Default and loss given default in agriculture

Default and loss given default in agriculture Purpose – The purpose of this paper is to investigate the relationship between loan default and loss given default (LGD) in an agricultural loan portfolio. The analysis employs a simulation model approach to evaluate the role that systematic and non‐systematic risks play in determining the economic capital requirements under different agricultural economic conditions. Design/methodology/approach – The authors employ the theoretical approach suggested by Miu and Ozdemir to assess the role of LGD in the banking industry. A Monte Carlo simulation model is developed using Excel and calibrated to an agricultural credit association using historical data. The simulation model is used to evaluate the mark‐up to economic capital that is implied by increasing credit risks due to cyclical changes in farm real estate values. Findings – The paper demonstrates that historical systematic risks due to the correlation between probability of default (PD) and LGD through the business cycle can result in a significant mark‐up in the economic capital required by an agricultural lender. Using historical land price changes as the driver of systematic risk, the authors show that the correlations between changing PD and land values and between the PD and LGD provide evidence of how sensitive credit risk exposure is to these parameters. Originality/value – This paper is the first application of the Miu and Ozdemir model of systematic risk to an agricultural lending institution. The model approach can be adapted by farm lenders to evaluate their changing economic capital requirements through an economic cycle in agriculture. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Agricultural Finance Review Emerald Publishing

Default and loss given default in agriculture

Agricultural Finance Review, Volume 71 (2): 14 – Aug 2, 2011

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Publisher
Emerald Publishing
Copyright
Copyright © 2011 Emerald Group Publishing Limited. All rights reserved.
ISSN
0002-1466
DOI
10.1108/00021461111152546
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to investigate the relationship between loan default and loss given default (LGD) in an agricultural loan portfolio. The analysis employs a simulation model approach to evaluate the role that systematic and non‐systematic risks play in determining the economic capital requirements under different agricultural economic conditions. Design/methodology/approach – The authors employ the theoretical approach suggested by Miu and Ozdemir to assess the role of LGD in the banking industry. A Monte Carlo simulation model is developed using Excel and calibrated to an agricultural credit association using historical data. The simulation model is used to evaluate the mark‐up to economic capital that is implied by increasing credit risks due to cyclical changes in farm real estate values. Findings – The paper demonstrates that historical systematic risks due to the correlation between probability of default (PD) and LGD through the business cycle can result in a significant mark‐up in the economic capital required by an agricultural lender. Using historical land price changes as the driver of systematic risk, the authors show that the correlations between changing PD and land values and between the PD and LGD provide evidence of how sensitive credit risk exposure is to these parameters. Originality/value – This paper is the first application of the Miu and Ozdemir model of systematic risk to an agricultural lending institution. The model approach can be adapted by farm lenders to evaluate their changing economic capital requirements through an economic cycle in agriculture.

Journal

Agricultural Finance ReviewEmerald Publishing

Published: Aug 2, 2011

Keywords: Default; Loss; Business cycles; Credit; Systematic risk; Agriculture; Simulation

References

  • Default recovery rates in credit risk modelling: a review of the literature and empirical evidence
    Altman, E.; Resti, A.; Sironi, A.

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