Generalized Method Of Moments Research Articles

Does board knowledge matter for ESG performance in the European banking industry?

AbstractThis study investigates the influence of the knowledge endowment of directors on the environmental, social, and governance (ESG) performance in the banking industry. Applying the generalized method of moments (GMM) two‐step analysis, we analyzed a sample of 115 banks listed in Europe between 2014 and 2022. Building on the Resource Based View and Resource Dependence Theory, we find empirical evidence that board knowledge in terms of cultural, industrial, and financial background affects ESG performance in the banking industry, providing several contributions to the extant knowledge management and corporate governance literature. The research is intended to stimulate the development of practical knowledge management strategies inside companies to improve directors' decision‐making toward corporate social responsibility‐oriented initiatives.

The effect of renewable energy aid and governance quality on environmental tax effort in Sub-Saharan Africa

The literature on foreign aid and tax efforts largely overlooks the specific role of environmental aid and taxation. To fill this gap, we examine the effects of renewable energy development assistance (EDA) and governance quality on climate change tax effort, air pollution tax effort, and aggregate environmental tax effort in Sub-Saharan Africa (SSA). Utilizing panel data from 15 SSA countries over 20 years (2000–2019), the sample is divided into two groups based on income levels: seven low-income countries (LIC) and eight middle-income countries (MIC). The instrumental variable generalized method of moments (IV-GMM) regression technique is employed to estimate the parameters of the baseline model specifications. The study also uses the Smoothed Instrumental Variable Quantile Regression (SIVQR) technique to test the robustness of the baseline model. Among middle-income SSA countries, the findings suggest that renewable energy aid inflows reduce climate change tax efforts but increase air pollution and aggregate environmental tax efforts. However, among low-income SSA countries, renewable energy aid negatively impacts all three categories of environmental tax efforts. Governance quality tends to enhance all three categories of environmental tax effort in both low-income and middle-income SSA countries. The implications of these results are discussed.

Effect of Entrepreneurship on Urban-Rural Income Inequality in China

ABSTRACT Entrepreneurship is a two-edged sword, promoting economic mobility for some but potentially leading others into poverty. This research explores the effect of entrepreneurship on urban-rural income disparity in China, utilizing data collected in 265 Chinese cities from 2013 to 2019. Using a two-step System Generalized Method of Moments (GMM) for dynamic panel data, we found that entrepreneurship consistently reduces income inequality across various income levels in different digitalization environments. The findings underscore the significance of entrepreneurship in narrowing the disparity in income between urban and rural areas. Policies would be adaptable to the challenges and opportunities in different locations, with the goal of creating a favorable climate for the growth of both urban and rural economies.

Re-investigating the Impact of Economic Growth, Energy Consumption, Financial Development, Institutional Quality, and Globalization on Environmental Degradation in OECD Countries

Abstract This study attempts to quantify various macroeconomic variables’ influences on environmental quality. Being significantly negative in character, the impacts of economic growth (EG), energy consumption (EC) levels, financial development (FD) tools, changes in institutional qualities (IQUs), and globalization (GLO) on environmental degradation are regarded worthy of research. The dynamic panel model reports robust results using quantile regression and generalized moment method approaches. Renewable EC, GLO, and IQU significantly reduce the negative impacts on the natural environment across all quantiles. In contrast, electricity consumption has a significant deleterious impact across all quantiles, except at the 95% level, where the impact is not detrimental. EG and FD produce significantly positive injurious effects on the environment across all quantiles. Our findings reveal that callous indifference to global environmental degradation should not be tolerated for economic and ethical reasons, and it falls on the OECD countries to show leadership and take the initiative. OECD countries can mitigate environmental degradation by sharing knowledge and experience of balancing growth to promote sustainable development and responsible consumption globally.

