scholarly journals Bonds Between Earnings Management and Corporate Financial Stability in the Context of the Competitive Ability of Enterprises

2021 ◽  
Vol 13 (4) ◽  
pp. 167-184
Author(s):  
Katarina Valaskova ◽  
Ane-Mari Androniceanu ◽  
Katarina Zvarikova ◽  
Judit Olah
Keyword(s):  
Earnings Management ◽  
Financial Distress ◽  
Financial Stability ◽  
Statistical Technique ◽  
Earnings Manipulation ◽  
Financial Health ◽  
Chi Square ◽  
Multivariate Statistical ◽  
Financial Strength ◽  
Chi Square Test

The financial health of enterprises and their continued profitability and competitiveness in the market are influenced considerably by the level of earnings achieved. Enterprises are forced to report the best possible results to demonstrate financial strength and competitiveness and to provide a good accounting for investors and creditors. Thus, the main objective of the study is to investigate whether there is any mutual dependence between corporate financial stability and earnings management. To measure these categories, Altman’s Z score was used to determine the financial health of enterprises, and the Beneish M-score and modified Jones model were applied to detect earnings manipulation. Using the chi-square test, the results revealed a statistically significant dependence between financial distress and earnings manipulation. Then, a multivariate statistical technique of correspondence analysis was applied to the categorical data to find categories of factors that are mutually correspondent. Based on a dataset of 11,105 enterprises operating in the Visegrad countries, the results found that enterprises that are threatened by bankruptcy or located in the gray zone tend to manipulate their earnings to maintain credibility, creditworthiness, and competitiveness. Because the financial health of an enterprise provides a potential incentive for earnings manipulation, state authorities, regulators, and policy-makers may benefit from the findings of the study.

scholarly journals Using Piotroski F-Score for Assessing Financial Health: Evidence from Leading Indian Private Banks

2021 ◽  
Vol 8 (S1-Feb) ◽  
pp. 117-132
Author(s):  
S Rangapriya ◽  
J Meenakumari
Keyword(s):  
Financial Distress ◽  
Investment Decision ◽  
Relative Strength ◽  
Valuable Insight ◽  
Financial Health ◽  
Investment Decision Making ◽  
Financial Strength ◽  
Private Banks ◽  
Level Analysis

This research investigates the efficacy of Piotroski F-score to screen firms with good financial health and to identify early signs of financial distress in Indian banking stocks. This study complements existing empirical evidence which indicate that the venerable model can provide valuable insight for investment decision making and risk management.The evidence is drawn from valuation signals across leading private banks in India for a period ranging from 2014-2020. Piotroski F-score evaluates companies with a discrete number between zero and nine, the score facilitates determination of financial strength of the company. Higher score indicates better financial health and viceversa. The F-score is calculated as a sum of criteria which evaluates profitability signals, leverage and liquidity, sources of funds and operating efficiencies. In this study, each of these ratios have been analyzed to gain valuable insight on the banks (company-level). Analysis of Variance (ANOVA) of various ratios, ascertains intensity of relationship across banks (industry-level). This can help manage exposure in the portfolio as per the economic environment.The Piotroski F-score evaluates the generic financial health of the firm and indicates the direction in which the firm is headed. By studying individual factors, relative strength can be assessed. Piotroski F-score ranged between 0-7 for all the banks under study, indicating that none of them were a ‘compellingbuy’ (score 8 or 9) over the seven-year horizon. Some banks have consistently shown depleting F-score over at least 3 years, this can be interpreted as a signal of financial distress. It is evident that consistent monitoring of F-score empowers pro-active risk management.This work attempts to introduce Piotroski F-score as an integral valuation metric in evaluating Indian banking stocks. F-score can be used for initial screening, it’s consistent monitoring can facilitate optimized returns at risk-adjusted levels.

