Analyzing FSA Direct Loan Borrower Payback Histories: Predictors of Financial Improvement and Loan Servicing Actions

Classical and count data regression models are estimated to predict improvement in three key financial indicators—net worth, debt-to-asset ratio and current ratio—as well as the number of loan restructurings and delinquencies. Data consist of Farm Service Agency direct loans originated in fiscal years 1994-1996. Models to predict outcomes vary by loan type. Models explaining variation in the financial measures have modest explanatory power but initial levels of debt-to-asset ratio and current ratio are significant in explaining changes in debt-to-asset ratios and current ratios, respectively. Models explaining number of restructurings and delinquencies for operating loans have satisfactory explanatory power. Increasing crop revenues to total farm revenues and increasing farm size lead to increased loan servicing actions


Issue Date:
2009
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/49340
Total Pages:
28
JEL Codes:
q14; q12
Series Statement:
Selected Paper
613123




 Record created 2017-04-01, last modified 2017-08-25

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