Is the demand of the index-based
livestock insurance and informal insurance
network substitute or complement?
Kazushi Takahashi
(with Chris Barrett and Munenobu Ikegami)

Motivation
 Index insurance attracts attention as the next financial
revolution.
 Several studies discuss that formal insurance may crowd
out informal insurance networks (de Janvry et al. 2013 ;
Boucher and Delpierre, 2014;)
 Free-riding: well-connected individuals can free-ride on their
group-members' insurance payout, resulting in a socially
suboptimal level of coverage
 Moral hazard: a greater degree of formal insurance allows for
excessive risk-taking, which informal networks should absorb,
imposing a negative externality on network members-
crowding-out of informal risk-sharing

Motivation
 Counterargument is also provided to explain that the
demand of the index insurance can be complementary to
informal insurance networks (Berhane, et al., 2014:
Chemin, 2014; Dercon et al., 2014; Mobarak and
Rosenzweig, 2013;) .
 Basis risk and crowed-in: the difference between the losses
actually incurred and the losses insured= idiosyncratic risk of
incomplete compensation  pooled and managed within an
informal risk-sharing group
 Increased trust: social learning in groups from early adopters
who have tested the system before, and thus alleviate fears of
non-reimbursement

Motivation
 Empirical evidence on whether the index insurance
crowed-in or crowed-out informal risk-sharing networks
when sold to individuals is scarce, and it is theoretically
ambiguous.
 Our paper aims to provide empirical evidence to this
issue, by using the data collected in Borena, Ethiopia.

Data
 17 Study sites in Borena-Southern Ethiopia (near to Kenya Boundary)
 514 households from Round 3

Design of IBLI
 IBLI insures against area average herd loss predicted based on the index
fitted to past livestock mortality data.
 Index: Normalized Differenced Vegetation Index (NDVI) –
a numerical indicator of the degree of greenness recorded by satellite
 Payout rule: if the index falls below the 15th percentile of historical
distribution since 1981.
ZNDVI: Deviation of NDVI from long-term averageNDVI (Feb 2009, Dekad 3)

Design of IBLI
 Insurance contract
Timing of Purchase: before rainy seasons (two times in a
year)
Coverage: 1 year
Timing of Payout: after dry seasons (two times in a year)

Design of IBLI
 Premium payment:
𝑊𝑜𝑟𝑒𝑑𝑎 𝑠𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝑖𝑛𝑠𝑢𝑟𝑎𝑛𝑐𝑒 𝑝𝑟𝑒𝑚𝑖𝑢𝑚 𝑟𝑎𝑡𝑒𝑠 ∗ 𝑇𝐼𝐻𝑉.
(9.75% for Dilo, 8.71% for Teltele, 7.54% for Yabello, 9.49% for Dire, 8.58% for Arero, 9.36% for Dhas,
and 11.05% for Miyo and Moyale, depending on differences in expected mortality risk)
 Total insured herd value (TIHV):
# 𝑜𝑓 𝑐𝑎𝑚𝑒𝑙 𝑖𝑛𝑠𝑢𝑟𝑒𝑑 ∗ 15,000 + (# 𝑜𝑓 𝑐𝑜𝑤𝑠 𝑖𝑛𝑠𝑢𝑟𝑒𝑑) ∗
5,000 + (# 𝑜𝑓 𝑔𝑜𝑎𝑡𝑠 𝑎𝑛𝑑 𝑠ℎ𝑒𝑒𝑝 𝑖𝑛𝑠𝑢𝑟𝑒𝑑) ∗ 700
 Indemnity Payout:
Max: 0.5*TIHV Min: Premium payment
(depending on the severity of the drought)

Empirical strategy
 We want to explore the impact of informal insurance on the
uptake of IBLI or vice versa.
 Potential problems
 Formation of informal networks/uptake of IBLI is clearly endogenous
 Measuring informal network is often problematic (Santos and
Barrett, 2011; Maertens and Barrett, 2013)
 Census is costly, and infeasible
 Network within sampling method (either list up certain number or not)
artificially truncates the network, and resultant network data are non-
representative
 Open question tends to elicit only strong network link
 Remedy
 Apply “random matching within a sample” method

Empirical strategy
 A household is randomly matched with 5 near neighbors and 3
non-near neighbors within a sample
 Two questions: (1) Do you know (the match)? (2) If yes, are
you willing to transfer cattle as a loan if the match asked for it.
 A dummy, representing a link, equal to 1 if the answer to (2) is
yes
 This is a hypothetical question, but hopefully, this may not be
a problem as informal asset transfers among Boran pastoralists
are generally small. Also, there is evidence that the inferred
determinants of insurance networks derived from this
approach closely match those obtained from analysis of real
insurance relations among the same population (Santos and
Barrett, 2011).

