Agricultural Loan Evaluation with Discriminant Analysis

Johnson, Ryan; Hagan, Albert R.

doi:10.1017/s0081305200011249

Cited by 22 publications

(13 citation statements)

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“…We consider punctual repayment of scheduled loans (used by Reinsel and Brake, 1966) and credit ratings on good and problem loans (used by Johnson and Hagan, 1973;Bauer and Jordan, 1971;Knopf and Schoney, 1993;Turvey andBrown, 1990 andMortensen et al 1988) to be ambiguous and subjective. Similarly, changes in net worth (used by Krause and Williams, 1971) also seem to provide an unsatisfactory measure of financial success.…”

Section: Methodsmentioning

confidence: 99%

Accounting Information and the Prediction of Farm Viability

Argilés

1998

SSRN Journal

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Abstract:Farms make little use of accounting and until now have been largely excluded from the scope of accounting standards. However, we hypothesize that the use of accounting-based information can significantly improve the explanation and prediction of farm viability/failure. Two dichotomous logit models were applied to subsamples of viable and unviable farms in Catalonia, Spain. One model included non-accounting-based variables, while the other also considered accounting-based variables. It was found that, when accounting variables were added to the model there was a significant reduction in deviance.

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Section: Methodsmentioning

confidence: 99%

Accounting Information and the Prediction of Farm Viability

Argilés

1998

SSRN Journal

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“…The first and most fundamental application of MDA was from Altman [19], with a sample of 66 firms (33 distressed and 33 not-distressed), which gave rise to the well-known Z-Score, which the same author then developed into the EM-Score [20], which is aimed at classifying firms in a given rating class, i.e., default risk. The application of MDA has also been relevant in the agricultural sector, with analyses aimed at paying bank debts [21] and envisaging a progressive increase in explanatory variables [22]. MDA is able to provide a dichotomous indication, dividing firms between distressed and not-distressed, but is limited by not providing indications in terms of probability of insolvency.…”

Section: Financial Ratio Analysismentioning

confidence: 99%

Analysis of the Risk of Bankruptcy of Tomato Processing Companies Operating in the Inter-Regional Interprofessional Organization “OI Pomodoro da Industria Nord Italia”

Iotti

Bonazzi

2018

Sustainability

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The tomato sector is a major area of agricultural activity in Italy; tomato production and processing characterize different Italian regions; in particular, there are two production districts, one in southern Italy and one in northern Italy, in the Po Valley. In recent years, processing firms have encountered increasing difficulties, due both to an increase in raw material costs and market difficulties. Tomato processing firms are often characterized by significant investment in fixed assets and working capital, with an ensuing increase in equity or debt financing, which increases the risk of bankruptcy, as has happened to many firms in the sector in recent years. Therefore, the aim of this research was to analyze the financial sustainability of tomato processing firms by applying financial ratios. To achieve this goal, this research focused on the annual data of a sample of 17 tomato processing firms operating in the Interregional Interprofessional Organization, "OI Pomodoro da Industria Nord Italia". The firms were divided into still-active (not-distressed) and failed (distressed) firms, with the aim of analyzing the differences between the financial data and management practices of the two groups. The data suggest that larger firms, with an adequate financial structure, have been able to withstand the tomato market crisis in recent years, whereas distressed firms are on average smaller and suffer from higher recourse to debt capital and lower profit margins than not-distressed firms. This research could be applied by entrepreneurs, managers, bankers and public operators to define good management practices that should be achieved and measured with financial ratios, even as a means of reducing the risk of distress for firms operating in the tomato sector. This research highlights that financial ratios could be usefully applied for predicting the continuity of activity and therefore the sustainability of the management cycle, including its relationship to the whole socioeconomic system over time.

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“…Loans are classified using statistical techniques into potential problem loans and good loans (Bauer and Jordan 197 1 ;Johnson and Hagan 1973;Dunn and Frey 1976;Moms, Harwell and Kaiser 1980;Hardy and Weed 1979;Tongate 1986;Lufburrow, Barry and Dixon 1984;Kohl 1987). Loans are classified using statistical techniques into potential problem loans and good loans (Bauer and Jordan 197 1 ;Johnson and Hagan 1973;Dunn and Frey 1976;Moms, Harwell and Kaiser 1980;Hardy and Weed 1979;Tongate 1986;Lufburrow, Barry and Dixon 1984;Kohl 1987).…”

Section: Review Of Literature To Select Criteria and Measuresmentioning

confidence: 99%

“…Another area of research deals with the classification of borrowers with credit scoring models. Loans are classified using statistical techniques into potential problem loans and good loans (Bauer and Jordan 197 1 ;Johnson and Hagan 1973;Dunn and Frey 1976;Moms, Harwell and Kaiser 1980;Hardy and Weed 1979;Tongate 1986;Lufburrow, Barry and Dixon 1984;Kohl 1987). Many financial and nonfinancial characteristics have been considered.…”

Section: Review Of Literature To Select Criteria and Measuresmentioning

confidence: 99%

Agricultural Financial Analysis Expert Systems: Software Description

McGrann

Karkosh

Osborne

1989

Canadian J Agri Economics

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SUMMARY The Agricultural Financial Analysis Expert Systems (AFAES) include software to prepare: agricultural financial statements; analysis summaries and graphic presentations of the analysis; and expert systems that present a diagnostic analysis of the financial statement data. In addition, there is a lender data base management system (STANDARDS) to check borrower documentation, to compare borrower data to lender standards and to summarize data from the lender portfolio of borrowers. Using AFAES software helps organize financial data in a format following accounting procedures. The expert system provides a consistent diagnostic analysis of financial data useful to both producers and lender. AFAES is developed to interface with existing accounting and financial statement software or lender data bases. AFAES not only has been developed and verified in Texas but also its development has involved two national task forces, land‐grant university professionals, software vendors, accountants, lenders and representatives of regulatory agencies. Experience gained through development and verification efforts indicate that expert systems technology will be a valuable tool to enhance knowledge delivery by agricultural economists. Economics and finance are areas where expertise is often limited, leading to inadequate use of data and analysis tools by producers, lenders and educators. Expert systems offer a significant delivery technology.

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Agricultural Loan Evaluation with Discriminant Analysis

Cited by 22 publications

References 0 publications

Accounting Information and the Prediction of Farm Viability

Accounting Information and the Prediction of Farm Viability

Analysis of the Risk of Bankruptcy of Tomato Processing Companies Operating in the Inter-Regional Interprofessional Organization “OI Pomodoro da Industria Nord Italia”

Agricultural Financial Analysis Expert Systems: Software Description

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