Mandating increased risk-sharing through iddir groups in Ethiopia. This encouraged higher demand for formal weather index insurance by 29% and increased some welfare outcomes. Formal insurance on its own encouraged more productive investments like fertilizer use but strengthening informal risk-sharing did not have additional impact beyond increasing insurance demand. The study tested the impacts of formal insurance, strengthening informal groups, and combining both approaches on outcomes like investments, transfers and welfare using a randomized controlled trial with over 100 villages.

1. ETHIOPIAN DEVELOPMENT
RESEARCH INSTITUTE
1
Formal and Informal Insurance:
Experimental Evidence from Ethiopia
Guush Berhane*, Stefan Dercon++, Ruth Vargas Hill+ and
Alemayehu Seyoum Taffesse*
* International Food Policy Research Institute
++ University of Oxford and Department of International Development, UK
+ The World Bank
Workshop on
“Innovations in Index Insurance to Promote
Agricultural and Livestock Development in Ethiopia”
Capital Hotel, Addis Ababa
Dec 3, 2015,

2. 2
Background
 Weather risk remains a major challenge to farming and
farming communities in Ethiopia;
 Many large surveys in Ethiopia report a large fraction of
rural households – 50% (ERHS), 32% (AGP), 51% (this
survey) - are affected by drought every year.
 This is over and above the large slow onset drought (that
now seems to occur every 10 years or so).
 Evidence documenting drought had significant impacts on
welfare; short- and long-term.
 Suggestive evidence that some insurance against weather
risk would have high demand.

3. 3
Background
 Information asymmetry problems and high
implementation costs limit viability of traditional
insurance;
 Informal insurance hampered by risk covariance
 Index-based weather insurance offers new possibilities;
 However, demand remains invariably low with basis-
risk, trust & transaction cost being among some of its
key challenges;
 Little is known about how to mitigate basis risk & to what
extent doing so would trigger demand in poor rural
environments like in Ethiopia;

4. 4
 index insurance becomes a complement to informal risk-
sharing (iddirs, for example) in the presence of basis risk
(Dercon et al, 2012);
 demand for index insurance can be higher among group members that
can share risk partly via reducing basis risk and improving trust.
 enhancing the resilience and adaptation of traditional groups in the
face of covariant shocks.
 informal risk-sharing arrangements such as iddirs can serve
as sustainable retail outlets for index insurance;
 reduce transaction costs,
 increase trust.
Premise

5. 5
Research questions
 Study objective: to assses the (welfare) impact of:
 providing a well-priced, well-designed insurance product;
 supporting informal risks-sharing groups, and
 combine support to informal risk-sharing groups and weather
index insurance.
 Specific questions:
 Can informal insurance groups be encouraged to mitigate basis risk -
by increasing transfers in the event of individual-specific bad
outcomes that may not be correlated with the index?
i. Does this encourage demand for insurance?
ii. Does this impact other informal transfers?
 What is the impact of formal and informal insurance on productive
investments and welfare?

6. 6
 Study approach:
 randomized field experiment conducted from 2011-
2013 with an index insurance product offered
alongside activities to strengthen risk-sharing groups
in the area: iddir.
 110 villages selected around 3 weather stations in Oromia
region – Shashemene, Dodota and Bako Tibe (all ERHS
woredas);
 Primary interest - target risk-sharing groups: iddirs.
Network mapping exercise to ensure low probability of
network overlap between “treatment” and “control”
villages.
Weather index pilot in Ethiopia

7. 7
In-depth discussions to understand the context

8. 8
Villages within 15 km radius of weather stations

9. 10
110 villages
INSURANCE
(60 villages)
CONTROL
(50 villages)
RANDOMIZATION:
Insurance
insurance contract:
 Designed on the basis of information collected by the long
ERHS panel survey – useful within limits;
 Price discounts offered
o 40-100% (free) in 2011
o 10-60% in 2012
o None in 2013

10. 11
110 villages
INSURANCE
(60 villages)
CONTROL
(50 villages)
INDIVIDUAL
(25 villages)
GROUP
(35 villages)
RANDOMIZATION:
Group vs. Individual
• Group: encouraged to insure against basis risk: e.g. payment to member
if ill-health prevented working on the field. 800 Birr offered to groups to
start a fund for this (incentive)
• Individual: 16 individuals randomly selected to receive 50 Birr.
• Total flow of money into the village is the thus same

11. 12
110 villages
INSURANCE
(60 villages)
CONTROL
(50 villages)
INDIVIDUAL
(25 villages)
GROUP
(35 villages)
MANDATED
(18 villages)
NON-MANDATED
(17 villages)
RANDOMIZATION:
Mandated v NOT

12. 13
Strengthening risk sharing rules:
two approaches
1. Mandated rules
 The group establishes regular savings to a common pot;
 10% of any insurance payout in this group goes to this pot;
 This pool is disbursed to members that experience
idiosyncratic basis risk, as a zero-interest loan;
 Disbursement criteria is discussed and set by the group at the
beginning of the year;
 Members apply for the loan, group follows disbursement rules!
2. Non-mandated: iddir free to set rules ex-ante or ex-post,
idea suggested but no format prescribed.

