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The curved relationship between subjective well-being and age

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PARIS-JOURDAN SCIENCES ECONOMIQUES
48, BD JOURDAN E.N.S. 75014 PARIS
TEL. : 33(0) 1 43 13 63 00 FAX : 33 (0) 1 43 13 63 10
www.pse.ens.fr
WORKING PAPER N° 2006 - 29
The curved relationship between
subjective well-being and age
Andrew E. Clark
Andrew J. Oswald
JEL Codes : C23, I31, J10
Keywords : Happiness, ageing, well-being
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE ÉCOLE DES HAUTES ÉTUDES EN SCIENCES SOCIALES
ÉCOLE NATIONALE DES PONTS ET CHAUSSÉES ÉCOLE NORMALE SUPÉRIEURE
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The Curved Relationship Between
Subjective Well-Being and Age
Andrew E. Clark
PSE and IZA, Paris, France
Email: andrew.clark@ens.fr
Andrew J. Oswald
University of Warwick, UK
Email: andrew.oswald@warwick.ac.uk
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The Curved Relationship Between
Subjective Well-Being and Age
October 10, 2006
Abstract
This article is concerned with a body of work on happiness and age represented by
important papers such as Mroczek and Kolarz (1998) and Mroczek and Spiro (2005).
Using a large British data set, the paper presents new longitudinal evidence. It also
points out that, perhaps unknown to many psychologists, a parallel literature on this
topic exists in economics journals. The paper shows that subjective well-being follows
a U-shape through the life course. We argue that eventually the two literatures will
have to be made consistent with one another, and suggest that, although it is not easy to
live in both worlds, with their different styles and conventions, economists and
psychologists still have much to learn from one another.
Keywords: Happiness; ageing; well-being
Corresponding author: andrew.oswald@warwick.ac.uk.
Address: Department of Economics, University of Warwick, Coventry CV4 7AL,
United Kingdom.
Telephone: (+44) 02476 523510
Acknowledgements: Paris-Jourdan Sciences Economiques (PSE) is a Joint Research
Unit CNRS-EHESS-ENPC-ENS. The second author’s work was funded by an
ESRC professorial research fellowship
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The Curved Relationship Between
Subjective Well-Being and Age
The relationship between happiness and age is important but still imperfectly understood. On
page 1336 of an interesting article in this journal, Mroczek and Kolarz (1998) state that, to
their knowledge, “no previous study has considered the possibility of nonlinear relationships
between age and happiness.” A follow-up study by Mroczek and Spiro (2005) is in the same
spirit but uses different methods. The former article finds that positive affect has an
upwardly curved component; the latter suggests that subjective well-being follows an
inverted U-shape and peaks at around age 60. On our reading of these two papers, they are
important work. They are currently acquiring high numbers of citations in the Social Science
Citation Index. A literature in psychology journals is growing up around them.
We present new longitudinal evidence on this issue. Its chief finding does not seem to exist
in the psychology journals. A second aim of our article is to alert psychologists to a parallel
literature on the nonlinear relationship between happiness and age. It is research published
mainly in economics journals. This stream of work may have originated from Clark and
Oswald (1994). Using a 12-item measure of psychological well-being, and a cross-section of
6100 randomly sampled Britons from the first wave of the British Household Panel Survey,
that paper found mental well-being to be U-shaped in age. The authors’ data were for 1991.
The paper drew the conclusion that the happiness minimum along the U is reached around a
person’s mid-30s.
Since then, a body of work by economists and statisticians has suggested, across a range of
settings, that the relationship between subjective well-being and age is curved. Almost every
study replicates the basic conclusion: that happiness is U-shaped in age, with a minimum
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point in a range from the mid-30s to approximately the late-40s. The result has now been
demonstrated for perhaps fifty nations. It has been found especially in data from Western
countries such as the United States, the United Kingdom, Australia, France, Italy, Belgium,
Germany, Spain, and Switzerland.
