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Recent public policy initiatives seek greater transparency in financial reporting through an honest, balanced and thorough management discussion of company performance in the annual report. Management’s discussion invariably includes key performance indicators, such as financial ratios, relevant to external stakeholders. We model the impact of accounting estimates, assumptions, choices and errors on the risk of misleading financial ratios. This framework is illustrated through good and bad examples of financial reporting practices and by simulation of financial data of public companies. We provide a structured approach to inform policymakers, auditors and other stakeholders of the incremental financial reporting risk that accompanies current regulatory efforts.

Sees the objective of teaching financial management to be to help managers and potential managers to make sensible investment and financing decisions. Acknowledges that financial theory teaches that investment and financing decisions should be based on cash flow and risk. Provides information on payback period; return on capital employed, earnings per share effect, working capital, profit planning, standard costing, financial statement planning and ratio analysis. Seeks to combine the practical rules of thumb of the traditionalists with the ideas of the financial theorists to form a balanced approach to practical financial management for MBA students, financial managers and undergraduates.

US decoupled direct payments, paid to farm operators based on historic yields and base acreage under the 2002 Farm Bill, may alter a farmer's access to credit or his ability to meet debt servicing obligations. More specifically, direct payments might improve the farmer's liquidity position or repayment capacity enabling the farmer to obtain more favorable credit terms. In turn, more favorable credit terms might allow a farm to remain in business or expand production, leading to current production distortions. Since direct payments are based on historic production, beginning farmers tend to receive lower levels of direct payments and hence these payments might impact beginning farmers differently than more experienced farmers. The purpose of this paper is to investigate the effects of direct payments on liquidity and repayment capacity for experienced and beginning farmers.

Given the manner in which direct payments are calculated and administered, it is likely that direct payments affect beginning farmers and more experienced farmers differently; hence the authors analyze the impacts of direct payments on the current and term debt coverage ratios for these two groups separately. In the analysis, the authors control for farm financial characteristics, farm operator characteristics, and other factors. Data from the US Department of Agriculture (USDA) Agricultural Resource Management Survey (ARMS) for the years 2005, 2006, and 2007 were used in the weighted regression analysis and jackknifed standard errors computed.

A positive significant relationship was found between the level of direct payments (in dollars) and the term debt coverage ratio for experienced farmers, suggesting that direct payments improve repayment capacity. However, this relationship is not significant for beginning farmers. Also, a negative significant relationship was found between the number of base acres and the current ratio for experienced farmers, while this relationship lacks significance for beginning farmers.

The paper provides evidence that decoupled direct payments impact a farmer's liquidity and repayment capacity. Furthermore, direct payments impact beginning and experienced farmers differently. This paper also contributes to the growing body of research investigating the mechanisms by which decoupled payments have the potential to distort current production.

This chapter focuses on the IFRS 15 Revenue from Contracts with Customers and IFRS 16 Leases in the airline industry considering the case of Air France – KLM (AF-KLM). This airline timely adopted IFRS 15 and early adopted IFRS 16 for the year 2018 and restated its 2017 financial statements using the full retrospective method so that the 2018 financial statements of the airline provide comparative financial information during the transition phase from IAS 18 to IFRS 15 as well as from IAS 17 to IFRS 16. In the first part of the chapter, liquidity, solvency, and profitability ratios along with cash flow ratios were used to analyze the cumulative effect of IFRS 15 and IFRS 16 using 2017 and restated 2017 financial statements. In this context, results indicate that the liquidity ratios decreased, and the solvency ratios increased in general. In addition, the cumulative effect of IFRS 15 and IFRS 16 created an upward change in general on profitability ratios based on the several performance parameters that should be considered during the transition from IAS 18 to IFRS 15 and from IAS 17 to IFRS 16. Overall, IFRS 15 has minor effect and IFRS 16 has major effect on the financial statements of AF-KLM. In the second part of the chapter, the compliance level of the mandatory disclosures requirements of the airline was examined from the lessee standpoint and the research pointed out that the airline fully complied with these disclosures at its first adoption of IFRS 16 and provided some voluntary disclosures as well.

The typical accounting curriculum focuses on technical knowledge, which makes it challenging to devote time toward developing other important skills, such as examining how accounting rules may impact a company’s financial statements. Recently, the accounting rules for lease transactions changed significantly, and this chapter provides an overview of an assignment used in an intermediate accounting course to engage students in a real-world application. Students had the opportunity to apply accounting rules to a publicly traded company, measure the significance of changes to generally accepted accounting principles, read financial disclosures, reinforce concepts of present value and ratio analysis, and engage in critical thinking. This type of assignment does not have to be limited to leases, and instructors could discuss any accounting rule by following a similar model, whether the rule itself is current or proposed. This would offer students context beyond textbook learning.

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.

The purpose of this research is to evaluate the financial performance measures calculated and reported by the Economic Resource Service (ERS) from Agricultural Resource Management Survey (ARMS) data. The evaluation includes the calculation method and the underlying assumptions used in obtaining the reported values. Recommendations for improving the information reported are proposed to ERS.

The financial measures calculated and reported are compared with those recommended by the Farm Financial Standards Council (FFSC). The underlying assumptions are identified by analyzing the software code used in calculating the values reported. The values reported by ERS are duplicated and alternative methods for calculating the financial performance measures are considered. The values obtained from the various calculation methods are compared and contrasted.

Recommendations for ERS include: calculate and report the financial measures recommended by FFSC, note values that are imputed, periodically update and validate assumptions used in calculating imputed values, review its policy for flagging estimates as statistically unreliable, report medians and other select percentiles, and consider reporting the percent of farm businesses that have values within critical zones.

A total of four methods for calculating financial performance measures are compared and contrasted. These are the aggregate mean, sample mean, sample median, and percentage of farm businesses with values in critical zones.

The origins of financial ratio analysis can be traced back to the first decade of the twentieth century. It began with the development of a single ratio, the current ratio, for a single purpose—the evaluation of credit worthiness. Today ratio analysis involves the use of several ratios by a variety of users including credit lenders, credit rating agencies, investors and management.

This article estimates the loan spread equation taking into account the endogenous matching between banks and firms in the loan market. To overcome the endogeneity problem, I supplement the loan spread equation with a two-sided matching model and estimate them jointly. Bayesian inference is feasible using a Gibbs sampling algorithm that performs Markov chain Monte Carlo (MCMC) simulations. I find that medium-sized banks and firms tend to be the most attractive partners, and that liquidity is also a consideration in choosing partners. Furthermore, banks with higher monitoring ability charge higher spreads, and firms that are more leveraged or less liquid are charged higher spreads.