Generalized Method Of Moments Research Articles

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.

The Impact of Economic Openness and Institutional Environment on Technological Innovation: Evidence From China’s Provincial Patent Application Data

Analyzing the impact of economic openness and institutional environment on technological innovation is of great significance for China to build a new system of open economy. This study investigates the short- and long-run effects of economic openness and institutional environment on innovation by applying a dynamic panel regression model and two-step system generalized method of moments (GMM) method to dynamic panel data of China’s 30 provinces, autonomous regions and municipalities directly under the Central Government (referred to as provinces hereafter) from 2008 to 2017. Results indicate that trade openness impedes innovation, whereas foreign direct investment (FDI) significantly promotes China’s innovation particularly in the long-run. The continuous improvement of institutional environment promotes domestic innovation particularly in the long run. The integration of economic openness and institutional environment magnifies the effects of trade openness and FDI on innovation. The effects of economic openness and institutional environment on innovation differ by region with a descending pattern from China’s Eastern to the Central and Western regions.

The Moderating Effect of Economic Policy Uncertainty on the Relationship Between Working Capital Management and Profitability: Evidence from UK Non-Financial Firms

Uncertainty in economic policy is one of many factors that can have an impact on the relationship between working capital and profitability. The corporate sector places a higher priority on working capital management that employs its working capital resources to have an advantage over rivals. The objective of our study is to determine how economic policy uncertainty (EPU) index for UK, as measured based on newspaper coverage frequency, affects the relationship between working capital management (CCC), return on operating assets, and other profitability measures across several businesses listed on the UK stock exchange for the years 2006 to 2021. To analyze the data for 199 UK manufacturing companies, we applied the Fixed Effect Method, Random Effect Method, and two-stage Generalized Method of Moments (GMM) to tackle the endogeneity problem and report robust findings. The findings of the study revealed that EPU statistically significantly affected the relationship between CCC and profitability. When uncertainty is high, companies may be hesitant to make investments or develop new products, which can lead to a reduction in working capital and lower profitability. Companies that can effectively manage their working capital in the face of uncertainty may be better positioned to maintain their profitability over the long term. This study can provide valuable insights for both companies and investors, helping to improve financial performance and enhance strategic decision-making regarding their working capital management policies in the face of economic policy uncertainty.

Utilising AI-based Chatbot for Maximising Value and Profitability of Islamic Financial Institutions

global Islamic finance industry has experienced significant growth in recent years, establishing Islamic financial institutions (IFIs) as prominent players in the international financial landscape. To maintain competitiveness and sustainability, IFIs must embrace innovation and explore avenues for maximising their performance. This research aims to investigate the effect of AI-based Chatbots on the value and profitability of IFIs in Organisation of Islamic Cooperation (OIC) countries. The study has employed quantitative methodology, and the data was collected from the Bloomberg database, Thomson Reuters DataStream, World Development Indicators and annual reports of 104 IFIs across 44 OIC countries from 2020 to 2022. Employing the Generalised Method of Moments (GMM), this study investigates the impact of AI-based Chatbots on the value and profitability of IFIs. The findings show a positive impact of Chatbot on Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q (TBQ). Furthermore, the analysis reveals that variables such as Gross Domestic Product (GDP), institutional size (SIZE), and age (AGE) exhibit positive associations with the value and profitability of IFIs. Conversely, the study identifies Consumer Price Index (CPI) as exerting a negative influence on the value and profitability of IFIs, indicating potential challenges posed by inflationary pressures. IFIs may consider investing in the development and deployment of advanced AI technologies to enhance overall profitability. Keywords: AI-based Chatbot; Profitability; Islamic financial institutions (IFIs); OIC Countries; Dynamic GMM

Factors influencing the participation of Vietnamese enterprises in global value chains: Insights from the manufacturing and processing sectors

