official statis-

tics, the population of Germany was 81.1 million (US Department of State 2012). Of this

total, it is estimated that approximately 25 million Germans (31 %) profess affiliation to

the Roman Catholic Church while approximately 24 million Germans (30 %) profess

affiliation to the Protestant Church. Together, Catholics and Protestants accounted for just

over 60 % of the total population. The second largest religious denomination in Germany

is Islam, which accounts for approximately 5 % of the population (i.e., approximately 4

million Muslims). Finally, approximately 35 % of all Germans (79 % in East Germany)

reported having no religious affiliation (US Department of State 2012).

The stark differences in religious beliefs between West and East Germany continue to

persist post-reunification. For example, between 1998 and 2008, West Germany showed a

consistent growth rate in the belief of God while an opposite trend was observed for East

Germany (Smith 2012). Froese and Pfaff (2005) have argued that this situation is, in

essence, due to: (1) the suppression of religion in East Germany by the former community

party; and (2) the re-introduction of church taxes—following reunification—for registered

members of religious organisation. Consequently, the ‘combination of lingering ideolog-

ical hostility to religion and a highly regulated religious marketplace’ make East Germany

a ‘very inhospitable terrain for religious revival’ (Froese and Pfaff 2005: 414). Thus, from

a theoretical perspective, we would expect a priori that the anticipated association between

religion and life satisfaction will be stronger in West than East Germany.

2.5 Research Questions

We contribute to the literature by using data drawn from the G-SOEP which contains

information on life satisfaction and religion as well as detailed data on the economic and

social characteristics of its participants. Thus, the G-SOEP survey provides us with a

unique opportunity to investigate the following research questions for Germany:

1. Is attendance at religious services positively associated with life satisfaction?;

2. Does attendance at religious services have an independent impact on life satisfaction

after controlling for social networks (i.e., the number of close friends and frequency of

social gatherings)?; and

3. In examining these associations are there any differences between West and East

Germany?

By addressing these questions, we are able to empirically test the theoretical proposition

whether attendance at religious services is positively associated with life satisfaction and

what role social networks may play in attenuating this relationship.1 Our study also con-

tributes to the literature in the following ways: (1) we provide—to the best of our

knowledge—the first empirical analysis of this particular issue for Germany; (2) we

1 . While the research questions posed in our study examines a relationship that runs from religiousparticipation to social networks to life satisfaction, it needs to be stressed that many of these associationshave been shown to be bi-directional (see, e.g., Adams 1988; Lyubomirsky et al. 2005a, b).

Religion and Life Satisfaction

123

examine whether differences exist between West and East Germany; and (3) we explicitly

exploit the panel nature of G-SOEP survey to more effectively account for unobserved

individual heterogeneity.

3 Data and Empirical Approach

3.1 Data

The data used in this study were derived from the G-SOEP, which is one of the longest

running panel surveys in the world. Since its inception in 1984 (Wave 1) with around 6,000

households, the panel has grown to around 11,000 households over the last 30 years

(Deutsches Institut fur Wissenschaft 2014). The survey collects representative micro-data,

objective as well as subjective indicators to measure social continuity and change of

persons, households and families living in Germany using a multi-step random sampling

process. A response rate of 86 % was obtained in Wave 1, while response rates for each

refreshment sample ranged from 70 to 90 % (Frick 2010). The panel spans over three

generations for some participating households and more than 2,000 persons have taken

part in the survey for over 30 years.

In this study, we focus on German participants aged 18 years and over from the 2003,

2007 and 2011 waves of the G-SOEP on which full information on all relevant data items

were available. The principal advantage of using the G-SOEP is that it is one of the largest

surveys in Germany to collect data on life satisfaction and religiosity as well as detailed

economic and social information on its respondents.

3.1.1 Life Satisfaction Measure

In the G-SOEP, overall life satisfaction is assessed using the following question: ‘‘How

satisfied are you currently, all in all, with your life?’’ Respondents are required to answer

this question on a scale ranging from 0 to 10, where 0 means ‘completely dissatisfied’ and

10 means ‘completely satisfied’. This measure of SWB has been shown to be closely

associated with other more objective measures of happiness (Frey and Stutzer 2002). The

distribution of responses to the life satisfaction question is reported in Table 1 with over

Table 1 The distribution of lifesatisfaction in Germany,2003–2011

Life satisfaction Frequency Percent Cum.

