Recipient Organization
PENNSYLVANIA STATE UNIVERSITY
208 MUELLER LABORATORY
UNIVERSITY PARK,PA 16802
Performing Department
Agri Economics & Rural Sociol
Non Technical Summary
Ag commodity markets have become highly volatile since the energy crisis. The prices of corn, wheat, and milk set all-time high records in 2008. Ag input costs became increasingly volatile with the per ton price of nitrogen increasing by approximately 300% between 2000 & 2008-09. Because of increased price volatility in ag commodities and manufactured input costs including seed, fertilizer and chemicals, farmers find marketing decisions now have unprecedented impact on bottom-line profit. U.S. "dollar signs" than was typical during the 80's & 90's. Concomitantly, cash flow management has increasingly become a high priority in agriculture. Greater price volatility in commodity and manufactured input prices has increased the incentives for producers to do a (more) careful analysis of both farmer costs of production and alternative marketing options. Ag land costs represent another large financial hurdle for producers, whether land is purchased or leased. The "biofuels boom" of recent years, led by the introduction of corn-based ethanol as a motor fuel, spurred aggressive bidding for ag land. The inclusion of demand factors related to development pressures in highly populated areas of PA can increase the purchase price of 160 acres, several fold higher, than one million dollars. To better contend with the current high-risk setting for agriculture, producers are focusing more intensely on management issues that directly relate to their farm financial situation. The rapid pace of technological advance in agriculture, the potential to grow higher yields with improved seed genetics, the unprecedented increase in land rents and land purchase prices, and the increasing options made available to farmers to market crop and livestock commodities with Futures and Options instruments, combine to create an agricultural industry that is entering previously uncharted financial territory. The proposed research will focus on evaluation of farmer strategies to fix priority production problems on on-going farms and ranches. Production agriculture has increasingly evolved from intense efforts to obtain maximum yields per cow/acre, to viewing production and finances as two-fold priorities in the farm management process. The research will achieve several useful outcomes. At an initial research stage a survey of identified farm problems related to production and finance will be developed that will provide insight into critical areas of farm decision-making. Following a catalog of high priority problems identified by producers in the course of their educational program, an analysis of the associated producer-identified solutions will also be developed. The clustering of high priority problems and respective solutions will enrich statistical analysis to better understand the determinants of production and finance problems in agriculture. A critical outcome will be the quantification of the profit and yield impacts brought about by implementation of problem solving strategies on participant farms.
Animal Health Component
100%
Research Effort Categories
Basic
(N/A)
Applied
100%
Developmental
(N/A)
Goals / Objectives
(1) Identify high-priority production problems on a farm enterprise basis. (2) Identify farm financial constraints that tend to impede the resolution of outstanding production problems. (3) Develop individualized producer Impact Plans with associated financial impacts to solve the identified high-priority problems at enterprise and farm-levels. (4) Determine the monetary success of the implementation of individualized producer Impact Plans with follow-on surveys.
Project Methods
(1) Producer evaluations of high-priority problem areas on their farms will be completed in the process of complying with finance and production training requirements of the USDA/Farm Service Agency. Dr. Hanson's continued leadership of USDA/FSA producer training at state, regional and national levels will facilitate collection of producer information. Dr. Robert Parsons, Farm Management, University of Vermont will collaborate in all project activities. USDA Farm Loan Officers from Pennsylvania and other states will also provide planning and feedback for project steps. Enterprise performance will be evaluated by producers on various measures of timeliness, machinery and labor performance, disease control, and animal comfort. Based on the lowest-rated areas, the high priority problem(s) will be identified. (2) Information indicating technology inadequacy, poor balance sheet solvency, projected cash flow shortfalls, financial ratio warning levels, as well as poor or outdated technology will be collected from producers in order to identify credit and finance barriers to efficiency enhancement. A rating system will be developed to quantify key bottle-neck constraints that have the potential to impede or limit the success of fixing high-priority production problems. (3) Partial budget exercises will identify additional investment, production system changes, yield changes, and cost savings. Technology upgrade benefits will be identified. Impacts in each enterprise will be summarized to estimate whole-farm financial benefits of the individualized Impact Plan. Based on individualized course work completed, producers will further assess resource adequacy for addressing high-priority problems on an enterprise basis. The thought-process explored in the project is a form of adaptative optimization where producers, who are the closest to their production system, complete individualized steps of an evaluation and analysis process that benefits from their own observation and experience, including learning-by-doing or learning-by-making-mistakes. (4) A short two-page mail survey will be sent to project participants after completion of the succeeding 12-month production cycle to determine the achieved benefits of their individualized Impact Plans. The Dillman total design method of follow-on post card reminders and surveys will be incorporated to ensure a high rate of survey completion. Survey results will be statistically modeled with Logistic Regression, Factor Analysis, and Cluster Analysis to identify the determinants of more successful and less successful financial Impact Plans.