Determinants of Subjective Well-Being
A Romanian Case Study
Cristina Bratu
Economics 399
January 26, 2011
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1. Introduction
Survey data has shown that countries in Eastern Europe have consistently
reported, on average, lower levels of life satisfaction and happiness than their Western
counterparts over the past two decades (see Graph 1 and Table 1 in the Appendix). Only
a small portion of the literature on subjective well-being is dedicated to investigating this
region, so this paper aims to fill this gap by empirically examining the evolution of the
determinants of subjective well-being in Romania, from 1990 to the present.
In the 1970s, the idea that a higher income always produces higher utility was
hardly disputed. Easterlin (1974) then published his seminal paper in which he argued
that over time, increasing levels of income do not necessarily translate into higher levels
of life satisfaction, which contradicted everything that standard economic thought took
for granted up until that point. There has since been an ongoing debate between
supporters and opponents of the so-called “Easterlin paradox”, thanks to which there is
now a significant amount of research in the field of happiness economics. The general
consensus is that in a particular society, at a given point in time, the wealthy are generally
happier than the poor (Di Tella and MacCulloch 2006: 26). Easterlin and his followers
then argue that this pattern does not hold over time, which implies that economic
development is essentially useless in improving individual well-being. Stevenson and
Wolfers (2008) provide an extensive review of the arguments on the other side of the
debate.
Though attempting to establish the precise relationship between income and life
satisfaction has so far been the main focus of this literature, a number of researchers have
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shifted their attention to other determinants of well-being. For example, there has been
consistent evidence that the unemployed tend to be less happy than the employed (see
e.g. Frey and Stutzer (2002), Oswald (1997)), that married people are happier, on
average, than those who are single (e.g. Oswald (1997)), that those who believe in God
are more satisfied with their lives than those who do not (e.g. Frey and Stutzer (2002))
and that a good state of health is generally positively associated with subjective wellbeing (e.g.. Helliwell and Putnam (2004)). More recently, some researchers have argued
that institutional aspects also factor in individual happiness functions. Inglehart and
Klingemann (2000) argue that people who live in flourishing democratic countries are
happier than those in less democratic environments (179). The extent to which people act
upon their right to civic participation also seems to influence their well-being, according
to Frey and Stutzer (2002:136). These last two factors seem particularly interesting to
investigate in the Romanian context, as the country makes its transition to a democratic
state.
This paper is organized as follows. Section 2 gives a brief overview of the
concept of subjective well-being. Section 3 addresses some methodological concerns
associated with using subjective measures in economics. Section 4 talks about
Romania’s recent history and hypothesizes about the nature of the relationship between
life satisfaction and income in Romania over the two decades in question. Section 5
describes the data to be used. Section 6 briefly outlines the empirical strategy. Section 7
summarizes some preliminary results.
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2. Subjective well-being (SWB): a brief overview of the concept
In standard economic theory, it is generally assumed that people always behave in
a way that maximizes utility, thus individuals’ observed choices (revealed preferences)
should provide enough information for economists to infer how their utility functions
look like (Frey and Stutzer 2002: 19-20). In simpler words, individuals are presumed to
make only decisions that make them happy. This cardinal approach, though still
widespread has lately been challenged by skeptical economists who are not as willing to
put an equal sign between revealed preferences and happiness (Frey and Stutzer 2002:
20). They (reasonably) claim that a subjective approach needs to complement the
objective one because “everybody has their own ideas about happiness and the good life
and that observed behavior is an incomplete indicator for individual well-being” (Frey
and Stutzer 2002a: 405). They believe that actually listening to what people have to say
about their overall happiness and satisfaction with life is a good start to figuring out what
“makes people tick” (Oswald 1997:1816). Thus, for their data, they turn to global selfreports that include questions on life satisfaction and happiness. It has now become
standard practice to use survey data to examine the determinants of subjective well-being
(SWB). Note that subjective well-being, life satisfaction and happiness are generally
used interchangeably in the literature. I will do the same throughout this paper.
3. Methodological concerns
Given the subjective nature of the well-being concept, a number of
methodological issues will undoubtedly arise during the attempt to investigate its
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determinants empirically. It is important to acknowledge the limitations of this type of
research so as not to overestimate the significance of our results.
