Work Ethic in Formerly Socialist Economies

Susan J. Linz*Yu Wei Chu

Department of EconomicsMichigan State University

East Lansing, Michigan 48823

June 2012revised December 2012

* contact: Susan J. Linz, 110 Marshall Hall, MSU, East Lansing, MI 48823 USA; linz@msu.eduPhone: (517) 353-7280 Fax: (517) 432-1068

Linz acknowledges financial support provided by Michigan State University (CERES, CASID/WID,CIBER), William Davidson Institute at the University of Michigan, International Research andExchanges Board (IREX), as well as financial support from the University of Delaware (ResearchCompetition Grant) and the National Council for Eurasian and East European Research (NCEEER),both under authority of a Title VIII grant from the U.S. Department of State. We thank PatriciaHuddleston and Linda Good for assistance with questionnaire development; Elvin Afandi, RamzisAkmitzyanov, Firdovsi Fikretzade, Ana Jovancai, Inna Maltseva, Inna Petrova, Karina Simonyan,Nazira Tiuliundieva, and Guzel Tulegenova for assistance with data collection and data entry, andTerry-Ann Craigie and Sarah Vultaggio for assistance with data entry. Nicole Funari, Ilya Rahkovskyand Ting Ting Xin provided assistance with data management.

Work Ethic in Formerly Socialist Economies

Abstract

Do younger workers in transition economies have a different work ethic from those who were trainedand employed in the former socialist economy? Is there a positive link between work ethic andearnings among workers in transition economies? We address these questions using data collectedfrom employee surveys conducted in Armenia, Azerbaijan, Kazakhstan, Kyrgyzstan, Russia, andSerbia. Employing a composite measure, we find that younger workers tend to adhere more strongly,and older workers less strongly. This result is obtained in the majority of cases for the individualwork ethic components, as well. We also find work ethic adherence is stronger among men thanwomen, among supervisors, and among participants who exhibit an internal locus of control. Thelink between work ethic and earnings is positive: participants who scored highest on the work ethicmeasure earn 15% more than those who scored lowest. Commonalities across these six culturallyand economically diverse countries provide a foundation for developing a more global perspectiveof work ethic and worker performance.

Key Words: work ethic, earnings, locus of control, transition economies, generation, gender JEL Classification: J2, P2

Work Ethic in Formerly Socialist Economies

1. Introduction

“We pretend to work, they pretend to pay us” is a phrase often used to characterize

workplace conditions in socialist economies, particularly the former Soviet economy. Low labor

productivity, stemming in part from the combination of ‘guaranteed’ employment and wages not

linked to performance, was one of many inefficiencies contributing to the rejection of the centrally

planned socialist economic system at the end of the twentieth century. While studies indicate that

the socialist legacy continued to influence labor market outcomes even as market-oriented

economies were established (Commander and Coricelli 1995, Standing 1996), two decades after the

transformation began, a new generation of workers began to populate firms in former socialist

economies. Young generation workers, individuals born after 1982, for example, have been trained

in educational and workplace environments that increasingly reflect curricula and conditions

associated with developed market economies; young generation workers received no training or

work experience in the former socialist economy.

Recent studies suggest that values, generally, and work values in particular, have been

influenced by the changing socio-economic environment in countries undergoing a transformation

from socialism to capitalism (Alesina and Fuchs-Schundeln 2007, Denisova et al. 2007, EBRD

2007, 2011; Linz and Chu 2012, Pew Global Attitudes Project 2011, Torgler 2011). However, to the

best of our knowledge, no studies have systematically addressed the question: To what extent do

young generation workers in transition economies adhere to the work ethic typically associated with

capitalist market economies? Do young generation workers adhere more strongly to this work ethic

than older generation workers, current employees who were trained and worked in the former

socialist economy?

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As former socialist economies adopt market-oriented institutions and behaviors, labor

market outcomes associated with developed market economies have become widespread. In

developed market economies, there appears to be a positive link between a ‘strong’ work ethic and

individual (and firm) performance (Ali and Falcone 1995, Ghorpade et al. 2006, Hill and Fouts

2005, Mann 2010, Meriac 2012). Individuals characterized as having a ‘strong’ work ethic are those

who place a high value on doing a good job; those who are committed to work. The positive link

between ‘strong’ work ethic and performance is explained in part by the quality and quantity of

work effort expended on the job and in part by fewer days absent from the workplace. A logical, but

as yet unanswered question in the social science and management literatures, is whether or not

individuals exhibiting a ‘strong’ work ethic earn more.1

We address these questions using data collected from an employee survey conducted in six

former socialist economies – Armenia, Azerbaijan, Kazakhstan, Kyrgyzstan, Russia (all part of the

former Soviet Union), and Serbia (part of the former Yugoslavia) – countries which began

transformation to market-oriented economies in the early 1990s. While culturally and economically

diverse, these countries all had reached a similar stage in the transition process by the time our2

survey began. As seen in Figure 1, which provides an average score by country for nine transition

Recent studies, such as Basten and Betz (2012) using data from Switzerland, and Spenkuch (2011) using1

data from Germany, investigate the link between adherence to Protestant religious beliefs and various measures ofearnings/income, but do not explicitly examine the link between work ethic and earnings.

We use ethnic groups and religion to capture cultural diversity, and per capita income and share of2

agriculture in GDP to capture economic diversity across these six countries. In terms of cultural diversity, accordingto US State Department reports, Armenia (98% population report themselves as ethnic Armenians; 93% belong toArmenian Apostolic Church) and Azerbaijan (91% population are Azeri, with 93% reporting themselves as Muslims)are the most culturally homogeneous of the countries included in this analysis. In Serbia, ethnic Serbs account for83% of population, with 84% practicing Eastern Orthodox. In Russia, just over 80% of population are ethnic Russian(about 60% practice Eastern Orthodoxy; 16% report themselves as non-believers). In Kazakhstan, 56% reportthemselves as ethnic Kazakh (Sunni Muslims account for nearly half of the population; 44% practice EasternOrthodoxy), compared to just under 70% of population in Kyrgyzstan reporting themselves as ethnic Kyrgyz (with75% reporting themselves as Muslims and 20% practicing Eastern Orthodoxy). In terms of economic diversity,Kyrgyzstan has the lowest per capita income (($620 USD in 2007) and highest share of agriculture in GDP (31% in2007), followed by Armenia ($2570, 20%), Azerbaijan ($2710, 7%), Serbia ($4450, 13%), Kazakhstan ($4970, 6%)

and Russia ($7590, 4%). See http://www.state.gov/p/eur/ci/index.htm .

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indicators (EBRD 2011), except for Serbia, much of the institutional foundation for a market-

oriented economy had been laid by the end of the 1990s. Indeed, empirical and anecdotal evidence

suggests that labor market conditions and workplace environments in transition economies have

grown increasingly similar to developed market economies (Casez and Nesporova 2003, Rutkowski

2006), even among countries that are not part of the European Union (Gimpelson and

Kapeliushnikov 2011, Semykina and Linz 2007).

Our objective is twofold. First, we seek to discover whether adherence to the work ethic

typically associated with capitalist market economies differs by generation, where generation is

defined by training or work experience in the former socialist economy: older generation workers

had such experience, younger generation workers did not. Given that younger generation workers

were not shaped by the socialist legacies that contributed to the “we pretend to work and they

pretend to pay us” characterization, we hypothesize that younger generation workers will adhere

more strongly to the work ethic typically associated with capitalist market economies. Similarly, we

also hypothesize that older generation workers, even those who continued to work in the newly-

emerging market-oriented environment, will adhere less strongly. We note that the generational

differences in work ethic that we hypothesize stand in direct contrast to studies conducted in

developed market economies which suggest that work ethic is weaker among younger generation

workers (Cennamo and Gardner 2008,Twenge et al. 2010).

Second, we investigate the link between work ethic and earnings. Because firms in formerly

socialist economies now pay more attention to motivating their employees and retaining the most

productive ones (Lehmann and Zaiceva 2012, Linz et al. 2012), we hypothesize a positive link

between work ethic and earnings for both younger generation and older generation workers.

We contribute to the work ethic literature in a number of important ways. First, like many

existing studies, we use a multidimensional construct to capture work ethic. Following Blood

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(1969), Miller et al. (2002), and others, our work ethic measure is not tied to any one set of religious

beliefs, although it often is referred to as the ‘Protestant Work Ethic’ (Hassall et al. 2005).

Moreover, given the relatively low reliability statistic reported in empirical studies using a

composite work ethic measure (see Abdalla 1997 and Furnham 1990, for example), following

Meriac et al. (2009), we also conduct our analysis of generational differences using the individual

components of the multidimensional work ethic measure. Unlike the majority of existing studies,

however, we utilize employer-employee matched data collected in culturally and economically

diverse countries which initiated a transformation from a collectivist to individualist orientation

(Hofstede 1980). While several studies examine work ethic in different cultural environments (Ali

1988 1992, Arslan 2001, Furnham et al. 1993, Niles 1999, for example), to the best of our

knowledge, few studies examine work ethic in countries experiencing wholesale socio-economic

change (Linz and Chu 2012, Torgler 2011). Yet documenting adherence to a particular work ethic,

even if only at one point in time, provides an important foundation for better understanding of the

link between attitudes, values and behavior. Similarities that emerge in these diverse settings likely

signal results that will contribute to developing a more global perspective of factors influencing

worker performance.

