The US Government spent $24 billion on farm programmes in 2000. The benefits were distributed through a variety of income-enhancing and risk-reducing policies. For instance, some programmes provided price protection, others a direct subsidy, and others subsidised the purchase of crop insurance.
How
do these programmes individually and collectively reduce agricultural risk? Are these
programmes 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 programmes 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 programmes into the model to determine their impacts. Finally
they combined all the programmes and crop insurance into the model. They compared
the simulation outcomes to determine the impact of the various payment/subsidy mechanisms.
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Study Results
The @RISK simulation model demonstrated that a combination of all government programmes
would raise average farm incomes by almost 45%. Additionally, the programmes would
reduce the economic risks associated with farming by half. Most importantly, the
model allowed researchers to examine how the programmes 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 programmes impact each other and subsidised crop
insurance. According to Dr. Gloy, “Our results indicate that the risk reduction
provided by the standard programmes significantly reduce the value that risk averse
producers derive from crop insurance programmes.” 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 bg49@cornell.edu.
