Disability is associated with lower subjective well-being through two main pathways: 1) People with disabilities experience less positive and more negative emotions during daily activities like work, housework, leisure and self-care. 2) To compensate, people with disabilities allocate more time to activities with relatively higher positive emotions, like leisure, and less time to activities like work that induce more negative emotions. However, the negative impact of reduced positive emotions during activities generally outweighs the positive impact of increased time in more enjoyable activities. So overall, disability is linked to lower levels of subjective well-being as measured by net affect.

1. DISABILITY AND SUBJECTIVE WELL-BEING
Disentangling the effect of time-use and emotional affects among older
persons in low and middle income countries
Michael Ingenhaag
University of Lausanne, Institute of Health Economics and Management
Swiss Health Economics Workshop, Lucerne 2013
Michael Ingenhaag SHEW 2013 1 / 20

2. MOTIVATION AND BACKGROUND
WHAT IS DISABILITY?
International Classification of Functioning, Disability and Health (ICF,
WHO, 2001)
”Disability refers to difficulties encountered in any or all of three areas
of functioning”
Impairments (e.g. blindness)
Activity limitations (e.g. walking, eating)
Participation restrictions (e.g. discrimination in employment or
transportation)
Impact on everyday life and on nature and context in which
activities are performed
Michael Ingenhaag SHEW 2013 2 / 20

3. MOTIVATION AND BACKGROUND
PREVALENCE OF DISABILITY
Figure: WHO, The World Bank, 2011
Vulnerable groups: women, poor and older people
Predicted increase in prevalence of disability
Positive trend in health conditions associated with disability, e.g.
noncommunicable chronic diseases
Global ageing
Michael Ingenhaag SHEW 2013 3 / 20

4. MOTIVATION AND BACKGROUND
EFFECTS OF DISABILITY I
Being disabled is associated with
disadvantages in educational attainment (e.g., Eide and Loeb, 2006,
Filmer, 2008)
disadvantages in productivity/labor market outcomes (poverty) (e.g.,
Contreras et al., 2006, Mitra et al., 2011, Trani and Loeb, 2012)
higher health care spending (e.g., Tibble, 2005, Saunders, 2006, )
social exclusion
Exacerbated in developing countries
Disability increasingly understood as human rights issue
Standard Rules on the Equalization of Opportunities of Persons with
Disabilities (UN) ⇒ Advertise policy measures to promote social
participation of Disabled
Michael Ingenhaag SHEW 2013 4 / 20

5. MOTIVATION AND BACKGROUND
EFFECTS OF DISABILITY II
Some evidence that disabled people or people suffering from severe
health shocks report to be ”happy”
E.g., Brickman, 1978, Diener and Diener, 1996, P´agan-Rodr´ıguez,
2010, Freedman et al., 2012
Disability Paradox (Albrecht et al., 1982, 1999)
Explanations using adaptation theory or set point theory
Michael Ingenhaag SHEW 2013 5 / 20

6. RESEARCH QUESTION
CONTRIBUTION
Understand lived experiences of older persons with disabilities in low
and middle income countries
Combine time-use analysis and the analysis of affect reporting
Explore potential mechanisms and pathways underlying relationship
between disability and lived experiences
Analyze association between disability and allocation of time and
emotional affects
Analyze interplay of those two components and effect on lived
experiences
Michael Ingenhaag SHEW 2013 6 / 20

7. RESEARCH QUESTION
1 DATA
2 CONDITIONAL ANALYSIS
3 COUNTERFACTUAL ANALYSIS
4 CONCLUSION
Michael Ingenhaag SHEW 2013 7 / 20

8. DATA
SAMPLE
WHO Study on AGEing and Health (SAGE)
Multi-country Survey: 2 upper-middle (Russia, South Africa), 2 lower-middle
(China, India), and 1 low income country (Ghana)
Information about demographics, household composition, SES, health (. . .),
and SWB
Ghana India China South Africa Russia
Age 64 61 62 62 63
Male 53% 52% 49% 39% 43%
Married 59% 76% 85% 48% 62%
Urban 42% 25% 45% 61% 73%
Years of education 4 4 5 6 11
Working 71% 43% 45% 30% 44%
Observations 2952 4635 8469 1884 2401
Source: SAGE
The entries in each column are country-specific averages using population weights.
Michael Ingenhaag SHEW 2013 8 / 20

