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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?
1
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 .
2
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
3
(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
4
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
5
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.
6
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.
7
(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-
8
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.
9
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
10
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).
11
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).
12
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.
13
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.
14
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).
15
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
SerbiaArmenia Azerbaijan Kazakhstan Kyrgyzstan Russia
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