Second, our study extends the literature that examines links between work ethic and

demographic characteristics. For example, separate from analyses of generational differences, a

number of studies investigate the relationship between work ethic and age, reporting mixed results

(Boatwright and Slate 2002, Ghorpade et al. 2006, Hill and Fouts 2005). Results also are mixed

regarding the relationship between work ethic and other demographic characteristics, such as gender

and education (Chanzanagh and Akbarnejad 2011, Meriac et al. 2009). Additionally, rather than

employ representative samples, these studies tend to rely on student responses, or focus on workers

in a particular firm or sector. Like the majority of studies, we do not have access to data collected

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from representative samples. However, in contrast to these studies, with more than 10,880

participants employed in a wide variety of workplaces in these six countries, we are able to provide

a more systematic analysis of the link between work ethic and demographic characteristics. For

example, we investigate the link between work ethic and age, gender, personality, marital status,

education, work experience, unemployment experience, and supervisory responsibilities, while

controlling for a number of workplace characteristics (ownership, sector, average firm earnings).

Third, while existing studies find a positive association between work ethic and

performance, the majority tend to involve students rather than actual employees (Firestone et al.

2005, Ghorpade et al. 2006, Meriac et al. 2009 2010, Poulton and Ng 1988, Smola and Sutton

2002). In contrast, we focus exclusively on employees, including both supervisory and non-

supervisory personnel from over 665 workplaces. More importantly, we address a knowledge gap in

the literature by explicitly investigating the link between work ethic and earnings. Do employees

with a ‘stronger’ work ethic earn more? Studies show that earnings are influenced not only by

cognitive skills, but also by non-cognitive traits such as personality (Nyhus and Pons 2005, Mueller

and Plug 2006, Semykina and Linz 2010), and loyalty (Linz et al. 2012). Including work ethic in the

basic human capital model typically used among economists further illuminates the role of non-

cognitive traits in explaining differences in of earnings.

Finally, despite a growing literature documenting the importance of peers’ earnings in

analyses of worker performance and assessments job and workplace conditions (Clark et al. 2009,

Linz and Semykina 2012, Sloan and Williams 2000), we found no studies which investigate the

relationship between work ethic and peers’ earnings. Do peers’ earnings influence own work ethic?

Our analysis addresses this knowledge gap by including in our regression analysis a measure of

relative earnings: the ratio of own earnings to average earnings of others at the workplace.

Despite the remarkably rich data set available for use in our analysis, we note a number of

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limitations. First, our data are not drawn from random samples, thus the results cannot be

generalized to some broader population of workers in these six countries. While we are careful to

restrict our discussion and interpretation of results to those employees participating in our survey,

explicitly stating that we are working with convenience samples rather than nationally representative

samples precludes any confusion. Our results are perhaps best considered as exploratory rather than

conclusive, highlighting potential future research topics to investigate should nationally

representative data become available. Second, because our survey was conducted at workplaces, our

participants are all employed in the ‘formal’ or ‘official’ economy. Consequently, our data to do not

permit analysis of potential work ethic differences among employees in the formal and informal

sectors. Should data from nationally representative samples become available, this would be an

important topic to pursue. Third, regarding the link between work ethic and earnings, we note that

the cross-sectional nature of our data precludes establishing causality. Moreover, because we use

self-reported earnings, our data and analyses are subject to limitations imposed by same-source data.

Additionally, cross-sectional data limit our ability to systematically investigate whether or not work

ethic changes over time as the socio-economic transformation proceeds. Given the cross-sectional

nature of our data, we were obliged to devise a number of ways to illuminate potential generational

differences in adherence to work ethic, as well as to assess whether work ethic adherence varies

within the older generation of workers as they gain experience with a market-oriented economy.

Our analysis proceeds as follows. Section 2 briefly reviews the relevant work ethic literature.

Section 3 describes the data and provides a descriptive analysis of our work ethic measure. Section 4

outlines our methodology, first, for evaluating whether young and older generation workers differ in

adherence to work ethic, and second, for analyzing the link between work ethic and earnings. In

Section 5 we report and discuss our results, limiting our discussion and interpretation of results to

those workers participating in our survey. We offer summary and concluding remarks in Section 6.

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2. Work Ethic

Work ethic typically is viewed as a cultural norm that underscores adherence to a belief that

work has intrinsic value or that doing a good job is a worthy endeavor. This view gained

prominence following the theological doctrines of Martin Luther and John Calvin, and the rapid

expansion of commerce and industrialization (Hill 1996). Weber (1904-1905) introduced the term

“Protestant ethic” to capture beliefs he viewed as important contributing factors to economic growth

and the development of capitalism – a commitment to the values of hard work, achievement, thrift,

discipline, and self-reliance (Hill 1996, Jones 1997). Indeed, empirical studies of work ethic tend to

focus on the Protestant Work Ethic (PWE), and numerous PWE measures have been developed to

capture this multi-dimensional construct (Blood 1969, Blau and Ryan 1997, Ho and Lloyd 1984,

Mirles and Garrett 1971, Ray 1982). More recently, studies are finding that PWE is not unique to3

Protestants (Ali 1992, Arslan 2000, Aygun et al. 2008, Furnham et al. 1993), but does tend to be

higher the stronger one’s religious beliefs (Aygun et al. 2008, Giorgi and Marsh 1990), leading

Niles (1999) and others to argue for dropping “Protestant” in studies of work ethic.

2.1 Work Ethic and Generation

Are there generational differences in work ethic? Existing studies conducted in market

economies suggest that individuals born in the 1960s and before adhere more strongly to work ethic

and work centrality than individuals born in the 1970s and after (Cennamo and Gardner 2008,

Twenge 2010). Older generation workers tend also to adhere less strongly to preferences for leisure,

and such extrinsic values as money and status (Meriac et al. 2010, Twenge 2010). This is not

surprising. In developed market economies, where the vast majority of work ethic studies have been

conducted, socio-economic institutions and environments are fairly stable, thus the effect of time

Antonio (2005) argues that Weber’s popularity after World War II is connected to efforts to highlight the3

advantages of capitalism (PWE) over communism (no PWE) during the Cold War era.

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(an additional year) would be small. If values are formed relatively early in life, as suggested by

Giuliano and Spilimbergo (2009) and Low et al. (2005), among others, the age effect, due to

differences in life cycle or career stage, would also be small. Hansen and Leuty (2012) find that

generational differences in work values are small in magnitude, but that generation influences work

values more than age.

Generally, separating generation and age effects, especially using cross-sectional data, is

problematic, especially if the age distribution is restricted in the sample (Parry and Unwin 2011). To

address the confounding nature of generation and age, Twenge et al. (2010) use a nationally

representative sample of U.S. high school seniors and a time-lag research design that compares

responses to the same set of questions in three different years: 1976, 1991, and 2006. They find that

leisure values increased steadily over the generations and work centrality declined. Smola and

Sutton (2002) apply a similar research design by comparing the responses in their sample (MBE and

Executive MBA students) to the results reported by Cherrington (1980) using data collected in

1974. They conclude that younger generation workers exhibit lower adherence to centrality of work.

Meriac et al. (2010) pool samples of business students across 12 years and use a work ethic measure

similar to the one used in this analysis. They find that the young generation adheres less strongly

than the older generation on all components of the work ethic measure except leisure.

The situation considered in our analysis is quite different. Socio-economic conditions

changed dramatically in the 1990s in all six countries. In our analysis, generation is defined by this

change. We hypothesize that young generation workers will adhere more strongly than older

generation workers to the work ethic typically associated with capitalist market economies; that is,

that the economic transformation will have an influence on work ethic. As the effect of age (life-

cycle or career stage) should be similar in both market economies and transition economies, any

generational difference in our analysis is less likely driven by age effects. However, since our cross-

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sectional data cannot capture time effects, which are likely large in transition economies, our4

analysis faces limitations similar to existing studies which try to partial out the age, generation, and

time effects. We consider a number of different specifications in an effort to address these issues.

2.2 Work Ethic and Demographic Characteristics

Numerous studies investigate demographic determinants of work ethic, considering age,

gender, education, and religious beliefs. In most cases, the results are mixed. For example, while5

some studies show a positive association between work ethic and age (Aldag and Brief 1975, Ali et

al. 1995, Goodale 1973), others find a negative association (Ghorpade et al. 2006, Tang and Tzeng

1992, Wentworth and Chell 1997); some studies show no statistically significant association

(Boatwright and Slate 2002, Ma 1986, Mann 2010, Meriac et al. 2009, Wayne 1989, Wong et al.

2008). Parry and Urwin (2011) argue that the mixed results likely stem from problems associated

with failure to distinguish between generation and age, and limitations imposed by cross sectional

data, especially in samples where the age distribution is restricted (to students, for example).

