The study addresses problems in measuring credit risk under the structure model, and then proposes a seemingly unrelated regression model (SUR) to predict farms’ ability in meeting their current and anticipated obligations in the next 12 months. The empirical model accounts for both the dependence structure and the dynamic feature of the structure model, and is used for estimating asset correlation using FBFM data for 1995-2004. Farm credit risk is then predicted by copula based simulation process with historical default rates as benchmark. Results are reported and compared to previous studies on farm default
Current USDA forecasts indicate that US farms are entering a period of lower net farm income, follow...
This study uses the cohort approach to estimate the credit risk migration probability of farm busine...
is deemed most suitable for agricultural lending. The CreditRisk+ model is modified to overcome its ...
The study addresses problems in measuring credit risk under the structure model, and then proposes a...
The study measures farm credit risk by using farm records collected by Farm Business Farm Management...
Credit risk models are developed and used to estimate capital requirements for agricultural lenders ...
Credit risk models are developed and used to estimate capital requirements for agricultural lenders ...
217 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003.Four explanatory variables: D...
A framework is identified for modeling credit risk in agriculture. A CreditRisk+ type model is deeme...
155 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1993.Credit scoring models were de...
The study identifies important criteria that should be used by lenders in risk-rating of their farm ...
With farm income at record, or near record levels, the overall agricultural production sector has fa...
Pro forma financial performance evaluation of agricultural producers is an important issue for lende...
Farmer Mac is the GSE charged with creating a secondary market in loans backed by agricultural real ...
Cash income data obtained from farm records is decomposed with a regression technique suggested by p...
Current USDA forecasts indicate that US farms are entering a period of lower net farm income, follow...
This study uses the cohort approach to estimate the credit risk migration probability of farm busine...
is deemed most suitable for agricultural lending. The CreditRisk+ model is modified to overcome its ...
The study addresses problems in measuring credit risk under the structure model, and then proposes a...
The study measures farm credit risk by using farm records collected by Farm Business Farm Management...
Credit risk models are developed and used to estimate capital requirements for agricultural lenders ...
Credit risk models are developed and used to estimate capital requirements for agricultural lenders ...
217 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003.Four explanatory variables: D...
A framework is identified for modeling credit risk in agriculture. A CreditRisk+ type model is deeme...
155 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1993.Credit scoring models were de...
The study identifies important criteria that should be used by lenders in risk-rating of their farm ...
With farm income at record, or near record levels, the overall agricultural production sector has fa...
Pro forma financial performance evaluation of agricultural producers is an important issue for lende...
Farmer Mac is the GSE charged with creating a secondary market in loans backed by agricultural real ...
Cash income data obtained from farm records is decomposed with a regression technique suggested by p...
Current USDA forecasts indicate that US farms are entering a period of lower net farm income, follow...
This study uses the cohort approach to estimate the credit risk migration probability of farm busine...
is deemed most suitable for agricultural lending. The CreditRisk+ model is modified to overcome its ...