1. Farmer Risk Perceptions and Demand for Risk Management Education Keith H. Coble, Mississippi State University Thomas O. Knight, Texas A&M University George F. Patrick, Purdue University Alan E. Baquet, University of Nebraska www.agecon.msstate.edu/riskedu

2. Supportive Research to Provide a Baseline of Agricultural Risk Management Education Needs Shed light on producer risk management perceptions –How producers perceive the risk they face and manage those risks? –How they want risk management education delivered? –What factors, such as size, age, and education, influence producers’ perceptions? –How do perceptions vary by region and commodity? Investigate agricultural lenders’ and extension educators’ perceptions and understanding of alternative risk management tools and strategies.

3. Activities to Date Surveys of: –Row crop producers A preliminary summary of data (http://www.agecon.msstate.edu/riskedu/) An analysis of policy preferences The demand for risk management education –Beef cattle producers –Hog producers –Limited-resource producers

4. Crop Producer Survey Mail survey in four states Stratified by gross revenue Crops emphasized –Indiana: Soybeans and Corn –Mississippi: Cotton and Soybeans –Nebraska: Soybeans and Corn –Texas: Cotton and Sorghum 1812 useable responses – approximately 30% response rate

5. Crop Producer Survey - Results Perceptions of risks and risk management tools

6. Assessment of Risks Confronting the Farm

7. Rated Effectiveness of Risk Management Strategies

8. Farmer Interest and Demand for Risk Management Education Participation in risk management educational activities Sources of risk management information Comfort in using risk management tools Desired content and delivery of future risk education

9. Participation in Educational Programs During the Past Three Years

10. Average Hours of Risk Management Training During the Past Three Years

11. Percent of Risk Management Training During the Past Three Years From Extension

12. Comfort in Using Risk Management Tools

13. Interest in Additional Risk Management Education

14. Rating of Alternative Learning Methods

15. The Research Question -- Probit models of expressed ‘strong interest’ in additional training in the use of 5 risk management practices? –Forward contracting-Futures and options –Crop yield insurance-Crop revenue insurance –Financial management Dependent variable –“How would you rate your interest in obtaining additional information or education on each of the following risk management tools?” –Rating scale 1-5 where 1 indicates “Low Interest” and 5 indicates “High Interest” –Dependent variable = 1 for ratings of 4 or 5

16. Explanatory Variables Hours of prior training Prior use of practice Cropland acres Off farm income Percent borrowed Operator age College education High potential effect of price risk High potential effect of yield risk Practice recommended by lender Willingness to accept lower price to avoid risk Percent of crop acres in corn / cotton / sorghum / soybeans /wheat

17. Descriptive Statistics

19. Marginal Effect Results From Probit models

20. Summary of Results Those individuals who had attended average hours of training in the past three years were about 12% more likely to express interest in additional training in each of the areas except forward pricing. Persons who had used a practice in the past two or three years were about 10% to 12% more likely to express interest in additional training. Farmers with higher debt-to-asset ratios expressed greater interest in all five areas.

21. Summary of Results Operator age had a negative effect on interest in training on forward contracting, futures and options, and financial management. College educated respondents expressed greater interest in training on futures and options, revenue insurance, and financial management. Persons who perceived themselves as being subject to a high level of price risk had greater interest in training in all areas.

22. Summary of Results Persons who perceived themselves as subject to a high level of yield risk had greater interest in training on yield insurance and revenue insurance. Individuals whose lender advocated the use of a risk management practice were about 9% to 13% more likely to express interest in training. Persons willing to accept a lower price to avoid price risk were about 5% to 11% more likely to express interest in training in areas other than forward contracting.

23. What does this mean for risk management education (RME)? Results confirm that producers view price and yield variability as having the highest potentials to affect their incomes. Other sources of risk are less important - less than 4 but greater than 3 on scale. Being low-cost producer, maintaining financial reserves, and enterprise diversification were rated above forward pricing and crop insurance for effectiveness in reducing risk.

24. Implications for RME Only 35.0% of producers indicated a willingness to take a lower price to reduce price risk. 51.3% disagreed with statement their primary marketing goal was to reduce risks rather than raise net sales price. 33.6% of cotton producers and 36.8% of corn producers would not give up ANY yield to avoid yield variability.

25. Implications for RME Many producers’ perceptions of risk management strategies apparently do not reflect the risk/reward trade-off that underlies most of risk management Phase 1 educational programs will need to help those producers understand the fundamentals of risk management. Only after producers understand fundamentals can more specific programs be effective.

26. Implications for RME Costs of risk management is not a popular lesson with many producers. Programs on reducing price risks are not likely to be popular if producers think they “can beat the market.” Helps explain some of the lack of success in past efforts. Results suggest that farm magazines are likely to work better than the Internet for this message.

27. Implications for RME Large-scale producers have greater interest in risk management information and are more comfortable using tools than small-scale producers Extension has worked with both large and small- scale producers, but has not provided the majority of educational training in risk management. Needs of producers of different sizes are likely to be different. This challenges us to be creative in program design and delivery

28. Implications for RME Probit analyses suggest that the most likely customer for tomorrow’s risk management education program is the current or past customer. Challenge to broaden the customer base –New tools like AgRisk? –Partnering with private sector in delivery? –Partnering in development and delivery?