The U-shape in age is documented in, for example, Gerlach and Stephan (1996), Oswald
(1997), Theodossiou (1998), Winkelmann and Winkelmann (1998), Di Tella et al (2001),
Frey and Stutzer (2002), Helliwell (2003), Blanchflower and Oswald (2004), Graham (2005),
Frijters et al (2004, 2005), Senik (2004), Van Praag and Ferrer-i-Carbonell (2004), Clark
(2005), Long (2005), Shields and Wheatley Price (2005), Propper et al (2005), Powdthavee
(2005), Bell and Blanchflower (2006), and Uppal (2006). Blanchflower (2001) documents
the U-shape in 23 East European transition nations. Di Tella et al (2003) provides the same
for 12 separate Western industrial nations. Clark et al (1996) makes a similar argument for
job satisfaction equations, and also gives some results for mental well-being equations.
Recently, Blanchflower and Oswald (2006), using data on approximately half a million
Europeans and Americans, argues that allowance for the inclusion of cohort effects makes
little difference to the finding of a U-shape.
These papers’ methods vary slightly. Nevertheless, each of them, as in the work of Mroczek
and Kolarz (1998), draws upon multiple-regression models. In this way, factors other than
age are held constant.
We here report briefly an updated version of the results of Clark and Oswald (1994). Since
then, the British Household Panel Survey has happened annually, so it is possible to re-do
those calculations on a longitudinal data set now exceeding 100,000 observations. A new
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test can now be done, in which both fixed-effects and age can be allowed for in a multiple
regression equation framework.
One variable we use is life satisfaction. It is measured on a seven point scale from 1 (not
satisfied at all) to 7 (completely satisfied). Over all 14 waves of the BHPS, this has a mean
of 5.19 with standard deviation 1.26.
Another is a General Health Questionnaire (GHQ) score. This is a questionnaire-based
method of measuring psychological well-being and has been used widely in the health and
epidemiological research literature (for recent examples, see Cardozo et al 2000, Martikainen
et al 2003, and Pevalin and Ermish 2004). It amalgamates answers to the following list of
twelve questions:
Have you recently:
1. Been able to concentrate on whatever you are doing?
2. Lost much sleep over worry?
3. Felt that you are playing a useful part in things?
4. Felt capable of making decisions about things?
5. Felt constantly under strain?
6. Felt you could not overcome your difficulties?
7. Been able to enjoy your normal day-to-day activities?
8. Been able to face up to your problems?
9. Been feeling unhappy and depressed?
10. Been losing confidence in yourself?
11. Been thinking of yourself as a worthless person?
12. Been feeling reasonably happy all things considered?
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Responses are made on a four-point scale of frequency of a feeling in relation to a person's
usual state: "Not at all", "No more than usual", "Rather more than usual", and "Much more
than usual".
The between-item validity of the GHQ-12 is high in the BHPS, with a Cronbach alpha of
0.89. For simplicity, we use the so-called Caseness GHQ score, which counts up the number
of questions for which the response is in one of the two "low well-being" categories. This
count is then reversed, to convert it into a well-being rather than ill-being score, which thus
runs from a possible low of 0 (all twelve responses indicating poor psychological health) to a
high of 12 (no responses indicating poor psychological health). The well-being GHQ
measure has mean of 10.14 and standard deviation of 2.92.
Life-satisfaction and GHQ measures of subjective well-being seem valuably complementary.
They capture different aspects of affect. However, as we show below, the two exhibit a
similar pattern over the life course.
Although the size of the BHPS data set has expanded since the initial research was done, and
it is now possible to control for people’s unchanging dispositions (fixed effects), the main
conclusion remains approximately the same as in the simpler evidence of Clark and Oswald
(1994). Both wellbeing-GHQ and life satisfaction are U-shaped across age groups. In the
full longitudinal data set here from 1991 to 2004, it reaches a minimum in the age range 40-
49, which is a little later than the early estimate that came out of our single-year of 1991 data.
The coefficients on the other age-bands reveal a fairly smooth curve -- down and then up --
through the lifespan. This finding is not sensitive to the exact specification of the well-being
equations. The pattern in the raw data is illustrated in Figure 1 for the latest wave at our
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disposal, which is 2004. As is clear from the Figure, it is not necessary to use regression
equations to see the approximate U-shape across age-groups.
It is known that many variables shape subjective well-being (Diener et al 1999, Easterlin
2003, Lucas et al 2004, and Gilbert 2006). If we control in the regression equations for
region, year, income, the work status of the individual (ie. whether employee, self-employed,
unemployed, retired from work), the number of children, gender, marital status, whether a
renter or home-owner, the level of education, and subjective physical health, then, once
again, well-being reaches a minimum in the age band 40-49.
