College - Author 1

College of Agriculture, Food and Environmental Sciences

Department - Author 1

Agribusiness Department

Degree Name - Author 1

BS in Agricultural Business



Primary Advisor

Xiaowei Cai, College of Agricultural, Food, and Environmental Sciences, Agribusiness Department


This project was a case study completed to find a specific time where an agricultural borrower’s credit began to have problems, and to find new measures agricultural lenders can utilize as a way to predict future defaults and better analyze credit risk.

These calculations were used on actual borrower information generously provided by Farm Credit West. All information that could divulge the identity of the borrower and any private business measures taken by Farm Credit West have been purposefully omitted from this report. This project used common credit risk ratios and values: Current Ratio, Debt-to-Equity, Loan-to-Value, and Debt Coverage Ratio. General credit analytics were implemented in determining the results of this project. The introduction and function of the Debt Capacity calculation and the Altman Z-Score were incorporated in the analysis, and played a large role in the conclusions of this project.

Problems began for the borrower in 2003 after a large conversion to long-term debt solved a liquidity issue, but resulted in more negative impacts for the borrower in later years. This conclusion was arrived at by employing the traditional agricultural credit analysis tools as well as the major Indicators previously mentioned: Debt Capacity calculation and Altman Z-Score. All of these calculations coincided very well to indicate when the borrower’s troubles began.

My recommendation is that agricultural lenders implement the Debt Capacity calculation and the Altman Z-Score into their credit analysis with their traditional calculations as a way to better mitigate credit risk. I also recommend more experiments be done on the effectiveness of these two new calculations in agricultural lending credit analysis.