Remittance inflows in a digital economy: A Sub-Saharan African experience

The undeniable importance of migrants’ remittances to the welfare of developing countries was again demonstrated during the COVID-19 pandemic. This has therefore led to a significant shift in attention to the relevance of remittances and has likewise spurred research interest in factors that motivate the inflows of remittances. However, in spite of the increasing recognition of the roles of digital technology in the macroeconomic performance of developed and developing economies alike, empirical analysis of its possible impacts on remittance inflows has not been well explored in the literature. Therefore, pooling the annual data of 35 sub-Saharan African (SSA) countries from 2011 to 2020, this study investigates the nexus between digital technology and remittance inflows within the generalized method of moments (GMM) framework. Using two measures of digital technology infrastructure—internet usage and mobile cellular subscription—the study finds a positive relationship between digital technology and remittances inflow. In addition, the findings indicate that the magnitude of the effect is relatively higher for internet usage. The study thus shows that the increased rate of remittance mobilization constitutes a significant pathway through which digital technology impacts the economies of the SSA region. Moreover, it offers further insight on the importance of digital technology in the socioeconomic development of developing countries. From a policy standpoint, governments and policymakers in SSA countries should intensify efforts to promote the diffusion and penetration of digital infrastructure.

Gender economic inclusion, governance institutions and economic complexity in Africa

AbstractThis study examines the effects of gender economic inclusion on economic complexity in Africa, as well as the moderating role of governance institutions on the relationship between gender inclusion and economic complexity. The analysis was based on the pooled OLS and the system generalized method of moments (GMM) estimation techniques, with data from 34 African economies between 2010 and 2021. The analysis uncovered several important findings. First, from the most robust model (i.e., GMM), positive synergies are apparent because gender economic inclusion promotes economic complexity, and governance dynamics further enhance the positive effect of gender economic inclusion on economic complexity. Second, regardless of the adopted technique, a predominantly positive and statistically significant relationship was identified between gender economic inclusion and economic complexity. Third, it was observed that while governance institutions exhibit a negative relationship with economic complexity, they play a positive role in moderating the relationship between gender inclusion and economic complexity. Fourth, factors such as foreign direct investment inflow, trade openness, and international tourism were identified as potent drivers of economic complexity in Africa, while the impact of human capital appears to be relatively subdued. Consequently, the study emphasizes the need for institutional reforms to improve governance transparency, accountability, and efficiency, alongside advocating for gender‐inclusive policies and increased investment in education.

IFRS, financial development and pollutant emissions: an empirical analysis of developed and developing countries

PurposeThe purpose of this study is to examine the relationship between pollutant emissions, financial development and IFRS in developed and developing countries between 1998 and 2022.Design/methodology/approachData were obtained from World Development Indicators and World Governance Indicators of the World Bank.FindingsUsing FGLS and GMM estimators, the results provide evidence that financial development has a significant positive impact on a variety of pollutant emissions. However, this positive impact is moderated by IFRS for the overall sample and country income groups.Practical implicationsGovernments and regulatory organizations should support companies’ investments in clean energy and technologies to slow down environmental degradation. Tax credits and subsidies may be helpful to achieve this goal. Also, governments may encourage companies to cooperate with universities and research institutions to develop environment-friendly production and distribution methods to reduce pollution. Although stakeholders may obtain information about environmental issues in financial statements that are prepared in accordance with IFRS, there is a need for standardization of their contents.Social implicationsGreenhouse gases are major contributors to climate change and global warming. In addition to private costs borne by producers, the production and consumption of products have social costs arising from pollution that affects air, water, and soil. Pollution adversely affects people's physiological and psychological health, which decreases labor productivity, thereby leading to a decrease in economic growth. Originality/valueAccording to the author’s knowledge, this is the first study that examines the impact of IFRS on the relationship between financial development and pollutant emissions.

Relationship between microfinance institutions' self‐sustainability and financing sources: Moderating role of external governance

AbstractThe self‐sustainability of microfinance institutions (MFIs) is a growing concern as they work as non‐profit organizations to achieve global poverty reduction goals. This study aims to examine the MFIs' self‐sustainability using an efficiency measurement technique based on Data Envelopment Analysis (DEA). It also determines the influence of different financing sources on MFIs' self‐sustainability as well as the moderating impact of external governance on this relationship. It uses the Generalized Method of Moments (GMM) estimator to analyze the panel data from 661 MFIs in 86 countries during the 2010–2018 period. The DEA analysis reveals that MFIs are still in the intermediate stage of self‐sustainability in terms of technical and cost efficiency. The second‐stage regression results reveal that financing sources such as retained earnings and equity have a robust positive and statistically significant effect on the MFIs' self‐sustainability, implying that MFIs that rely more on these two sources are more likely to be self‐sustainable. The moderation analysis reveals that good governance accelerates the positive effect of financing sources on MFIs' efficiency. Given these empirical findings, MFIs' decision‐makers can benefit from considering their own funding and equity. Quality governance can be ensured by government agencies and regulatory bodies to support the MFIs' sustainability.

