OLS Method Research Articles

Copula-Based Regression with Mixed Covariates

In this paper, we focused on developing copula-based modeling procedures that effectively capture the dependence between response and explanatory variables. Building upon the work of Noh et al. (J. Am. Stat. Assoc. 2013, 108, 676–688) we extended copula-based regression to accommodate both continuous and discrete covariates. Specifically, we explored the construction of copulas to estimate the conditional mean of the response variable given the covariates, elucidating the relationship between copula structures and marginal distributions. We considered various estimation methods for copulas and distribution functions, presenting a diverse array of estimators for the conditional mean function. These estimators range from non-parametric to semi-parametric and fully parametric, offering flexibility in modeling regression relationships. An adapted algorithm is applied to construct copulas and simulations are carried out to replicate datasets, estimate prediction model parameters, and compare with the OLS method. The practicality and efficacy of our proposed methodologies, grounded in the principles of copula-based regression, are substantiated through methodical simulation studies.

Depression in children: Impact of the father companionship and peer relationship

AbstractReasons for the increased incidence of depression in Chinese children remain poorly understood. Therefore, this study explored the influence of paternal companionship and peer relationships on depression in children based on OLS method using data reported by 2498 children from China (children Mage 10.7; 52.1% girls). We found that both variables could alleviate depression among children, but the effect of peer relationships was significantly greater than that of paternal companionship. This conclusion remains robust after considering gender, age and family structure. Heterogeneity studies have found that paternal companionship significantly impact boys, while peer relationships significantly impact girls. Mechanism analysis demonstrated that both factors can indirectly alleviate depression in children by regulating anxiety. Our research results emphasize the importance of increasing paternal companionship and peer relationships to alleviate depression in children.

Does Government Environmental Concern Affect Enterprise Sustainable Development? Evidence from China

As the executor and agent of China’s environmental policy, local governments’ environmental concern reflects local governments’ determination in environmental governance. To figure out how the strengthening environmental concerns affect enterprises’ long-term activities, this study focuses on pharmaceutical manufacturing enterprises due to the enormous and complex composition of emissions. We apply bag of words to summarize relevant environmental words from the annual work reports in local governments to measure environmental concern. The empirical results of the OLS method reveal that the increasing environmental concerns of local governments did decrease the growth rate of chemical oxygen demand (COD) emission authentically. At the same time, it will inhibit the research and experimental development (R&D) activity intensity, but promote production efficiency of pharmaceutical manufacturing enterprises. After that, we discuss the heterogeneity of enterprise ownership, corporate social responsibility and regional regulatory strength of enterprises. Overall, we conclude that environmental concern did reduce COD emission and promote production efficiency, but it also has negative spillover effects. The novel contribution of this paper is that it enriches the trade-off between strengthening environmental compliance costs and long-term production and innovation activities. These results indicate that pharmaceutical manufacturing enterprises prioritize optimizing existing production processes instead of adopting efficient technology when complying with stricter environmental regulation. The reduction of R&D activities may pose risks to the long-term sustainable development of enterprises.

The Factors Influencing Import of Raw Crystal Sugar From Thailand to Indonesia

This research aims to determine what factors influence the import of raw crystal sugar from Thailand to Indonesia. The method for determining regions is purposively used, namely, in Indonesia. The data collection method used in this research is secondary data. The data analysis method used is a multiple linear regression test with the Ordinary Least Square or OLS method. The results of this research are as follows: (1) The regression model used passed the classical assumption test, namely Multicollinearity, Heteroscedasticity, Autocorrelation, and Normality. (2). Factors that have a significant positive effect on the quantity of imported raw crystal sugar (raw sugar) from Thailand to Indonesia are GDP (gross domestic product) per capita. In contrast, one factor that significantly affects the number of imports of raw crystal sugar (raw sugar) from Thailand to Indonesia is the price of imported sugar. (3). Factors that do not significantly influence the quantity of raw crystal sugar imports from Thailand to Indonesia are sugar import tariffs and consumption rates

Determinants JCI of the Indonesian Stock Exchange (Comparison of IHSG Projection of OLS Method and ARIMA and GARCH Methods for the Period 2015-2023)

This study aims to examine the effect of interest rate, exchange rate, inflation, gross domestic product and LQ-45 index variables on the movement of the Composite Stock Price Index using the ordinary least square method. Comparison in predicting the movement of the stock price index through three models, and then compared with the projection results with OLS, ARIMA and GARCH methods. This research was conducted using monthly data on JCI, interest rates, exchange rates, inflation, gross domestic product and the LQ-45 index for the period May 2015 - December 2023. From the results it can be concluded that interest rates have a significant negative effect on JCI, exchange rates have a significant negative effect on JCI, inflation has a significant negative effect on the value of JCI, gross domestic product has a significant negative effect on JCI and the LQ-45 index has a positive effect on JCI. The results of the comparison of JCI projections with 3 models showed that the OLS model offers more accurate results and has the lowest MAPE value in predicting stock price movements.

