Method Of Moments Estimator Research Articles

The role of macro institutional factors in determining types of entrepreneurial start-ups: a longitudinal panel study

Purpose What shapes entrepreneurs’ intention to allocate entrepreneurial effort towards different types of entrepreneurial start-ups? Grounded in a “national business systems” approach, the purpose of this paper is to examine the impacts of institutional dimensions on Schumpeterian and Kirznerian entrepreneurship. Design/methodology/approach Drawing upon a global context comprising 82 countries over the period between 2007 and 2018, this research applies a dynamic panel modelling approach, namely, the dynamic panel generalised method of moments estimator. This estimator allows to account for unobserved country-specific heterogeneity and to address endogeneity constraints that might occur between institutions and entrepreneurship. Findings The findings reveal that there are positive relationships between financial capital and both Schumpeterian and Kirznerian entrepreneurship. Educational capital positively affects the allocation of entrepreneurial efforts towards opportunity-based entrepreneurial activities. Moreover, institutional regulatory conditions could hinder the allocation of entrepreneurs’ resources into a Schumpeterian while facilitating the allocation of resources into a Kirznerian type of venture. Finally, a higher level of corruption promotes innovative entrepreneurial activities (i.e. a Schumpeterian type of venture) and leads to constraints on Kirznerian entrepreneurship. Practical implications The research findings demonstrate the significance of the macro environment for enacting and implementing policies to reap the benefits of different types of start-ups. It suggests different political actions are needed to motivate highly qualified individuals to engage in Schumpeterian and Kirznerian entrepreneurship, rather than focusing purely on enhancing a country’s overall start-up rates. Originality/value By acknowledging the multidimensional nature of entrepreneurship, this research provides greater theoretical exposition and empirical support for the role played by macro-level institutions in determining types of entrepreneurship. It reveals the important role played by macro institutional conditions in influencing choices about different types of start-ups and gives rise to the multidimensional nature of entrepreneurship.

Moment estimation of uncertain autoregressive model and its application in financial market

Uncertain autoregressive model is a powerful analytical tool that uses uncertainty theory to predict future values based on previously observed values. In the study of uncertain autoregressive model, one of the core problems is how to estimate the unknown parameters and uncertain disturbance term in the model. In this paper, a moment estimation method for uncertain autoregressive model is proposed to determine these unknown parameters and uncertain disturbance term. Following that, the uncertain hypothesis test is used to verify the suitability of the estimated uncertain autoregressive model. In addition, we also provide a case study of Disney stock prices to illustrate the advantages of moment estimation method over other statistical inference methods.

Financial reporting quality dynamics in India: the role of IFRS convergence and corporate governance

Purpose This paper aims to investigate the impact of International Financial Reporting Standards (IFRS) convergence on value relevance and earnings management for Indian listed firms while also exploring whether the relationship is moderated by the firms’ corporate governance structures. Design/methodology/approach Corporate governance (CG) scores of 573 listed firms were calculated by using a self-constructed index for a period of 7 years (2014–2015 to 2020–2021). Static and dynamic panel models with generalized method of moments (GMM) estimators were used to test the conditional hypothesis that the impact of the Indian IFRS converged standards (Indian Accounting Standards [IndAS]) on information quality is affected by the firm’s corporate governance strength. Findings The estimates reveal that the positive effect of corporate governance scores on the value relevance of earnings reduces in the presence of IFRS, whereas the interaction of both the variables on book values remains insignificant. Secondly, the use of IndAS reduces discretionary accruals, but corporate governance does not have a significant moderating effect within the equation. Practical implications The results offer an interesting perspective into the debate on IFRS consequences and the role of internal institutional frameworks. It provides preliminary evidence suggesting that although corporate governance improves the value relevance of earnings, it may not be entirely effective in reducing the management of earnings. Originality/value To the best of the authors’ knowledge, it is the first study in India to provide empirical findings on the role played by corporate governance mechanisms in explaining the relationship between IFRS convergence and accounting information quality. The analysis accounts for modelling issues such as endogeneity and autocorrelation by using dynamic panel models and instrumental variables.

