At the Workshop in Index Insurance to Promote Agriculture and Livestock Development held on December 3rd, 2015 in Addis Ababa, Ethiopia, Professor Michael Carter of UC Davis and Director of the Feed the Future BASIS Assets and Market Access Innovation Lab presented on the challenges that need to be considered before implementing index insurance initiatives

1. The design and implementation of index insurance initiatives for
agricultural development in Africa:
3 Challenges for Policy
Michael R Carter
University of California, Davis & NBER
BASIS I4 Index Insurance Innovation Initiative
http://basis.ucdavis.edu
Innovations in Index Insurance to
Promote Agricultural and Livestock Development
Addis Ababa
December 2, 2015
M.R. Carter Index Insurance Design & Implementation

2. What Can Index Insurance Do?
Know that risk is directly costly
Makes Households Poor when it leads them to adopt less risky
activities, but lower returning activities
Keeps Households Poor when it leads them accumulate
unproductive ’buffer’ assets
Deepens capital constraints also as
Cuts off self-finance by holding of ’unproductive’ savings
Discourages external finance (credit), especially when risk is
correlated
Reducing risk via insurance should address all these problems
Note also that when twined with technology adoption,
insurance becomes relatively inexpensive
But can insurance really work for low wealth agricultural &
pastoralist households?
M.R. Carter Index Insurance Design & Implementation

3. What Can Index Insurance Do?
Maize producers in Ghana invest more when insured
Randomly offered some farmers insurance at variable prices
Other farmers offered a capital grant for purchasing inputs
Found that farmers offered insurance:
Expand area cultivated by some 15%
Increase input use by 40%
Capital grants by themselves have little impact
Source: Karlan et al. (2014). “Agricultural Decisions after Relaxing Risk & Credit
Constraints,” Quarterly J of Econ.
M.R. Carter Index Insurance Design & Implementation

4. What Can Index Insurance Do?
Cotton producers in Mali invest more when insured
Designed a dual-scale index contract with radically lower basis
risk
Insurance offered to a random subset of villages–find that in
insured villages:
Area planted to cotton & input use increased by 45%
Output & income increased as expected (result not statistically
significant)
Currently scaling up in Burkina Faso
Source: Elabed & Carter (2014) “Ex-ante Impacts of Agricultural Insurance: Evidence
from a Field Experiment in Mali,” Working Paper
M.R. Carter Index Insurance Design & Implementation

5. What Can Index Insurance Do?
Kenyan pastoralists reduce dependence on costly coping strategies
IBLI Insurance had payout in October 2011 after a prolonged
drought that sparked 30-40% livestock mortality
October 2011 survey asked insured and uninsured households
how they had been coping with the drought prior to the
payout/survey & how they anticipated coping after the
payout/survey
M.R. Carter Index Insurance Design & Implementation

6. What Can Index Insurance Do?
Kenyan pastoralists reduce dependence on costly coping strategies
Initially better off households:
Before Payout: No impact on consumption reduction nor on
asset sales prior to payout
After Payout: 65 %-point reduction in asset sales after payout
Initially worse off households:
Before Payout: 30 %-point reduction in “meals reduced” prior
to payout; No impact on asset sales
After Payout: 43 %-point reduction in “meals reduced” after
payout; No impact on asset sales
Source: Janzen & Carter (2014) “After the Drought: The Impact of Microinsurance
on Consumption Smoothing and Asset Protection,” NBER Working Paper No. 19702.M.R. Carter Index Insurance Design & Implementation

7. Policy Challenges for Index Insurance
Achieving these social protection and growth impacts faces key
policy challenges:
1 Cost-effective, integrated social protection system
Response: Public provision of minimum insurance protection
for vulnerable families
2 Quality contracts that do not fail households when losses occur
Response: Public certification of index insurance quality
3 Competitive insurance (risk) pricing
Response: Backstop public reinsurance facility
Let’s look at each of these
M.R. Carter Index Insurance Design & Implementation