The Impact of the ChatGPT Platform on Consumer Experience in Digital Marketing and User Satisfaction

ChatGPT, an artificial intelligence (AI) chat platform, facilitates conversation between humans and bots. By integrating machine learning and natural language processing, it revolutionizes the way people interact with AI. Many people are excited about using ChatGPT because it has numerous potential applications and advantages compared to other similar programs. Therefore, this paper demonstrates that, in line with specific ethical considerations, ChatGPT has enormous potential to revolutionize and shape the future of marketing. We begin by questioning whether ChatGPT has a significant impact on consumer experience in digital marketing and overall user satisfaction. The methods used in the study include descriptive and inferential statistical methods, as well as the OLS method. The results show that the use of ChatGPT is continuously rising and increasingly being implemented in various industry segments, particularly in the field of digital marketing. Automation of customer care, increased productivity, automated research, and better understanding of consumers are ways it can assist marketing professionals.

The Influence of Macroeconomic Variables on Non-Performing Finance in Sharia Commercial Banks

One of the advantages of the sharia banking business is financing productive sectors that do not contain haram elements. Financing in the micro, small and medium sectors is a sharia banking financing business line, but there is a big risk of bad credit. In recent years, increasing global and domestic economic uncertainty has led to depreciation of the exchange rate, unstable prices of basic commodities, thereby reducing people's purchasing power. This research aims to examine macroeconomic variables such as the exchange rate, inflation and production index as a proxy for GDP towards NPF of sharia banking. The research uses monthly time-series data and the OLS method. The research results show that macroeconomic variables have an influence on NPF. The research implication is that the stability of macroeconomic conditions can maintain people's purchasing power which can influence the NPF level of sharia banking.

Can issuing carbon neutral bonds promote low-carbon investment in renewable energy industry？

Guiding by the goal of carbon neutrality and carbon peaking, the importance of low-carbon finance in renewable energy industry is becoming increasingly prominent, and carbon neutral bond (CANB) is showing a strong development trend. This study explores the impact of CANB on low carbon investment (LOCI) in renewable energy industry based on the OLS method combined with the quarterly samples, and the following results are obtained. First, issuing CANB can lead to a 4.7 % increase in LOCI. Second, the higher the scale, duration, and rating of CANB, the more they can promote LOCI. Third, CANB may promote LOCI by strengthening corporate environmental responsibility and alleviating financing constraints, while CANB may reduce LOCI by increasing operational pressure. Fourth, CANB has a stronger promoting effect on the LOCI of large-scale firms, central state-owned firms, and eastern firms. Fifth, under the pressure of carbon peaking and public low-carbon attention, CANB has a higher promoting effect on LOCI. This study aims to provide policy implications for promoting low-carbon development of renewable energy firms.

The moderating role of governance on the nexus of financial crime and sustainable development

AbstractThis study aims to highlight the connection between good governance and financial crime to achieve optimal sustainable development for society. Governance issues are integral to a sustainable economy, as sustainability cannot be considered without strong measures to combat financial crime. The theoretical foundation of this relationship posits that enhanced institutional quality and laws reduce opportunities to circumvent environmental regulations, thereby improving the ecological footprint. This paper examines the moderating role of governance on the impact of four types of crime—corruption, shadow economy, money laundering, and cybercrime—on sustainable development indicators such as the Human Development Index, Environmental Performance Index, carbon dioxide emissions and greenhouse gas emissions. The sample includes 185 countries, analysed over the period from 2015 to 2022. Methodologies used range from the Pooled OLS method for panel data with interactions to panel threshold regression modelling. Our findings provide strong evidence of the mediating role of good governance in mitigating the negative impact of financial crime on sustainable development, potentially reducing it by up to half. This study offers insights into how improving governance can manage the environmental effects of financial crimes, thereby enhancing sustainable development and reducing financial and economic crime.