For the formal analysis, as say reported using simple methods in Table 1, it makes no
substantive difference whether we use logistic regression or simple methods like Ordinary
Least Squares (OLS), or random-effects or fixed-effects models. The third column of Table
1 follows the same individuals through time -- annually from 1991 to 2004 -- whilst holding
constant their unchanging fixed-effects, and allowing for many other characteristics such as
marital status. By using banded age dummy-variables, in a way that to our knowledge has
not been done before in longitudinal work of this sort, in either the psychology or economics
literatures, Table 1 provides clear evidence of a U-shape.
Our finding of a U-shape using longitudinal data does not appear to exist in the psychology
literature. It is not clear why the results of this economics research literature differ in some
significant ways from, say, those in Mroczek and Spiro (2005), which finds almost the
reverse -- an inverted U-shape in age. It seems important that future work explore these
interesting issues more fully. A deeper theoretical understanding of the empirical happiness-
age curve will also be required.
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Psychologists were working on well-being data some decades before researchers in
economics (Bradburn 1969, Diener 1984). We hope, nevertheless, that this short article
might be a useful guide to economists’ writings on happiness and age.
Over recent decades, economists -- including ourselves -- have been guilty of not reading the
psychology journals sufficiently. Psychologists, similarly, may not have read the economics
journals as much as might be ideal. Despite the methodological differences, both sides
would, arguably, benefit if we could learn to communicate more effectively.
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Figure 1. Mean Life-Satisfaction and Wellbeing-GHQ in British Data. BHPS Wave 14 (2004)
Mean Life Satisfaction. BHPS 2004
4.7
4.8
4.9
5
5.1
5.2
5.3
5.4
5.5
5.6
16-19 20-29 30-39 40-49 50-59 60-69
Mean GHQ. BHPS 2004
9.85
9.9
9.95
10
10.05
10.1
10.15
10.2
10.25
10.3
10.35
16-19 20-29 30-39 40-49 50-59 60-69
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Table 1. Well-Being Regressions. BHPS Waves 1-14.
No controls Demographic
controls Demographic
controls plus
Individual Fixed
Effects
Age 20-29 -0.154** -0.230** -0.161**
(0.021) (0.023) (0.025)
Age 30-39 -0.224** -0.380** -0.170**
(0.023) (0.029) (0.034)
Age 40-49 -0.315** -0.487** -0.187**
(0.024) (0.031) (0.042)
Age 50-59 -0.155** -0.334** -0.165**
(0.026) (0.032) (0.050)
Age 60-69 0.188** -0.053 -0.061
(0.028) (0.038) (0.059)
Constant 5.339** 5.023** 4.938**
(0.019) (0.036) (0.496)
Observations 90567 87797 87797
R-squared 0.014 0.146 0.025
No controls Demographic
controls Demographic
controls plus
Individual Fixed
Effects
Age 20-29 -0.093** -0.223** -0.228**
(0.036) (0.040) (0.045)
Age 30-39 -0.248** -0.399** -0.374**
(0.042) (0.053) (0.064)
Age 40-49 -0.347** -0.452** -0.464**
(0.045) (0.057) (0.081)
Age 50-59 -0.228** -0.186** -0.314**
(0.048) (0.059) (0.099)
Age 60-69 0.157** 0.197** -0.106
(0.049) (0.067) (0.119)
Constant 10.265** 9.204** 9.625**
(0.032) (0.067) (1.247)
Observations 145424 141875 141875
R-squared 0.003 0.119 0.032
Notes. The omitted age band is 16-19 years old. Standard errors in parentheses.
* significant at 5%; ** significant at 1%. The controls in columns 2 and 3 are for
income, labour force status, number of children, sex, marital status, education,
health,and wave and regional dummies.