0—‘completely dissatisfied’ 41 0.15 0.15

1 75 0.28 0.43

2 232 0.85 1.28

3 548 2.01 3.29

4 850 3.12 6.41

5 2,740 10.06 16.47

6 3,066 11.25 27.72

7 6,677 24.51 52.23

8 8,890 32.63 84.87

9 3,263 11.98 96.84

10—‘completely satisfied’ 860 3.16 100

E. Sinnewe et al.

123

48 % of participants reporting a life satisfaction score of 8 or higher. To put this into

context, the OECD Better Life Index, ranks Germany 17th out of 34 member countries in

terms of life satisfaction (OECD 2013).

3.1.2 Religiosity Measures

Religiosity was assessed using the following two survey questions which asked respon-

dents about their: (1) religious affiliation; and (2) frequency of attendance at religious

services. As shown in Table 2, religious affiliation was measured by a set of dummy

variables identifying Catholics (29.6 %), Protestants (31.4 %), and Other religions (5 %).

Respondents who reported no-religious affiliation (34.1 %) were chosen as the reference

group in our subsequent regression analysis.

Religious activity was assessed by the following survey item: ‘‘Please indicate the

frequency of each activity: every week; every month, less frequently, never. Attend church

Table 2 Descriptive statistics for the variables used in the analysis, 2003–2011 (N = 27,242)

Variables Description Mean (SD)

Dependent variable

Lifesatisfaction

Overall life satisfaction. (0 = completely dissatisfied;10 = completely satisfied).

7.103 (1.607)

Religious affiliation

No religion 1 = No religion; 0 = otherwise. 0.341

Protestant 1 = Protestant; 0 = otherwise 0.314

Catholic 1 = Catholic; 0 = otherwise 0.296

Other 1 = Other religious affiliation 0 = otherwise 0.050

Religiousattendance

Attendance of religious services (1 = Never; 4 = Every week) 1.679 (0.884)

Social networks

Close friends Number of close friends. 4.428 (4.009)

Social contact How often do you attend social gatherings with friends, relatives etc.(1 = Never; 4 = Every week).

3.231 (0.737)

Controls

Age Age in years. 43.399 (11.706)

Sex Sex. 1.480

Education Years of education. 12.649 (2.724)

Income Log of annual gross income in Euros. 10.068 (0.868)

Married 1 = Married; 0 = otherwise. 0.625

Children Number of children. 1.349 (1.144)

Unemployed 1 = Unemployed; 0 = otherwise. 0.057

Health Self-reported health status (1 = Bad; 5 = Very good). 3.547 (0.843)

Trauma 1 = Negative life event occurred in this or last year; 0 = otherwise. 0.047

WestGermany

1 = West Germany; 0 = otherwise. 0.770

2003 Reference group. 0.308

2007 1 = 2007; 0 = otherwise. 0.351

2011 1 = 2011; 0 = otherwise. 0.341

Religion and Life Satisfaction

123

or other religious events’’. The frequency of attendance at religious services was coded as:

1 = ‘‘never’’; 2 = ‘‘less frequently’’; 3 = ‘‘every month’’; and 4 = ‘‘every week’’.

3.1.3 Social Network Measures

Social networks were measured using the following questions: (1) ‘‘How often do you

attend social gatherings with friends, relatives etc.’’; and (2) ‘‘How many close friends do

you have?’’ The frequency of ‘social gatherings’ was coded as: 1 = ‘‘never’’; 2 = ‘‘less

frequently’’; 3 = ‘‘every month’’; and 4 = ‘‘every week’’. For ‘close friends’, respondents

were asked to specify the number of ‘close friends’ they had.

3.1.4 Control Variables

Guided by the previous empirical literature (Argyle 2001; Diener et al. 2009, 1999), we

included the following control variables in our statistical analysis: age in years; sex

(1 = male; 2 = female); years of education; income (the log of annual gross income in

Euros); marital status (1 = married; 0 = otherwise); the number of children; self-reported

health status (a five point scale ranging from 1 = ‘bad’ to 5 = ‘very good’); unemployment

status (1 = unemployed; 0 = employed); and whether the respondent reported having a

major negative life event in the current or previous year (1 = yes; 0 = no). Moreover, we

also included the following additional control variables to account for the potential influence

of regional differences (1 = the respondent resides in West Germany; 0 = the respondent

resides in East Germany) and period effects (i.e., an indicator variable for wave).