The role of training in the “school-to-work” transition in the Russian labour market

PurposeThe article aims to describe the role of training and examines the impact on the wages of university and college graduates.Design/methodology/approachWe use nationwide administrative data on university and college graduates in 2019. The population includes 1.3 million observations, of which 222,000 (∼16%) received training after graduation from an educational institution (from July 2019 to 2022). We used OLS and the “difference-in-differences” methods to estimate the returns to training. Estimates obtained using the DID method turned out to be several times smaller because they consider unobserved characteristics (abilities).FindingsWe obtained several key findings. First, the participation of graduates in training is high, despite their recent education. Second, undergoing training is conditional on the existence of wage returns. The results show a wage premium of 17.8% (OLS method) and 2.0% (DID method). Third, graduates from nonselective universities (with low state exam score) try to participate more actively in training to acquire missing knowledge and skills. The wage premium for graduates from nonselective universities is 19.1% (OLS method) and 5.1% (DID method). Fourth, there is a high return to training for graduates from socially relevant fields (education and healthcare), where training is regular and mandatory.Originality/valueThis paper is one of the first to estimate the involvement and returns to training for graduates using nationwide administrative data in Russia.

Digital agricultural technology services and farmers’ willingness to choose digital production technology in Sichuan province, China

IntroductionDigital agricultural technology service has the characteristics of high efficiency, convenience and flexibility, and plays an important role in the process of Chinese agricultural digitalization, which is of great significance for realizing the modernization and intelligent development of agricultural production.MethodsBased on micro-survey data of small-scale farmers in Sichuan Province, this study utilizes the OLS method and the mediation effect model to investigate the impact of digital agricultural technology services on farmers’ willingness to adopt digital production technologies and its underlying mechanisms.ResultsThe results indicate that digital agricultural technology services effectively enhance farmers’ willingness to adopt digital production technologies, especially among those engaged in cooperative. Further analysis of mechanisms suggests that digital agricultural technology services influence farmers’ choices of household production and management methods by expanding their information channels, enhancing their cognition of digital production technologies, and facilitating access to technology. Moreover, heterogeneous analysis reveals significant differences in the willingness of farmers with varying levels of digital literacy to adopt digital production technologies. Digital agricultural technology services have a more pronounced impact on the willingness of highly digitally literate farmers.DiscussionThe findings of this paper deepen our comprehension of the operational mechanisms of digital agricultural technology services in the context of agricultural development, and advocate for policy recommendations such as enhancing the supply of digital agricultural technology services, strengthening the role of new agricultural entities, improving farmers’ digital literacy training, and enhancing policy support systems.

Regional Climate Risk and Corporate Social Responsibility: Evidence from China

ABSTRACT Although firms suffer from regional climate risk in their production and operation, they are still highly expected by the public to play a leading role in addressing regional climate risk. In this paper, we study how regional climate risk affects corporate social responsibility (CSR). By constructing regional climate risk indicators and employing the OLS method to conduct empirical analyses, we find that regional climate risk can significantly promote CSR. Furthermore, regional climate risk can suppress firm’s cash flow, thereby exerting internal pressure on firms to assume CSR. Meanwhile, regional climate risk can raise higher public expectations for firms, imposing external pressure on them to assume CSR. We suggest that external pressure from the public plays a dominant role in CSR decision-making. Besides, we confirm that CSR can achieve a win-win goal for both firms and the public by mitigating the damage of regional climate risk on the firm’s long-term performance. We provide a new perspective for studying firm’s motivation to assume CSR under the influence of regional climate risk.

Health Security and Cybersecurity: Analysis of Interdependencies

The development of medical digital platforms with data on patients, medical institutions and medicines, the growing use of IoT devices in medicine, the development of telemedicine accelerated by the COVID-19 pandemic, the growth of big data-based treatment technologies – all this makes it necessary to ensure reliable cyberdefence in the field of public health, maintain the confidentiality of financial information of clinics and health insurance companies, protect databases with patient records from hacking, and ensure secure communication. The article uses economic and mathematical modelling to study the relationship between two well-known international indexes and their components: The Global Health Security Index (GHSI) and the Global Cybersecurity Index (GCSI) for 190 countries in 2021. The input base included 6 cybersecurity subindexes and 7 health security subindexes for 2021. Based on the iterative divisive k-means method, all countries were grouped into 3 clusters. The first cluster includes 55 countries (medium levels of the studied indexes), the second – 49 (high levels), the third – 86 (low levels). The feasibility of dividing into clusters and choosing their optimal number is substantiated by means of variance analysis. Via the methods of Sigma-restricted parameterisation, Univariate Tests of Significance, Pareto Chart of t-Values and correlation analysis, all factors, without exception, proved to be relevant. Due to the OLS method, multiple linear regressions describing the relationships between various components of these indexes and their integral values are generated. The statistical significance of the factors included in the model is confirmed, and the model itself is tested for adequacy and accuracy. On the basis of correlation analysis, existence and magnitude of statistical relationship between the components of these indexes are revealed. The strongest correlations are observed between the integral values of these indexes, as well as between pairs of subindexes: 1) Legal Measures (GHSI component) and Prevention (GCSI component); 2) Technical Measures (GHSI component) and Detection and Reporting (GCSI component). To identify the causal relationship between the groups of factors, a canonical analysis was carried out, which showed the GHSI parameters are causal and the GCSI parameters are resultant. The linear regression model showed a significant positive relationship between the GHSI and GCSI indexes.

