This paper addresses whether the index-based livestock insurance and informal insurance network substitute or complement using the data collected in rural Ethiopia, Borena zone, which is the southern part of the country.
Index insurance has attracted world wide attention as it does not suffer from classical incentive problems, such as moral hazard and adverse selection, traditional insurance faced. Although it is expected to be diffused rapidly, the overall uptake rate is not so high.
Recent theoretical advancements argue that low uptake can be partly explained by the existing of informal insurance network. For example, de Janvry et al. (2014) demonstrates individuals who are connected with informal networks can free-ride on their friends' insurance payout, which creates externatilty, each member expects others to be formally insured, resulting in a socially suboptimal level of insurance coverage. So, unless insurance is sold to a group, which can adjust these externalities through group coordination, informal insurance networks may lead to lower uptake of formal insurance. In a detailed theoretical model, Boucher and Delpierre (2013) show that formal insurance induces behaviroal changes, leading riskier choices (increasing residual risks), so the risk that informal networks must absorb increases, generating a negative externality on network members, and each will leave the informal risk-sharing group.
Yet there is also counterargument. Dercon et al. (2014) model that most index insurance products are designed to target aggregate shocks that affect an entire community, but basis risk remains and such idiosyncratic shocks should be recovered by individual farmers. If individuals within a group can commit to offer mutual protection to each other against such idiosyncratic shocks, then index products offer better value to farmers. They argue that the presence of basis risk makes index insurance a complement to informal insurance networks sharing, and that the demand for index insurance should therefore increases when there is within group risk sharing.
Chemin also discusses that one of the constraints on uptake of microinsurance is trustworthiness of insurance company. It found that support for social learning in groups from early adopters who have tested the insurance system before, and thus alleviate fears of non-reimbursement, implying that group can resolves some constraints.
Although one of the remedy for low uptake seems to provide index insurance to groups, we know little about when whether the index insurance crowed-in or crowed-out informal risk-sharing networks when sold to individuals is scarce.
The primary purpose of this article is to seek empirical support for the alternative theoretical predictions on the demand for group index insurance.
Our study site is in Borene region in southern Ethiopia, about 550 km away from Addis Abeba, Capital of the country. Borena is located near to Kenya boundary. From this region, we selected 17 core areas as study site and collected the baseline data from 515 households in 2012. In 2014, 514 households with some replacement is again covered by the survey.
As an index, the normalized differenced vegetation index, which is a numerical indicator for by satellite was used. The indemnity payout will be done if the cummulative NDVI falls below the 15th percentile of historical distribution since 1981.
In our study, regions are divided into eight Woreda, which is an administrative unit of Ethiopia, and premium rate is set to be the same within the Woreda. Actual premium payout is the woreda-specific premium rate multiplied by total insured herd value which varies with the species of animals.
The region is comprised of arid and semi-arid ecological zones with four seasons: a short rainy season (October to November); and a short dry season (December to February) a long rainy season (March to May); a long dry season (June to September); IBLI is marketed and sold during two periods per year, directly preceding each rainy season (August-September and January-February), with coverage lasting one year and the potential for two indemnity payouts, one after each dry season During each sales period, a household decides whether to buy IBLI and how many animals to insure. If a household buys IBLI in the August-September sales period, it is insured from October 1 to September 30 of the following year and may receive indemnity payouts in March and/or October of the year following purchase. Note that if a pastoral household buys IBLI not only in the August-September sales period but also the following January-February sales period, then insurance coverage periods for the two contracts overlap from March to September, and the household may receive indemnity payouts for both contracts in October.
More precisely, 𝑇𝐼𝐻𝑉= # of camel insured ∗15,000+ (# of cows insured)∗5,000 + (# of goats and sheep insured)∗700 and 𝑃𝑟𝑒𝑚𝑖𝑢𝑚 𝑝𝑎𝑦𝑚𝑒𝑛𝑡=Woreda specific insurance premium rates ∗ 𝑇𝐼𝐻𝑉.
We apply the random matching within sample method, implemented by Santos and Barrett (2011) and Maertens and Barrett (2013), to elicit one’s network and willingness to form informal risk sharing networks. Since within and outside sub-region network will have different implications about IBLI-informal risk sharing nexus, as distance increases, lower correlations exist in terms of shocks, hence more useful in terms of informal insurance. To know differential IBLI impacts, then we may want to add 3 randomly drawn households to the matches from the sub-sample outside each location.
Basically, knowing is important, but not necessary condition for lending.
Here is the result of ivprobit. (1) does not include the far dummy, while (2) includes it. Both show negative, but insignificant: purchase of IBLI and link formation is neither substitute nor complement.
This is extension. I have estimated multivariate probit (three equations: ) and include the predicted variable in the regressors. The results show that if other buy IBLI, pastrorist does not buy IBLI by him/her self. –an indication of free-riding. Also, not robust, but if other buy IBLI, one is more willing to form informal networks with hi/her. Again, purchase of IBLI and link formation is neither substitute nor complement, though signs turns to be positive.
Vasilaky: Formal insurance may encourage additional risk taking, creating residual idiosyncratic risks that the group will incur. (2) nd question is to know closeness of the match and strategic action when one thought that the match is reliable.
Is the demand of the index-based livestock insurance and informal insurance network substitute or complement?
Is the demand of the index-based
livestock insurance and informal insurance
network substitute or complement?
(with Chris Barrett and Munenobu Ikegami)
Index insurance attracts attention as the next financial
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
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
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
Our paper aims to provide empirical evidence to this
issue, by using the data collected in Borena, Ethiopia.
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
Timing of Purchase: before rainy seasons (two times in a
Coverage: 1 year
Timing of Payout: after dry seasons (two times in a year)
Design of IBLI
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
Max: 0.5*TIHV Min: Premium payment
(depending on the severity of the drought)
We want to explore the impact of informal insurance on the
uptake of IBLI or vice versa.
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-
Open question tends to elicit only strong network link
Apply “random matching within a sample” method
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
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
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
Knowing and lending
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%
No 599 1,365 1,964
30.5% 69.5% 100%
Yes 34 479 513
6.63% 93.37% 100%
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
VARIABLES Link Link
𝐼𝐵𝐿𝐼𝑖 -0.057 -0.022
Not simultaneous decision. Given others’ previous purchase
(1) (2) (3) (4)
Link 𝐼𝐵𝐿𝐼𝑖 Link 𝐼𝐵𝐿𝐼𝑖
𝐼𝐵𝐿𝐼𝑖 0.141 0.134
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
Some indication of free-riding:
negative coefficient of others’ IBLI purchase on own purchase
positive coefficient of others’ IBLI purchase on link formation (lend
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
More risk averse households tend to buy IBLI
Discount coupons positively affect the uptake of IBLI
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
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,
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?