It is worth noting that there is some disagreement in the literature over whether one should

include marital status as a control variable in the current context. The chief question is: if

marital status is thought to be part of one’s social network should it be included as a control

variable? This is particularly important in our situation since we are primarily interested in

establishing whether social networks attenuate the relationship between ‘attendance’ and life

satisfaction. While similar studies traditionally include marital status as a control variable

(e.g., Lim and Putnam 2010) other studies have demonstrated that ‘romantic relationships’—

as opposed to friendships—exert a greater influence on subjective well-being (e.g., Demir

2010). To explore the possible role that marital status may play in the German social milieu,

we estimated our most extensive regression model (Eq. 1 below) with and without our

marital status variable. Our results—not shown but available upon request—demonstrate that

the inclusion of marital status makes very little difference to our findings. In other words, our

estimated regression coefficients for ‘attendance’ and ‘social networks’ do not appreciably

change when marital status is treated as a control variable. Against this background, we elect

to retain marital status as a control variable, which also allows the comparison of our results

with those from other studies (e.g., Lim and Putnam 2010).

Our composite measure of major negative life events was constructed by identifying

whether respondents reported experiencing either one of the following major negative life

events: death of partner, death of child, death of father, death of mother, or separation. Our

indicator variable for regional differences (1 = the respondent resides in West Germany;

0 = the respondent resides in East Germany) was also included for the following reasons:

(1) the vast majority of non-religious people live in East Germany (Religionen in Deu-

tschland 2009); and (2) even after reunification following the fall of the Berlin Wall in

1989, differences in the beliefs about God in West and East Germany continue to widen

(Smith 2012). Descriptive statistics for all variables are reported in Table 2.

E. Sinnewe et al.

123

3.2 Empirical Approach

To examine the association between life satisfaction and religion, we estimated a series of

regression models, with life satisfaction as the dependent variable. In our first regression

model we only include indicator variables for religious affiliation to ascertain whether

different religious traditions may exert differential impacts on life satisfaction. In our

second regression model, we included our extensive range of control variables to determine

whether these factors explain the associations between life satisfaction and religious

affiliation. In our third regression model we introduced attendance at religious services to

examine whether attendance is positively related to life satisfaction. Finally, in our fourth

regression model, we included measures of social networks to determine whether the

association between attendance and life satisfaction is operating through these social

networks. Thus, our most extensive regression model is:

LSit ¼ a þ b1Xit þ b2Rit þ b3Sit þ ai þ lit ð1Þ

In Eq. (1) above, LS is the survey participant’s life satisfaction score, X is a vector of

control variables (i.e., age in years, sex, years of education, unemployment status, income,

marital status, the number of children, self-reported health status, whether the respondent

reported a major negative life event, whether the respondent resides in either West or East

Germany, plus an indicator variable for wave), R is a vector of religious variables (i.e.,

religious affiliation and attendance at religious services), S is our measure of social net-

works (i.e., the number of close friends and frequency of social gatherings), and l is an

i.i.d. error term.

In modelling life satisfaction, a number of studies have recognized that the determinants

of life satisfaction remain practically unchanged whether one models life satisfaction as

either an ordinal (e.g., using an ordered logistic regression model) or cardinal (e.g., using

an OLS regression model) variable (Ferrer-i-Carbonell and Frijters 2004). Thus, for ease of

estimation and interpretability of the regression coefficients, we opt to treat life satisfaction

as a cardinal variable and initially use a conventional ordinary least squared (OLS)

regression model to estimate the association between life satisfaction and religion.

Since we observe the same respondents in 2003, 2007, and 2011, our standard errors are

clustered at the individual level to account for within-person serial correlation. We then

took advantage of the panel nature of G-SOEP to control for unobserved individual het-

erogeneity by estimating the association between life satisfaction and religion using a

fixed-effect (FE) regression model to control for time invariant factors (ai in Eq. 1) such as

cognitive ability, personality, and sex, which may influence life satisfaction and, conse-

quently, reduce the influence associated with omitted variable bias.

4 Results

4.1 Cross-Sectional Regression Results

In Table 3 we present our OLS regression results, which are based on a sample of 27,242

individuals. In Model I we only included our indicator variables for religious affiliation. In

terms of life satisfaction, the estimated regression coefficients indicate that there is a

statistically significant difference between each religious category and the reference group

of ‘no religion’. For example, Model I indicates that Protestants and Catholics had, on

Religion and Life Satisfaction

123

Tab

le3

OL

Sre

gre

ssio

ns

of

reli

gio

non

life

sati

sfac

tion

for

Ger

man

y(n

=2

7,4

24

)

Model

IM

odel

IIM

odel

III

Model

IV

bS

Eb

SE

bS

Eb

SE

Rel

igio

us

affi

liat

ion

Pro

test

ant

0.2

37***

(0.0

29)

