Index-Based Livestock Insurance in northern Kenya: An analysis of the patterns and determinants of purchase
Upcoming SlideShare
Loading in...5
×
 

Index-Based Livestock Insurance in northern Kenya: An analysis of the patterns and determinants of purchase

on

  • 1,733 views

Presented by Andrew G. Mude and Christopher B. Barrett at the I4 Meetings, Rome, 14 June 2012

Presented by Andrew G. Mude and Christopher B. Barrett at the I4 Meetings, Rome, 14 June 2012

Statistics

Views

Total Views
1,733
Views on SlideShare
1,039
Embed Views
694

Actions

Likes
0
Downloads
15
Comments
0

6 Embeds 694

http://www.ilri.org 469
http://unjobs.org 201
http://ilri.org 18
http://www.ilri.cgiar.org 3
http://users.unjobs.org 2
http://www.ilri.org. 1

Accessibility

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

CC Attribution-NonCommercial-ShareAlike LicenseCC Attribution-NonCommercial-ShareAlike LicenseCC Attribution-NonCommercial-ShareAlike License

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Index-Based Livestock Insurance in northern Kenya: An analysis of the patterns and determinants of purchase Index-Based Livestock Insurance in northern Kenya: An analysis of the patterns and determinants of purchase Presentation Transcript