For gender, the pattern of mixed results is repeated – some studies show women adhere more

strongly to a particular work ethic measure than men (Ghorpade et al. 2006, Mann 2010). Other

studies find that women adhere less strongly than men (Ali and Azim 1995, Boatwright and Slate

2000, Wentworth and Chell 1997), and some studies find no statistically significant gender

difference (Ma 1986, Tang and Tzeng 1992, Wayne 1989). While the transformation that occurred

Access to longitudinal data would permit documentation of the influence of time (economic4

transformation) on work values. We would expect economic transition to increase older generation workers’adherence to work ethic rather than decrease it; that is, the time effect would be positive. This implies that in ouranalysis, which is based on cross-sectional data, the results will likely under-estimate the ‘true’ effects of transitionon work ethic adherence; that is, the generational effect is likely larger than our estimated coefficients indicate.

Numerous studies focus on link between work ethic and religious beliefs (Ali 1988 1992, Arrunada 2010,5

Arslan 2001, Aygun et al. 2008, Furnham et al. 1993, Ma 1986, Niles 1999). Because we were not able to collectinformation about each participant’s religious beliefs or ethnicity, we are not able to provide any direct informationon this relationship. We do note, however, that the populations in Armenia, Azerbaijan, and Serbia are quitehomogeneous (see footnote 1), but quite different from each other, so we are able to investigate commonalitiesacross culturally and economically diverse countries.

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among formerly socialist economies in the 1990s allowed women more legal opportunities to

withdraw from the workforce, perhaps leading to speculations that those women who remained in

the workforce had a strong work ethic, it is likely that deteriorating economic conditions associated

with the transition may have obliged women to remain in the workforce regardless of their work

ethic. Thus, given the mixed results in the literature, we are neutral about whether the female

workers participating in our study will adhere to the work ethic measure more or less strongly than

the participating male workers.

Similarly, for education, the results are mixed: Wollack et al. (1971) and Goodale (1973)

find a positive association between work ethic and education; Ma (1986) and Wentworth and Chell

(1997), among others, find a negative association; Aldag and Brief (1975) and Boatwright and Slate

(2002) find no association. Given these mixed results, we are neutral about the link between

education and work ethic.

2.3 Work Ethic and Performance

Empirical research exploring the link between work ethic and performance has generated

few conclusive results, but the general consensus is a positive relationship between work ethic and

performance (Ghorapde et al 2006, Mann 2010, Ntayi 2005, Poulton and Ng 1988). Individuals with

‘strong’ work ethic tend to work longer hours (spend less time on leisure) or accomplish more tasks,

which translates into higher performance. Given the evidence that formerly socialist economies have

adopted market-oriented economies and are generating similar labor market outcomes, we therefore

hypothesize a positive association between work ethic and performance among the participating

employees from these six formerly socialist economies. In particular, we hypothesize a positive

association between work ethic and earnings.

3. Data description

Under the auspices of a project designed to investigate factors influencing worker

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performance in formerly socialist economies, an employee survey was conducted in Russia,

Armenia, Azerbaijan, Kazakhstan, Kyrgyzstan and Serbia. Local project coordinators in each6

country used personal connections and snowball method to contact over 700 workplaces requesting

permission to conduct the survey. Financial constraints precluded obtaining a representative sample

of firms. Financial constraints also precluded getting a representative sample of workers in7

organizations where permission was granted. Instead, the questionnaire was administered in

common areas in the workplace or at specific job sites, with the objective of including as much

diversity among participants as possible (young and older, men and women, supervisors and non-

supervisors, skilled and unskilled). If workers agreed to participate, they had the option of returning

a complete or incomplete questionnaire, without further follow up. Each participant indicated their

understanding of the procedures used to protect the confidentiality and anonymity of their responses.

More than 10,880 employees in over 665 workplaces participated.

Our convenience sample represents a wide variety of workers and workplaces, and involves

multiple geographic locations in each country. For the purposes of this paper, we restrict the sample

to include only those participants who answered all questions relevant to this analysis of work ethic,

giving us a total of 7,086 observations. For simplicity, we utilize the country name to refer to8

participating workers from that country. Sample characteristics are summarized in Table 1.

Country selection was driven by the presence of established contacts who agreed to act as local project6

coordinators.

In all cases, local project coordinators were connected to universities or business/economic development7

programs, and knew of former students and colleagues working in local and regional business. When the survey wascompleted at one organization, the contact person there was asked to provide referrals and/or contact theircounterpart at other organizations to request permission to conduct the survey.

Missing information most frequently occurred among the worker characteristic variables, particularly8

experience with unemployment, where 1,646 participants left this blank. Education and earnings also account formany missing observations. While participants with missing unemployment experience show a lower adherence toour work ethic measure (even in comparison to participants who report unemployment experience), the work ethic-generation regression results are nearly identical if we drop unemployment experience as a control variable (that is, ifwe expand the sample size to include those 1,646 participants).

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As seen in the top half of Table 1, average age of participating employees ranges from mid-

to-late 30s, the majority of whom are relatively highly educated. Average workplace tenure ranges9

from 5 to 9 years. In all but Azerbaijan, at least half of the participating employees are female; in

Kyrgyzstan and Russia, the percentage of female participants is higher, in large part a consequence

of the connections of the local project coordinators in education/health care and the public sector

(local and federal government organizations). At least one-quarter of the participating employees

held supervisory positions at the time the survey was conducted. In all but Serbia, 10-15% held

multiple jobs at the time the survey was conducted. A significant percentage of participants reported

experience with unemployment: over half among participating employees in Krygyzstan; just over

20% among Russian participants.

In terms of workplace characteristics, at least one-quarter of the survey participants worked

in state-owned organizations, typically in education and health care organizations, or manufacturing

plants. In Kyrgyzstan, due to the contacts of the local project coordinator, over 80% of the

participants were employed in state-owned organizations, with a substantial proportion working in

local, regional or federal government offices. This may contribute to less diversity in workplace

culture and policies, and thus less variation among work ethic adherence among Krygyz

participants. While relatively few were employed in construction/transportation or finance (except

Serbia), between 20% and 40% were employed in manufacturing organizations (except Kyrgyzstan).

3.1 Measuring Work Ethic

Our work ethic measure includes eight components. As seen in Table 2, four components10

are positively worded, with participants asked to respond using a scale from 1 (strongly disagree) to

The fact that the majority of those who elected to participate in the survey had relatively high level of9

education results in little variation in the years of schooling variable, making this variable unlikely to contributemuch to explaining variation in work ethic among the participants in our study.

Our measure, based on Blood (1969), was originally pre-tested and used in a survey conducted in 199510

of Russian and Polish retail workers by Huddleston and Good (1999).

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5 (strongly agree). Four components are negatively worded, using the same 5-point scale, which we

reverse-coded. We sum the eight components into a single work ethic measure, with a minimum

value of eight and maximum value of forty, where higher scores indicate stronger adherence.

Table 2 provides the work ethic mean score by country. For informational purposes, we

include the individual components, and the reliability coefficients (Cronbach alpha) for both the

positively and negatively-worded statements, as well as for the composite measure. As seen in Table

2, there is little variation by country in the mean score, ranging from 23 (of 40) among Russian

participants to 25 among Azeri participants. We note, however, that there is sometimes a large

difference by country in mean response for particular components. For example, participants from

Kyrgyzstan and Russia are quite different in their view about whether ‘hard work makes one a better

person,’, as well as about ‘people who do things the easy way.’ In comparison to participating

employees from the other countries, Azeris are more likely to agree that ‘wasting time is as bad as

wasting money’ and less likely to believe that a person should ‘relax and accept life as it is, rather

than striving.’ We also note that the Cronbach alpha is rather low in all six countries, which might

be a result of worker diversity. It is also possible that work ethic has many different aspects, not all

of which are captured here. Indeed, Furnham (1990) and Abdalla (1997) report similarly low

reliability scores, attributing the result to the multi-dimensionality of the construct. Additional

research on alternative measures, using data collected from nationally representative samples of

employees in different socio-economic and cultural environments, appears warranted.

For illustrative purposes, and following the literature that describes adherence to work ethic

as ‘strong’ or ‘weak,’ we created two categories to capture possible country differences in adherence

to our work ethic measure: weak (score less than 16) and strong (score more than 29). As seen in

Figure 2, Azeri participants are much more likely to exhibit strong adherence to our composite work

ethic measure than any other participating group.

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3.2 Work Ethic and Generation

Because our focus is on whether workers from the ‘old’ and ‘new’ economic regimes have

the same work ethic, we created two age categories. One coincides with workers born before 1977

who had received training and worked in the former socialist economy and continue to work in the

‘new’ economic environment (older generation workers). The second captures workers born after

1981 who received training and worked in the emerging market-oriented economy (young

generation workers). Table 2a summarizes the country results by generation. We note that those11

1,443 participants born between 1977 and 1981, the middle generation workers, are not included in

the results presented in Table 2a.

