Aspirations and well-being outcomes in Ethiopia Evidence from a randomized field experiment
1. Aspirations and well-being outcomes in
Ethiopia
Evidence from a randomized field experiment
Tanguy Bernard1, Stefan Dercon2, Kate Orkin 2, and Alemayehu Seyoum Taffesse1
1International
Food Policy Research Institute
2 University
of Oxford
April 20, 2012
Department of Economics, Addis Ababa University
2. "Fatalism" in Ethiopia
"We live only for today"
"We have neither a dream nor an imagination"
"Waiting to die while seated"
"It is a life of no thought for tomorrow"
(Rahmato and Kidane,1999)
3. Under-investments by the poor
• Fatalistic outcome: not making the necessary investment to
improve one’s well-being, despite existing opportunities
• Explanations:
– Individual’s environment affect private returns
– Attributes of decision maker affect internal logic
• Mixed approach:
– Decision making depend on individuals’ beliefs and perception vis-
a-vis their environment.
– Individual condition affects perception of environment and related
investment to explore pathways into better wellbeing.
4. • Aspirations :
– A desire or an ambition to achieve something
– An aim and implied effort to reach it
– Combination of preferences and beliefs
• Related concepts
– Economics : Satisficing
– Psychology : self-efficacy, locus of control
– Anthropology : Aspiration failures
• Common elements
– Goals and aspirations are important to determine success
– Evolution through time in response to circumstances
– Role of social comparisons and learning from relevant others, beyond
social learning
• An individual-level yet culturally determined concept towards
exploration of individual-group symbiosis
5. “Aspirations” project
Step 1 – correlates of aspiration-related concepts
Step 2 – test and validate a measurement strategy
Step 3 – assess validity of « aspiration window " theory
• A “mobile movie” experiment
– Exogenous shock to aspirations: Mini-documentaries of
local success stories screened to randomly selected
individuals. Placebo: local TV show.
– 3 rounds of data
• Baseline pre-treatment (Sept-Dec 2010)
• Aspirations retest immediately after treatment
• Follow-up (Mar-May 2011)
6. Aspiration measures
200,000 ETB ~ value of
one harvest of chat
from one hectare • 4 dimensions
– Annual income in cash
100,000 ETB ~ value of
one harvest of chat
from half a hectare
– Assets – house, furniture,
consumer goods, vehicles
– Social status – whether people in
0 ETB
the village ask advice on decisions
– Level of education of oldest child
• “What is the level of <> you would like to
achieve?”
• Individual specific weights
• Standardised
max
M d ,i z d ,i
ad ,i max min
Md Md
9. Aspirations – Impact
Hypothetical demand for credit
loan_1year_R1 loan_5years_R1 loan_10years_R1
asp_r1 5,382.324 21,487.324 61,547.013
(4.09)** (2.53)* (3.43)**
N 1,702 1,702 1,702
* p<0.05; ** p<0.01
Screening site fixed effects not reported
Robust standard errors clustered at village-level
t-stats in parentheses
Other effects
• Increase in withdrawal and deposit into savings among treatment group – small
net increase in savings;
• Decrease in proportion of treatment group who agree that poverty has
“fatalistic” (destiny, bad luck) causes;
13. Compliance and power of treatment
• High and ‘clean’ compliance rate:
– Average of 30mn for people to come see the screening.
– 95% invited and interviewed showed up. No difference across treatment or placebo. No difference
across gender.
– 92% of invited only showed up. No difference across treatment or placebo. No difference across gender.
– No-one that was not invited saw the screening.
• Overwhelming majority of people appreciated the screening.
– 96% of treatment group ‘liked it a lot’, 73% in placebo group.
– 95% treatment group discussed content with neighbour, 71% in placebo group.
– 92% : documentaries generated ‘a lot’ of interest in village, 72% for placebo.
– 6 months later: 33% still discuss treatment, 21% still discuss placebo.
• But compliance does not mean ‘take-up’ here…
Think about the story you found the most relevant to your own life…
How was his/her present condition as compared to yours now
Worse The same Better
How was his/her Worse 60 9 258
initial as compared to The Same 31 16 78
your five years ago Better 43 11 136
14. Estimation strategy
16
ys2,v ,i T T
ns ,v ,i y1,v ,i
s s v i
s 1
• s=screening site, v=village, i=individual.
• T=treatment, nT=number of treated peers of ind i
• y1 = asp at round 1
• π=screening site fixed effects.
All standard errors clustered at village level, since part
of the treatment is done at the village level.