Life Satisfaction
GHQ
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... A wealth of research has reported that the cognitive and affective domains of SWB either remain broadly stable or increase across old age (for overviews see Sheldon &Lucas 2014 andRoysamb et al., 2014). For example, regarding the cognitive domain, studies often report mean-level stability of life satisfaction across later adulthood and old age (Larson, 1978;Lucas & Donnellan, 2007;Hamarat et al., 2002), with any declines reported therein typically being small in size and rarely reaching levels reported by younger and middle-aged adults (Baird et al., 2010;Blanchflower & Oswald, 2008;Clark & Oswald, 2006). Because cognitive appraisals of the circumstances of one's life are rooted in early temperamental predispositions that persist into old age (Costa & McCrae, 1980;Harris et al., 2017; see Personality Theories, Table 1.1) evidence of stability presumably reflect the stabilizing influence of personality (e.g., Steel et al., 2008). ...
... Likewise, more participants were included in SOEP (N = 3,418) than BASE-II (N = 1,216), and participants in SOEP covered a wider age range (60-100 years) than those in BASE-II (60-88 years). Hence, the mean-level increase in life satisfaction might have arisen because SOEP included participants in the oldest-old, an age bracket for which some large-scale long-term longitudinal studies have reported increases in life satisfaction (e.g., Clark & Oswald, 2006). ...
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... This critique in turn has produced several replies, indicating that the U-shape exists, even when accounting for these critiques (Blanchflower & Graham, 2020;Blanchflower & Oswald, 2009;Clark, 2019). A further criticism is that a lot of evidence on the U-shape stems from cross-sectional data (Galambos et al., 2020;Ulloa et al., 2013), although some studies confirm the U-shape based on longitudinal data (Cheng et al., 2017;Clark & Oswald, 2006;Van Landeghem, 2012). Looking at cross-sections might produce a U-shape because events can affect disparate age groups differently. ...
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Several studies indicate that happiness follows a U-shape over the life cycle: Happiness decreases after the teenage years until reaching its nadir in middle age. A similar number of studies views the U-shape critically, stating that it is the result of the wrong controls or the wrong model. In this paper, we study the upward-pointing branch of the U-shape, tracing the happiness of European citizens 50 and older over multiple waves. Consistent with a U-shape around middle age, we find that happiness initially increases after the age of 50, but commonly stagnates afterwards and eventually reverts at high age. This pattern is generally observed irrespective of the utilized happiness measure, control variables, estimation methods, and the consideration of selection effects due to mortality. However, the strength of this pattern depends on the utilized happiness measure, control variables, and on mortality effects. The general pattern does not emerge for all countries, and is not always observed for women.
... British (Clark and Oswald, 2006) populations, demonstrating that age-related differences in wellbeing may show a similar picture across cultures. This could be true for gender differences in wellbeing as well, where similar to our findings, a survey in 60 nations found that younger women reported higher levels of overall life satisfaction than young men (Inglehart, 2002). ...
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This study sought to explore the level of personal wellbeing and identified the determinants of happiness among Indian adolescents and youth. Data were collected from a sample of 495 participants (aged 11–23 years) residing in the National Capital Region of Delhi (Delhi-NCR), using the bilingual version (Hindi and English) of the Personal Wellbeing Index (PWI). Their PWI score was 80.06, indicating high happiness levels in the nonwestern normative PWI range. Domains of personal relationship s, community connectedness , and safety represented high overall wellbeing with the highest mean scores. Multivariate analysis showed that the least happy group on life as a whole domain was students aged 19–23 years as compared with the 11–14 and 15–18 years age group. Furthermore, men had higher happiness levels on personal safety , while women had higher scores on life achievement . The qualitative analysis illustrated the socio-cultural basis of these wellbeing determinants as rooted in the hierarchical social structures and collectivistic cultural orientation.
... Recent studies show that the distribution of life satisfaction by age takes the U-shape, with the minimum at the 40-50 years age group ( Helliwell, 2003). Even controlling for cohort effects (Clark, 2007) or unobserved heterogeneity (Clark & Oswald, 2006) the U-shaped pattern still holds. However, there is no consensus in the literature about that -so far psychological literature has shown no relationship between age and life satisfaction (Cantril, 1965;Frijters & Beatton, 2012;Palmore & Luikart, 1972). ...
