OLS Approach Research Articles

Integrating LGBTI Inclusivity and Innovative Capacity in India: Analyzing the Effects of Globalization

Globalization can have enormous effects if LGBTI people are well blended into the pool of resources and tapped efficiently. This research investigates LGBTI inclusivity and the effects of globalization on economic development since the 2009 legalization verdict favoring homosexuality. The theoretical prospects are trifold: trade liberalization and labor market de-regulation; Becker’s theory of discrimination; and Heckscher-Ohlin-Samuelson postulate, along with a diagrammatic representation showcasing the impact of LGBTI inclusivity in the labor market. An OLS approach in conjunction to the ECI_Trade and ECI_Technology has been employed to examine the integration of LGBTI individuals into the Indian economy considering capital stock, domestic credit, employment, population and human capital as default controls to the model and year dummies have been incorporated at a later stage of modelling to highlight the precision level. The study found that LGBTI inclusivity is positively correlated with India's ECI_Trade and ECI_Technology value, increasing it approximately by 6.3% and 15.4%. Further, a number of robustness checks show that even after accounting for macroeconomic variables as default controls, the positive association continues to persist. The LGBTI inclusivity increases the ECI_Trade value by 13.2% and ECI_Technology value by 24.4%, respectively. Consequently, the authors emphasized on the economic ramifications of inclusivity in relation to wage gaps, discrimination, and the development of human capital and have tried to exemplify the integration of LGBTI individuals in EPZs, trade and technological advancement, and skill development to justify the default conceptualized postulates in support of inclusivity.

Exploring the LCC Hypothesis in the Nordic Region: The Role of AI Innovation, Environmental Taxes, and Financial Accessibility via Panel ARDL

This study investigates the impact of artificial intelligence (AI) innovation on environmental sustainability in the Nordic region. Additionally, it tests the Load Capacity Curve (LCC) hypothesis by incorporating factors such as financial accessibility, environmental tax, and urbanization, using data spanning from 1990 to 2020. The methodology includes the Cross-Sectional Dependence test and the slope homogeneity test, revealing issues of heterogeneity and cross-sectional dependence. Furthermore, first and second-generation panel unit root assessments indicate that the variables are free from unit root problems. Panel Cointegration tests confirm that the variables are cointegrated in the long run. To analyze both short-run and long-run relationships, the study employs the Panel Autoregressive Distributed Lag (ARDL) model. The results from the Panel ARDL model support the LCC hypothesis in the Nordic region, showing a U-shaped relationship between income and load capacity factor. Moreover, AI innovation and environmental tax significantly and positively contribute to environmental sustainability in both the short and long run. In contrast, higher financial accessibility and urbanization degrade environmental sustainability over these timeframes. To validate the robustness of the Panel ARDL estimations, the study also uses Fully Modified OLS, Dynamic OLS, and Fixed Effects OLS approaches, all of which corroborate the ARDL findings. The study employs the D-H causality test to explore causal relationships among the variables. The test results reveal a unidirectional causal relationship between income and AI innovation to the load capacity factor and a bidirectional causal relationship between financial accessibility and the load capacity factor, as well as between urbanization and the load capacity factor. However, no causal relationship is found between environmental tax and the load capacity factor.

Do financial inclusion and bank competition matter for banks’ stability in Asia?

This study investigates the effect of financial inclusion (FI), considering micro and macro indicators as well as micro- and macro-FI separately, on the stability of Asian banks and examines the moderating effect of bank competition (BC) on this relationship. Using data from 2011 to 2021, this study examines the relationship between FI, BC, and bank stability (BS). The hypotheses were tested using a “two-step system-GMM framework”. The findings were also authenticated using the panel OLS approach. The results indicate that FI (considering micro- and macro-indicators) and micro- and macroFI have significant positive effects on the stability of Asian banks. However, the impact of micro-FI is greater than that of macro-FI on the BS in Asia. Furthermore, the results manifest that BC has a significant positive impact on BS and positively moderates the relationship between micro-FI and BS, whereas it negatively moderates the relationship between macro-FI and BS. The findings of this study have practical implications for regulators, bankers, and policymakers involved in formulating strategies to enhance Asian banks’ stability.