  • Index-Based Livestock Insurance in Northern Kenya: An Analysis of the Patterns and Determinants of Purchase (very provisional, initial results!) Andrew G. Mude and Christopher B. Barrett I4 Meetings, Rome June 14, 2012
  • ASAL, Pastoralists and Vulnerability• Arid and semi-arid lands (ASAL) cover ~ 2/3 of Africa, home to ~20mn pastoralists, who rely on extensive livestock grazing• ASAL residents confront harsh and volatile environments• Livelihoods are primarily transhumant pastoralism• Pastoralist systems are adapted to variable climate, but very vulnerable to severe drought events. Big herd losses cause humanitarian crises, such as the 2011 headline event in East Africa (esp. famine in parts of Somalia).
  • Study Area in Northern Kenya  Marsabit District 360 km Marsabit 410 km  Pop. 291,166, 0.75% of country, (2009 census)  Four main ethnic groups  Two ecological/livelihood zones: Upper: arid/pastoral Lower: semi-arid/agro-pastoral
  • Northern Kenya: Context for IBLI Component Shares of Income Cause of Livestock Mortality a • Sale of livestock and livestock products • Drought is by far the leading cause of constitute 40% of household income livestock mortality • External support (food and cash) make • Disease and Predation likely to be up nearly 25% of household income directly related to drought Livestock Share of Productive Assets (Median 100%, Mean 49%)Data source: Project baseline 2009 (924 Marsabit Households)
  • Northern Kenya: Context for IBLI Risk of livestock losses based on ALRMP (2000-2010)• Droughts are main cause of catastrophic livestock losses (≥20%)• Livestock losses from droughts are highly covariate, in contrast to other, smaller, idiosyncratic shocks (predation, accident, disease, etc.) in other years Seasonal Location Aggregate Livestock Mortality (%) 70% 60% North Horr 50% Kalacha 40% Maikona Logologo 30% Korr 20% Karare 10% Ngurunit 0% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010• Key drought years in sample: 2000, 2005-06, 2009• Drought-related catastrophic herd losses are largely uninsured!
  • Designing the IBLI indexNormalized difference vegetation index (NDVI) from MODIS sensor Normal year (May 2007) Drought year (May 2009) • Indication of availability of vegetation over rangelands (reflecting joint state of weather realizations and stocking rates) • Spatiotemporally rich (1x1 km2 resolution, available in near-real time every 16 days from 2001- present)
  • Key Contract FeaturesSPATIAL COVERAGE ILLERET SABARET DUKANAHow wide a geographic area can/should a single index- EL-HADI DARADE BALESA FUROLE NORTH HORRcover? MOITE GALAS EL GADE HURRI HILLS KALACHA MAIKONA GAS• Two Separate NDVI-Livestock Mortality Response Functions LOIYANGALANI TURBI ARAPAL LARACHI KURUGUM OLTUROT MT. KULAL BUBISA MAJENGO(MARSABIT) KARGI JIRIMEQILTA• Five Separate Index Coverage Regions HULAHULA SAGANTE KURUNGU OGUCHODIRIB GOMBO KITURUNI SONGA KARARE JALDESA SHURA SOUTH HORR(MARSA) HAFARE KAMBOYE KORR ILLAUT(MARSABIT) LOGOLOGOGUDAS/SORIADI LONYORIPICHAU NGURUNIT LAISAMIS Designing the IBLI index LONTOLIO KOYA IRIR MERILLEEMPORAL COVERAGEver what time span should an index cover?
  • Predicted Mortality Index Readings
  • Impact Evaluation: Two-Way Stratification Design Site selection: 16 locations Confounding factor: ongoing implementation of cash transfer (HSNP) • Randomly select 50% from locations with and without HSNP Encouragement design • Insurance education game: played among 50% sample in game site • Discount coupon for 1st 15 TLU insured: (no subsidy for 40% of sample, 10%-60% subsidies for the rest) Legend ILLERET SABARET MarsabitIBLI DUKANA HSNP, IBLI Game_HSNP, No IBLI No IBLI EL-HADI FUROLE HSNP, IBLI Game Game Game DARADE BALESA NORTH HORR HSNP, No IBLI Game HURRI HILLS MOITE EL GADE No HSNP, IBLI Game HSNP 4 sites 4 sites GALAS GAS KALACHA MAIKONA No HSNP, No IBLI Game LOIYANGALANI TURBI ARAPAL LARACHI KURUGUM No HSNP 4 sites 4 control sites OLTUROT MT. KULAL MAJENGO(MARSABIT) KARGI JIRIMEQILTA BUBISA HULAHULA SAGANTE KURUNGU OGUCHODIRIB GOMBO KITURUNI SONGA KARARE JALDESA SHURA SOUTH HORR(MARSA) HAFARE KAMBOYE KORR Sample selection: 924 households ILLAUT(MARSABIT) LOGOLOGOGUDAS/SORIADI LONYORIPICHAU NGURUNIT LAISAMIS LONTOLIO • Sample/site proportional to relative pop. sizes IRIRMERILLE KOYA •For each site, random sampling stratified by livestock wealth class (L, M, H)