The Influence of Board Characteristics on Corporate Social Performance

This paper explores the relationship between relevant board characteristics and the corporate social performance represented by the Social pillar of ESG scores. By applying the generalised method of moments (GMM) system version of the Arellano-Bond estimator, we analyse the 50 biggest and most traded companies in the Eurozone from 2015 to 2022. Our empirical evidence shows that more gender-diverse and independent boards, as well as the presence of a CSR sustainability committee, enhance corporate social performance. These results are largely confirmed by investigating the four sub-pillars of Social score, i.e. Human Rights, Workforce, Product Responsibility, and Community. To our knowledge, this paper is the first to highlight how high corporate governance standards positively affect the Social pillar in the Euro Stoxx 50 index context. Our findings provide important implications for several stakeholders, including regulators and policymakers. Increasing attention should be paid to board characteristics to improve corporate social performance.

Tourism Activities in the Context of Ecological Footprint: Panel Data Analysis For Mediterranean Countries

Tourism is seen as one of the important sources of economic growth in developing countries. It makes positive contributions to the country's economy, with national income, foreign currency inflow and employment created. While the basis of investments in the tourism sector is primarily to achieve economic gains, today is the sustainable tourism concept emerged and the effects of tourism on the environment have come to the fore. Sustainability in tourism emerges as a new tourism approach that takes environmental damage into consideration. The aim of this study is to examine the relationship between tourism activities and ecological footprint in countries bordering the Mediterranean, using annual data for the period 2001-2021. In the analysis; Generalized Moment Method (GMM), system GMM, constant effects model and random effects models were used. The results of the analysis showed that tourism activities have a significant and positive impact on the ecological footprint of countries bordering the Mediterranean. The findings obtained from the study confirm the expectations that tourism activities increase the ecological footprint by causing environmental degradation.

Icts And Labour Productivity Nexus In Developing Countries: Evidence From Panel Estimation Approach

This study examines the impact of information and communication technologies (ICTs) on labour productivity in developing countries from 2000 to 2019, using the two-step System GMM estimation and dynamic panel quantile regression. The empirical results present new evidence on the moderating effect of ICTs with human capital, financial development and trade openness on labour productivity in developing countries. The interaction terms between ICTs and these three moderators show positive and statistically significant determinants of labour productivity. These three interaction terms have a greater influence on labour productivity than the impact of each variable assessed individually. The dynamic panel quantile regression results revealed that ICTs statistically significant to enhance labour productivity in lower and intermediate quantiles than in the highest quantiles in developing countries. This finding suggested that ICTs play an essential role in improving productivity at the lower and average labour productivity levels. This study can help policymakers develop a long-term strategy in terms of ICTs adoption and usage more intensively in developing countries as they strive to achieve the goals of industrial 4.0.

A Comparative Study between Growth of offering supply chain finance with Non-offering Banks in Pakistan.

This study empirically examines a comparative study between banks growth of offering supply chain finance with Non-offering Banks in Pakistan. This study used dynamic generalized method of moments (GMM) technique, based on 22 Pakistani Banks (10 offer supply chain finance and 12 non-offering supply chain finance) data during 2012-2022. The results show a significant difference between banks growth by offering and non-offering supply chain finance. Furthermore, the results show a significant positive impact of banks growth with supply chain finance on banks financial performance. This study encourages banks to offer supply chain finance that contributes towards their growth and financial performance.

