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The purpose of this paper is mainly to develop the adjoint method within the method of magnetic moment (MMM) and thus, to provide an efficient new way to solve topology optimization problems in magnetostatic to design 3D-magnetic circuits.

First, the MMM is recalled and the optimization design problem is reformulated as a partial derivative equation-constrained optimization problem where the constraint is the Maxwell equation in magnetostatic. From the Karush–Khun–Tucker optimality conditions, a new problem is derived which depends on a Lagrangian parameter. This problem is called the adjoint problem and the Lagrangian parameter is called the adjoint parameter. Thus, solving the direct and the adjoint problems, the values of the objective function as well as its gradient can be efficiently obtained. To obtain a topology optimization code, a semi isotropic material with penalization (SIMP) relaxed-penalization approach associated with an optimization based on gradient descent steps has been developed and used.

In this paper, the authors provide theoretical results which make it possible to compute the gradient via the continuous adjoint of the MMMs. A code was developed and it was validated by comparing it with a finite difference method. Thus, a topology optimization code associating this adjoint based gradient computations and SIMP penalization technique was developed and its efficiency was shown by solving a 3D design problem in magnetostatic.

This research is limited to the design of systems in magnetostatic using the linearity of the materials. The simple examples, the authors provided, are just done to validate our theoretical results and some extensions of our topology optimization code have to be done to solve more interesting design cases.

The problem of design is a 3D magnetic circuit. The 2D optimization problems are well known and several methods of resolution have been introduced, but rare are the problems using the adjoint method in 3D. Moreover, the association with the MMMs has never been treated yet. The authors show in this paper that this association could provide gains in CPU time.

While science has researched the impact of air pollution on human health, the economic dimension of it has been less researched so far. Renewable energy consumption is an important factor in determining the level of life expectancy and reducing health expenditure. Thus, this study aims to investigate the impact of renewable energy, carbon emissions, health expenditure and urbanization on life expectancy in G-7 countries over the period of 2000–2019.

This study has adopted a novel Method of Moments Quantile Regression (MMQR). Furthermore, as a robustness check for MMQR, the fully modified ordinary least square, dynamic ordinary least squares and fixed effect ordinary least square estimators have been used.

The results indicated that renewable energy consumption, health expenditure and urbanization lead to an increase in life expectancy across all quantiles (5th to 95th), whereas higher carbon dioxide emissions reduce life expectancy at birth across all the quantiles (5th to 95th).

The empirical findings conclude that governments should recognize their potential in renewable energy sources and devise policies such as tax-related regulations, or relevant incentives to encourage further investments in this field.

This paper in comparison to the other research studies used MMQR to investigate the impact of factors affecting life expectancy. Also, to the best of the authors’ knowledge, so far no study has investigated the impact of renewable energy on life expectancy in G-7 countries.

The purpose of this paper is to investigate the influence of macroeconomic cyclical indicators and country governance on bank non-performing loans in African countries.

Data was collected from the 53 African countries covering 2005–2021. The paper develops an empirical model to examine the impact of country governance in reducing macroeconomic cycle-induced adverse effects on bank credit risk. This research estimates Random Effects models and the General Method of Moment to examine the link between microeconomic and governance factors on bank non-performing loans. Stata version 15.1 was used to conduct panel regression analysis.

The findings of the study revealed that the generalized method of moments findings contributes valuable insights into the persistence of NPLs over time and the specific effects of variables on NPL levels. The study findings highlight that the debt-to-GDP ratio, unemployment, regulatory quality, government effectiveness and inflation have significant relationships with NPLs, shedding light on their specific contributions to credit risk dynamics.

The focus on a specific set of determinants for NPLs, which may not capture all the factors that influence NPL levels. Thus, the study did not consider the impact of macroeconomic shocks, such as natural disasters or global economic crises, which can have a significant impact on NPLs.

Policymakers should prioritize maintaining sustainable debt levels, promoting employment growth and controlling inflation rates to mitigate credit risk and reduce nonperforming loans. Also, enhancing regulatory quality and government effectiveness is crucial in ensuring financial stability and minimizing non-performing loans in Africa.

This paper provides a new possible solution to minimise bank non-performing loans risk by examining interactions of country governance regarding the macroeconomic cycle behaviour.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0729

The purpose of this study is to analyze the effect of off-balance sheet activities on the credit risk of African banks.

