Index Insurance and Cash Transfers: A Comparative Analysis from Northern Kenya

Index Insurance and Cash Transfers:

A Comparative Analysis from Northern Kenya

Nathaniel D. Jensen, Andrew G. Mude and Christopher B. Barrett

Presented by Nathan JensenMinneapolis, MN

July, 2014

MotivationBoth cash transfers and index insurance are often endorsed as effective tools for reducing poverty and providing social protection.

Cash transfers have been extensively studied while the rapid proliferation of index insurance programs in developing countries has progressed without a parallel growth in knowledge of the quantity or impacts of such programs.

In one of the most extensive synthesis written about the impacts if index insurance, Cole et al. (2012) conclude the following:

NATHANIEL JENSEN JULY 2014 | CORNELL UNIVERSITY 2

“The field is in urgent need of evaluations analysing take-up and impact of marketed products… …at this stage, research on the impact of index-based insurance should be the key priority. It cannot be emphasised enough that very few empirical evaluations of marketed index-based micro-insurance programmes exist” (Cole et al. 2012, p. 46-47).

What impact does index insurance coverage have on the production strategies and welfare of pastoralists? How do those outcomes compare to that of an unconditional cash transfer program?

Behavioral changes to investment & production strategies in response to changes in risk profile and base income

• Cash Transfers: Bianchi & Bobba 2013; Covarrubias et al. 2012; Gertler et al. 2012; Stoeffler & Mills 2014

• Index Insurance: Cai et al. 2010; Karlan et al. 2014; Mobarak & Rosenzweig 2012

Welfare impacts of behavioral changes and direct financial transactions• Cash Transfers: An abundance of encouraging although not necessarily consistent

studies. See Arnold (2011) and Fiszbein & Schady (2009) for surveys of the literature• Index Insurance: Karlan et al. 2014; Janzen & Carter 2013


Setting: Pastoralists in Marsabit, Kenya• Pastoralists generate a large portion of their income from livestock and livestock

byproducts. (43% of our observations are 100% livestock dependent)

• Drought is the largest killer of livestock.

• Droughts periodically decimate herds.


Causes of Livestock Mortality Marsabit, Kenya

Source: Author’s calculation (2009-2012)

• Introduced in northern Kenya, January 2010

• Objective: To insure households against livestock mortality associated with droughts

• Signal: Remotely sensed normalized differenced vegetation index (NDVI) as an indicator of forage availability

• Index: Predicts division average seasonal livestock mortality rate

• Privately provided with public support (DFID, GoK, ILRI, USAID, WB)

• See http://livestockinsurance.wordpress.com/, Chantarat et al. (2013) for details

NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 5

Source: Esri

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

Index Based Livestock Insurance (IBLI)

For more information on the IBLI project, visit http://livestockinsurance.wordpress.com/

http://livestockinsurance.wordpress.com/

http://livestockinsurance.wordpress.com/

Hunger Safety Net Program (HSNP) • Part of the larger GoK National Safety Net Program• Phase I: 2009-2013 (funded by DFID)• Unconditional bi-monthly cash transfers (~$28/transfer1)• 3 targeting strategies randomized at the community level:

1. Social pension: All members over the age of 542. Depends ratio: Ratio of members that are dependent > 57%3. Community based targeting: 50% of the community, selected by the

community• No retargeting or graduation• See http://www.hsnp.or.ke/, Hurrell & Sabates-Wheeler (2013) for details.


1 $ indicates USD, which is calculated using exchanges rates from 1/1/2010. As a reference point, the average monthly income in our data is $51.57.

http://www.hsnp.or.ke/



Research Design & DataSurvey data

• Annual longitudinal survey of 924 households for 4 rounds

• 4/5 IBLI index divisions• Seasonal data collected for the most relevant

variables

Research Design• Overlap with a cash transfer program (HSNP) in 8 of

16 communities• Randomized distribution of coupons providing from

10-60% discount on IBLI policies to 60% of sample each sales window


KARGI

SHURA

MAIKONA

BUBISA

TURBI

ILLERET

GALAS

SABARET

KOYA

DARADE

NORTH HORR

DUKANA

EL GADE

KORR

KURUGUM

BALESA

LAISAMIS

EL-HADI

FUROLE

KALACHA

HAFARE

GAS

HURRI HILLS

LOIYANGALANI

KURUNGU

LONTOLIO

ARAPAL

LOGOLOGO

QILTA

MT. KULAL

MOITE

GUDAS/SORIADI

KARARE

IRIR

NGURUNIT

LARACHI

KAMBOYESOUTH HORR(MARSA)