Dynamics of Inflation in Indonesia: The Role of CPI, E-Money, Money Supply (M1), and Exchange Rate

This research aims to compare the influence of the consumer price index (CPI), electronic money transactions (e-money), money supply (M1) and exchange rates on inflation in Indonesia between the periods before the pandemic and after the Covid-19 pandemic . This research is a quantitative research with 67 data samples obtained. The data used in this study is published on the official website of the Central Bureau of Statistics and Bank Indonesia. The analysis in this study uses the Chow Test and Error Correction Model with the Engle-Granger method and also multiple linear regression with the OLS method assisted by the Eviews 9 data processing software. The results of the Chow test show that the regression model is differentiated according to the period; before and after the pandemic. The results of the OLS test before the pandemic, the variable value of e-money transactions and the money supply affected the inflation rate, while the CPI, exchange rate, and BI rate were not affected. After Covid-19, the analysis results showed that the CPI, exchange rate, and BI Rate had a significant effect on the inflation rate. Meanwhile, the variable value of e-money transactions and the money supply has no effect on inflation rate in Indonesia.

The Impact of Carbon Emissions on Corporate Cost of Debt (COD): A Research on Borsa İstanbul (BIST) Sustainability Index

This study examines the influence of carbon emissions of companies traded on the BIST Sustainability Index on the cost of debt for 2017-2021. In other words, the study aims to guide decision-makers towards carbon emissions reduction by showing a significant impact between the cost of debt and carbon emissions. The data were obtained from the Public Disclosure Platform, companies’ financial statements, annual reports, sustainability reports, integrated reports, and the DataStream database and were subjected to statistical analysis. Panel data pooled OLS method was used in the study. The study found a significant impact of total carbon emissions, carbon emission intensity, leverage, and structure variables on the cost of debt. However, it was concluded that the size, return on assets, growth, and cash flow variables did not significantly impact the cost of debt.

Public Sector Capital Expenditure and Tax Revenue Generation in Nigeria

Public sector capital expenditure is an important issue that cannot be ignored due to how it relates to tax revenue generation in Nigeria. This study examined the impact of public sector capital expenditure on tax revenue generation proxy by petroleum profit tax (PPT) in Nigeria. The baseline theory of this study is the Keynesian theory. The research design adopted in this study is the quasi-experimental research design. Secondary data was collected from the National Bureau of Statistics and CBN statistical bulletin. The multiple regression analysis based on the OLS method aided by E-view version 12 computer software was used to analyse the data, and the results were used to test the hypotheses. The findings showed positive significant relationship between the capital expenditure on road construction and PPT in Nigeria. It also revealed a significant positive relationship between capital expenditure on power, light and that PPT in Nigeria. The study revealed significant positive relationship between capital expenditure on security and PPT in Nigeria. Therefore, the study concluded that public sector capital expenditure played a vital role in improving tax revenue generation in Nigeria. The study recommends that since there is a positive relationship between capital expenditure on security, road construction and power with that of PPT, the variables should be sustained in this study. Government should look for means to solve the security challenges in the country, construct more roads, revolutionize electricity and power generation so as to enhance tax revenue generation in Nigeria.

Socioeconomic determinants of COVID-19 vaccine acceptance.

