Jerry Skees University of Kentucky President, GlobalAgRisk, inc. Co-authors Dr. Barry Barnett and Benjamin Collier

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1 Jerry Skees University of Kentucky President, GlobalAgRisk, inc Co-authors Dr. Barry Barnett and Benjamin Collier Source: UNFCCC, 2007

2 Benefit and Challenge of Offering Agricultural Insurance Household asset portfolio Insurance reduces the variance in livelihoods/returns Allow more risk taking Asymmetric Information Adverse selection/ Hidden information Moral hazard / Hidden actions Correlated Risk Problem

3 Weather Risk and Insurance Pure Risk Frequency Regularity of weather event (drought) Severity Magnitude of the event Using historical data to forecast losses Cognitive Failure Households often fail to plan for infrequent, severe risks Frequency Probability Density Function Central Tend dency Severity High-Frequency, Low-Severity Events Variance around the median Low-Frequency, High-Severity Events Tails of the distribution

4 Pricing Agricultural Insurance Price of Insurance = Cost of the risk Pure risk Ambiguity load Catastrophe load + Administrative costs Controlling adverse selection Monitoring moral hazard Loss adjustment Delivery costs + Cost of Ready Access to Capital Reinsurance Insurer Reserves

5 Multiple Peril Crop Insurance Provides expensive, but comprehensive coverage Covers many types of risk High administrative costs High cost of capital Relies on government subsidies Costs are increased for lower income countries Small farms Poorer access to reinsurance Poor actuarial performance

6 Index Insurance 1. Area-Yield Index Insurance 2. Weather Index Insurance Lower Administrative Costs Low asymmetric information problems No individual loss adjustment Better potential than MPCI in lower income countries Several pilot programs with good progress Need more time to evaluate fully

7 Country Risk Event Index Measure Target User Status Bangladesh Drought Rainfall Smallholder rice farmers Caribbean (CCRIF) China Ethiopia Hurricanes and Indexed data from earthquakes NOAA and USGS Rainfall and storm Low, intermittent rainfall day count In development; pilot launch planned for 2008 Caribbean country governments Implemented in 2007 Smallholder watermelon farmers Drought Rainfall WFP operations in Ethiopia Drought Rainfall Smallholder farmers 2006 pilot Drought Satellite and weather data Implemented June, 2007 in Shanghai only USD 7 million insured for 2006; NGO Implemented in 2007 Honduras Drought Rainfall In development India Drought and flood Rainfall Smallholder farmers Pilot began in 2003 Kazakhstan Drought Rainfall Medium and large farms In development Kenya Mali Drought Drought Malawi Drought Rainfall Mexico Natural disasters impacting smallholder farmers (drought) Major earthquakes Satellite and weather data Satellite and weather data Rainfall, windspeed, and temperature Richter scale readings NGO Implemented in 2007 NGO Implemented in 2007 Groundnut farmers who are members of NASFAM State governments for disaster relief; Supports the FONDEN program Mexican government to support FONDEN Source: Authors (An earlier version published in Barnett, Barrett, and Skees, n.d.) Pilot began in 2005; Pilot began in 2002 Introduced in 2006

8 Country Risk Event Index Measure Target User Status Mexico (Continued) Mongolia Drought affecting livestock Insufficient irrigation supply Large livestock losses due to severe weather Normalized Difference Vegetation Livestock breeders Launched in 2007 Index Reservoir levels Water user groups in the Rio Mayo area Proposed Area livestock mortality rate Nomadic herders Second pilot sales season of pilot completed in 2007, Morocco Drought Rainfall Smallholder farmers Nicaragua Peru Senegal Drought and excess rain during Flooding, torrential rainfall from El Niño Drought Drought No interest from market due to declining trend in rainfall Rainfall Groundnut farmers Launched in 2006 ENSO anomalies in Rural financial institutions Pacific Ocean Area-yield production Cotton farmers index Rainfall and crop Smallholder farmers yield Proposed Proposed Proposed Tanzania Drought Rainfall Smallholder maize farmers Pilot implementation in 2007 Thailand Drought Rainfall Smallholder farmers Pilot implementation in 2007 Ukraine Drought Rainfall Smallholders Implemented in 2005 Vietnam Flooding during rice harvest River level The state agricultural bank and, ultimately, smallholder rice farmers Source: Authors (An earlier version published in Barnett, Barrett, and Skees, n.d.) In development

9 Climate Change and Insurance Consensus that climate change is occurring and will affect farming Increases in temperatures More extreme rainfalls (drought and excess rain) Models do not agree on the extent Poor predictive ability on the regional level Climate change affects the weather risk 1. Changing the norm the central tendency 2. Increasing variability weather variance

