ABSTRACT
This paper presents unique descriptive and explanatory analyses of cross-national variation in work ethic in 44 European countries (European Values Study 2008). A strong work ethic is the conviction that people have a moral duty to work. To explain differences in the adherence of the work ethic between countries two alternative theories are tested: modernisation theory and social institutional theory. Modernisation theory hypothesises that richer, more highly educated and urbanised countries have a weaker work ethic. Alternatively, social institutional theory predicts that countries' religious heritage, generosity of the welfare state and political history can explain differences in work ethic between countries. Multilevel regression models on an unprecedented set of 44 countries show that the modernisation hypotheses are supported. With regard to institutions, it is shown that work ethic is stronger in countries with an Islamic and Orthodox heritage as compared to a Protestant and Catholic heritage and in ex-communist countries and countries with less generous welfare states. When both theories are tested simultaneously, variance decomposition suggests that social institutional theory has more explanatory power than modernisation theory. Religious heritage is shown to be the most important factor to explain variation in work ethic between countries. Thus, although our modern societies become increasingly secularised, religious heritage still impacts our norms and values about work in a significant manner.
Introduction
This paper sets out to describe and explain variation in work ethic in Europe. Work ethic is defined as the conviction that work is a moral duty. It is not about personal motives, preferences or personal work values; involves the moral embeddedness of work (Applebaum 1992; Niles 1999; De Witte 2000). Work ethic is thus a norm referring to people in general. We follow the definition of Ter Bogt et al. (2005: 421): ‘No matter what one's motivation to work is – money, power, social contacts – no matter if one likes certain aspects of a job or not, work ethic precedes these attitudes and evaluations as a core imperative that one should work'.
A strong work ethic has been argued to be beneficial for societies. Weber (1958[1904–1905]) argued that work ethic was the driving force behind capitalism and, consequently, economic growth and prosperity. Although nowadays capitalism seems to be the common economic system regardless of societies’ degree of work ethic, work ethic is still considered to fuel economic growth (Ali et al.1995). A contemporary example is the rise of economic power blocks in Asia, which has been argued to be related to strong work ethics (Niles 1999; Lim and Sin Lay 2003). Following this line of thought, work ethic may also play a role in narrowing the gap in prosperity within Europe. It can be expected that the populations of more prosperous societies feel economically more secure, which makes that their values are aimed at self-expression and autonomy, instead of survival (Inglehart and Welzel 2005), which contradicts a strong work ethic. A decline of the work ethic in the more advanced European countries would give room to upcoming countries to catch up. However, it has not been systematically examined whether the countries that are currently less strongly developed are also the countries with a strong work ethic, and hence presumably with the potential to catch up. This study sets out to describe and explain variation in work ethic between European countries.
Our explanation of the cross-national variation is based on two alternative macro-level theories: modernisation theory and social institutional theory (Gundelach 1994; Inglehart 1997; Hult and Svallfors 2002; Esser 2005). Modernisation theory predicts that countries with higher levels of socio-economic development prioritise ‘postmodern’ values that emphasise individual autonomy and that contradict the moral duty to work, whereas countries with lower affluence will prioritise traditional or ‘modern’ values aimed at security and survival (Inglehart 1990, 1997). Social institutional theory, however, argues that institutional characteristics of countries produce variation in values (Gundelach 1994).
Over the years modernisation theory has been criticized (e.g., Haller 2002), especially for its cultural bias and the idea that social change is a linear process (So 1990). Nevertheless, Gundelach (1994) argues that although these weaknesses limit the use of this theory as a strict theoretical framework for studying social change, it can be used as a broad foundation for creation of hypotheses on value change (Ester et al.1993). Ester et al. (1993) do propose the use of social institutional theory as a way to solve the limitations of modernisation theory, because the former may be able to explain value differences between countries with similar levels of development. This study contributes in a number of ways to the existing literature on work ethic. First, it provides new and unique information on the variation in work ethic between European countries and its predictors, by employing the new 2008 wave of the European Values Study (EVS 2010), covering 47 countries. Second, modernisation theory and social institutional theory are tested simultaneously. Third, by analysing a large number of countries, results will be more reliable than other studies based on a smaller set of countries. Fourth, because we employ a multilevel approach to explain country differences, we can distinguish between composition effects and effects of country characteristics.
Theory
Modernisation theory argues that when countries reach higher levels of socio-economic development, their inhabitants will increasingly emphasise emancipative values (post-modern values) instead of traditional conformity values (modern values) (Welzel et al.2003). This argument is based on a needs-principle; when people experience scarcity, they focus on values that reflect their most pressing needs of security and survival; limiting human choice. When people have access to abundant resources, they can choose from a wider range of possible human activities. This enables them to focus on the higher-ordered needs in the hierarchy of human needs as proposed by Maslow (1954), such as self-expression which emphasises human choice. In addition to this ‘scarcity hypothesis’, Inglehart (1990, 1997) proposed the ‘socialization hypothesis’, arguing that there is a time-lag between changing socio-economic conditions and the shift in values. Values change gradually when older generations die out and are replaced by younger ones. Each of these generations has been brought up in different socio-economic circumstances, and has internalised different values during their youth, which are assumed to remain stable during one's life.
A strong work ethic, expressing that work is a moral duty, can be considered a traditional conformity value, because it tells people what they should do. Consequently, work ethic is expected to be weaker in socio-economically more developed countries. In order to derive more concrete hypotheses about the relationship between modernisation and work ethic, three interrelated processes within the broader process of (post)modernisation are discussed later.
Socio-economic development consists of a set of closely linked changes. First, socio-economic development involves technological innovation, productivity growth and rising incomes (Welzel et al.2003). These processes increase economic growth and prosperity of countries, and as a result they increase the amount of economic resources available to countries’ populations. Living in a country with a high economic prosperity gives all inhabitants a feeling of higher existential security, which makes it possible to focus on ‘higher-ordered’ needs (Maslow 1954) and emancipative values. Work ethic is expected to be weaker in countries with higher degrees of economic prosperity.