Institutions and economic growth: the role of financial inclusion, public spending on education and the military

PurposeThe paper aims to investigate the relationship between institutions and economic growth in developing countries, considering the role of financial inclusion, education spending and military spending.Design/methodology/approachThe study employs dynamic panel analysis, specifically two-step system generalized method of moments (GMM), on a sample of 61 developing countries over the period 2009–2020.FindingsThe results confirm that weak institutional quality, weak financial inclusion and increased military spending are barriers to economic growth, conversely, increased spending on education and gross capital formation contribute to economic growth in developing countries. Regarding the specific institutional factor, we find that corruption, ineffective government, voice and accountability and weak rule of law contribute negatively to growth.Practical implicationsThe study calls for strengthening institutions so that the financial system supports economic growth and suggests increasing spending on education to improve access to and the quality of human capital, which is an important determinant of economic growth.Originality/valueThe study contributes to scarce literature by empirically analyzing the relationship between institutions and economic growth by considering the role of financial inclusion, public spending on education and military spending, factors that have been ignored in previous studies. In addition, the study identifies the institutional dimension that contributes to reduced economic growth in developing countries.

Climate change impacts on agricultural trade and food security in emerging economies: case of Southern Africa

Climate change has been a significant threat to sustainable agriculture impacting trade and food security. This research investigates the impacts of climate change on agricultural trade and food security in emerging economies focusing on Southern Africa. The research employed the dynamic panel Generalised Method of Moments (GMM) using panel data for the period 2012 to 2021 obtained from a sample of 12 Southern African countries selected based on data availability. The main independent variables to the research were climate change variables (temperature and precipitation). Other control variables included were population growth, food inflation and agricultural growth. The study found significant negative effects of climate change on agriculture trade. Whilst temperature changes were found to have insignificant effects, precipitation changes were found to have significant positive effects. The research recommends concerted efforts towards climate change adaptation and mitigation for sustainable agriculture. Based on the Findings, sustainable food security and agricultural trade Southern African emerging economies may be attained through effective climate change mitigation and adaptation approaches particularly promoting climate-smart agriculture (CSA).

Effect of ICT and Urbanization on Economic Growth: New Insight from OIC Countries

ABSTRACT This paper examines the relationship between ICT, urbanization, and economic development. The context of the analysis is the Organization of Islamic Countries from 1997 to 2019. We develop an original empirical approach based on principal component analysis to generate ICT index. To mitigate any endogenous issue, we utilize the instrumental variable generalized method of moments. Further, we use pooled mean group estimation to check the short-run and long-run relationships between the variables. Our results have two significant implications. First, we demonstrate the favorable influence of ICT on economic growth in OIC nations in both the short and long term. Second, both urbanization and economic growth have a clear and substantial impact in the short and long term. Finally, our analysis supports the feedback hypothesis between ICT and economic growth. These novel empirical findings will help policymakers design ICT development policies to fulfill sustainable economic development in OIC countries.

The interplay of bank competition and institutional quality: Implications for shadow economy

This study investigates the impact of institutional quality and banking competition on shadow economy for 127 economies for the period of 2005–2017. It further explores if institutional quality/competition shapes the relationship differently between banking competition/institutional quality and shadow economy. This paper uses the system GMM estimator to tackle potential omitted variable bias, endogeneity, and simultaneity issues. The findings suggest that overall, greater competition among banks and stricter institutions in the country reduce the size of shadow economy. Furthermore, impact of competition on shadow economy is even stronger in countries with weak institutions and the impact of institutional quality is greater in lower competitive environment. Only severe competition matters for shadow economy in case of developed countries. To sum up the novel findings of this research, competition and institutions complement each other in reducing the size of shadow economy. These findings are robust to different econometric estimators. The findings carry vital policy implications for the governments and regulators to play their part in reducing the shadow economy.

Enhancing prediction and analysis of UK road traffic accident severity using AI: Integration of machine learning, econometric techniques, and time series forecasting in public health research