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Background The aim of this paper is to construct the tool that can be used to measure multidimensional quality of life of persons with disabilities in comparison with population without disabilities for the purpose of monitoring of the UN Convention on the Rights of Persons with Disabilities (UNCRPD). Methods The Sen’s capability approach was applied to conceptualize the quality of life. We followed guidelines of The Quality of Life Framework developed within the European Statistical System. The QoL scores in each domain (covered by the UNCRPD) were constructed using multiply indicators and multiple causes model (MIMIC). All analysis were based on 2018 EU-SILC data for Poland. We constructed quality of life indicators for population with and without disabilities and compared the differences. ResultsPersons without disability experienced higher QoL as compared to population with disabilities, overall and in various domains. Lower average QoL of persons with disabilities is a result of a lower share of those who experience high QoL. The biggest difference is observed for health and for productive and main activity domains. For material conditions and economic security and physical safety there was a moderate difference recorded. For the leisure and social relations domain there is almost no difference observed. Additionally, we identified diversified impact of particular determinants (such as age, gender, household situation, education, partner status, urbanization, health) on the QoL across domains and analysed populations.Conclusions This tool developed in this paper can be calibrated to enable cross-country and in time comparisons between different populations support evidenced-based social policy.
... Healthy women from Austrian families who are under age 25 or are over age 55 are the most likely to be living alone in Vienna (Statistik Journal Wien 2016, p. 22). At the same time, studies have shown that women experience higher levels of well-being than men when living alone (Ballas 2013;Hejj 1997); and that among singles, age typically forms a ushaped relationship with well-being (Ballas 2013;Brown et al. 2016;Clark and Oswald 2006;Fasang et al. 2016). People who are young and healthy might also find it easier to compensate for the lack of family ties with large networks of colleagues and friends (Chandler et al. 2004). ...
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More people than ever are living in cities, and in these cities, more and more people are living alone. Using the example of Vienna, this paper investigates the subjective well-being of single households in the city. Previous research has identified positive and negative aspects of living alone (e.g., increased freedom vs. missing social embeddedness). We compare single households with other household types using data from the Viennese Quality of Life Survey (1995-2018). In our analysis, we consider overall life satisfaction as well as selected dimensions of subjective well-being (i.e., housing, financial situation, main activity, family, social contacts, leisure time). Our findings show that the subjective well-being of single households in Vienna is high and quite stable over time. While single households are found to have lower life satisfaction than two-adult households, this result is mainly explained by singles reporting lower satisfaction with family life. Compared to households with children, singles are more satisfied with their financial situation, leisure time and housing, which helps to offset the negative consequences of missing family ties (in particular with regard to single parents).
... In average, at the age of 53, life satisfaction is at its lowest level of 4.9 and started increasing again with age. This result is commonly found in the literature (see Frey and Stutzer, 2002;Clark, 2003;Blanchflower and Oswald, 2004;Clark and Oswald, 2006;Oswald and Powdthavee, 2008;Pagan, 2010 The level of overlap between equivalised income and equivalent income when identifying the worst-off ...
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The use of multidimensional wellbeing has emerged from a shift of the main focus of policies from income to the consideration of other non-income dimensions. Using the ordered logit fixed effects modelling technique in a life satisfaction regression to estimate coefficients related to income and non-income life domains, the study has examined the computation of a preference-based single index measure of wellbeing called equivalent income. It is noted that one contribution from this study is that the analysis takes into account hedonic adaptation when computing of equivalent income. This aspect is new in the literature and none of the previous studies included adaptation in the estimation of equivalent income. The coefficients related to income and non-income life domains estimated from the life satisfaction regressions are used to calculate equivalent income at the individual level. The results confirm low degree of overlap between individuals with the lowest equivalent income and those worst-off identified by equivalised income and by life satisfaction. The estimated willingness to pay (WTP) for perfect health accounts for a large proportion of equivalised income, while WTP for being employed is quite low. In addition, the findings conclude that across wellbeing measures, women aged 40-50 with lower education, living with other people in an urban area, childless and do not own a home outright are often identified as the worst-off. Regarding adaptation, the results confirm no adaptation to impairment after more than three years since onset.