Second, the increasing cognitive autonomy in a country (Inglehart and Welzel 2005) refers to a larger proportion of people living in a country who have the ability and the need to make their own autonomous decisions. This will have a large impact on the country's public opinion and political debates. Values that emphasise and stimulate freedom of choice become increasingly important and will affect all people in that country. The level of cognitive autonomy in a country is, among other things, increased by rising educational levels. We expect countries with a highly educated population to have a weak work ethic, net of the individual effect of education, because these countries expose their entire population to a larger extent to values that are aimed at human choice and autonomy.
The third dimension of modernisation refers to increasing social complexity, which results from urbanisation (Welzel et al.2003). Urbanisation changes the type and the frequency of social interactions between people. Cities allow for more human interaction, but on another basis than rural communities do: whereas social ties in rural communities are based on ascription and physical or cognitive dependency, ties in cities are predominantly based on mutual bargaining and choice. The changing social ties as a result of the urbanisation process imply that social control has weakened. In addition, the increasing interaction between people who have very diverse lifestyles makes one more receptive to the idea of human autonomy. Looser social ties, less social control, and the confrontation with diverse lifestyles result in less compliance with conformity values and the emergence of emancipative values. In countries with higher levels of urbanisation, more people will prioritise emancipative values instead of conformity values. This will in turn affect country's public opinion and political debates and result in a national climate that is aimed primarily at human autonomy and freedom of choice. We expect that countries with a higher level of urbanisation show a central tendency toward emancipative values and will have a weaker work ethic than countries that are characterised by a lower level.
Social institutional theory argues that differences and similarities of countries’ institutions can explain differences and similarities in these countries’ value orientations (Gundelach 1994). Institutions are for example churches, welfare states or schools. Social institutions affect the values and behaviour of the individuals living in a country by the formal and informal norms that they produce; they provide people with a set of prescribed behaviours, attitudes, and values within some acceptable boundaries (Ingram and Clay 2000; Schwartz and Sagie 2000). These so-called models for behaviour gradually become taken for granted through repeated use and interaction, which makes institutions endure (Berger and Luckmann 1967; DiMaggio and Powell 1991). This does not mean that all individuals react in the same way to the incentives and disincentives posed by the institutional environment, but people do tend to conform to these institutional logics, which results in observable differences between countries (Parboteeah et al.2009). We now will consider three sources of institutional influence.
Culture, which consists of norms and values, is argued to be path-dependent (Inglehart and Baker 2000) and thus to have been formed by institutional forces for many centuries. One of the most important forces is religious heritage, which is argued to be a defining characteristic of societies (Inglehart 1990; Huntington 1996). In pre-industrial times religion played an extremely important role in everyday live; one could even say that culture was religion (Inglehart 1990). Although religion may be generally less important nowadays, it is argued that the religious heritage still indirectly impacts our contemporary norms and values, because for many centuries, the prescriptions of the church, also those with regard to work have been explicated and reinforced throughout society as a whole. Over time, these norms have become institutionalised and shared by all members in society (Parboteeah et al.2009). Thus even if countries have become secularised through the process of modernisation, religious values and norms are still deeply entrenched in countries’ collective norms and value-system. As a result, they will still affect daily life even if people are not religious and are not aware of the possibility that their own norms and values have their origin in religion.
Earlier research has pointed out that a country's (traditional) religious denomination is an important predictor of work ethic and work values in general (e.g., Niles 1999; Parboteeah et al.2009). Although work ethic has traditionally particularly been linked to Protestantism (e.g., Weber 1958[1904–1905]), more recent studies have shown that all major religions prescribe work as an individual's obligation (Parboteeah et al.2009). With regard to variation in work ethic between countries with different religious heritages, the literature is very limited. Only on the individual level some evidence is found for differences between the four major religions (Roman Catholic, Protestant, Islam and Orthodox) in Europe. Greeley (1989) argues that because Protestants are more likely to emphasise personal responsibility than Catholics, they will also be more likely to emphasise a work ethic. However, empirical evidence shows that there are no or small differences in the adherence of the work ethic between Protestantism and Catholicism (Greeley 1989; Ali et al.1995; Arslan 2001; Arrunada 2009). With regard to the Islam, the Quran states that hard work and dedication towards work are virtues; that sufficient effort should be put in one's work; and that work is regarded as an obligation for every capable individual (Yousef 2001). Studies showed that Islamic managers have a stronger work ethic than Protestant managers (Arslan 2000, 2001). With regard to Orthodoxy, Ardichvili (2006, 2009) argues that Orthodox believers were expected not only to have spiritual goals, but also pursue worthy earthly vocations by working hard. There seems to be a positive relation between Orthodoxy and a strong work ethic, but there is, to our knowledge, no literature on the comparison of Orthodoxy with other religions. Although results of these individual-level studies cannot be directly translated to the country level and are not representative for the full range of societies we examine, we argue that individual-level rankings of denominations regarding work ethic can be extended to the country level since it is the religious content, which is unrelated to the level of analysis, that determines to what extent work is seen as a moral duty. For Orthodoxy we have no a priori expectations, because the literature provides no evidence on that.
The second institution we consider is the welfare state. Generous welfare states are often criticised for decreasing the incentive to work, because the difference between salaries and unemployment benefits is relatively small and because there are only limited monitoring possibilities, which creates ‘free-riders’ (Lindbeck 1995). From this point of view, a generous welfare state could be argued to signal that work is not a duty to all; it spreads the view that people in need of social assistance should not be blamed but be provided help. As explained before, such signals and norms become internalised in the population with a weaker work ethic as a result. An additional explanation for a negative relationship between a generous welfare state and work ethic can be derived from the scarcity hypothesis: people prioritise values that are aimed at human autonomy – which include a weak work ethic –if their basic needs are assured. The safety-net offered by generous welfare states provides these basic needs and security. In sum, we expect that work ethic is weaker in countries with a generous welfare state. Note that more recent literature argues that, alternatively, welfare states may contribute to reciprocity between duties and rights (e.g., Mau 2004) implying that higher generosity leads to a stronger work ethic.
