scholarly journals Does a Company’s Profitability Influence the Level of CSR Development?

2021 ◽  
Vol 13 (6) ◽  
pp. 3304
Author(s):  
Luis Otero-González ◽  
Pablo Durán-Santomil ◽  
Luis-Ignacio Rodríguez-Gil ◽  
Rubén Lado-Sestayo
Keyword(s):  
Economic Performance ◽  
Regression Models ◽  
Negative Relationship ◽  
Minimum Size ◽  
Panel Regression ◽  
Small Companies ◽  
Social Dimensions ◽  
Managerial Opportunism ◽  
Corporate Social ◽  
Panel Regression Models

The objective of this paper is to analyze the effect of economic and financial performance on Corporate Social Responsibility (CSR). For this reason, we have used the data from a sample made up of 662 companies, 146 registered as medium-sized or large and 516 as small or micro, highlighting the significant weight of small companies in the sample. CSR has been measured using an indicator estimated from the data gathered by way of a questionnaire containing information related with the economic, environmental, and social dimensions. The analysis has been conducted by estimating panel regression models with robust errors. The results show a negative relationship between economic performance and more CSR activities implemented, supporting the Managerial Opportunism Hypothesis. Furthermore, large companies under the pressure of stakeholders are more prone to implementing certain CSR actions than small ones, meaning that a minimum size is essential according to this research.

scholarly journals Factors Affecting the ProfitabilitFactors Affecting the Profitability of Indonesian Real Estate Publicly-listed Companiesy of Indonesian Real Estate Publicly-listed Companies

2017 ◽  
Vol 9 (1) ◽  
pp. 396
Author(s):  
John Francis T Diaz ◽  
Martha Christianie Tjokro Hindro
Keyword(s):  
Real Estate ◽  
Regression Models ◽  
Positive Relationship ◽  
Negative Relationship ◽  
Medium Size ◽  
Panel Regression ◽  
Sales Growth ◽  
Current Ratio ◽  
Specific Factors ◽  
Panel Regression Models

The research studies the relationship between eight firm-specific factors on the profitability of large-, medium-, and small-scale real estate Indonesian companies. The data uses forty-seven real estate companies listed in the Indonesian Stock Exchange from 2010 to 2014. The study utilized multiple linear panel regression models, namely, ordinary least squares (OLS), fixed effects (FE) and random effects (RE) in examining the effect on the return on asset of firm-specific factors, which include: number of days account receivables, number of days inventory, number of days of account payable, size of the company, current ratio, debt ratio, sales growth, and tangibility. Empirical findings show that the number of days account receivable has negative relationship with profitability, but it has no effect on medium-size Indonesian real estate companies. The factor number of days inventories has negative relationship in small-size companies, but the inverse is true for large companies, because large real estate firms have more liquid assets that covers maintenance costs related to real estate inventories. Size and sales growth have positive relationship on profitability for both large and small Indonesian real estate firms. On one hand, current ratio has positive relationship in large companies, while a negative relationship was found in small companies, because of the lower current asset base usually being experienced by smaller real estate firms. Lastly, tangibility has negative relationship with profitability for large companies, while the opposite is true for medium-sized real estate firms. Findings of this research are strong in using two panel regression models, and can help real estate managers have a general perspective regarding determinants of profitability in the expanding Indonesian market. This study also provides fresh perspectives in creating suitable strategies to controlling factors that maximizes profitability.

scholarly journals Relationships between Renewable Energy and the Prevalence of Morbidity in the Countries of the European Union: A Panel Regression Approach

2021 ◽  
Vol 18 (12) ◽  
pp. 6548
Author(s):  
Robert Stefko ◽  
Beata Gavurova ◽  
Miroslav Kelemen ◽  
Martin Rigelsky ◽  
Viera Ivankova
Keyword(s):  
European Union ◽  
Renewable Energy ◽  
Statistical Methods ◽  
Regression Models ◽  
Kidney Diseases ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Panel Regression ◽  
The European Union ◽  
Panel Regression Models

The main objective of the presented study was to examine the associations between the use of renewable energy sources in selected sectors (transport, electricity, heating, and cooling) and the prevalence of selected groups of diseases in the European Union, with an emphasis on the application of statistical methods considering the structure of data. The analyses included data on 27 countries of the European Union from 2010 to 2019 published in the Eurostat database and the Global Burden of Disease Study. Panel regression models (pooling model, fixed (within) effects model, random effects model) were primarily used in analytical procedures, in which a panel variable was represented by countries. In most cases, positive and significant associations between the use of renewable energy sources and the prevalence of diseases were confirmed. The results of panel regression models could be generally interpreted as meaning that renewable energy sources are associated with the prevalence of diseases such as cardiovascular diseases, diabetes and kidney diseases, digestive diseases, musculoskeletal disorders, neoplasms, sense organ diseases, and skin and subcutaneous diseases at a significance level (α) of 0.05 and lower. These findings could be explained by the awareness of the health problem and the response in the form of preference for renewable energy sources. Regarding statistical methods used for country data or for data with a specific structure, it is recommended to use the methods that take this structure into account. The absence of these methods could lead to misleading conclusions.

