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This study assesses the change in states’ financial condition by examining their financial data in fiscal years (FY) 2003 and 2004. It explores and explains how much the change was, how it occurred, and whether and how closely the change might respond to states’ socioeconomic development. The study finds that states’ financial condition varied significantly from FY 2003 to FY 2004. Changes in different aspects of financial condition are interrelated, although these changes may not occur simultaneously at the same pace. The change in financial condition may result from the multi-year cumulative socioeconomic development in personal income and employment, but not in population. The impact of personal income and employment on financial condition of a government is likely long term; it may take 3-4 years for the growth in personal income and employment to benefit a government’s financial condition. The results also suggest that the cumulative improvement of personal income and employment for consecutive years prior to a fiscal year is more likely to improve the financial condition of that year than a personal income or employment increase that follows an up-and-down pattern of growth. These findings can be used to develop effective strategies to improve financial conditions in government.

The purpose of this article is to investigate the impact of counterparty risk on the basis risk of industry loss warranties as well as on reinsurance with and without collateral under different dependence structures. The authors additionally compare the solvency and Sharpe ratio for different premium loadings and contract parameters.

The authors propose a model framework extension to account for the counterparty risk of risk transfer arrangements. Copulas are used to also take into account non-linear dependencies between risk factors, and Monte Carlo simulation is employed to derive numerical results and to conduct sensitivity analyses.

The authors show that the impact of counterparty risk is particularly pronounced for higher degrees of dependencies and tail dependent losses, i.e. in cases of basis risk levels that appear low if counterparty risk is not considered. With respect to counterparty risk management, the authors find that already partial collateralization limits counterparty and basis risk to more acceptable levels.

The study results are particularly relevant to practitioners, as insurers may not only underestimate the “true” basis risk of index-linked instruments, but also the effect of counterparty risk of reinsurance contracts along with the consequences for solvency and profitability.

The authors extend existing literature by allowing for the (partial) default of industry loss warranties and reinsurance under different dependence structures. Furthermore, the authors include profitability in addition to risk considerations. The interaction effects between counterparty risk and the basis risk of index-based alternative risk transfer instruments are largely unstudied, despite their considerable relevance in practice.

This paper aims to develop and utilize a conceptual framework to examine the impact of liquidity and solvency on cost efficiency for a sample of Kansas farms.

A standard cost-efficiency model is modified to incorporate liquidity and solvency ratios. Tobit regressions are used to determine the impact of farm characteristics on improvements in efficiency.

Results confirm that liquidity and solvency measures have a significant impact on improving cost efficiency. Farms with larger expenditures on purchased inputs relative to capital were less likely to improve efficiency when liquidity and solvency were considered.

To the authors' knowledge, the paper is the first to add liquidity and solvency ratios to the cost-efficiency model developed by Färe et al. for the analysis of farms.

The purpose of this study is to examine how US farm sector performed in 2020, the first year of the pandemic. There were significant supply and demand shocks due to the pandemic. Furthermore, there was significant fluctuation in commodity prices and record high government payments in 2020. This study aims to examine the performance and position of US farm sector (financially) to system (and global economy) wide shocks.

The authors examine 2020 values for farm sector financial ratios before and after the onset of the Coronavirus (COVID-19) pandemic using the data from the United States Department of Agriculture to understand the financial position and performance of the US farm sector.

The authors find solvency ratios (which are indicators of the sector's ability to repay financial liabilities via the sale of assets) worsened in 2020 relative to pre-pandemic expectations. Efficiency ratios (which evaluate the conversion of assets into production and revenue) and liquidity ratios (which are indicators of the availability of cash to cover debt payments) showed mixed outcomes for the realized results in 2020 relative to the pre-pandemic forecasts. Four profitability ratios were stronger in 2020 relative to pre-pandemic expectations. All solvency, liquidity and profitability ratios plus 2 out of 5 efficiency ratios for 2020 were weaker than their respective average ratios obtained from 2000 to 2019 data.

This research is one of the first papers to use financial ratios to examine how the US farm sector performed in 2020 compared to expectations prior to the pandemic.

This study explores the influence of the coronavirus disease 2019 (COVID-19) career experience on the investment behavior and risk tolerance of chief executive officers (CEOs). Specifically, this study focuses on CEOs' abilities to allocate financial assets and maintain solvency.

This study adopts a comprehensive approach to analyze financial assets and asset-to-liability ratios. Financial data and individual information of CEOs from listed companies are collected from 2020Q1 to 2021Q4, along with statistics on confirmed COVID-19 cases. Instrumental and alternative variables are used to examine the robustness and endogeneity of the research, ensuring a thorough analysis.

A significant positive correlation is revealed between CEOs' COVID-19 career experience and their capacity to effectively allocate financial assets. However, COVID-19 has a negative effect on firm performance in terms of solvency. These findings contribute to the empirical evidence linking the pandemic to company performance, representing part of the initial research in this area.