As seen in Table 2a, in four of the six countries, young generation workers exhibited

stronger adherence than older generation workers, although it is only statistically significant among

Armenian and Kyrgyz participants (at 5%); and marginally significant among Kazakh participants

(at 10%). Interestingly, several instances of generational differences do emerge when considering

the individual components of the work ethic measure. For example, as seen in the top panel, in four

of the six countries, young generation workers are significantly less likely to agree that ‘a good

indication of a person’s worth is how well his/her job is done.’ Among Kazakh and Serbian

participants, the same is true for ‘better to have job with a lot of responsibility than one with only a

little responsibility.’ Indeed, where the generational differences in the positively-worded statements

are statistically significant, in only half as many cases (4 compared to 8) do young generation

workers adhere more strongly than older generation workers to the particular component of the

work ethic measure.

In contrast, as seen in the lower panel of Table 2a, where the statements are negatively-

We tried different cutoff dates (1974, 1975) in an effort to expand the number of participants in the old11

and young categories and found that the results were not sensitive to the different cutoff dates.

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worded, in all but one of the cases where generational differences are statistically significant, young

generation workers adhere more strongly to the particular work ethic component. Among Azeri,

Kazakh and Kyrgyz participants, for example, this holds true for ‘job is supposed to provide means

for enjoying free time’ (a sentiment shared by young Armenian workers as well), ‘person should

relax and accept life as it is rather than striving’ (similarly for young Russian workers), and ‘people

who do things the easy way are the smart ones.’

While data collected from nationally representative samples are necessary to more accurately

portray to link between work ethic and generation, our findings illuminate a common pattern of

generational differences among participants from these six formerly socialist economies and provide

some support for the proposition that adherence to work ethic is likely less strong among workers

trained and employed in the former socialist economy. Moreover, acknowledging the rather

exploratory nature of our data, these findings begin to lay the foundation for developing a better

understanding work ethic commonalities across culturally and economically diverse countries.

We now turn to regression analysis to more systematically explore the links between work

ethic and demographic characteristics, and the relationship between work ethic and earnings.

4. Methodology

4.1 Generational Differences in Work Ethic?

To test our hypothesis that older generation workers adhere less strongly than young

generation workers to a work ethic typically ascribed to capitalist market economies, we use the

composite work ethic measure, workethic, summarized in Table 2, a cardinal, rather than

categorical, variable. Since workethic is bounded, taking on values from 8 to 40, we conduct the

regression analysis using fractional logit (Papke and Wooldridge 1996). In order to check the

robustness of our results, we also employ OLS regression analysis. To facilitate interpretation of the

estimated coefficients, we rescale workethic to be in the unit interval (subtract 8 and divide by 32).

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Consequently, the estimates can be interpreted as changes in the probability that a worker has the

highest work ethic score. Because we are interested in generational rather than country differences

in work ethic, we use pooled data, with dummy variables for each country (Azerbaijan is reference12

country).

Our generation variable, older, is a dummy variable equal to one if the individual was

trained and worked in the socialist economy (born before 1977); thus older generation workers are

compared to all other workers in the sample. To illuminate the link between work ethic and

generation, we control for a number of worker characteristics: age, age-squared, years of schooling,

years employed at the current workplace, and dummy variables equal to one if the participant is

female, married, supervisor, holds multiple jobs, or experienced unemployment in five years prior to

participating in the survey.

Because unobservable personal characteristics, such as ‘ability’, may be correlated with

work ethic, we include a composite variable, perform, constructed using three statements that asked

participants to compare their performance with others doing similar work. For each option, a scale13

of 1 (= much worse than others) to 5 (= much better than others) was provided, meaning the

composite measure has a minimum value of 3 and maximum value of 15.

Similarly, to account for the possibility that one’s work ethic may be correlated with the

performance of others at the workplace, we include a measure of relative earnings (natural log value

of the ratio of own earnings to average workplace earnings), which is possible to construct because

We thank two anonymous readers for suggesting this strategy.12

Participants were given the following wording: For the following items, compare yourself to other13

employees at your organization who do work similar to yours. How do you rate yourself in terms of quantity andquality of performance? Check the appropriate response (where 1 = much worse than others, 5 = much better thanothers). The specific statements are as follows: Compared to other employees doing similar work, the overall qualityand quantity of my work is ... Compared to other employees doing similar work, how productive are you? Compared to other employees doing similar work, how well do you anticipate problems that may arise and try toprevent them or minimize their effect? The Cronbach alpha scores for the performance composite measure rangefrom approximately 0.45 (Serbia) to 0.85 (Armenia) with Russia, Kazakhstan and Kyrgyzstan at 0.80 and Azerbaijanat 0.70.

16

we have employer-employee linked data. We report the mean values of own earnings and relative

earnings by country in Table 1. In the pooled data, and for our regression analysis, we transform the

earnings variables (own earnings, average workplace earnings, relative earnings) from local

currency to U.S. dollars using the annual average local currency-dollar exchange rate for the year in

which the survey was conducted (see Table 1).

Finally, because work ethic may be correlated with personality (Mirels and Garrett 1971,

Mudrack 1993), we include locus of control (Rotter 1966), perhaps the most frequently used single

personality trait, especially among economists (Coleman and DeLeire 2003, Semykina and Linz

2007, 2011). Our LOC measure is described in Appendix Table A1.

We also control for a number of workplace characteristics: dummy variable equal to one if

the organization is state-owned, dummy variables for different sectors (education/health care, retail

and other services, finance, public, construction/transportation; manufacturing is the reference

sector), and average workplace earnings (natural log value).

Following recent studies that explore different dimensions of work ethic (Meriac et al. 2010,

Meriac et al. 2009, Miller et al. 2002, Pogson et al. 2003), and given the relatively low reliability

associated with the work ethic measure among our survey participants, we repeat our analysis using

the individual components of the work ethic measure (see Table 2). Because the individual

components are categorical variables with values from 1 to 5, we employ ordered probit regression

analysis.

In all specifications, we cluster by firm to take into account the likelihood that a firm’s

policies or workplace environment might influence employee work ethic; that is, there might be

within firm correlation.

4.2 Work ethic and earnings

To ascertain whether there is a positive link between work ethic and earnings, we use OLS

17

regression analysis, clustering at the firm level. Our earnings measure, reported by country in Table

1, is given by participants in response to a question asking about their average monthly earnings at

the time the survey was conducted. We converted reported earnings to dollar values using the

annual average of the local currency-dollar exchange rate for the year in which the survey was

conducted in a particular country. Using dollar value (natural log value), to a modest extent,

accounts for inflationary trends in a country over time and between countries at any given time.

Because we use pooled data, we include dummy variables for each country ( Azerbiajan is the

reference group).

Our main variable of interest in the earnings regression is workethic, the composite measure

summarized in Table 2. Following standard practice, we control for the basic worker characteristics

typically included in earnings regressions: age, age-squared, years of schooling, work

experience/years employed at the current workplace, dummy variables equal one for female,

married, supervisor. To capture features somewhat unique to labor market conditions in transition

economies, we include dummy variables equal to one if the worker experienced unemployment in

five year period prior to participating in the survey or if the worker was holding more than one job

at the time the survey was conducted. Recognizing the growing number of studies that empirically

document the importance of non-cognitive factors in influencing earnings, we include a personality

measure, LOC (see Appendix Table A1), and a measure of the participating worker’s assessment of

his/her performance, perform, described above. Given the nature of our data, we are also able to

control for a number of workplace characteristics: dummy variable equal to 1 if state-owned,

dummy variables equal to 1 for sector (education/health care, retail and other services, finance,

public, construction/transportation, with manufacturing as the reference sector), and average

workplace earnings.

To check the robustness of our results, we repeat the earnings regression controlling for firm

18

fixed effects (using dummy variables for each firm).

5. Results and Discussion

5.1 Generational Differences in Work Ethic?

The regression results associated with our investigation of generational differences in work

ethic are reported in Table 3. The coefficients and estimated standard errors reported in Table 3 are14

scaled by 100, and thus reflect changes in percentage points.

In column 1 we present the results associated with our basic specification (age is linear). In

column 2, we allow age to be non-linear. The coefficients on older indicate that, among the

participants in our survey, older generation workers’ adherence to the composite work ethic measure

is lower than that of all other workers by 2-2.5%. We note that older generation employees have

been working in the new economic environment since the early 1990s and may have modified their

work ethic in response to the changing socio-economic environment or newly-emerging workplace

conditions and policies. Additionally, since we only surveyed employees, we do not include older

generation individuals who no longer work. Consequently, it may be that, in this exploratory

analysis, we underestimate work ethic adherence among older generation individuals who

experienced the transition from a socialist economy to a market-oriented economy. Future analyses

that include data collected from all categories (employed, unemployed, pension, discouraged

workers) would be valuable, as would studies that include individuals participating full time in the

informal economy.

In column 3, we report estimates for an alternative specification in which young and middle

Because the fractional logit and OLS regression results are nearly identical, we elected to present the14

OLS results; OLS being a more widely used estimation method. To simplify presentation, country dummy variablesand workplace control variables described in section 4 are not reported, but are provided upon request.