9. DATA
DISABILITY MEASURE
WHO Disability Assessment Schedule 2.0 (WHODAS) based on ICF
Individuals aged 50+
Captures aspects of disability based on six domains: cognition,
mobility, self-care, getting along, life activities, and participation
12-item score based on questions: Overall in the last 30 days, how
much difficulty did you have ...
learning a new task, walking long distances, standing for long periods,
dressing, washing, daily work, hh responsibilities, joining community
activities, concentrating, making new/maintaining friendships, dealing
with strangers, emotionally affected by health?
Single items range from 1 ”None” to 5 ”Extreme/Cannot do”
Disabled ≡ Top 30% of the distribution of 12-item score
Michael Ingenhaag SHEW 2013 9 / 20

10. DATA
DEFINITION LIVED EXPERIENCES
Day Reconstruction Method (Kahneman et al. 2004)
Combination of time-use analysis and measurement of affective experiences
Ask individuals what activities they were doing and for how long
Evaluate strength of positive and negative affects during each activity
Define 5 activity groups:
work, housework, traveling, leisure, self-care
Define Net Affect (Edgeworth, 1881, Kahneman et al., 2004)
Ui =
a
tiauia
tia fraction of time spent in activity a, uia net affect during activity a
uia sum over positive affect ratings minus the sum over negative affect
ratings
Michael Ingenhaag SHEW 2013 10 / 20

11. CONDITIONAL ANALYSIS NET AFFECTS
DISABILITY AND LIVED EXPERIENCES
U = α + βDisabled + γ X +
Ghana India China South Africa Russia
Disabled -0.145∗∗ -0.402∗∗∗ -0.155∗∗∗ -0.398∗∗∗ -0.270∗∗
∗
(p < 0.10), ∗∗
(p < 0.05), ∗∗∗
(p < 0.01)
Note: The entries in each column are country-specific coefficients of being dis-
abled from a linear regression of U on Disabled controlling for a large set of demo-
graphics (age, gender, marital status, level of urbanity, ethnic minority, household
composition), socio-economic status (education level, household income), and
social cohesion (trust in others, perceived safety).
Michael Ingenhaag SHEW 2013 11 / 20

12. CONDITIONAL ANALYSIS TIME SHARES
TIME ALLOCATION – ESTIMATION
Time shares are fractions, i.e.
ta ∈ [0, 1] ∀a = 1, ..., 5
5
a=1
ta = 1
Use Multivariate Fractional Logit Model (Mullahy, 2010)
ta = αa + βt
aDisabled + γaX + a ∀a = 1, ..., 5
Michael Ingenhaag SHEW 2013 12 / 20

13. CONDITIONAL ANALYSIS TIME SHARES
RESULTS
Ghana India China South Africa Russia
Work −0.054∗∗∗ −0.052∗∗∗ −0.046∗∗∗ −0.060∗∗∗ −0.105∗∗∗
Housework −0.049∗∗∗ −0.021∗∗ −0.017∗∗ −0.049∗∗ −0.037
Travel −0.031∗∗∗ −0.013∗∗ −0.005 −0.019∗∗ −0.049∗∗∗
Leisure 0.135∗∗∗ 0.056∗∗∗ 0.068∗∗∗ 0.110∗∗∗ 0.160∗∗∗
Self-care −0.000 0.030∗∗∗ 0.000 0.019 0.031∗∗
∗
(p < 0.10), ∗∗
(p < 0.05), ∗∗∗
(p < 0.01)
Note: The entries in each column are country-specific marginal effects of being disabled from a multivariate
fractional regression of time shares ta on Disabled controlling for a large set of demographics (age, gender,
marital status, level of urbanity, ethnic minority, household composition), socio-economic status (education level,
household income), and social cohesion (trust in others, perceived safety). Note that we do not control for
employment status as we model the proportion of time spent working, along with time spent doing housework,
traveling, leisure and self-care.
Disability associated with reallocation of time from working etc. to
leisure and self-care
Michael Ingenhaag SHEW 2013 13 / 20

14. CONDITIONAL ANALYSIS AFFECT SCORES
AFFECT SCORES – ESTIMATION
Note: Only observe affect score ua for individuals spending time in
activity a
Use Seemingly Unrelated Regression Model (SUR)
ua = αa + βu
a Disabled + γaX + a ∀a = 1, ..., 5
Michael Ingenhaag SHEW 2013 14 / 20

