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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 aims to examine the relationship between objective and subjective aspects of financial well-being, the role of family financial support and depression symptoms of Chinese older adults.

This study used two waves (2015 and 2018) of the Harmonized China Health and Retirement Longitudinal Study. Two financial ratios: the expenditure-to-income ratio and the financial assets ratio, were used to measure the objective aspect of financial well-being. Perceived money management difficulty was employed to measure the subjective aspect of financial well-being. Depression symptoms were measured using the Center for Epidemiologic Studies Depression Scale (CES-D) score. Three analytical models, including an ordinary least squares (OLS) model, an OLS model controlling for lagged depression and a random effects model using panel data, were used to examine the relationships between the objective and subject aspects of financial well-being and depression.

The results from the three models showed consistent relationships: the expenditure-to-income ratio was a positive contributor, while the financial assets ratio was a negative contributor to depression of older adults in China. The robustness check using binary-coded financial ratio thresholds showed that reaching the suggested thresholds was negatively associated with depression. Perceived money management difficulty contributed positively to depression. The robustness check using the fixed effects model showed no significance of the two ratios, while perceived money management difficulty was positively associated with depression. The insignificance might be due to data limitation (limited waves or rare changes across waves).

The findings indicate that both objective and subjective financial well-being matters in relation to depression symptoms and, therefore, to the overall mental health of the Chinese elderly. Developments in public policies are needed to promote accessible financial services, assistance programs, mental health services and facilities for the older population in China.

The study seeks to find the effect of financial leverage on the firm performance of non-financial companies listed in the Tokyo stock market.

The study collected data from 263 companies in the automobile and industrial producer sectors listed on the Tokyo stock exchange between 2001 and 2021. The generalized method of moments was used to estimate the effect of leverage on financial performance due to its ability to overcome the problems of endogeneity and autocorrelation.

The study found that the equity multiplier has a positive and statistically significant effect on return on assets (ROA), return on equity (ROE) and earning per share (EPS). The study discovered that the interest coverage ratio has a positive and statistically significant effect on ROA, ROE, EPS and Tobin’s Q. The results revealed that the degree of financial leverage and debt to earnings before interest, taxes, depreciation and amortization (EBITDA) have a negative and statistically significant effect on ROE, EPS and Tobin’s Q. The study also found that the capitalization ratios of the firms have a negative and statistically significant effect on ROA, ROE, EPS and Tobin’s Q.

The use of debt financing, which presents financial leverage, indicates that the companies can make enough earnings to pay off the interest and principal (debt service obligations), which were shown by the interest coverage ratio, as well as to pay all the long-term fixed expenses, which were shown by the fixed charge coverage ratio. Interest and fixed charge coverage have a positive statistically significant effect on the financial performance of automobile and industrial producer companies.

The study focused on the effect of financial leverage on financial performance by relying on pecking and trade-off theories to contribute to the existing body of literature in finance.

This study aims to explore and verify the influence of the corona pandemic on the stock returns of the Palestinian companies listed on the Palestine Exchange during the period 2020–2021.

The research makes use of secondary financial data from 52 companies in the industrial, investment, services, banking and insurance sectors. Many financial ratios are calculated to assess stock returns: current ratio, cash ratio and average collection time as liquidity measures; debt-to-equity ratio as an indication of leverage or solvency; and net profit margin as an indicator of profitability. The research examines ratios between the (2020 and 2021) precorona outbreak using the Wilcoxon signed rank test and financial ratio analysis during the corona pandemic.

The findings show that liquidity in the investment, banking, insurance and industrial sectors has decreased significantly, whereas liquidity in the service sector has improved. The statistics reveal a considerable growth in debt in the service sector, while it stays unchanged in the other sectors. However, there is no discernible change in profitability during and after the corona outbreak.

The present research faced many limitations, such as the approach to gathering primary data, which depended heavily on disclosures, financial reports and secondary data, as well as only analyzing one context and one country.

The findings of this study can guide the Palestinian government and decision-makers to respond to the COVID-19 outbreak and must act quickly because strong short-term policies are more functional than long-term policy measures. In addition, the temporal discrepancy between their policy actions and financial regulations regarding the stage of the outbreak, integrating monetary treatment methods, strengthening their control over exchange rate fluctuations and extending the duration of financial participation measures that ensure stable exchange rates, such as attempting to restrict trade of the monetary system between countries was assessed to reduce the important monetary stimulation policy.

This study presents important facts and results for regulators and decision-makers regarding the investment, industry, banking, insurance and services sectors as sectors that are most affected by the corona pandemic as a sample for this study from the Palestinian companies listed in Palestine Stock Exchange due to the corona pandemic.

This study empirically investigates the relationship between goodwill assets and capital structure (i.e. debt ratio) of firms and the moderating effect of financial market development on the relationship between goodwill assets and capital structure.

This research applied a quantitative method. The article collects large samples of listed firms from 23 developing and nine developed countries and applied the panel data techniques. This research used firm-level data from the DataStream database for both developed and developing countries. The study uses 4,912 firm-level data from 23 developing countries and 4,303 firm-level data from nine developed countries.

The findings reveal a significant positive relationship between goodwill assets and capital structure in developing countries, but goodwill assets have a significant negative relationship with capital structure in developed countries. Moreover, financial market development positively moderates the relationship between goodwill assets and the capital structure of firms in developing countries. The results inform firm managers that goodwill assets serve as additional collateral to secure debt financing. Moreover, policymakers should formulate a debt market policy that recognizes goodwill assets as additional collateral for the purpose of obtaining debt capital.

