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Measurement of Farm Credit Risk: SUR Model and Simulation Approach 31
Yan, Yan; Barry, Peter J.; Paulson, Nicholas D.; Schnitkey, Gary D..
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.
Tipo: Conference Paper or Presentation Palavras-chave: Credit Risk Measurement; Seemingly Unrelated Regression Model; Simulation; Agribusiness; Agricultural Finance; Farm Management; Research Methods/ Statistical Methods; Risk and Uncertainty.
Ano: 2009 URL: http://purl.umn.edu/49222
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RISK BALANCING USING FARM LEVEL DATA: AN ECONOMETRIC ANALYSIS 31
Yan, Yan; Katchova, Ani L.; Barry, Peter J..
In the paper, an econometric model is proposed to test the risk balancing hypothesis using farm level data. For the purpose, a constraint on expected utility maximization with respect to farm financial structure is given. Cluster method is applied to pick out the farms on the efficient frontier under expected utility maximization given risk attitude and actual interest rate. Regression results are given and compared to previous findings. Farm characteristics associated with the risk behaviors of farms with optimal utility are identified and compared with other farms.
Tipo: Conference Paper or Presentation Palavras-chave: Risk and Uncertainty.
Ano: 2004 URL: http://purl.umn.edu/20142
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The Structure Model Based Determinants of Capital Structure: A Seemingly Unrelated Regression Model 31
Yan, Yan; Shi, Xiangdong; Barry, Peter J.; Paulson, Nicholas D.; Sherrick, Bruce J..
This study proposed a seemingly unrelated regression model to investigate the predicting capability of the structure model and test the capital structure theories. The model considered dynamic property of the structure model and characteristics of farm records. FBFM data are used in empirical analysis. The regression results provide new supportive evidence on capital theories.
Tipo: Conference Paper or Presentation Palavras-chave: Structure Model; Capital Structure; Seemingly Unrelated Regression; Research Methods/ Statistical Methods.
Ano: 2008 URL: http://purl.umn.edu/6171
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