10 Figure Source: IPCC, n.d.

11 Changes in the Central Tendency The price of insurance is very sensitive to shifts in the central tendency The majority of weather events occur around the central tendency The central tendency is the foundation for establishing the pure risk

12 Sahel: Shifts in the Central Tendency 800 Sahel data Sahel Semi-arid region below the Sahara Dynamic climate largely due to oceanic oscillations Unlike the Sahel, climate change may lead to more permanent changes

13 Sahel: Hypothetical Insurance Product Insurer pricing insurance in 1962, 1990, Insurer would re-center data around the central tendency

14 Sahel: Rainfall Distribution Using Data from 1900 to 1961 Insurance contract for wheat farmers Indemnities when rain is below 425 mm Central Tendency: 510 mm Payout Threshold: 425 mm Pure Risk: 2% Pure risk will likely result in insurance affordable to households

15 Sahel: Rainfall Distribution Using Data from 1962 to 1989 Central tendency is below payout threshold Insurance is inappropriate in this setting Central Tendency: 328 mm Payout Threshold: 425 mm Pure Risk: 44% Pure risk would make insurance unaffordable for households

16 Sahel: Rainfall Distribution Using Data from 1990 to 2006 Increases in rainfall reduced the weather risk Insurance would be affordable depending on other costs (Delivery, ambiguity loading, etc.) Central Tendency: 456 mm Payout Threshold: 425 mm Pure Risk: 6% Pure risk may result in affordable insurance for households

17 Climate Change Increases Ambiguity and Catastrophe Loads Misestimating the central tendency is very costly Green distribution Insurer forecast in 1962 Blue distribution Actual loss experience of next 30 years Insurers expecting climate change greatly increase ambiguity and catastrophe loads

18 Increasing Variability Increasing variability increases variance of weather risk This will result in more losses and indemnities Variability changes weather risk at the margins 0.60% 0.50% Probability 0.40% 0.30% 0.20% 0.10% Insurance pricing is less sensitive to increasing variability 0.00% Rainfall (mm)

19 Farmers knowledge and decision processes Literature shows farmers optimize farmers adapt farmers are good Bayesians farmers know central tendency on yields cognitive failure sets in for catastrophic events CHALLENGE Communicating information about climate change in a fashion that decision makers can use that information

20 Insurance and Climate Change Insurance can be appropriate in limited contexts of climate change because of effects on the price 1. Pure risk effects Depends on the degree of climate change Depends on the type of change (central tendency and/or variability changes) 2. Ambiguity and Catastrophe load effects Depends on the level of uncertainty regarding future changes (ability to forecast) Price signals can push households to make difficult decisions to adapt

21 Adaptation, Policy Interventions, and Climate Change Households must adapt or experience increasing farm losses 1. Change farming practices 2. Transition out of farming Governments and donors can help Insurance, by itself, is not a means of adaptation So governments must be careful if they choose to support insurance Insurance can be used to facilitate adaptation (e.g., linking insurance, credit, and improved seed varieties in Malawi)

22 Insurance Subsidies and Farmer Production Decisions Policy makers premium subsidies for insurance Insurance subsidies and shifts in the central tendency Farmers make production decisions around central tendency Farmers incorporate insurance subsidies into production decisions This can distort household incentives to adapt taking more risk at the government s expense Experience of developed nations with MPCI Insurance subsidies and increasing variability Farmers are less likely to change production decisions based on increasing variability Creates more opportunities for government and donor support

23 Insurance Facilitating Adaptation 1. Risk Layering Approach Government provides coverage for most extreme risk Cognitive failure prevents incentive distortions Market product for large risk benefits 1. Pure risk reduced Self-Retention Layer 2. Catastrophe loading reduced 3. Ambiguity loading reduced 2. Livelihoods Insurance When possible, insurance products that increase household choices to adapt are preferred Market Risk-Transfer Layer Government Layer

24 Conclusions Government and donor support for insurance should be considered for crowding-in markets Insurance must be considered in the larger context of household adaptation to climate change Because so many needs exist, on-going premium subsidies may carry high opportunity costs Regional uncertainty regarding climate change makes determining where insurance programs will be feasible difficult Improvements in forecasting can lower insurance costs and create new opportunities

Global Learning And Evidence Exchange (GLEE) Climate Smart Agriculture: Africa

Tamuka Magadzire, FEWS NET Scientist, Southern Africa Gideon Galu, FEWS NET Scientist, East Africa tmagadzire@fews.net, ggalu@fews.net Global Learning And Evidence Exchange (GLEE) Climate Smart Agriculture: