Index-Based Livestock Insurance (IBLI): Preliminary Findings on the Positive

Impacts of An Imperfect Product

Christopher B. Barrett, Cornell University

International Livestock Research Institute, Nairobi, KenyaJuly 3, 2014

Motivation: Why IBLI?

Catastrophic herd loss risk due to major droughts identified as the major cause of poverty traps facing east African pastoralists (Lybbert et al. EJ 2004, Barrett et al. JDS

2006, McPeak et al. book 2011, Santos & Barrett JDE 2011).

Climate change may aggravate this (Barrett and Santos EE 2014).

Standard responses – food aid, post-drought restocking – are often slow, insufficient and expensive.

Conventional commercial insurance not viable due to high transactions costs, moral hazard/adverse selection.

The Potential of IBLI

Index insurance (like IBLI) is a variation on traditional insurance:- Does not insure individual losses. - Instead insures some “index” that is strongly correlated

with individual losses, objectively verifiable, low cost, near-real time, not manipulable by either party to the contract.

- Resolves cost and information problems of conventional insurance at the price of basis risk (imperfect correlation between individual losses and the insured index).

IBLI can, in principle, offer a timely, financially sustainable, self-targeting safety net against catastrophic drought shocks. Can help accelerate herd recovery and reduce human suffering.

But it’s necessarily imperfect … lottery ticket or true insurance?

(Jensen, Barrett &2014)

Index-Based Livestock Insurance: Design

The signal: Normalized Difference Vegetation Index (NDVI) collected by satellite

Response function: regress historic livestock mortality onto transforms of historic cumulative standardized NDVI (Czndvi) data. In Borana, just NDVI.

Indemnity payments: In Kenya, predicted livestock mortality >15% according to:

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb

Period of NDVI observations forconstructing LRLD mortality index

Predicted LRLD mortality is announced.Indemnity payment is made if IBLI is triggered

LRLD season coverage SRSD season coverage

1 year contract coverage

Sale periodFor LRLD

Sale periodFor SRSD

Predicted SRSD mortality is announced.Indemnity payment is made if IBLI is triggered

Period of NDVI observationsFor constructing SRSDmortality index

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb

Period of NDVI observations forconstructing LRLD mortality index

Predicted LRLD mortality is announced.Indemnity payment is made if IBLI is triggered

LRLD season coverage SRSD season coverage

1 year contract coverage

Sale periodFor LRLD

Sale periodFor SRSD

Predicted SRSD mortality is announced.Indemnity payment is made if IBLI is triggered

Period of NDVI observationsFor constructing SRSDmortality index

Temporal Structure of IBLI contract:12 month contract sold during 2-month sales windows just prior to usual start of seasonal rains. Payouts March 1 and/or October 1.

Chantarat et al. 2013

(Jensen, Barrett &2014)

IBLI Pilots in Ethiopia and Kenya

IBLI products (surveys) launched in Marsabit, Kenya in Jan 2010 (Oct 2009) and in Borana, Ethiopia, in Aug 2012 (Mar 2012).

(Jensen, Barrett & Mude 2014)

IBLI: An Imperfect Product

Covariate risk is important but household losses vary a lot …

Jensen, Barrett & Mude 2014

Notes: The left figure illustrates the covariate (average) loss rate in each season. The right figure illustrates the distribution of losses within each seasons. The boxes depict the interquartile range, the upper and lower adjacent values are either 3/2 the interquartile range or the value furthest from the median. The remaining observations fall outside the adjacent values.

and the index does not perfectly track covariate losses.

Notes: Covariate loss-index observations are seasonal division average mortality paired with the index value for that division-season. Fitted lines and confidence intervals are generated by regressing livestock mortality rates on the index.

- IBLI hhs still hold most risk: Division avg downside basis risk 68-93% of total.- Most basis risk is idiosyncratic and random, not targetable or correctable.- Significant spatial variation in covariate share – geographically target IBLI?

IBLI Uptake Significant Nonetheless

In HH surveys , in Borana (Ethiopia)/Marsabit (Kenya):- 54/44% ever purchased IBLI within first 4 sales periods- But repurchase rates low: 18-68%/16-27%- High rates of disadoption : 26/41% within 2 years

Key determinants of IBLI uptake

General uptake findings — robust across specifications and surveys

Price: Responsive to premium rate (price inelastic). Price elasticity grows w/design risk. Design Risk: Design error reduces uptake; greater effect at higher premium rates.Idiosyncratic Risk: Hh understanding of IBLI increases effect of idiosyncratic riskUnderstanding: Extension/marketing improves accuracy of IBLI knowledge but no

independent effect of improved understanding on uptake.Herd size: Likelihood of uptake increasing in HH herd sizeLiquidity: IBLI purchase increasing w/HSNP participation and HH savingsIntertemporal Adverse Selection: HHs buy less when expecting good conditions.Spatial Adverse Selection: HHs in divisions with covariate risk are more likely to

purchase and with greater coverage (spatial adverse selection).Gender: no gender diff in uptake. Women more sensitive to risk of new product.

