The New Basel Capital Accord (Basel II) provides added emphasis to the
development of portfolio credit risk models. An important regulatory change in Basel II
is the differentiated treatment in measuring capital requirements for the corporate
exposures and retail exposures. Basel II allows agricultural loans to be categorized and
treated as the retail exposures. However, portfolio credit risk model for agricultural loans
is still in their infancy. Most portfolio credit risk models being used have been developed
for corporate exposures, and are not generally applicable to agricultural loan portfolio.
The objective of this study is to develop a credit risk model for agricultural loan
portfolios. The model developed in this study reflects characteristics of the agricultural
sector, loans and borrowers and designed to be consistent with Basel II, including
consideration given to forecasting accuracy and model applicability. This study
conceptualizes a theory of loan default for farm borrowers. A theoretical model is
developed based on the default theory with several assumptions to simplify the model.
An annual default model is specified using FDIC state level data over the 1985 to
2003. Five state models covering Iowa, Illinois, Indiana, Kansas, and Nebraska areestimated as a logistic function. Explanatory variables for the model are a three-year
moving average of net cash income per acre from crops, net cash income per cwt from
livestock, government payments per acre, the unemployment rate, and a trend. Net cash
income generated by state reflects the five major commodities: corn, soybeans, wheat,
fed cattle, and hogs. A simulation model is developed to generate the stochastic default
rates by state over the 2004 to 2007 period, providing the probability of default and the
loan loss distribution in a pro forma context that facilitates proactive decision making.
The model also generates expected loan loss, VaR, and capital requirements.
This study suggests two key conclusions helpful to future credit risk modeling
efforts for agricultural loan portfolios: (1) net cash income is a significant leading
indicator to default, and (2) the credit risk model should be segmented by commodity
and geographical location.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/2276 |
| Date | 29 August 2005 |
| Creators | Kim, Juno |
| Contributors | Penson, John B. |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | 950553 bytes, electronic, application/pdf, born digital |
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