Estimating the precise form of uncovered interest parity under the Stock–Watson dynamic OLS approach

The standard uncovered interest parity (UIP) – a logarithm version – is inappropriate for currencies with a high-interest rate because the high-interest rate (i) does not satisfy the ln(1+i)=i condition. Therefore, we develop a precise form of UIP and evaluate its existence using BRICS countries as an example. The Stock–Watson dynamic ordinary least squares (DOLS) approach based on a panel cointegration test provides individual and group estimation, finding that UIP holds for all BRICS members except for China. This implies that the financial markets of other four economies are fully integrated with the United States financial market.

Modelling the impact of turbulent economic conditions on non-audit services provision and audit quality during the global financial crisis

PurposeMotivated by concerns and the ongoing debate regarding auditors’ independence and impartiality, this paper aims to examine the impact of the financial crisis on non-audit services (NAS) provision and audit quality (main and robust variables) in the four largest Eurozone countries together during the global financial crisis (GFC).Design/methodology/approachThe authors used a time trend OLS model with a dummy variable as well as a baseline model with a dummy and control variables accounting for multicollinearity, considering the characteristics of the GFC.FindingsIt documented a positive (negative) relationship between NAS provision (audit quality) and crisis in four Eurozone countries, Germany, France, Italy and Spain, in the context of a baseline approach, supporting the hypotheses that there are higher non-audit fees and a lower audit quality. Moreover, it is revealed that NAS provision and audit quality behave similarly, using a time trend approach, during the GFC. Considering the role of the auditor specialization or not (Big4 vs non-Big4) in companies, a significant effect from crisis on non-audit fees and audit quality for the four countries under the baseline approach is found. In general, the findings persist for NAS provision and audit quality using the robust methods of the time trend and panel OLS approaches. Multicollinearity was not found to affect the findings of the regressions.Practical implicationsThe study provides important implications for firm managers, auditors and regulatory authorities.Originality/valueTo the best of the author’s knowledge, it is the first time that the impact of the crisis on non-audit fees and audit quality is investigated during the GFC with two sets of OLS models (a time trend OLS with a dummy and a panel OLS with a dummy and control variables) in four largest Eurozone countries together.

How and When Does Engaging Customers in Environmental Sustainability Pay Off? The Role of Business Strategy

This study explores the influence of consumer engagement for sustainability purposes on customer satisfaction and firm performance. Our study utilized unique actual data on the study variables to test these relationships in the context of S&P 500 firms. We collected data from 405 firms from 2013 to 2022. The analysis revealed that customer engagement is positively related to firm performance and customer satisfaction. The OLS approach demonstrated that a one-unit increase in CE resulted in an 8.1% improvement in company value and a 4.7% improvement in customer satisfaction. It also revealed that the relationship between customer engagement and firm performance is stronger when the company integrates climate change into their strategies. These findings offer meaningful implications for theory and practice in the context of sustainability.

The Role of Technological Innovation, Natural Resources, and Economic Growth in Fostering Environmental Sustainability: A Case Study of Thailand

Thailand, an emerging economy, is seeing a rise in greenhouse gas emissions and environmental strain due to its significant dependence on non-renewable energy sources. In this sense, a nation's strategic utilization of technical innovation and resource management become essential requirements. Thus, using the EKC paradigm, this study investigates the relationship between ecological footprint, economic growth, natural resources, and technological innovation. To ensure reliable results, the study used co-integration, FMOLS, DOLS, and OLS approaches. The empirical result validates the existence of the EKC hypothesis, which states that sustained economic expansion causes environmental quality to first fall before improving over time with a doubling of per capita income. Moreover, it was discovered that the natural resource coefficients did not exhibit statistical significance in any of the equations, highlighting their theoretical value. On the other hand, technical advancements had a major detrimental effect that eventually reduced the ecological footprint It emphasizes how important environmental conservation is. In order to accomplish significant environmental improvement, the report suggests focusing more on innovation-driven initiatives and improving the management of natural resources.

