Explaining Index Based Livestock Insurance in Kenya through Games: Describing Our Approach and Analyzing Game Play. John McPeak, 215 Eggers Hall, Department of Public Administration and International Affairs, Maxwell School of Citizenship and Public Affairs, Syracuse University. (315)

IBLI – Index Based Livestock Insurance This research was made possible by support provided in part by the US Agency for International Development (USAID) Agreement No. EDH awarded to the Assets and Market Access Collaborative Research Support Program (AMA CRSP). This research was conducted in collaboration with Andrew Mude, Munenobu Ikegami, Sommarat Chantarat, Chris Barrett, and Michael Carter and other individuals at the International Livestock Research Institute, Cornell University, University of Wisconsin-Madison, The Australian National University, and the University of California-Davis. All views, interpretations, recommendations, and conclusions expressed in this paper and presentation are those of the author and not necessarily those of the supporting or collaborating institutions.

TIMELINE ALRMP gathering data from late 90’s to present in Arid Districts of Kenya. PARIMA, a GL-CRSP funded project, active in Northern Kenya / Southern Ethiopia Quarterly panel data on 330 households from 2000 to DFID launches HSNP in 2007; cash transfers to reduce poverty IBLI begins in 2007 to develop index based livestock insurance 2008, Index Construction, WTP study, first round of extension games played game revision, baseline survey written and run, and second round of games played in First round of insurance purchase in February-March, repeat survey in October to December 2011 Second round of insurance purchase in February-March repeat survey in the field now. Some problems with the insurance partner led to lower sales than expected.

The Basic Idea

Research Design IBLI is asset protection, reduce impact of shocks to A. HNSP is cash transfer, works like U. Sites with IBLI and HSNP Sites with only IBLI or HSNP Sites with neither Full comparison is ahead

Top photo by John McPeak, Bottom photo by Sharon Osterloh

Google Earth Map of IBLI sites. Top photo by Chris Barrett, Bottom photo by John McPeak

NDVI Normal Year (May 2007) Drought Year (May 2009) From Chantarat and Mude 2011

Annual Deviation of NDVI

What Is the Index Part?

Why Index Insurance for Livestock? Figure 1: Share of Total Income from Different Sources, PARIMA data, Kenya sites,

Why Index Based Livestock Insurance? Figure 2: Mean Herd Size and Income per Person per Day, PARIMA data,

Nutrition as well as income impact Mude et al., Food Policy, 2009

What is the Index Predicting? Total number of animal deaths from the Kenya sample of 180 households per round and reason cited for the death.

Creating informed Demand: The Index Insurance Game Random Draw Initial Herd Size Pay ‘consumption’ – Generates Bifurcating Asset Dynamics Buy insurance Draw idiosyncratic outcome Draw covariate outcome Calculate herd size change Pay out on insurance policies if applicable Move to new round Each round is a rainy season dry season six month period

Creating informed Demand: The Index Insurance Game 2008 All Sites Covariate value -30%-20%0%10%20% Probability of value 6% 13%44%31% Idiosyncratic value -10%0%10% Probability of value 33% 2009 Upper Marsabit Covariate value40% (-25%)30% (-15%)20% (-5%)10% (5%)0% (15%) Probability of value10% 60% Idiosyncratic value-15%0%15%30% Probability of value30%50%10% 2009 Lower Marsabit Covariate value30% (-15%)20% (-5%)10% (5%)0% (15%) Probability of value15% 10%60% Idiosyncratic value-15%0%15%30% Probability of value25%50%12.50% Mean Net Change (Threshold) Variance Net ChangePrice per month per TLUPricing in Game 2008 All Sites 7.5% (6.7 TLU) KSH100 KSH covers 6 months 2009 Upper Marsabit 10.0% (5 TLU) KSH750 KSH covers 12 months 2009 Lower Marsabit 9.0% (5.6 TLU) KSH750 KSH covers 12 months

2008 Game Play, Karare Kenya

GameWeb for Start at about 6:45

How Did People Play the Game The 2008 data had been analyzed before, and is presented in an Agricultural Finance Review (2010) article. The 2008 and 2009 were combined to be presented here. Specification based on 2008 findings Issues: 2009 cost more, could only be bought in even rounds, and had a different probability distribution. Control by using price per TLU per month. – Trying to use Expected Herd growth also does not work as too much covariation with site dummy and game play parameters defined by site.

