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This presentation examines the impact of weather derivatives on water use and risk management in Georgia, specifically focusing on the agricultural sector. The objective is to demonstrate the viability of irrigation as a risk management strategy and to investigate the effect of water pricing policy and financial instruments on production risk and optimal water use. The methodology includes an economic model, crop simulation model, and design of a proposed weather derivative product. The results show the impact of optimal irrigation on producers' certainty equivalent revenue, the effect of potential water pricing policy on producers' irrigation decision, and the cumulative water use for various crops in different counties. The study concludes that irrigation is an important risk management strategy in agricultural production and that weather derivatives could be an attractive tool for reducing water use while increasing farmer welfare.
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Impact of Weather Derivatives on Water Use and Risk Management in Georgia Shanshan Lin (presenting), Jeffrey D. Mullen and Gerrit Hoogenboom Agricultural and Applied Economics The University of Georgia May. 2007 Funded by USDA Special Grant #PA 2005-06007 Flint River Basin TAC
Background • Water scarcity is an emerging issue in Georgia • Agriculture is primary consumptive water user • Need to increase water application efficiency • Technology-based approaches have limitations
Objectives of this Presentation • Demonstrate irrigation is a viable risk management strategy • Examine effect of water pricing policy on optimal irrigation strategies • Investigate the impact of financial instruments on production risk and optimal water use
Methodology • Economic Model (Maximize Expected Utility). • Irrigation application criteria (plant-available water threshold) • Crop simulation model (DSSAT) • Design of the proposed weather derivative product (choice variables: i*, λ, x)
Data • 4 Crops : Corn, Cotton, Peanut, Tomato • 3 Soils : Wagram Sand, Tifton Loam Sand, and Norfolk Loam Sand • 3 Locations : Mitchell, Miller, and Lee Counties • Weather Data : Daily Solar Radiation, Temp. (Max & Min), and Precipitation • Irrigation Cost per Application : Fixed and Variable
Results • (1) Impact of the optimal irrigation on producers’ Certainty Equivalent Revenue
(2) Impact of Potential Water Pricing Policy on producers’ Irrigation Decision and Certainty Equivalent Revenue
(3)Impact of Weather Derivative on Water Use • Cumulative water use for corn, cotton, peanut, and tomato in Mitchell, Miller, and Lee
Impact of Weather Derivative on Farmer Welfare • Regardless of risk aversion, better off • even though the premium included a 10% proportional load. • One exception in Lee County • the decreases in CER are very small.
Conclusion • Irrigation is as an important risk management strategy in agricultural production. • The proposed water pricing policy may have limited effect on irrigation water use. • Even when precipitation derivative is offered
Conclusions (Cont.) • A precipitation insurance contract could be an attractive risk management tool for a variety of crop producers in Georgia • May reduce water use while increasing farmer welfare.
Thank you • Questions?
Economic ModelDecision Criteria in the Presence of Risk • Maximize Expected Utility • Utility curve • Risk Averse: concave utility • Risk Neutral: linear utility • Risk aversion : the degree of concavity of the utility function • Decreasing absolute risk aversion-
Presentation Outline • Objective : develop a dynamic model that conceptualizes irrigation and financial decisions of farmers who face weather uncertainty and vary in their risk preferences. • Methodology - Expected Utility Model - Crop Growth Simulation Model - Weather Derivative Design • Results and Discussions
Why irrigation in a humid area • Economic benefit to region (Makes land much more productive ) • Allows year-round production • Offset the impact of rainfall variability on crop yield and to reduce the risk associated with weather variability.
Weather data Soil data Crop Property data Crop Management data Precipitation data Weather Derivative Design Plant simulation model Payoff: f Premium: π NRwithout weather derivative Economic Model
CER • U(CER)=EU(R) • U(R)=(R^(1-r))/(1-r) • U(CER)=(CER^(1-r))/(1-r)