Corporate Reporting, Corporate Governance Mechanisms and Tax Aggressiveness: Evidence from Indonesia

This study aimed to empirically analyze the relationship between corporate reporting, both mandatory (financial reporting) and voluntary (Corporate Social Responsibility (CSR) disclosure) reporting, three corporate governance mechanisms (board size, independent board, and CEO duality), and tax aggressiveness in Indonesia. The study used a collected dataset of 121 public companies listed on the Indonesian stock exchange from 2016 to 2020. The data was collected from annual and sustainability reports published on the IDX and the company websites. The data was categorized based on classifications of non-financial industries because different characteristics and business cycles may influence tax aggressiveness decisions. Using the panel OLS approach, the research found that, in most industries, aggressive financial reporting positively relates, while CSR disclosures were negatively related to tax aggressiveness. The results also found that corporate governance mechanisms significantly related to tax aggressiveness in most industries. The findings suggest that board members, particularly independent boards with tax expertise and experience, can influence aggressive tax decisions. This study is the first to extract testing by industry classification, using mandatory financial reporting and voluntary CSR disclosures in Indonesia as indicators of corporate tax aggressiveness. The findings provide knowledge on company governance strategies to reduce aggressive tax actions. Keywords: aggressive financial reporting, corporate social responsibility, corporate governance mechanisms, tax aggressiveness

Exponential method of estimation in sampling theory under robust quantile regression methods

–In the regression analysis, ordinary least square techniques is commonly used. However, the data’s outcomes may be untrustworthy if there is an outliers in it. In order to deal with the outliers problem, robust quantile regression methods have been frequently presented as alternatives to OLS for a long time. In this article, primarily a exponential ratio-type estimators is suggested. After that, robust quantile regression estimators are proposed, that is a useful strategy. The application of robust quantile regression empowered the efficiency of the estimators especially for outliers in the data. The MSE equations of the various estimators are computed and compared to OLS approaches. Numerical illustration and simulations studies are performed to support our theoretical findings.

Sustainable Working Capital and Financial Performance in Cement Industry of Pakistan: An OLS Approach*

This research aims to demonstrate for the first time how the Pakistani cement sector's financial health is impacted by sustainable working capital. The cement Industry uses sustainable working capital techniques and practices for magnificent financial outcomes. Considering the importance of these profitable techniques, we practice these in cement firms with a sample size of 25 cement firms listed in the Pakistan stock market (PSX) from 1997-2022. The data is collected from annual reports available on the financial statements. The current ratio and Quick ratio are measured for liquidity. Ordinary Least Square & correlation analysis indicates that the cash conversion cycle (β1= -0.564, p= 0.00), Current ratio (β2= -0.20, p= 0.040), Quick ratio (β3= -0.585, p= 0.000) and Inventory Turnover ratio (β4= -0.244, p= 0.004) have a negative effect on financial performance (Tobin's Q). This study helps policymakers that can handle liquidity Sustainable working capital for the cement industry.

Testing the Validity of Uncovered Interest Parity for BRICS Countries: A Dynamic OLS Approach

Testing the Validity of Uncovered Interest Parity for BRICS Countries: A Dynamic OLS Approach

Faktor – Faktor Yang Mempengaruhi Impor Produk Pertanian di Indonesia

This study aims to determine; (1) the influence of households on imports of agricultural products to Indonesia, (2) the effect of the curve on imports of Indonesian agricultural products, (3) the effect of gross domestic product (GDP) on imports of agricultural products to Indonesia. This type of research is descriptive and associative research. The data used is secondary data in the form of times series data from 1989 to 2020. The research method uses the OLS approach, so there are several, namely: (1) Normality Test; (2) Multicollinearity Test; (3) Autocorrelation Test; (4) Autocorrelation Test; (5) Heteroscedasticity Test. The results showed that; (1) T consumption of the agricultural sector has a significant effect on imports of agricultural products to Indonesia. (2) that the exchange rate has a significant effect on imports of agricultural products to Indonesia. (3) GRDP of the agricultural sector has a significant effect on imports of agricultural products to Indonesia, (4) consumption of agricultural products, the exchange rate and GRDP of the agricultural sector together have a significant effect on imports of agricultural products to Indonesia.

