Search

We quantify a production-based asset pricing model with fixed and variable capitals based on the GMM structural estimation. The estimation results match the stylized characteristics of the U.S. stock market return and help enlighten the equity premium puzzle. In addition, the model performance is reliable throughout the business cycle. [ABSTRACT FROM AUTHOR]

This paper focuses on analysing the effects of sector orientation and the origin of FDI on the types of corruption. The GMM technique and the IV-2SLS on a panel of Sub-Saharan African countries were used. Globally, we find that FDI increases political corruption in SSA. Moreover, the study shows that sector orientation and the origin of FDI have significant effects on each type of corruption. Primary sector FDI enhances public sector corruption and reduces judicial corruption. Secondary sector FDI increases executive, public, and judicial corruption. In the tertiary sector, executive and public corruption are enhanced while judiciary corruption is reduced. Regarding the origin, FDI from France increases public sector corruption whereas FDI from China and the USA reduces it. Executive corruption is reduced by FDI, regardless of its origin. FDI from France and the USA discourages judiciary corruption while FDI from China increases it. FDI from China reduces legislative corruption, while FDI from the USA tends to increase it. Furthermore, the analysis of the transmission channels shows education and development levels as important channels through which FDI could reduce corruption in SSA. Relevant policy implications derived from this study include the necessity for policy-makers to combat all types of corruption and mostly public corruption. [ABSTRACT FROM AUTHOR]

This study set out to investigate the role played by human capital development in the nexus between financial inclusion and economic growth in Africa. We use GMM as the estimation technique to analyze country-level data pooled from 40 African countries from 2005 to 2018. The findings suggest the presence of a non-linear U-shaped relationship between financial inclusion and economic growth. It was also found that human capital development fully mediates the relationship between financial inclusion and economic growth in Africa. Hence, the growth-enhancing benefits of financial inclusion are transmitted through human development. Whilst pursuing their financial inclusion targets, efforts should be made by governments across the African continent to simultaneously improve the level of human capital development to realize the positive benefits of financial inclusion. Plain language summary: Providing people with easy access to affordable financial services is seen as one of the surest ways to promote economic prosperity. Whilst some studies have been conducted to test this assertion, their findings are mostly conflicting. We attempt to unravel this puzzle in Africa by arguing that the relationship is both negative and positive depending on the extent to which people have access to financial services. We argue that the possibility that access to finance will promote economic prosperity is dependent on the productive capacity of the people. To empirically test these, we collect archival data across 40 African countries from 2005 to 2018 which we analyzed using the GMM regression technique. We conclude from our findings that, the effect of access to finance on the economy is negative when a large proportion of the population is excluded from the financial system. However, as many more people obtain access to financial services the effect becomes positive. Also, we conclude that access to finance improves overall economic well-being via an enhancement of the productive capacity of the population. Therefore, we recommend that policymakers across the continent speed up their efforts to ensure near-universal access by the adult population to financial services; in that, it is then that the positive benefits on the economy will be guaranteed. Our study did not determine the exact level of access required to transform the effects of access to finance from negative to positive due to data limitations and this can be addressed in future research. [ABSTRACT FROM AUTHOR]

Our study is the first to analyze the influence of CEO power and ownership structures on earning manipulation. This study also clarifies whether different ownership structures discourage powerful CEOs from manipulating earnings in family businesses. The sample data is a balanced panel with 985 observations of 116 family businesses in Vietnam from 2005 to 2020. We primarily employ the dynamic system Generalized Method of Moments with cross-sectional fixed effect to overcome endogeneity and heterogeneity issues. Our findings indicate the negative relationship between CEO power and earning manipulation. Higher state or institutional ownership restrains powerful CEOs from manipulating earnings in family businesses. However, Powerful CEOs in family businesses with higher participation of blockholders increase the earning manipulation. Our robustness results show that CEOs from 50 to 70 years old reduce earning manipulation the most in family businesses. Our findings support agency theory, stewardship theory, resource dependency theory, monitoring and accountability theory, legal framework theory, reputation theory, monitoring theory, Maslow's need hierarchy, and prior literature. Our study contributes practical policy and management implications to sustainably reduce earning manipulation in family businesses. [ABSTRACT FROM AUTHOR]

