Volunteering and well-being Cristina Rosemberg New Directions
in Welfare II 8 July, Paris
Slide 2
Motivation Explore potential positive effects of participating
on civic engagements and of taking a more active role in society.
Literature have established a positive correlation between
volunteering and well-being (Li&Ferraro, 2005,
Helliwell&Putman, 2004): Formal volunteering have beneficial
effects on subjective well-being, particularly on depression among
older people. Civic engagements have a robust positive correlation
with happiness and life satisfaction However, the positive
correlation found in the literature could be spurious given three
main problems: 1.Reverser causality: does volunteering increases
subjective well-being, or is it that people with higher levels of
well-being is more willing to engage in this type of activities?
2.Self-selection: are there underlying characteristics that make
individuals to selected themselves into the volunteering that are
also correlated with their well- being? 3.Omitted variables: are
there factors which can not observed- that determines a both, a
higher propensity to volunteers and to report higher levels of well
being? (e.g. personality traits).
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Methodology (I) Instrumental variables Need to find an
instrument (Z) that affects Mental Health indirectly just through
its effects on volunteering. More precisely, the instrument has to
full-fill two requirements: 1.Corr(X,Z)!=0 2.Corr(Z,ni)=0
Slide 4
Methodology (II) Data British Household Panel Survey (BHPS) 18
waves, random sample of aprox. 10,000 individuals (5,500 British
households), 15 years and older. Includes measures of well-being,
volunteering, social characteristics How to measure well-being?
Preference satisfaction, hedonic accounts, evaluation accounts
Combined measures: mental health GHQ12 Brief self-report measure,
with excellent properties as a screening instrument for psychiatric
disorders in nonclinical settings (Goldberg & Williams, 1988).
Use extensively in medical, psychological and sociological
research. GHQ-12 comprises six positive and six negative items
concerning the past few weeks. Presence or intensity of the state
is ranked by the respondent using a 4-point scale. It cover issues
of social functioning (feeling capable of making decisions),
anxiety and depression (being able to sleep well ) and confidence
(thinking of oneself as worthless). Likert GHQ score: obtained by
assigning the value of 3 to the most negative answer and the value
of 0 the most positive ones. Score: from 0 (most posittive outcome)
to 36. How to measure volunteering?: Memberships (W1-W5, W7, W9,
W11, W13, W15, W17): Q.: Are you currently a (n active) member of
any of the kinds of organisations [...]? It is not clear what are
the resources (money, time) that individuals contribute to these
organisations: what does active mean? Variable seems to be
capturing a broad measure of social capital better than
volunteering.
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Methodology (III) How to measure volunteering? (cont): Unpaid
voluntary work (W6,W8,W10,W12,W14,W16,W18): Q: We are interested in
the things people do in their leisure time, I'm going to read out a
list of some leisure activities. Please look at the card and tell
me how frequently you do each one... Do unpaid voluntary work. Main
concern: unpaid voluntary work questions could be capturing
participation in informal volunteering or the existence of family
strategies such as caring for a family member that lives inside or
outside the household. According to the literature, this kind of
volunteering might be detrimental to carers mental health
(Li&Ferraro, 2005). However, caring for a family member does
not seem to driven the responses to this question: Volunteering
among individuals that do care for a household member is similar to
volunteering among individuals that do not report providing that
kind of support (20.6% and 20.7% respectively). And the difference
is not statistically significant.
Slide 6
GHQ12: 36 point Likert scale Wave 6 Volunteering Average 7
waves Average score: 11.20
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Methodology (IV) Instrument: Percentage of people in the region
that engages in volunteering, per year. Positively correlated with
volunteering...but not reason to believe that it is correlated with
any underlying factors determining individual mental health. Other
controls:. Second stage (Mental health): sex, age, age^2, physical
health, marital status, financial strain, log annual income. First
stage: instrument and covariates of 2 nd stage.
Results (III) Validity of the instruments: Weakness:
first-stage regression shows a strong (positive) correlation
between the instrument and volunteering. Over identification: We
cannot reject the null that the instruments are valid. Hausman test
of endogeneity: There are no systematic differences between IV and
OLS estimates. If endogeneity is ruled out, then OLS provides
consistent and efficient estimators, while IV provides consistent
but inefficient estimators. Fixed effects seem to be removing
problems of omitted variables and reversed causality.
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Results (III) What about self-selection? A treatment effect
model The idea behind the model is to regress two equations
simultaneously: The first is the probability of volunteering
controlling by personality traits (Big 5: extraversion, openness,
neuroticism, agreeableness and conciousteness). The second is the
outcome regression (mental health) as a function of the treatment
variable (volunteering). To simultaneously estimate the two
regressions we have to assume that the error terms are jointly
normally distributed. Estimate treatment effect model using Wave
16. Wald-test tests the null that the correlation between the error
terms of the two equations is biased towards zero. With a chi2(1)=
119.26, p-value=0.000, we can conclude that there is selection bias
in our model. However, once the model have been corrected,
volunteering is still positive and significantly correlated with
mental health. E(Mental Health volunteering=1)= 11.25 E(Mental
Health volunteering=0)= 11.53
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Results (IV) What are the mechanisms through which volunteering
generates a positive effect on mental health? Hypothesis:
Volunteering as a buffer mechanism to deal with potentially
negative personal episodes/situations: Retirement Financial strain
Termination of marriage
Slide 14
Conclusions Fixed effect models seem to be successfully dealing
with issues of reverse causality and omitted variables.
Self-selection problem is not tackle with OLS estimations, however:
Treatment effects model provide similar OLS estimators once
estimation have been corrected by selection bias. Volunteering has
a positive effect on mental health. Volunteering seems to be
playing a role on alleviating potential negative effects of
personal episodes/situations: It increases well-being among
retirees: Hypothesis: Helps volunteers to find a sense of purpose
after their working life. Decreases the negative effects of being
on financial strain: Hypothesis: Helps volunteers to see things in
perspective/Helps volunteers to achieve personal satisfaction that
is not related to monetary rewards. Deludes the negative effect of
being separated, divorced or widowed (as opposed to being married).
Hypothesis: Helps volunteers to see things in perspective Further
research: Test this results with other measures of well-being such
as life satisfaction. More in-depth analysis needed to understand
how those mechanism work in the field work