CMF-CAB Conference on Microfinance, January 16-17 th
“Optimizing Microfinance Distribution Channels”
Results from Rainfall Insurance Studies in Gujarat and
Andhra Pradesh
Raghabendra Chattopadhyay
Indian Institute of Management -Calcutta
1

Based on results from :
“
Barriers to Household Risk Management: Evidence from India” working paper
Shawn Cole
HBS
Petia Topalova
IMF
Xavier Gine
World Bank
Robert Townsend
MIT
Jeremy Tobacman
Wharton
James Vickery
NY Fed
2


Tests competing theories of household insurance demand to understand the barriers to adoption of a specific risk management product

Using a set of randomized experiments
◦ In Andhra Pradesh, with BASIX
◦ In Gujarat with SEWA, an NGO


Why don’t more households participate in formal markets when available?

We study participation in a rainfall insurance product offered to rural Indian households.

The context is one in which benefits of risk diversification appear to be high. Indian monsoon risk is an aggregate local shock, but uncorrelated with global financial markets

80% of respondents cite weather shocks as a major risk faced by household.


Design of treatments is guided by potential barriers to adoption:

Neoclassical (standard)
◦ Transaction Costs
◦ Credit constraints
◦ Price / Expected value

Non-standard
◦ Financial literacy / complexity
◦ Trust
◦ Framing


What are the determinants of adoption?

What is the impact of insurance on investment, risk-sharing and consumption?







Product Description
Sample and Summary Statistics
Patterns of Take-up
Experimental Design
◦ Andhra Pradesh
◦ Gujarat
Results
Conclusions


Financial derivative on rainfall
◦ Basis is rain measured at rainfall station
◦ Sold within 20 Km of station
◦ Payout based on amount of rainfall

First sold in India in 2003 (Andhra Pradesh)

Designed by World Bank and ICICI


Coverage during Kharif season (monsoon)

Payout designed to correlate to economic loss from drought / flood

Limitations on how complex product can be
◦ Transparency
◦ Pricing

ICICI Policies (Gujarat in 2006 and AP in all years)
◦ Policy starts after 20-50 mm accumulated
◦ Three phases: sowing, flowering, and harvest
◦ Each phase pays out or not separately


Key benefits:
◦ No adverse selection (except maybe temporal)
◦ No moral hazard
◦ Easy to price
◦ Divisible: policies as cheap as $1.50, promising to pay up to $12
◦ Easy to purchase (private company, not government)
◦ Fast claim settlement


Key limitations:
◦ Basis Risk
 Water needs perhaps not linear
 Rain in plots may differ from rain at gauge
 Non-weather related risks: pests, prices, etc
◦ Complicated
◦ Potentially expensive
 Expected payout ranges from 30%-95% of premium cost
◦ Designed as catastrophic insurance: Pays 1 in 9 years, but max payout (return of 900%) is triggered
1 in 100 years.
◦ Limited re-insurance market


Gujarat (Chattopadhyay,Cole,Tobacman, Topalova)
100 villages in 3 districts, half offered insurance
◦ Non-random sample selection. In each village:
5 at random from SEWA member lists
 5 with significant bank account balances
 5 identified as likely to adopt insurance
◦ SEWA (NGO) sells ICICI & IFFCO policies
◦ Low levels of human capital and financial literacy
◦ Relatively poor, many landless laborers


Andhra Pradesh (Gine,Townsend, Vickery)
◦ 1,000 households from 37 villages in two districts of
Andhra Pradesh
◦ Stratified sample after village enumeration on purchase of insurance in 2004 and marketing meeting attendance
◦ BASIX (MFI) sells ICICI/Lombard insurance
◦ Experiment conducted by ICRISAT staff
◦ Relatively wealthy, groundnut and castor farmers

Land Ownership
Own Land
Amount of Land owned (bigha=.5 acres)
Number of plots
HH had credit in May 2006 (1=Yes)
AP
100%
13.0
1.79
89.8%
Gujarat
48%
6.03
1.64
71.8%