Speaker verification is a biometric-based method for individual authentication. However, there are still several challenging problems in achieving high performance in short utterance text-independent conditions, maybe for weak speaker-specific features. Recently, deep learning algorithms have been used extensively in speech processing. This manuscript uses a deep belief network (DBN) as a deep generative method for feature extraction in speaker verification systems. This study aims to show the impact of using the proposed method in various challenging issues, including short utterances, text independence, language variation, and large-scale speaker verification. The proposed DBN uses MFCC as input and tries to extract more efficient features. This new representation of speaker information is evaluated in two popular speaker verification systems: GMM-UBM and i-vector-PLDA methods. The results show that, for the i-vector-PLDA system, the proposed feature decreases the EER considerably from 15.24 to 10.97%. In another experiment, DBN is used to reduce feature dimension and achieves significant results in decreasing computational time and increasing system response speed. In a case study, all the evaluations are performed for 1270 speakers of the NIST SRE2008 dataset. We show deep belief networks can be used in state-of-the-art acoustic modeling methods and more challenging datasets. [ABSTRACT FROM AUTHOR]

EFSA was requested by the European Commission (in accordance with Article 29 of Regulation (EC) No 178/2002) to provide a scientific opinion on the application of new developments in biotechnology (new genomic techniques, NGTs) to viable microorganisms and products of category 4 to be released into the environment or placed on the market as or in food and feed, and to non‐viable products of category 3 to be placed on the market as or in food and feed. A horizon scanning exercise identified a variety of products containing microorganisms obtained with NGTs (NGT‐Ms), falling within the remit of EFSA, that are expected to be placed on the (EU) market in the next 10 years. No novel potential hazards/risks from NGT‐Ms were identified as compared to those obtained by established genomic techniques (EGTs), or by conventional mutagenesis. Due to the higher efficiency, specificity and predictability of NGTs, the hazards related to the changes in the genome are likely to be less frequent in NGT‐Ms than those modified by EGTs and conventional mutagenesis. It is concluded that EFSA guidances are 'partially applicable', therefore on a case‐by‐case basis for specific NGT‐Ms, fewer requirements may be needed. Some of the EFSA guidances are 'not sufficient' and updates are recommended. Because possible hazards relate to genotypic and phenotypic changes introduced and not to the method used for the modification, it is recommended that any new guidance should take a consistent risk assessment approach for strains/products derived from or produced with microorganisms obtained with conventional mutagenesis, EGTs or NGTs. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The main goal of this paper is to study the effect of governance on economic growth. Our main focus is on the 17 Middle Eastern and North African (MENA) countries during the period 2002- 2018. Using a dynamic panel System GMM approach by Blundell and Bond (1998). We found insignificant effect of Governance on economic growth in the MENA countries. The nature of the relationship between growth and governance explains the outbreak of the "Arab Spring" in some countries of the region which revealed pervasive corruption, especially in the political sector, also the region have been vulnerable to global, financial and political crises, negatively impacting its prospects of economic growth. [ABSTRACT FROM AUTHOR]

In this paper, we study the asymptotic behavior of specification tests in conditional moment restriction models under first‐order local identification failure with dependent data. More specifically, we obtain conditions under which the conventional specification test for conditional moment restrictions retains its standard normal limit when first‐order local identification fails but global identification is still attainable. In the process, we derive some novel intermediate results that include extending the first‐ and second‐order local identification framework to models defined by conditional moment restrictions, establishing the rate of convergence of the GMM estimator and characterizing the asymptotic representation for degenerate U‐statistics under strong mixing dependence. Importantly, the specification test is robust to first‐order local identification failure regardless of the number of directions in which the Jacobian of the conditional moment restrictions is degenerate and remains valid even if the model is first‐order identified. [ABSTRACT FROM AUTHOR]