LONYORIPICHAU

SONGA

MERILLE

ILLAUT(MARSABIT)

HULAHULA

MAJENGO(MARSABIT)

OGUCHO

OLTUROT

JALDESA

KITURUNIDIRIB GOMBO

JIRIME

SAGANTE

LegendMarsabitIBLIHSNP, IBLI Game_HSNP, No IBLI Game_No HSNP, IBLI Game_No HSNP, N

HSNP, IBLI Game

HSNP, No IBLI Game

No HSNP, IBLI Game

No HSNP, No IBLI Game

Econometric Strategy

Unobserved Use household fixed effect model

Assume Ǝ unobserved that are correlated with & Instrument for a. IBLI: Randomly distributed discount couponsb. HSNP: Exogenous eligibility thresholds

= (Cumulative prior seasons as an HSNP participant, Current HSNP participant)=(Cumulative prior seasons with IBLI coverage, Current IBLI coverage in TLUs)


HSNP (FE-IV) IBLI (FE-IV) Previous

Participation Current

ParticipantPrevious

Coverage Current

Coverage (TLU)Production strategies: Herd Size -0.167 -3.216 -5.912** 0.139 (0.453) (4.121) (2.776) (0.662)Veterinary Expenditures (KSH) 11.06 371.3 955.3** 5.039

(59.95) (316.4) (462.2) (167.5)Ratio of Herd Held at Home 0.0126 0.106 0.169 -0.118*

(0.0185) (0.0965) (0.165) (0.0711)Household is Partially/Fully MobileA 0.0322 0.185** -0.0871 0.0934

(0.0206) (0.0855) (0.147) (0.0658)Production outcomes: Milk income per TLU (KSH) 74.08** -103.1 760.8*** 118.8**

(30.47) (127.8) (211.1) (57.25)Livestock Mortality Rate -0.0260** 0.0556 -0.00838 -0.00280

(0.0115) (0.0348) (0.0599) (0.0161)A complete list of covariates, coefficient estimates, and model statistics can be found in Jensen, Mude & Barrett (2014). A A linear probability model is used to estimate the likelihood that a household is partially or fully mobile. Clustered and robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.


Current HSNP Participant

(FE-IV)

Current IBLI Coverage (FE-IV)

Shock 0.261*** 0.362*** (0.087) (0.082)Participation/Coverage (P/C) 0.215 0.188** (0.166) (0.083)P/C*Shock 0.0163 -0.215 (0.203) (0.158) H0: P/C + P/C *Shock=0 (t-statistic) 1.118 -0.200Observations 6,564 6,570Model F-statistic 4.993 5.054The shock is an indicator that the division average livestock mortality rates in the current season are equal to or above 15%. A complete list of covariates, coefficient estimates, and model statistics can be found in Jensen, Mude & Barrett (2014). Clustered robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.

The impact of covariate shocks and program participation on livestock sales (TLUs)


HSNP (FE-IV) IBLI (FE-IV) Previous

Participation Current

ParticipantPrevious Coverage

Current Coverage

(TLU)Indicators of Welfare:Consumption per Adult Equivalent (AE)

-60.36* -32.17 355.7 -180.7(34.01) (372.9) (150.7) (150.7)

[15.67] [13.03] Asset Index -8.715*** 16.98* -16.13 -6.077 (3.031) (8.765) (23.26) (4.697) [18.26] [21.04] Income per AE 0.595 374.5 132.9 420.7***

(41.35) (293.5) (304.1) (150.2) [17.99] [19.13] School Enrollment 0.0242 -0.0392 0.0931 0.0629

(0.0244) (0.0941) (0.115) (0.0501) [4.077] [3.785] MUAC 0.0729 0.539 -0.417 -0.0185 (0.109) (0.651) (0.846) (0.226) [7.086] [6.504]A complete list of covariates, coefficient estimates, and model statistics can be found in Jensen, Mude & Barrett (2014). Clustered robust standard errors in parentheses. Model F-statistic in brackets. *** p<0.01, ** p<0.05, * p<0.1. NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 11

VOI Mean VOI in Final Period

HSNP 0.89HSNPC 3.89IBLI 0.48IBLIC 1.20Values are calculated for the subset of clients in each program.

