Regression Analysis Of Data Research Articles

Competition Plays A Moderating Role in The Impact of Liquidity Creation on Bank Capital

Introduction/Main Objectives: This study examines the moderating influence of bank competition, proxied by the Lerner index, on the impact of liquidity creation, measured using the Catfat method, on bank capital, proxied by the equity-to-total-assets ratio. Background Problems: Limited academic literature explores how competition moderates the relationship between liquidity creation and bank capital, which is essential for maintaining stability and risk absorption in the banking sector. Novelty: This study fills the gap by demonstrating that the effect of liquidity creation on bank capital depends on the level of bank competition. Research Methods: The study uses purposive sampling, covering 96 banks from 2013 to 2023, and applies panel data regression analysis with Hayes’ method. Control variables include ROA, LDR, NPL, GDP, inflation, and Bank Indonesia interest rates. Findings/Results: The results indicate that competition moderates the negative effect of liquidity creation on bank capital, weakening this impact. This suggests that competition enables banks to maintain higher capital levels. Conclusion: The study highlights the importance of competition in moderating the liquidity creation-capital relationship, with implications for bank management and regulatory policies.

Impact of auditor characteristics on audit quality during COVID-19: Evidence from Saudi Arabia

This study aimed to analyze the impact of auditor characteristics on audit quality in Saudi Arabia during the COVID-19 pandemic by assessing how auditor characteristics (such as gender, age, education level, professional certificate, sector, size of the employees, revenue, experience, and region) impact audit quality in crisis conditions. It employed a descriptive-analytical approach and quantitative regression analysis of cross-sectional data. The survey was conducted in 2021 among 203 auditors in Saudi Arabia. Data collection was facilitated through the assistance of the Saudi Organization for Chartered and Professional Accountants (SOCPA) to make the sample more structured and representative. The results reveal that auditor characteristics played a significant role in determining audit quality during the pandemic. Gender, education level, audit firm size, and professionalism experience showed a strong correlation (r = 0.619) between professional experience and adaptability to remote auditing conditions. The regression analysis indicates a positive impact on audit performance. The results suggest practical implications for improving auditor selection, training programs, and regulatory frameworks to enhance audit resilience in times of crisis. It offers theoretical contribution by validating existing models under pandemic conditions and providing insights for the future of auditing practices. It also assists in establishing confidence in financial reporting together with control, making investors feel secure, and maintaining stability in the business world.

Determining the prior mean in Bayesian logistic regression with sparse data: a nonarbitrary approach

Abstract Logistic regression models lead to a bias of the odds ratio (OR) as estimated using the maximum-likelihood (ML) method, when there are few study participants at the binary outcome and factor levels. Although Bayesian methods are frequently applied to reduce this sparse data bias, the specification of the prior distribution for regression coefficients is the most controversial feature. We propose a nonarbitrary and empirical method to determine the prior mean for regression coefficients in Bayesian logistic regression analysis for sparse data. The proposed prior mean is calculated as the difference between the observed log OR and the quasi-expectation of log OR, and is interpreted as a shrinkage statistic of the ML estimate. Further, for easy and fast inference, the proposed method applies to Bayesian logistic regression with the normal prior and the log-F prior via data augmentation. Simulation results indicate that the OR bias based on the proposed method is consistently smaller than that based on the ML method. The OR bias estimated using the proposed method is generally smaller than that based on the mean prior of zero for the regression coefficient. We apply the proposed methods to 2 real data sets.

Traffic safety at level crossings in the Czech Republic

The article deals with the issue of evaluation of the causes of accidents at level crossings in the Czech Republic, including the prediction of the development and proposals of measures for prevention and thus reduction of their number. The goal of this work is to verify the hypothesis that the number of accidents at level crossings in the Czech Republic is decreasing. The authors use available data from the Ministry of Transport and process statistical data for ten years (2013–2022) of railway operation. Accidents are divided into groups related to accidents at level crossings and the result is expressed in graphical form. These data are then processed and evaluated using the method of regression data analysis. The results of the work are also new proposals and recommended measures to reduce the accident rate at level crossings.