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In this paper, we employ a correlated random effects econometric framework to simultaneously estimate the within and between effects of age on subjective well-being based on longitudinal survey data from the German Socio-Economic Panel (SOEP). The proposed approach helps to explain differing findings on the relationship between age and subjective well-being reported in a series of studies based on cross-sectional and/or longitudinal panel data. We find empirical support for a wave-like pattern of subjective well-being over the life course. In contrast to the existing literature, our results point to significantly different life cycle patterns for the within- and between-person results. While the between-person results show robust turning points of age around the mid-40s and 90s, the within-person findings indicate that subjective well-being is rather stable between age 16 and 23 and then approaches a local maximum at age 75. We show that the type of variation employed in the empirical analysis (e.g., cross-sectional vs. longitudinal panel) of the age-well-being association has a non-negligible impact on the obtained results and the inferences drawn. Moreover, we do not find support of a U-shape association between subjective well-being and age. This finding holds even if we restrict the sample to those survey respondents aged 18–65 years, indicating that the age-well-being relationship is more complex than a U-shape would predict. A series of additional robustness tests corroborate our main findings.
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W. Wilson's (1967) review of the area of subjective well-being (SWB) advanced several conclusions regarding those who report high levels of "happiness." A number of his conclusions have been overturned: youth and modest aspirations no longer are seen as prerequisites of SWB. E. Diener's (1984) review placed greater emphasis on theories that stressed psychological factors. In the current article, the authors review current evidence for Wilson's conclusions and discuss modern theories of SWB that stress dispositional influences, adaptation, goals, and coping strategies. The next steps in the evolution of the field are to comprehend the interaction of psychological factors with life circumstances in producing SWB, to understand the causal pathways leading to happiness, understand the processes underlying adaptation to events, and develop theories that explain why certain variables differentially influence the different components of SWB (life satisfaction, pleasant affect, and unpleasant affect). (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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How do we measure happiness? Focusing on subjective measures as a proxy for welfare and well-being, this book finds ways to do that. Subjective measures have been used by psychologists, sociologists, political scientists, and, more recently, economists to answer a variety of scientifically and politically relevant questions. Van Praag, a pioneer in this field since 1971, and Ferrer-i-Carbonell present in this book a generally applicable methodology for the analysis of subjective satisfaction. Drawing on a range of surveys on people's satisfaction with their jobs, income, housing, marriages, and government policy, among other areas of life, this book shows how satisfaction with life "as a whole" is an aggregate of these domain satisfactions. Using German, British, Dutch, and Russian data, the authors cover a wide range of topics. This groundbreaking book presents a new and fruitful methodology that constitutes a welcome addition to the social sciences. The paperback edition has been revised to bring the literature review up-to-date and the chapter on poverty has been revised and extended to take account of new research. Available in OSO:
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This paper attempts to explain international trends and differences in subjective well-being over the final fifth of the twentieth century. This is done in several stages. First there is a brief review of some reasons for giving a central role to subjective measures of well-being. This is followed by sections containing a survey of earlier empirical studies, a description of the main variables used in this study, a report of results and tests, discussion of the links among social capital, education and well-being, and concluding comments. The main innovation of the paper, relative to earlier studies of subjective well-being, lies in its use of large international samples of individual respondents, thus permitting the simultaneous identification of individual-level and societal-level determinants of well-being. This is particularly useful in identifying direct and indirect linkages between social capital and well-being.
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The paper studies the labor markets of 23 transition countries from eastern and central Europe—Albania, Armenia, Belarus, Bulgaria, Croatia, Czech Republic, East Germany, Estonia, Georgia, Hungary, Kazakhstan, Kyrgyzstan, Latvia, Lithuania Macedonia, Moldova, Poland, Romania, Russia, Slovakia, Slovenia, Ukraine, and Yugoslavia. It uses new micro-data from a large number of surveys on over 200,000 randomly sampled individuals from these countries for the years 1990–1997. The microeconometric structure of unemployment regression equations in the nations of eastern Europe appears to be similar to the industrialised west. Estimation of east European wage curves produces a local unemployment elasticity of between –0.1 and –0.3. This is somewhat larger in absolute terms than has been found elsewhere. On a variety of attitudinal measures, eastern Europeans said they were less contented than their western European counterparts. The strongest support for the changes that have occurred in eastern Europe is to be found among men, the young, the most educated, students, and the employed and particularly the self-employed. Support for market reforms is particularly low amongst the unemployed who were found to be particularly unhappy on two well-being measures. J. Japan. Int. Econ., December 2001, 15(4), pp. 364–402. Department of Economics, Dartmouth College, New Hampshire 03755; and NBER.