The study has several implications. First, goodwill assets are identified as a factor of capital structure in this study. Fixed assets have been identified as one of the drivers of capital structure in previous research, although goodwill assets are seldom included. Second, this article shows that along with demand-side determinants, supply-side determinants also play an important role in terms of the firms' choice about the capital structure. Therefore, firms should take both the demand-side and supply-side factors into consideration when sourcing for external financing (i.e. debt capital).

The study considered goodwill as a component of capital structure. The study analysis includes a large sample of enterprises, including 4,912 big firms from 23 developing countries and 4,303 large firms from nine industrialized or developed countries, which adds to the current capital structure information. Furthermore, a large sample size increases the results' robustness and generalizability.

This study is conducted to determine the factors that affect profitability in Chinese listed companies (by using financial ratios). Four independent variables liquidity, intangible assets, working capital and company leverage were empirically tested for their relationships with profitability besides two control variables which are firm size and company efficiency.

This study used secondary data extracted manually from the annual reports of non-financial Chinese listed companies on the Shanghai stock exchange (http://www.szse.cn/); the data set covers 100 companies during the period of 2017–2019, and a random selection method was used in order to achieve credibility and fairness as much as possible.

The findings show firm size, working capital and intangible assets have positive and significant relationships with profitability [return on assets (ROA) and earnings per share (EPS)]. Positive working capital is important to lower the cost of capital and improve companies' profitability. Intangible assets are also an essential source to improve profitability due to their low costs. In addition, the findings display a negative and strong relationship between liquidity and profitability, meaning that companies suffer low profit due to inefficient use of liquid items. Interestingly, leverage, which is measured by debt ratio and leverage ratio, shows mixed results; debt ratio shows a positive and strong association with ROA but not with EPS; while leverage ratio displays a strong but negative association with ROA but not with EPS. These results confirm the inverted U-shape relationship between leverage and profitability, which depends on the balance between benefit and cost of debt.

Profitability is also important for employees and society where business organization provides sustainability and stability for both of them. Employees can then significantly contribute to achieve higher firm's profitability by efficiently using firm's resources.

This study differs than previous studies in number of aspects: First, this study focuses on financial ratios to explain profitability in Chinese companies. This study provides empirical results about the factors connected to profitability and help stakeholders to make their right decisions. Second, it examines the impact of four independent factors and two control variables that some of them are new in Chinese context such as intangible assets. Third previous studies focus on financial industry such as banks; however, this study focuses on non-financial industry.

This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

The objective of this study is to investigate how the coronavirus disease 2019 (COVID-19) pandemic affects firms' financial management in China's manufacturing sector. In addition, the authors analyze the changes in various financial indicators before and during the COVID-19 pandemic. Further, the authors make a cross-country comparison of the COVID-19's impact on financial management between China and Romania.

The study uses the balanced panel data of 2,272 manufacturing listed companies from 2019 to 2020, and applies the t-test method and multiple regression method.

The results show that firms' financial performance in most manufacturing sub-sectors decreased during the observed period. In addition, the authors find that equity financing, proper liquidity management and an expanded firm scale can improve firms' financial performance. The authors further compare the results with the Romanian results, and find that the negative impact of debt-to-equity ratio on firms' financial performance in Romania is greater than that in China and the positive impact of financial autonomy ratio and working capital ratios is greater in China than that in Romania.

The findings can help corporate managers make the best financial management decision in response to crisis.

This study is one of the pioneers that analyze how manufacturing companies carried out their financial management during the COVID-19 crisis in the Chinese context, and provides a cross-country analysis of corporate financial management practices in China and Romania.

Emerging market multinational companies have been vigorous in pursuing inorganic growth through cross-border acquisitions (CBAs). The fundamental studies till now have portrayed that rapid internationalization through CBAs tends to create value for these emerging market firms (EMFs) in the short term. However, there is an ambiguity about whether these firms endure better performance in the long term. The purpose of this study is to assess the long-term (ex-post) financial and operating performance of EMFs involved in overseas acquisitions before the COVID-19 pandemic hit the world economy.

CBAs completed by Indian and Chinese companies constitute the sample of the study. The performance has been analysed during the pre-COVID period spanning 17 years from 2001 to 2017. A comprehensive set of 14 financial ratios has been used to represent change (improvement/decline) in enterprises’ post-acquisition operating performance; these ratios have been divided into four broad groups: profitability, efficiency, solvency and liquidity ratios.

The performance of Indian companies has deteriorated significantly after the acquisition. However, there has been no change (deterioration/improvement), subsequent to CBAs, in the profitability of Chinese firms.

The findings of the study support that firms from emerging economies exploit CBAs as a “springboard” to obtain strategic assets including intangible resources and brands rather than to achieve synergies through economies of scale and scope. Apparently, outbound acquisitions by emerging economy firms are not driven by cost-reduction or revenue-generation activities.

None of the studies, to the best knowledge of the authors, has carried out performance analysis using a comprehensive set of financial ratios. The comparative study of two emerging economies is another valuable addition to the existing literature. The study holds the potential to serve as the benchmark to assess the performance of CBAs executed after COVID-19.

This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.

The analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.

The study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.

In the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.

Public policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.

The research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.

The study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.