Regional deprivation and suicide mortality in Germany

Abstract Background Regional deprivation has been shown to be an important determinant of suicide risk. However, little is known about regional differences in suicide mortality in Germany. Methods Data from cause of death statistics (2015 to 2021) were analyzed. Regression analysis for data with negative binomial distribution was used to examine the association between the German Index of Multiple Deprivation 2015, covering 401 districts and district-free cities in Germany, and suicide mortality. Results The adjusted rate ratio for suicide in the most deprived deprivation area compared to the least deprived area was 1.18 (95% CI [1.72, 2.00]). A sensitivity analysis shows similar rate ratios for men (1.99 (95% CI [1.80, 2.18])) and women (1.69 (95% CI [1.49, 1.92])), but a higher rate ratio for rural areas (2.29 (95% CI [2.04, 2.57])) compared with urban areas (1.51 (95% CI [1.36, 1.68])). Conclusions The findings suggest that regional deprivation is associated with suicide mortality, and call for a more targeted approach to suicide prevention in deprived regions. Key messages • Study reveals higher suicide rates in deprived regions in Germany. • Study calls for tailored prevention strategies to address this disparity.

Examining the complex dynamics influencing acute malnutrition in Turkana and Samburu counties: Study protocol.

Acute malnutrition in children under 5 years is persistent in Eastern Africa's arid and semiarid lands. This study aimed to identify the drivers of acute malnutrition in Turkana and Samburu counties, Kenya. This was a population-based longitudinal mixed-methods observational study. Qualitative and quantitative data were collected at Wave 1, but only quantitative data were collected during follow-up. Participants were a representative sample of children and their primary caregivers from households with children under 3 years at Wave 1. Anthropometric measurements of all children under 5 years in the sampled households were taken at Wave 1 (May to July 2021), and one child under 3 years was randomly selected for follow-up about every 4 months over 2 years for six data collection waves. The study also collected data on sociodemographics; child feeding practices and morbidity; household water and food insecurity; shocks; coping strategies, social safety nets and economic safeguards; water, sanitation and hygiene; women's decision-making and food consumption. Qualitative data were collected through community dialogues, focus group discussions, in-depth interviews, photovoice and key informant interviews with mothers and fathers with children under 5 years, community leaders, county officials and staff of nongovernmental organisations. Data collection is complete and analysis is ongoing. The analysis includes thematic analysis of qualitative data and descriptive and multi-variable regression analyses of quantitative data.

Evaluating the effect of horizontal Integration strategy on performance of commercial State corporations in Kenya

This study aimed to evaluate the impact of horizontal integration on performance of Commercial State Corporations in Kenya. The study was based on positivist research philosophy. A cross-sectional correlational design was adopted as the study design. The target population was 1,026 senior managers of the Commercial State Corporations. The sample size was 99 senior managers in Commercial State Corporations. Primary data were gathered using a structured questionnaire. Collected data was analysed using descriptive data analysis techniques (Mean, Standard Deviation, Maximum and Minimum) and regression analysis. The findings of the study were presented using figures and tables. The study established a significant effect of horizontal integration strategy on financial, customers, internal business process and learning, growth and development performance of Commercial State Corporations in Kenya (? =0.536, p=0.000<0.05; ? =0.548, p=0.000<0.05;? =0.359,p=0.000<0.05;? =0.201,p=0.027<0.05). The study concluded that the horizontal integration strategy significantly improved the financial, customer, internal business process, and learning, growth, and development performance of Commercial State Corporations, supported by statistical evidence. The study recommends that Commercial State Corporations should streamline regulations to facilitate horizontal integration, ensure alignment with strategic objectives, prioritise sectors that enhance efficiency and service delivery, collaborate with competition authorities to comply with antitrust laws, and proactively address market concentration and anti-competitive concerns.

Green Accounting Performance on Profitability on The Indonesian Stock Exchange

The aim of this research is to investigate and analyze the impact of green accounting and Kinerja Lingkungan on the profitability of food and beverage companies listed on the Indonesia Stock Exchange (IDX) from 2018 to 2022. The sample, consisting of 8 companies, was determined using a purposive sampling method. The data utilized in this research comprise secondary data extracted from the annual reports of food and beverage companies listed on the Indonesia Stock Exchange (IDX) spanning the period 2018-2022. The analytical approach employed is panel data regression analysis, with the random effect model (REM) selected as the research model. According to the findings from the analysis conducted using Eviews (Econometric Views) version 12, it was discovered that the green accounting variable influences profitability. This is attributed to the perception of green accounting as a long-term investment for the company, wherein present expenditures can bolster the company's reputation. Conversely, the Kinerja Lingkungan variable does not impact profitability. Despite most companies receiving a blue rating, signifying compliance with environmental regulations, the results of Kinerja Lingkungan have not ensured an augmentation in the company's profitability.