AP sample more likely to own land and have higher landholdings
SEWA intentionally markets to landless laborers

Assets
Tractor
Tresher
Bullocks
Furniture
Bicycle
Motorcycle
Sewing Machine
Elec. Appliances
Telephone
AP
4.5%
0.6%
23.4%
88.0%
46.5%
14.7%
6.6%
63.7%
23.0%
Gujarat
2.21%
0.80%
4.28%
98.40%
32.24%
7.83%
5.81%
64.62%
13.83%
2.30


Gujarat is a richer state than AP
Yet by asset measure, AP sample seems richer


Risk Aversion measured through choice of lotteries
(Binswanger, 81)

Discount rates through hypothetical questions
◦ Would you prefer to receive Rs X today or Rs Y one month from today?

Financial Literacy measured using questions from DHS
(Lusardi and Mitchell, 2006), on interest, inflation, and risk diversification (four questions)

Knowledge of insurance through hypothetical question
◦ Imagine that the trigger was X and actual rainfall Y. Would you receive a payout, and if so how much?

Knowledge of millimeters
◦ Starting from [thick black line], can you show me how far
60mm is?

Average Score, Financial Literacy
Average Score, Math Questions
Average Score, Probability Questions
Averag Score, Insurance Questions
Knowledge of mm
Risk Aversion
AP
--
--
--
0.80
0.21
0.57
Gujarat
0.34
0.62
0.72
0.68
--
0.46

Utility function
Risk aversion
Subjective discount rate
Beliefs about return on insurance
Above average expected monsoon rain (normalized)
Basis risk
Pct. of cultivated land that is irrigated
Pct cultivated land in castor or groundnut
Wealth, income and credit constraints
Number of plots
Logarithm of wealth
Logarithm of Monthly Per Capita Expenditures
Has savings account
(1=Yes)
0
+
0
0
++
0
0
0
0
AP
---
0
Gujarat
---
0
---
++
---
+++
0
0
+
18

Gujarat
Familiarity with insurance and BASIX
Average insurance payouts in the village 2004 and 2005
HH bought weather insurance in 2004 (1=Yes)
Financial literacy
Probability skill
Insurance skills (normalized)
Household has other insurance (1=yes)
Don't know Provider (1=Yes)
Technology diffusion / networks
HH belongs to a BUA / WUG group (1=Yes)
Number of groups that the household belongs to
Demographic Characteristics
Scheduled Caste or Tribe
Muslim
Household head's gender (1=male)
Log of household head 's age
Log of Household Size
Highest education level is higher or equal to secondary school
AP
+++
+++
+++
+++
---
0
+
0
0
0
0
0
0
++
+++
0
+++
++
+++
0
0
0
19



Andhra Pradesh
◦ Visit: Household is visited by team
◦ Endorsement: Visit is endorsed by BASIX representative
◦ Education: Additional training converting mms into soil moisture
◦ Liquidity: Households receive either Rs 25 or Rs
100
Gujarat
◦ “Subtle” Marketing Manipulations
◦ Random discounts


Door-to-door visit
◦ Visit affects take-up substantially
 Households are 13 percentage points more likely to purchase insurance
◦ Hard to reconcile with transaction costs story: BASIX representative available in village on weekly basis


Endorsement
◦ Increases take-up by six percentage points
◦ Not a matter of transactions costs as BASIX representative is available on weekly basis in village


Education Module
◦ Only 10 percent of households understand link between mm to soil moisture, yet policy triggers are set in mm
◦ No effect
◦ Caveats
 Visits with module were only 2 minutes longer than visits without. (Average visit 25 min)
 Recipients were no more likely to understand mm after
2 months.


