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The purpose of this paper is to examine empirical customer account data from 2006 through 2012 to review the probability of default (PD) rating methodology implemented by a FCS association for production agricultural accounts. This analysis provides insight into the migration of accounts across the association’s currently established PD rating categories with negative migration being a precursor to potential loan default.

The data set contained 17,943 observations from the years 2006 to 2012 and consisted of various fields of data including balance sheet date, earnings statement date, and PD rating as of the statement date. The methods include analysis on the dynamics of the PD ratings and component ratios. OLS regression was used to analyze the data to see how the current period PD rating and component ratios affected the PD rating one year, three years, and five years out. OLS regression examined the statistical significance of the PD ratings and ratio components for this analysis. The dependent variable, Future PD Rating, represents the assigned PD rating for the observed farm either one, three, or five years into the future. It is expected that the initial PD rating in any given year would have a positive relationship, and be statistically significant in estimating future PD ratings. The independent variables are the current PD rating and the various component ratios of the inverse current ratio (CR), the debt to asset ratio (D/A), the gross profit to total liabilities ratio, the inverse debt coverage ratio, working capital to gross profit, and funded debt to EBITDA.

Results indicate that financial ratio information gathered today can do a good job forecasting PD ratings up to three years in the future. CR information does not forecast five years into the future very well. Thus, there is an important need to update financial information on a regular basis. The results indicate that the D/A information is very important in predicting risk ratings. As the production agriculture sector has experienced difficult financial conditions during 2014 and 2015, agricultural finance institutions need to obtain up-to-date financial information from their clientele to effectively assess the risk of and manage their financial portfolio.

Several previous works have examined and established models to assess risk in agricultural lending. This research adds to this body of work by examining the migration of an account’s risk-rating class over time using actual lender account data.

Utilising data from 18 in‐depth case studies, this study seeks to explore training, development and human resource development (HRD) practices in European call centres. It aims to argue that the complexity and diversity of training, development and HRD practices is best understood by studying the multilayered contexts within which call centres operate. Call centres operate as open systems and training, development and HRD practices are influenced by environmental, strategic, organisational and temporal conditions.

The study utilised a range of research methods, including in‐depth interviews with multiple stakeholders, documentary analysis and observation. The study was conducted over a two‐year period.

The results indicate that normative models of HRD are not particularly valuable and that training, development and HRD in call centres is emergent and highly complex.

This study represents one of the first studies to investigate training and development and HRD practices and systems in European call centres.

The performance, management, and risk exposure of financial institutions operating in rural and agricultural markets determine the cost of agriculture’s ongoing access to financial capital. The evolution of general banking and agricultural finance research contributions in the structure, performance, and risk management of financial institutions lending to agriculture and providing financing to rural markets is described and discussed in this paper. A summary of future research priorities in each of these areas is also provided. Ongoing regulatory change, institution consolidation, financial innovations, and the changes occurring in the agricultural sector drive research opportunities in this area. Ongoing research will be critical to maintain efficient rural financial markets that can provide consistent and competitively priced credit for rural America.

Recent research has indicated that livestock producers who want to manage risk and diversify their operations should invest in the stock market. This research evaluates whether or not a portfolio of publicly held companies that are first handlers of pork products would provide pork producers with a means of enhancing annual returns and reducing the volatility in the annual returns. Ex ante results suggest producers can gain from investment in value‐added stocks. Ex post results, however, imply producers must choose active management of their portfolio to receive the same type of benefits as the ex ante portfolio.

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 hypothetical agricultural loan requests. Each loan request differed by the borrower’s character, financial record keeping, productive standing, Fair Isaac credit bureau score, and credit risk. Lenders provided information about themselves and their financial institutions. The survey data obtained determine the relative importance of financial and nonfinancial information when analyzing agricultural loan applications. Tobit models are estimated to identify the borrower and lender characteristics that are important in determining loan approval, while OLS models are used to investigate the factors that affect interest rates offered to farm borrowers. The results offer a comparison of agricultural lending between two important agricultural states and provide lenders with insight on the factors that influence the decision‐making process of other agricultural lenders.

The purpose of this paper is to examine the use of single vs multiple lenders by Kansas farms. Previous studies suggest that as the risk level of the firm changes, borrowers desire to enhance the probability of obtaining credit at the lowest possible cost may cause them to use multiple lenders.

A model is adopted from the banking literature to describe farm behavior in obtaining credit from a single vs multiple lenders. Using farm-level data from the Kansas Farm Management Association, an empirical model analyzes how farm characteristics affect the number of lending relationships. A model is developed to analyze the number of lending relationships effect on the profitability of the farm.

It is found that highly leveraged farms seek additional lending relationships supporting the theoretical model and that additional lending relationships correlate to a decrease in profitability. Roughly, 50 percent of Kansas farmers that borrow use a single lender. Roughly 48 percent use from two to four lenders, with the remaining 2 percent using more than four lenders.

Provides empirical results to support developed theoretical framework on the number of lending institutions. This study helps understand factors correlated to a farmer's decision to use multiple lenders. Analyzing the number of lending relationships helps understand how farmers manage their debt to maintain access to credit when needed at the lowest possible cost.

The purpose of this paper is to identify relevant financial concepts and skills that are being taught and/or should be taught, as part of the financial management curriculum in undergraduate agricultural economics and agribusiness programs.

The skill gap analysis uses survey respondents' rankings of the importance and competence scores of recent graduates' skills. The scores help to identify opportunities for improvement in the most critical areas of importance. The skill gap is calculated as (Average importance–Average competence)*Average importance.

Generally, employers in the agricultural financial services sector saw greater opportunities for improvement in finance skills relative to non‐finance skills. The results also indicated a greater focus on business and financial risk might be helpful in increasing the competence of new hires. Finally, respondents strongly endorsed maintaining a focus on the problem‐solving skills in undergraduate agribusiness programs.

The value of the study would be that departments of agricultural and applied economics would use the results of this survey to enhance their financial management curriculum and their undergraduate program. By responding to the desires of employers, agricultural economics and agribusiness programs cannot only remain relevant as a source of employees for the industry but the first choice of agricultural financial services sector when they are searching for new hires. This should also help inform students of the desirability of the skills they acquire in their degree programs. This information will also benefit the agricultural finance services sector by assisting college and university instructors in developing and/or enhancing their agricultural finance course(s) so that the may provide their students with the requisite financial and non‐financial skills that they require.

The purpose of this research is to examine the usability and communication methods of the Agricultural Resource Management Survey (ARMS) data. Recommendations for improving access and usability are proposed to Economic Research Service (ERS).

The current methods for accessing the ARMS data are described. Several accounting issues related to the usability of the data are presented. Cost of production issues related to the data are also discussed.

Recommendations to ERS include: increase efforts to disseminate the ARMS results more widely, make the ARMS web tool easier to access, develop partnerships with universities, increase the value of the web tool by providing more information on the data that are already available, consider the accounting items of extraordinary income, inventory valuations, and nonmonetary income and consider issues related to cost of production items.

By identifying the factors limiting the current use of the ARMS data, changes can be made that may result in wider dissemination and use of the data.