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Case Studies
Cornell University
Product: @RISK
Application: Agriculture Policy Assessment
University of Buenos Aires
Product: @RISK
Application: Agricultural Investment
Western Australia
Department of Agriculture

Product: NeuralTools
Application: Wool Pricing

@RISK was vital to the simulation model.
Dr. Brent Gloy
Applied Economics and Management
Cornell University
Cornell and Purdue use @RISK to Assess US Agriculture Policy

The US Government spent $24 billion on farm programs in 2000. The benefits were distributed through a variety of income-enhancing and risk-reducing policies. For instance, some programs provided price protection, others a direct subsidy, and others subsidized the purchase of crop insurance.

How do these programs individually and collectively reduce agricultural risk? Are these programs having the desired effects? Is the money helping producers reduce risk and thereby providing a disincentive to purchase crop insurance? And are there better ways to address agricultural risk?

Researchers at Cornell University and Purdue University recently completed a study that assesses the impacts of US farm programs on farm returns and answers some of the above questions. The researchers used Palisade’s @RISK to create a simulation model that illustrates the effects of government policy tools on farm incomes.

The @RISK Simulation Model
To assess the impacts of government policy tools on farmland risk and return the researchers developed an economic model for farm income and expenses based on a representative parcel of land and crop mix. @RISK allowed the researchers to model the uncertainties associated with crop yield and price. After running base-line simulations, the researchers added the individual farm programs into the model to determine their impacts. Finally they combined all the programs and crop insurance into the model. They compared the simulation outcomes to determine the impact of the various payment/subsidy mechanisms.

Study Results
The @RISK simulation model demonstrated that a combination of all government programs would raise average farm incomes by almost 45%. Additionally, the programs would reduce the economic risks associated with farming by half. Most importantly, the model allowed researchers to examine how the programs interact with one another to alter the return distribution.

@RISK’s Contribution
Producers must make decisions regarding cash rental bids, crop mixes, and even farmland purchases based upon expected returns. These decisions are based on the expectations for market prices, yields and costs – all uncertain elements.

Assistant Professor Brent Gloy of Cornell University’s Applied Economics and Management Department was one of the researchers. “@RISK was vital to the simulation model. It allowed us to incorporate uncertainties and run random simulations on the various scenarios.” He adds, “@RISK’s ability to correlate distributions of random variables was essential to the model. Additionally, we used @RISK’s output statistics to compare the various model scenarios.”

Policy Impacts
The study quantifies how government programs impact each other and subsidized crop insurance. According to Dr. Gloy, “Our results indicate that the risk reduction provided by the standard programs significantly reduce the value that risk averse producers derive from crop insurance programs.” He adds, “@RISK was instrumental to the simulation model. It allowed us to incorporate uncertainties and correlations, and to systematically evaluate each of the farm policy tools.”

The study was recently published in the Review of Agricultural Economics. For more information about the study, contact Brent Gloy at 607-255-9822 or .

» Cornell University
» Purdue University

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