Liquidity Constraints
◦ Cash on-hand single most important determinant of insurance participation
◦ Survey compensation of Rs. 100 vs. Rs. 25 increases take-up by 34 percentage points, against mean of 24 percent


30 of 99 villages treated in 2006

20 more villages treated in 2007

Marketing manipulations: three (non-random) groups selected
◦ “Old” treatment villages: flyers
◦ “New” treatment villages:
 Surveyed households: video treatments
 Non-surveyed households: video treatment

Within groups, marketing treatments randomly assigned


Individual vs. Group
◦ Individual: Purchase insurance to protect yourself during drought
◦ Group: Purchase insurance to ensure you can help your friends and family in case of drought

Religion
◦ Figure in flyer has Muslim / Hindu / no name
◦ Standing in front of a Mosque / Temple /
Building



Video players, $100/each
Allows more control of message
27


Video Treatment: Surveyed Households (N=315)

Payout Framing [Asian Disease]:
◦ Positive: “This policy would have paid out 2 of the past 10 years”
◦ Negative: “This policy would have not paid out 8 of the past 10 years”

Insurance Framing:

◦ Security: ”Purchase insurance to ensure that you are safe and secure” with picture of lush fields and happy farmers
◦ Vulnerability: ”Purchase insurance to avoid suffering in case of drought” with picture of dry land and forlorn farmers
Video treatments reinforced with fliers


Video Treatment: Non-Surveyed Households
(N=1098)

Peer vs. Authority: The product is introduced by a teacher (authority) vs. a fellow SEWA member (peer)

SEWA Brand: Does SEWA's brand figure prominently in the video?



Price Variation: For all video treatments
Randomly assigned in advance
◦ 40% Rs. 5
◦ 40% Rs. 15
◦ 20% Rs. 30
30

Video Treatments Total
Sample Size 1413
Surveyed Non-Surveyed
315 1098
Sewa Association
Peer Endorse
2/10 yes
Vulnerability Frame
Discount==5
Discount==15
Discount==30
Flyer Treatments
Sample Size
Individual
Neutral
Muslim
0.62
0.59
0.52
0.11
1.00
1.00
0.50
0.51
0.51
0.47
0.52
0.00
0.42
0.38
0.19
0.48
0.34
0.18
0.41
0.40
0.20
2,391
0.52
0.35
0.35
-

2006
% Take-up
2007
Take-Up
Premium (Rs.)
2006 2007
Premium (USD)
2006 2007
Anand
Ahmedabad
Patan
Total
14%
18%
34%
23%
40%
17%
47%
34%
144
155
257
Repeat Purchases
Buy in '06 Buy in '07
No
Yes
No
No
No
Yes
Yes
Yes
52%
13%
25%
10%
44
72
85
$ 3.43
$ 3.69
$ 6.12
$ 1.05
$ 1.71
$ 2.02
32



Video Treatment
◦ Framing main effects statistically indistinguishable from zero, but bounds nontrivial
◦ Test of joint framing main effects cannot reject no effects
◦ (Much larger sample than laboratory experiments)
Discount has a large effect:
◦ Rs. 30 discount leads to ~13 percentage point increase in take-up (off a base of 26%)


Treatment interactions:
◦ SEWA brand negative
 Discount even more important w/SEWA brand
 But maximum discount doesn’t overcome negative effect
 Currently measuring trust in SEWA
◦ No direct effect of peer endorsement
 But peer endorsement more than halves demand elasticity

Gujarat Results

Take-Up Rate and Returns to Insurance
Discount
5
15
30
Ahmedabad
"Return" Take-Up
0.64
0.87
1.81
25%
37%
47%
Patan
"Return" Take-Up
0.54
0.61
0.78
0.22
0.22
0.30
n/a n/a n/a
Anand
"Return" Take-Up
0.36
0.37
0.44
• Calculate expected return of policy using historical data
• Purchase increasing in “return” / decreasing in price
• 53% of households decline policy with expected 81% return over four months
35


Andhra Pradesh
◦ Farmers self-report: no change in behavior

Gujarat
◦ Strong first stage (t-stat of 14)
◦ No effects on HYV adoption, investment decision

Unit demand puzzle
◦ 90 percent of households purchase only one unit of insurance.
 Max payout per policy is roughly Rs 1,000
 Average total income is Rs 60,000

