Agricultural lenders in today’s environment face many challenges when evaluating the creditworthiness of farm borrowers. To address these challenges, a survey was conducted with financial institutions in Kansas and Indiana where agricultural lenders were asked for their response to...

Can remotely sensed imagery improve hedonic land price models? A remotely sensed variable was added to a hedonic farmland value model as a proxy for land productivity. Land cover data were used to obtain urban and recreational effects as well. The urban and recreational effects were...

An out-of-sample prediction of Kansas farmers' responses to five surveyed questions involving risk is used to compare ordered multinomial logistic regression models with feedforward backpropagation neural network models. Although the logistic models often predict more accurately than the neural...

This paper attempts to improve the ability of farm managers and lenders to forecast expected financial performance of farm businesses using a neuro-fuzzy inference system. Ex-ante farm financial performance is examined to identify the farms that are likely to become financially stressed before...

Agricultural lenders in today’s environment face many challenges when evaluating the creditworthiness of farm borrowers. To address these challenges, a survey was conducted with financial institutions in Kansas and Indiana where agricultural lenders were asked for their responses to...

This study investigates the dynamics of agribusiness stock returns and the market return for 22 firms in a switching-regression framework. Threshold levels and regression slopes are estimated and tested. Results indicate how parameters differ for alternative regimes, at what levels dynamic...

Parametric, non-parametric, and semi-parametric approaches are commonly used for modeling correlated distributions. Semi-parametric and non-parametric approaches are used to examine the risk situation for Kansas agriculture. Results from the model indicate that 2000 will be another difficult...