Application of Data Mining Techniques to Further Understand the Relationship Between Drought and Impacts in the Pacific Northwest
Agricultural crop insurance is an important component for mitigating farm risk, particularly given the potential for unexpected climatic events. Using a 2.8 million national insurance claim dataset from the United States Department of Agriculture (USDA), this research study examined spatiotemporal variations of agricultural insurance loss across the 24-county region of the inland Pacific Northwest (iPNW) portion of the United States, from 2001 to 2015. Applying a time-lagged algorithmic technique to find the most relevant associations between climate and insurance loss, the researchers constructed a random forest model which tracked the overall variation of insurance loss for wheat due to drought, with a modest R2 of .45. The results of this research indicate a threshold relationship between economic and climatic influences on insurance outcomes, with variations based on geography, crop regime, climate, and commodity pricing.