Bageant 2014; Jensen, Mude & Barrett 2014; Takahashi et al. 2014

IBLI’s Impacts: Herd mortality risk

Proportion better off with IBLI coverage

Statistic Loaded & Unsubsidized SubsidizedMean 0.304 1.000Variance 0.346 0.346Skewness 0.818 0.818Semi-Variance 0.354 0.595

Subsidized Rate1 Actuarially Fair2 Loaded & Unsubsidized3

Coefficient of Risk Aversion Lower Upper Lower Upper Lower Upper

R=0 (risk neutral) 0.999 0.938 0.942 0.536 0.626 0.741R=1 0.975 0.914 0.921 0.584 0.613 0.737R=2 (risk averse) 0.966 0.912 0.890 0.605 0.569 0.7481At that time that this data was collected, the annual subsidized rates were Central/Gadamoji=3.325%, Laisamis=3.325%, Loiyangalani=3.325%, and Maikona= 5.5%. 2The within-sample actuarially fair annual premium rates are Central/Gadamoji=9.25%, Laisamis=7.5%, Loiyangalani=7.0%, and Maikona=12.25%. 3The commercial annual premium rates are Central/Gadamoji=10.6%, Laisamis=11.3%, Loiyangalani=9.2%, and Maikona=10.7%.

Proportion of households that are better off with IBLI than without (Simulated utility analysis)

Proportion of households for whom IBLI improves their position with respect to each statistic

Jensen, Barrett & Mude 2014

IBLI’s Impacts: Livestock productivity/income

HSNP Participation:• Improves the likelihood that target type (poor, old, many dependents) households remain mobile, an important characteristic for pastoralists

IBLI coverage:• Increases investments in maintaining livestock through vet expenditures

• Increases total and per TLU income from milk.

Note: TLU veterinary expenditures are pos/sign related to milk productivity

HSNP (FE-IV) IBLI (FE-IV)Production strategies:Herd Size -3.405 -2.639

(4.349) (2.190)[0.090] [0.079]

Veterinary Expenditures (KSH) 363.9 592.1**(269.8) (295.2)[0.095] [0.090]

Household is Partially or Fully Mobile

0.231*** 0.184(0.088) (0.142)[0.261] [0.247]

Production outcomes:Milk income (KSH) 1,143 4,605**

(1,411) (1,995)[0.181] [0.161]

Milk income per TLU (KSH) 12.71 671.3***(136.8) (197.8)[0.221] [0.170]

Livestock Mortality Rate (X100) 0.0150 -0.0466(0.0362) (0.0512)[0.177] [0.175]

A complete list of covariates, coefficient estimates, and model statistics can be found in Jensen, Mude & Barrett (2014). Clustered and robust standard errors in parentheses. R2 in brackets. *** p<0.01, ** p<0.05, * p<0.1.

Jensen, Mude & Barrett 2014

Janzen & Carter 2013

IBLI’s Impacts: Less adverse post-drought coping

Marsabit HHs received IBLI indemnity payments in October 2011, near end of major drought. Survey HHs with IBLI coverage report much better expected behaviors/outcomes than the uninsured:- 36% reduction in likelihood of distress livestock sales, especially

(64%) among modestly better-off HHs (>8.4 TLU)- 25% reduction in likelihood of reducing meals as a coping

strategy, especially (43%) among those with small or no herds

IBLI appears to provide a flexible safety net, reducing reliance on the most adverse behaviors undertaken by different groups.

IBLI’s Impacts: Household subjective well-being

Borana survey HHs report overall life satisfaction. In principle, insurance helps risk averse people even when it doesn’t pay out. But an imperfect product with commercial loadings might not.

• IBLI has a positive, stat sig effect on HH well-being, even after premium payment and w/o any indemnity payments • IBLI coverage for 5 TLU moves a HH 1 step up the SWB scale• Fully insuring 20 TLU (roughly sample mean) shifts HH from lowest to

highest SWB category• Ex post of contract, purchasers exhibit some buyer’s remorse in the absence

of indemnity payments.• But the positive effect of IBLI coverage is significantly higher than the

negative effect of buyer’s remorse.

Even with prospective buyer’s remorse, IBLI purchase improves subjective well-being.

Hirfrot et al. 2014

Although IBLI offers incomplete and imperfect coverage against herd loss, uptake is solid and IBLI has clear favorable impacts on purchasers.

IBLI is a promising option for addressing poverty traps that arise from catastrophic drought risk

Thank you for your time, interest and comments!For more information visit www.ilri.org/ibli/