This research aims to investigate the factors that impact the participation of companies in Vietnam's Manufacturing and Processing sector in the Global Value Chain (GVC). We employ panel data analysis with a dataset of 387,994 observations from 107,125 enterprises in this industry spanning 2011-2020. Both Ordinary Least Squares (OLS) and Generalized Moment Method (GMM) are used to assess the factors affecting the industry's GVC engagement. The Arellano-Bond test checks for autoregressive processes of order one (AR(1)) or order two (AR(2)) in the model to see if the idiosyncratic error term exhibits serial correlation. The Sargan test checks for over-identifying restrictions in the statistical model. The results reveal that the ratio of large enterprises" exerts the most significant positive influence on the participation of Vietnamese enterprises in the GVCs, closely followed by "Institutional and policy environment." Conversely, HHI, TFP, and GDP growth rates show significant negative impacts. For Foreign Direct Investment (FDI), horizontal spillovers are positive and statistically significant. However, significant results also show a negative coefficient in the Backward GVC and a positive one in the Forward GVC. From these findings, we point out some important policy implications: (1) the government should strengthen favorable conditions for the participation of large enterprises and leading SMEs; (2) It is necessary to improve the institutional and policy environment and refine policies to attract FDI, especially with a focus on promoting forward linkages to facilitate greater engagement of the enterprises in the GVCs.

Green Accounting, Corporate Governance and Firm Value in Southeast Asia Region

Objective –This study is to investigate the relationship between green accounting, managerial ownership, institutional ownership, independent commissioners and audit committees on firm value of mining companies in Southeast Asia region including Indonesia, Malaysia, Thailand, the Philippines and Vietnam.Design/Methodology –The method used is OLS with 500 samples of mining company observation data in the Southeast Asia for the 2016-2020 periods. GMM estimation is to address the potential endogeneity of the multiple variables used in the estimation, unobserved heterogeneity, and autocorrelation, which cannot be resolved with a fixed effect.Results –This study found that institutional ownership has positive significant effect on the firm value. Independent commissioners and audit committees have negative significant relationship with firm value of mining companies in the Southeast Asia, while green accounting and managerial ownership have no effect on the firm value.Research Limitations/Implications –There is no availability of data to access company’s annual reports from several countries and the annual reports of several countries are not made in English, educational background and social relations are not considered in measuring the independent board of commissioners and the audit committee. The results of this study can be used by company management in providing information about the percentage required for institutional ownership as a consideration in making decisions to increase company value.Novelty/Originality –The researcher's knowledge, this is the first research to investigate green accounting on firm value in mining company in the Southeast Asia region which is included in emerging markets.

How export and import concentration influence natural resources and green growth nexus in OECD countries

Green growth (GG) is a multifaceted phenomenon that maintains environmental sustainability with economic growth; however, the resource curse paradox inhibits economic growth. Therefore, it is indispensable to explore the promoting factors of GG, comprising export diversification (EXD), import diversification (IMPD), and natural resources (NR) for 33 selected OECD economies from 2010 to 2022. The system generalized moment method (System-GMM) is employed for empirical investigation, elucidating that EXD associates negatively with GG. However, IMPD significantly encourages the GG by unveiling the positive relationship. NR negatively associated with GG and confirms the resource curse hypothesis. The integrative impact of EXD and IMPD mitigates the resource curse, driving GG by 0.012% and 0.018%, respectively, implying that diversified trade structures in imports and exports convert the resource curse problem into a blessing. Besides, the alternative panel estimator affirms the empirical outcome endorsed by the system-GMM model. Among all variables, EXD, IMPD, and NR reveal the bi-directional causality, while remaining show the unidirectional association. The findings recommend valuable policy ramifications to policymakers of OECD countries in attaining green and low-carbon economies.

Impact of Covid-19 on Income Inequality; a Comparative Analysis for China and Italy

This study examines the impact of covid 19 on income inequality and comparison between China and Italy. Trends in Gini coefficient showed differentiated results for two countries. In this comparison various indicators came to consideration that affected inequality. For empirical investigation from the past data collected from World Development Indicators and Generalized methods of moments (GMM) for panel data analysis. Results indicated that poverty and unemployment have significant positive impact on income inequality while rate of taxes shown negative and significant impact on income inequality. These results supported many other studies but the post covid trend in Gini coefficient shows contradictory results. Rising trend in income inequality in China and falling trend in Italy drives the attention in mitigation policies. China preferred to save its population from corona virus and implemented strict stay at home and isolation policy. In this regard inequality showed rising trend. Whereas Italian government along with isolation and stay at home policies financed poor much and paid less attention to rich. In this way the gap between rich and poor came down. This study pays attention to the country-based policies reflecting government preferences and initiatives taken for betterment.