0.0

94***

(0.0

27)

0.0

00

(0.0

28)

-0.0

01

(0.0

28)

Cat

holi

c0.3

11***

(0.0

30)

0.1

19***

(0.0

28)

-0.0

20

(0.0

31)

-0.0

20

(0.0

31)

Oth

er0.1

39**

(0.0

58)

-0.0

16

(0.0

52)

-0.1

84***

(0.0

54)

-0.2

32***

(0.0

53)

Contr

ol

var

iable

s

Age

0.0

02**

(0.0

01)

0.0

01

(0.0

01)

0.0

04***

(0.0

01)

Sex

0.1

03***

(0.0

22)

0.1

00***

(0.0

22)

0.0

95***

(0.0

22)

Educa

tion

0.0

28***

(0.0

04)

0.0

25***

(0.0

04)

0.0

19***

(0.0

04)

Inco

me

0.1

04***

(0.0

14)

0.1

07***

(0.0

14)

0.1

14***

(0.0

13)

Mar

ried

0.2

02***

(0.0

24)

0.1

87***

(0.0

24)

0.2

13***

(0.0

24)

Chil

dre

n-

0.0

06

(0.0

11)

-0.0

14

(0.0

11)

-0.0

07

(0.0

10)

Hea

lth

0.8

13***

(0.0

14)

0.8

06***

(0.0

14)

0.7

83***

(0.0

13)

Unem

plo

yed

-0.3

46***

(0.0

44)

-0.3

37***

(0.0

44)

-0.3

11***

(0.0

44)

Tra

um

a-

0.2

44***

(0.0

46)

-0.2

47***

(0.0

46)

-0.2

45***

(0.0

45)

Wes

tG

erm

any

0.3

76***

(0.0

28)

0.3

87***

(0.0

28)

0.3

42***

(0.0

28)

2007

0.0

91***

(0.0

19)

0.0

96***

(0.0

19)

0.0

95***

(0.0

19)

2011

0.1

51***

(0.0

20)

0.1

57***

(0.0

20)

0.1

52***

(0.0

20)

Att

endan

ce0.1

37***

(0.0

13)

0.1

15***

(0.0

13)

Soci

alnet

work

s

Clo

sefr

iends

0.0

19***

(0.0

03)

Soci

algat

her

ings

0.2

38***

(0.0

15)

Const

ant

6.9

3***

(0.0

20)

2.0

75***

(0.1

52)

1.9

99***

(0.1

51)

1.1

32***

(0.1

56)

Adju

sted

R2

0.0

07

0.2

16

0.2

20.2

34

Sta

ndar

der

rors

inpar

enth

eses

**,

and

***

signifi

cant

atp

\0.0

5,

p\

0.0

1,

resp

ecti

vel

y

E. Sinnewe et al.

123

average a 0.24 and 0.31 higher life satisfaction score, respectively, compared to those

respondents who reported no religious affiliation.

In Model II we introduced our extensive set of control variables, which explains around

20 % in the total variation in life satisfaction. The inclusion of these control variables

substantially attenuates the difference between the ‘no religion’ category and the Protestant

and Catholic affiliations categories. A statistically significant positive association was

observed for the following control variables: age (b = 0.002); sex (b = 0.103); education

(b = 0.028); income (b = 0.104); marital status (b = 0.202); health status (b = 0.813);

and residing in West Germany (b = 0.376). Furthermore, statistically significant negative

associations were observed for being unemployed (b = -0.346) and experiencing a

traumatic event (b = -0.244).

In Model III we included our measure of attendance at religious services, which is

statistically significant at the 1 % level (b = 0.137). In comparing Models II and III, the

introduction of the ‘attendance’ variable makes a marginal improvement to our adjusted-R2

value and there is very little change in the estimated coefficients on our control variables.

While the inclusion of ‘attendance’ in Model III only marginally improves our adjusted-R2

value, it does, however, further mitigate the influence of our ‘Protestant’ and ‘Catholic’

variables (which are no longer statistically significant). This implies that attendance at

religious services in Germany may partly account for some of the observed differences in

life satisfaction between religious and non-religious respondents. Interestingly, we now

find that individuals in the ‘Other’ religious category now suffer an extremely large life

satisfaction penalty (b = -0.184; p \ 0.01). The ‘Other’ religious estimates—which is

largely comprised of non-Christians—needs to be interpreted with some caution, since

only 5 % of observations in our sample fall into the ‘Other’ religious category.

