A new study by agricultural economics experts from Texas A&M AgriLife and Virginia Tech makes a strong case for using historical weather information in crop insurance programs for even more accurate policy pricing.
About crop insurance rates
Crop insurance is the most expensive agricultural policy in the U.S., with over $110 billion in liability in 2020. Agricultural producers and others purchase crop insurance to protect against either the loss of crops due to natural disasters or loss of revenue due to declines in the prices of agricultural commodities.
In the U.S. federal crop insurance program, a fundamental principle in the design of crop insurance policies is that they should be actuarially fair, meaning the expected indemnity under the policy should be equal to the premium.
“Achieving this objective requires accurate pricing of policies, and accurate pricing depends on accurate modeling of all the variables causing losses,” Liu said.
Traditionally, he said, known or fixed historical yield data or historical loss cost data have estimated yields or loss costs.
“For example, soil information is fixed or known at the time the policy is sold,” he said. “Incorporating this type of known information is conceptually similar to dealing with time trends and other fixed determinants of yields or loss costs.”
Liu said They then use loss probabilities and expected losses to calculate premiums. Many rating procedures exclusively use fixed or deterministic variables in determining expected losses.
“But it is widely recognized that a large part of the observed variation in yields and loss costs is due to changes in weather and other variables,” Liu said. “Current loss variables used in determining crop insurance rates can be amended to incorporate other applicable variables like the weather.”
Stochastic variables, like the weather, have a random probability distribution or pattern that may be analyzed statistically but not be precisely predicted. Unlike fixed variables, stochastic variables are unknown when they sell the policy.
“Including these variables, most particularly incorporating long-term weather data, would allow for a more thorough and accurate estimation of the distribution over time,” Liu said.
The case for using historical weather information
Liu noted that the federal crop insurance program they have already incorporated historical weather information through after-the-event rate adjustments. He also said that reinsurers frequently use weather information when evaluating crop insurance portfolios and risk.