1 Asking the right questions Weather Insurance experiments February 21, 2009

2 Asking the right questions Problem statement –Farmers, both who own land and wage laborers, are exposed to vagaries of weather (in particular rainfall) during the cropping season. Directly affects yield and income. Interventions: think about what is feasible, costs and benefits –Alternate livelihood opportunities –Infrastructure: better irrigation facilities –Insure against yield risks (crop/rainfall-index)

3 What do we know? 60% of land holdings in India are rain-fed and 90% of crop losses can be attributed to weather This survey: 80% of the respondents cite weather shocks as a major risk faced by the household Rainfall-index insurance –No adverse selection –No moral hazard –Easier to price –Faster claim settlement –Divisible – unit purchase – anyone can buy –BUT, we do need historical data to be able to price the policy and weather stations (basis risk). –Catastrophic insurance: Pays 1 in 9 years, maximum payout was triggered once in 1 in 100 years –Indian monsoon is an aggregate local shock but not correlated with global financial markets – re-insurance market is still under-developed

4 Asking the right questions Primary research question: What is the impact of providing rainfall insurance on income and consumption of households? Proximate effect: What is the impact of providing rainfall insurance on investment decisions of households? Proximate questions: Which factors impact the take-up of rainfall insurance? –Are farmers liquidity/credit constrained? (ability to pay premium) –Do farmers understand insurance products? (financial literacy) –How does the design of the policy affect demand? (price & willingness to pay, risk-seeking behavior) –Role of trust and influence (Africa – insecticide take-up experiments) –Finally, what marketing mechanisms can increase take-up? (delivery channel, information provided)

5 Research design 100 villages across Anand, Ahmedabad and Patan districts where SEWA had presence; rainfall station less than 30 kms distance. Currently 50 Treatment villages and 50 Control villages. 15 households interviewed in each village Randomly sampled 5 households from SEWA members list (trust) Local SEWA employee identified an additional 5 households as being likely to purchase insurance (investment decisions) Randomly selected 5 households from SEWA list who had a positive bank balance (credit constraints) Simple marketing experiments –Probability of payouts –Positive and negative framing – insurance purchase Policy developed jointly by SEWA, insurer and researchers – Kharif season

6 Research design: policy details First year (2006) –By ICICI Lombard: deficit cover –Policy start date when 50 mm of accumulated rainfall or latest by June 25 th 2006 –Divided into 3 phases: sowing, growing and harvesting –Each phase pays out separately – Rs 5 for each mm of shortfall. –Two of the districts – high and low rainfall covers –Total maximum payout Rs 1500; premium about Rs 150

7 Research design Second year (2007) –20 villages added to the treatment. –Marketing experiments became more complex Individual versus group Religion Video treatment (payouts, insurance framing, SEWA brand, peer/authority figure) –By IFFKO-TOKIO: policy made less complicated – no phases; but paid in case of both excess and deficit rainfall

8 Questionnaire design What is the impact of providing rainfall insurance on income and assets of households? –Assets – purchase and sale –Income and consumption level; expectation of income –Savings and borrowing –Essentially, think of all income and consumption smoothing mechanisms employed What is the impact of providing weather insurance on investment decisions of households? –Agricultural land use: investment in high yield varieties and fertilizers, irrigation facilities, etc. –Crop diversification and crop switching –Risk-seeking behavior (choice of lotteries) –Time discounting (hypothetical questions about payouts) –Catastrophic events

9 Questionnaire design Product specific questions –Do they have any other type of insurance? –Financial literacy level (math skills, understanding of interest rates) –Understanding of rainfall measurement units (mm)

10 Some statistics Gujarat Household size5.94 Scheduled castes35% Agriculture as a source of income72% Agricultural labour as primary source of income42% Own land48% Amount of land owned (bigha =.5 acres)13.0 Number of plots1.79 HH had credit in May 2006 (1=Yes)89.8% Assets: Tractor2.21% Assets: Thresher0.80% Assets: Bicycle32.24% Assets: Electronic appliances64.62%

11 Summary statistics Average scoresGujarat Financial literacy0.34 Math questions0.62 Probability questions0.72 Insurance questions0.68 Risk aversion0.46

12 Some statistics

13 Summary statistics Predictors of take-up –Risk aversion –Skill with insurance –Muslim households are more likely to purchase insurance (?) –Video treatment (29.3% purchase) and flyer (25.9% purchase). Remember – difference in media as well as the fact that flyer treatment group already exposed to insurance –Expectation of weather: not correlated –SEWA brand, peer endorsement, payout framing, positive/negative framing: not correlated

14 Future plans Forced payouts in the last year – encourage take-up One unit puzzle: test price sensitivity and liquidity constraints more –Framing issues –Discount related to # of units purchased Crop specific policies Reduce the basis risk and increase probability of payouts –Historical data at block-level not available; policy designed using district-level data but payouts will be based on rainfall stations in the block