In Model IV we introduced our social networks variables. The coefficient on our ‘close

friends’ variable is positive and statistically significant (b = 0.019; p \ 0.01). Our ‘social

gatherings’ variable is also positive and statistically significant (b = 0.238; p \ 0.01). In

essence, these findings indicate that there is a strong association between our measure of

social networks and life satisfaction. While the introduction of our social networks mea-

sures mediates our ‘attendance’ variable it still remains statistically significant (b = 0.115;

p \ 0.01). We also performed Sobel mediation tests (Sobel 1982) and found statistically

significant indirect effects of attendance at religious services on life satisfaction via both

our ‘close friends’ (Z = 8.978; p \ 0.01) and ‘social gatherings’ (Z = 14.970; p \ 0.01)

variables. Moreover, the proportion of the total effect that is mediated through our ‘close

friends’ and ‘social gatherings’ variables are 5.7 % and 16.4 %, respectively.

In essence, this means that social networks—the number of close friends and frequency

of social gatherings—only partially capture some aspects of attendance that influence life

satisfaction. This signifies that attendance at religious services exerts a substantial direct—

or independent—impact on life satisfaction in Germany. These findings also demonstrate

that there is a relatively weak but positive correlation between attendance and social

networks, which is borne out in simple bivariate correlation (r = 0.07; p \ 0.01).

4.2 Panel Regression Results

While the findings reported in our cross-sectional analysis suggest that attendance at

religious services enhances life satisfaction in Germany, we cannot rule out the possibility

that unobserved individual differences between G-SOEP survey respondents are respon-

sible for the results presented in Table 3. As such, we now turn to our FE panel analysis

reported in Table 4.

Religion and Life Satisfaction

123

Tab

le4

Pan

elre

gre

ssio

ns

of

reli

gio

no

nli

fesa

tisf

acti

on

for

Ger

man

y

Mo

del

IM

od

elII

Mo

del

III

Mo

del

IV

Fix

edef

fect

sF

ixed

effe

cts

Ran

dom

effe

cts

Ran

dom

effe

cts

BS

EB

SE

bS

Eb

SE

Pa

nel

A:

Ger

ma

ny

Pro

test

ant

0.0

15

(0.0

73)

-0

.03

9(0

.07

1)

0.1

06

**

*(0

.02

9)

0.0

15

(0.0

27)

Cat

ho

lic

0.1

50

**

(0.0

90)

0.1

13

(0.0

85)

0.1

23

**

*(0

.03

1)

0.0

00

(0.0

30)

Oth

er-

0.3

98

**

*(0

.18

0)

-0

.38

5*

**

(0.1

73)

-0

.153

**

*(0

.05

8)

-0

.209

**

*(0

.05

3)

Att

end

ance

0.0

66

**

*(0

.02

5)

0.0

54

**

*(0

.02

5)

0.1

44

**

*(0

.01

3)

0.1

09

**

*(0

.01

2)

So

cial

net

work

s

Clo

sefr

ien

ds

0.0

08

**

(0.0

04)

0.0

05

(0.0

04)

0.0

21

**

*(0

.00

3)

0.0

17

**

*(0

.00

2)

So

cial

gat

her

ing

s0

.104

**

*(0

.02

2)

0.0

85

**

*(0

.02

1)

0.2

75

**

*(0

.01

5)

0.2

03

**

*(0

.01

4)

Co

nst

ant

6.5

93

**

*(0

.08

8)

-4

.88

4(5

.39

6)

5.8

3*

**

(0.0

53

)1

.53

8*

**

(0.1

54)

Ad

dit

ion

alco

ntr

ols

No

Yes

No

Yes

No

.o

bse

rvat

ion

s2

7,2

42

27

,24

22

7,2

42

27

,24

2

Ad

just

edR

20

.004

0.0

70

––

Pa

nel

B:

Wes

tG

erm

an

y

Pro

test

ant

0.0

78

(0.0

83)

0.0

05

(0.0

79)

-0

.012

(0.0

34

)0

.02

8(0

.03

1)

Cat

ho

lic

0.1

87

**

*(0

.09

4)

0.1

24

(0.0

88)

-0

.049

(0.0

36

)0

.00

1(0

.03

2)

Oth

er-

0.3

69

**

(0.1

92)

-0

.38

4*

**

(0.1

86)

-0

.316

**

*(0

.06

1)

-0

.214

**

*(0

.05

5)

Att

end

ance

0.0

63

**

(0.0

27)

0.0

47

**

(0.0

26)

0.1

48

**

*(0

.01

4)

0.1

07

**

*(0

.01

3)

So

cial

net

work

s

Clo

sefr

ien

ds

0.0

1*

**

(0.0

04)