13. 14
Marketing: village & iddir level meetings, trainings

14. 15
Marketing: … involved drought games

15. 16
• Initially sales were small
• Product refined further –
consecutive dry spells introduced;
• Discounts offered for late season
policies (September):
• Demand increased (now 13% of
target clients);
• There was payout in the later
season
• Next season sales went up to 1500
hhs … payouts help, suggesting
TRUST is key!!!
• Basis risk still a problem – Gap
insurance introduced in 2012
Insurance sales and product refinements

16. Three key product features
17
1) Cumulative rainfall cut-offs
2) Consecutive dry days
3) Crop-cutting – gap insurance
• Overall more than 5,000 farmers bought insurance in 55 sites.
• We had wide variation in penetration rates from less than 1% to 45% in
different places and at different times

17. 18
Survey and analysis

18. 19
Timeline: sales vs. survey
2011
Baseline Survey Feb-Mar, 2011
Group rules +
Sales
Insurance
1st
follow-up
Survey
Dec, 2011
2012
2nd follow-up
Survey
Feb-Mar, 2012
Sales
Insurance
3rd
follow-up
Survey
Dec 2012- Jan2013
2013
Sales
Insurance Implemented by BG alone

19. 20
Baseline characteristics
 High incidence of drought: 51% experienced drought shock
in the last three years;
 Formal insurance an almost unknown concept:
 10% had heard about traditional indemnity (car, life or health)
insurance;
 No-one had heard of weather or crop insurance before;
 Also:
 Only 21% have heard of what a millimeter is;
 Only 7% had a bank account;
 Initial interest in index-type insurance:
 87% were interested in a weather indexed insurance policy described
to them in the survey;
 Indications of huge basis risk:
 only 32% thought rainfall measured at the nearest weather station
could accurately measure rainfall on their plots;

20. 21
Informal insurance very prevalent:
only 5% did not belong to an iddir; 92% belonged to 1-5
iddirs
0
10203040
Percent
0 2 4 6 8
d1_how many iddir are you or members of your household a member of?
Baseline characteristics

21. 22
 estimate the ANCOVA for outcome variables of interest with
baseline data:
𝒚𝒊𝒕 = 𝜷 𝟎 + 𝜷 𝒚𝒕−𝟏 𝒚𝒊,𝒕−𝟏 + 𝜷 𝑻 𝑻𝒊 + 𝜺𝒊
 estimate a difference in outcome equation for outcome
variables of interest without baseline data:
𝒚𝒊𝒕 = 𝜷 𝟎 + 𝜷 𝑻 𝑻𝒊 + 𝜺𝒊
 IV - insurance treatment and the discount value to instrument
an individual’s decision to purchase insurance.
 Stratification at location (weather station-level) so dummies
are included for this in all regressions
 Randomization at village level, so standard errors are
clustered at the village level
 Groups compared depend on the research question
Econometric analysis

22. Comparison groups
Impact of formal
insurance
Impact of
informal
Impact of
mandating
Impact of formal
and informal
Reference
group
Reference
group
Reference
group

23. 24
Key results

24. 1. Formal insurance encourages productive investments
 Formal insurance increased risk-taking - adoption of modern
inputs - use of chemical fertilizers (consistent with other studies).
 Specifically, formal insurance increases:
 the number of plots on which fertilizer is applied,
 the proportion of households spending on fertilizer,
 the amount of fertilizer purchased and amount spent on
fertilizer purchase,
 the use of improved seeds (weakly)
 It also slightly increased maize yields but not other crops
(probably due to increased use of fertilizer on maize and/or
through maize’s higher fertilizer-yield response
25

25.  Selling insurance through iddirs increases risk-sharing but
only through mandating/strengthening (no difference
observed between non-mandated and controls):
 Mandating improves access to grants/loans from the
iddirs to cover crop losses;
 Mandating increases perceived ability to finance
emergencies;
 Also some evidence that mandating reduces individual
bilateral transfers (evidence of crowding-out effect)
26
2. Selling insurance through iddirs increases risk-sharing

26.  Strengthening informal insurance (i.e., mandating iddirs):
 increase formal insurance demand by 29%– risk-sharing
can help reduce some (not all!) of basis risk and some trust
problems.
 leads to increases in some welfare outcomes –
purchase of some consumer goods (cloths and mobile
phones)
 But does not cause formal insurance to have any additional
effect on productive outcomes (other than through
increasing demand for formal insurance)
27
3. Strengthening risk-sharing through iddirs increases formal
insurance demand and some welfare

27. 28
Back to the research questions - observations
1. Can informal insurance groups be encouraged to mitigate
basis risk by increasing transfers in the event of
individual-specific bad outcomes?
i. Does this encourage demand for insurance? YES
ii. Does this impact other informal transfers? Some evidence of it.
2. impact of formal and informal insurance on productive
investments and welfare? Yes, positive impacts on
investments and some welfare indicators