  • Determinants of IBLI Demand Research Question• What are the determinants of household demand for IBLI? (price sensitivity, wealth, herd size, education, product understanding, risk aversion, credit access, livelihood diversification, trust…) Existing Literature Authors Product Results Bryan 2010 Insured loan Malawi Uptake ↓ ambiguity aversion Cole et al. 2010 Rainfall Insurance India Uptake ↑ literacy and trust, ↓ price, credit constraints Cole et al. 2007 Rainfall Insurance India Uptake ↑ wealth, edu, risk aversion, ↓ price Gine et al. 2008 Rainfall Insurance India Uptake ↑ wealth, trust, ↓ risk aversion, credit constraints Gine and Yang 2007 Insured loan Malawi Lower uptake of insured loan than loan Hill et al. 2011 Rainfall Insurance Ethiopia Uptake ↑ edu, wealth, ↓ risk aversion New (?) Contributions to Existing Literature• Considering asset risk while prior products concern income risk• Basis risk controls; hypotheses of spatial and intertemporal adverse selection• Setting is characterized by non-convex asset accumulation dynamics (which could determine household’s valuation of IBLI, Chantarat et al. working paper)
  • Data and Key Variables Data and Key Variables Baseline Data (Collected Oct/Nov 2009 prior to first IBLI sales in Jan 2010)Unless otherwise specified the baseline is the source of all explanatory variablesBought IBLI Dependent Variable Probit Model Sourced from Round 2 (Oct/Nov 2010) survey, verified by administrative data. (Dummy =1 if household indicates that they purchased IBLI in Jan/Feb 2010)Ln(tluIBLI) Dependent Variable Linear Model Sourced from Round 2 self-reported number and type of livestock insured verified by administrative dataEffective Price Price net of premium discount for those who received discount coupons. Administrative data used to match households with the receipt and value of discount coupon . Unit: percent insured value paid as premium.TLU drought mortality Seasonal drought-related TLU mortality rate (LRLD – Mar09-Sept09), (SRSD – Oct08-Feb09). Focused on(LRLD SRSD) mortality resulting from drought/starvation. Denominator is max of beginning season or end season mortality.TLU drought mortality z score sq (individual mortality – location mean mortality)/(location SD mortality) (squared)(LRLD SRSD)Relative TLU drought mortality = 1 if individual mortality is greater than location-level mean mortality(LRLD SRSD)Know IBLI Index of IBLI knowledge adding correct answers from 4 related questions in Round 2 survey. 1 point was given to correct answers for each of the following multiple-choice questions: Based on your understanding of IBLI, 1) How often do you have to pay a premium to remain reinsured? 2) when do you expect compensation? 3) what does compensation depend on,?4) do you expect your premium to be returned if you do not get compensated?Played Game =1 if household was selected to play the insurance game. Administrative data on game households used to identified treated households.Expected Loss Respondent’s subjective expected herd mortality (%) rate for the 2009-2010 SRSD and LRLD coupled seasons
  • Probit Estimateshhsizeheadage 0.014* 0.003 Result 1: Determinants of IBLI Purchaseheadagesq 0headsex -0.049respondantsex 0.055  Price has expected strong effect. Discount coupon has a positivegradeattain -0.01 behavioral effect on purchase independent of its price discount.daycons_percap 0index -0.001  Basis risk impact: As expected households with higher than meaneffectprice -4.729***receivediscoupon 0.212*** (LRLD) mortality less likely to purchase.lstockincshare -0.069lslivelihood -0.065*  Risk preferences: Increased appetite for risk increases probabilitytlu -0.002* of purchase. Innovators’ characteristic or indications of a lottery?tlu2 0LRLDtludrghtmortality 0.036SRSDtludrghtmortality -0.586***  Intertemporal Adverse Selection: More likely to purchase asLRLDtludrghtmortzscoresq -0.001 expectation of future mortality loss increases.LRLDtludrghtmortrelational -0.133***SRSDtludrghtmortzscoresq 0.01**SRSDtludrghtmortrelational 0.022  Knowledge: Better understanding of product associated withrisktaking 0.139*** uptake. But, other than impact on knowledge, playing extensionriskmoderate 0.148*** game has no effect.expectloss 0.242***cashTLU10 0.021hardloanlstock 0.131***  Spatial Adverse Selection: Three divisions of Lower Marsabit faceimploanlstock 0.06 same market price of 3.25% but have different historical burnreceiveHSNP 0.024 rates (Central 1.4%, Laisamis 2.9%, Loiyangalani 1.7%). Patternsplayedgame 0.002knowibli 0.026** of uptake consistent with spatial adverse selection, not withnuminfosource 0.038*** marketing-based or other differences (lower uptake in Centralnumnetgroups 0.029 and Loiyangalani relative to Laisamis).CENTRALDIV -0.137**LAISAMISDIV 0.02 Pseudo R2 0.469LOIYANGALANIDIV -0.181***