8. Challenge 1
Cost-effective, integrated social protection system
Cash transfers, food aid & other forms of social protection
target those who are poor and have perhaps become
economically unviable/stuck
Clear financial logic to protecting the vulnerable so that they
do not fall into destitution and become transfer eligible
And yet public funds devoted to the vulnerable diverts
resources from the already poor
While the ability of the vulnerable to pay for their own
insurance is limited, analysis suggests that some public funding
of insurance for the vulnerable can be cost effective
M.R. Carter Index Insurance Design & Implementation

9. Challenge 1
Consider 2 policy scenarios:
1 Reactive cash transfer scenario in which government only
reacts to indigence & transfers resources to the indigent
2 Integrated social protection scenario in which government also
provides partial insurance subsidy to vulnerable households
Policy 2 results in lower rates & depths of chronic poverty & costs
no more than policy 1
0 5 10 15 20 25 30 35 40 45 50
0
10
20
30
40
50
60
70
80
90
100
Consumption−basedPovertyHeadcount
Time
Autarky
Insurance (Market Price)
Insurance (Targeted Subsidy)
0 5 10 15 20 25 30 35 40 45 50
0
2
4
6
8
10
12
Consumption−basedPovertyGap
Time
Autarky
Insurance (Market Price)
Insurance (Targeted Subsidy)
source: Janzen & Carter (2015), “The impact of insurance markets on chronicM.R. Carter Index Insurance Design & Implementation

10. Challenge 1
Cost-effective, integrated social protection system
In the policy simulation, insurance subsidy works well because
it harnesses two forces:
Vulnerability Reduction Effect: As in Kenya IBLI study,
protects assets so families do not collapse into indigence
Investment Incentive Effect: As in Ghana & Mali studies,
enhances investment incentives so families can prudentially
invest & create a pathway from poverty
Together these forces bring the dramatic drops in chronic
poverty & increases in self-reliance
Key features of this approach
Public purchase (or partial purchase) helps make the market
(& instills confidence)
Unlike ad hoc schemes in some South American countries,
individuals can buy insurance beyond the publicly-funded
margin, enhancing investment incentives & growth
M.R. Carter Index Insurance Design & Implementation

11. Challenge 2
Quality contracts that do not fail households
Index insurance has advantages for small-scale farming: Cheap
to administer; avoids moral hazard & adverse selection
But, its achilles heal is that it does not cover all losses:
Designing quality contracts is a non-trivial problem:
M.R. Carter Index Insurance Design & Implementation

12. Challenge 2
Quality contracts that do not fail households
The problem is far from trivial as the following analysis of the
relationship between average losses and indemnity payments
under rainfall insurance in India shows:
Clarke, D. et al. (2012). “Weather Based Crop Insurance in India.”
Such contract failures can also hurt lenders & destroy trust &
confidence in insurance companies (and government)
Consider today new ways to reduce the magnitude of
uncovered risks (A+B)
M.R. Carter Index Insurance Design & Implementation

13. Challenge 2
Quality contracts that do not fail households
Devices to reduce the uncovered ’design risk’ B:
Improved satellite predictors of biomass growth
Fail-safe audit rules that are implemented when index fails to
properly predict common losses
Devices to reduce uncovered ’idiosyncratic risk’ A:
Linking formal with informal insurance
Use dual trigger index to allow smaller geographic scale for
core index
Let’s look at devices to manage design risk using a study from
Tanzania
M.R. Carter Index Insurance Design & Implementation

14. Challenge 2
Measuring insurance quality for rice farmers in Northern Tanzania
M.R. Carter Index Insurance Design & Implementation

15. Challenge 2
Village-level Area Yield vs. Optimized Satellite-based Contract
For each small area (“village”), we collected 10 years of
retrospective data on yields
Best satellite predictor of village yields proved to be based on
’Gross Primary Production’ (based on EVI, FPAR & LAI)
Let’s compare this (cheap to administer) satellite based index
with an (expensive) village-level area yield contract:
50010001500200025003000
Predictedyield(kg/acre)
500 1000 1500 2000 2500
Actual yield (kg/acre)
Predicted vs. actual area yields in Makindube
M.R. Carter Index Insurance Design & Implementation

