Berg and Zia
Entertainment media to see impact on financial decisions, soap Opera Scandal
Methodological challenges
Counterfactual group, impossible to restrict everyone to watch. Financial incentives to watch another programme during same time
helps also lower survey attrition
possible greater attention (not good thing)
results
- Increase likelihood of borrowing through fromal channels
- borrow for productive purpose
- lower gambling
- short term effect on usage of debt helpline
depature from classical literature on financial education (useless)
Emotions
emotional connection to chrcaters play a role, knowledge outcomes related to main protagonist higher than smaller roles
key difference length of exposure
post experiment group discussions, people recall protagonist more often
Tutorial1
Symmetric Encouragement Design
Give financial incentives to both
Treatment : more people watch Scandal
Control : more people watch Muhvango
high compliance
min exposure to both (same on TV)
min spillovers (2 streets between households)
Stratified randomization
example: you want same amount of men and women in control and treatement (balanced groups) -> u do stratified randomization
Dupas
See if for experienced goods a one-off subsidy could also boost long-run adoption through learning, more advanced ben-nets
learning might spread to others
Problems with subsidies
- sunk cost: people who pay more, use it more
- screening effect: if free also people with zero WTP get product
- acnhoring: take previous price as good unwilling to pay higher
if product learning effects this might change
Results
- Low subsidy beggining (increase short-run adoption) -> learning -> get it also in phase 2 increase future WTP
- Higher exposure (spatial to nighbors with nets) -> positive spill over effect
- no evidence phase1 price taken anchor phase 2 price
possible with bad learning (water disinfectant) results change
Tutorial2
Spillovers
- Direct : lower chance of infection
- Indirect: lower chance of transimssion
SUTVA when person i does not influence person j (not hold)
We need to consider vriable spillover in regression
Fixed effects
captures variations between areas of houshold location
school farm ecc all under one vector v
in regression estimate captures area specific effects, both observed and unobserved
Banerjee Duflo (education)
Hiring young women to help poor perfomring students, increase in learning outcomes. After one year initial gains remained but they fade out
Education issues
- High suplly, low attendance
- Very low quality and scarce results
first generation learners (stuff just too difficult to begin with)
additional teachers, school books don’t do shit
Intervention
- Balsakhi Women from community to help with basic skills
- Computer learning program
Tutorial3
Clustered standard errors
- assumption for OLS : i.i.d error terms
- Often not like this, students in same grade are more like each other than from same grade but another school (unobserved errors correlated)
- standard errors not accurate (no impact on coefficient)
- Cluster-level at same level of randomization
Fixed effects different (capture heterogeneity between diff. groups)
Results
positive effect (short-run), waker students gained the most (higer test scores), also computer thing effective.
Normalized difference
they do this in the paper for test results
can distort treatment effects, inflates effectiveness of intervetion done one more homogeneous groups (smaller standard deviation)
why still use it ?
Allows for easy comaparbility (meta-analysis)
cost-effective calculations
Kate Orkin
Bernard et al. , (Aspirations)
documentary of successful peope in etiopia to influence aspirations of people. 5 years later people increase future oriented investments and in children’s education
Experiment
Treatment watched doc on role models
Control some bullshit entertainment
After 5 years
Results
- higher investments in agriculture ecc
- extra working hours
- spend more on children education
- improved lifestyle (housing, durable goods )
behaviour starte quick 6 month after
tutorial4
Ancova
Estimate ture effect of treatment
** include baseline outcome variable** why ?
persistence ( outcome variable aspiration, more or less the same as yesterday)
past outcomes affect the outcome variable ( dream big as a kid, aspirations inherently higher)
decreases its standard error
no change in treatement estimate
Randomized Saturation Design
Does treatment intensity lead to more spillovers, if we expect no change estimates for HI and LI should be the same
otherwies HI > LI
in paper no spillovers
Banerjee Duflo (Microcredit)
Lot of backlash of micro credit (farmes debt pressure suicide), need to estimate average effect of microcredit ->
evalutation of effect of group-lending model.
Results
Households borrow more from microcredit institutions, informal declines (less demand than expected)
Consumption no difference but more buygin durable goods.
Not more likely to be entrepeuners, more investing in already business.
Increase average profit -> driven by upper-tail businesses.(95th percentile)
After 3 years treatment more assets (also 85th percintile increas in profits)
