Use of Farm-Level Survey Data in the Development of CARD Production Budgets

1. Use of Farm-Level Survey Data in the Development of CARD Production Budgets Luba Kurkalova, Todd Campbell, Phil Gassman, Uwe A. Schneider, and Chris Burkart CARD, Iowa State University Presented at 2002 AAEA Meeting Long Beach, CA, July 2002

2. Research Interest • Policy studies to do Integrated Environmental and Economic Analysis • 12 states, National Resource Inventory (NRI)

3. Data Needs • Input to economic models: costs of production (PROCOST) • Inputs to bio-physical simulation models (EPIC, CENTURY, and SWAT) • List of practices (operations) • Tillage operations: how many passes, when, what implements, tractor characteristics • Fertilizer applications: how many applications, when, how, rate • Etc.

4. CPS: Fertilizercorn after soybeansconventional till Number of applications 0 1 2 3 4 63% 2% 63% 29% 5% 0% 59% 5% 24% 59% 10% 1% 42% 0% 12% 29% 42% 15%

5. CPS: Machinerycorn after soybeans, Iowaconventional till 11.8% Chisel plow Fall Field cultivator Spring Planter Tandem disc Spring Tandem disc Spring Planter 8.9% Chisel plow Fall Field cultivator Spring Field cultivator Spring Planter 2.9% Chisel plow Fall Tandem disc Spring Field cultivator Spring Planter 2.5% Tandem disc Spring Tandem disc Spring Field cultivator Spring Planter 2.5%

6. Representative practice vs. whole sample • Cost of most frequently used practice (mode) • $204.6 • Cost via whole sample • Mean cost: $243.0 • Standard deviation of cost: $24.8

7. Development of budgets for large regions • Representative practice approach • Potential biases • Disaggregated approach • Sort CPS practices by state, crop, previous crop, tillage, and irrigation • Sort NRI points by the same criteria • Assign each NRI point a CPS practice from the corresponding group using weighted random draw

8. Disaggregated Approach NRI by state, crop, prev. crop, tillage, and irrig. CPS CPS practices by state, crop, prev. crop, tillage, and irrig. Costs and physical simulation model inputs at every NRI point Technical coeff., planting dates, etc. Soils, weather prices, cost coefficients, etc.

9. Conclusions and discussion • The disaggregated approach allows retention of observed variability of farming practices • To improve • Finer geographic identifiers • ARMS data, 1997 and later