19

generation workers are compared to older generation workers; that is, older is the omitted group.15

As seen in Table 3, column 3, the estimates for both young and middle are positive and highly

significant. In comparison to older generation workers, the young generation workers participating

in our survey adhere more strongly to the work ethic measure, by about 3.1%. For middle

generation workers, work ethic adherence is stronger by 2.3% in comparison to older generation

workers. These estimates are consistent with our hypothesis that young generation workers in

transition economies will adhere more strongly (older generation workers less strongly) to the work

ethic measure typically associated with capitalist market economies.

Because older generation workers participating in our survey worked in both the socialist

economy and the emerging market-oriented economy, to more systematically examine the effect of

socio-economic regime change on work ethic, we divided the older generation workers into three

age categories (‘born before 1960,’ ‘born in 1960s,’ ‘born between 1970 and 1976’) to reflect their

relative work experience in both economic systems. We use ‘born before 1960' as our reference

group, keeping young and middle, and report the estimated coefficients in column 4. For

informational purposes, we also conduct the regression analysis by country and report the results in

Appendix Table A2.

As seen in Table 3 (column 4), the estimates for these different cohorts indicate that work

ethic adherence is decreasing with age, even among the older generation workers, and the results are

highly significant. This pattern is consistent with our proposition that work experience in the

market-oriented economy is associated with ‘stronger’ work ethic. That is, participating workers

born in 1960s, and those born between 1970 and 1976, were relatively early in their work lives

when the transition began. Thus their work ethic would likely be influenced by the new workplace

We include young, a dummy variable equal to 1 if the worker was born after 1981 (had no training or15

work experience in socialist economy), and middle, a dummy variable equal to 1 if the worker was born between1976 and 1982.

20

policies and conditions emerging with the transition process.

Without panel data, we cannot directly exclude the possibility that our results are driven by

age effects. Using cross-sectional data, it is hard to separate generation (cohort) effects from age-

related effects such as differences in life-cycle and career stage. We note, however, that our estimate

for age is uniformly positive and significant across three age-linear specifications. This implies16

that within each generation/age category, older workers adhere more strongly than younger workers

to work ethic. Moreover, the estimated coefficient magnitudes for age increase when more cohort

dummy variables are included. This implies that, among the participants in our study, the age effect

works in the opposite direction of the cohort effect. Consequently, because we hypothesize stronger

adherence to work ethic among young generation workers, the positive age effect works against the

generation effect, suggesting that among the participants in our study, support for the hypothesis is

rather robust.

5.2 Work Ethic and Demographic Characteristics

As seen in Table 3, among participants in our study, work ethic is positively linked to

education and supervisory responsibilities. Work ethic is stronger among married workers and those

who report their performance as better than others doing similar work. Work ethic also is stronger

among participants who exhibit an internal locus of control, as well as among those earning above-

average wages. Work ethic is weaker among the participating women. While there is a negative link

between work ethic and recent experience with unemployment, the result is not statistically

significant. Nor does workplace tenure or holding multiple jobs influence work ethic among the

participants in our study.

5.3 Examining Different Aspects of Work Ethic

When we control for age in non-linear manner (age-squared is reported in column 2; we also included16

age-cubed), our overall results are very similar, but the estimate for age and its higher order terms become very noisyand insignificant. As Torgler (2011) points out, the non-linearity effect in age is less obvious in work ethic.

21

Our ordered probit regression results for the individual components of the work ethic

measure are presented in Table 3a. We report the marginal effect on the probability that a worker17

strongly agrees with the particular statement.

As seen in Table 3a, for all components except RELAX, young (and middle) generation

workers exhibit stronger adherence than older generation workers to the positively-worded

statements and weaker adherence to the negatively-worded statements. For example, in comparison

to participating workers born before 1960 (the reference group), young generation workers are about

10% more likely to strongly agree with the statements that ‘hard work makes one a better person’

and ‘better to have job will a lot of responsibility,’ but 15-18% less likely to strongly agree with the

statements that ‘one should forget job when the workday finished’ and ‘one’s job is to provide

means for enjoying free time.’ Interestingly, because the results in Table 3a are consistent with those

reported in Table 3, which is based on the composite work ethic measure, this suggests that the

unitary (composite) measure is appropriate. Moreover, this consistency helps to exclude the

possibility that generational differences found when the composite work ethic measure is used are

due to different interpretations across generations for particular components.

5.4 Work Ethic and Earnings

In Table 4 we present the OLS regression results from our estimation of the relationship

between an individual’s work ethic and earnings. The dependent variable is the natural log of

average monthly earnings, so the work ethic estimates can be interpreted as the percentage

difference in earnings between a worker who scored 40 (the maximum score) on the work ethic

measure and a worker who scored 8 (the minimum score). As is common in earnings regressions,

we include a quadratic term for age to capture life-cycle effects, and we estimate a specification that

Unlike Meriac et al. (2010) we are not able to examine the measurement equivalence within each17

dimension across generations because our cross-sectional data contains only one response for each dimension.

22

replaces workplace characteristics with firm fixed effects (dummy variables for each firm). Because

we include average firm earnings (column 1) or firm fixed effects (column 2), we compare the effect

of work ethic on earnings among participants working in firms with the same average earnings

(column 1) or in the same firm (column 2).

As seen in Table 4, the results are nearly identical in both columns. On average, conditional

on worker and workplace control variables, participants who scored highest on the work ethic

measure earn 15% more than people who scored lowest. Moreover, estimated coefficients on the

remaining explanatory variables are generally consistent with conventional wisdom. The estimates

on age and age-squared indicate the common concave age-earning profile. Earnings are positively

linked to education; the estimates imply that an additional year of schooling contributes 3% to

earnings among the participants in our study. Participants who hold supervisory positions and those

who self-report better performance have higher earnings, on average, as do married participants.

Women participating in our study earn approximately 16% less than the participating men. Like

other studies (Coleman and DeLeire 2003, Semykina and Linz 2010), participants who exhibit an

internal locus of control have higher earnings, although the magnitude of the personality effect is

relatively small: 2% (5 x .004) higher earnings for each standard deviation increase in LOC.

To check the robustness of our results, we repeat the earnings regression by country and

report the results in Appendix Table A3. As expected, the estimates are noisier, but they are not very

different from the pooled regression results. Except for Kazakhstan and Serbia, the results indicated

a positive relationship between work ethic and earnings.

6. Summary and Conclusions

Do young generation workers in formerly socialist economies adhere more strongly than

older generation workers to the work ethic typically associated with capitalist market economies?

Do workers with a stronger work ethic earn more? We address these questions using data collected

23

from employees in six culturally and economically diverse transition economies.

Regardless of specification, our results indicate that among the participants in our survey

work ethic adherence is significantly weaker among older generation workers; a result that stands in

contrast to studies conducted in developed market economies. We find a positive relationship

between work ethic and earnings. On average, participants who scored highest on the work ethic

measure earn 15% more than people who scored lowest.

Regarding the links between demographic characteristics and work ethic, we find a number

of interesting results. Among the participants in our study, adherence to work ethic is stronger

among men than women. Work ethic is positively linked to education and relative earnings, and is

stronger among supervisors, married participants, participants who self-report better performance

than their colleagues, and participants with an internal locus of control.

While exploratory in nature, these results take a step toward developing a better

understanding of factors influencing worker performance. They also signal the need for additional

research examining the component parts of composite work ethic measures by gender, using

nationally representative data. While a positive link between work ethic and earnings is evident in

our results, this finding would be greatly strengthened if we had not been limited by same-source

data. Furthermore, without direct knowledge of workplace practices regarding the firm’s

commitment to retaining older workers, we not able to eliminate the influence of work contracts as a

possible confounding factor. Nonetheless, the commonalities across these six culturally and18

economically diverse countries begin to lay the foundation for developing a more global perspective

of work ethic and worker performance.

We thank anonymous reader for highlighting this point. 18

24

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Figure 1: Transition Indicators, average score, by country

EBRD Transition Indicators (2012): average score calculated using 8 individual transition indicators and the overall infrastructure indicator.