Factor Andhra Pradesh
Reputation of Seller Yes
Price (20% discount) --
Liquidity (50% of premium) Yes
Education No
Salience (House Visit) Yes
Subtle Psychological Cues --

Models finding support:
◦ Rational
◦ Credit constraints
◦ Trust
Gujarat
--
Yes
--
--
Yes (non-exp)
Some


Insurance demand is sensitive to price

Liquidity constraints are an important barrier to household risk management

Non-standard factors such as trust are important

Behavioral cues may affect demand elasticity

Unit demand unresolved puzzle





Crop-specific insurance policies (cotton, rice)
Incorporate rainfall variation over monsoon
Have policies written at a taluka/tehsillevel
Use agri-loans as a distribution channel
39
















Motivation – technical
Product Description
Graphic for sampling in AP
Religion cue
Summary stats on SC/ST, Religion
Speculation
Repeat buyers – AP
Gujarat video / flyer interactions
Gujarat video effects
Gujarat results – video interactions
AP marketing results
AP interactions
Gujarat flyer results
AP : Patterns of take-up
Gujarat : difference between Group vs. Individual framing
40


Theory suggests households should not hold idiosyncratic risk

Yet, most individuals (and countries) hold idiosyncratic risk:
◦ Housing price risk
◦ Local weather
◦ Commodity prices
◦ Regional income fluctuations
◦ Disability

In some cases, financial contracts simply do not exist, while in other cases, their use is not widespread.
Shiller (1998):
It is odd that there appear to have been no practical proposals for establishing a set of markets to hedge the biggest risks to standards of living

payout
• Total payout = sum of payouts across three phases.
• Insurance premium based on actuarial value + 25% admin fee + tax.
2 nd trigger
(corresponds to crop failure)
1 st trigger

Radius of circle = 20km


Farmers used to worry about whether the rains would come. After all, only God can control the rain. But weather insurance provides protection and security.

Ramjibhai used to worry about whether the rains would come. After all, only God can control the rain. But weather insurance provides protection and security.

Hamikhan used to worry about whether the rains would come. After all, only God can control the rain. But weather insurance provides protection and security.
44

Demographics
Household Size
Scheduled Caste
Scheduled Tribe
Muslim
AP
6.26
10%
2%
4%
Gujarat
5.94
35%
8%
9%

AP households less likely to be minority


Index-based insurance may indeed develop into a mature product
◦ Temperature, wind
◦ Satellite imagery (pilot in India this year)

Government of India subsidies hurting private market
◦ But public subsidies may be necessary for adoption
46

Yes
No
Yes
Yes
Yes
2004
No
No
No
No
Yes
No
Yes
Yes
2005
No
No
Yes
No
Yes
Yes
No
Yes
2006
No
Yes
No
Pct of Sample
50.14
15.57
1.05
12.7
0.48
6.21
2.67
2.1

Surveyed Households: Video
(2/10 | 8/10 ) * (Vulnerability | Security) * (SEWA
Brand) * (Rs. 5 | 15 | 30)
Non Surveyed Households: Video
(2/10 | 8/10 ) * (SEWA Brand | not) * (Peer | teacher) * (Rs. 5 | 15 | 20) * (Security)
Flyer Manipulations
(Individual | Group )* (Muslim | Hindu | Neutral)
48

Panel A: Main Effects
"Vulnerability" Frame
Pays 2/10 Years
Discount Percent
Sewa Brand Strong
Peer Endorser
Surveyed Household
Sample
Village FE No
All
0.05
(0.05)
-0.03
(0.02)
0.307 ***
(0.076)
-0.03
(0.03)
-0.03
(0.03)
0.16 **
(0.06)
0.04
(0.05)
-0.03
(0.02)
0.339 ***
(0.075)
-0.03
(0.03)
-0.02
(0.03)
0.18 ***
(0.06)
1413 1413
Yes