This study investigates the firms' performance following cross-border mergers and acquisitions (M&As) from 2000 to 2022, employing the generalized method of moments (GMM) technique within the French context. Grounded in the theories of organizational learning and the institutional-based view, the empirical findings reveal that acquiring firms exhibit an improved long-term performance after engaging in cross-border M&A deals. Additionally, acquisition experience and industry relatedness significantly enhance the firms' performance. Institutional quality and cultural similarity are also found to positively moderate the impact of cross-border M&As on firms' performance. [ABSTRACT FROM AUTHOR]

The study aims to ascertain the key determinants of firm value and to analyze the contribution of each determinant at different percentiles of the probability distribution of firm value for 1,592 firms across eight major Indian manufacturing firms. The sample consists of data from 2009 to 2020 and studies the variables such as enterprise value, effective tax rate, firm size, profitability, firms' growth rate, financial leverage, asset tangibility, and non-debt tax shield. The study employed, linear, non-linear, and non-parametric panel regression models. Quantile regression models are further used to decompose the determinants at various quantiles of firm value. Several diagnostic tests such as Breusch–Pagan, White's Test, and Sargan Test are used to ensure robust estimates. The results obtained from this study show the presence of a concave relationship between firm value with firm size, financial leverage, and non-debt tax shield. Effective tax rates and inflation rates substantially and positively affect the value of firms in higher percentiles. The capital structure is found to significantly and positively affect the value of firms in the lower percentile. The profitability is also found to contribute to the value of firms across all the quantiles, whereas sales growth fails to strongly drive the value. [ABSTRACT FROM AUTHOR]

Drawing from 645 microfinance institutions across 56 countries, this paper examines the deposit‐borrowing dynamic of microfinance institutions' source of capital. We find that deposits and borrowings are substitutes rather than complements. We further find that the degree of substitutability is more pronounced among microfinance institutions operating in a developed financial sector where the level of information asymmetry is lower. Our findings represent novel contribution in understanding microfinance institutions' funding behaviour that supports its quest for further growth and long‐term sustainability. [ABSTRACT FROM AUTHOR]

Climate change is one of the main issues facing countries in sub‐Saharan Africa. Improving green productivity is essential for transitioning to low‐carbon economies and mitigating climate change in this region. The existing literature does not emphasise the role of the energy transition in green productivity growth. Yet this analysis is important given the essential role of energy in the production process and the high endowment of renewable energy sources in the area. Thus, this paper contributes to the literature by examining the effect of the renewable energy transition on green productivity growth through a convergence analysis for 35 sub‐Saharan African countries from 2000 to 2020. The results of the logt test reveal the existence of three main convergence clubs in terms of green productivity. The first club with low productivity is made up of 23 countries, the second club with average productivity contains 8 countries, and the third club with high productivity comprises 3 countries, while 1 country is divergent. The renewable energy transition is a determining factor in the formation of these convergence clubs. Indeed, the results of the ordered logit regression show that an increase in the level of the renewable energy transition has a positive impact on the probability of countries joining convergence clubs with higher green productivity. Further analysis with the Generalized Method of Moment (GMM) reveals that the critical threshold for renewable energy share in the energy mix that allows countries to converge globally toward the green productivity frontier in the long term is 32.63%. Regarding policy implications, the results highlight the need to encourage the renewable energy transition to increase green productivity in sub‐Saharan African countries. This could involve strengthening policies to promote investment in the sector (creation of green funds and/or tax incentives) and subsidies for renewable energy consumption. [ABSTRACT FROM AUTHOR]