Third, of all the 44 countries under study in this paper, half have been under communist rule during the second half of the twentieth century. Countries under communist rule operated under a planned command economy, instead of a market economy. This entailed that full employment was guaranteed. Ardichvili (2009) argues that during the Soviet period work was considered the most honoured activity, whereas unemployment was labelled as ‘parasitism’ (Aslund 2007). Work ethic as a moral duty for all persons in society was strongly propagated by the communist regime. But note that believing that everyone in society should work is not the same as working hard yourself. Several authors (e.g., Lipset 1992; Neimanis 1997; Pučėtaitė and Lämsä 2008) claimed that personal work effort, motivation, and productivity were corroded by the communist ideology. Nevertheless, given our definition of work ethic as a moral duty to work, we expect that work ethic will be stronger in ex-communist countries compared to other countries.
Data and measurement
We use the fourth (2008) wave of the EVS (2010), enriched by country characteristics from external data sources. The EVS covers 47 European countries. In each country, a random sample of 1500 respondents aged 18 and older completed a standardised questionnaire in face-to-face interviews. We left out Kosovo and Iceland because information on some country characteristics was lacking and Azerbaijan following the advice of the EVS-team. We included only respondents aged between 18 and 80 years in the sample. Our analyses are based on 61,112 (95.7%) cases from 44 European countries (Table 1).
Country . | valid N . | Work ethica . | GDP per capitab . | Education indexc . | Urban populationd . | Religious heritagee . | Communist historyf . | Fiscal freedomg . |
---|---|---|---|---|---|---|---|---|
The Netherlands | 1434 | 3.13 | 41,247 | 0.99 | 81.5 | Protestant | No | 51.6 |
Finland | 1111 | 3.23 | 37,897 | 0.99 | 84.4 | Protestant | No | 64.3 |
Sweden | 1114 | 3.27 | 38,432 | 0.97 | 84.5 | Protestant | No | 32.7 |
Northern Ireland | 465 | 3.27 | 36,656 | 0.96 | 73.3 | Protestant | No | 61.2 |
Belgium | 1462 | 3.31 | 36,656 | 0.97 | 97.3 | Catholic | No | 43.9 |
United Kingdom | 1417 | 3.31 | 36,981 | 0.96 | 73.3 | Protestant | No | 61.2 |
Croatia | 1456 | 3.39 | 17,362 | 0.92 | 57.1 | Catholic | Yes | 68.8 |
Switzerland | 1201 | 3.43 | 43,760 | 0.94 | 73.5 | Protestant | No | 68.0 |
France | 1409 | 3.45 | 34,633 | 0.98 | 83.4 | Catholic | No | 53.2 |
Latvia | 1455 | 3.46 | 17,753 | 0.96 | 67.9 | Protestant | Yes | 83.4 |
Ireland | 942 | 3.47 | 42,754 | 0.99 | 61.2 | Catholic | No | 71.5 |
Poland | 1445 | 3.48 | 18,522 | 0.95 | 61.2 | Catholic | Yes | 68.6 |
Denmark | 1453 | 3.52 | 38,818 | 0.99 | 86.4 | Protestant | No | 35.0 |
Lithuania | 1450 | 3.52 | 19,312 | 0.97 | 66.8 | Catholic | Yes | 86.3 |
Malta | 1428 | 3.52 | 24,601 | 0.89 | 94.2 | Catholic | No | 61.3 |
Spain | 1404 | 3.54 | 30,934 | 0.98 | 77.1 | Catholic | No | 54.5 |
Estonia | 1453 | 3.55 | 21,219 | 0.96 | 69.4 | Protestant | Yes | 86.0 |
Bosnia Herzegovina | 1484 | 3.56 | 8140 | 0.87 | 47.2 | Muslim | Yes | 73.7 |
Russian Federation | 1421 | 3.56 | 17,407 | 0.93 | 73.1 | Orthodox | Yes | 79.2 |
Norway | 1087 | 3.58 | 56,343 | 0.99 | 78.5 | Protestant | No | 50.3 |
Belarus | 1459 | 3.60 | 13,686 | 0.96 | 73.4 | Orthodox | Yes | 81.0 |
Czech Republic | 1727 | 3.60 | 27,036 | 0.94 | 73.5 | Catholic | Yes | 71.3 |
Luxembourg | 1583 | 3.64 | 83,058 | 0.98 | 84.6 | Catholic | No | 65.4 |
Serbia | 1473 | 3.66 | 11,751 | 0.89 | 55.3 | Orthodox | Yes | 84.1 |
Slovenia | 1301 | 3.66 | 30,338 | 0.97 | 49.9 | Catholic | Yes | 62.4 |
Montenegro | 1488 | 3.68 | 13,113 | 0.89 | 61.6 | Orthodox | Yes | 91.3 |
Italy | 1424 | 3.70 | 30,857 | 0.97 | 68.0 | Catholic | No | 54.3 |
Ukraine | 1445 | 3.70 | 8009 | 0.96 | 68.3 | Orthodox | Yes | 79.0 |
Austria | 1463 | 3.72 | 40,462 | 0.96 | 67.0 | Catholic | No | 51.2 |
Germany | 1982 | 3.72 | 36,107 | 0.95 | 73.6 | Protestant | No | 58.4 |
Greece | 1436 | 3.78 | 31,704 | 0.98 | 60.9 | Orthodox | No | 65.6 |
Slovak Republic | 1425 | 3.81 | 23,866 | 0.93 | 55.3 | Catholic | Yes | 89.4 |
Macedonia | 1464 | 3.83 | 9708 | 0.88 | 59.2 | Orthodox | Yes | 88.1 |
Northern Cyprus | 490 | 3.84 | 10,506 | 0.83 | 68.5 | Muslim | No | 77.7 |
Hungary | 1476 | 3.85 | 20,632 | 0.96 | 67.2 | Catholic | Yes | 70.0 |
Moldova | 1508 | 3.85 | 3413 | 0.90 | 45.1 | Orthodox | Yes | 83.0 |
Romania | 1430 | 3.85 | 13,568 | 0.92 | 56.1 | Orthodox | Yes | 85.6 |
Armenia | 1448 | 3.87 | 5833 | 0.91 | 64.2 | Orthodox | Yes | 89.0 |