Average values in the final survey round (clients)

Income from Milk Income per AECost structure Impact Impact/

CostImpact Impact/

CostTotal Program Cost/Participant:

HSNP 1,585 0.0333 336 0.0071 IBLI 2,536 0.0587 361 0.0084 Marginal Cost of an Additional Participant:

HSNP 1,585 0.0469 336 0.0099IBLI 2,536 1.1660 361 0.1662

All values in real 2009 Kenya Shillings. Impacts are estimated using the average client value and costs provided below, and parameter estimates in the previous two slides.

Impacts Normalized by Cost Among Clients


HSNP IBLITotal Program Cost/Participant

47,600(2.7BN/57,811HH)

43,200(99MM/

3,297contracts*1.44 contract/HH)

Marginal Cost of an Additional Participant

33,800 (14.6 transfers)

2,175 (4.41TLUs)

Average cumulative cost per client by the final round (KSH)

VOI Mean VOI in Final Period

HSNP 0.89HSNPC 3.89IBLI 0.48IBLIC 1.20Values are calculated for the subset of clients in each program.

Average values in the final survey round (clients)

Income from Milk Income per AECost structure Impact Impact/

CostImpact Impact/

CostTotal Program Cost/Participant:

HSNP 1,585 0.0333 336 0.0071 IBLI 2,536 0.0587 361 0.0084 Marginal Cost of an Additional Participant:

HSNP 1,585 0.0469 336 0.0099IBLI 2,536 1.1660 361 0.1662

All values in real 2009 Kenya Shillings. Impacts are estimated using the average client value and costs provided below, and parameter estimates in the previous two slides.

Impacts Normalized by Cost Among Clients


HSNP IBLITotal Program Cost/Participant

47,600(2.7BN/57,811HH)

43,200(99MM/

3,297contracts*1.44 contract/HH)

Marginal Cost of an Additional Participant

33,800 (14.6 transfers)

2,175 (4.41TLUs)

Average cumulative cost per client by the final round (KSH)

Conclusions• Households with IBLI coverage reduce herd size

(precautionary savings), are more active in livestock markets during non-shock seasons, increase investments in livestock health services and realize greater productivity.

• HSNP participants are more mobile, experience reduced livestock mortality and increased productivity.

• Both programs are likely to improve income/AE.• HSNP & IBLI produce similar improvements/TPC/participant.• IBLI generates greater improvements/MC/participant.


IBLI IVs• A test of balance between coupon recipients and non-recipients finds

few significant differences (<10% of the characteristics observed).• Receiving a coupon has a positive and significant impact on demand.


Dummy(=1 if purchased)

Level(TLUs insured)

Coupon Dummy 0.206*** 0.541*** (0.028) (0.076) Observations 7,042 7,042F(2,1008) 33.5 32.7R2 0.225 0.128Regression includes the following covariates: adult equivalence, age of head, age of head squared, maximum education in household, a dummy indicating the head of household is a widow, the current season’s predicted livestock mortality rate, the current season’s predicted livestock mortality rate squared, division-period dummies and the three HSNP targeting characteristics to the first, second, and third power. Clustered and robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1

HSNP IVs• Tests for distortions in the responses around the thresholds does

not reveal misreporting to meet eligibility requirements.• The intent to treat indicator has a positive and significant impact

on the likelihood of participating in HSNP.


HSNP ParticipantITT 0.614*** (0.050) Observations 7,036Pseudo R2 0.524Regression includes the following covariates: adult equivalence, age of head, age of head squared, maximum education in household, a dummy indicating the head of household is a widow, the current season’s predicted livestock mortality rate, the current season’s predicted livestock mortality rate squared, division-period dummies and the three HSNP targeting characteristics to the first, second, and third power. Clustered and robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1

Documents

Index Insurance and Cash Transfers: A Comparative Analysis from Northern Kenya