15. Impact on aspirations – final round
asp_r2 asp_r2 asp_r2 asp_r2
treat_cont 0.040 0.040
(1.15) (1.13)
plac_cont 0.005 0.004
(0.13) (0.12)
nb_doc 0.020 0.012
(0.96) (0.61)
nb_plac -0.020 -0.009
(0.93) (0.40)
asp_r1 0.446 0.447 0.418 0.419
(10.91)** (10.93)** (11.27)** (11.30)**
R2 0.19 0.19 0.17 0.17
N 1,061 1,061 1,076 1,076
* p<0.05; ** p<0.01
Screening site fixed effects not reported
Robust standard errors clustered at village-level
t-stats in parentheses
16. Impact on aspirations – post screening
asp_fu asp_fu asp_fu asp_fu
treat_cont 0.014 0.013
(0.34) (0.32)
plac_cont -0.049 -0.046
(1.35) (1.26)
nb_doc 0.015 0.051
(0.74) (2.44)*
nb_plac -0.001 -0.001
(0.07) (0.05)
asp_r1 0.573 0.574 0.500 0.505
(10.20)** (10.32)** (10.40)** (10.27)**
R2 0.30 0.30 0.29 0.28
N 1,004 1,004 1,022 1,022
* p<0.05; ** p<0.01
Screening site fixed effects not reported
Robust standard errors clustered at village-level
t-stats in parentheses
17. Above median initial aspiration – final round
asp_r2 asp_r2 asp_r2 asp_r2
treat_cont 0.025 0.024
(0.47) (0.45)
plac_cont -0.024 -0.023
(0.44) (0.42)
nb_doc 0.053 0.015
(2.34)* (0.70)
nb_plac -0.045 -0.021
(1.56) (0.71)
asp_r1 0.315 0.318 0.280 0.280
(4.23)** (4.25)** (4.25)** (4.25)**
2
R 0.09 0.09 0.09 0.09
N 539 539 523 523
* p<0.05; ** p<0.01
Screening site fixed effects not reported
Robust standard errors clustered at village-level
t-stats in parentheses
18. Educational aspiration only – final round
a_educ_r2 a_educ_r2 a_educ_r2 a_educ_r2
treat_cont 0.107 0.107
(1.70) (1.72)
plac_cont 0.040 0.041
(0.67) (0.69)
nb_doc 0.058 0.055
(1.74) (1.58)
nb_plac -0.078 -0.007
(2.21)* (0.23)
a_educ_r1 0.240 0.241 0.242 0.244
(7.11)** (7.08)** (8.64)** (8.61)**
2
R 0.09 0.09 0.07 0.07
N 1,151 1,151 1,174 1,174
* p<0.05; ** p<0.01
Screening site fixed effects not reported
Robust standard errors clustered at village-level
t-stats in parentheses
19. Educational aspiration only – post-screening
a_educ_fu a_educ_fu a_educ_fu a_educ_fu
treat_cont 0.100 0.101
(1.59) (1.61)
plac_cont 0.070 0.075
(1.07) (1.12)
nb_doc 0.017 0.076
(0.69) (2.76)**
nb_plac -0.034 0.002
(0.89) (0.06)
a_educ_r1 0.429 0.429 0.401 0.402
(7.43)** (7.42)** (6.85)** (6.76)**
R2 0.22 0.22 0.20 0.20
N 1,134 1,134 1,160 1,160
* p<0.05; ** p<0.01
Screening site fixed effects not reported
Robust standard errors clustered at village-level
t-stats in parentheses
20. Impact on demand for loans
loan_10years_R2 loan_10years_R2 loan_10years_R2 loan_10years_R2
treat_cont 5,670.973 4,897.515
(1.01) (0.89)
plac_cont 516.208 896.126
(0.12) (0.22)
nb_doc 5,278.431 5,778.825
(1.63) (2.12)*
nb_plac 3,802.248 4,224.977
(1.15) (1.38)
loan_10years_R1 0.277 0.283 0.591 0.595
(2.34)* (2.40)* (4.28)** (4.30)**
N 1,230 1,230 1,245 1,245
* p<0.05; ** p<0.01
observations left-censored at demand = 0
Robust standard errors clustered at village-level
t-stats in parentheses
21. Conclusion
• "Weak " treatment and very preliminary analysis,
but some indications that:
– Documentaries affect perception more than placebo
– Not so much seeing the documentary, but discussing it
with friends who’ve seen it – more of an aspiration
window story rather than a role model one.
– Impact more important on education-related aspiration
– Indication of positive effects onto demand for credit
– Although some decay, effects still visible 6 months after
treatment
