Empowerment presentation masset nov 17 2014
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Transcript of Empowerment presentation masset nov 17 2014
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Measuring empowerment using vignettes
Edoardo Masset
Washington DC, 17 Nov 2014
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Motivation
• Specific goal: evaluating the impact of a rural livelihood project on women empowerment
• General goal: is showing how this method can be used in measuring empowerment
• Existing approaches are costly and are biased by subjective perceptions
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Empowerment is multidimensional
• Empowerment is a multidimensional concept: Solava and Alkire (2007) found 29 different definitions in the literature
• Indices have tried to capture multidimensionality
• This has resulted in long survey questionnaires
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Example: World Bank Empowerment Index
• 8 domains:• Justice• Politics• Public services• Labour• Goods• Private services• Intra-household• Intra-community
• 164 questions
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Example: Women’s Empowerment in Agriculture Index
• 6 domains:• Production• Resources• Income• Leadership• Time
• 60 survey questions
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Subjective perceptions are not comparable
• People interpret questions in different ways and meanings vary with the context
• Perceptions can be culturally determined and being ‘false’
• Perceptions are not comparable across people, groups or countries
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Examples of subjective questions
• World Bank Index: “how much influence do you think you have when the community selects its leaders?”
• Empowerment in Agriculture index: “To what extent do you feel you can make your own personal decisions regarding these aspects of household life if you wanted to”
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Andhra Pradesh Rural Livelihood Project
• Goal of reducing poverty by building social capital and empowering women
• Operates through Self-Help Groups to• Channelling funds• microfinance
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Women’s empowerment vignette 1. How much freedom/opportunity do you have?
VIGNETTES1. Neelamma takes a loan from the SHG and starts a grocery
shop. Despite his initial opposition, her husband is won round to the idea when he sees the good returns from the business.
2. Manemma takes a loan from the SHG to start a small home business. But her husband argues with her that the money is needed for land improvement, and she reluctantly parts with the loan money.
3. Chandamma wants to take a loan from the SHG of which she is a member to start a tea stall. She could not take the loan because her husband and mother-in-law did not agree.
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Men’s vignette1. How much influence do you have in your village?
VIGNETTES1. Davender is in a dispute over some land he claims title to. The
other man claiming this land is a close friend of the Sarpanch, and, lacking connections himself, Davender has little hope of winning the dispute.
2. Vinod is in a dispute over some land he claims title to. He supported the Sarpanch in the last election, bringing him many votes from his family and families of those who work for him. He is optimistic that he will win the dispute.
3. Kiran is in a dispute over some land he claims title to. Both he and the other man in the dispute have some blood relations with leading men in the village. He has some hope that he may win the dispute but realizes it may go either way.
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Goal of vignettes
• Find systematic differences in reporting across groups
• Comparing self-reported assessments after purging them of reporting bias
• In the analysis use a two step procedure (HOPIT model)
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The Hopit model
• 2-part model (Tandon et al 2003; King et al. 2004)
1.Model reporting behaviour. For example, women of different caste may rate vignettes in different ways
2.Model self-assessments using cut-off points identified in part 1
• Covariates are normally the same in the two parts
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Estimation• 2-step: ordered probit of vignettes and
interval regression using estimated cut-off points
• Simultaneous estimation by maximum likelihood. Methods: Programme in R Use GLLAMM (generalised linear latent and mixed
model) in STATA Set the likelihood function in STATA
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Examples from the literature• Compare political efficacy in Mexico and China• Compare reported work disability in US and
the Netherlands• Compare job-satisfaction across EU countries• Reported health across demographic groups in
Indonesia, China and India • First study to compare groups with and
without a project
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Women’s empowerment and literacy
0.1
.2.3
.4
literate illiterate
Women's power by husband's literacy
no power little powersome power a lot of power
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Men’s influence and literacy0
.1.2
.3.4
.5
literate illiterate
Men's power by literacy
no power little powersome power a lot of power
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Women’s empowerment and wage work
0.1
.2.3
.4
no-wage wage earner
Women's power by wage earning status
no power little powersome power a lot of power
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Men’s empowerment and wage work
0.1
.2.3
.4.5
no-wage wage earner
Men's power by wage earning status
no power little powersome power a lot of power
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Women’s empowerment and caste0
.1.2
.3.4
SC ST BC OC
Women's power by caste
no power little powersome power a lot of power
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Men’s empowerment and caste0
.2.4
.6
SC ST BC OC
Men's power by caste
no power little powersome power a lot of power
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Empowerment and SHG0
.1.2
.3.4
no SHG SHG
Women's power by SHG membership
no power little powersome power a lot of power
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Ordered probit HopitSHG member 0.081* 0.037* (0.099) (0.712)Scheduled tribe 0.058 -0.173 (0.499) (0.502)Other backward caste 0.076* -0.054 (0.225) (0.675)Other caste 0.041 0.091 (0.622) (0.607)Age 0.020 0.022 (0.123) (0.354)Age square -0.001 -0.001 (0.296) (0.321)Illiterate 0.052 0.202 (0.457) (0.165)Husband’s education 0.083*** 0.012 (0.000) (0.749)Female headed household 0.237** 0.140 (0.003) (0.307)Household size -0.019 -0.052* (0.134) (0.060)Land size 0.005 0.001 (0.439) (0.993)Agricultural labourer 0.157** 0.099 (0.004) (0.387)Observations 1,431 1,431
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Adjusted and unadjusted women self-assessments
• Before adjusting empowerment is correlated with:• SHG membership• Husband literacy• Female headed household• Earning capacity
• After adjusting none of the variables is correlated with empowerment except SHG
• Most differences found are perceptual rather than real
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Men’s empowerment
• No expected project impact on men’s empowerment
• Influence correlated with caste, literacy, household size, wage work
• Correlations hold after adjustments of perception bias
• Exceptions are: higher caste understate their influence while OBC overstate their influence
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Test of homogeneity in responses
Female respondents Male respondents
Homogeneity test Full sample Full sample
All covariates 0.002** 0.379
SHG member 0.096* 0.387
Caste 0.568 0.162
Age 0.514 0.494
Illiterate 0.040** 0.100
Husband’s education 0.041**
Female headed household 0.000***
Household size 0.452 0.343
Land size 0.253 0.826
Agricultural labourer 0.835 0.232
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Impact of SHG on women’s empowerment
• The data do not contain a valid control group• We follow two approaches:• Instrumented variables• Difference-in-differences
• In both cases, the impact of SHG on empowerment vanishes
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Additional question: non-parametric approach
5. How would you compare your freedom/opportunity with that of the women described above? (less than Chandamma, same as Chandamma, more than Chandamma but less than Manemma, same as Manemma, more than Manemma but less than Neelamma, same as Neelamma, more than Neelamma)
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SHGs and empowerment
Coefficient Standard error
observations
SHG instrumented hopit model full sample
0.238 0.844 1,431
SHG instrumented hopit model restricted sample
0.199 0.794 236
Difference-in-difference restricted sample
0.202 0.313 232
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Conclusions• Much of the differences in empowerment
observed in our Andhra Pradesh sample are perceptual rather than real
• Empowerment and SHG are correlated but it appears that causality runs from empowerment to SHG rather than the other way
• Vignettes are a simple, unbiased and powerful tool to assess empowerment programmes
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Thank you