PERBEDAAN EARNINGS MANAGEMENTBERDASARKAN UKURAN PERUSAHAAN: STUDI EMPIRIS PADA PERUSAHAAN YANG TERDAFTAR DI BEI

2010 ◽  
Vol 6 (2) ◽  
pp. 139
Author(s):  
Fensy Oktavia Komala
Keyword(s):  
Earnings Management ◽  
Stock Exchange ◽  
Discretionary Accruals ◽  
Company Size ◽  
Management Behavior ◽  
Chi Square ◽  
Chi Square Test

The purpose of this reseacrh is to investigate Earnings management differences accross companies according to its size. Previous researches show company size tend to affect earnings management behavior. Sample are collected from companies listed on Indonesian Stock Exchange year over 2003-2009. Using Chi-Square Test, the result shows that statistically there is no differences of Earnings management magnitude between small, medium and large companies. Keywords:  Earnings Management, Discretionary Accruals, Non Discretionary Acruals, Total Accruals.

scholarly journals Impacts of financial distress on real and accrual earnings management

2018 ◽  
Vol 22 (2) ◽  
pp. 222
Author(s):  
Danella Rachel Muljono ◽  
Kim Sung Suk
Keyword(s):  
Earnings Management ◽  
Financial Distress ◽  
Listed Companies ◽  
Production Costs ◽  
The Other ◽  
Real Earnings Management ◽  
Financial Health ◽  
Other Hand ◽  
Management Approaches ◽  
The Impact

This research investigates the impact of financial distress on the magnitude of different earnings management approaches, namely real earnings management and accruals earnings management. This research utilizes a total of 2002 firm-year observations from 259 publicly-listed companies and 20 sub-industries in Indonesia from the year 2005 to 2014. Financial distress causes a significant increase of real earnings management and a significant decrease of accruals earnings management. It means that the healthier the company, the bigger the magnitude of real earnings management that is conducted through managing production costs and discretionary expenses. On the other hand, the lower the financial health of the company, the bigger the magnitude of accruals earnings management that is conducted through managing discretionary component of accruals.

scholarly journals Being an outlier: a company non-prosperity sign?

Equilibrium ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. 359-375 ◽  
Author(s):  
Lucia Svabova ◽  
Marek Durica
Keyword(s):  
Financial Distress ◽  
Value Added ◽  
Financial Ratios ◽  
Financial Indicators ◽  
Chi Square ◽  
Equality Of Means ◽  
Statistical Hypotheses ◽  
Chi Square Test ◽  
Almost All ◽  
Difficult Situations

Research background: The state of financial distress or imminent bankruptcy are very difficult situations that the management of every company wants to avoid. For these reasons, prediction of company bankruptcy or financial distress has been recently in a focus of economists and scientists in many countries over the world. Purpose of the article: Various financial indicators, mostly financial ratios, are usually used to predict the financial distress. In order to create a strong prediction model and a statistically significant prediction of bankruptcy, it is advisable to use a deep statistical analysis of the data. In this paper, we analysed the real financial ratios of Slovak companies from the year 2017. In the phase of data preparation for further analysis, we checked the existence of outliers and found that there are some companies that are multivariate outliers because are significantly different from other companies in the database. Thus, we deeply focused on these outlying companies and analysed whether to be an outlier is a sign of financial distress. Methods: We analysed whether there are much more non-prosperous companies in the set of outlier companies and if their financial indicators are significantly different from those of the prosperous companies. For these analyses, we used testing of the statistical hypotheses, such as the test for equality of means and chi-square test. Findings & Value added: The ratio of non-prosperous companies between the outliers is significantly higher than 50 % and the attributes of non-prosperity and being an outlier are dependent. The means of almost all financial ratios of prosperous and non-prosperous companies among outliers are significantly different.

scholarly journals Dynamic Panel Estimate–Based Health Surveillance of SARS-CoV-2 Infection Rates to Inform Public Health Policy: Model Development and Validation (Preprint)