Though psychologists may use more diversified measures of individual wellbeing, economists choose to rely mostly on self-reported levels of life satisfaction and
happiness, as these transpire from surveys. This evaluation method already poses a
number of problems. By their very nature, surveys are vulnerable to all sorts of biases,
no matter how much effort one puts into designing them. Such seemingly harmless
details as wording or ordering of questions can significantly influence the way people
respond to these surveys (Frey and Stutzer 2002a: 406), especially when it comes to
something as problematic – in terms of the non-existence of a one-fits-all type of
definition – as subjective well-being. One can also expect that some respondents are
either unwilling to be completely honest when filling out a survey, or that they let
themselves be influenced by “transitory moods” (Bok 2010: 35) or by what they think
would be socially desirable answers, which unintentionally leads to less than honest
responses (Easterlin 1974: 97). These types of occurrences can clearly take away from
the reliability and validity of the collected data (Frey and Stutzer 2002: 32).
But in order not to hastily discard happiness data as unreliable, we have to make
an important distinction. Undoubtedly, personality traits such as a certain inclination to
perceive things, in a more positive or a more negative light, will have an effect on how
people rate their overall satisfaction with life (Bok 2010: 37). But such responses, though
sometimes questionable from an outsider’s point of view, cannot be dismissed as
“inaccurate”, since we’re assuming that people are the best judges of what makes them
happy; they can at most be considered “unreasonable”, as Bok (2010) emphasizes (35).
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Though I acknowledge the measurement issues that happiness data is vulnerable
to, I will assume –as is common practice in the literature – that it will be reliable enough
to produce trustworthy results. Also, since economists who study happiness reject from
the very beginning the idea that well-being can be simply inferred from people’s
observed choices, subjective measures of life satisfaction are, for economists’ purposes,
the only measures at hand (i.e. survey data will have to make do).
4. What’s up with Romania?
The Romanian case is interesting to study in the realm of subjective well-being
for a number of reasons. First, one can expect a great deal of wishful thinking associated
with the fall of the regime that resulted from the 1989 Revolution (by that date, Romania
had been a communist state for more than four decades). As the shift to a democratic
state occurred (at least formally) in 1989, most people must have had high expectations
concerning the future, especially given the fact that the socioeconomic conditions of the
country had greatly worsened in the 1980s. But these expectations had, more often than
not, no realistic basis. It is probably fair to assume that the majority of the population did
not know how a market economy really worked. As massive lay-offs took place in all
fields of the economy, but especially in the overstaffed heavy industry – to name just one
of the immediate consequences - the relative stability that communism had ensured
quickly turned into a widespread feeling of uncertainty soon after 1989 (Smith 2001:
129).
We should therefore expect subjective well-being to have been negatively
affected during transition due to at least two complementary phenomena. First,
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aspiration-level theory would suggest that, at any given point in time, people evaluate
their life in terms of a certain level of aspiration, which they form based on their hopes
and expectations of the future at that particular point in time (i.e. this level is not
constant, it adjusts over time). If an individual does not achieve his aspiration level, he is
very likely to suffer a loss in his subjective well-being (for in-depth discussions of the
theory, see e.g. Siegel (1957), Easterlin (1974), Frey and Stutzer (2002), Hayo and Seifert
(2003)). As unemployment rose (a concept with which most people were not really
familiar with at that point) and GDP fell by 25% only in 1990-2 (Smith 2001:129), we
can expect that a lot of Romanians experienced not only the psychological impact from
not having their expectations fulfilled, but also the very tangible impact of having their
incomes sliced.
GDP started to slightly pick up soon after, although up until 2008, it faced a rather
bumpy road, with both positive and negative growth rates (see Graph 2 in the Appendix).
It will be interesting to observe whether at the individual level, subjective well-being
follows the same pattern as GDP. In his discussion of life satisfaction in transition
countries, Easterlin (2009) suggests that the “loss aversion” theory formulated by
Kahneman et al. (1991) may explain much of the fluctuation in subjective well-being that
is observed in these countries. According to this theory, an increase in income is valued
less - in terms of its impact on life satisfaction - than a decrease of the same amount
(Easterlin 2009: 10). His data also reveals that people find it more difficult to recover
from a loss than to adapt to a gain in income (Easterlin 2009:11-12). This would suggest
that income and subjective well-being need not follow the same path, i.e. that life
satisfaction can, in principle, fall behind income at a given point in time (Easterlin 2009:
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12). It is early to predict what the case for Romania would be, but this theory is
definitely worth keeping in mind when trying to explain the causes behind the way the
determinants of subjective well-being have evolved over time.