Portugal | 1446 | 3.89 | 22,555 | 0.93 | 59.2 | Catholic | No | 61.3 |
Albania | 1510 | 3.90 | 7302 | 0.89 | 49.3 | Muslim | Yes | 90.3 |
Georgia | 1431 | 3.93 | 5323 | 0.92 | 52.6 | Orthodox | Yes | 90.7 |
Cyprus | 960 | 4.02 | 29,335 | 0.91 | 69.9 | Orthodox | No | 78.2 |
Bulgaria | 1443 | 4.07 | 13,200 | 0.93 | 70.8 | Orthodox | Yes | 82.7 |
Turkey | 2209 | 4.23 | 13,912 | 0.83 | 68.5 | Muslim | No | 77.7 |
Country . | valid N . | Work ethica . | GDP per capitab . | Education indexc . | Urban populationd . | Religious heritagee . | Communist historyf . | Fiscal freedomg . |
---|---|---|---|---|---|---|---|---|
The Netherlands | 1434 | 3.13 | 41,247 | 0.99 | 81.5 | Protestant | No | 51.6 |
Finland | 1111 | 3.23 | 37,897 | 0.99 | 84.4 | Protestant | No | 64.3 |
Sweden | 1114 | 3.27 | 38,432 | 0.97 | 84.5 | Protestant | No | 32.7 |
Northern Ireland | 465 | 3.27 | 36,656 | 0.96 | 73.3 | Protestant | No | 61.2 |
Belgium | 1462 | 3.31 | 36,656 | 0.97 | 97.3 | Catholic | No | 43.9 |
United Kingdom | 1417 | 3.31 | 36,981 | 0.96 | 73.3 | Protestant | No | 61.2 |
Croatia | 1456 | 3.39 | 17,362 | 0.92 | 57.1 | Catholic | Yes | 68.8 |
Switzerland | 1201 | 3.43 | 43,760 | 0.94 | 73.5 | Protestant | No | 68.0 |
France | 1409 | 3.45 | 34,633 | 0.98 | 83.4 | Catholic | No | 53.2 |
Latvia | 1455 | 3.46 | 17,753 | 0.96 | 67.9 | Protestant | Yes | 83.4 |
Ireland | 942 | 3.47 | 42,754 | 0.99 | 61.2 | Catholic | No | 71.5 |
Poland | 1445 | 3.48 | 18,522 | 0.95 | 61.2 | Catholic | Yes | 68.6 |
Denmark | 1453 | 3.52 | 38,818 | 0.99 | 86.4 | Protestant | No | 35.0 |
Lithuania | 1450 | 3.52 | 19,312 | 0.97 | 66.8 | Catholic | Yes | 86.3 |
Malta | 1428 | 3.52 | 24,601 | 0.89 | 94.2 | Catholic | No | 61.3 |
Spain | 1404 | 3.54 | 30,934 | 0.98 | 77.1 | Catholic | No | 54.5 |
Estonia | 1453 | 3.55 | 21,219 | 0.96 | 69.4 | Protestant | Yes | 86.0 |
Bosnia Herzegovina | 1484 | 3.56 | 8140 | 0.87 | 47.2 | Muslim | Yes | 73.7 |
Russian Federation | 1421 | 3.56 | 17,407 | 0.93 | 73.1 | Orthodox | Yes | 79.2 |
Norway | 1087 | 3.58 | 56,343 | 0.99 | 78.5 | Protestant | No | 50.3 |
Belarus | 1459 | 3.60 | 13,686 | 0.96 | 73.4 | Orthodox | Yes | 81.0 |
Czech Republic | 1727 | 3.60 | 27,036 | 0.94 | 73.5 | Catholic | Yes | 71.3 |
Luxembourg | 1583 | 3.64 | 83,058 | 0.98 | 84.6 | Catholic | No | 65.4 |
Serbia | 1473 | 3.66 | 11,751 | 0.89 | 55.3 | Orthodox | Yes | 84.1 |
Slovenia | 1301 | 3.66 | 30,338 | 0.97 | 49.9 | Catholic | Yes | 62.4 |
Montenegro | 1488 | 3.68 | 13,113 | 0.89 | 61.6 | Orthodox | Yes | 91.3 |
Italy | 1424 | 3.70 | 30,857 | 0.97 | 68.0 | Catholic | No | 54.3 |
Ukraine | 1445 | 3.70 | 8009 | 0.96 | 68.3 | Orthodox | Yes | 79.0 |
Austria | 1463 | 3.72 | 40,462 | 0.96 | 67.0 | Catholic | No | 51.2 |
Germany | 1982 | 3.72 | 36,107 | 0.95 | 73.6 | Protestant | No | 58.4 |
Greece | 1436 | 3.78 | 31,704 | 0.98 | 60.9 | Orthodox | No | 65.6 |
Slovak Republic | 1425 | 3.81 | 23,866 | 0.93 | 55.3 | Catholic | Yes | 89.4 |
Macedonia | 1464 | 3.83 | 9708 | 0.88 | 59.2 | Orthodox | Yes | 88.1 |
Northern Cyprus | 490 | 3.84 | 10,506 | 0.83 | 68.5 | Muslim | No | 77.7 |
Hungary | 1476 | 3.85 | 20,632 | 0.96 | 67.2 | Catholic | Yes | 70.0 |
Moldova | 1508 | 3.85 | 3413 | 0.90 | 45.1 | Orthodox | Yes | 83.0 |
Romania | 1430 | 3.85 | 13,568 | 0.92 | 56.1 | Orthodox | Yes | 85.6 |
Armenia | 1448 | 3.87 | 5833 | 0.91 | 64.2 | Orthodox | Yes | 89.0 |
Portugal | 1446 | 3.89 | 22,555 | 0.93 | 59.2 | Catholic | No | 61.3 |
Albania | 1510 | 3.90 | 7302 | 0.89 | 49.3 | Muslim | Yes | 90.3 |
Georgia | 1431 | 3.93 | 5323 | 0.92 | 52.6 | Orthodox | Yes | 90.7 |
Cyprus | 960 | 4.02 | 29,335 | 0.91 | 69.9 | Orthodox | No | 78.2 |
Bulgaria | 1443 | 4.07 | 13,200 | 0.93 | 70.8 | Orthodox | Yes | 82.7 |
Turkey | 2209 | 4.23 | 13,912 | 0.83 | 68.5 | Muslim | No | 77.7 |
aMeasured on a scale from 1 to 5: higher scores imply a stronger work ethic.
bData for 2009, corrected for Purchasing Power Parity (IMF 2008).
cData for 2007 (UNDP 2007), based on adult literacy rate and the gross enrolment ratio in primary, secondary and tertiary education.
dThe percentage of inhabitants that live in urban areas, based on national census data: average calculated over 2005 and 2010 (UNdata 2009).
eHistorical dominant denomination (Inglehart 1990: 440; Verbakel and Jaspers 2010).
fIndicator for Communist/State Socialist government in period after World War II.
gData for 2008 (The Heritage Foundation 2008), based on the top tax rate on individual income and on corporate income and the total tax burden as a percentage of GDP.