Digital trade (DT), a key component of today's digital economy, is pivotal in attaining "carbon neutrality and carbon peaking", essential for low-carbon and high-quality growth. This study delves into the intermediary role of carbon emissions (CE) reduction in DT, analyzing both production and consumption angles, and examines the moderating influences of CE in DT through industrial agglomeration and low-carbon pilot policy. The research employs spatial panel and system GMM models for an empirical investigation. On the production side, the scale and technological effects on CE outweigh the structural impact on emissions. In terms of consumption, the mediating role of urban residents' consumption upgrading is to enhance the effect of DT on reducing CE by promoting consumption upgrading, whereas the mediating role of rural residents' consumption upgrading is to promote consumption upgrading but weaken the effect of DT on reducing CE. Regarding regulatory influences, the factor of industrial agglomeration tends to diminish the impact of DT on reducing CE; thus, industrial agglomeration does not amplify the reduction effect of DT on CE. Low-carbon pilot policy(pol)s can enhance the CE reduction effect of DT, showing stronger CE reduction effects in provinces participating in low-carbon pilot programs. [ABSTRACT FROM AUTHOR]

This study contributes to income equality (IE) literature by examining four important issues. First, the study examines the effects of foreign bank presence (FBP) on IE. Second, the paper identifies the minimum threshold level of FBP which can lead to IE. Third, the effect of economic freedom on IE was investigated. Fourth, the paper determines whether economic freedom interacts with FBP to minimise IE. The findings are based on macro data for 33 African countries from 1995 to 2020. The findings from the two-stage system generalised method of moment indicate that unconditionally, FBP reduces income inequality. Also, results from the threshold effect reveal that whilst FBP reduces income inequality, if it exceeds 52%, it may contribute to it. Additionally, the study reveals that economic freedom dampens IIE. Furthermore, economic freedom conditions FBP to reduce IE. Based on these findings, policymakers are advised to exercise caution in attracting foreign banks and to promote local financial institutions. Policymakers are also advised to implement policies to promote economic freedom. [ABSTRACT FROM AUTHOR]

In the current scenario, liver abnormalities are one of the most serious public health concerns. Cirrhosis of the liver is one of the foremost causes of demise from liver diseases. To accurately predict the status of liver cirrhosis, physicians frequently use automated computer-aided approaches. In this paper, through clustering techniques like fuzzy c-means (FCM), possibilistic fuzzy c-means (PFCM), and possibilistic c means (PCM) and sample entropy features are extracted from normal and cirrhotic liver ultrasonic images. The extracted features are classified as normal and cirrhotic through the Gaussian mixture model (GMM), Softmax discriminant classifier (SDC), harmonic search algorithm (HSA), SVM (linear), SVM (RBF), SVM (polynomial), artificial algae optimization (AAO), and hybrid classifier artificial algae optimization (AAO) with Gaussian mixture mode (GMM). The classifiers' performances are compared based on accuracy, F1 Score, MCC, F measure, error rate, and Jaccard metric (JM). The hybrid classifier AAO–GMM, with the PFCM feature, outperforms the other classifiers and attained an accuracy of 99.03% with an MCC of 0.90. [ABSTRACT FROM AUTHOR]

This paper explores the influence of corporate governance on the profitability and credit risk of a sample of listed banks in Tunisia. The methodology involves two main steps. Firstly, principal component analysis is employed to construct a novel governance index, assessing the quality of both internal and external bank governance. This index takes into account the degree of compliance and application of directives and laws mandated by the Tunisian Central Bank regarding banking governance. In the second step, panel data analysis is conducted to scrutinize the impact of internal and external governance mechanisms on the profitability and risk of Tunisian banks. The results reveal that as the governance index increases, the profitability of banks improves in terms of return on assets and stock market performance. Additionally, a higher governance index is correlated with a reduction in credit risks, as indicated by lower instances of non‐performing loans and an increased rate of coverage for classified debts. To enhance the robustness of our results, we calculate a standard governance score based on existing empirical literature. Furthermore, to account for potential endogeneity, we employ the two‐step system generalized method of moments. [ABSTRACT FROM AUTHOR]

