<p dir="ltr">The Farm Service Agency's Guaranteed Loan Program supports eligible lender's ability to provide credit to farms who would otherwise not qualify for loans by guaranteeing up to 95% of principal and interest if the farmer defaults. The first chapter examines the degree to which bank characteristics influence FSA guaranteed loan rates paid by farmers. We leverage the unique characteristics of a panel of FSA guaranteed loans that include both borrower and lender information. Relative to pooled OLS, our preferred fixed-effects regression specification suggests that both time-varying and invariant lender effects are a significant determinant of FSA guaranteed loan rates. Further, when controlling for lender-effects, the significance of borrower characteristics largely diminish. These findings are consistent with prior studies of broader lending market interaction. This is the first study to examine FSA guaranteed loans which accounts for bank-level variation in lending terms. The findings may be of interest to policymakers, program administrators, lenders, and farmers.</p><p dir="ltr">Bankers’ expectations have been shown to provide reasonable forecasts of land value. In the second chapter, we test the informativeness of bankers’ expectations in predicting FSA guaranteed loan application volumes. Once again, we leverage proprietary administrative data from the FSA and, this time, pair it with survey data from the Federal Reserve Bank of Chicago to evaluate bankers’ forecasts. Results show that bankers’ forecasts are outperformed by naïve models, and including bankers’ expectations does not improve predictive models. Once again, these results will be of interest to FSA program administrators, lenders, and potential borrowers.</p><p dir="ltr">The study of risk is an important thread of farm management research as agriculture is an industry with many sources of risk. In the third chapter, we link broad measures of policy risk in the form of Equity Market Volatility trackers to farmer’s perceptions of risk and uncertainty. We consider disagreement in ex ante sentiment questions to measure farmer risk. Through a series of pairwise VARs, we show which sources of risk matriculate as concerns for farmers measured by uncertainty in the Purdue University-CME Group Ag Economy Barometer. Increases in tax policy, trade policy and infectious disease uncertainty are found to Granger-cause movement in farmer sentiment uncertainty.</p>
Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/26332360 |
Date | 18 July 2024 |
Creators | Megan N. Hughes (8775677) |
Source Sets | Purdue University |
Detected Language | English |
Type | Text, Thesis |
Rights | CC BY 4.0 |
Relation | https://figshare.com/articles/thesis/_b_Essays_in_Agricultural_Finance_b_/26332360 |
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