0.0

07

(0.0

04)

0.0

24

**

*(0

.00

4)

0.0

17

**

*(0

.00

3)

So

cial

gat

her

ing

s0

.093

**

*(0

.02

5)

0.0

67

**

*(0

.02

4)

0.2

56

**

*(0

.01

7)

0.1

95

**

*(0

.01

6)

Co

nst

ant

6.6

78

**

*(0

.10

4)

-1

0.0

91

(8.4

67)

6.0

58

**

*(0

.06

4)

2.1

65

**

*(0

.18

1)

E. Sinnewe et al.

123

Tab

le4

con

tin

ued

Mo

del

IM

odel

IIM

odel

III

Mo

del

IV

Fix

edef

fect

sF

ixed

effe

cts

Ran

dom

effe

cts

Ran

dom

effe

cts

BS

EB

SE

bS

Eb

SE

Ad

dit

ion

alco

ntr

ols

No

Yes

No

Yes

No

.o

bse

rvat

ion

s2

0,9

80

20

,98

02

0,9

80

20

,98

0

Ad

just

edR

20

.00

40

.07

4–

–

Pa

nel

C:

Ea

stG

erm

an

y

Pro

test

ant

-0

.159

(0.1

59)

-0

.142

(0.1

55)

-0

.048

(0.0

71

)-

0.0

42

(0.0

64)

Cat

ho

lic

-0

.173

(0.2

63)

-0

.085

(0.2

84)

0.0

22

(0.1

19

)0

.01

4(0

.10

7)

Oth

er-

0.3

21

(0.3

58)

-0

.248

(0.3

69)

-0

.392

(0.3

14

)-

0.1

52

(0.2

90)

Att

end

ance

0.0

83

(0.0

76)

0.0

78

(0.0

76)

0.1

54

(0.0

42

)0

.11

9*

**

(0.0

39)

So

cial

net

work

s

Clo

sefr

ien

ds

-0

.002

(0.0

09)

-0

.004

(0.0

09)

0.0

17

(0.0

06

)0

.01

4*

**

(0.0

05)

So

cial

gat

her

ing

s0

.14

3*

**

(0.0

46)

0.1

46

**

*(0

.04

4)

0.2

81

(0.0

30

)0

.22

2*

**

(0.0

29)

Co

nst

ant

6.2

44

**

*(0

.17

8)

-0

.768

(6.6

87)

5.6

1(0

.10

7)

0.5

81

**

(0.3

16)

Ad

dit

ion

alco

ntr

ols

No

Yes

No

Yes

No

.o

bse

rvat

ion

s6

,26

26

,26

26

,26

26

,26

2

Ad

just

edR

20

.00

40

.06

7–

–

Sta

nd

ard

erro

rsin

par

enth

eses

**

,an

d*

**

sig

nifi

can

tat

p\

0.0

5,

p\

0.0

1,

resp

ecti

vel

y.

Ad

dit

ion

alco

ntr

ols

com

pri

se:

age

iny

ears

,se

x(f

or

RE

mod

elo

nly

),y

ears

of

edu

cati

on

,u

nem

plo

ym

ent

stat

us,

inco

me,

mar

ital

stat

us,

nu

mb

ero

fch

ild

ren

,se

lf-r

epo

rted

hea

lth

stat

us,

wh

eth

erth

ere

spo

nden

tre

po

rted

am

ajo

rn

egat

ive

life

even

t,p

lus

anin

dic

ato

rv

aria

ble

for

wav

e

Religion and Life Satisfaction

123

In our FE regression analysis we: (1) estimated the association between religious

affiliation, attendance at religious services, and social networks with and without our block

of control variables; and (2) stratified our analysis according to whether G-SOEP

respondents resided in either West Germany or East Germany (Models I and II in Table 4).

Initially, we estimated our FE regression models for Germany as a whole (Panel A, Model

I and Model II). In Model I, we observed a statistically significant positive association

between ‘attendance’ and life satisfaction (b = 0.066; p \ 0.01). Furthermore, we still

observed a positive association between ‘close friends’ (b = 0.008; p \ 0.05) and ‘social

gatherings’ (b = 0.104; p \ 0.01). Turning to Model II in Panel A, the inclusion of our

block of control variables had very limited impact on our estimated regression coefficients

(apart from ‘close friends’ which is no longer statistically significant).