Panel B: Main Effects and Interactions
"Vulnerability" Frame
Pays 2/10 Years
Discount Percent
Sewa Brand Strong
Peer Endorser
Surveyed Household
Discount * "Vulnerability Frame"
Discount * Pays 2/10 Years
Discount * Sewa Brand Strong
Discount * Peer Endorser
Discount * Surveyed Household
All
0.13
(0.10)
-0.04
(0.04)
0.37 **
(0.15)
-0.08 **
(0.04)
0.02
(0.04)
0.21 ***
(0.07)
-0.43
(0.33)
0.05
(0.13)
0.26 **
(0.12)
-0.25 *
(0.15)
-0.23
(0.31)
1413
0.13
(0.10)
-0.05
(0.04)
0.40 ***
(0.15)
-0.08 **
(0.04)
0.04
(0.05)
0.21 ***
(0.07)
-0.47
(0.34)
0.07
(0.13)
0.23 *
(0.13)
-0.27 *
(0.14)
-0.15
(0.31)
1413
50

Treatment
Visit (1=Yes)
Endorsed by LSA (1=Yes)
Education module (1=Yes)
High reward (1=Yes)
Village was endorsed (1=Yes) x Visit (1=Yes)
HH Controls
Village dummies
Mean Dependent Variable
Observations
0.162
0.132
0.123
(0.043)*** (0.050)*** (0.051)**
0.064
0.065
(0.036)* (0.036)*
-0.021
-0.023
0.063
(0.037)*
-0.025
(0.030)
0.342
(0.030)
0.338
(0.030)
0.326
(0.030)*** (0.031)*** (0.031)***
0.014
(0.046)
0.062
(0.059)
0.074
(0.060)
No
No
0.268
952
No
Yes
0.268
952
Yes
Yes
0.269
939


Interactions with variables that may influence:
◦ Endorsement
 Does not Know BASIX
◦ High reward
 Log PCE
 Log Wealth
Treatment Interactions
VAR x Endorsed by LSA (1=Yes)
VAR x Education Module (1=Yes)
VAR x High reward (1=Yes)
DK Basix Log Wealth Log PCE
-0.183
0.031
(0.071)*** (0.027)
0.048
(0.063)
0.016
(0.025)
0.01
(0.067)
-0.028
(0.026)
0.038
(0.063)
0.038
(0.058)
-0.114
(0.059)*

Muslim Treatment
Hindu Treatment
Group Treatment
0.00
(0.02)
0.00
(0.02)
0.02
(0.02)
0.00
(0.02)
0.01
(0.02)
0.01
(0.02)
0.00
(0.02)
0.00
(0.02)
0.02
(0.02)
0.00
(0.02)
0.01
(0.02)
0.01
(0.02)
Muslim * Group
Hindu * Group
N
Village FE
2391
No
2391
Yes
2391
No
2391
Yes
•
No detectable effect
•
Sizeable confidence intervals (4 percentage points)

Muslim Treatment
Hindu Treatment
Group Treatment
Muslim * Group
Hindu * Group
N
Village FE
0.04
(0.03)
0.01
(0.03)
0.06 *
(0.03)
-0.09 **
(0.04)
-0.03
(0.05)
2391
No
0.04
(0.03)
0.02
(0.03)
0.06
**
(0.03)
-0.10
**
(0.04)
-0.04
(0.05)
2391
Yes



Some evidence “Group” and neutral effective…
◦ Muslim offsets
90% of sample is Hindu
Coding names to check for same-religion effect
54

All Villages
2003
2004
2005
2006
N. Villages where insurance sold
2
24
12
37
Study Area
Villages where insurance sold in 2004
Share of HHs
Purchasing insurance
N. Villages where
Share of HHs
Purchasing insurance sold insurance
0.15
0.04
0.05
0.03
--
24
11
24
--
0.04
0.06
0.03
Entire State
N. Villages where insurance sold
17
43
422
538
Average number of buyers per village
11.4
7.4
6.6
7.6

Rainfall insurance is still in its infancy and has yet to receive widespread acceptance.


This new insurance product helps people like you and helps you help your neighbors and relatives in case of draught. It is for people whose livelihoods depend on rain.

This new insurance product helps people like you in case of drought. It is for people whose livelihoods depend on rain.
56