5. Data
The data used comes from the European Values Study (EVS), a cross-national
and longitudinal survey that provides insight into Europeans’ views on life, family, work,
religion, politics and society (EVS). The sample of respondents differs every year, i.e.
the EVS does not follow the same people over time. The size of the representative,
stratified random sample varies each year, but it converges to 1500 adults (18 and older).
However, it is likely that this sample size will get reduced when I actually run
regressions, since there are missing values for some questions. I do not expect this to
significantly affect my results. The study has been conducted in Romania in 1990,
1999/2000 and most recently in 2008. The availability of three different survey waves
allows for a time-series analysis that will help establish whether the determinants of
subjective well-being have changed over time. Given Romania’s recent history, being
able to look at this evolution will be particularly revealing.
EVS has two questions that address the notion of subjective well-being. The first
one asks people whether taking all things together, they would say they are very happy,
quite happy, not very happy or not at all happy. The second one asks participants, all
things considered, how satisfied they are with their life as a whole these days; they are
given a scale of 1 to 10 from which to choose their level of life satisfaction (where 1 is
dissatisfied and 10 is satisfied).
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The EVS also asks people about their annual income levels (they are given
income ranges from which to choose) and about certain demographics such as age,
gender, legal marital status, educational level, and employment status. The income
variable will be slightly problematic to interpret because the ranges are clearly not
descriptive enough (see Table 2 in the Appendix). More than a third of the sample
belongs to the lowest three categories but that shouldn’t imply that a third of the entire
population lives off just below €6,000 a year. One thing to keep in mind, for example, is
that 44.9% of the population lives in rural areas (Romanian Statistical Yearbook 2007).
One can thus expect that a lot of respondents grow their own food or have family who do,
which means that they would need a smaller share of their income to go towards food
consumption. Including a rural-urban dummy variable would probably control for some
of this variation. Other indicators, such as expenditure levels, or whether the respondent
owns a house or a car, would also give a better idea of the actual economic status of the
respondent. The Research Institute for the Quality of Life in Romania puts out an annual
report on the perceived quality of life in Romania. They administer their own surveys, in
which they ask participants what the different sources of their income are. I will try to
get access to their data so that I can assemble a more accurate measure of economic wellbeing.
In the EVS study, participants are also asked about their educational level and
their occupational status. They self-rate their state of health and provide answers to
questions that have to do with what they value (or don’t value, for that matter), such as:
religion, satisfaction with democracy, and confidence in the government and the health
care system. In keeping with previous findings, I will use these as explanatory variables.
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Since there are multiple questions on each of these broader concepts, I will have to decide
the answers to which question would be more revealing in the Romanian context. For
example, if I were to use church attendance as a measure of religiosity, that wouldn’t be
particularly relevant because the general attitude is that “you can pray at home, too”, so
lower values on that variable wouldn’t necessarily mean that the respondent is less
religious.
The quantitative data provided by the EVS data will be complemented by
qualitative data obtained from conducting face-to-face interviews over the summer in
Romania. The sample is really small (around 50 respondents) and by no means
representative since I used a snowball sampling technique to identify participants. Even
though the interview was a semi-structured one, I designed it in such a way that most of
the questions asked were closely related to EVS questions relevant to the present research
(see end page of Appendix for the list of questions). I am hopeful, then, that the
interviews will prove helpful in explaining some of the results obtained from the EVS
data.
6. Model
As suggested by Frey and Stutzer (2002a) or Hayo and Seifert (2003), among
others, I will estimate the SWB function using an ordered logit model. For present
purposes, this seems to be the most appropriate model as it captures the fact that
assigning a certain value to the SWB variable does not occur arbitrarily. For example, a
score of 10 on the life satisfaction measure is higher than a score of 8, and this
observation in and of itself is already telling (Wooldridge 2002: 504). Frey and Stutzer
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(2002a) argue that the ordered logit “allows us to analyze each factor that is correlated
with reported subjective well-being separately”, which is exactly what this paper wants to
look at (406). In its roughest form, the model can be written as:
SWBit=α+ β*incomeit + γ*Xit + εit
where Xit is a vector of known socio-demographic characteristics, as well as different
attitudes of the individual i at time t (i.e. year of the survey wave) and εit captures
measurement errors and unobserved characteristics (such as personality traits).