In Panel B of Table 4 the results for West Germany are reported. Turning to Model II in

Panel B the following points are worth noting. In first place, there is a statistically sig-

nificant positive relationship between ‘attendance’ and life satisfaction (b = 0.047;

p \ 0.05). Secondly, there is a positive association between ‘social gatherings’ and life

satisfaction (b = 0.067; p \ 0.01). Finally, the magnitude of the estimated coefficients for

West Germany (Panel B, Model II) are very similar to those for Germany as a whole (Panel

A, Model II).

In Panel C of Table 4 the results for East Germany are reported. Looking at the FE

models in Panel C (i.e., Model I and Model II) it is important to note that religious

involvement does not appear to influence life satisfaction in East Germany (i.e., ‘religious

affiliation’ and ‘attendance’ are not statistically significant). However, it needs to be borne

in mind that there is a strong and statistically significant positive relationship between

frequency of ‘social gatherings’ and life satisfaction in East Germany. Expressed differ-

ently, these results suggest that attendance at religious services in East Germany does not

bolster life satisfaction. In addition, this finding also suggests that attendance at religious

services in East Germany is most likely a chosen activity as opposed to matter of social

compliance or conformity. This observation is, in part, supported by the fact that even after

25 years since the fall of the Berlin Wall there remain stark differences in religious beliefs

between West and East Germany (Smith 2012).

While our FE analysis controls for unobservable heterogeneity and undoubtedly pro-

vides a more stringent empirical assessment of the association between religious

involvement and life satisfaction, it is possible that a random effects (RE) specification

may be more appropriate. In the RE model, it is assumed that the unobserved effect, ai, in

Eq. (1) is uncorrelated with each independent variable across each time period. To explore

this issue further, the results from the RE regression specification are also reported in

Table 4 (i.e., Models III and IV in Panels A, B and C).

While a conceptual argument can be advanced that a FE specification is preferred to a

RE specification on the basis that unobservable variables such as personality are likely to

be highly correlated with our independent variables, we conducted a Hausman specifica-

tion to empirically test whether our FE specifications (i.e., Models I and II in Panels A, B

and C) are favoured to our RE specification (i.e., Models III and IV in Panels A, B and C).

In this statistical test, the null hypothesis (H0) is that the RE specification is the appropriate

specification versus the alternative hypothesis (H1) that the FE specification appropriate.

Based on the results from the Hausman test for Germany (Panel A), West Germany (Panel

B) and East Germany (Panel C) we rejected the null hypothesis and concluded that the FE

model is the appropriate—and hence our preferred—specification.

E. Sinnewe et al.

123

5 Discussion

In this article, we examined the association between life satisfaction and religion for

Germany. Employing data from the G-SOEP survey, we were able to contribute to the

literature by investigating whether attendance at religious services: (1) is positively

associated with life satisfaction; and (2) has an independent impact on life satisfaction after

controlling for the number of ‘close friends’ and frequency of ‘social gatherings’.

With regard to our cross-sectional regression analysis, a number of points are worth

mentioning. In the first place, our results provide further evidence of the importance of a

core set of control variables in estimating life satisfaction (Argyle 2001; Diener et al. 1999;

2009). Indeed, the introduction of our control variables accounts for the vast majority of

the explanatory power in our series of regression models and remains statistically signif-

icant across all four specifications (Table 3). With respect to our block of control variables,

marital status, self-reported health status, and residing in West Germany had the most

substantial positive impact on life satisfaction while unemployment status and experi-

encing a major negative life events had the most sizeable negative impact on life

satisfaction.

In second place, the inclusion of our ‘attendance’ variable in Model III (Table 3)

indicates that there is a statistically significant positive association between attendance at

religious services and life satisfaction. Furthermore, while the inclusion of our social

network variables in Model IV (Table 3) mitigates our ‘attendance’ variable, it remains

statistically significant. This finding, which mirrors results from the U.S. (e.g., Ellison et al.

1989; Greeley and Hout 2006), indicates that attendance at religious services exerts an

independent impact on life satisfaction even after controlling for social networks (i.e., the

number of ‘close friends’ and frequency of ‘social gatherings’).

We also exploited the panel nature of the G-SOEP dataset to further explore the

association between religion and life satisfaction. In our preferred fixed effects (FE)

specification, our results for Germany as a whole (Panel A, Models I and II, Table 4)

indicate that frequency of attendance at religious services exerts an independent impact on

life satisfaction. Similarly, our FE analysis for West Germany (Panel B, Models I and II,

Table 4) also indicates that attendance at religious services exerts an independent influence

on life satisfaction. On the other hand, our FE analysis for East Germany (Panel C, Models

I and II, Table 4) suggests that there is no association between ‘attendance’ and life

satisfaction. More generally, these findings suggest that when analyzing the G-SOEP data

it is important to consider and effectively control for the potential differences between

survey respondents residing in either West or East Germany.

