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Flex Leases Land Bubble and Profitability Henderson County January 12, 2011

Flex Leases Land Bubble and Profitability Henderson County January 12, 2011. Greg Halich 859-257-8841 Greg.Halich@uky.edu http://www.ca.uky.edu/agecon/index.php?p=169. Dept. Agricultural Economics University of Kentucky December, 2010. Areas Covered Today. Land Bubble

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Flex Leases Land Bubble and Profitability Henderson County January 12, 2011

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  1. Flex LeasesLand Bubble and ProfitabilityHenderson CountyJanuary 12, 2011 Greg Halich 859-257-8841 Greg.Halich@uky.edu http://www.ca.uky.edu/agecon/index.php?p=169 Dept. Agricultural Economics University of Kentucky December, 2010.

  2. Areas Covered Today • Land Bubble • Profitability by Soil Type • Communication • Leasing Game • Flex Leases

  3. Hypothetical Story Central Kentucky: • Profit • Knowledge • Competition • Greed

  4. True or False Cropland Prices drive Cash Rents? False!!!

  5. What Drives Cropland Prices? Investor – Expected Land Rents Farmer – Expected Profits

  6. What Is the Relationship Between Land Rents and Profits? Profits Drive Land Rents: • Higher the profit, the more that a farmer can bid for land rent. • In long-run, most of profit will be bid into land rents.

  7. What About Land Appreciation? Yes, but… Except for Development Potential → Future land rents and/or profits determine appreciation.

  8. Formula to Estimate Max. Cropland Value Investor Perspective: Land Value = Land Rent – Costs Interest Rate

  9. Investor Perspective Example $220/acre Expected Land Rent $20/acre Expected Costs 5% Interest Rate Land Value = $220 – $20 = $4000 .05

  10. Formula to Estimate Max. Cropland Value Farmer Perspective: Land Value = Profit per Acre Interest Rate

  11. Farmers Perspective Example $300/acre Expected Profit 5% Interest Rate Land Value = $300 = $6000 .05

  12. How is Interest Rate Determined? If self-financed: → Required return on investment. If Borrowing: → Rate of the loan.

  13. Effect of Interest Rate As rate decreases: → Land value increases.

  14. What Interest Rate to Use? Returns on other investments → Lot of risk out there. → Farmland seems like safe investment.

  15. Land Rent vs. Profit Approach Short-run: Farmers will have competitive advantage over investors in areas with less then perfect bidding. Long-run: Land rent and profit will be very close.

  16. Ohio Valley Dynamics Most Competitive Land Rents: • $200-$275 last year. • $300+ this fall. What land prices will this support?

  17. Projected Profitability 2012 • Commodity prices down from late summer high. • Determine if land rents can be supported in 2012 at current commodity levels. • Evaluate range of commodity prices.

  18. Critical Budget Assumptions Does not include land rent. Includes “non-cash” costs (e.g. depreciation/overhead, unpaid labor). P and K application at removal rate. Grain trucked directly to elevator.

  19. Agronomic Assumptions

  20. Budget Assumptions

  21. Land Bubble? • 1970’s vs. 2010’s → What are differences? → Let’s look at land values.

  22. Land Bubble? Main difference today vs. 1970’s? Politically imposed demand for grain. → Ethanol used 40% of corn crop 2011. → Political issue, not market issue.

  23. Summary Current farmland values not unreasonable at current profitability levels. However price levels will hinge on ethanol policy. How will market react to: → 40% of corn crop dumped on market. → Market response to higher profitability.

  24. Land Rents by Soil Productivity Question: If 150 bu ground rents for $200, how much would you pay for 125 bu corn ground? • We will look at partial budgets to help answer this. Note: Base rents are purely hypothetical.

  25. Land Rents by Soil Productivity If productivity increases 20% → Land Rent increases by 20%. Does this seem fair?

  26. Land Rents by Soil Productivity Productivity Change of 25 bu corn: • $109/acre net corn. • $64/acre net soybeans. • $86/acre net 50-50 rotation. Note: Based on assumptions previous two slides.

  27. Land Rents by Soil Productivity Summary: • 17% dec. yield → 43-50% dec. rent. • Not linear relationship. • Better ground may be underpriced. • Poorer ground may be overpriced.

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