The study suggests that the implementation of potential policy implications, such as loose monetary policies and tax and fee reduction measures, may alleviate the tax burden on listed companies.

Insurance companies play a significant role in every economy; hence, it is essential to investigate and understand the factors that propel their profitability. Unlike previous studies that present a linear relationship, this study provides initial evidence by exploring the non-linear impacts of the determinants of profitability amongst life insurers in South Africa.

The study uses a panel dataset of 62 life insurers in South Africa, covering 2013–2019. The generalised method of moments and the dynamic panel threshold estimation technique were used to estimate the relationship.

The empirical results from the direct relationship reveal that investment income and solvency significantly predict life insurance companies' profitability. On the other hand, underwriting risk, reinsurance and size reduce profitability. Further, the dynamic panel threshold analysis confirms non-linearities in the relationships. The results show that insurance size, investment income and solvency promote profitability beyond a threshold level, implying a propelling effect on life insurers' profitability at higher levels. Below the threshold, these factors have an adverse effect. The study further points to underwriting risk, reinsurance and leverage having a reduced effect on life insurers' profitability when they fall above the threshold level.

The findings suggest that insurers interested in boosting their profit position must commit more resources to maintain their solvency and manage their assets and returns on investment. The study further recommends that effective control of underwriting risk is critical to the profitability of the life insurance industry.

The study contributes to the literature by providing first-time evidence on the determinants of life insurance companies' profitability by way of exploring threshold effects in South Africa.

The paper's aim is to test the usefulness of ratio analysis to predict bankruptcy in a period of stability of an emerging economy, such as the case of Argentina in the 1990s.

Financial profiles of 22 bankrupt and healthy companies are examined and a model is built using the multiple discriminant analysis technique, thus providing comparability with previous studies.

The set of models tested in this paper show that the financial data of Argentine companies in the 1990s do have information content, but the model to use depends on the preferences of the decision maker. Comparing models it is observed a common use of solvency ratios in terms of total assets and profitability ratios in terms of sales.

Data availability constitutes the primary limitation of this and similar studies, here is reflected in the sample size: 11 healthy and 11 bankrupt.

The model can be used to assist investors, creditors, and regulators in Argentina and other emerging economies to predict business failure. The Z ′‐score model of Altman can be used for public companies in emerging economies because it pays attention to solvency indicators, but in rapid changing environment, profitability ratios should also be considered.

The incremental information content of profitability and solvency in predicting bankruptcy is examined and a simple and reliable failure prediction model for large Argentinean firms is developed. Also this paper offers a classification method that is publicly available to all investors and creditors interested in Argentinean companies.

This paper aims to use coordinated financial statements' system properties that include exogenous and endogenous variables to answer important questions. These questions include the following: What is the financial condition of the firm? What if there is a change in the firm's exogenous variable(s) – how will the financial condition of the firm change? And, how much of a change in the firm's exogenous variable(s) is required for the firm to reach its financial goal(s)?

This paper uses coordinated financial statements to construct solvency, profitability, efficiency, liquidity and leverage (SPELL) ratios to answer the question: what is the financial condition of the firm? It answers what-if questions by changing an exogenous variable(s) and recalculating SPELL ratios. It answers how-much questions by using Excel's Goal Seek algorithm to find the required change in an exogenous variable to reach a firm's goal.

The authors find that coordinated financial statements' system properties can be used to answer important what-is, what-if and how-much questions about the firm.

The usefulness of coordinated financial statements' system properties to answer what-is, what-if and how-much questions about the firm depends – mostly on the accuracy of exogenous data used to represent the firm's external financial environment. Furthermore, the usefulness of what-if and how-much analysis depends on how appropriate the changes are in exogenous variables used to represent alternative scenarios.

Using coordinated financial statements' system properties to answer what-is, what-if and how-much questions provides the firm's financial manager the tools to not only asses the firm's current financial condition but also to assess its ability to respond to opportunities and threats posed by future scenarios.

The ability to assess the financial condition of a firm and to assess its strengths and weaknesses in key to making sound financial decisions. In addition, the consistency imposed on coordinated financial statements makes it an effective tool for discovering errors in its data.

The authors know of no similar work.

While the passage of Statement No. 34 by the Governmental Accounting Standards Board (GASB, 1999) created a more robust financial reporting model, local officials continue to struggle with defining financial condition, interpreting it from annual financial statements, and communicating it in a systematic way. This review presents a framework for analyzing, interpreting, and communicating financial condition within the fund and government-wide reporting structure. It specifically responds to the void in the public administration literature for a manageable, yet comprehensive, approach to financial condition analysis. The goal is to help local officials conceptualize financial condition from the interpretation of resource flow and stock as presented in annual financial statements.