Evaluating risk profile and financial performance of various types of agricultural and natural resource operations in Maine

The agricultural and natural resource sector in Maine faces challenges from an array of natural hazards and financial disturbances. A significant amount of resources have been spent on minimizing such risks. However, for farmers, how to make optimal production decisions facing these risks? How to utilize the available financial instrument to better hedge risks? For government agencies,  how to protect farmers from unexpected losses? How to assess existing and proposed policies? All these concerns could be traced back to a lack of research on the risk profiles of Maine’s agricultural and natural resource operations’ owners. This project aims to answer how to quantify these farmers and resource owners’ risk profiles, including the risks that they face and their risk preferences. With such a better understanding, this study can further evaluate Maine farmers’ financial status, economic sustainability of their operations and effectiveness of financial instruments, and therefore influence the farmers, natural resource owners, policy makers and other stakeholders’ attitudes, perceptions and willingness to support risk management products, programs and policies in Maine’s agricultural and natural resource sector. I plan to disseminate my research findings to stakeholders through different channels such as technique bulletin, seminar presentation and workshop. Such an outreach effort will benefit the Maine agricultural and resource sector. For example, this project will provide effective economic tools (models) for farmers to improve their decision making process. Further, the agricultural and resource operations in Maine share a lot of similarities with their counterparts in the Northeast and other regions in the U.S. My research results should also enhance a better understanding of agricultural and resource productions at the regional and even national level. Meanwhile, the econometric and economic models developed in this project will supply useful tools for scholars studying similar topics from other regions and even countries.

Investigator: Chen, XU.

Unit: School of Economics

Termination Date: 30-Sep-20