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Agricultural lenders manage relatively under-diversified loan portfolios and when rising loan defaults are combined with adverse agricultural business cycle developments and/or systematic changes in agricultural economic conditions these factors may pose a significant threat to financial performance and capital positions. So, how should an agricultural lender adjust its capital position to guard against the consequences of unexpected economic downturns in the agricultural sector? This is a timely question, since the farm credit system (FCS) is inquiring about how to integrate tiers 1 and 2 capital standards similar to those found in the Basel Capital Accord (that other federal financial regulators are adopting for banking organizations) with the existing capital standards used by the FCS ([5] Farm Credit Administration, 2010). The Basel Accord recognizes the existence of fluctuations in the economy and the impact of both default and loss rates given the lender's level of risk exposure ([4] Basel Committee on Banking Supervision, 2004), and it makes broad recommendations on how banks should adjust their capital holdings in response to market fluctuations. Yet, the majority of agricultural lenders (including FCS associations and agricultural banks) are small- to medium-sized institutions and they typically do not have the resources to adequately explore these requirements. Thus, additional research might focus on identifying which factors lenders should focus upon in order to better understand their portfolio risk exposures and capital adequacy positions.
[1] Altman (2010) provides a review of recent studies and suggests that codependence between probability of default and loss given default (the PD/LGD link) is an important consideration when assessing credit risk exposure. [3] Altman et al. (2004) provide a comprehensive review of modeling practices where credit risk models have typically assumed stationary loss distributions. In these models, the recovery rate is either constant or independent of the PD. [2] Altman et al. (2005) evaluate two of the dominant credit risk models (CreditRisk+ and CreditMetrics) on a simulated portfolio of bank loans and they show that if default and loss rates are significantly correlated these models will understate the resulting value-at-risk when those correlations are ignored. As a consequence, a lender would hold an insufficient economic capital position at the bottom of the business cycle when loan defaults and losses are at their peak. The methodology used...