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Ex-ante Impacts of Agricultural Insurance: Evidence
from a Field Experiment in Mali
Ghada Elabed* & Michael R Carter**
*Mathematica Policy Research**University of California, Davis & NBER
BASIS Assets & Market Access Research Program &I4 Index Insurance Innovation Initiative
http://basis.ucdavis.edu.
Annual Global Development Conference, Casablanca
13 June 2015
Elabed & Carter Impacts of Insurance in Mali
Uninsured Risk Is Costly
Risk is costly:
Makes Households Poor when it leads them to adopt less risky,but lower returning activitiesKeeps Households Poor not only when it de-capitalizes them inthe wake of a shock, but also when it leads them to accumulateunproductive 'bu�er' assets in anticipation of shocks
Can insurance have real development impacts?
Not just ex post smoothing e�ects (see previous work)But allowing farmers to ex ante prudentially invest more andincrease their average incomes
This presentation looks at the investment and income impactsof index insurance for cotton farmers in Mali
Elabed & Carter Impacts of Insurance in Mali
Logic of Index Insurance
Conventional insurance (based on individual loss adjustment)has a dismal record
Costly to verify losses for smallholdersMoral hazard if do not/cannot reliably verify lossesAdverse selection
Index insurance does not pay based on (veri�ed) individuallosses, but instead based on a cheap to measure 'index' that iscorrelated with individual losses (e.g., average yields in a zone,or rainfall)
Cuts costsEliminates moral hazard & adverse selection
Elabed & Carter Impacts of Insurance in Mali
Cotton Production in Mali
Most farmers are smallholders and grow a mix of subsistencecrops and cotton
Cotton is their main (and often only) source of cash
Cotton is a pro�table, but risky crop
Production organized in cooperatives
Cotton is controlled by the Compagnie malienne pour ledéveloppement du textile (CMDT), a parastatal
CMDT provides input loans and buys the harvest at a priceannounced before planting
Elabed & Carter Impacts of Insurance in Mali
Risk and Capital Constraints in Mali
Farmers access credit via group loans:
Amount of loan is on average 95,000CFA/ha, and the netrevenue from cotton is 105,000CFA/haIf the cooperative yield falls below 750 kg/ha, loan repaymentis tenuousP(yield < 750) = 10%Consequences of default are substantial (informal collateral)
The collateral risk of default appears to discourage farmersfrom growing as much cotton as they otherwise might�classicexample of risk rationing
Output can be taxed away to pay for others in the group
Elabed & Carter Impacts of Insurance in Mali
Dual Scale Area-yield Index Contract
To address these issues, developed an area-yield insurancecontract
Can do this easily because monopsony buyer (CMDT) alreadymeasures area and output
Insured unit is the cooperative (as it holds the joint liabilitydebt for all farmers in the village)
Payouts based on the average yield of the cooperative and ofthe �ZPA� grouping (an agglomeration of 10-15 villagecooperatives)
This dual scale area-yield contract has a low level of basis risk:Conditional on a loss, the probability of getting a payment is80%, and the probability that net proceeds are less than thevalue of 750 kg of cotton per-hectare drops to 2%
Elabed & Carter Impacts of Insurance in Mali
The Mali Pilot Project
In cooperation with PlaNet Guarantee implemented arandomized control trial for the 2011/12 year
87 cooperatives: 59 were randomly selected for treatment(o�ered insurance), 28 served as control
An encouragement design: reduced the price of contract to50%, 75%, or 100% of the actuarially fair premium
Decisions to buy the insurance made in May 2011 (plantingseason)
30% of the treated cooperatives purchased the insurancecontract
Elabed & Carter Impacts of Insurance in Mali
The Mali Pilot Project
Note that the insurance purchase decision was a joint decisionby co-op
Creates the possibility that an individual farmer may not knows/he is insured (e.g., if missed meeting)
Ex ante e�ects can of course only occur if farmers know theyare insured
In the analysis to follow, we will both look at the impacts ofbeing insured (co-op purchased insurance) and also impact iffarmer reports that s/he is insured.
