Insuring against the weather using traditional groups


Published on

  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Insuring against the weather using traditional groups

  1. 1. Insuring against the weather:Using traditional groups to promote index-based weather insurance in Ethiopia Guush Berhane, Daniel Clarke, Stefan Dercon, Ruth Vargas Hill and Alemayehu Seyoum Taffesse IFPRI ESSP-II Improved evidence towards better food and agricultural policies in Ethiopia; November 02, 2012 Hilton Hotel, Addis Ababa 1
  2. 2. Introduction Weather risk remains a major challenge to farming in the arid and semi-arid areas of the tropics; With ever changing climatic conditions, agriculture has become increasingly uncertain business! Drought explains largest share of income variability in Ethiopia  Household level = 60 – 75%  National - strong GDP and rainfall variability 2
  3. 3. Introduction Thin insurance possibilities. Informal insurance hampered by risks correlated across households and villages; Index-based weather insurance offers new possibilities; Several experimenations, including in Ethiopia, but demand remains invariably low; chances of scalling up stiil very low! Basis-risk – a key challenge Efforts to mitigate basis risk are so far very limited; 3
  4. 4. Introduction Question – design simple, flexible, and affordable generic insurance policy that mitigates basis risk?  Reduce basis risk by increasing side-payments?  Institutionalization of pre-defined sharing rules needed?  Would such insurance design work? Welfare effects?  If so, what are the mechanism through which this would work? Can we achieve the dual goal of ‘harnessing groups to mitigate basis risk’ and ‘make them more resilient to correlated risks’? Approach - randomized field experiment 4
  5. 5. Weather index pilot in Ethiopia Long run pilot—looking at group institutions takes time  first year in 2011, second year in 2012, continues …! 57 Kebeles selected around 3 weather stations in Oromia region of Ethiopia – Shashemene, Dodota and Tibe; Primary interest is to target risk-sharing group, so we designed the pilot such that we can evaluate effects of our intervetions! 5
  6. 6. Pilot Design 57 Kebeles (110 Villages) TREATMENT CONTROL (60 villages) (50 villages) GROUP INDIVIDUAL (35 villages) (25 villages) MANDATED NON-MANDATED (18 villages) (17 villages) 6
  7. 7. Mandated sharing-rules What did we mandate?  Discuss and set sharing rules (or bylaws) … key features  Regular savings to a common pot;  Contribute 10% of any insurance payout in this group to this pot;  Disburse this pot to members that experience idiosyncratic basis risk, as loan at zero-interest; 7
  8. 8. Provision of savings Money was contributed (to the pot) by project as “savings” with the aim of  Examine disbursements and promote trust!  Help initiate discussions on formulation of (pre-defined) additional sharing-rules Disbursed to 800 Birr to both iddir villages (mandated and non- mandated) and individual villages (16 individuals, 50 Birr each). 8
  9. 9. Insurance marketing Village & iddir level meetings, trainings, … 9
  10. 10. Insurance marketing Games demonstrating chances of rain failure 10
  11. 11.  Innovative Field Staff …. 11
  12. 12. Insurance marketing Very few early season (May, June and July) polices were sold in 2011! Discounts offered for late season (September/Meskerem) in 2011 & for all season in 2012 policies  Free insurance in Dodota and Bako Tibe;  Price discounts in Shashemene: 40%, 60%, and 80% discounts randomly allocated across villages; 12
  13. 13. Insurance sales …2011 296 policies were sold in Shashemene (134 individuals and 435 iddir members), about 13% of households; 13
  14. 14. Payouts …2011 September rains were poor in Shashemene – index triggered a payout! Insurance payout was made at the end of October in Shashemene. “Savings” payouts were also made at the end of October in all three sites. 14
  15. 15. Survey & data Baseline survey: February –March 2011:  1760 households in 110 villages (16 households per village); Follow up survey I: December 2011; Follow up survey II: February-March 2012; Follow up survey III: February-March 2013; 15
  16. 16. Baseline characteristics … households High incidence of drought:  51% experienced drought shock in the last three years; Very little knowledge of insurance:  10% had heard about traditional indemnity (car, life or health) insurance; High initial interest in index-type insurance:  87% were interested in a weather indexed insurance policy described to them in the survey; Indications of huge basis risk:  only 32% thought rainfall measured at the nearest weather station can accurately measure rainfall on their plots; 16
  17. 17. Baseline characteristics … Iddirs Key features of Iddirs:  Very prevalent in those areas (as in many parts of Ethiopia)  92% households belong to 1-5 iddirs; only 5% did not belong to an iddir  They are limited to ‘the village ‘…  80% span within the village 17
  18. 18. Data analysis Compare outcomes between the control and the following treatment groups:  Individual and iddir  Mandated and non-mandated iddirs Run a simple ANCOVA for outcome variables of interest with baseline data; 18
  19. 19. Results Effects on insurance take-up:  Interventions increased insurance purchases both in individual and mandated iddir villages, but no statistical difference in amount purchase between the two! Effects on access to loans and grants:  Insurance improved access to grants/loans to cover crop loss (crowding in of risk-sharing);  Insurance increased perceived ability to finance emergencies, but not business ventures;  Result is driven by changes in the iddir villages, particularly changes in the mandated ones; 19
  20. 20. Results Impact on welfare: Only moderate effects in the short-term Where there were payouts (Shashemene):  Those in mandated villages more likely to purchase household durables (clothing, footwear and mobile phones) in the 4-5 months following payouts than those in control villages.  Livestock ownership increased in mandated villages  No effect on food consumption; Where there were no payouts (non-Shashemene sites):  No effect on food consumption or durable purchases; 20
  21. 21. Conclusions & implications Limits to formal and informal insurances to mitigate weather risk  Index-based insurance unable to meet individual specific risks  Iddirs unable to meet risks correlated across households and villages! We find evidence that there is high potential to dealing with this problem by integrating both:  Formal insurance addressing correlated risks via the index;  informal insurance addressing individual specific risks through strengthening of existing iddir rules; promoting more loans & transfers.  Iddirs as retail outlets – reduce cost,& promote trust 21
  22. 22. Conclusions & implications We find evidence that a product that integrates both  Increases household welfare (purchase of household durables) However, for all these to work, institutionalization of new sharing rules is required! Policy implications:  Immense potential of ‘traditional groups’ for scaling up of weather related insurance;  Pool iddirs beyond the village, possibily bring them under one national – risk pooling - umbrella!  Among others, favorable national legal framework, one that allows including international re-insurance is needed! 22
  23. 23. What next …, 2012, & beyond? Continued with the same design, but Add an innovative feature to the index – gap insurance – A lot of optimism last Meher season (2012) –  1537 policies sold in Shashemene (where payouts were made in 2011)  Payouts made in Dodota & Shashemen for May 2012 Enthusiasm of our partner (BG) MFI for scalling up as a business model, also linked to its saving & credit products 23
  24. 24. Thank You 24