  • Result 2: IBLI Demand Elasticity EstimatesDep var : ln (total TLU insured)  Demand seems relatively price inelastic (surprisingly).lneffectprice -0.7064***lnmonthpcincome 0.0823  Considerable and statisticallytlu 0.0146** significant behavioral effect oftlu2 -0.0002* discount coupon receipt, independent of pricereceivediscoupon 0.2734**knowibli 0.0104  Financial liquidity: measured as areceiveHSNP 0.0981 dummy = 1 if household indicatescashTLU10 0.3608** sufficient cash savings to purchase 10 TLU worth of IBLI, matters toCENTRALDIV 0.4574** quantity demanded. But cashLAISAMISDIV -0.0522 transfer (HSNP) receipts do not.LOIYANGALANIDIV -0.5316***  Herd size: very modest increase up_cons -2.7105*** to ~mean+1 SD. Only weakly consistent w/ poverty trap hyp.r2 0.404  No effect of knowledge of IBLI, norN 221 of income
  • Provisional Summary FindingsDemand for IBLI in Marsabit, Kenya pilot appears:-Reinforce prior index insurance studies’ findings on: - price effects (price inelastic demand) - risk preference effects - wealth effects - financial liquidity effects-More novel: - behavioral effects from promotional coupons but not from game exposure - associated with superior understanding of product - negatively associated with a proxy for basis risk - perhaps some intertemporal and spatial adverse selection
  • Thank you for your time,interest and comments!
  • Variable LabelsVARIABLE LABEL VARIABLE LABELboughtIBLI =1 if hh purchased IBLI as per R2 survey LRLDtludrghtmortality LRLD TLU drought mortality LRLD location level tlu drought mortality z scorehhsize Household size LRLDtludrghtmortzsq squared =1 if LRLD TLU mortality is greater than locationheadage age of household head LRLDtludrghtmortrelational level meanheadsex gender of household head (=1 if female) SRSDtludrghtmortality sRSD TLU drought mortality gender of survey respondent (=1 if SRSD location level tlu drought mortality z scorerespondantsex SRSDtludrghtmortzsq female) squared Highest grade attained by household =1 if SRSD TLU mortality is greater than locationgradeattain SRSDtludrghtmortrelational head level mean =1 if risk aversion from preference gamedayconPC Daily per capita consumption (in KSH) risktaking indicates either slight or neutral aversion to risk =1 if risk aversion from preference gameasset index Asset index from first PC riskmoderate indicates either intermediate or moderate aversion to risk Effective price taking into account theeffectprice expectloss expectation of future livestock loss. value of discount received (if any) Whether you received a discount =1 if cashsavings sufficient to purchase 10TLU ofreceivediscoupon cashTLU10 coupon for IBLI as per R2 survey insurance fraction of annual income representated =1 if chances of getting loan for restocking arelstockincshare by sales of livestock and livestock hardloanlstock deemed quite difficult to difficult products =1 if hh heads primary economic =1 if chances of getting loan for restocking arelslivelihood imploanlstock activity is herding of livestock. deemed impossible TLU standardized livestock owned at R1 =1 if household member is HSNP programtlu receiveHSNP survey period in Sept 09 recipient =1 if household located in Central =1 if member of the household played the IBLICENTRALDIV playedgame Division game =1 if household located in Laisamis Index of IBLI knowledge adding correct answersLAISAMISDIV knowibli Division from 4 IBLI featured (R2 survey) =1 if household located in Loiyangalani Number of sources from which they heard aboutLOIYANGALANIDIV numinfosource Division IBLI as per R2 survey Total number of social network groups members
  • Summary Statistics variable mean sd min max variable mean sd min maxboughtIBLI 0.272 0.445 0 1 LRLDtludrghtmortality 0.280 0.280 0 1.778hhsize 5.571 2.353 1 14 LRLDtludrghtmortzsq 0.985 1.712 0.000 15.023headage 47.888 18.329 18 98 LRLDtludrghtmortrelational 0.452 0.498 0 1headsex 0.371 0.483 0 1 SRSDtludrghtmortality 0.063 0.221 0 3.560respondantsex 0.746 0.436 0 1 SRSDtludrghtmortzsq 0.987 4.313 4.99E-06 64.872gradeattain 1.121 3.091 0 13 SRSDtludrghtmortrelational 0.291 0.455 0.000 1dayconPC 53.969 107.015 6.610 3032.146 risktaking 0.290 0.454 0 1asset index 0.000 1.000 -0.945 6.664 riskmoderate 0.440 0.497 0 1effectprice 0.031 0.012 0.013 0.055 expectloss 0.352 0.182 0.05 0.95receivediscoupon 0.325 0.468 0 1 cashTLU10 0.084 0.278 0 1lstockincshare 0.419 0.395 0 1 hardloanlstock 0.459 0.499 0 1lslivelihood 0.447 0.497 0 1 imploanlstock 0.380 0.486 0 1tlu 16.125 24.534 0 361.143 receiveHSNP 0.183 0.387 0 1CENTRALDIV 0.239 0.427 0 1 playedgame 0.297 0.457 0 1LAISAMISDIV 0.219 0.414 0 1 knowibli 1.512 1.344 0 4LOIYANGALANIDIV 0.249 0.433 0 1 numinfosource 2.036 1.699 0 9 numnetgroups 0.550 0.823 0 6