The aim of the paper is to evaluate the relative importance of the set of socioeconomic characteristics of population on collective decision on COVID-19 vaccine acceptance. We apply cross-section OLS methods to the municipal-level non-survey data for 145 municipalities in Serbia, on the COVID-19 vaccination rate and socioeconomic characteristics of the population, to evaluate the determinants of cross-municipal variation in vaccine uptake decision. Using the estimated coefficients from the OLS regressions, we apply the standardized beta method to evaluate the relative importance of each factor. Vaccine acceptance in municipalities rises with the average level of education (especially in the female population), age and employment, while being negatively linked to religiosity of people and the proportion of rural population. We also find some evidence on the positive impact of the overall trust in government. Education level has the single largest impact, shaping around 37% of (explained) variation in the vaccination rate across municipalities, a rise in the proportion of people with higher degree by 1% being associated with increase in vaccination rate by 0.36%. Age of population explains 21%, urban-rural structure 13% and religiosity 11% of variation in vaccine acceptance, while employment status and trust in government each explain around 9% of variation in vaccine uptake across municipalities. Effective vaccination promotion strategy should be focused on younger, less-educated, unemployed cohorts, as well as on rural areas and should involve representatives of mainstream religions. Fostering education and strengthening trust in government are some of the key structural factors that may promote efficient collective behaviour in this respect.

The Nexus Between Transformational Leadership and Greece’s Public Sector Performance: Educational Leadership Extension

The paper aims to extend our understanding of how effective educational leadership impacts a nation’s performance in the context of public sector risk and value. It seeks to broaden the insights gleaned from the author’s empirical research conducted within the scope of their dissertation on this topic, namely “Leadership and organizational change in the financial decision making in Greek public sector in a time of financial and humanitarian crises”. This paper replicates the author’s empirical research, focusing on the educational impact of leadership qualities in Greek secondary education. Accordingly, it examines leadership through surveys from teachers and stakeholders, highlighting attributes such as influence, motivation, intellectual stimulation, personal attention, and job satisfaction. The study investigates the connection between these leadership characteristics and critical economic indicators, thoroughly analysing their interplay. Data spanning 2015-2019 from sources like the World Bank, the Greek Ministry of Economics and Finance, the OECD, and Eurostat underpins this investigation, shedding light on how educational leadership influences economic patterns. By employing a robust econometric technique using the OLS method, the research reveals that enhanced leadership within schools directly benefits educational quality from the perspectives of teachers, professors, and students. Furthermore, the implementation of transformational leadership strategies significantly boosts performance across various quantiles, reflecting the value added to Greece’s public sector education.

DETERMINAN PERMINTAAN PERUMAHAN DI KOTA MATARAM

A place to live or a house is a necessary necessity in living human daily life. Mataram City is the capital of West Nusa Tenggara (NTB) Province and is one of the centers of economic growth, with a high population growth rate compared to 10 other districts/cities in NTB. This population growth causes the demand for housing/own houses or property rights to be very high, but on the other hand, land is getting narrower and more expensive, resulting in house prices becoming expensive and this has a big impact on people who are less fortunate in terms of their income. To meet the demand for housing from the community, we encourage developers to build housing with various types/models that are tailored to the income and desires of the community. The aim of the research is to analyze the influence of population, per capita income and inflation on housing demand in Mataram City. This research uses secondary data obtained from BPS Mataram City, BPS NTB Province, NTB Housing Statistics and other data sources relevant to this research. The data were analyzed using a multiple linear regression model with panel data and using the Eviews 12 calculation tool. The results of the study showed that the results of the multiple linear regression using the OLS method were found to have two variables that had a significant effect, namely the population and GRDP variables, while the inflation variable had an effect not significant.

Confucian Culture and Enterprise Strategic Change from a Perspective of the Golden Mean Ethics

AbstractAs an important informal system, the impact of Confucian culture on enterprise strategic change decision‐making and economic and social development is often ignored. By using the OLS method and drawing from publicly listed companies on China's Shanghai and Shenzhen stock markets from 2002 to 2020 as research samples, this article empirically analyzes the relationship between Confucian culture and enterprise strategic change from the perspective of the “golden mean” ethics (a Confucian moral standard and philosophy of conduct). The article also attends to the moderating effects of foreign culture shock and stock rights between the relationship of Confucian culture and enterprise strategic change. A key finding is that the ethical thought of “golden mean” and “harmony” contained in Confucian culture has an inhibitory effect on the initiation of enterprise strategic change. Foreign culture shock positively moderates the relationship between Confucian culture and enterprise strategic change. When “shocked” by dominant foreign cultures, the negative impact of Confucian culture on enterprise strategic change will be weakened. Moreover, unlike previous research findings based on agency theory that suggests how state ownership may retard corporate development, the authors found that in an informal institutional environment with a strong Confucian culture, stock rights can play a positive moderating role in the relationship between Confucian culture and enterprise strategic change. When an enterprise is state‐owned, the inhibitory effect of Confucian culture on enterprise strategic change will be weakened further.