Analisis Pengaruh Beban Pajak Kini, Beban Pajak Tangguhan, dan Aset Pajak Tangguhan Terhadap Manajemen Laba

This study aims to empirically determine the effect of current tax burden, deferred tax burden, and deferred tax assets on earnings management in automotive companies listed on the Indonesia Stock Exchange (IDX) during the 2018-2022 period. The research method used is a quantitative research method. The data used are secondary data, namely financial statements registered on the Indonesia Stock Exchange (IDX) from 2018 to 2022. The sample was selected using purposive sampling. Based on the determined criteria, a total of 6 automotive companies listed on the Indonesia Stock Exchange (IDX) from 2018 to 2022 were obtained. The analysis techniques used in this study are panel data regression analysis, panel data regression model testing, classical assumption testing, and the coefficient of determination test. The results of this study indicate that the current tax burden affects earnings management, while the deferred tax burden and deferred tax assets do not affect earnings management. Furthermore, the study found that simultaneously, the current tax burden, deferred tax burden, and deferred tax assets affect earnings management.

Coconut Testa Flour Sub-Fractions: Correlation Between FTIR Spectral Data and α-Glucosidase Inhibitory Activities

Fourier-transform infrared spectroscopy (FTIR) serves as a rapid analytical technique to characterize food specimens chemically. The purpose of this study was to investigate the potential of FTIR combined with multivariate statistics to detect Alpha-glucosidase (Alpha-glu) inhibitory activities of a non-cereal flour-like coconut testa flour (CTF). CTF of five distinct local cultivars was sequentially extracted with hexane, ethyl acetate (EtOAc), and methanol (MeOH) to assay the Alpha-glu inhibitory activity. FTIR spectra of CTF extracts were obtained within the range of 4000–500 cm−1 and the prominent spectral peaks obtained for both hexane and EtOAc extracts were roughly similar but some additional peaks were observed in EtOAc extracts representing phenolic constituents. The major absorbance peaks found in MeOH extracts were primarily indicative of the occurrence of the hydroxyl group associated with carbohydrates and phenolic compounds. The multivariate predictive models developed using partial least squares (PLS) and orthogonal partial least squares (OPLS) regression analyses indicated a strong correlation between Alpha-glu inhibitory activity and spectral data. Models developed for the spectral regions 3700–2800 cm−1 and 1800–500 cm−1 exerted the highest regression coefficients with the lowest root mean square errors. In OPLS regression analysis, the model obtained with third-derivative spectral data was identified as the best, exhibiting the highest regression coefficients and the lowest root mean square errors. Both PLS and OPLS regression analyses indicated a potential correlation of Alpha-glu inhibitory activity with FTIR spectral regions. Notably, OPLS models offered enhanced interpretability of the model parameters. This study suggests that the application of multivariate regression analysis of FTIR spectral data on coconut-based products could help to detect Alpha-glu inhibitory activities.

Pengaruh Pemahaman dan Kesiapan terhadap Penerapan Standar Akuntansi Keuangan Entitas Mikro Kecil dan Menengah (SAK EMKM) pada UMKM Jenis Perdagangan dan Reparasi di Kabupaten Ponorogo

Micro, Small and Medium Enterprises (MSMEs) in Indonesia are one of the priorities in national economic development. Therefore, reporting in this type of MSME business activity must be able to make systematic reports with the recording process following the applicable Financial Accounting Standards. So, there needs to be an understanding and readiness factor in preparing the report, so that SAK EMKM can be implemented in the management of MSMEs. This research aims to determine the effect of understanding and readiness for SAK EMKM on Trade and Repair MSMEs in Ponorogo Regency. This type of research uses primary data in the form of data on the number of trade and repair type MSMEs in 2021. This research method is a quantitative descriptive approach. Meanwhile, the data analysis method uses data quality testing, regression analysis, and hypothesis testing, while data collection is by distributing questionnaires and interviews. The results of this research show that there is a significant influence of understanding and readiness factors on the implementation of SAK EMKM in Ponorogo Regency. This means that the government needs to pay more attention or provide outreach/direction regarding the preparation of financial reports to MSME actors in Ponorogo Regency in accordance with applicable financial standards.

