These notes cover a wider area and are relevant to everyone basing on the theory of consumer behavior

1. Estimating Well-Being in
Developing Countries

2. Well-Being
(1) What is well-being?
(2) Why should economists be interested in well-being?
(3) Estimating well-being equations
(4) Empirical Findings

3. Well-Being
(1) What is well-being?
Aristotle sees ‘happiness’ and ‘living –well’ as the same thing and that living
well consists of doing something.
Well-Being and Ill-Being – Jeremy Bentham in 19th Century.
World Health Organisation Quality of Life – Concerned with measuring
physical health, psychological health, social relationships, and the
environment.
“What people have or do not have (material); what people do or cannot do with it
(relational); what people think or feel (subjective)”. Wellbeing in Developing
Countries WeD (2009).

4. Well-Being
We focus on subjective well-being (SWB).
However, SWB will be closely correlated with material and
relational factors.
If have a house and car then better-off in yourself (SWB) and
when compared to others (relational).
It is the relative position of an individual that is arguably most
interesting in both the theoretical and empirical literature.

5. Well-Being
Issue of who to compare your well-being to….
(i) keeping up with the Jones’ – neighbour or village effect.
(ii) peer group – fellow worker, average worker, race, gender,
age, caste
(iii) different time periods – yesterday, last year.
(iv) different generations – parents
(v) some pre-determined social norm – sociology.

6. Well-Being
(2) Why should economists be interested in well-being?
Well-being and satisfaction are similar concepts hence can directly test utility.
It is assumed in micro-foundations of neo-classical theory that utility is formed based
on consumption of goods which in itself is determined by the budget constraint
(income).
A
B
Satisfaction=Utility

7. Well-Being
However Easterlin (1974) found that over time happiness did not increase with
income – Easterlin paradox
If increasing income does not increase satisfaction or utility then why be
obsessed with this?
Time
Average
Satisfaction
and GDP per
capita
Satisfaction with life
GDP per capita

8. Well-Being
Richard Layard and others (e.g. Frey and Stutzer, 2002), argue
that it is relative income that explains why happiness does not
increase significantly beyond
(i) a certain level of GDP per capita (Macro)
(ii) a certain individual absolute income level (Micro)
So if your income increases but so does everyone elses then your
relative position is the same.
Indeed, if your income increases but at a slower rate than the
average income increase then your relative position worsens –
income inequality is becoming more skewed towards the very
highest decile in the US and UK…..is this why we’re not more
satisfied?

9. Well-Being
Lucas et al (2004) argue that while income, health and family are
correlated with life satisfaction that they do not explain much of
the variance in satisfaction.
Personality variables account for a much larger share of
subjective satisfaction – use of twin studies indicates that 80% of
the variance in satisfaction is something that comes from within.
Genetic.
Any exogenous shocks thus have an impact on short-term
variation in satisfaction, but in the long-run individuals return to
some ‘set-point’.

10. Well-Being
Years
SWB
Negative Shock – e.g. unemployment,
death, tragic news
Set Point
Positive Shock – e.g.
inheritance, lottery win,
house prices
Older people tend to report
higher levels of life
satisfaction – Why?
0
10

11. Well-Being
Cross-Country Comparisons
Many studies compare countries (e.g. Stevenson and Wolfers, 2008) and
suggest that GDP per capita is significant in subjective happiness.
Other factors that are important include health and unemployment rates.
However variations in happiness between countries can be criticised.
Does someone who scores 8 in Sweden really have the same level of
happiness as someone who scores 8 in India? – reference group.

12. Well-Being
(3) Estimating well-being equations.
Using the Likert scale for happiness or life satisfaction as the dependent
variable.
Economists can test a number of hypotheses.
(1) Are income, wealth, assets positively correlated with happiness?
In cross-country studies use GDP per capita as measure of income.
In national study use income per adult equivalence for household level
income, use the squared term too to see if happiness increases with income at
a decreasing rate.
Same method for information on assets and wealth – may need to create an
index or use factor analysis to get a single measure of household
assets/wealth e.g. pots and pans, knives, agricultural tools.