Elabed & Carter Impacts of Insurance in Mali
Research design
Unfortunately, we discovered �aws in roll-out (not all treatedco-ops were actually o�ered insurance)
Fortunately, we had audit questions that allowed us to �gureout what really happened
But only 22.5% of the treated households believed they wereinsured (and 10% of non-treated households!)
Results shown here use the audit-based reclassi�cation oftreatment and control areas
Paper includes all results�similar estimated impacts but lessprecise
Audit-adjusted treatment & control groups are balanced interms of observable covariates
Let's focus now on key outcome variables
Elabed & Carter Impacts of Insurance in Mali
Econometric Method
The decision to buy insurance (and to know insured) are ofcourse economically & econometrically endogenous
To obtain unbiased estimates of the impacts of insurancepurchase and farming knowing insured, we exploit ourrandomized controlled trial and use instrumental variablemethods to recover standard local average treatment e�ects.
Elabed & Carter Impacts of Insurance in Mali
Conclusion
Impact of insurance are substantial at the extensive margin:
Area in cotton rose by 1.3 to 1.4 hectares (a 60% increase)Matching increases in loans and inputsNo impacts on input intensity, nor any impact on reduction inother ag activityOutput (and income) increases are estimated to be about40%, but this �gure is not signi�cant (noisy outcome measure)
We thus see that insurance can have substantial developmentimpact
New pilot in Burkina Faso�stay tuned!
Elabed & Carter Impacts of Insurance in Mali
Cumulative cotton area in 2011
0.2
.4.6
0 1 2 3Area (ha)
cdf_insurance cdf_control
Cumulatives:Coton area in 2011, below 3 ha
.6.7
.8.9
1
0 5 10 15 20Area (ha)
cdf_insurance cdf_control
Cumulatives:Coton area in 2011, above 3 ha
Elabed & Carter Impacts of Insurance in Mali
Prior Evidence on Risk Transfer�Impact of Index InsuranceMaize producers in Ghana invest more when insured
Randomly o�ered some farmers insurance at variable prices
Other farmers o�ered a capital grant for purchasing inputs
Found that farmers o�ered insurance:
Expand area cultivated by 15%Increase input use by 40%
Capital grants by themselves have little impactSource: Karlan et al. (2014). �Agricultural Decisions after Relaxing Risk & CreditConstraints,� Quarterly J of Econ.
Elabed & Carter Impacts of Insurance in Mali
Logic of Index InsuranceComparison of Index versus Conventional Insurance in Ecuador
Elabed & Carter Impacts of Insurance in Mali
Dual Scale Area-yield Index ContractEquivalently priced single & dual-scale contracts (Mali)
Source: Elabed, Carter, Guirking & Bellemare (2014). �Managing Basis Riskwith Multi-scale Index Insurance Contracts,� Agricultural Economics
Elabed & Carter Impacts of Insurance in Mali
Risk Rationing and Cotton Production
Loans come with a binding joint liability clause
Consequences of default are substantial (informal collateral)
Survey in 2006: 32% of the farmers growing cotton haddi�culty with their loan repayment
38% had to sell their assets4% sent one of their children to work for another farmerSome saw their credit line reduced and faced exclusion fromthe credit group
The collateral risk of default appears to discourage farmersfrom growing as much cotton as they otherwise might�classicexample of risk rationing
Elabed & Carter Impacts of Insurance in Mali
Research question and Research Strategy
There is modest but growing evidence that risk transfer (viainsurance) & risk reduction (via stress tolerant varieties) haseconomically notable impacts
Protecting current and future assets: Janzen and Carter (2014)Relaxing risk and capital constraints: Karlan et al (2014)Incentivizing technology adoption: Mobarak and Rosenzweig(2012)
Use the remainder of our time to look at the investment andincome impacts of insurance for cotton farmers in Mali
We designed an insurance contract for cotton cooperatives inMali
We randomly o�ered insurance to 87 cotton cooperatives
Elabed & Carter Impacts of Insurance in Mali
Behavior of the Insured versus UninsuredThese are NOT impact results
Elabed & Carter Impacts of Insurance in Mali
Risk Rationing and Cotton Production
Loans come with a binding joint liability clause
Consequences of default are substantial (informal collateral)
Survey in 2006: 32% of the farmers growing cotton haddi�culty with their loan repayment
38% had to sell their assets4% sent one of their children to work for another farmerSome saw their credit line reduced and faced exclusion fromthe credit group
The collateral risk of default appears to discourage farmersfrom growing as much cotton as they otherwise might�classicexample of risk rationing
Elabed & Carter Impacts of Insurance in Mali
Dual Scale Area-yield Index Contract
To address these issues, developed an area-yield insurancecontract
Can do this easily because monopsony buyer (CMDT) alreadymeasures area and output
Insured unit is the cooperative (as it holds the joint liabilitydebt for all farmers in the village)
But at what scale set the trigger or strikepoint that determinespayment?