While our findings provide limited support for the ‘social network’ explanation, it is

possible that social networks could, in fact, link religious activity and life satisfaction (Lim

and Putnam 2010). Several researchers have suggested that ‘religious social networks’

confer a number of benefits by providing adherents with a greater sense of belonging and

comfort (e.g., Ellison and George 1994; Haslam et al. 2009; Krause and Wulff 2005;

Krause 2008).

To further explore this possibility, we believe that a profitable avenue of research in the

German context would be for future studies to collect data which draw a clear distinction

between ‘religious social networks’ and ‘secular social networks’. To adequately address

this question, primary data collection would need to focus on collecting information on

religious social networks like the number of congregational friends, strength of religious

identity, and degree of religious homogeneity in one’s social network (Lim and Putnam

2010). This, in turn, would permit researchers to unravel and identify what role ‘religious

Religion and Life Satisfaction

123

social networks’ may play in contemporary German society and whether these results

would mirror those found in the U.S. (Lim and Putnam 2010).

While our panel analysis provides evidence of an association between religious par-

ticipation and life satisfaction it is possible that other changes in the lives of G-SOEP

respondents may have led to the changes in attendance at religious services and life

satisfaction. For example, individuals may decide to self-select into religion based on the

anticipated benefits associated with religious participation and it is conceivable that ben-

efits of religion may be restricted to those who elect to become religious. On the other

hand, individuals may decide to opt out of religion if they do not find happiness in it and

thus persons who leave religion may actually experience an increase in life satisfaction

(Lim and Putnam 2010). While our panel analysis estimates the mean effect of those

participants who experience religious change it does not, however, resolve the potential

problems associated with these ‘joining’ and ‘leaving’ effects. On this issue, we agree with

Lim and Putnam (2010) that additional research is needed to address this problem and that

our findings should be viewed as being indicative.

More generally, the following caveats need to be taken into account when interpreting

our results. In the first place, our study is principally confined to German Christians. This is

an important point as SWB has been shown to vary with regard to culture and nationality.

For example, Diener et al. (2009) has noted that Confucian cultures regard the optimal

level of life satisfaction as one of neutrality while Argyle (1999) has reported that the link

between religion and happiness is, on balance, stronger for Americans than Europeans.

Secondly, it is important to note that finding an association between religiosity and

SWB may also depend on how SWB is measured. For instance, in a review by Lewis and

Cruise (2006) it was reported that research conducted with the Oxford Happiness Inventory

consistently found that religion was associated with happiness while research conducted

using the Depression-Happiness Scale consistently found the opposite.

Finally, measuring life satisfaction with a single survey question is rather limiting. In

the present context, it provides no way to evaluate life satisfaction under different sit-

uations or aspects of our lives. Put differently, it is possible that religion is related to

some but not all aspects of our lives in terms of subjective well-being. Thus, in an effort

to consider alternative aspects of well-being, we re-ran our analysis using ‘self-reported

health status’ and ‘job satisfaction’ as dependent variables. Our results—not shown but

available upon request—were mixed. Our cross-sectional analysis indicates that while

‘attendance’ was associated with ‘self-reported health status’, this association was mit-

igated with the inclusion of social networks (a finding that was mirrored in our FE

analysis). However, a different story emerges when we used ‘job satisfaction’ as a

dependent variable. Our cross-sectional analysis indicates that while ‘attendance’ was

associated with ‘job satisfaction’, this association was attenuated with the inclusion of

social networks. On the other hand, our panel analysis revealed that there was no

association between ‘attendance’ and ‘job satisfaction’. Taken together, this analysis

provides some prima facie evidence that ‘attendance’—at least in the German social

setting—is related to some but not all dimensions of our lives in terms of subjective well-

being.

6 Conclusion

In this paper we examined the association between attendance at religious services and life

satisfaction using panel data from the G-SEOP survey. Our study provides evidence of a

E. Sinnewe et al.

123

positive association between attendance at religious services and life satisfaction for

respondents residing in West Germany. While social networks partially mediate this

relationship for West Germany, there appears to be a remaining direct impact of attendance

on life satisfaction. On the contrary, we find no evidence of an association between

attendance at religious services and life satisfaction for respondents residing in East

Germany. To investigate this relationship further, we believe that there is a need to sep-

arately assess what impact religious and non-religious social networks may play on life

satisfaction in German society.

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