0.00000

0.50000

1.00000

1.50000

2.00000

2.50000

3.00000

3.50000

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Armenia

Azerbaijan

Kazakhstan

Kyrgyzstan

Russia

Serbia

0

5

10

15

20

25

Armenia Azerbajian Kazakhstan Kyrgyzstan Russia Serbia

Figure 2: Work Ethic by country

Weak (<16)

Strong (>29)

All Armenia Azerbaijan Kazakhstan Kyrgyzstan Russia SerbiaWorker CharacteristicsAge (at time of interview, years) 36.8 37.9 32.9 33.7 39.2 38.2 35.8

(11.10) (11.88) (9.54) (9.49) (12.39) (11.59) (7.62)Years of schooling 14.6 15.1 13.7 14.9 14.7 14.3 14.6

(2.74) (2.09) (2.73) (2.35) (3.62) (2.86) (2.02)Job tenure (years at current workplace) 7.3 6.8 5.1 4.9 8.8 9.4 6.4

(7.78) (7.38) (6.71) (4.45) (9.50) (8.89) (4.95)Self-reported performance (mean score) 10.5 10.7 10.8 10.2 10.4 10.2 11.1

(1.75) (1.93) (1.93) (1.49) (1.71) (1.59) (1.56)Locus of control (mean score) 1.09 0.87 -0.86 1.01 2.30 1.00 2.20

(5.10) (4.49) (6.38) (4.43) (4.94) (5.73) (2.68)Women (%) 57.7 52.7 38.1 54.8 68.2 71.1 49.5Married (%) 54.2 47.7 55.0 56.4 55.6 57.6 53.8Supervisor (%) 34.3 36.0 38.1 44.0 34.8 35.6 23.5Holds multiple jobs (%) 12.3 15.3 15.4 9.4 14.6 13.7 0.5Experience w/ unemployment (%) 34.2 28.1 44.7 39.8 52.5 20.8 30.7

Workplace CharacteristicsState-owned (%) 44.5 34.2 24.9 31.4 82.6 45.3 42.1Manufacturing (%) 25.1 22.2 44.2 22.7 0.6 39.5 16.1Education/Health Care (%) 19.1 17.9 19.0 16.2 13.5 29.4 10.9Retail and other services (%) 22.2 33.4 15.7 31.0 7.6 19.7 27.0Finance (%) 5.9 2.9 10.2 6.5 2.4 0.0 21.2Public sector (local, region, federal) 22.7 20.1 5.9 19.6 75.3 5.0 13.2Construction/Transportation (%) 4.9 2.8 5.0 4.0 0.5 6.4 11.7

Average earnings Own earnings (local currency) $315 USD 86253 387 25158 3528 5159 54427

(379) (73179) (322) (35775) (2631) (4694) (22761)Own to peers' earnings ratio 1.16 1.15 1.13 1.20 1.11 1.25 1.10

(0.97) (0.92) (0.67) (0.87) (0.69) (1.06) (1.42)

Number of observations 7,086 1,493 958 757 1,189 1,769 920

Number of workplaces 557 183 63 97 96 89 29Standard deviations in parentheses.

Self-reported performance scale: 3 (much worse than others) to 15 (much better). See text for PERFORM description.Locus of control scale: 20 (purely internal) to -20 (purely external). See Appendix for description of LOC variable.For pooled data, own earnings converted to US dollars using exchange rate at time survey conducted.

Armenia: employee survey conducted in Yerevan (2005) and Shirak region (2008)Azerbaijan: employee survey conducted in Baku, Sumgait, Shabran, Sabirabad (2011)Kazakhstan: employee survey conducted in Almaty, Taldyquorghan, and surrounding locales (2005).Kyrgyzstan: employee survey conducted in Bishkek (2007) and Kara Balta (2008)Russia: Rostov region (2002), Sverdlovsk region (2003), Bashkortostan autonomous republic (2005)Serbia: employee survey conducted in Belgrade (2008), Novi Sad (2009)

Table 1: Sample Characteristics, pooled and by country

Table 2: Work Ethic Components, pooled and by country

Please indicate your agreement or disagreement with the following statements by circling appropriate response: All Armenia Azerbaijan Kazakhstan Kyrgyzstan Russia Serbia

Positively-worded statements (1= strongly disagree, 5 = strongly agree)Hard work makes on a better person (BETTER PERSON) 3.17 3.35 3.64 3.12 4.00 1.99 3.67

(1.44) (1.44) (1.27) (1.35) (1.11) (1.22) (0.94)Wasting time is as bad as wasting money (WASTE) 4.14 4.16 4.41 4.12 4.25 4.20 3.58

(1.05) (1.02) (1.02) (1.01) (1.15) (1.05) (0.82)A good indication of a person's worth is how well his/her 3.79 3.72 3.93 3.99 4.06 3.82 3.19 job is done (WORTH) (1.07) (1.06) (0.96) (1.01) (1.10) (1.10) (0.87)All other things equal, better to have a job with lot of 3.40 3.51 3.05 3.61 3.86 3.17 3.27 responsibility than one with little responsibility (RESPONSBL) (1.21) (1.15) (1.45) (1.14) (1.11) (1.25) (0.79)

Cronbach alpha 0.42 0.43 0.39 0.46 0.49 0.43 0.23

Negatively-worded statements (reverse coded)When the work day is finished, a person should forget his/her 4.08 4.22 3.74 4.17 4.15 4.16 3.86 job and enjoy himself/herself (FORGET JOB) (1.14) (1.06) (1.33) (1.06) (1.19) (1.09) (1.06)The principal purpose of a person's job it to provide a means 3.86 3.87 3.96 4.03 4.08 3.85 3.33 for enjoying free time (ENJOY) (1.11) (1.09) (1.22) (1.00) (1.12) (1.18) (0.74)Whenever possible, person should relax / accept life as is, 3.52 3.62 2.60 3.80 3.69 3.60 3.74 rather than always striving for unreachable goals (RELAX) (1.33) (1.24) (1.51) (1.20) (1.37) (1.26) (1.05)People who 'do things the easy way' are smart (EASY WAY) 3.20 3.14 3.72 3.36 3.72 2.74 2.86

(1.37) (1.30) (1.42) (1.43) (1.34) (1.34) (0.98)

Cronbach alpha 0.41 0.43 0.52 0.43 0.51 0.50 0.41

PWE composite 23.8 23.9 25.0 23.5 24.5 22.8 23.9(3.67) (3.26) (4.25) (3.24) (3.60) (4.10) (2.43)

Cronbach alpha 0.50 0.57 0.58 0.58 0.59 0.43 0.48

Number observations 7086 1493 958 757 1189 1769 920Standard deviations in parentheses.

Table 2a: Work Ethic Components, by generation and country

Young Old Young Old Young Old Young Old Young Old Young Old Young OldPositively-wordedBETTER PERSON 3.40*** 3.08 3.54** 3.31 3.41 3.97*** 2.90 3.07 4.02 4.01 2.55*** 1.89 3.53 3.70

(1.34) (1.49) (1.39) (1.45) (1.32) (1.19) (1.42) (1.38) (1.03) (1.14) (1.30) (1.20) (1.06) (0.94)WASTE 4.27*** 4.13 4.20 4.15 4.48*** 4.29 4.20 4.17 4.18 4.24 4.05 4.24** 3.58 3.60

(1.05) (1.06) (1.03) (1.03) (0.96) (1.13) (0.90) (1.00) (1.16) (1.18) (1.18) (1.03) (0.92) (0.80)WORTH 3.75 3.83** 3.72 3.72 3.77 4.15*** 4.04 4.03 3.93 4.09** 3.55 3.86*** 2.96 3.22**

(1.07) (1.07) (1.11) (1.05) (1.01) (0.93) (0.95) (0.98) (1.09) (1.10) (1.11) (1.11) (0.98) (0.87)RESPONSIBILITY 3.32 3.40** 3.51 3.46 3.12** 2.90 3.20 3.63** 3.81 3.87 3.21 3.17 3.11 3.30*

(1.30) (1.20) (1.15) (1.15) (1.48) (1.44) (1.20) (1.15) (1.03) (1.14) (1.17) (1.28) (0.93) (0.79)Cronbach alpha 0.44 0.42 0.44 0.42 0.45 0.31 0.37 0.49 0.49 0.49 0.49 0.44 0.40 0.29

Negatively-wordedFORGET JOB 4.02 4.11*** 4.17 4.22 3.81** 3.62 4.20 4.18 4.14 4.18 4.37** 4.17 3.71 3.91

(1.23) (1.12) (1.07) (1.06) (1.35) (1.35) (1.17) (1.06) (1.21) (1.18) (0.91) (1.10) (1.22) (1.02)ENJOY 3.79 3.91*** 3.62 3.90*** 3.89 4.05** 3.78 4.09*** 3.87 4.14*** 3.73 3.92** 3.18 3.35*

(1.18) (1.11) (1.07) (1.10) (1.24) (1.18) (1.07) (0.96) (1.16) (1.12) (1.21) (1.17) (0.75) (0.75)RELAX 3.06 3.65*** 3.68 3.61 2.48 2.79*** 3.46 3.89*** 3.45 3.80*** 3.28 3.71*** 3.89 3.70

(1.47) (1.27) (1.13) (1.23) (1.46) (1.58) (1.39) (1.18) (1.46) (1.31) (1.33) (1.23) (0.98) (1.05)EASY WAY 3.34*** 3.16 3.09 3.09 3.66 3.86** 2.88 3.40*** 3.55 3.76** 2.75 2.74 2.73 2.87

(1.44) (1.37) (1.31) (1.29) (1.47) (1.40) (1.47) (1.42) (1.33) (1.35) (1.33) (1.37) (1.10) (0.98)Cronbach alpha 0.39 0.42 0.58 0.39 0.60 0.33 0.45 0.41 0.36 0.55 0.52 0.49 0.46 0.43