scholarly journals PENGARUH CORPORATE SOCIAL RESPONSIBILITY TERHADAP KINERJA KEUANGAN PERUSAHAAN (Studi Empiris Perusahaan Sektor Pertambangan dan Pertanian yang Terdaftar Di Bursa Efek Tahun 2012-2014)

2017 ◽  
Vol 2 (02) ◽  
Author(s):  
Rachmat Harisianto ◽  
Dewi Sutjahyani
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Financial Performance ◽  
Economic Performance ◽  
Structural Equation ◽  
Stock Exchange ◽  
Negative Relationship ◽  
Partial Least Square ◽  
Least Square ◽  
Corporate Social

ABSTRACTThis research was conducted to analyze the effect of Corporate Social Responsibility performance indicators Economic, Environmental, and Social on financial performance. This study was made to determine how the implementation of Corporate Social Responsibility Financial Performance. The method used in this research is quantitative method and the population is a company mining and agricultural sectors listed in Indonesia Stock Exchange in 2012-2014, using data analysis SEM (Structural Equation Modelling) by the application program PLS (Partial Least Square) version 3.2. 1. Results obtained indicate that Corporate Social Responsibility (CSR) of the three indicators Economic Performance (KE), Environmental Performance (KL), Social Performance (KS) to the company's financial performance and Agriculture Mining sector not significant coefficient -0317 parameter Corporate social yangberarti responsibility (CSR) to the financial performance had a negative relationship which means no direction opposite relationship. Keywords: Influence of Corporate Social Responsibility of the three indicators Economic Performance, Environmental, and Social the Financial Performance.

scholarly journals Does ESG Disclosure Create Value to Firms? The Malaysian Case

2018 ◽  
pp. 515-521
Keyword(s):  
Social Norms ◽  
Regression Models ◽  
Financial Data ◽  
Panel Regression ◽  
Tobin’S Q ◽  
Publicly Traded ◽  
Tobin's Q ◽  
Publicly Traded Firms ◽  
Governance Disclosure ◽  
Panel Regression Models

We examine whether ESG (Environmental, Social and Governance) disclosure creates value to Malaysian firms. Based on the dataset of 37 Malaysian publicly traded firms, our results obtained from various panel regression models show that the overall ESG disclosure score and its environmental and governance pillars are positively associated with Tobin’s Q. This implies that Malaysian firms which act in accordance to social norms will be rewarded by the market. The outcomes of this research highlight the importance of non-financial data disclosure in Malaysian market.

Influence of tree cover and urban area on streamflow in the United States using multiple statistical attribution techniques

2021 ◽  
Author(s):  
Bailey Anderson ◽  
Louise Slater ◽  
Simon Dadson ◽  
Annalise Blum
Keyword(s):  
Land Cover ◽  
Urban Area ◽  
Regression Models ◽  
The United States ◽  
Additive Models ◽  
Tree Cover ◽  
Panel Regression ◽  
Distributional Regression ◽  
Panel Regression Models ◽  
Modelling Approaches

<p>There is still limited quantitative understanding of the effects of tree cover and urbanisation on streamflow at large scales, making it difficult to generalize these relationships. We use the globally consistent European Space Agency (ESA) Climate Change Initiative (CCI) Global Land Cover dataset to estimate the relationships between streamflow, calculated as high (Q0.99), median (Q0.50), and low (Q0.01) flow quantiles, and urbanization or tree cover changes in 2865 catchments between the years 1992 through 2018. We apply three statistical modelling approaches and examine the consistencies and inconsistencies between them. First, we use distributional regression models -- generalized additive models for location, scale, and shape (GAMLSS) -- at each site and assess goodness-of-fit. Model fits suggested a strong association between land cover, especially urban area, and low and median flows at sites with statistically significant trends in streamflow. We then examine the sign of the distributional regression model coefficients to determine whether the inclusion of a land cover variable in the regression models results in a relative increase or decrease in flow, regardless of the overall direction of trends in streamflow. Finally, we use fixed effects panel regression models to estimate the average effect across all sites. Panel regression results suggested that a 1% increase in urban area corresponds to between a < 1% and 2.1% increase in streamflow for all quantiles. Results for the tree cover panel regression models were not significant. We highlight the value of statistical approaches for large-sample attribution of hydrological change, while cautioning that considerable variability exists across catchments and modelling approaches.</p>

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