NB: Correlations between linear macro variables are: GDP-Education Index: 0.619, GDP-Urban population: 0.604, GDP- Fiscal freedom: −0.663, Education index-urban population: 0.453, Education Index-Fiscal freedom: −0.564, urban population-Fiscal freedom: −0.632.
Work ethic has been composed of five items: ‘To fully develop your talents, you need to have a job’, ‘It is humiliating to receive money without having to work for it’, ‘People who don't work turn lazy’, ‘Work is a duty towards society’, and ‘Work should always come first, even if it means less spare time’. These items reflect a secular functional approach to the concept of work; there is no explicit connection with religious beliefs (Jahoda 1982; De Witte 2000). Respondents rated the items on a 5-point scale. We constructed a scale based on the averaged sum of at least three valid scores on the five work ethic items1 to allow for straightforward interpretation. Note that the correlation between mean scores and factor scores is very high (r=0.998).2 The Cronbach's alpha of the scale ranges from 0.58 in Armenia and Norway to 0.79 in Czech Republic. On average, the Cronbach's alpha is 0.70, which is generally considered to be sufficient.3 The work ethic measure meets the requirements for configural invariance, which means that the configuration of salient and non-salient factor loadings is the same in all countries (Steenkamp and Baumgartner 1998).4 The mean work ethic score in the final sample of 61,112 respondents is 3.65 on a scale of 1 (weak work ethic) to 5 (strong work ethic).
Economic security has been measured by the Gross Domestic Product (GDP) per capita, corrected for purchase power parity (PPP), expressed in thousands of US dollars (IMF 2008), covering the year 2009. Cognitive autonomy has been measured by the Education Index (United Nations Development Program, version 2007). It is a component of the Human Development Index, and is based on the adult literacy rate and the gross enrolment ratio in primary, secondary and tertiary education. Social complexity has been measured by the percentage of inhabitants who live in urban areas (United Nations World Urbanization Prospects, average of 2 years: 2005 and 2010).
To measure religious heritage, we used the classification published by Inglehart (1990: 440) and Verbakel and Jaspers (2010), distinguishing Roman Catholic, Protestant, Orthodox, and Muslim countries, and we extended it to countries that were not in these samples. Inglehart (1990) used this classification as an indicator for the preindustrial cultural heritage of societies; it thus refers to societies’ dominant religion in pre-industrial times. Of course, this classification of countries is open to discussion. One could argue that there are for instance countries with a mixed religious heritage (e.g., Jagodzinski 2009). However, robustness checks, leaving out six supposedly mixed countries (Germany, Latvia, Albania, Macedonia, Montenegro and Bosnia Federation) did not yield different results. Communist history was measured by a dummy variable. Generosity of the welfare state was measured by the fiscal freedom of a country. The measure of fiscal freedom (The Heritage Foundation 2008) was comprised of three components: the top tax rate on individual income and on corporate income and the total tax burden as a percentage of GDP. Each of these variables was weighted equally. We assume that a high tax burden goes together with a generous welfare state, although it does not explicitly address where governments spend the tax money on. Information on the proportion of GDP spent on social protection was only available for a much smaller set of countries, but for this restricted set of countries (N=30) the correlation between the two measurements of generosity of the welfare state amounts to 0.80.5 Scores on the fiscal freedom measure can vary from 0 to 100 and a higher score implies a lower tax burden and hence a less generous welfare state. The country-level variables are correlated (see note in Table 1), but multicollinearity checks showed that there is no reason to suspect multicollinearity; all VIF scores are below 4 (Cohen et al. 2003).
In our models we include a number of individual-level controls. Household income is corrected for purchase power parity and is measured in thousands of Euro's per month. Education is measured by the first digit of the International Standard Classification of Education (ISCED). Size of town indicates the degree of urbanisation of the respondents’ place of residence and has eight categories ranging from under 2000 inhabitants to over 500,000 inhabitants. Religious denomination was measured by seven dummy variables: Protestant, Roman Catholic, Muslim, Orthodox, other, none and missing. Employment status was coded in five dummy variables: being employed, not employed (retired persons excluded), unemployed, retired and missing. We also included age of the respondent and a dummy indicator for male respondents. We control for these individual characteristics because we want to assess the effects of country characteristics net of composition effects resulting from differences between countries’ work force composition, age distribution and gender composition. Missing values of linear variables have been imputed with the country-mean and are controlled for by dummy variables.6Table 2 shows descriptive information on all dependent and independent variables.