The study investigates the effect of FinTech on financial inclusion in Southern African Development Community (SADC) member states over the period 2011–2021, while also looking at the transmission channels. The study adopts a battery of econometric techniques such as ordinary least squares (OLS), the two‐step system generalized method of moments (GMM) and the Driscoll and Kraay covariance estimator. The study finds that FinTech (proxied by digitization) deepens financial inclusion (access to loan) and a decline in the number of bank branches in SADC member states. This is logical since the operations of FinTech are digital. This implies that an attempt to promote financial inclusion by traditional means such as building physical bank structures may be limited, especially in Africa where large swathes of the populace remain unbanked. As expected, FinTech (measured by automated teller machines [ATMs]) increases the number of bank branches in SADC. We also find that mobile cellular subscription, the share of population with access to electricity and Internet access and mean years of schooling are important transmission channels of FinTech to financial inclusion in SADC. In general, the result shows that FinTech enhances and deepens financial inclusion in SADC member states. The research and policy implications are discussed. [ABSTRACT FROM AUTHOR]

This paper identifies the dimensions of international trade in services that promote export product diversification in an unbalanced panel of 48 countries in Sub-Saharan Africa (SSA) over the period 2005–2019. Using the two-step system Generalized Methtod of Moments (GMM), the results show that tourism, total services exports, export in transport services, travel services, insurances services, financial services, use of licenses services and other business services promote export product diversification in SSA. Policy makers can make commercial services export an important lever for export products diversification by adopting policies and strategies to develop and orient the commercial services towards more efficient and high value-added services. [ABSTRACT FROM AUTHOR]

Purpose: Consumer goods firms often tie up inventory and accounts receivable resources, creating cost and liquidity issues. Dynamic working capital management (DWCM) can mitigate these concerns and enhance operational profitability. The study investigates DWCM's impact on operational efficiency (OE). Design/methodology/approach: The empirical estimation uses pooled ordinary least squares (OLS), random effect and system generalized method moments (GMM) regression analysis of consumer goods firms in Scandinavia from 2005 to 2022 to present the results. Findings: The findings indicate that DWCM has an inverse relationship with operating cost, while positively impacting operating profit. The final outcome demonstrates that DWCM enhances OE. Furthermore, the working capital ratio (WCR) consistently exceeds the cash conversion cycle (CCC) in all models, indicating that prudent management of cash in accounts receivable, inventory and accounts payable leads to higher cost savings and superior performance. Practical implications: The results suggest that organizations that prioritize the management of the absolute cash committed to inventory, receivables and payables as much as the CCC experience improved OE. Originality/value: This paper adds to the literature on how DWCM affects OE in the consumer goods sector. It also highlights the impact of time management and cash management in WCM on OE. Additionally, it analyzes how DWCM variables affect operating costs and profits, shedding light on their efficiency impact. [ABSTRACT FROM AUTHOR]

Countries around the world have shown concerns towards the sustainability aspects of the firms for their long-term growth and survival. The representation of women directors on board is often looked as a positive sign for improving various governance related aspects. Based on this premise, the study investigated the relationship between gender diversity on board and sustainability reporting using a sample of 220 firms for a period of 5 years (2018–2022). The study used rigorous framework based on ESG scores developed by CRISIL to measure the sustainability reporting in the Indian context. The analysis was conducted with the help of dynamic panel data regression models, and it was found that gender diversity positively impacts corporate sustainability disclosure. The study is unique in the context of India which is an emerging economy and provides valuable suggestions for improving the governance and sustainability practices by firms in India. [ABSTRACT FROM AUTHOR]

This study analyzes the mediating effect of human capital between foreign direct investment and economic growth and establishes the human capital threshold for the last 15 least developed African countries over the period from 2000 to 2019. The used econometric technique GMM and the regression of the dynamic threshold (TR) showed that foreign direct investment and human capital have no significant impact on economic growth. If the term 'interaction' between foreign direct investment and human capital has been introduced into the model, the effect of foreign direct investment becomes positive and significant. However, the coefficient of the interaction term is negative and statistically significant. This presupposes that countries do not have a sufficient labor force to absorb and disseminate the benefits of foreign direct investment. For this reason, this study applied the TR to determine the minimum level of human capital and established a threshold of 61.57%. It therefore becomes relevant for decision-makers in the countries concerned to develop human capital to strengthen their absorption capacities in order to reap the full benefits of foreign direct investment. [ABSTRACT FROM AUTHOR]