Construction of a composite fintech index to measure financial inclusion for developing countries

ABSTRACT This study estimates fintech-driven financial inclusion in developing economies across three dimensions: availability, penetration, and usage. To create a new composite fintech index (FI) to measure financial inclusion, we include indicators for mobile money and internet usage, elements often overlooked in prior research. Our dataset, a balanced panel from 2011–2021, is gathered from 40 developing countries. To overcome criticism related to the arbitrary selection of weights in nonparametric methods, we utilize a two-stage Principal Component Analysis (PCA) to construct the FI. We test the robustness of our FI by employing OLS regression and the two-step system generalized method of moments (GMM) estimation techniques. Our proposed index is the first composite fintech index that is robust and powerful across measuring methods, dimensions, and fintech proxies in developing countries. This versatile index is a functional tool for policymakers to identify gaps in financial inclusion and inform policy responses. In addition, remarkable progress in fintech scores between 2011 and 2021, welcoming the mobile, internet, and agent banking era for developing countries. However, the transition to fintech presents substantial challenges, including the requirements for large-scale investment, financial literacy, and customer protection – issues that policymakers, regulators, and financial institutions need to address.

Political Economy of Tourism Growth in Developing Countries: A Comparative Study of Pakistan and Bangladesh

Tourism is a big source of revenue for a country. Political Stability and good governance promote tourism growth of a country by providing a favorable environment for tourism. Present study is empirical evidence of Pakistan and Bangladesh to investigate the role of political stability and governance in tourism growth. Furthermore, along with the principal variable, the study also estimates the role of corruption in tourism growth. Panel times series data, from the year 1996 to 2021, was used for analysis of results. GMM estimation methodology has been employed which show that political stability and governance increase tourism growth in Pakistan and Bangladesh. The finding also shows that variables including in analysis are control of corruption, political economy is also a determinant of tourism. So, finding indicates that political economy along with significant economic growth is desirable for promoting tourism in Pakistan and Bangladesh. They study concludes that in order to promote tourism in Pakistan and Bangladesh. political stability, good governance, role of law, and regulatory quality are significant.

Environment, Institutional quality and corruption impact on Trade in Developing Countries

The objectives of this study are to examine the impact of environment, institutions and corruption on trade in developing countries. For this purpose, the study considers 37 developing countries and data from 1990 to 2021 has been used in this study and it is collected from World Development Indicators and the study has utilized the index for institutions and eight governance indicators developed by World Governance Indicators. Generalized method of moments (GMM) is employed on the panel data for estimation of econometric results. The results conclude that environment and institutions have positive effects on trade while corruption has negative effect on trade in developing countries.

Empirical Analysis of Financial Inclusion's Role in Economic Growth and Poverty Reduction in Sub-Saharan Africa

This research aims to investigate the correlation between financial inclusion (FI), economic growth (EG), and poverty reduction in several Sub-Saharan African (SSA) countries throughout the period of 2014-2021. The research used the generalized method of moments (GMM) econometric methodologies. A financial inclusion (FI) composite index was constructed using principal component analysis (PCA) to include the many attributes of FI indicators. The findings indicate a positive and significant impact of financial inclusion on economic development and a reduction in poverty in Sub-Saharan Africa. These results emphasize the crucial significance of legislators and governments giving priority to policies that enhance the availability, utility, and accessibility of financial goods and services. The outcome will include a reduction in poverty and an increase in equitable economic progress throughout Sub-Saharan Africa.

INSTITUTIONAL ENVIRONMENT AND MARKET STRUCTURE AS DRIVERS OF BANKING INDUSTRY PERFORMANCE

We analyze the effects of market concentration, income diversification, and institutional environment on banking industry performance. We used a sample of 168 countries for the 1994-2019 period and the GMM estimators for dynamic panel data regressions. Our results show that market concentration and diversification have a positive effect on bank performance. The institutional environment, both public-political and private-regulatory, has a negative effect on bank profitability, showing that these financial institutions obtain higher returns in countries with institutional weaknesses. When countries have a high institutional quality, the positive impact of market concentration and income diversification is reversed. Strengthening countries’ institutional quality makes it possible to combine competition between banks and specialization in traditional activities with higher performance. These results are relevant for bank stability and financial policy design, given that the institutional framework includes both direct and indirect channels that affect the general behavior and strategies of banks in the industry.We analyze the effects of market concentration, income diversification, and institutional environment on banking industry performance. We used a sample of 168 countries for the 1994-2019 period and the gmm estimators for dynamic panel data regressions. Our results show that market concentration and diversification have a positive effect on bank performance. The institutional environment, both public-political and private-regulatory, has a negative effect on bank profitability, showing that these financial institutions obtain higher returns in countries with institutional weaknesses. When countries have a high institutional quality, the positive impact of market concentration and income diversification is reversed. Strengthening countries’ institutional quality makes it possible to combine competition between banks and specialization in traditional activities with higher performance. These results are relevant for bank stability and financial policy design, given that the institutional framework includes both direct and indirect channels that affect the general behavior and strategies of banks in the industry.