The theory about the relationship between off-balance sheet activities and bank risk was used to construct a conceptual model of the effect of off-balance sheet on credit risk in an African context. The accounting approach is chosen by collecting accounting data extracted from the annual reports of 24 private and conventional African banks during the period 2010–2019. Both statistical and empirical studies are conducted. The statistical study aims to give a description of sample banks in terms of off-balance sheet activities and key financial indicators. The empirical study has the goal of exploring the correlations between, on the one hand, credit risk and, on the other hand, off-balance sheet ratio and control variables (bank- and country-specific variables). This study is based on dynamic panels using the two-step generalized method of moments technique to estimate regressions between credit risk and the explanatory variables.

The statistical study reveals that sample banks use moderately off-balance sheet activities; most of them use essentially guarantees and letters of credit, have satisfactory financial indicators and are slightly exposed to credit risk. The empirical results from the two-step generalized method of moments technique disclose that off-balance sheet activities have an intensifying effect on the credit risk of African banks. However, the increasing effect can be minimized when African banks use moderately off-balance sheet activities.

Using judiciously off-balance sheet activities does not exacerbate the exposure of African banks to credit risk. Therefore, managers of African banks are recommended to maintain a moderate level of off-balance sheet activities, especially guarantees and letters of credit.

The findings of this study eliminate the opacity about the effect of off-balance sheet activities on credit risk. Moreover, this study fulfills the huge gap in the related literature by completing the scarcity of recent studies, considering all items of the off-balance sheet, focusing on the African context, describing off-balance sheet activities and financial indicators of sample banks due to a statistical study and estimating regressions of dynamic panels between credit risk and both bank-specific and country-specific variables due to a two-step generalized method of moments technique.

The main objective of this article is to analyze the role of governance quality in influencing the economic growth of 22 selected Sub-Saharan African Countries.

The study applied the panel dynamic Generalized Method of Moments (GMM) to analyze the data obtained from the World Bank database over the period from 2002 to 2020.

The overall finding indicated that the composite governance index has a positive significant effect on the economic growth of the countries; where a unit improvement in the aggregate governance index leads to a 3.05% increase in GDP. The disaggregated result has shown that corruption control and government effectiveness have a negative significant effect on growth performance, whereas, the rule of law and regulatory quality showed a positive significant effect. Political stability and voice and accountability have an insignificant effect on economic growth.

Due to data limitations, this study could not address the whole members of Sub Sahara African Countries and could not see the causal relationship.

The study suggested a strong commitment to the implementation of policy and reform measures on all governance factors. This may add to the need to devise participatory corruption control mechanisms; to closely look at the proper implementation of policies and reforms that constitute the government effectiveness factors, and properly implement the rule of law at all levels of the government with a strong commitment to realizing it so that citizens at all levels can have full confidence in and abide by the rules of society.

Even though there are some studies conducted using conventional methods of panel data analysis such as random effect or fixed effects, this empirical study used more advanced panel dynamic generalized moment of methods to examine the role of improvement in governance quality on economic growth.

The performance of financial markets is significantly influenced by the political environment during general elections. This study investigates the effect of general elections on stock market performance in selected African markets.

Prior studies have been inconsistent in determining whether electioneering events negatively or positively influence stock market performance. The study utilized panel data set with annual observations from 1990 to 2020. The generalized method of moments (GMM) is employed to investigate the effect of electioneering and change in government on key stock market performance indicators, including stock market capitalization, stock market turnover ratio and the value of stock traded.

The study finds that electioneering activities generally have a positive impact on the performance of the stock market, whereas a change in government has a negative impact. As a result, the study recommends that stakeholders of the stock market remain vigilant and actively monitor electioneering events to devise and implement effective policies aimed at mitigating political risks during general elections. By adopting these measures, investor confidence can be significantly enhanced, fostering a more robust and secure investment environment.

The study investigates a neglected section of the literature by highlighting not only the effect of elections on stock market indicators but also possible change in government during elections.

The main purpose of this study is to evaluate the probability of default and examine the relationship between default risk and financial performance, with dynamic panel moderation of firm size.

This study utilizes a total of 1,500 firm-year observations from 2013 to 2018 using dynamic panel data approach of generalized method of moments to test the relationship between default risk and financial performance with the moderation effect of the firm size.

This study establishes the findings that default risk significantly impacts the financial performance. The relationship between distance-to-default (DD) and financial performance is positive, which means the relationship of the independent and dependent variable is inverse. Moreover, this study finds that the firm size is a significant positive moderator between DD and financial performance.

