Aspirations and well being outcomes in ethiopia evidence from a randomized field experiment...

ETHIOPIAN DEVELOPMENT RESEARCH INSTITUTE

Aspirations and well-being outcomes in Ethiopia Evidence from a randomized field

experiment

Tanguy Bernard, Stefan Dercon, Kate Orkin , Fanaye Tadesse, and Alemayehu SeyoumTaffesseIFPRI ESSP-II and University of Oxford

Ethiopian Economic Association ConferenceJuly 19, 2011Addis Ababa

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"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)

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.

• 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

“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)

Aspiration measures200,000 ETB ~ value of

one harvest of chat

from one hectare

100,000 ETB ~ value of

one harvest of chat

from half a hectare

0 ETB

• 4 dimensions

– Annual income in cash

– Assets – house, furniture, consumer goods, vehicles

– Social status – whether people in 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

Aspirations - Determinants

asp_r1 a_income_r1 a_wealth_r1 a_educ_r1 a_status_r1

age 0.012 0.003 -0.008 0.035 -0.004

(2.99)** (0.38) (0.80) (2.92)** (0.33)

age2 -0.000 -0.000 0.000 -0.000 0.000

(2.80)** (0.73) (0.73) (2.57)* (0.85)

gender 0.178 0.203 0.074 0.262 0.167

(7.46)** (4.19)** (1.93) (5.90)** (3.20)**

read 0.102 -0.016 0.193 0.263 0.081

(3.04)** (0.28) (2.90)** (4.13)** (1.35)

R2 0.10 0.06 0.04 0.08 0.03

N 1,638 1,748 1,759 1,754 1,778

* p<0.05; ** p<0.01

Screening site fixed effects not reported

Robust standard errors clustered at village-level

t-stats in parentheses

Aspirations - Determinants asp_r1 a_income_r1 a_wealth_r1 a_educ_r1 a_status_r1

age 0.009 0.003 -0.008 0.034 -0.008

(2.93)** (0.46) (0.86) (2.88)** (0.77)

age2 -0.000 -0.000 0.000 -0.000 0.000

(2.70)** (0.89) (0.75) (2.52)* (1.18)

gender 0.179 0.196 0.073 0.270 0.160

(7.37)** (3.84)** (1.86) (6.18)** (3.29)**

read 0.117 0.040 0.201 0.244 0.100

(3.80)** (0.75) (3.06)** (4.06)** (1.85)

others_asp 0.033

(27.81)**

others_a_income 0.031

(41.01)**

others_a_wealth 0.019

(7.15)**

others_a_educ 0.021

(9.73)**

others_a_status 0.030

(18.14)**

R2 0.28 0.26 0.06 0.11 0.18

N 1,638 1,748 1,759 1,754 1,778

* p<0.05; ** p<0.01




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




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;

Experimental design

Surveyed : Treatment, 6 households (12 individuals)/village

Placebo, 6 households (12 individuals)/village

Control, 6 households (12 individuals)/village

Non-Surveyed : Treatment, 18 households (36 individuals)/ treatment village

Placebo, 18 households (36 individuals)/ placebo village

Treatment village Placebo village

16 Screening sites, 4 villages/screening sites (2 Treatment and 2 Control)

Distribution of treatment

All villages Treatment villages Placebo villages

Treatment individuals 0.32 0.33 0.31

(0.46) (0.47) (0.46)

Placebo individuals 0.33 0.32 0.34

(0.47) (0.46) (0.47)

Control individuals 0.33 0.33 0.33

(0.47) (0.47) (0.47)

# peers invited to treatment 0.85 1.26 0.40

(0.93) (0.97) (0.63)

# peers invited to placebo 0.79 0.38 1.24

(0.89) (0.31) (0.93)

Sample balanced on gender, literacy, age and most outcomes

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

initial as compared to

your five years ago

Worse 60 9 258

The Same 31 16 78

Better 43 11 136

Estimation strategy

162 1

, , , , , ,

1

T

s v i s v i s v i s v i

s

y T n y

• 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.

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




Impact on aspirations – post screening

asp_fu asp_fu asp_fu asp_fu


(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




Above median initial aspiration – final round

asp_r2 asp_r2 asp_r2 asp_r2


(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)**

R2 0.09 0.09 0.09 0.09

N 539 539 523 523

* p<0.05; ** p<0.01




Educational aspiration only – final round

a_educ_r2 a_educ_r2 a_educ_r2 a_educ_r2


(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)**

R2 0.09 0.09 0.07 0.07

N 1,151 1,151 1,174 1,174

* p<0.05; ** p<0.01




Educational aspiration only – post-screening a_educ_fu a_educ_fu a_educ_fu a_educ_fu


(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




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



Conclusion

• "Weak " treatment and very preliminary analysis, butsome indications that:

– Documentaries affect perception more than placebo

– Not so much seeing the documentary, but discussing itwith friends who have seen it – more of an aspirationwindow 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 aftertreatment

Aspirations and well being outcomes in ethiopia evidence from a randomized field experiment...

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