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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 . Based on results from :
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CMF-CAB Conference on Microfinance, January 16-17th “Optimizing Microfinance Distribution Channels” Results from Rainfall Insurance Studies in Gujarat and Andhra Pradesh Raghabendra Chattopadhyay Indian Institute of Management -Calcutta
Based on results from : “Barriers to Household Risk Management: Evidence from India” working paper
This paper: • 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
Motivation • 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.
What do we do? • 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
Research Questions • What are the determinants of adoption? • What is the impact of insurance on investment, risk-sharing and consumption?
Outline of Talk • Product Description • Sample and Summary Statistics • Patterns of Take-up • Experimental Design • Andhra Pradesh • Gujarat • Results • Conclusions
Product Description • 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
Product Description • 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
Product Description • 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
Product Description • 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
Sampling • 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
Sampling • 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
Summary Statistics • AP sample more likely to own land and have higher landholdings • SEWA intentionally markets to landless laborers
Summary Statistics • Gujarat is a richer state than AP • Yet by asset measure, AP sample seems richer
Summary Statistics • 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?
Experiments • 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
AP Results • 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
AP Results • Endorsement • Increases take-up by six percentage points • Not a matter of transactions costs as BASIX representative is available on weekly basis in village
AP results • 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.
AP Results • 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
Gujarat Design • 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
Gujarat Design: Flyers • 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
Gujarat Design • Video players, $100/each • Allows more control of message
Gujarat Design: Video • 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
Gujarat Design: Video • 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?
Gujarat Design: Video • Price Variation: For all video treatments • Randomly assigned in advance • 40% Rs. 5 • 40% Rs. 15 • 20% Rs. 30
Gujarat Results • Video Treatment • Framing main effects statistically indistinguishable from zero, but bounds non-trivial • 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%)
Gujarat Results: Video interactions • 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 • 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
Results on Investment Behavior • 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
Summary Factor Andhra Pradesh Gujarat Reputation of Seller Yes -- Price (20% discount) -- Yes Liquidity (50% of premium) Yes -- Education No -- Salience (House Visit) Yes Yes (non-exp) Subtle Psychological Cues -- Some • Models finding support: • Rational • Credit constraints • Trust
Conclusions • 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
Future Directions of Study • Crop-specific insurance policies (cotton, rice) • Incorporate rainfall variation over monsoon • Have policies written at a taluka/tehsil-level • Use agri-loans as a distribution channel
Appendix • 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
Motivation • 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 2nd trigger (corresponds to crop failure) 1st trigger Product Description • Total payout = sum of payouts across three phases. • Insurance premium based on actuarial value + 25% admin fee + tax.
Sampling in AP Radius of circle = 20km
Religion cue • 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.
Summary Statistics • AP households less likely to be minority
Speculation • 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
Gujarat Design 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)