Interactions Between the Atmospheric Sciences and Insurers in the United States

Changnon, Stanley A.; Fosse, Erik; Lecomte, Eugene L.

doi:10.1007/978-94-015-9265-9_7

Cited by 21 publications

(18 citation statements)

References 25 publications

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“…In sum, the results of this study agree with the spirit of Changnon et al (1999), who suggest that climate information can help farmers and insurers mitigate losses related to climate variability. Climate information can help farmers to select crop insurance that maximizes their net returns.…”

Section: Discussionsupporting

confidence: 89%

Optimal Crop Insurance Under Climate Variability: Contrasting Insurer and Farmer Interests

Cabrera¹,

Solís²,

Letson³

2009

Transactions of the ASABE

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ABSTRACT. This study illustrates the potential synergies and conflicts of interest between farmers and insurers in the selectionlimatic variability significantly affects agricultural production, profitability, and risk (Hansen, 2002;Chen and Chang, 2005). Several studies have shown that agricultural management has been improved during the last years based on the prediction of seasonal climate (Baigorria et al., 2008;Podestá et al., 2002;Nnaji, 2001). Predictability of seasonal climate variations can help in reducing farm risk by tailoring agricultural management strategies to mitigate the impacts of adverse conditions or to take advantage of favorable conditions (Letson et al., 2005;Hill and Mjelde, 2002). In this respect, crop insurance offers farmers economic stability under the uncertainty of future random events, including climate (Mahul, 2001). However, optimal crop insurance choices for farmers differ from those of insurers. In addition, once farmers buy crop insurance, they have a greater incentive to engage in risky behavior; clearly moral hazard can cause farmers' and insurers' interests to diverge. Predictable climate variations may offer an opportunity to close this gap by improving some monitoring features of the crop insurance market (Fraser, 2004).Previous research on the value of climate forecasts on the crop insurance market has been performed from either the farmer's or the insurer's viewpoints, but none have investigated the potential interactions between them. Thus, this article adds to the literature by evaluating optimal crop insurance strategies for farmers and insurers based on different climatic scenarios and levels of risk aversion. The goal of this study is to offer a thorough picture of the value of climate forecasts for the whole crop insurance market. Our hypothesis is that both conflicts and synergies exist between farmers and insurers regarding crop insurance selection and that they are influenced by climate variability.To reach our goal, we analyze the case of a representative 40 ha, rainfed, cotton-peanut farm located in Jackson County, Florida. The southeastern U.S. offers an illustrative setting for studying the interaction of climate variability and crop insurance strategies. Several studies have shown that the El Niño Southern Oscillation (ENSO) is a strong driver of seasonal climate variability that impacts cotton and peanut crop yields in this geographical area (e.g., Hansen, 2002;Jones et al., 2000). In this study, we integrate biophysical simulation models and stochastic non-linear whole-farm optimization models to identify an optimum crop insurance product for farmers and insurers based on different scenarios for ENSO and levels for risk aversion. The riskiness of the decision strategies is evaluated using a constant relative risk aversion utility function for farmers (Letson et al., 2005) and a conditional value-at-risk model (CVaR) for insurers (Liu et al., 2008). These results are then contrasted to evaluate the synergies and conflicts between the two groups under stu...

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Section: Discussionsupporting

confidence: 89%

Optimal Crop Insurance Under Climate Variability: Contrasting Insurer and Farmer Interests

Cabrera¹,

Solís²,

Letson³

2009

Transactions of the ASABE

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“…The fact that regional trends in freezing rain days were found to differ from the national trend is important to those in the insurance industry who may use this data to assess changing risk (Changnon et al, 1999). Similar regional/national trend differences were noted for hail-day and thunderstorm-day frequencies Changnon, 2000, 2001), and suggest that as we continue to examine historical fluctuations and trends in damaging weather events, whether the results are integrated into climate change scenarios or insurance ratings, information at various scales needs to be considered.…”

Section: Discussionmentioning

confidence: 98%

“…The goal was to determine whether the occurrence of freezing rain (observed at manned first-order NWS stations) fluctuated in spatially coherent patterns across the United States. These results could be used by a wide range of users, especially those involved with long-term planning activities in insurance, forestry, and utility industries (Bendel and Paton, 1981;Changnon et al, 1999). …”

Section: Introductionmentioning

confidence: 93%

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Fluctuations in US Freezing Rain Days

Changnon

Bigley

2005

Climatic Change

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Freezing rain occurrences during a 50-year period, 1949/1950-1998/1999, derived from carefully examined records of 161 first-order stations distributed across the United States, were assessed for temporal fluctuations and trends. Classification of station fluctuations based on five 10-year periods revealed five unique distribution types in areas east of the Rockies. One of these five distributions, for stations located in the western Great Plains, experienced its greatest 10-year value at the end of the 50-year period. The other four regional distributions experienced their highest 10-year value in either of the first two 10-year periods. Nationally, the 10-year period when the greatest number of stations experienced their maximum value was 1949/1950-1958/1959, while the period when the greatest number of stations experienced their minimum value fell near the end of the 50-year record (1979/1980-1988/1989). The 50-year linear trends defined one region, the western Great Plains, with increasing values, while three areas of decreasing trend were identified; the Great Lakes, the eastern Ohio River valley, and southern New England. These analyses also indicate the need to examine and consider such time-space changes in the frequency of climate variables at various spatial scales when assessing weather risks and developing climate change scenarios.

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“…It was a group of insurance loss experts organized to identify and make records of major loss events, labeled as catastrophes, and each causing $1 million or more in insured losses. Such property losses could come from weather events, fires, or earthquakes, and included losses to homes, businesses, buildings, vehicles, and other personal effects (Changnon et al, 1999). Studies have found that insured property losses from storms represent 90 percent of all national property losses (Changnon et al, 2001).…”

Section: Data and Analysismentioning

confidence: 99%