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Financing Agriculture under
Climatic Risk:
Lessons from Crop Insurance
Scheme in Malawi
Ajayi et al
Email : Ajayi@cta.int
Outline
•Why weather-based crop insurance in Malawi?
•Design and implementation
•Outcome of the insurance scheme
•Can crop insurance improve finance for agriculture
in Africa?- potential opportunities and pitfalls
Context
•Over 70% of population engaged in agriculture
•Low productivity: gap between potential vs actual crop
yield, inputs use very low
•Agric is dependent almost entirely on single rainfall
regime per season
•Poor access to finance for agriculture, perceived as a risky
venture
•To become worse with due to climatic uncertainties
Fig 1: Annual rainfall from Makoka and Kasungu weather stations, Malawi
1983-2007
0
200
400
600
800
1000
1200
1400
1600
1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Kasungu Makoka
Year
Annualrainfall(mm)
Table 1: Frequency of crop failure reported by farmers
in Shire Basin over a five-year period
Frequency of
crop failure
Proportion of farmers (%)
Male Female All
None 38 35 38
Once 9 7 9
Twice 22 20 21
Thrice 24 36 27
4 or more 7 2 5
Total 100 100 100
Why & when?
Objective:
•Help farmers to access loans and improved farm inputs,
•Insulates finance institutions and farmers from the
vagaries of weather
•When- began in 2005/2006 season
•Crops insured- groundnut and maize (based on different criteria)
Partnerships
Partner Role
Farmers’ organization
(main beneficiaries)
 Organizes several smallholder farmers
together
Government technical
deptartments
 Establish a “Weather Index” for crops,
to know when insurance payment is
triggered
Insurance company
 Provides insurance cover for the farm
inputs
Banks & finance
corporation
 Provides funds to purchase farm inputs
for farmers
Table 2: Outcome-
loan secured through the scheme insurance in pilot
districts
Agric season District
No of farm
families
Total loan (US$)
Year 1
Lilongwe North 79 3,316
Kasungu 223 1,175
Nkhotakota 580 23,345
Mchinji 0 0
Total Year1 882 27,860
Year 2
Lilongwe North 494 61,255
Kasungu 419 13,766
Nkhotakota 122 4,197
Mchinji 672 38,218
Total year2 1,707 117,436
Two-Year Total 2,589 145,296
Source: NASFAM
Crop insurance-
to be or not to be?
•Quality of weather data & weather stations
•Extent of coverage of insurance-
– drought or/and flood?
– absolute rainfall or temporal distribution?
•Twinning food crops and cash crops for same household
•The dilemma of maize in crop insurance schemes
•Upfront part-payment of insurance premiums
•Information gap & sensitization on how insurance works
Thank you
Merci

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Financing Agriculture under Climatic Risk: Lessons from Crop Insurance Scheme in Malawi

  • 1. Financing Agriculture under Climatic Risk: Lessons from Crop Insurance Scheme in Malawi Ajayi et al Email : Ajayi@cta.int
  • 2. Outline •Why weather-based crop insurance in Malawi? •Design and implementation •Outcome of the insurance scheme •Can crop insurance improve finance for agriculture in Africa?- potential opportunities and pitfalls
  • 3. Context •Over 70% of population engaged in agriculture •Low productivity: gap between potential vs actual crop yield, inputs use very low •Agric is dependent almost entirely on single rainfall regime per season •Poor access to finance for agriculture, perceived as a risky venture •To become worse with due to climatic uncertainties
  • 4. Fig 1: Annual rainfall from Makoka and Kasungu weather stations, Malawi 1983-2007 0 200 400 600 800 1000 1200 1400 1600 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Kasungu Makoka Year Annualrainfall(mm)
  • 5. Table 1: Frequency of crop failure reported by farmers in Shire Basin over a five-year period Frequency of crop failure Proportion of farmers (%) Male Female All None 38 35 38 Once 9 7 9 Twice 22 20 21 Thrice 24 36 27 4 or more 7 2 5 Total 100 100 100
  • 6. Why & when? Objective: •Help farmers to access loans and improved farm inputs, •Insulates finance institutions and farmers from the vagaries of weather •When- began in 2005/2006 season •Crops insured- groundnut and maize (based on different criteria)
  • 7. Partnerships Partner Role Farmers’ organization (main beneficiaries)  Organizes several smallholder farmers together Government technical deptartments  Establish a “Weather Index” for crops, to know when insurance payment is triggered Insurance company  Provides insurance cover for the farm inputs Banks & finance corporation  Provides funds to purchase farm inputs for farmers
  • 8. Table 2: Outcome- loan secured through the scheme insurance in pilot districts Agric season District No of farm families Total loan (US$) Year 1 Lilongwe North 79 3,316 Kasungu 223 1,175 Nkhotakota 580 23,345 Mchinji 0 0 Total Year1 882 27,860 Year 2 Lilongwe North 494 61,255 Kasungu 419 13,766 Nkhotakota 122 4,197 Mchinji 672 38,218 Total year2 1,707 117,436 Two-Year Total 2,589 145,296 Source: NASFAM
  • 9. Crop insurance- to be or not to be? •Quality of weather data & weather stations •Extent of coverage of insurance- – drought or/and flood? – absolute rainfall or temporal distribution? •Twinning food crops and cash crops for same household •The dilemma of maize in crop insurance schemes •Upfront part-payment of insurance premiums •Information gap & sensitization on how insurance works