13. Well-Being
Endogeneity Issues
It could well be that someone of a happier disposition
will earn more in the labour market (Ruut Veenhoven).
This could be picking up social network effects and
being more sociable. It could also be picking up
unobservable characteristics of individuals not
traditionally found in earnings functions, e.g. optimism,
positive attitude, work ethic?

14. Well-Being
(2) Employment and Satisfaction
Well known in the labour economics literature that the unemployed are scarred – we
would expect that the unemployed would, ceteris paribus, report lower levels of
satisfaction than the employed.
As well as this basic test the applied literature has used the satisfaction data to test
whether the searching and non-searching unemployed report different satisfaction
rates.
This tests the neo-classical hypothesis that via maximising utility the non-searching
unemployed are voluntarily unemployed as they choose not to search.
If it is found that the non-searching are as satisfied as the searching unemployed or
even less satisfied then this is consistent with the ‘discouraged worker hypothesis’.

15. Well-Being
(3) Satisfaction and Relative Consumption
Evidence from Hinks and Davies for Malawi (2008), Copestake et al (2009) for
Peru indicates that even amongst very poor communities, as average
consumption increases so satisfaction declines.
Suggests that relative economic position in the community is important to
satisfaction.
This can be tested further by calculating whether your household consumption
(or income) is above the community average or not.
Studies on job satisfaction have found that relative earnings are important –
findings tend to confirm that as the average earnings of someone with your skill
set increases then, ceteris paribus, job satisfaction declines.
change
does
on
satisfacti
increase
n
consumptio
average
As
H
on
satisfacti
in
change
no
is
there
increases
n
consunptio
average
As
H


1
0

16. Well-Being
Other Hypotheses of interest-
Satisfaction and Crime – Powdthavee (2008), Hinks and
Davies (2010).
Satisfaction and Race or Gender – Hinks & Gruen
(2007), Hinks and Davies (2008).
Satisfaction and Social Networks – Hinks and Davies
(2008), Polygamy, Religion and Satisfaction.

17. Well-Being
(4) Empirical Evidence
(i) Well-Being, Income and Relative Income
Evidence is conclusive with a positive relationship
within country well-being or happiness and income
level. For both developing and developed countries.
E.g. Powdthavee (2005), Hinks and Gruen (2007),
Hinks and Davies (2008, 2010) work using cross-
sectional data sets for developing countries.

18. Well-Being
(ii) The Case of Employment Status and Well-Being
Lucas et al (2004, pp.11) find that (i) satisfaction begins to
decline before the worker is unemployed (ii) life satisfaction is
reduced massively when unemployed and (iii) satisfaction
increases but not back to pre-unemployment level.

19. Well-Being
Case Study of South Africa – Kingdon and Knight (2006).
First issue is that of endogeneity – are the unhappiest people more likely to be
unemployed?
Evidence from longitudinal studies by psychologists is that this reverse causality is
‘doubtful’ – Veenhoven suggests that happier people are more likely to be employed
first than unhappier people.
Happiness is on a 5-point scale, 0 is very dissatisfied and 5 is very satisfied.
Only collected for head of households – so not individual level.
The searching unemployment rate = (No. of searching unemployed in HH/No. of
broad labour force participants).
The non-searching unemployment rate = (No of non-searching unemployed in
HH/No. of broad labour force participants).

21. Well-Being
No significant difference in life satisfaction between the
searching and non-searching unemployed.
Implication is to reject the hypothesis that the non-searching
unemployed are happier than the searching and accept that
worker discouragement is at work in South Africa.
Given the strict rate of unemployment is high (still officially 24%
in 2nd quarter of 2009) this is perhaps unsurprising but
importantly adds to the evidence against voluntary
unemployment.