2020 ◽  
Author(s):  
James Francis Oehmke ◽  
Theresa B Oehmke ◽  
Lauren Nadya Singh ◽  
Lori Ann Post
Keyword(s):  
Public Health ◽  
Measurement Error ◽  
The United States ◽  
Statistical Technique ◽  
Health Surveillance ◽  
Dynamic Panel ◽  
Chi Square ◽  
Data Contamination ◽  
Persistence Rate ◽  
Chi Square Test

BACKGROUND SARS-CoV-2, the novel coronavirus that causes COVID-19, is a global pandemic with higher mortality and morbidity than any other virus in the last 100 years. Without public health surveillance, policy makers cannot know where and how the disease is accelerating, decelerating, and shifting. Unfortunately, existing models of COVID-19 contagion rely on parameters such as the basic reproduction number and use static statistical methods that do not capture all the relevant dynamics needed for surveillance. Existing surveillance methods use data that are subject to significant measurement error and other contaminants. OBJECTIVE The aim of this study is to provide a proof of concept of the creation of surveillance metrics that correct for measurement error and data contamination to determine when it is safe to ease pandemic restrictions. We applied state-of-the-art statistical modeling to existing internet data to derive the best available estimates of the state-level dynamics of COVID-19 infection in the United States. METHODS Dynamic panel data (DPD) models were estimated with the Arellano-Bond estimator using the generalized method of moments. This statistical technique enables control of various deficiencies in a data set. The validity of the model and statistical technique was tested. RESULTS A Wald chi-square test of the explanatory power of the statistical approach indicated that it is valid (χ<sup>2</sup><sub>10</sub>=1489.84, <i>P</i>&lt;.001), and a Sargan chi-square test indicated that the model identification is valid (χ<sup>2</sup><sub>946</sub>=935.52, <i>P</i>=.59). The 7-day persistence rate for the week of June 27 to July 3 was 0.5188 (<i>P</i>&lt;.001), meaning that every 10,000 new cases in the prior week were associated with 5188 cases 7 days later. For the week of July 4 to 10, the 7-day persistence rate increased by 0.2691 (<i>P</i>=.003), indicating that every 10,000 new cases in the prior week were associated with 7879 new cases 7 days later. Applied to the reported number of cases, these results indicate an increase of almost 100 additional new cases per day per state for the week of July 4-10. This signifies an increase in the reproduction parameter in the contagion models and corroborates the hypothesis that economic reopening without applying best public health practices is associated with a resurgence of the pandemic. CONCLUSIONS DPD models successfully correct for measurement error and data contamination and are useful to derive surveillance metrics. The opening of America involves two certainties: the country will be COVID-19–free only when there is an effective vaccine, and the “social” end of the pandemic will occur before the “medical” end. Therefore, improved surveillance metrics are needed to inform leaders of how to open sections of the United States more safely. DPD models can inform this reopening in combination with the extraction of COVID-19 data from existing websites.

scholarly journals Role of Education in Empowering Women: A Case Study

2018 ◽  
Vol 7 (1) ◽  
pp. 16-20
Author(s):  
Bhajan Chandra Barman
Keyword(s):  
West Bengal ◽  
Secondary Data ◽  
Structured Interview ◽  
Statistical Technique ◽  
Primary Data ◽  
Great Contribution ◽  
Chi Square ◽  
Use Of Resources ◽  
Chi Square Test

According to Census Report 2011, nearly 50% of the population of our country are women. They have a great contribution in society. Therefore, we cannot deny the importance of them. In spite of great contribution in society, the women are less empowered in every field of society. The conception of empowerment is based on the notion of power; empowerment by definition means “enabling”, “giving, receiving or obtaining power” or “giving the official or legal authority or the freedom to do something”. In addition, empowerment is defined as the equalization of power and the more efficient use of resources Women’s education leads to empowerment. There are two reasons behind selecting the topic “Role of Education in Empowering Women” for the present study. Firstly, there has been no found any comparative study in the review of literature regarding the measurement of empowerment between educated and uneducated women. Secondly, no literature has been found on education and women empowerment in the study area. The present paper fulfills this research gap. Dinhata block-II of Cooch Behar district, West Bengal has been selected for the purpose of the study. The study is based on both primary and secondary data. Primary data have been collected from a field survey in Dinhata block-II of Cooch Behar district, West Bengal. Secondary data have also been collected from various journals, articles, working papers and education related website. For study purpose it has been selected 200 women from the study area. Among them 100 are educated and the rest 100 women are uneducated. A structured interview schedule was prepared and used for collecting data from the respondents in the study area. To analyse the results a simple statistical technique like percentage has been used. To compare the results, Chi-square test has been used. In the present study, it has been considered nine indicators to measure empowerment between educated and uneducated women. From the results and discussion it has been observed that educated women are more empowered as compare to uneducated one. Chi-square Test shows the significance difference between educated and uneducated women regarding empowerment. Thus, it can be conclude that education is very important factor in empowering women.