. | Minimum . | Maximum . | Mean . | Standard deviation . |
---|---|---|---|---|
Dependent variable | ||||
Work ethic | 1 | 5 | 3.65 | 0.76 |
Country characteristics | ||||
GDP (PPP) per capita (×1000) | 3.41 | 83.06 | 25.05 | 15.59 |
Education index | 0.83 | 0.99 | 0.94 | 0.04 |
% Urban population | 45.06 | 97.34 | 68.26 | 12.11 |
Religious heritage | ||||
Roman Catholic | 0.37 | |||
Protestant | 0.23 | |||
Muslim | 0.09 | |||
Orthodox | 0.30 | |||
Communist history | 0.53 | |||
Fiscal Freedom | 32.7 | 91.3 | 70.44 | 15.08 |
Individual variables | ||||
Monthly household income (×1000) | 0 | 14.73 | 1.29 | 1.21 |
Education | 0 | 6 | 3.09 | 1.35 |
Size of town | 1 | 8 | 4.36 | 2.40 |
Religious denomination | ||||
Roman Catholic | 0.29 | |||
Protestant | 0.11 | |||
Muslim | 0.08 | |||
Orthodox | 0.24 | |||
Other | 0.03 | |||
None | 0.25 | |||
Missing | 0.01 | |||
Employment status | ||||
Employed | 0.52 | |||
Unemployed | 0.10 | |||
Not employed | 0.17 | |||
Retired | 0.21 | |||
Missing | 0.01 | |||
Age | 18 | 80 | 45.93 | 16.83 |
Male | 0.44 |
. | Minimum . | Maximum . | Mean . | Standard deviation . |
---|---|---|---|---|
Dependent variable | ||||
Work ethic | 1 | 5 | 3.65 | 0.76 |
Country characteristics | ||||
GDP (PPP) per capita (×1000) | 3.41 | 83.06 | 25.05 | 15.59 |
Education index | 0.83 | 0.99 | 0.94 | 0.04 |
% Urban population | 45.06 | 97.34 | 68.26 | 12.11 |
Religious heritage | ||||
Roman Catholic | 0.37 | |||
Protestant | 0.23 | |||
Muslim | 0.09 | |||
Orthodox | 0.30 | |||
Communist history | 0.53 | |||
Fiscal Freedom | 32.7 | 91.3 | 70.44 | 15.08 |
Individual variables | ||||
Monthly household income (×1000) | 0 | 14.73 | 1.29 | 1.21 |
Education | 0 | 6 | 3.09 | 1.35 |
Size of town | 1 | 8 | 4.36 | 2.40 |
Religious denomination | ||||
Roman Catholic | 0.29 | |||
Protestant | 0.11 | |||
Muslim | 0.08 | |||
Orthodox | 0.24 | |||
Other | 0.03 | |||
None | 0.25 | |||
Missing | 0.01 | |||
Employment status | ||||
Employed | 0.52 | |||
Unemployed | 0.10 | |||
Not employed | 0.17 | |||
Retired | 0.21 | |||
Missing | 0.01 | |||
Age | 18 | 80 | 45.93 | 16.83 |
Male | 0.44 |
Source: European Values Study, wave 2008; Listwise deletion of missing values, N=61,112.
Results
Figure 1 maps countries' average level of work ethic (see Table 1). Scores vary between 3.13 and 4.23 on a scale of 1–5, implying that Europeans generally do not reject the idea that work is a moral duty, but that on average support is not very strong. Many of the higher scores can be found in Eastern Europe with Turkey and Bulgaria having the strongest work ethic. Southern European countries also have a relatively strong work ethic, especially compared to the countries in Western and Northern Europe. Apart from these observations, the map does not reveal a clear pattern. Multilevel regression analysis will provide tests of our hypotheses.
Work ethic in 45 European countries (European Values Study, wave 2008)
Table 3 presents the effects of the individual-level controls and informs about the between-country variance that can be explained by composition effects. Model 1 is the empty model which is used as a baseline for the variance decomposition. We can see that approximately 10% of the unexplained variance is at the country level and 90% is at the individual level. Model 2 shows that, as expected, the individual level modernisation indicators income, educational level and size of the town have a negative effect on work ethic. Roman Catholics and Muslims have a stronger work ethic than Protestants, while people with no religion have a weaker work ethic. In addition, the unemployed and non-employed have a weaker and the retired a stronger work ethic than the employed. Older people have a stronger work ethic than younger people,7 and men have a stronger work ethic than women. The individual characteristics explain only 3.6% of the between-country variance. We observe that, if our selection of individual level predictors is appropriate, there is ample room to expect effects of country characteristics.
. | Model 1 . | Model 2 . | ||
---|---|---|---|---|
. | b . | SE . | b . | SE . |
Individual level controls | ||||
Household income | −0.010** | 0.003 | ||
Education (0–6) | −0.031** | 0.002 | ||
Size of town (1–8) | −0.018** | 0.001 | ||
Personal religious denomination | ||||
(Protestant = ref.) | ||||
Roman-Catholic | 0.072** | 0.014 | ||
Muslim | 0.136** | 0.021 | ||
Orthodox | 0.013 | 0.016 | ||
Other | −0.007 | 0.021 | ||
None | −0.056** | 0.013 | ||
Employment status | ||||
(Employed = ref.) | ||||
Unemployed | −0.143** | 0.011 | ||
Not employed | −0.152** | 0.009 | ||
Retired | 0.027** | 0.010 | ||
Age | 0.005** | 0.000 | ||
Male | 0.060** | 0.006 | ||
Intercept | 3.635** | 0.036 | 3.581** | 0.040 |
N Individuals | 61,112 | 61,112 | ||
N countries | 44 | 44 | ||
Variance at individual level | 0.515 | 0.489 | ||
Variance at country level | 0.055 | 0.053 | ||
% Country variance explained vs Model 1 | 3.6% |
. | Model 1 . | Model 2 . | ||
---|---|---|---|---|
. | b . | SE . | b . | SE . |
Individual level controls | ||||
Household income | −0.010** | 0.003 | ||
Education (0–6) | −0.031** | 0.002 | ||
Size of town (1–8) | −0.018** | 0.001 | ||
Personal religious denomination | ||||
(Protestant = ref.) | ||||
Roman-Catholic | 0.072** | 0.014 | ||
Muslim | 0.136** | 0.021 | ||
Orthodox | 0.013 | 0.016 | ||
Other | −0.007 | 0.021 | ||
None | −0.056** | 0.013 | ||
Employment status | ||||
(Employed = ref.) | ||||
Unemployed | −0.143** | 0.011 | ||
Not employed | −0.152** | 0.009 | ||
Retired | 0.027** | 0.010 | ||
Age | 0.005** | 0.000 | ||
Male | 0.060** | 0.006 | ||
Intercept | 3.635** | 0.036 | 3.581** | 0.040 |
N Individuals | 61,112 | 61,112 | ||
N countries | 44 | 44 | ||
Variance at individual level | 0.515 | 0.489 | ||
Variance at country level | 0.055 | 0.053 | ||
% Country variance explained vs Model 1 | 3.6% |
Source: European Values Study, wave 2008; **p<0.01; *p<0.05.