The literature on democracy and corruption is inconclusive on the effect of democracy on corruption. We intend to supplement this void by arguing that interaction between democracy and unemployment may exist in shaping the de facto corruption levels. This paper examines whether such conjuncture exists. We estimate a linear dynamic panel-data model using data from 80 developing countries over the period 1990–2018. We find that democracy reduces corruption. However, the potential beneficial effect of democracy on corruption is eroded by a higher unemployment rate. The results are robust and quantitatively similar across different empirical specifications. These results imply that developing countries should focus on decreasing the unemployment level so as to take advantage of democratization in their fight against corruption. [ABSTRACT FROM AUTHOR]

This paper delves into the fascinating world of bank capital and its profound impact on banking sector productivity in the CEMAC region. Drawing on data from respected sources such as the Central African Banking Commission, the Bank of Central African States and the World Bank spanning more than two decades (1998–2022), this study uses cutting-edge tools such as the Malmquist index and the GMM to uncover the intricate relationship between bank capital, efficiency and overall productivity. The results are eye-opening, showing that a robust level of bank capital is not only important, but essential for enhancing the competitiveness, stability and productivity of CEMAC banks. This, in turn, propels them to new heights of market dominance, making them more attractive to both local and international investors. In essence, bank capital is emerging as a linchpin in the growth and development of the region’s banking sector, setting the stage for a bright and prosperous future. [ABSTRACT FROM AUTHOR]

Traditional commercial banks are impacted by financial disintermediation amid the advent of online banking. Lower revenue has forced banks to focus on new non-interest revenue to increase bank revenue. With banks' serious efforts toward digital transformation, this study is interested in examining whether digital transformation can affect non-interest income in China. Nonetheless, as the net profit of Chinese banks has dropped by 4.95 percent, rapid digital transformation does not promote non-interest income effectively. This study foresees the crucial role of financial inclusion in moderating the case and sets this as the ultimate aim of this study. This article uses the GMM to conduct an empirical study on the data of 116 banks from 2014 to 2021. As expected, the results show a non-favorable effect of digital transformation on non-interest income, but financial inclusion successfully brings a positive note. Hence, to grow together with customers, while initially, banks may have to lower the interest charges, efforts to enhance everyone's pursuit for a better financial life may help banks to enjoy more profit via higher non-interest income. [ABSTRACT FROM AUTHOR]

Copyright of Jurnal Ilmu Ekonomi Terapan is the property of Universitas Airlangga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Geo-referenced data are characterised by an inherent spatial dependence due to geographical proximity. In this paper, we introduce a dynamic spatiotemporal autoregressive conditional heteroscedasticity (ARCH) process to describe the effects of (i) the log-squared time-lagged outcome variable, the temporal effect, (ii) the spatial lag of the log-squared outcome variable, the spatial effect, and (iii) the spatiotemporal effect on the volatility of an outcome variable. We derive a generalised method of moments (GMM) estimator based on the linear and quadratic moment conditions. We show the consistency and asymptotic normality of the GMM estimator. After studying the finite-sample performance in simulations, the model is demonstrated by analysing monthly log-returns of condominium prices in Berlin from 1995 to 2015, for which we found significant volatility spillovers. [ABSTRACT FROM AUTHOR]