scholarly journals Assessment of Performance of Students using Conditional Statistical Technique

2020 ◽  
Vol 9 (5) ◽  
pp. 1025-1031
Keyword(s):  
Student Performance ◽  
Educational Data Mining ◽  
Statistical Technique ◽  
Chi Square ◽  
Factors Affecting ◽  
Chi Square Test ◽  
Student’S Performance ◽  
Low Performance ◽  
Improving Student Performance ◽  
Pie Chart

Educational data mining (EDM) is gaining importance in every field. Due to the competency in every branch of engineering, the institutions are concentrating mainly on improving the performance of students. Efforts are also put towards knowing the reasons for low performance and identifying the factors affecting the student’s performance. Researchers are working on preparing predictive models for improving student performance. The present study is considering the educational data of 1186 students. The data is classified as demographic and study related variables. An effort is made to predict the student performance, using a statistical technique – Chi Square test. The attributes affecting and not affecting the performance of students are assessed. The results are plotted using Pie Chart and histograms. The association between demographic and education variables with semester results is tabulated.

scholarly journals KNOWLEDGE AND ADOLESCENT ATTITUDE OF SMK COKROAMINOTO MANADO ABOUT REPRODUCTIVE HEALTH

2018 ◽  
Vol 6 (2) ◽  
pp. 91-98
Author(s):  
Susanti V. Umar ◽  
Monica S. Tandiayuk ◽  
Nurseha S. Djaafar
Keyword(s):  
Reproductive Health ◽  
Total Sample ◽  
Statistical Technique ◽  
Female Students ◽  
Measuring Instruments ◽  
Chi Square ◽  
Cross Sectional ◽  
Adolescent Attitudes ◽  
Chi Square Test ◽  
Knowledge And Attitude

Background: Knowledge of reproductive health for adolescents is very important. Based on the nursing problems at the Cokroaminoto Manado Vocational School found in interviews with 5 female students, it shows that female students do not yet know about problems that often occur in reproductive health such as sexually transmitted diseases (STDs) and how to maintain healthy hygiene reproduction. Objective: This study was to determine the relationship of knowledge with adolescent attitudes about reproductive health at SMK Cokroaminoto Manado. Method: This type of research is analytic with a cross-sectional approach using a total sample technique to obtain 30 female teenage respondents at the time of the study. The statistical technique used is the Chi-square test with significance value ≤0.05. Measuring instruments used are knowledge and attitude questionnaires. Results: The test results obtained by the Pearson Chi-square test obtained value x ² = 15,200 with p (asmp.sig) = 0.001 <0.05 means significant, so H0 is rejected and Ha is accepted. Conclusion: There is a relationship between knowledge and adolescent attitudes about reproductive health at SMK Cokroaminoto Manado. Suggestions for young women to seek more information about reproductive health so that the knowledge of adolescent girls increases.

scholarly journals Combining Regression and Factor Analysis for Use in Agricultural Economics Research

1976 ◽  
Vol 8 (2) ◽  
pp. 145-149
Author(s):  
John T. Scott
Keyword(s):  
Time Series Data ◽  
Correlation Coefficients ◽  
Ordinary Least Squares ◽  
Statistical Technique ◽  
Regression Coefficients ◽  
Series Data ◽  
Least Squares Regression ◽  
Chi Square ◽  
Explanatory Variables ◽  
Chi Square Test