AGRIBISNIS KOPI DALAM MENDUKUNG PENGEMBANGAN AGROWISATA DI DESA COLOL, KECAMATAN LAMBA LEDA TIMUR, KABUPATEN MANGGARAI TIMUR (Coffee Agribusiness In Supporting Agrotourism Development In Colol Village, Lamba Leda Timur District, East Manggarai District)

Colol Village is a wilaya located in East Manggarai Regency, East Nusa Tenggara Province, which has good environmental and geographical characteristics, fertile soil and a suitable climate for coffee cultivation. The coffee varieties that are being developed are Arabica coffee and Robusta coffee. The people of East Manggarai have a cultural tradition that is close to coffee. The aim of this research is to analyze the factors that influence coffee production in Colol Village, determine farmers' perceptions of agrotourism development in Colol Village and describe the implementation of the coffee agribusiness system in Colol Village, East Manggarai Regency. This research used mixed methods with a sample size of 56 people using multiple linear regression data analysis methods, Likert scale analysis and descriptive qualitative analysis. The results of the research show that in coffee production the factors of land area, farming experience, farmer age, education level, household income, and coffee sales income level influence the development of agrotourism in Colol Village, East Manggarai Regency and based on Likert scale analysis, Colol coffee farmers agree with the development of coffee agrotourism in Colol Village and coffee production and agrotourism potential are related, the potential for coffee farming as a tourist attraction thereby strengthening the local economy and creating sustainable opportunities for the development of Colol village, East Manggarai

Stability Of Islamic Commercial Banks In Indonesia: Company Size, Profitability, And Efficiency

This study aims to analyze the effect of company size, profitability, and efficiency on the stability of Islamic commercial banks (ICB). This study uses a quantitative approach. The population of this study is Islamic commercial banks, and the sampling technique used is purposive sampling, obtained from four ICBs. The data source used is secondary data from each ICB's financial statements. The data analysis technique used is panel data regression analysis using e-views software version 13. The results of this study indicate that company size positively affects ICB's stability. However, profitability negatively affects ICB's stability. In contrast, efficiency does not affect ICB's stability. This study can complement existing theories, especially regarding the effect of size on company stability, and can be a reference for further research. Practically, this study can be a reference for banks in maintaining the stability of company operations in terms of company size and profitability.

Joint regression analysis of clustered current status data with latent variables.

Clustered current status data frequently occur in many fields of survival studies. Some potential factors related to the hazards of interest cannot be directly observed but are characterized through multiple correlated observable surrogates. In this article, we propose a joint modeling method for regression analysis of clustered current status data with latent variables and potentially informative cluster sizes. The proposed models consist of a factor analysis model to characterize latent variables through their multiple surrogates and an additive hazards frailty model to investigate covariate effects on the failure time and incorporate intra-cluster correlations. We develop an estimation procedure that combines the expectation-maximization algorithm and the weighted estimating equations. The consistency and asymptotic normality of the proposed estimators are established. The finite-sample performance of the proposed method is assessed via a series of simulation studies. This procedure is applied to analyze clustered current status data from the National Toxicology Program on a tumorigenicity study given by the United States Department of Health and Human Services.

The Influence of Return on Equity and Debt to Asset Ratio on Financial Distress in Properties Subsector Companies and Registered Real Estate on the Indonesian Stock Exchange Period 2015-2023

This research aims to determine the effect of return on equity and debt to asset ratio on financial distress. The research method used is an associative descriptive method with a quantitative approach. The population in this research is the Properties and Real Estate subsector companies listed on the Indonesia Stock Exchange for the 2015-2023 period. The sample for this research was determined using a Purposive Sampling technique and obtained 4 companies in the Properties and Real Estate subsector with an observation period of nine years to obtain 36 sample data. Hypothesis testing in this research uses panel data regression analysis using the E-Views 12 program and the confidence level used is 5%. The results of this research show that simultaneously return on equity and debt to asset ratio have a significant effect on financial distress with a significance of 0.0000 < 0.05 and f-count > f-table (34.14013 > 3.327654499) and the coefficient of determination using Adjusted R-Squared is equal to 61.73% while the remaining 65.44% was influenced by other variables not examined in this research. Meanwhile, partially return on equity has a significant positive effect on financial distress with a significance of 0.0018 < 0.05 and t-count > t-table (3.387986 < 2.04227), debt to asset ratio has a significant negative effect on financial distress with a significance of 0.0004 < 0.05 and t-count > t-table (|-3.912824| > 2.04227).

Causes of Audit Report Lag with Reputation of Audit Firm as a Moderating Variable

Audit report lag is an important problem because it can cause delays in submitting financial reports by companies to the OJK. This study examines the effect of audit opinion, profitability, and company size on audit report lag with Reputation of audit firm as a moderating variable in non-primary consumer goods companies listed on the IDX. The sample used in this study were 78 non-primary consumer goods companies listed on the IDX 2018-2022. The data analysis method used in this research is panel data regression analysis and moderation regression analysis. The results of this study indicate that audit opinion and profitability have a negative effect on audit report lag, while company size has no significant effect on audit report lag. Reputation of audit firm is able to strengthen the effect of profitability on audit report lag and weaken the effect of company size on audit report lag and but is unable to moderate the effect of audit opinion on audit report lag.