The objective of this study is to investigate the effects of the shadow economy on environmental pollution and how this effect depends on the levels of corruption. The study utilizes an annual panel dataset of 127 selected developing countries worldwide, spanning from 2002 to 2018, and employs the Generalized Method of Moments (GMM) technique, which effectively addresses potential endogeneity issues in the model. The estimation results reveal that the shadow economy increases the level of environmental pollution. Furthermore, the results indicate that corruption intensifies the impacts of the shadow economy on environmental pollution. This highlights a significant complimentary between the shadow economy and corruption, indicating that an increase in the levels of corruption will lead to an increase the shadow economy and will also strengthen its harmful impact on environmental pollution through the channel of corruption. Additionally, the estimates remain robust when using alternative measure of the shadow economy. [ABSTRACT FROM AUTHOR]

Abstract Machine learning (ML) has been used in human gait data for appropriate assistive device prediction. However, their uptake in the medical setup still remains low due to their black box nature which restricts clinicians from understanding how they operate. This has led to the exploration of explainable ML. Studies have recommended local interpretable model‐agnostic explanation (LIME) because it builds sparse linear models around an individual prediction in its local vicinity hence fast and also because it could be used on any ML model. LIME is however, is not always stable. The research aimed to enhance LIME to attain stability by avoid the sampling step through combining Gaussian mixture model (GMM) sampling. To test performance of the GMM‐LIME, supervised ML were recommended because study revealed that their accuracy was above 90% when used on human gait. Neural networks were adopted for GaitRec dataset and Random Forest (RF) was adopted and applied on HugaDB datasets. Maximum accuracies attained were multilayer perceptron (95%) and RF (99%). Graphical results on stability and Jaccard similarity scores were presented for both original LIME and GMM‐LIME. Unlike original LIME, GMM‐LIME produced not only more accurate and reliable but also consistently stable explanations.

Purpose – The present study investigates the effect of foreign direct investment (FDI) and governance quality on carbon emissions in the Economics Community of West African States (ECOWAS). Design/methodology/approach – To achieve the objective of this research, panel data for dependent and explanatory variables over the period 2005–2016, collected in the World Development Indicators (WDI) database and World Governance Indicators (WGI), are analyzed using the generalized method of moments (GMM). Also, the panel-corrected standard errors (PCSE) method is applied to the four segments of the overall sample to analyze the stability of the results. Findings – The findings of this study are (1) FDI inflows have a negative effect on carbon emissions in ECOWAS and (2) The interaction between FDI inflows and governance quality have a negative effect on carbon emissions. These results show the decreasing of environmental damage by increasing institutional quality. However, the estimation results on the country subsamples show similar and non-similar aspects. Practical implications – This study suggests that policymakers in the ECOWAS countries should strengthen their environmental policies while encouraging FDI flows to be environmentally friendly. Originality/value – The subject has rarely been explored in West Africa, with gaps such as the lack of use of institutional variables. This study contributes to the literature by drawing on previous work to examine the role of good governance on FDI and the CO2 emission relationship in the ECOWAS, which have received little attention. However, this research differs from previous work by subdividing the overall sample into four groups to test the stability of the results.

Poverty in Indonesia is a problem that needs special attention by the government. Poverty is due to the high level of inequality, unequal distribution of income, and the number of poor people, which continue to increase. Therefore, it can affect society’s economy. This research aims to identify incongruities between endogenous and exogenous variables that influence poverty levels in Indonesia. By applying a descriptive quantitative analysis approach for 2013-2022 in the form of secondary data from the Indonesian Central Statistics Agency, the research model uses dynamic panel data regression analysis based on the Generalized Method Of Moment method (GMM). The method was developed by Arellano-Bond, of which the two best models are First-Difference GMM and System GMM, which create an impartial, consistent, and efficient model for determining short-term ang long-term effects. The research results show that HDI has a significant negative impact on short-term and long-term relationships with poverty levels, resulting in low human resources. Exports have a significant negative impact on poverty levels in the short and long term. This means that if exports increase, poverty levels can be reduced. Imports have a significant positive impact on short-term and long-term with poverty levels. In import activities, the higher the price increases, the more people's purchasing power decreases. The results are declared to have a significant effect because the p-value is significance of level 5% or 0.05. It is expected that the research will become reference material for macroeconomic development and further research regarding poverty alleviation.