Uncertainty and the transmission of monetary policy via bank liquidity creation

PurposeThis paper investigates the moderating role of uncertainty in the impact of monetary policy on bank liquidity creation.Design/methodology/approachUtilizing data from Vietnam spanning 2007–2022, the paper measures uncertainty in the banking industry through the dispersion of shocks to crucial bank-level variables and considers both interest rate- and quantity-based tools of the monetary policy regime. The study regresses economic models using different econometric methods, including the generalized method of moments (GMM) estimator in the main section and the least squares dummy variable corrected (LSDVC) estimator for the robustness check.FindingsMonetary expansion enhances banks’ ability to create liquidity, affirming the existence of the bank liquidity creation channel. Further analyses suggest that monetary policy adjustments aimed at regulating bank liquidity creation may be less effective in the presence of higher uncertainty in the banking system. This observation holds for both interest rate- and quantitative-based monetary policy tools, emphasizing the functioning of the monetary policy transmission mechanism through bank liquidity creation and the mitigating effect of uncertainty.Originality/valueThis study contributes novel insights to the existing literature by presenting the first attempt to explore the dynamics of monetary policy transmission through the bank liquidity creation channel in the context of banking sector uncertainty. Moreover, our contribution extends to examining a multi-tool environment, incorporating both interest rate- and quantitative-based indicators.

Energy poverty and developments in finance, economic complexity and economic conditions

Purpose Energy poverty presents substantial challenges for both developed and developing nations, with the latter experiencing more pronounced adverse effects due to issues related to the provision and equitable access of energy resources. This study aims to provide a deep understanding of how financial development, economic complexity and government expenditures can impact energy poverty. Design/methodology/approach This research employs generalized method of moments (GMM) estimation on panel data to investigate the economic determinants of energy poverty in 31 developing countries from 2000 to 2020. For a comprehensive analysis, the proxies for energy poverty include access to electricity, access to clean fuels and energy consumption. Findings The findings suggest that while financial development cannot facilitate access to clean fuels in developing countries, it contributes to an increase in energy access and consumption. Another finding is that energy poverty can be alleviated by enhancing economic complexity since economic complexity can result in increased access to electricity and increased use of clean energy sources. Furthermore, the results underscore the pivotal role of government expenditures, surpassing the influence of financial development. In other words, government expenditures have the potential to significantly improve energy poverty across all three indices. Originality/value This is a pioneering research that seeks to examine some economic dynamics including, financial development and economic complexity on energy poverty and provide valuable guidance for policymakers aiming to promote sustainable energy development with respect to economic dynamics.

Regression to the mean for overdispersed count data

In repeated measurements, regression to the mean (RTM) is a tendency of subjects with observed extreme values to move closer to the mean when measured a second time. Not accounting for RTM could lead to incorrect decisions such as when observed natural variation is incorrectly attributed to the effect of a treatment/intervention. A strategy for addressing RTM is to decompose the total effect, the expected difference in paired random variables conditional on the first being in the tail of its distribution, into regression to the mean and unbiased treatment effects. The unbiased treatment effect can then be estimated by subtraction. Formulae are available in the literature to quantify RTM for Poisson distributed data which are constrained by mean–variance equivalence, although there are many real life examples of overdispersed count data that are not well approximated by the Poisson. The negative binomial can be considered an explicit overdispersed Poisson process where the Poisson intensity is chosen from a gamma distribution. In this study, the truncated bivariate negative binomial distribution is used to decompose the total effect formulae into RTM and treatment effects. Maximum likelihood estimators (MLE) and method of moments estimators are developed for the total, RTM, and treatment effects. A simulation study is carried out to investigate the properties of the estimators and compare them with those developed under the assumption of the Poisson process. Data on the incidence of dengue cases reported from 2007 to 2017 are used to estimate the total, RTM, and treatment effects.

How do ESG challenges affect default risk? An empirical analysis from the global banking sector perspective

Purpose A review of the literature provides a solid reason to believe that an increase in environmental, social and corporate governance (ESG) activities have a positive impact on banks’ default risk (DR). However, the increasing impact of climate risk on credit, operational and market risks, as well as the reduced availability of funding for banks that underperform in terms of ESG risk, is a concern. Therefore, the purpose of this study is to verify the relevance of the implementation of ESG policies to a bank’s DR, against the background of macroeconomic and bank-specific factors. Design/methodology/approach Using a data set of 303 commercial banks from 61 countries from 2012 to 2021 and a panel regression methodology, the empirical importance of ESG activities for bank DR is documented. The two-stage generalized method of moments estimator was used to test the research questions. Findings Comparing different factors, the results highlight the positive impact of ESG activities on the bank’s DR. However, this relationship varies according to the specific pillars of the bank’s sustainability policies and changes into negative ones. Originality/value This paper fits the domain of DR management research, investigating whether ESG performance affects bank DR while controlling macroeconomic and market drivers. Prior literature has shown evidence on the relationship between macro and market forces and a bank’s risk profile while a limited one on the non-market drivers. The main contribution is to consider ESG (in total and as separate pillars) as independent drivers of the bank risk profile.