Table 4 presents models in which the three indicators of modernisation are added to the individual model. The indicators are first included separately (Models 3, 4 and 5), and then simultaneously (Model 6). The effect of GDP is negative, as expected.8 Differences between countries with respect to economic modernisation add 21.9% to the explanation of the between-country variance. The second indicator of modernisation, the Education Index, also supports the idea of modernisation. The Education Index is negatively related to work ethic and adds 30% to the explanation of the country variance. The effect of the third indicator of modernisation, urbanisation, is also in the expected direction: higher levels of urbanisation are associated with lower levels of work ethic. It explains an additional 21.9% of the country variance on top of the variance explained in Model 2.
. | Model 3 . | Model 4 . | Model 5 . | Model 6 . | ||||
---|---|---|---|---|---|---|---|---|
. | b . | SE . | b . | SE . | b . | SE . | b . | SE . |
Modernization | ||||||||
GDP per capita (×1000) | −0.007** | 0.002 | −0.001 | 0.003 | ||||
Education Index | −3.155** | 0.701 | −2.340** | 0.867 | ||||
% Urban population | −0.009** | 0.003 | −0.005 | 0.003 | ||||
Variance at individual level | 0.489 | 0.489 | 0.489 | 0.489 | ||||
Variance at country level | 0.041 | 0.036 | 0.041 | 0.033 | ||||
Additional country level variance explained compared to Model 2 | 21.9% | 30.0% | 21.9% | 36.4% | ||||
N Individuals | 61,112 | 61,112 | 61,112 | 61,112 | ||||
N countries | 44 | 44 | 44 | 44 |
. | Model 3 . | Model 4 . | Model 5 . | Model 6 . | ||||
---|---|---|---|---|---|---|---|---|
. | b . | SE . | b . | SE . | b . | SE . | b . | SE . |
Modernization | ||||||||
GDP per capita (×1000) | −0.007** | 0.002 | −0.001 | 0.003 | ||||
Education Index | −3.155** | 0.701 | −2.340** | 0.867 | ||||
% Urban population | −0.009** | 0.003 | −0.005 | 0.003 | ||||
Variance at individual level | 0.489 | 0.489 | 0.489 | 0.489 | ||||
Variance at country level | 0.041 | 0.036 | 0.041 | 0.033 | ||||
Additional country level variance explained compared to Model 2 | 21.9% | 30.0% | 21.9% | 36.4% | ||||
N Individuals | 61,112 | 61,112 | 61,112 | 61,112 | ||||
N countries | 44 | 44 | 44 | 44 |
Source: European Values Study, wave 2008; **p<0.01; *p<0.05.
Note: Controlled for individual characteristics shown in Table 3, Model 2.
Model 6 combines the effects of the three modernisation indicators. Interestingly, in this model only the effect of the Educational Index is significant. We note that this does not mean that economic modernisation is not important, since growing prosperity and educational expansion go hand in hand. We evaluate the effect size of the Education Index by its maximum effect, which is defined by the product of the range of the Index (0.99 minus 0.83 = 0.16) and the effect in Model 4 (−3.155). The maximum effect is −0.51, which is quite substantial since the range in work ethic between countries is 1.1 (4.23–3.13). We conclude that modernisation is clearly associated with the cross-national variation in work ethic, over and above the effects of composition.
In Table 5 the effects of social institutions on work ethic are presented. Models 7, 8 and 9 again show the separate effects of the three institutions we distinguish, and Model 10 shows the effects when they are included simultaneously. Model 7 shows that the four European Muslim countries have the strongest work ethic, followed by the Orthodox countries (difference is not significant). Catholic countries have a weaker work ethic, but it is significantly stronger than in Protestant countries, which clearly display the weakest work ethic. These results are partly in line with our expectations. The idea that Muslim countries have a strong work ethic is supported, but that people living in Protestant countries have a significant lower work ethic than Catholic countries is surprising. However, it is important to note that Protestant countries have much higher scores on the modernisation characteristics. We will address this issue later. In terms of explained variance, this variable explains an additional 51% of the unexplained variance at the country level, which is more than any of the modernisation variables. This implies that traditional denomination is a very important predictor of countries’ work ethic.
. | Model 7 . | Model 8 . | Model 9 . | Model 10 . | Model 11 . | |||||
---|---|---|---|---|---|---|---|---|---|---|
. | b . | SE . | b . | SE . | b . | SE . | b . | SE . | b . | SE . |
Context | ||||||||||
Historical religious denomination | ||||||||||
(Protestant = ref.) | ||||||||||
Roman Catholic | 0.142* | 0.063 | 0.138* | 0.062 | 0.125 | 0.064 | ||||
Muslim | 0.432** | 0.095 | 0.383** | 0.093 | 0.304* | 0.142 | ||||
Orthodox | 0.403** | 0.066 | 0.342** | 0.079 | 0.349** | 0.079 | ||||
Communist history | 0.143* | 0.066 | −0.089 | 0.069 | ||||||
Fiscal Freedom | 0.009** | 0.002 | 0.005* | 0.003 | ||||||
Education Index | −1.117 | 0.935 | ||||||||
Variance at individual level | 0.489 | 0.489 | 0.489 | 0.489 | 0.489 | |||||
Variance at country level | 0.025 | 0.048 | 0.036 | 0.023 | 0.025 | |||||
Additional country level variance explained compared to Model 2 | 51% | 11% | 31% | 54.6% | 51% | |||||
N Individuals | 61,112 | 61,112 | 61,112 | 61,112 | 61,112 | |||||
N countries | 44 | 44 | 44 | 44 | 44 |
. | Model 7 . | Model 8 . | Model 9 . | Model 10 . | Model 11 . | |||||
---|---|---|---|---|---|---|---|---|---|---|
. | b . | SE . | b . | SE . | b . | SE . | b . | SE . | b . | SE . |
Context | ||||||||||
Historical religious denomination | ||||||||||
(Protestant = ref.) | ||||||||||
Roman Catholic | 0.142* | 0.063 | 0.138* | 0.062 | 0.125 | 0.064 | ||||
Muslim | 0.432** | 0.095 | 0.383** | 0.093 | 0.304* | 0.142 | ||||
Orthodox | 0.403** | 0.066 | 0.342** | 0.079 | 0.349** | 0.079 | ||||
Communist history | 0.143* | 0.066 | −0.089 | 0.069 | ||||||
Fiscal Freedom | 0.009** | 0.002 | 0.005* | 0.003 | ||||||
Education Index | −1.117 | 0.935 | ||||||||
Variance at individual level | 0.489 | 0.489 | 0.489 | 0.489 | 0.489 | |||||
Variance at country level | 0.025 | 0.048 | 0.036 | 0.023 | 0.025 | |||||
Additional country level variance explained compared to Model 2 | 51% | 11% | 31% | 54.6% | 51% | |||||
N Individuals | 61,112 | 61,112 | 61,112 | 61,112 | 61,112 | |||||
N countries | 44 | 44 | 44 | 44 | 44 |
Source: European Values Study, wave 2008; **p<0.01; *p<0.05.