Tax Planning, Corporate Tax Avoidance and Real Earnings Management: GMM Approach in Nigeria

The study examines the effect of tax planning and corporate tax avoidance on Real Earnings Management (REM) in Nigeria. Data were gathered from the financial reports of 58 listed non-financial firms for twelve years, from 2010 to 2021. Preliminary analyses such as descriptive statistics, correlation matrix, and variance inflation factor were conducted. The Generalized Method of Moments (GMM) was employed to identify a possible effect on REM. The study revealed that tax planning has a positive and significant effect on REM, while corporate tax avoidance has a negative and significant influence on REM. Also, leverage revealed a negative significant effect on REM, while firm growth has no significant effect on REM. However, firm size has a significant positive influence on REM. The study concludes that tax planning and corporate tax avoidance have a significant influence on REM. Thus, the study recommends that tax authorities should ensure that firm management engages in lowering capitalization limits, ensures first-in, first-out instead of last-in, reduces nonobligatory expenses for short periods, and ensures moderate deferred tax expenses in order to reduce REM through tax planning.

Resilience through mineral resource development, oil, and natural resource efficiency: Strengthening economies

This study examines the role of resilience in bolstering economies via the development of mineral resources and oil, alongside adaptability and natural resource efficiency, particularly within the G7 economies from 1995 to 2022. Employing the Generalized Method of Moments (GMM) model, the research aims to unravel the complexities of how resource-rich economies can leverage their natural assets to enhance economic resilience and sustainability. The investigation reveals a positive correlation between the strategic development of mineral resources, oil, and the adaptability of economies to external shocks, highlighting the critical importance of natural resource efficiency in ensuring long-term economic stability and growth. These findings underscore the necessity for G7 nations to implement policies that not only foster the responsible exploitation and development of natural resources but also promote adaptability and efficiency in resource use. The study's policy implication suggests a paradigm shift towards more sustainable and resilient economic models, emphasizing the balanced integration of resource development and environmental stewardship.

The Asymmetric Effects of Consumer Confidence on Credit Card Spending in Turkey

This paper analyzes the asymmetric effects of consumer confidence on personal credit card expenditures in Turkey. To this end, the impact of the consumer confidence index on real credit card spending is investigated from January 2013 to June 2023 using the threshold generalized method of moments (GMM). The linear GMM model findings indicate that consumer confidence increases real credit card expenditures. Furthermore, when the threshold GMM model is estimated using the annual percentage change of the consumer confidence index as a threshold variable, the coefficients differ across low- and high-confidence regimes. More specifically, the consumer confidence index has a statistically significant positive impact on credit card expenditure in the low-confidence regime but not in the high-confidence regime. This indicates that the optimistic expectations of economic units in a low-confidence environment may stimulate credit card spending.

The Impact Of Islamic Finance, Economic Growth, And Globalization On CO2 Emissions

This paper examines the impact of Islamic finance, economic growth, and globalization (economic, social, political, and overall aspects) on carbon dioxide emissions in 4 countries for the period 2015-2020. Employing the System GMM estimation method, which fulfills criteria for model unbiasedness, validity, and consistency. Findings reveal that Islamic finance, economic growth, and globalization simultaneously contribute to increasing and decreasing carbon dioxide emissions with a significance level of 0.010. Partially, Islamic finance and globalization’s overall aspect in short or long term contribute to a decrease in carbon dioxide emissions with a significance level of 0.010. Meanwhile, economic growth and globalization in economic, social, or political aspects in short or long term contribute to an increase in carbon dioxide emissions with a significance level of 0.010. This scientific article provides a new contribution to the research results that have been obtained with a significance level of 0.010 or 99 per cent confidence level.