22. Well-Being
An abridged version of an estimated happiness equation taken from Hinks and Davies (2008).
Analysis of some findings:
(i) Find that larger consumption raises life satisfaction. In developing countries there is
still a great need to increase economic growth to raise income levels.
(ii) If relatively better off in terms of consumption then more satisfied. The importance of
relative position is confirmed.
(iii) The perceptions of your neighbours’ wealth positively predicts more satisfaction for
you. Capturing some of the log consumption variable as this coefficient decreases in size.
(iv) Wealthier households (assets) are more satisfied
(vi) The salaried employed and self-employed are more satisfied than farmers.

23. Model 1 Model 2 Model 3 Model 4 Model 5
ln(Per Capita Consumption) 0.338*** 0.173*** 0.184*** 0.138*** 0.072**
(13.905) (6.115) (7.044) (4.811) (2.322)
ln(Mean Community Consumption) -0.193***
(-5.267)
Relative Household Consumption 1 0.152*** 0.174*** 0.164***
(4.910) (5.586) (5.212)
Relative Household Consumption 2 0.061***
(5.671)
Neighbours' Subjective Wealth 0.108*** 0.101***
(8.627) (7.996)
Asset Score 0.096***
(5.564)
Salaried Employment Dummy 0.144*** 0.136*** 0.135*** 0.124*** 0.091***
(4.442) (4.234) (4.199) (3.848) (2.737)
Self-Employed Dummy 0.151*** 0.145*** 0.146*** 0.137*** 0.130***
(4.417) (4.244) (4.266) (4.002) (3.797)
N 11264 11264 11264 11248 11205
Pseudo R-Squared 0.068 0.068 0.068 0.070 0.071
Chi2 1802.312 1793.891 1812.681 1850.342 1869.723

24. Some Useful Websites for Economics of Wellbeing, Quality of Life and
Happiness
(1) World Health Organisation Quality of Life,
http://www.who.int/substance_abuse/research_tools/whoqolbref/en/
(2) Wellbeing in Developing Countries WeD,
http://www.welldev.org.uk/
(3) World Values Survey
http://www.worldvaluessurvey.org
(4) World data base of Happiness – Ruut Veenhoven
http://worlddatabaseofhappiness.eur.nl/
(5) International Society for Quality of Life Studies
http://www.isqols.org/

25. References
Easterlin, R., (1974), ““Does Economic Growth Improve the Human Lot?,” in Nations and Households in Economic Growth:
Essays in Honor of Moses Abramovitz, ed. by P. A. David, and M. W. Reder. New York: Academic Press.
Stevenson, B, and Wolfers, J., (2008), “Economic Growth and Subjective Well-Being: Reassessing the Easterlin Paradox”,
NBER Working Paper Series, No. 14282
Layard. R., (2005), Happiness: Lessons from a new science, Penguin, London.
Frey, B., and Stutzer, A., (2002), Happiness and Economics: How the Economy and Institutions Affect Human Well-Being,
Princeton University Press, NJ.
Lucas, R., Clark, A., Georgellis, Y., and Diener, E., (2004), “Unemployment Alters the Set Point for Life Satisfaction”,
Psychological Science, 15(1): 8-13.
Powdthavee, N. (2005). Unhappiness and crime: Evidence from South Africa. Economica, 72, 531–547.),
Hinks, T., & Gruen, C. (2007). What is the structure of South African happiness equations?: Evidence from quality of life
surveys. Social Indicators Research, 82(2), 311–336.
Hinks, T., &Davies, S. (2008). Life satisfaction in Malawi. Journal of International Development, 20, 888–904.
Davies, S., and Hinks, T., (2010), “Crime and Happiness amongst heads of households in Malawi”, Journal of Happiness
Studies, 11: 457-476.
Copestake, J., Guillen-Royo, M., Chou, W. J., Hinks, T., Velazco, J., (2009). The relationship between economic and
subjective wellbeing indicators in Peru. Applied Research in Quality of Life, 4 (2), pp. 155-177.
Kingdon, G., and Knight, J., (2006), “The measurement of unemployment when unemployment is high”, Labour Economics
13(3): 291-315.