16. Challenge 2
Will I get paid probability measure
Consider a contract that pays anytime either measured or
satellite predicted village yields fall below average:
0.1.2.3.4.5.6.7.8.91
Probabilityofpayout
0 .2 .4 .6 .8 1 1.2 1.4
Plot-level yield (% of historic mean)
95% Confidence Interval Satellite Index Contract
Area-Yield Contract
Probability of receiving a payout by zone-level yields
M.R. Carter Index Insurance Design & Implementation

17. Challenge 2
How much will I get paid measure
M.R. Carter Index Insurance Design & Implementation

18. Challenge 2
Reservation Price Quality Measure
Actuarially fair prices for these contracts are 130 kg of rice
per-hectare insured
Unrealistically, assuming no local risk sharing
Minimalist Quality Standard: Reservation Price > Market
Price of Contract
M.R. Carter Index Insurance Design & Implementation

19. Challenge 2
Can We Do Better with an Audit Rule?
Can see that the satellite does well separating good from bad,
but has trouble distinguishing quite bad from slightly bad
What if we augmented satellite index with an audit on demand
scheme:
Agreed upon crop cut methodology at village level
Incentive compatible penalties to prevent unnecessary audits
M.R. Carter Index Insurance Design & Implementation

20. Challenge 2
Can We Do Better with an Audit Rule?
Assume that audits only requested when predicted yields are
5% below actual village area yields
17% of the time audits will take place
Shadow price will be close to pure area yield insurance
Data collection costs will only be 17% of those under area
yield contract
M.R. Carter Index Insurance Design & Implementation

21. Challenge 2
Work here suggests a safe minimum quality standard:
Reservation Price > Market Price
Note that even if insurance is subsidized, beneficiaries would
be better if simply given the subsidy rather than given cheap
insurance that approximates a lottery ticket
Issues of quality assurance are very important:
Without quality certification standards, markets will supply low
quality contracts predominate
Much to learn about how to implement those standards, but
also how to design contracts that meet those standards
(design failure in Nepal)
M.R. Carter Index Insurance Design & Implementation

22. Challenge 3
Competitive Pricing
Some jargon:
The actuarially fair price (or pure premium) of an insurance
contract is equal to the expected payouts under the contract
To cover administration costs (which should be low for index
insurance) & cost of capital, insurance companies have to
mark-up or load the cost of insurance (in US crop insurance,
the mark-up results in a price that is between 125% and 130%
of the ’AFP’)
A number of index insurance pilots have faced prices of
175-200% of AFP–why?
Thin markets, small project size & lack of competition/interest
Sparse data and uncertainty-penalized pricing
It is clear that prices at this level are non-starters for low
wealth households
What is to be done?
M.R. Carter Index Insurance Design & Implementation

23. Challenge 3
Competitive Pricing
With generous support from various donors, the IFC’s Global
Index Insurance Facility (GIIF) has to date provided an across
the board subsidy on prices set by private industry to various
projects, including IBLI
The USAID-funded Global Action Network on Index Insurance,
collaboration with the ILO & I4 is now in conversation with
IFC & the World Bank about alternative ways to lower price
Let a public sector entity (not allergic to uncertainty) carry the
layers of risk that are most worrisome to the private sector
Let a public sector entity serve a broker role, transparently
pricing and putting out to bid contracts with certified risk
estimates (perhaps bundling together multiple projects in the
spirit of the African Risk Capacity)
This same entity could also certify quality
Note that creating a minimum demand based on public
purchase of basic insurance coverage could further help bring
down prices
M.R. Carter Index Insurance Design & Implementation

24. In Conclusion
While we are beginning to see that index insurance can realize
its promise to fundamentally alter income growth & poverty
dynamics, it is no magic bullet
Substantial challenges remain to be resolved if index insurance
is to fully reach its promise
Kenya’s new KLIP/HSNP+ program is promising, not only
because it is well-designed, but also because it will likely help
us answer many of the key challenges about index insurance
that we have discussed today
Forward!
M.R. Carter Index Insurance Design & Implementation

25. Thank you!
M.R. Carter Index Insurance Design & Implementation