Work ethic composite 24.52*** 23.61 24.41** 23.80 24.94 24.98 24.01* 23.34 24.95** 24.34 23.22* 22.63 23.67 24.00(4.06) (3.60) (3.54) (3.18) (4.51) (3.89) (3.62) (3.23) (3.47) (3.65) (4.16) (4.05) (2.50) (2.46)

Cronbach alpha 0.35 0.52 0.45 0.56 0.64 0.45 0.51 0.58 0.52 0.60 0.48 0.44 0.61 0.47

Number observations 987 4683 138 1084 421 329 69 514 184 816 130 1387 45 589Standard deviations in parentheses. Bold figures indicate significantly higher mean scores that are consistent with our hypothesis: young adhere more strongly than old.Statistical significance: *** p<0.01, ** p<0.05, * p<0.1

All SerbiaArmenia Azerbaijan Kazakhstan Krygyzstan Russia

Table 3: OLS Regression Results; Work Ethic and Generation

1 2 3 4Older generation (born before 1976) -2.491*** -1.918***

(0.447) (0.526)Young generation (born after 1981) 3.134*** 6.298***

(0.597) (1.266)Middle generation (born 1976-1981) 2.289*** 4.997***

(0.457) (1.056)Older70s (born 1970-1975) 2.439***

(0.867)Older60s (born 1960-1969) 1.327**

(0.584)Age 0.046** -0.148 0.052** 0.143***

(0.020) (0.104) (0.020) (0.039)Age-squared 0.219*

(0.115)Years of schooling 0.117* 0.118* 0.120* 0.118*

(0.062) (0.062) (0.063) (0.063)Married 0.483* 0.555* 0.543* 0.541*

(0.292) (0.290) (0.293) (0.291)Female -0.998*** -0.972*** -0.988*** -0.944***

(0.341) (0.342) (0.340) (0.341)Supervisory responsibilities 0.825** 0.847** 0.831** 0.836**

(0.336) (0.336) (0.336) (0.335)Years at current workplace 0.015 0.012 0.0142 0.0134

(0.030) (0.030) (0.030) (0.030)Holds multiple jobs -0.002 0.008 0.018 0.017

(0.469) (0.470) (0.469) (0.469)Recent unemployment experience -0.482 -0.512 -0.500 -0.501

(0.370) (0.368) (0.369) (0.370)Relative earnings 0.618** 0.655** 0.631** 0.639**

(0.301) (0.303) (0.302) (0.303)Self-reported performance 0.362*** 0.364*** 0.365*** 0.358***

(0.091) (0.092) (0.092) (0.091)Locus of control 0.428*** 0.428*** 0.429*** 0.427***

(0.042) (0.042) (0.042) (0.042)

Workplace controls Yes Yes Yes Yes

Country controls Yes Yes Yes Yes

Observations 7,086 7,086 7,086 7,086R-squared 0.111 0.111 0.111 0.112

Workers born before the 1960 are omitted (reference) group in column 4.Robust standard errors in parentheses, clustered at firm level.

The coefficients and estimated standard errors are scaled by 100.

Statistical significance: *** p<0.01, ** p<0.05, * p<0.1

Table 3a: Ordered Probit Regression Results: Work ethic components and generation

better waste worth responsible forgetjob enjoy relax easywayYoung (born after 1981) 10.85*** 5.831 3.866 8.975*** -14.76*** -18.11*** 4.431 -5.545

(3.722) (5.627) (4.673) (3.319) (5.552) (5.116) (4.511) (4.061)Middle (born 1976-1981) 10.26*** 2.561 5.330 8.527*** -14.43*** -13.00*** 3.844 -0.503

(3.038) (4.740) (3.998) (2.759) (4.843) (4.250) (3.857) (3.391)Older70s (born 1970-1975) 7.673*** -1.204 2.391 3.038 -7.443** -7.591** 3.480 -0.826

(2.437) (3.811) (3.124) (2.276) (3.749) (3.361) (3.132) (2.721)Older60s (born 1960-1969) 4.166*** -1.424 1.029 0.802 -4.981* -5.787*** 3.092 -1.269

(1.557) (2.574) (2.278) (1.613) (2.560) (2.218) (2.277) (1.901)Age 0.248** 0.169 0.351** 0.269** -0.498*** -0.247 0.315** -0.086

(0.112) (0.173) (0.147) (0.111) (0.179) (0.154) (0.139) (0.124)Years of schooling -0.226 0.285 -0.333 0.060 -0.313 -0.576*** -0.413** -0.209

(0.177) (0.264) (0.203) (0.162) (0.295) (0.206) (0.206) (0.185)Married 1.151 1.973* 1.150 0.540 -0.499 -0.047 0.083 0.127

(0.837) (1.180) (1.020) (0.850) (1.265) (1.068) (1.002) (0.859)Female -5.411*** 2.597** -2.230** -0.511 4.904*** 0.771 1.807* -3.427***

(0.962) (1.244) (1.027) (0.909) (1.463) (1.158) (1.034) (0.857)Supervisory responsibilities -0.695 3.527** 2.358** 2.273** -2.435* 0.795 -1.191 0.668

(0.929) (1.488) (1.170) (0.987) (1.438) (1.320) (1.155) (0.997)Years at current workplace 0.093 0.221** 0.171** 0.111 0.029 0.085 0.362*** -0.040

(0.076) (0.108) (0.086) (0.073) (0.124) (0.098) (0.088) (0.082)Holds multiple jobs 0.330 -2.536 -3.046** -1.521 -4.874*** -2.048 1.108 -0.707

(1.294) (1.849) (1.544) (1.272) (1.654) (1.612) (1.700) (1.267)Recent unemployment -1.425 2.761** -1.492 -1.582* 3.259* 1.286 -2.061 0.404

(1.053) (1.357) (1.076) (0.940) (1.701) (1.344) (1.272) (1.017)Relative earnings -0.338 0.649 -0.169 0.353 -1.520 -1.463 -1.111 -1.551*

(0.819) (1.279) (0.981) (0.726) (1.190) (1.066) (0.990) (0.866)Self-reported performance 0.746*** 0.527 1.449*** 0.474* 0.0163 0.150 -0.378 -0.121

(0.277) (0.385) (0.311) (0.255) (0.406) (0.320) (0.313) (0.242)Locus of control 0.509*** 0.276* 0.824*** 0.515*** -0.484*** -0.741*** -0.009 -0.878***

(0.101) (0.144) (0.108) (0.105) (0.155) (0.138) (0.125) (0.114)Workplace controls Yes Yes Yes Yes Yes Yes Yes YesCountry controls Yes Yes Yes Yes Yes Yes Yes Yes

Observations 7,086 7,086 7,086 7,086 7,086 7,086 7,086 7,086The coefficients and estimated standard errors are scaled by 100.Workers born before the 1960 are omitted (reference) group.Robust standard errors in parentheses, clustered at firm level. Statistical significance: *** p<0.01, ** p<0.05, * p<0.1

Table 4: OLS Regression Results: Work Ethic and Earnings

Basic model Fixed effects

Work ethic 0.153*** 0.150**(0.057) (0.065)

Age 0.027 *** 0.029 ***(0.004) (0.004)

Age squared -0.030*** -0.032***(0.004) (0.005)

Years of schooling 0.023*** 0.029***(0.003) (0.003)

Married 0.027** 0.031**(0.013) (0.015)

Female -0.163*** -0.163***(0.017) (0.019)

Supervisory responsibilities 0.233*** 0.267***(0.017) (0.018)

Workplace tenure 0.002 0.002*(0.001) (0.001)

Holds multiple jobs -0.040* -0.021(0.023) (0.026)

Recent unemployment -0.012 -0.023(0.015) (0.016)

Self-reported performance 0.021*** 0.021***(0.003) (0.004)

Locus of control 0.004*** 0.004***(0.001) (0.002)

Workplace controls Yes Firm FE

Country controls Yes Yes

Observations 7,086 7,086R-squared 0.796 0.816Robust standard errors in parentheses, clustered at firm levelStatistical significance: *** p<0.01, ** p<0.05, * p<0.1

Appendix Table A1: Personality Trait Locus of Control

All Armenia Azerbaijan Kazakhstan Kyrgyzstan Russia SerbiaPersonality trait componentsInternal LOCSuccess comes from hard work, not luck 3.45 3.51 3.02 3.56 3.67 3.29 3.76

(1.24) (1.18) (1.45) (1.18) (1.26) (1.22) (1.00)People get respect deserved 3.72 3.83 3.30 3.89 4.03 3.68 3.54

(1.16) (1.09) (1.32) (1.02) (1.16) (1.25) (0.85)I can make my plans work 3.68 3.82 3.38 3.85 3.78 3.50 3.85

(1.02) (0.99) (1.00) (1.01) (1.02) (1.09) (0.78)I control what happens to me 3.72 3.61 3.75 3.97 3.85 3.54 3.79