While ordinary least squares regression has become a standard statistical technique, there are problems frequently overlooked or ignored by researchers in applying this statistical method. Two basic assumptions of the OLS regression model—(1) that the explanatory variables are independent of each other and (2) that the explanatory variables are known, fixed numbers—do not hold for most economic data, particularly time series data. This has been a consternation for econometricians, if not for the general researcher, for many years.In the case of nonindependence of explanatory variables (multicollinearity), signs of the regression coefficients often are inconsistent with economic theory and with correlation coefficients calculated from the data. Also, variances of the estimated regression coefficients are inconsistent. In practice for prediction equations, multicollinearity can usually be sufficiently reduced by either dropping one or more multicollinear variables or by indexing them and using the index as a regressor, thus circumventing the assumption regarding independence of the explanatory variables. A chi-square test for multicollinearity is available, and can be used as a guide to alert a researcher to the problem.

scholarly journals Dynamic Panel Estimate–Based Health Surveillance of SARS-CoV-2 Infection Rates to Inform Public Health Policy: Model Development and Validation

10.2196/20924 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e20924 ◽  
Author(s):  
James Francis Oehmke ◽  
Theresa B Oehmke ◽  
Lauren Nadya Singh ◽  
Lori Ann Post
Keyword(s):  
Public Health ◽  
Measurement Error ◽  
The United States ◽  
Statistical Technique ◽  
Health Surveillance ◽  
Dynamic Panel ◽  
Chi Square ◽  
Data Contamination ◽  
Persistence Rate ◽  
Chi Square Test

Background SARS-CoV-2, the novel coronavirus that causes COVID-19, is a global pandemic with higher mortality and morbidity than any other virus in the last 100 years. Without public health surveillance, policy makers cannot know where and how the disease is accelerating, decelerating, and shifting. Unfortunately, existing models of COVID-19 contagion rely on parameters such as the basic reproduction number and use static statistical methods that do not capture all the relevant dynamics needed for surveillance. Existing surveillance methods use data that are subject to significant measurement error and other contaminants. Objective The aim of this study is to provide a proof of concept of the creation of surveillance metrics that correct for measurement error and data contamination to determine when it is safe to ease pandemic restrictions. We applied state-of-the-art statistical modeling to existing internet data to derive the best available estimates of the state-level dynamics of COVID-19 infection in the United States. Methods Dynamic panel data (DPD) models were estimated with the Arellano-Bond estimator using the generalized method of moments. This statistical technique enables control of various deficiencies in a data set. The validity of the model and statistical technique was tested. Results A Wald chi-square test of the explanatory power of the statistical approach indicated that it is valid (χ210=1489.84, P<.001), and a Sargan chi-square test indicated that the model identification is valid (χ2946=935.52, P=.59). The 7-day persistence rate for the week of June 27 to July 3 was 0.5188 (P<.001), meaning that every 10,000 new cases in the prior week were associated with 5188 cases 7 days later. For the week of July 4 to 10, the 7-day persistence rate increased by 0.2691 (P=.003), indicating that every 10,000 new cases in the prior week were associated with 7879 new cases 7 days later. Applied to the reported number of cases, these results indicate an increase of almost 100 additional new cases per day per state for the week of July 4-10. This signifies an increase in the reproduction parameter in the contagion models and corroborates the hypothesis that economic reopening without applying best public health practices is associated with a resurgence of the pandemic. Conclusions DPD models successfully correct for measurement error and data contamination and are useful to derive surveillance metrics. The opening of America involves two certainties: the country will be COVID-19–free only when there is an effective vaccine, and the “social” end of the pandemic will occur before the “medical” end. Therefore, improved surveillance metrics are needed to inform leaders of how to open sections of the United States more safely. DPD models can inform this reopening in combination with the extraction of COVID-19 data from existing websites.

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