This study provides new and useful insight into the literature on the relationship between default risk and financial performance. The results of this study provide investors and businesses related to nonfinancial firms in the Pakistan Stock Exchange (PSX) with significant default risk's impact on performance. This study finds, on average, the default probability in KSE ALL indexed companies is 6.12%.

The evidence of the default risk and financial performance on samples of nonfinancial firms has been minimal; mainly, it has been limited to the banking sector. Moreover, the existing studies have only catered the direct effect of only. This study fills that gap and evaluates this relationship in nonfinancial firms. This study also helps in the evaluation of Merton model's performance in the nonfinancial firms.

This study aims to examine the role of financial inclusion and institutional factors such as corruption and the rule of law (RL) on the credit risk and stability of banks.

The study considers a sample of 61 developing countries and uses very robust estimation techniques that allow controlling for endogeneity, heteroskedasticity and serial correlation, such as instrumental variables method in two-stage least squares (IV-2SLS), instrumental variables generalized method of moments (IV-GMM), as well as system of generalized methods of moments in two stages (Sys-2GMM).

The results confirm that financial inclusion and strengthening the RL can significantly contribute to reducing credit risk and improving the financial stability of banks; in contrast, the authors find that weak control of corruption aggravates credit risk. In addition, they found that greater competitiveness in the banking sector increases credit risk.

This study supports the need to promote financial inclusion and strengthen institutional factors to improve the stability of the banking sector, as well as promote general well-being in the economy.

This study contributes to the scarce literature by simultaneously using institutional factors such as corruption and the RL and macroeconomic variables such as economic growth and inflation in the relationship between financial inclusion and the banking sector, as well as considering competitiveness as an explanatory factor for banks’ credit risk and stability.

Female entrepreneurship discussions will broaden and diversify as a result of global shifts. Studies of female entrepreneurship must take into account differences between male and female entrepreneurs due to the historical, cultural and social specificity of developing countries to narrow gender gaps, identify barriers, fine-tune support systems, release dormant potential and provide information for policymaking. This paper aims to measure and estimate the most crucial socioeconomic characteristics that Southeast Asian countries leverage to advance women’s business initiatives.

Using a panel data model whereby the Female Entrepreneurship Indicator Score serves as the dependent variable and the ten most important socioeconomic indicators serve as the independent variables. Ten southeast Asian countries are analyzed using the panel fixed effects approach of Method of Moments Quantile Regression (MM-QR) from 1980 to 2021.

It has been found by empirical panel quantile regression using the MM-QR method that the following indicators positively affect female entrepreneurship in southeast Asian countries: the assets indicator, the pay indicator, the workplace indicator, the mobility indicator and the a woman can sign a contract in the same way as a man indicator. But the parenthood indicator, the unemployment indicator, the school enrollment indicator, the men and women have equal ownership rights to immovable property indicator and the marriage indicator all have negative effects.

This paper uses a new method called MM-QR to look at how the most important socioeconomic factors affect female entrepreneurship in Southeast Asian countries. The results obtained will also add to and broaden the small amount of research that has been done on female entrepreneurs in developing countries.

This study examines the nexus of bond market development and economic growth from 2015 to 2022.

The system-generalized method of moments (GMM) is employed on economic growth, government market capitalization, corporate market capitalization, bond yield, interest rate spread, trade openness and investment level.

The findings show that the government bond market, corporate bond capitalization and bond yield positively impact the gross domestic product (GDP). The results equally reveal a causal link between the corporate bond market, bond yield and GDP.

Governments should emphasize creating, developing and sustaining bond markets in the economies of developing countries to boost economic activity by promoting structural transformation. Policymakers should improve the implementation of existing rules and regulations while complementing them with new ones since well-developed bond markets provide alternative sources of financing that make economies financially resilient. Policymakers should encourage the issuance of corporate bonds to enhance the efficiency of the capital markets and mobilize funds for economic growth stimulation. Governments and corporations should diversify their sources of funding into the bond markets since the bond yields are favorable to economic growth.

Earlier studies presented arguable results on the bond market development and economic growth nexus. Several findings indicate a positive link; others give a negative link between bond market development and economic growth. Some show causal directions, while other reveal none. The contradictory results motivate research. This research results contribute to the literature in that the government bond market, corporate bond capitalization and bond yield positively impact the GDP of developing nations.