(1.11) (1.11) (1.26) (1.00) (1.14) (1.17) (0.71)Getting what I want has little to do with luck 3.38 3.41 2.90 3.67 3.40 3.41 3.55 (1.14) (1.07) (1.33) (1.09) (1.18) (1.16) (0.79)External LOCWithout right breaks, cannot be good leader 3.69 3.69 3.75 3.77 3.67 3.63 3.71 (1.14) (1.10) (1.29) (1.12) (1.23) (1.21) (0.70)Unhappy outcomes caused by bad luck 3.22 3.32 3.46 3.51 2.90 2.95 3.47 (1.19) (1.10) (1.31) (1.19) (1.26) (1.20) (0.80)Promotions depend on luck 3.51 3.57 3.48 3.61 3.60 3.54 3.20

(1.20) (1.16) (1.29) (1.17) (1.33) (1.24) (0.81)Life is controlled by accidents 3.38 3.48 3.32 3.65 3.34 3.37 3.15

(1.10) (1.04) (1.12) (1.05) (1.21) (1.17) (0.82)I have no influence over things that happen to me 3.06 3.23 3.21 3.39 2.92 2.94 2.77 (1.20) (1.10) (1.21) (1.20) (1.32) (1.22) (0.98)Locus of Control (LOC) 1.09 0.87 (0.86) 1.01 2.30 1.00 2.20

(5.10) (4.49) (6.38) (4.43) (4.94) (5.73) (2.68)

Observations 7,086 1,493 958 757 1,189 1,769 920For each statement, participants given a 5-point scale: 1 = strongly disagree ; 5 = strongly agreeThe LOC variable is constructed by summing the first 5 components (internal LOC), and the second five components (external LOC),and then using the formula: LOC = (internal - external).

Appendix Table A2: OLS Regression Results; Work Ethic and Generation, by country

Armenia Azerbaijan Kazakhstan Kyrgyzstan Russia Serbia

Young (born after 1981) 5.728** 0.982 1.340 6.066** 7.077** 4.430(2.613) (5.353) (4.691) (2.324) (2.729) (2.975)

Middle (born 1976-1981) 4.054* -0.670 0.0824 5.661*** 7.251*** 4.235*(2.111) (4.555) (3.817) (1.967) (2.408) (2.224)

Older70s (born 1970-1975) 2.789 -2.374 -0.324 3.633** 2.653 3.122*(1.820) (3.877) (3.335) (1.774) (1.807) (1.737)

Older60s (born 1960-1969) 1.351 -0.271 1.573 1.210 1.289 1.920**(1.110) (2.952) (1.895) (1.286) (1.244) (0.863)

Age 0.137* -0.0255 -0.106 0.144** 0.189** 0.240**(0.076) (0.170) (0.149) (0.071) (0.086) (0.087)

Years of schooling 0.323** 0.190 0.485** 0.0129 0.042 -0.066(0.141) (0.193) (0.238) (0.0867) (0.138) (0.192)

Married 0.878 0.246 1.972** -1.049* 0.361 0.367(0.534) (0.884) (0.771) (0.603) (0.645) (0.693)

Female -1.989*** 0.955 -2.443*** -0.117 -0.808 0.914(0.513) (1.082) (0.923) (0.795) (0.632) (0.781)

Supervisory responsibilities -0.957 1.711 -1.417 1.559*** 2.186*** 0.358(0.644) (1.104) (0.867) (0.586) (0.779) (0.696)

Years at current workplace -0.037 -0.144 -0.031 -0.002 0.078 0.058(0.060) (0.102) (0.076) (0.056) (0.048) (0.135)

Holds multiple jobs -0.066 -2.056* 0.280 0.245 1.309 -1.207(0.778) (1.029) (1.044) (1.114) (0.964) (2.247)

Recent unemploy experience 0.928 -3.624*** -1.456 0.603 0.926 0.014(0.669) (1.157) (1.032) (0.617) (0.902) (0.667)

Relative earnings 1.063** 0.909 -0.249 0.875 0.491 -1.070(0.493) (1.070) (1.296) (0.736) (0.566) (1.141)

Self-reported performance 0.054 0.706** 0.726** 0.369* 0.572** -0.178(0.141) (0.284) (0.307) (0.197) (0.226) (0.162)

Locus of control 0.413*** 0.443*** 0.321*** 0.381*** 0.468*** -0.245*(0.075) (0.125) (0.105) (0.080) (0.071) (0.140)

Workplace controls Yes Yes Yes Yes Yes Yes

Observations 1,493 958 757 1,189 1,769 920R-squared 0.090 0.232 0.089 0.058 0.121 0.083

Workers born before 1960 are omitted (reference) group.Robust standard errors in parentheses, clustered at firm level.*** p<0.01, ** p<0.05, * p<0.1

The coefficients and estimated standard errors are scaled by 100.

Appendix Table A3: OLS Regression Results; Earnings and Work Ethic

Basic FE Basic FE Basic FE Basic FE Basic FE Basic FEWork ethic 0.203 0.322* 0.012 -0.054 -0.054 -0.056 0.133 0.124 0.170 0.157 -0.012 0.043

(0.124) (0.166) (0.099) (0.207) (0.207) (0.262) (0.129) (0.144) (0.125) (0.138) (0.126) (0.115)

Age 0.005 0.010 0.039*** 0.0435*** 0.044*** 0.046*** 0.023*** 0.025*** 0.047*** 0.048*** -0.000 0.003(0.007) (0.009) (0.007) (0.012) (0.012) (0.014) (0.007) (0.009) (0.009) (0.009) (0.015) (0.014)

Age squared -0.006 -0.012 -0.044*** -0.047*** -0.047*** -0.051*** -0.023*** -0.024** -0.053*** -0.054*** 0.008 0.006(0.008) (0.011) (0.008) (0.015) (0.015) (0.018) (0.008) (0.009) (0.010) (0.011) (0.020) (0.019)

Years of schooling 0.030*** 0.040*** 0.026*** -0.021 0.043*** 0.047*** 0.011*** 0.016*** 0.026*** 0.029*** 0.035*** 0.040***(0.007) (0.009) (0.006) (0.040) (0.009) (0.011) (0.004) (0.005) (0.006) (0.007) (0.007) (0.007)

Married 0.042* 0.057* 0.021 -0.124*** -0.021 -0.023 0.017 0.040 0.030 0.036 0.007 0.013(0.025) (0.030) (0.032) (0.034) (0.040) (0.049) (0.037) (0.042) (0.028) (0.030) (0.012) (0.013)

Female -0.096*** -0.108*** -0.240*** 0.043*** -0.124*** -0.112** -0.131*** -0.138*** -0.289*** -0.324*** -0.026 -0.015(0.028) (0.034) (0.029) (0.009) (0.034) (0.046) (0.032) (0.038) (0.041) (0.047) (0.017) (0.016)

Supervisory responsibilities 0.221*** 0.250*** 0.223*** -0.132*** 0.091*** 0.138*** 0.226*** 0.233*** 0.257*** 0.281*** 0.334*** 0.324***(0.032) (0.038) (0.040) (0.031) (0.028) (0.031) (0.038) (0.042) (0.037) (0.041) (0.035) (0.040)

Workplace tenure -0.001 0.003 0.002 -0.055 0.008* 0.011* 0.003** 0.005*** -0.002 -0.002 0.005 0.006(0.002) (0.003) (0.003) (0.048) (0.005) (0.006) (0.001) (0.002) (0.002) (0.003) (0.004) (0.004)

Holds multiple jobs -0.036 -0.047 -0.068* 0.008* -0.055 -0.026 0.075 0.105 -0.125** -0.118** 0.028 0.017(0.034) (0.043) (0.038) (0.005) (0.048) (0.059) (0.060) (0.065) (0.049) (0.051) (0.043) (0.030)

Recent unemployment -0.068** -0.077** -0.003 0.091*** -0.132*** -0.134*** 0.057 0.071 0.004 -0.024 -0.009 -0.015(0.030) (0.037) (0.024) (0.028) (0.031) (0.041) (0.038) (0.043) (0.041) (0.041) (0.024) (0.025)

Self-reported performance 0.017** 0.022*** 0.013 0.015 0.015 0.018 0.026*** 0.020** 0.034*** 0.036*** 0.001 0.001(0.007) (0.008) (0.008) (0.011) (0.011) (0.015) (0.008) (0.008) (0.008) (0.009) (0.004) (0.004)

Locus of control 0.007** 0.007* 0.002 0.008 0.008 0.006 -0.002 -0.003 0.006** 0.006* 0.003 0.001(0.003) (0.004) (0.002) (0.005) (0.005) (0.007) (0.002) (0.002) (0.003) (0.003) (0.003) (0.003)

Workplace controls Yes Firm FE Yes Firm FE Yes Firm FE Yes Firm FE Yes Firm FE Yes Firm FECountry controls Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Observations 1,493 1,493 958 958 757 757 1,189 1,189 1,769 1,769 920 920R-squared 0.626 0.664 0.653 0.684 0.570 0.612 0.431 0.476 0.439 0.467 0.741 0.759Robust standard errors in parentheses, clustered at firm level *** p<0.01, ** p<0.05, * p<0.1

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