Bifurcating Asset Dynamics Round of the Game TLUTLU

Game Play Percent of Game Herd TLU InsuredNumber of Game Herd TLU insured βSE β means Round 0 TLU ** ** Round Round squared/ Lag covariate shock ** ** Lag idiosyncratic shock *** *** Lag % net TLU change ** Round TLU *** *** Round TLU / *** Price/month Insurance *** ***3.277 Dirib Gombo *** Kargi *** Karare *** Logologo *** *0.167 North Horr *** Kalacha *** Turbi *** *0.027 Ilaut *** *0.025 Loiyangalani *** South Horr *** R2R F N2865

Predicted TLU Insured (y-axis) as function of game herd size (x-axis)

Implied Price Elasticity of Demand Implied price elasticity of demand moving from 16.7 KSH per month to 62.5 KSH per month – %ΔQ=-8%, %ΔP=73%, ε= Chantarat finds much more elastic results, more inelastic for poorer, more elastic for wealthier in the WTP study.

Response to Lagged Game Variables Shock or net % herd size change TLUINSUREDTLUINSURED

Game Play with Personal Characteristics (site dummy results omitted) Percent of Game Herd TLU InsuredNumber of Game Herd TLU insured βs.e.β Means Round 0 TLU ** *9.426 Round Round squared Lag % net TLU change **0.079 Lag covariate shock ** **0.054 Lag idiosyncratic shock *** ***0.004 Beg. TLUs each round *** ***9.588 Beg. TLUs squar~ ***0.117 Price/month Head is male *** ***0.728 Age of head * ** Head age squared/ *2.548 Head attended school * ***0.751 How many graduated HS *** ***0.513 Household size Dependency ratio * *0.467 Herd size *** *** Herd size sq/ **0.830 % immature animals ** ***0.223 R2R F N2759

Evidence on Sales October 2009: How many in a random sample of 924 people said they would buy insurance? 98% First round of sales in early 2010 covering March 2010 to February 2011 October 2010: How many in a random sample of 723 people did buy insurance? 35% Second round of sales in early 2011 covering March 2011 to February 2012 Currently working to manage a third round of contracts.

If not, why not from the 2010 sample?

March 2010_ February 2011 March 2011_ February 2012 People buying contracts 1, TLU Insured5,375 TLU1,086 TLU Value insured in USD $1,193,080$218,083 Insurance company received $77,636$13,641 Subsidy$31,039$5,456 Herders Paid$46,597$8,185 Subsidy as % of value insured 2.60%2.50% Herder paid as % of value insured 3.90%3.75% Insurance c. rec as % of value 6.50%6.25% TLU insured per person average 2.8 TLU1.7 TLU Premium per person average $39.23 ($15.68 subsidy, $23.55 herder) $21.38 ($8.55 subsidy, $12.83 herder) Payout total$0$19,947 Payout per person average $0$31 1 TLU (Tropical Livestock Unit)= 250 kg. liveweight =10 sheep or goats = 1 head of cattle = 0.7 camel. 15% predicted mortality ‘trigger’. Sales in Early 2010, again in early 2011

Conclusions Really just getting going on this analysis so preliminary Chantarat’s WTP sample has more covariates that merit comparison with game play for repeat has actual purchases, so we can look at both WTP and Game Play predictions in contrast to what happened.

Conclusions Major drought currently testing the product’s ability to insure against asset risk. Behavioral responses still to be identified: – More livestock with lower risk? – Higher sales from existing herd (higher offtake rates) if need to self-insure increases herd size? – Collateral / credit constraint impact?