Friendshoring: how geopolitical tensions affect foreign sourcing, supply base complexity, and sub-tier supplier sharing

PurposeThis paper examines the influence of geopolitical tensions—operationalized as political divergence between governments—on firms’ foreign supply bases and the resulting effects on supply base complexity and sub-tier supplier sharing.Design/methodology/approachThe authors conduct panel data regression analyses over the period 2003–2019 to investigate whether political divergence affects foreign supply bases for 2,858 US firms sourcing from 99 countries and to examine how political divergence exposure impacts the supply network structures of 853 US firms.FindingsFirms reduce their supply bases in countries exposed to heightened geopolitical tensions. These supply chain adjustments are associated with increased supply base complexity and greater sub-tier supplier sharing.Originality/valueThis study highlights the importance of state relations in global supply chain reconfiguration. Political divergence between governments provides a dual-view of political risk (i.e. buyer–supplier countries), which can help firms anticipate geopolitical disruptions. While reducing supply bases in foreign countries facing heightened geopolitical tensions is intended to mitigate disruptions, these supply base adjustments are linked to increased supply base complexity and sub-tier supplier sharing, thereby exposing firms to other types of supply disruptions. Additionally, this research contributes to understanding the effects of geopolitical tensions on supply base complexity through the lenses of transaction cost economics and resource dependence theory.

Maximizing Profit Growth: How Net Profit Margin And Return On Assets Interact With Firm Size

This study aims to analyze the effect of net profit margin and return on assets on profit growth by adding firm size as a moderating variable in property and real estate companies listed on the Indonesia Stock Exchange. The population in this study comprises property and real estate companies listed on the Indonesia Stock Exchange from 2019 to 2023. The sampling technique is determined using purposive sampling based on criteria set by the researchers, resulting in a sample of 52 property and real estate companies. Panel data regression and moderated regression analysis (MRA) are used to analyze the data. The results of this study indicate that the net profit margin variable does not affect profit growth, while return on assets has a significant effect on profit growth. Furthermore, firm size can moderate the effect of net profit margin on profit growth. However, firm size cannot moderate the effect of return on assets on profit growth. Based on the results of this study, it is expected that future researchers can add other factors that may influence profit growth. In selecting moderating variables, it is hoped that future researchers will choose appropriate moderating variables to strengthen profit growth.

The Effect of Dividend Yield on The Volatility of Stock Prices of IDX30 Index Companies Listed on the Indonesia Stock Exchange for the 2019-2023 Period

This study investigates the influence of Dividend Yield on Stock Price Volatility in companies included in the IDX30 index on the Indonesia Stock Exchange (IDX) during the 2019-2023 period. Utilizing secondary data from annual reports of IDX30 companies, panel data regression analysis was conducted to examine the relationship between the variables. The findings reveal that Dividend Yield positively affects Stock Price Volatility, contradicting the initial hypothesis. The results indicate that an increase in Dividend Yield leads to higher Stock Price Volatility, while a decrease in Dividend Yield results in lower Stock Price Volatility. This research provides valuable insights for investors in understanding the dynamics between dividend policies and stock price fluctuations.

Navigating Economic Uncertainties: The Role of Technological Innovations in Enhancing Supply Chain Resilience

This study explores the multifaceted impact of economic indicators, financial market dynamics, and technological innovations on supply chain efficiency and resilience. Through comprehensive quantitative analyses, including panel data regression, multivariate regression, and time-series analysis, we dissect the relationship between GDP growth rates, inflation, unemployment rates, interest rate fluctuations, exchange rate volatility, stock market trends, and supply chain performance metrics. Our findings highlight a significant correlation between economic growth and supply chain efficiencies, the exacerbating effect of inflation and unemployment on supply chain costs and demand, and the nuanced impacts of financial market dynamics on supply chain financing and operational strategies. Moreover, we delve into the transformative potential of digitalization, automation, blockchain technology, and advanced analytics in mitigating risks associated with economic fluctuations and financial uncertainties. The empirical evidence suggests that technological innovations not only enhance supply chain resilience but also offer strategic advantages in navigating the complexities of global economic landscapes. This study underscores the critical need for adaptive strategies that leverage technological advancements to sustain supply chain competitiveness in an era of economic and financial volatility.