Discovering the determinants of energy intensity of Indian manufacturing firms: a panel data approach

Our study pores on evaluating the impact of firm specific and macro level determinants of energy intensity of Indian firms belonging to manufacturing and power sector. We collect a panel dataset of 3316 firms for 10 years ranging from 2010 to 2020. We employ the advanced biased corrected method of moments estimator and the quantile regression estimator for panel data models for our empirical analysis. We find that poor labor efficiency is largely responsible for increasing energy intensity of the sample firms. Energy intensity can be optimized by investing in better plant and machinery. Moreover, machineries that require frequent repairs and maintenance need to be replaced with latest tools. While larger firms are found to be energy intensive, profitable firms are found to be in a better position to enhance their energy efficiency. Under macroeconomic scenario, GDP growth and trade openness lead to boosting up the energy consumption at the firm level whereas, the global energy prices act as a constraint and necessitate careful use of energy. Based on our findings we provide certain policy recommendations and suggestions in order to limit energy intensity and enhance energy efficiency of the Indian manufacturing firms.

Do firms’ performance act as a catalyst of innovation: empirical evidence from innovative Indian manufacturing firms

PurposeThis paper aims to explore whether firms’ performance determines innovation using a sample of Indian manufacturing firms. The impact of innovation on firms’ performance across specific countries has been discussed in the literature. However, the effect of firms’ performance on innovation output, especially for a developing country like India, remains an open question. Against this backdrop, this paper investigates whether firms’ performance determines innovation in Indian manufacturing firms.Design/methodology/approachThe authors use patent filing information to instrument innovation and total factor productivity to instrument firms’ performance. The patent data are collected from the Patent Search and Analysis Software database and firm-level data from the Centre for Monitoring Indian Economy’s Prowess database. The study uses a sample of 309 Indian manufacturing firms from 2005 to 2021. Given the count nature of the data set used in this study coupled with over-dispersion issues, the authors have used the negative binomial regression to estimate the empirical specification of the models. There could be a possible problem of endogeneity due to the contemporary nature of innovation and firms’ performance. Therefore, to address the possible issues of endogeneity in the model, the authors have used the Generalized Method of Moments (GMM) estimators for more robustness checks of the empirical results.FindingsThe empirical results exhibit a positive and significant impact of firms’ performance on the innovation output, validating that firms’ performance determines innovation in Indian manufacturing firms. The posterior estimation results using GMM estimation also corroborate that firms’ productivity is a determining factor for the innovation output of Indian manufacturing firms. Furthermore, empirical results exhibit that the ex ante innovativeness of the firms substantially affects the current innovation. This validates that the firms’ prior experience, learning by doing and past innovative efforts are more likely to precipitate more innovation in the current period.Originality/valueThis paper’s main contribution is empirically estimating whether firms’ performance determines innovation, which is hardly discussed in the existing innovation literature, specifically using Indian manufacturing industries. Further, it adds to the existing literature in two other prominent ways. First, this paper investigates whether firms require ex ante expertise to innovate or if a firm starting from scratch can innovate significantly without any hindrances. Second, it enriches the literature by instrumenting innovation in output terms with the patent application against input measures of innovation, such as research and development expenditures, acquisition of machinery and equipment, while discussing the relationship between firms’ performance and innovation, specifically in the context of a developing economy like India.

Modeling Determinants of Profitability in Ethiopia Manufacturing Companies: A Dynamic Panel Model Approach