Specific variables that are included in the Xit vector are, for reasons outlined in
previous sections: age, gender, marital status, employment status, educational level, selfreported health status, location (urban/rural), religion (I am currently inclined to include
the answers to the “Do you believe in God?” question), satisfaction with democracy (“On
the whole are you very satisfied, rather satisfied, not very satisfied or not at all satisfied
with the way democracy is developing in our country?”), confidence in the government
(a great deal, quite a lot, not very much or none at all), confidence in the health care
system (a great deal, quite a lot, not very much or none at all).
Both the income variable and most of the variables included in the Xit vector are
categorical. In order to capture the effect that each category has on the dependent
variable, I will break them down into dummy variables.
With regards to the dependent variable, as I have mentioned before, the terms
“life satisfaction” and “happiness” are usually used interchangeably because they tend to
be highly correlated. It is thus fair to assume that it wouldn’t make much of a difference
which of these two variables is going to be used as the dependent variable. However, my
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experience conducting interviews that included both life satisfaction and happinessrelated questions tells me that people (or at least people in Romania) tend to associate the
concept of “life satisfaction” with quantifiable or tangible aspects of their lives, such as
income, employment status and whether they afford taking a vacation or not. As such,
participants responded almost immediately with a number from 1-10. On the other hand,
asking about their “happiness” almost always resulted in either having to wait longer
before getting an answer or in people’s unwillingness to answer at all. My conclusion
from this is that the term “happiness” itself has a different resonance in people’s minds
than “life satisfaction” does; perhaps there’s a certain state of mind or spiritual well-being
that tends to factor in people’s level of happiness that doesn’t really matter when people
talk about how satisfied they are with their lives. Life satisfaction seems to be more
“accounting” than anything else. This would suggest that the answers to the “life
satisfaction” question are relatively more objective than those provided for the
“happiness” question.
The different reactions that these two questions give rise to might also have
something to do with the way “satisfied” and “happy” translate in Romanian. Translation
difficulties are often cited in the literature as potential creators of bias (see e.g. Easterlin
(1974), Inglehart and Klingemann (2000), Oswald (1997), Diener and Suh (2000)).
However, researchers generally agree that the effect of linguistic differences tend to wash
out in cross-country analyses. For the sake of curiosity, in the Romanian dictionary,
someone who is “satisfied” is described as someone who has everything he needs;
someone who is “happy”, on the other hand, finds himself in a state of complete spiritual
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satisfaction (own translation, DEX Online). Here, as well, we note the material vs.
spiritual dimensions associated with life satisfaction and happiness, respectively.
In light of the criticism that the type of data happiness economists use can hardly
be trusted due to the fact that it is not “objectively observable” (Frey and Stutzer 2002a:
404), using the “life satisfaction” variable as the dependent variable would address some
of this criticism. However, it would also miss an important dimension of subjective wellbeing that can only be captured by the “happiness” variable, as intuitively explained
above. The choice is then rather difficult to make. Ultimately, I will have to decide
which variable will provide the most accurate results (that is, given their intrinsic
subjectivity).
When it comes to interpreting the results that the model will generate, we should
be wary about establishing causal relationships. For example, will a positive correlation
between marriage and happiness imply that marriage causes happiness or that happiness
promotes marriage (Frey and Stutzer 2002: 57)? It could go both ways and I expect that
no correlation will lead me to conclude that causality unambiguously points in one
direction or another.
7. Preliminary Results
So far, I have run a number of linear regressions with the life satisfaction variable
as my dependent variable and I have included the following as my explanatory variables:
dummy variables for income categories, state of health, satisfaction with democracy,
employment status, marital status and belief in God. I have summarized the results for
one of my regressions in Table 3 in the Appendix. These results should be viewed in
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light of the fact that this regression is both wrongly specified (since it is linear) and
incomplete (as it does not include all variables I mentioned in the previous section).
However, they are good indicators of where to look next. Out of all variables, income
seems to be, oddly enough, the least significant. Moreover, it follows a nonlinear path
that is hard to interpret at this point. The health variable is as of now the strongest
predictor of life satisfaction, and the satisfaction with democracy variable seems to be
pointing towards something, though it is not yet clear towards what. I am confident,
however, that a better specified model will reveal more telling findings.
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Appendix
Graph 1. Subjective well-being by level of economic development. World Values
Surveys; GNP/capita purchasing power estimates from World Bank, World Development
Report, 1997. Source: R.Inglehart and H-D. Klingemann, "Genes, Culture and
Happiness," MIT Press, 2000.
