index insurance and cash transfers: a comparative analysis from northern kenya
Post on 08-Feb-2016
35 Views
Preview:
DESCRIPTION
TRANSCRIPT
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
NATHANIEL JENSEN JULY 2014 | CORNELL UNIVERSITY 3
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.
NATHANIEL JENSEN JULY 2014 | CORNELL UNIVERSITY 4
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/
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.
NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 6
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.
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
NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 7
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)
NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 8
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.
NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 9
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)
NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 10
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
NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 12
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
NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 13
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.
NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 14
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.
NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 15
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.
NATHANIEL JENSEN JUNLY 2014 | CORNELL UNIVERSITY 16
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
top related