28. 29
Thank You

29. 30
Key lessons learned

30. 31
• Basis risk was a major constraint to sales in the first year, even with
a unique 10 year household panel data set to help design contracts
(very rare)
• Introducing “gap insurance” seemed to have helped increase
farmers trust and value of the product and sales increased
substantially in the second year
• Gap insurance fills the gap between village level yield loss and the
weather index:
Gap insurance
If widespread yield losses are
observed but the weather index
does not suggest a payout, a petition
of farmers can call for a crop cut. If
the average yield is lower than a
specified amount an insurance
payout is made.
Lesson 1: a good product with minimal
basis risk

31. 32
• Not everyone needs it—consistently low demand in our
site with the least amount of rainfall risk.
• Not everyone can afford it but still a willingness to pay -
something to be insured beyond the insurance provided
by safety nets
– We randomized price discounts and this was an
important factor in determining demand.
– Demand was very low when unsubsidized.
Lesson 2: farmers are willing to spend on
insurance, but not much

32. 33
• Piloted selling through iddirs in all years
• Iddirs play two roles:
– make marketing easier and cheaper
– can help manage idiosyncratic basis risk
• Sales are consistently higher through groups than
through individuals even with very intensive marketing
effort to individuals.
• The role of the group in managing idiosyncratic basis risk
increases demand by 29%
Lesson 3: selling through groups helps

33. 34
• Trust in the provider is important
– The first year of sales in a place where there was no prior
experience of BG was much more difficult than in areas
where they were well known
• Selling early—around Meher
harvest—also seems to be
important, both when the farmer
has money and before
uncertainty surrounding rains in
the current season is resolved.
Lessons 4 and 5: trust and timing

34. 35
Thank You

35. Mandating increased number of groups that
offered grants and loans for crop-loss
Grantor
loanforcrop
loss
Grantor
loanforcrop
loss
Loanfor
croploss
Loanfor
croploss
Iddir 0.051** 0.066***
(0.022) (0.022)
Iddir(notmandated) 0.010 0.024
(0.027) (0.026)
Iddir(mandated) 0.087*** 0.102***
(0.029) (0.029)
Individual 0.024 0.024 0.042* 0.042*
(0.023) (0.023) (0.022) (0.022)
Constant
0.199*** 0.199*** 0.177*** 0.177***
(0.017) (0.017) (0.017) (0.017)
R-squared 0.010 0.013 0.013 0.016
Source:Authors’calculationbasedonsurveydata.
Notes:3,850observations;StandardErrorsinbrackets;***,**,*Significantat1%,5%,and10%level,respectively.
 Although no clear impact on group transfers
actually made

36. Some evidence of crowding out
Can receive
support for
1000 Birr
emergency
Have you
received a
transfer from
an individual
Have you
received a
transfer from
an individual
in the same
iddir
Have you
send a
transfer to
an individual
Have you
send a
transfer to
an individual
in the same
iddir
Mandated
iddir village 0.048 0.064 -0.007 -0.021 -0.028**
(0.036) (0.052) (0.012) (0.020) (0.011)
Constant 0.566*** 0.054 0.039*** 0.071** 0.032**
(0.052) (0.055) (0.015) (0.034) (0.013)
Observations 1,361 1,361 1,361 1,361 1,361
R-squared 0.066 0.167 0.040 0.028 0.016

37. Increasing group transfers increased formal
insurance demand
Demand for
insurance
Mandated iddir rules 0.108**
(0.053)
Individual 0.077*
(0.039)
Non-mandated iddir rules 0.023
(0.014)
Observations 387
R-squared 0.019

38. 39
Formal insurance encourages productive
investments
Did you use
fertilizer?
Amount of
fertilizer
used (kg, ln)
Amount spent
on fertilizer
(Birr, ln)
Input
expenditure
(Birr, ln)
Crop
revenue
(Birr, In)
Insurance
(instrumented) 0.308*** 2.703*** 2.111*** 0.314* 0.392***
(0.061) (0.815) (0.391) (0.161) (0.145)
Savings
-0.212* -1.849* -1.185* 0.139 -0.605*
(0.111) (0.961) (0.651) (0.179) (0.359)
Constant
0.553*** 1.622*** 3.103*** 4.080*** 4.342***
(0.054) (0.292) (0.347) (0.589) (0.331)
Observations
739 736 722 694 706
R-squared
0.160 0.216 0.243 0.203 0.319

39. No additional impact on productive investment
from insurance
Did you use
fertilizer?
Amount of
fertilizer
used (kg, ln)
Amount spent
on fertilizer
(Birr, ln)
Input
expenditure
(Birr, ln)
Crop
revenue
(Birr, In)
Insurance
(instrumented) 0.241*** 2.060*** 1.752*** 0.324*** 0.189
(0.041) (0.718) (0.308) (0.161) (0.114)
Insurance in
iddir villages 0.290 2.973 2.595 1.950 -0.958
(0.628) (5.686) (4.190) (2.146) (0.985)
Iddir village
-0.029 -0.296 -0.201 -0.318 0.066
(0.061) (0.595) (0.398) (0.268) (0.125)
Constant
0.588*** 1.762*** 3.663*** 3.616*** 4.127***
(0.040) (0.244) (0.273) (0.571) (0.292)
Observations
1856 1849 1818 1752 1781
R-squared
0.079 0.136 0.150 0.181 0.262