15. CONDITIONAL ANALYSIS AFFECT SCORES
RESULTS
Ghana India China South Africa Russia
Work −0.040 −0.365∗∗∗ −0.177∗∗ −0.730∗∗∗ −0.218
Housework −0.191∗∗ −0.433∗∗∗ −0.205∗∗∗ −0.402∗∗∗ −0.436∗∗∗
Travel −0.036 −0.351∗∗∗ −0.230∗∗ −0.191 −0.439∗∗
Leisure −0.213∗∗∗ −0.329∗∗∗ −0.164∗∗∗ −0.349∗∗∗ −0.200
Self-care −0.074 −0.364∗∗∗ −0.205∗∗∗ −0.376∗∗∗ −0.479∗∗∗
∗
(p < 0.10), ∗∗
(p < 0.05), ∗∗∗
(p < 0.01)
Note: The entries in each column are country-specific marginal effects of being disabled from a multivariate linear
regression of standardized net affect ua on Disabled controlling for a large set of demographics (age, gender,
marital status, level of urbanity, ethnic minority, household composition), socio-economic status (education level,
household income), and social cohesion (trust in others, perceived safety). We define five activity categories,
work, housework, travel/commuting, leisure and self-care.
Disability associated with lower emotional well-being during each
activity
Michael Ingenhaag SHEW 2013 15 / 20

16. COUNTERFACTUAL ANALYSIS
MOTIVATION
Ui =
a
tiauia
Found two effects of being disabled
Change of activity-specific net affects (Net Affect ↓)
Change of time allocation towards leisure (Net Affect ?)
Ex: If net affect during leisure if disabled is larger than net affect
during work if able-bodied, then ↑ SWB0.511.52
Able DisA
StandardizedScore
Aim: Disentangle & quantify (potential) opposing effects on lived
experiences
Michael Ingenhaag SHEW 2013 16 / 20

17. COUNTERFACTUAL ANALYSIS
THOUGHT EXPERIMENT
AFFECT RATINGS:
Suppose disabled and able-bodied have same time allocation but different
affect ratings
∆Affect
U =
a
¯ta × βu
a
TIME USE:
Suppose disabled and able-bodied have same affect rating but different time
allocations
∆Time
U =
a
¯ua × βt
a
Michael Ingenhaag SHEW 2013 17 / 20

18. COUNTERFACTUAL ANALYSIS RESULTS
RESULTS
Ghana India China South Africa Russia
Total Difference −0.105∗∗∗ −0.416∗∗∗ −0.222∗∗∗ −0.245∗∗∗ −0.377∗∗∗
Panel A. Activity-specific affects
Total −0.112∗∗∗ −0.374∗∗∗ −0.244∗∗∗ −0.262∗∗∗ −0.374∗∗∗
Work −0.010 −0.052∗∗∗ −0.047∗∗∗ −0.027∗ −0.058∗∗∗
Housework −0.019∗∗ −0.077∗∗∗ −0.056∗∗∗ −0.061∗∗∗ −0.116∗∗∗
Travel −0.001 −0.016∗∗∗ −0.008∗∗∗ −0.016∗∗∗ −0.025∗∗∗
Leisure −0.073∗∗∗ −0.155∗∗∗ −0.104∗∗∗ −0.106∗∗∗ −0.138∗∗∗
Self-care −0.010 −0.074∗∗∗ −0.029∗∗∗ −0.052∗∗∗ −0.037∗∗∗
Panel B. Time Composition
Total 0.044∗∗∗ 0.034∗∗∗ 0.034∗∗∗ 0.025∗∗∗ 0.080∗∗∗
Work 0.010∗∗∗ 0.011∗∗∗ 0.018∗∗∗ −0.001 0.039∗∗∗
Housework 0.002 0.002∗∗ 0.003∗∗∗ −0.009∗∗∗ 0.002
Travel 0.005∗∗∗ −0.001∗ −0.000 −0.001 0.002
Leisure 0.026∗∗∗ 0.013∗∗∗ 0.013∗∗∗ 0.030∗∗∗ 0.029∗∗∗
Self-care 0.000 0.010∗∗∗ 0.000 0.005∗∗ 0.009∗∗∗
∗
(p < 0.10), ∗∗
(p < 0.05), ∗∗∗
(p < 0.01)
Note: The entries in each column are country-specific differences in net affect between individuals with and without
disability. Standard errors are computed using 150 bootstrap replications
Opposing effects of time composition and affect rating
Michael Ingenhaag SHEW 2013 18 / 20

19. CONCLUSION
CONCLUSIONS
Disabled individuals report lower Net Affects
Being disabled has two effects:
Lower affect ratings during each activity
Shift time from work-related to leisure/self-care activities
Partially mediating effects of differences in time-use and emotional
affects
Lower affect scores increase difference in Net Affects
Shift towards leisure activities partially closes gap in Net Affects
Shows usefulness of combining time-use studies with studies on
emotional well-being
Michael Ingenhaag SHEW 2013 19 / 20

20. THANK YOU !