Empirical strategy
 Basic model (via ivprobit)
LINK 𝑖𝑗 = 𝜔 + 𝑎𝑥𝑗 + 𝑏𝑥𝑖 + 𝛽 𝐼𝐵𝐿𝐼𝑖 + 𝜏𝑖𝑗 + 𝜓𝑖𝑗
 LINK: 1 if there is the possibility of transferring cattle as a loan if the
match asked for it between a household i and j,
 Xi: characteristics of household i,
 Xj: characteristics of matched household j,
 Τ: characteristics to replect relationships between i and j
 𝐼𝐵𝐿𝐼𝑖: the predicted IBLI uptake of previous one year (instrumented
with some exogenous variables, such as the discount coupon
recipient (assigned randomly: RCT) dummy)
𝛽>0 is complementary; 𝛽<0 is supplement

Empirical strategy
 Some extension
 Assuming that individual knows others’ purchase decision.
 Individuals strategically decide whether to purchase IBLI given
others’ decisions .
 Set of recursive equations via multivariate probit:
𝐼𝐵𝐿𝑖𝑗= 𝜔1 + 𝑎1 𝑥𝑗 + 𝑐1 𝑧𝑗 + 𝜓𝑗
𝐼𝐵𝐿𝑖𝑖= 𝛽1 𝐼𝐵𝐿𝐼𝑗 + 𝜔2 + 𝑎2 𝑥𝑖 + 𝑐2 𝑧𝑖 + 𝜓𝑖
𝐿𝑖𝑛𝑘𝑖𝑗 = 𝛽1 𝐼𝐵𝐿𝐼𝑗 + 𝛽2 𝐼𝐵𝐿𝐼𝑖 + 𝜔 + 𝑎𝑥𝑗𝑡 + 𝑏𝑥𝑖𝑡 + 𝜏𝑖𝑗 + 𝜓𝑖𝑗

Descriptive statistics
Knowing and lending
Lend
Know No Yes Total
No 1,153 474 1,627
70.87% 29.13% 100%
Yes 633 1,844 2,477
25.56% 74.44% 100%
Have heard name, but never met
No 450 1,484 1,934
23.27% 76.73 100%
Yes 183 360 543
33.7% 66.3% 100%
Relative
No 599 1,365 1,964
30.5% 69.5% 100%
Yes 34 479 513
6.63% 93.37% 100%

Preliminary results
 Basic model (IVprobit)
IBLI: =1 if purchase IBLI at either 3 or 4 sales period
Control: HHsize, Head male (=1), Head age and its squared, Head’s completed
years of education, risk preference dummies, same clan (=1), study site fixed
effect for both own and mathed
IV: dummy to receive discount coupons at either 3 or 4 sales period
(1) (2)
VARIABLES Link Link
far -0.968***
(0.045)
𝐼𝐵𝐿𝐼𝑖 -0.057 -0.022
(0.233) (0.243)

Preliminary results
 Extension (IV+multivariate probit)
(1) (2) (3) (4)
Link 𝐼𝐵𝐿𝐼𝑖 Link 𝐼𝐵𝐿𝐼𝑖
far -0.971***
(0.081)
𝐼𝐵𝐿𝐼𝑖 0.136 0.139
(0.284) (0.311)
𝐼𝐵𝐿𝐼𝑗 0.248* -0.229*** 0.163 -0.240***
(0.138) (0.068) (0.143) (0.068)
*** p<0.01, ** p<0.05, * p<0.1

Preliminary results
 Robustness check
 Not simultaneous decision. Given others’ previous purchase
decision.
(1) (2) (3) (4)
Link 𝐼𝐵𝐿𝐼𝑖 Link 𝐼𝐵𝐿𝐼𝑖
far -0.973***
(0.080)
𝐼𝐵𝐿𝐼𝑖 0.141 0.134
(0.288) (0.319)
𝐼𝐵𝐿𝐼𝑗𝑅3 0.108 -0.301** 0.065 -0.312**
(0.150) (0.152) (0.165) (0.152)
*** p<0.01, ** p<0.05, * p<0.1

Preliminary findings
 Some indication of free-riding:
 negative coefficient of others’ IBLI purchase on own purchase
 positive coefficient of others’ IBLI purchase on link formation (lend
cow)
 no robust results on whether the own purchase of IBLI crowed-out
informal risk sharing network (insignificant coefficient of own IBLI
purchase on link formation, though sign is positive)
 Some other findings:
 If the match is in the same clan, prob (link) is positive and significant
 Others’ wealth measured in TLU does not affect own purchase
decision
 More risk averse households tend to buy IBLI
 Discount coupons positively affect the uptake of IBLI

Future work
 It seems important to investigate whether the free-riding is
driven by the fact that the subject knows very well about the
economic conditions of the matches.
 Cai et al. (2015) show positive network effects are driven by
the diffusion of insurance knowledge rather than purchase
decision.
 Vasilaky et al. (2014) show groups in which individuals knew of
one another's assets were less likely to purchase their
insurance within a group (in line with Boucher and Delpierre,
2014)
 We will add two questions in R4: (1) do you think the match
bought IBLI six month ago? (2) how many cows do you think
the match herds?