MACROECONOMIC FACTORS INFLUENCE THE DISTRIBUTION OF MSME FINANCING IN INDONESIAN ISLAMIC BANKS

This study examines macroeconomic factors affecting MSME financing in Indonesian Islamic banks from 2014 to 2021. These factors include inflation, BI rate and exchange rate. The methodology of this study is a quantitative method using the OLS approach. The data used in this study is monthly data from 2014 to 2021. Data was collected from Central Bank and OJK publications. This study found that macroeconomic conditions also affect how MSME financing is channeled in Islamic banks, so inflation and exchange rate partially, but BI Rate does not affect the distribution of MSME financing. This is because Islamic banks do not use an attractive interest rate system but a profit-sharing system. The findings of this study have significant consequences for decision makers, Islamic banks, and market participants. Islamic banks should work more to provide financing for MSMEs. Islamic banks should use innovation and creativity to develop and market new products in MSME financing. Due to its narrow focus on MSME financing in Islamic banks, this research has several limitations including that this research only focuses on macroeconomic factors, many other factors can affect MSME financing such as internal bank factors. Further research can examine the impact of Islamic banking financing on MSME development.

The Role of Digital Banking Services on Commercial Banks Performance in Somalia: A Descriptive and OLS Approach

The main objective of this study is to examine the role of digital banking services on commercial banks’ performance in Somalia. A descriptive research design was used in this study to illustrate the relationship between variables. The study selected 300 participants using stratified random sampling. The study employed the Kobo-collect tool to collect data from the field. SPSS v28 and Eviews12 data analysis tools were employed in this study. The ADF test results show that all variables are stationary in the first difference with a constant and trend for each of the three critical levels. Pearson chi-square statistics showed that the association between explanatory variables and commercial banking performance is statistically significant. Descriptive statistics showed that the skewness and kurtosis of the normal distribution of probability are best to fit and close to zero using the Jarque-Bera test. Positive kurtosis values suggest a peaked distribution with long, fatty tails, and it proposes that a large proportion of numbers are concentrated in its tails rather than its centre. The regression result gives the impression that the explanatory variables determine 86% of the overall variance in commercial banks’ performance. The correlation results showed a strong and significant positive correlation between digital banking service delivery and commercial banks' performance in Mogadishu, Somalia.

Robust Estimation OF The Partial Regression Model Using Wavelet Thresholding

Semi-parametric regression models have been studied in a variety of applications and scientific fields due to their high flexibility in dealing with data that has problems, as they are characterized by the ease of interpretation of the parameter part while retaining the flexibility of the non-parametric part. The response variable or explanatory variables can have outliers, and the OLS approach have the sensitivity to outliers. To address this issue, robust (resistance) methods were used, which are less sensitive in the presence of outlier values in the data. This study aims to estimate the partial regression model using the robust estimation method with the wavelet threshold and the PLM estimation method with the Speakman estimation and Nadarya-Watson smoothing, using simulation experiments at different sample sizes and contaminated ratios.
 The mean square error criterion was employed to compare the two methods. The robust method is more efficient in obtaining robust estimators than the PLM estimation method

Investigating the Impact of Bank-specific Determinants on Stock Price of Listed Commercial Banks: Evidence from Emerging Economy

This paper attempts to investigate the impact of bank-specific determinants on the stock price of Dhaka Stock Exchange (DSE) listed commercial banks in Bangladesh. Several bank-specific factors such as Book to Market Ratio, Return on Equity, Price/Earnings to Growth Ratio, Cash Flow per Share, Debt to Equity Ratio, Earnings per Share, Dividend per Share, Bank Size and Institutional Ownership Percentage have been analyzed for this study and tried to see the impact of each variable on the change in market price of share of 10 listed commercial banks spanning from 2011 to 2020. In empirical discussion four estimation models such as Fixed effects, Random effects, GLS, and Pooled OLS approach have been used to ensure the robustness of the models. To examine the validity of the models chosen for this study, the model specification test and many diagnostic checks were used, including the test of heteroskedasticity, the cross-sectional dependence test, the test of autocorrelation and the unit root test, etc. Our investiagtion reveals that only Bank Size and Book to Market Value explanatory variables are found significantly responsible for fluctuation in the change in share price of banks, contributing to the current literature by revealing the importance of bank-specific factors that include all metrics in their calculation. As a result, Bangladesh's DSE-listed banks should take appropriate measures to boost their stock values, such as attempting to improve the ratio that has a positive impact on the share price while decreasing the ratio that has a negative impact.