Note: Controlled for individual characteristics shown in Table 3, Model 2.
Model 8 shows that countries with a communist past have a stronger work ethic than countries without, which is in line with our hypothesis. Apparently, the communist ideology has left its traces on the values of the people that lived in states under communist rule. This variable explains 11% of additional variance at the country level. Model 9 focuses on the effect of the degree of fiscal freedom of a country, which indicates the generosity of the welfare state. Fiscal freedom (implying a low tax burden and a restricted welfare state) is positively related to work ethic. This is in line with our hypothesis. Higher tax burdens and, as a consequence, supposedly more redistribution of income seem to weaken work ethic.
Model 10 shows the results of the simultaneous test of our three hypotheses regarding social institutions. The effects of religious heritage are similar to those found in Model 7, and we observe a somewhat weaker but still significant effect of the degree of fiscal freedom.
The final model of our analysis focuses on the relative explanatory power of modernisation and religious heritage, being the two country characteristics with substantial independent effects so far. The results of Model 11 show that the effects of Muslim and Orthodox heritage are significant, while the effect of Catholicism does not reach significance (sig: 0.051). The effect of the Education index becomes insignificant and almost disappears (in comparison to Model 4). Thus, the effect of education does seem to explain the difference in work ethic between Catholic and Protestant countries.
Conclusion and discussion
The aim of this research was to gain more understanding about the existing differences in work ethic between European countries and to find out to what extent these differences could be explained by using two alternative approaches: modernisation theory and social institutional theory. We used the data of the European Values Study 2008 to answer these questions and found that there is substantial variation in work ethic between European countries. A multilevel analysis showed that the between-country variation is hardly explained by composition effects. Differences between populations with respect to individual characteristics like income, education and religion explain less than 5% of the unexplained variation between countries. We examined the extent to which three dimensions of modernisation – economic security, cognitive autonomy, and social complexity – and three types of social institutions – religious heritage, welfare state generosity, and communist past – affect work ethic. The major conclusion regarding the contextual explanations is that not the level of modernisation but the religious heritage of countries has the largest explanatory power. Religious heritage by its own explains half of the between-country variation in Europe.
We think that this is a rather surprising finding and would therefore like to comment on it some more. We presented modernisation theory and institutional theory as two alternative explanations for country differences in work ethic. Though theoretically distinguishable, the indicators used for the two theories are empirically related. For example, countries with a Protestant legacy are on average wealthy, early individualised countries. In other words, they are the countries that score high on modernisation. The relatively large number of countries in our dataset allows however for disentangling the country characteristics. The results show that, even after keeping modernisation indicators constant, the striking difference in work ethic between countries with different religious legacies remains present. Put differently, within groups of countries with the same religious heritage, variation in the level of modernisation does not matter.
Another note concerns the degree of secularisation. One may argue that secularisation may be responsible for the relationship between religious heritage and work ethic. Secularisation could be considered as part of the modernisation process: with increasing cognitive autonomy (and hence, an emphasis on autonomy) and increasing social complexity (and hence, looser social ties and less social control) people left the church. If Protestant countries have secularised more strongly than Muslim, Orthodox or Catholic countries, secularisation may explain the relationship between religious heritage and work ethic. Additional analyses have shown that this is not the case. More in particular, countries’ level of secularisation has no independent effect on work ethic and it does not explain the relationship between religious heritage and work ethic. This strengthens our confidence that it is the religious heritage with its deep roots in countries’ cultures that influences people's values regarding work ethic, and not level of modernisation.
This study focused on determinants of work ethic. We encourage future research to study the extent to which individual and national differences in work ethic are related to differences in work behaviour. Research on the consequences of work ethic may show, for example, whether work ethic stimulates postponing retirement and, consequently, can play a role in the solution for the shrinking labour force due to rise in the ageing population.
Footnotes
A total of 663 missing values.
Mean scores and factor scores produce the same conclusions.
Analyses excluding five countries with a relatively low Cronbach's alpha (Armenia, 0.5773; Latvia, 0.5992; Malta, 0.606; Norway, 0.5769; Switzerland, 0.6041) show no change in the modernization-effects and only slight changes in the institutionalization-effects: the effect of communism in Model 8 and of a Muslim heritage in Model 11 drop below the significance level.
In each country the five items load on 1 factor, with an Eigen value above 1.
Social protection expenditure significantly negatively relates to work ethic.
Analyses excluding all missing cases did not yield different results. Income has 18.7% missing cases. As a test we imputed conditional country means, on the basis of education, age, employment status, gender and size of town for each country separately. The correlation between imputed income and observed income is 0.65. Analyses based on this conditionally imputed variable did not yield different results.
The inflection point is at age 24, until that age work ethic decreases with age, after that work ethic increases with age.
The the inflection point is at GDP 50.64 (×1000), until that point work ethic decreases by GDP, after that it increases. Only two countries (Norway and Luxembourg) in our sample have a higher GDP than 50.64.
References
Kirsten Stam is a PhD student at the Department of Sociology at Tilburg University, The Netherlands. Her dissertation focuses on predictors and consequences of work ethic values from both a country-comparative and longitudinal perspective.
Ellen Verbakel is assistant professor in the Department of Sociology/ICS at Radboud University Nijmegen, The Netherlands. Her research interests include family and work, in particular labour market careers of couples and comparative research on values.
Paul M. de Graaf is Professor of Sociology at Tilburg University, The Netherlands. His research interests include the sociology of education, social stratification, demographic and social aspects of the life-course, and comparative research on values.