Aspirations and well-being outcomes in                  EthiopiaEvidence from a randomized field experiment      Tanguy Be...
"Fatalism" in Ethiopia"We live only for today""We have neither a dream nor an imagination""Waiting to die while seated""It...
Under-investments by the poor• Fatalistic outcome: not making the necessary investment to  improve one’s well-being, despi...
• Aspirations :   – A desire or an ambition to achieve something   – An aim and implied effort to reach it   – Combination...
“Aspirations” project    Step 1 – correlates of aspiration-related concepts    Step 2 – test and validate a measurement st...
Aspiration measures200,000 ETB ~ value ofone harvest of chatfrom one hectare         • 4 dimensions                       ...
Aspirations - Determinants          asp_r1       a_income_r1             a_wealth_r1             a_educ_r1        a_status...
Aspirations - Determinants                      asp_r1      a_income_r1           a_wealth_r1           a_educ_r1     a_st...
Aspirations – Impact    Hypothetical demand for credit                  loan_1year_R1            loan_5years_R1           ...
Experimental design16 Screening sites, 4 villages/screening sites (2 Treatment and 2 Control)           Treatment village ...
Distribution of treatment                                 All villages   Treatment villages   Placebo villages  Treatment ...
On going experiment
Compliance and power of treatment•   High and ‘clean’ compliance rate:     –   Average of 30mn for people to come see the ...
Estimation strategy                                             16     ys2,v ,i     T      T                        ns ,v ...
Impact on aspirations – final round                asp_r2              asp_r2              asp_r2         asp_r2  treat_co...
Impact on aspirations – post screening               asp_fu              asp_fu              asp_fu         asp_fu treat_c...
Above median initial aspiration – final round                          asp_r2            asp_r2            asp_r2       as...
Educational aspiration only – final round                a_educ_r2          a_educ_r2            a_educ_r2      a_educ_r2 ...
Educational aspiration only – post-screening             a_educ_fu          a_educ_fu            a_educ_fu      a_educ_fut...
Impact on demand for loans                  loan_10years_R2      loan_10years_R2            loan_10years_R2          loan_...
Conclusion• "Weak " treatment and very preliminary analysis,  but some indications that:  – Documentaries affect perceptio...
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Aspirations and well-being outcomes in Ethiopia Evidence from a randomized field experiment

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

  1. 1. Aspirations and well-being outcomes in EthiopiaEvidence 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. 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. 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. 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. 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. 6. Aspiration measures200,000 ETB ~ value ofone harvest of chatfrom one hectare • 4 dimensions – Annual income in cash100,000 ETB ~ value ofone harvest of chatfrom half a hectare – Assets – house, furniture, consumer goods, vehicles – Social status – whether people in0 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
  7. 7. Aspirations - Determinants asp_r1 a_income_r1 a_wealth_r1 a_educ_r1 a_status_r1age 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 0.03N 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
  8. 8. Aspirations - Determinants asp_r1 a_income_r1 a_wealth_r1 a_educ_r1 a_status_r1age 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 0.18N 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
  9. 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 parenthesesOther 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;
  10. 10. Experimental design16 Screening sites, 4 villages/screening sites (2 Treatment and 2 Control) Treatment village Placebo village 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
  11. 11. 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
  12. 12. On going experiment
  13. 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. 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 partof the treatment is done at the village level.
  15. 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. 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. 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. 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. 19. Educational aspiration only – post-screening a_educ_fu a_educ_fu a_educ_fu a_educ_futreat_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 0.20N 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. 20. Impact on demand for loans loan_10years_R2 loan_10years_R2 loan_10years_R2 loan_10years_R2treat_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. 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
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