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Table 1. Percent who responded “very happy” in the 2008 wave of the European Values
Study in a number of European countries. Source: European Values Study 2008
% very happy
Moldova
8.7%
Russian Federation 10.0%
Romania
12.2%
Ukraine
12.3%
Bulgaria
14.7%
Hungary
16.8%
Poland
20.4%
Austria
29.6%
France
35.0%
Switzerland
42%
Belgium
44%
The Netherlands
54%
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10
GDP growth rate
5
0
-5
-10
-15
Year
Graph 2. GDP growth rate 1990-2008. Source: Eurostat and Smith, Alan. "The
Transition to a Market Economy in Romania and the Competitiveness of Exports." PostCommunist Romania: Coming to Terms with Transition. By Duncan Light and David
Phinnemore. Houndmills, Basingstoke, Hampshire: Palgrave, 2001. 127-49.
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Table 2. Annual household income categories and their respective frequencies.
Source: European Values Study 2008
Categories
Frequency
Less than €1,800
221
€1,800 to under €3,600
329
€3,600 to under €6,000
307
€6,000 to under €12,000
165
€12,000 to under €18,000
56
€18,000 to under €24,000
33
€24,000 to under €30,000
23
€30,000 to under €36,000
13
€36,000 to under €60,000
13
€60,000 to under €90,000
8
€90,000 to under €120,000 4
€120,000 or more
2
Total: 1,174
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Table 3. OLS Results with life satisfaction as the dependent variable
Coefficient Standard Error t
Income_CAT2
.157
.304
0.52
Income_CAT3
.406
.341
1.19
Income_CAT4
.567
.436
1.30
Income_CAT5
-1.247
.765
-1.63**
Income_CAT6
.173
.833
0.21
Income_CAT7
.575
.926
0.62
Income_CAT8
.401
1.147
0.35
Income_CAT9
.012
1.818
0.01
Income_CAT10
3.30
1.459
2.26*
Income_CAT11
-1.839
2.525
-0.73
Health_very_good
2.977
.612
4.86*
Health_good
2.103
.506
4.15*
Health_fair
1.802
.500
3.60*
Health_poor
1.063
.535
1.99*
God
1.711
1.058
1.62**
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Democracy_very
.939
.733
1.28
Democracy_rather
1.201
.381
3.15*
.363
1.26
Democracy_not_very .457
Employed
-.184
.331
-0.56
Self-employed
-.912
.672
-1.36
Married
.566
.418
1.35
Widowed
.099
.485
0.21
Divorced
.146
.656
0.22
Separated
-1.534
1.49
-1.03
*significant at the 5% level
**significant at the 10% level
Notes:







Number of observations: 506.
Adjusted R-squared: 0.1080.
Income_CAT12 was omitted because there were only 2 observations belonging to
that category. The reference category for the Income variable is the first income
category.
The reference category for the Health variable is the very poor health category.
The reference category for the Democracy satisfaction variable is the not at all
satisfied category.
The reference category for the Employment Status variable is never had a paid a
job.
The reference category for the Marital Status variable is no legal marital status.
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List of questions
Note: This may not have been the exact order in which questions were asked. Also, in
some cases, some questions were added to or taken out of this list at the time the
interview was conducted.
1. On a scale from 1 to 10, how satisfied are you with your life as a whole? (1 = not
at all satisfied, 10 = very satisfied)
2. All things considered, would you say you are: very happy, happy, rather happy or
not at all happy?
3. What is your current employment status?
4. How important is work in your life? (Maybe follow up with: Do you think you
would work if money were not an issue?)
5. Would you say that, in any given year, you are able to put some money aside?
6. When you are able to do so, why do you put money aside?
7. What is the highest educational level that you have attained?
8. True or false: It is fair for someone with a higher education to earn more money
than someone with less education.
9. How old were you when the communist regime fell?
10. Do you think Romania is now better or worse off than it was before 1989?
11. Do you think your individual well-being is influenced by the state of the country in
general?
12. What do you think are the government’s main responsibilities?
13. Are you happy with the current government?
14. Would you say that you live in a tolerant environment?
15. Do you feel like you are in control of your life?
16. Do you believe in fate?
17. Do you believe in God?
18. How often do you go to church?
19. What is your current marital status?
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Works Cited
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