This research project explored into the intricacies of road traffic accidents severity in the UK, employing a potent combination of machine learning algorithms, econometric techniques, and traditional statistical methods to analyse longitudinal historical data. Our robust analysis framework includes descriptive, inferential, bivariate, multivariate methodologies, correlation analysis: Pearson's and Spearman's Rank Correlation Coefficient, multiple logistic regression models, Multicollinearity Assessment, and Model Validation. In addressing heteroscedasticity or autocorrelation in error terms, we've advanced the precision and reliability of our regression analyses using the Generalized Method of Moments (GMM). Additionally, our application of the Vector Autoregressive (VAR) model and the Autoregressive Integrated Moving Average (ARIMA) models have enabled accurate time series forecasting. With this approach, we've achieved superior predictive accuracy and marked by a Mean Absolute Scaled Error (MASE) of 0.800 and a Mean Error (ME) of -73.80 compared to a naive forecast. The project further extends its machine learning application by creating a random forest classifier model with a precision of 73%, a recall of 78%, and an F1-score of 73%. Building on this, we employed the H2O AutoML process to optimize our model selection, resulting in an XGBoost model that exhibits exceptional predictive power as evidenced by an RMSE of 0.1761205782994506 and MAE of 0.0874235576229789. Factor Analysis was leveraged to identify underlying variables or factors that explain the pattern of correlations within a set of observed variables. Scoring history, a tool to observe the model's performance throughout the training process was incorporated to ensure the highest possible performance of our machine learning models. We also incorporated Explainable AI (XAI) techniques, utilizing the SHAP (Shapley Additive Explanations) model to comprehend the contributing factors to accident severity. Features such as Driver_Home_Area_Type, Longitude, Driver_IMD_Decile, Road_Type, Casualty_Home_Area_Type, and Casualty_IMD_Decile were identified as significant influencers. Our research contributes to the nuanced understanding of traffic accident severity and demonstrates the potential of advanced statistical, econometric, machine learning techniques in informing evidence based interventions and policies for enhancing road safety.

The Effect of Village Fund on Inequality and Inclusive Growth in Indonesia: A District Level Case Study

Objective –This study tries to find the relationship between Village Fund expenditures and the inequality and growth inclusiveness using data from 434 districts for the time span of seven years from 2015 to 2021.Design/Methodology –This study uses quantitative research. The research data comprised the data of Village Fund, Gini Ratio, and Inclusive Growth Index from the Ministry of Finance, Central Bureau of Statistics, and the Ministry of National Development Planning. To investigate the relationship between variables, a dynamic panel data with Generalized Method of Moment (GMM) approach is applied.Results –This study revealed the relationship between Village Fund and Inequality and Inclusive Growth. We found that there is no strong relationship between the Village Fund, the first lag of the Village Fund, the second lag of Village Fund and Inequality among specifications. Similar relationships are also shown by the Village Fund, the first lag of Village Fund, the second lag of the Village Fund, and the Inclusive Growth among specifications. In other words, the implementation of Village Fund could not eradicate the inequality problem and could not support inclusion of economic growth in the village level.Research Limitations/Implications –The result of this study potentially has a major implication in terms of program delivery effectiveness and the factors that influence the program effectiveness. Furthermore, in this particular research, the major problems with village fund allocation are the equity issue of the allocation scheme and the clarity of the village service responsibilities.Novelty/Originality –This study uses a different approach to the panel data, which is a dynamic panel data with GMM approach. This study also uses a more specific scope of the data which is a district (kabupaten/kota) level in Indonesia.

Determinants of Local Revenue in West Nusa Tenggara Province

The economic growth of a region can be seen from the contribution of increasing regional original income originating from sources of taxes, regional levies, regional property and other separated regional wealth management results, and other legitimate regional revenues. The Province of West Nusa Tenggara in the last few decades has shown a significant increase in local revenue. In this study, the impact of population, inflation, and Gross Regional Domestic Product (GRDP) on local revenue from 2010 to 2021 is explored. The Generalized Method of Moments (GMM) technique uses district or city annual data in a quantitative panel data regression model for the study. According to the findings of statistical studies, local own-source revenue is significantly positively affected by government spending, population, and gross regional product (GDP), but inflation-related price increases have a negligible impact on local revenue. The money supply determines the rate of inflation, the high rate of inflation is caused by the amount of money in circulation.

Does investor base affect the firm-level ex-ante cost of equity capital?

This research investigates how investor base affect the cost of equity capital (COE) in Indian companies, particularly in market conditions with weak investor protection and increased ownership concentration by promoters and families. Using ordinary least squares (OLS), panel fixed effects, and two-step system generalised method of moments (GMM) analysis on data spanning from 2016 to 2021, we discovered that a dispersed ownership structure is linked to a higher ex-ante COE. Our findings indicate that companies with dispersed shareholders have less motivation to monitor managers, which leads to the expropriation of minority shareholders and results in higher COE.