Women Empowerment in Punjab: Dimensions, Determinants, and Implications for Access to Healthcare

In developing countries like Pakistan, because of the complex cultural and socio-demographic milieu women empowerment always remained the contested issue. Overall major indicators of human development of women have been considered lower rather than men. In Pakistan, some considerable measures have focused on women's empowerment however, their status is still miserable specifically in rural areas. This study was aimed to find out, the extent of rural women empowerment and the effect of women empowerment regarding access to healthcare in the Vehari district of Southern Punjab, Pakistan. The study used data of 240 married women respondents and employed Cronbach’s alpha and OLS approaches for various analyses of the study components. Scores of various components regarding women's empowerment were regressed over the scores of women's access to healthcare in the final analysis of the study. The finding of the study indicated that the power of decision-making (0.87), self-esteem (0.79), and mobility (0.89) has positive and significant effects on access to health care whereas control over the resource (0.73) estimates indicated positive while the insignificant impact on health access. Education access, adequate job opportunities, and media information approach considered more appropriate and feasible measures for adequate women empowerment and health care access. Emergency-based State-based policy measures need to be applied such as women schooling at doorstep, increasing females' priority-based job opportunities, and proper access to media for increasing awareness regarding their rights and significant role in society.

Comparison of decadal water storage trends from common GRACE releases (RL05, RL06) using spatial diagnostics and a modified triple collocation approach

GRACE (Gravity Recovery and Climate Experiment) and GRACE-FO (Follow-On) satellites have provided unique insights into the evolution of Terrestrial Water Storage (TWS) in space and time. Despite such advancements, various GRACE solutions produced by different data centers display uneven spatial attributes with varying associated uncertainties. Via spatial diagnostics tools and a modified triple collocation (MTC) approach, this research evaluates the TWS (terrestrial water storage) trend estimations “on the grid-scale” from 11 gridded GRACE products of RL05 and RL06 releases between 2002 and 2017. Distinct from classic TCA (triple collocation analysis), the MTC employs a GWR (geographically weighted regression) scaling scheme with distinctive spatial coefficients. The spatial diagnostics analyses identified different autocorrelation patterns, clustering tendencies of hot (positive) and cold (negative) spots agglomeration at varying spatial width, and unique frequency distributions. The results indicated that within a 10-degree spatial radius the SHs (Spherical Harmonics) of RL05 and RL06 are highly autocorrelated compared to the mascons (mass concentration blocks) solutions. The spatial clustering results revealed that many solutions agreed on the overall directions and distribution of the hot and cold spots. The clustering among mascon products, however, reflected more localized mass anomalies. At the scale of drainage basins, the trend magnitude, as well as their associated uncertainties appeared to be driven by the occurrence of spatial clusters within the basin area. The MTC results showed that the uncertainty patterns follow the same spatial extent within each cluster. The MTC analysis underscored the added benefits of cluster analysis and the GWR scaling over the classic OLS approach.

Elastisitas Permintaan Rumah Sederhana Tipe 36 di Kota Padang Provinsi Sumatera Barat

This research aims to analyze type 36 house demand elasticity in Padang City, West Sumatera Province. It used secondary data collected from 32 units of sample observation. The variables were 36-type housing price, distance to CBD, district density, number of household, and GDP per capita. The instruments of analysis were data panel regression using OLS approach, fixed effect , and random effect. The analysis results show that fixed method gives the best result of regression among the three approaches in the data panel. The variable of house price has a negative and significant correlation with the demand in Padang City with an elasticity level of 1.56%; the distance to CBD has a negative and correlation with demand with an elasticity level of 1.73%. The research results give a picture that the demand for simple houses in Padang city, West Sumatera Province is elastic toward the price of type 36 house, and distance to CBD.

Empirical Analysis of the Environmental Kuznets Curve for Co2 Emissions in Nigeria: The Role of Industrialization and Urbanization

The proposed inverted U-type relationship between environmental degradation and per capita income under EKC hypothesis has been examined in this paper for Nigeria over the period 1970-2019. Using the ARDL bounds testing approach to cointegration and ECM (OLS Approach), the EKC hypothesis does not seem to hold both in short-run and long-run. The estimated coefficients of the long-run relationship shows that LOGCO2(-1) is the only statistically significant variable explaining environmental degradation while the short run results indicate that D(LOGCO2(-1)) is the most significant variable in explaining environmental degradation in Nigeria followed by D(LOGIND(-1)).