If take average across a larger area, basis risk increasesIf take average across too small an area, collusion and moralhazard possible
Elabed & Carter Impacts of Insurance in Mali
Dual Scale Area-yield Index Contract
Rather than face the tradeo� between a village level yieldtrigger (moral hazard) versus a yield trigger based on a larger�ZPA� grouping (an agglomeration of 10-15 villagecooperatives), designed a dual scale contract
Payouts based on the average yield of the cooperative AND ofthe ZPA
Can think of the ZPA trigger as an audit rule�only believevillage yields are low due to nature if neighboring villages arealso showing some signs of stress
Conditional on a loss, the probability of getting a payment is80%, and the probability that net proceeds are less than thevalue of 750 kg of cotton per-hectare drops to 2%
Elabed & Carter Impacts of Insurance in Mali
Logic of Index Insurance
Conventional insurance (based on individual loss adjustment)has a dismal record
Costly to verify losses for smallholdersMoral hazard if do not/cannot reliably verify lossesAdverse selection
Index insurance does not pay based on (veri�ed) individuallosses, but instead based on a cheap to measure 'index' that iscorrelated with individual losses (e.g., average yields in a zone,or rainfall)
Cuts costsEliminates moral hazard & adverse selection
Elabed & Carter Impacts of Insurance in Mali
Econometric Method
The decision to buy insurance (and to know insured) are ofcourse economically & econometrically endogenous
To obtain unbiased estimates of the impacts of insurancepurchase and farming knowing insured, we exploit ourrandomized controlled trial and use instrumental variablemethods to recover standard local average treatment e�ects:
Yjc = α +β Ijc + γXjc + εjc
where Yjc is the outcome variable of interest (e.g., yields) forfarmer j in co-op c ,Xjc are a set of control variables (baseline wealth, experience,etc.), andIjc is the �rst stage estimate of whether or not individual jc is,or feels, insured.
Elabed & Carter Impacts of Insurance in Mali
Econometric Method
We derive these �rst stage estimates of insurance status byestimating two equations of this form:
Ijc = α +δ1Tjc +δ2Pjc + εjc
where Ijc = 1 if individual jc is (or believes) that is insured,Tjc is the randomly determined treatment variable (equals 1 ifco-op was o�ered insurance) andP ic is a measure of the strike point penalty randomly imposedby the reinsurance company
Elabed & Carter Impacts of Insurance in Mali
Strikepoint Penalty
Research team designed & then priced the contract under theassumption that yields for di�erent co-ops in the same area aredriven by a common parametric probability structure
Structure was allowed to parametrically shift with each co-op'saverage long-term yields
Resulted in a set of spatially stable prices
Elabed & Carter Impacts of Insurance in Mali
Strikepoint Penalty
Reinsurance partner rejected this approach and priced eachco-op separately using burn rates based on the short timeseries available on each co-op
Resulted in often radical downward shift in strike points, withneighboring co-ops sometimes o�ered radically di�erentcontracts
Also resulted in no contracts being o�ered to more than halfthe co-ops in pilot area
Because these strike point di�erences were driven byrandomness (did one co-op happen to have an especially badyear in its time series, whereas its neighbor did not), a measureof this strike point penalty should serve as a statistically validand strong instrument to explain insurance purchase
Elabed & Carter Impacts of Insurance in Mali