Background: Profitability is the primary measure of the overall success of company. The analysis of profitability ratios is important for the shareholders, creditors, prospective investors, manufacturers and government alike. Objective: The objective of this study was fitted a dynamic panel regression model that efficiently fit the data and further to identify the determinants contributing significantly to profitability in Ethiopia. Methods: This study was conducted on secondary data of 32 sample manufacturing companies collected from the audited financial statements of large tax payers’ office and national bank of Ethiopia. The study was covered a period of seven years from 2011 to 2017. The panel unit root test of Levin-Lin-Chu tests was made for each variable and applied first difference transformation for the variables that had unit root. A dynamic panel regression model was utilized for data handling technique using generalized method of moments (GMM) estimation. Results: We compared the results when one unit increase in lagged profitability, managerial efficiency, capital intensity, GDP, exchange rate and one ratio decrease in leverage, ceteris paribus, turn out were found to increase the profitability of manufacturing companies by around 0.69, 0.179, 4.52E-06, 3.844, 0.04 and 0.393 ratio, respectively. The model reveled that previous profitability, leverage, capital intensity, managerial efficiency, GDP and exchange rate had a statistically significant (P<0.05) effect on companies’ profitability in Ethiopia. Conclusion: As per our findings, the manufacturing companies should minimize leverage financing from its capitals and should emphasize the management of appropriate financing to increase profitability. Finally, we recommended that policy makers should coming up with better policies on improvement of profitability.

THE ROLE OF BANKING SYSTEM IN PROVINCIAL ECONOMIC DEVELOPMENT: A STUDY OF TURKIYE, FROM THE 70S TO THE 2000S

This research examines the relationship between banking activities and provincial economic development. In particular, the study offers insight on the nature of the regional economic development discrepancies in Turkiye. The study finds that, despite the trend towards decentralisation that takes place in regional economic policies, the banking system adopts centralisation policies. Using dynamic generalised method of moment (GMM) estimates, we evaluated a unique data set including 39 years of provincial demographic, socioeconomic, and financial factors in Turkey. The study demonstrates that the banking intermediation is detrimental to provincial development. The Turkish banking system’s hierarchical structure prevents financial intermediaries from fulfilling their role in fostering development. Consolidation and concentration strategies must be reassessed, since they tend to favour centralisation, which has been shown to be inefficient for regional convergence. The results also suggest that branch managers should be granted greater decision-making authority to make better use of locally produced information when approving or rejecting projects, which would eventually lead to a reduction in provincial disparities.

Dynamic panel data analysis of the impact of governance on bank capital structure in Indonesia

The banking industry plays a crucial role in driving the Indonesian economy. Therefore, any financial upheaval within this sector would have a significant influence on the overall economy. Hence, this study examines the capital composition of banking institutions in Indonesia to assess the financial soundness of the banks. A bank’s susceptibility to default will adversely affect client confidence in the bank. This study investigates the influence of governance attributes, such as board size, board meeting frequency, risk committee presence, institutional ownership, and independent committee existence, on the capital structure of Indonesian banks. 31 samples were intentionally chosen using purposeful sampling. Data estimation was performed using a two-step Arellano-Bond Generalized Method of Moments (GMM) estimator. The findings suggest that the bank risk committee, institutional ownership, and independent committee exert a notable and favorable influence on the capital structure of banks in Indonesia. Nevertheless, the size of the board and the frequency of board meetings do not exert a substantial impact. The size of the board and the use of leverage have no substantial impact. Developing efficient corporate governance procedures is essential for ensuring the bank’s financial stability. This involves maximizing the effectiveness of the risk committee, institutional ownership, and independent committee. AcknowledgmentThis paper is funded by PPM-PTM Grants of the Ministry of Education, Culture, Research and Technology of 2023 (03/SP2H/RT-MONO/LL4/2023).

Interlinkages between bilateral investment treaties and FDI flows to emerging economies: evidence from BRICS

PurposeThis study aims to examine the role of Bilateral Investment Treaties (BITs) in attracting higher foreign direct investment (FDI) inflows into the major emerging economies namely Brazil, Russia, India, China and South Africa (BRICS) from the source developed, developing and other emerging economies over a period of 18 years from 2001 to 2018.Design/methodology/approachTo estimate the results, panel data regression on a gravity-knowledge capital model has been used. To account for the problem of endogeneity we have used the two-step difference Generalised Method of Moments estimator proposed by Arellano and Bond (1991).FindingsWe find that contradictory to theory and expectations, BITs result in a fall in FDI inflows in BRICS economies. BITs ratified by BRICS economies are not able to provide a sound and secure investment environment to foreign investors, thereby discouraging FDI in these economies.Originality/valueTo the best of the authors’ knowledge, this study is the first to examine the impact of BITs on FDI inflows into the emerging BRICS economies. Further, the impact of BITs on FDI flows among developed nations, i.e. north-north FDI and from developed to developing countries, i.e. north-south FDI has already been studied by many researchers. But so far, no study has examined this impact on FDI among developing and emerging economies (south-south FDI), despite an increase in FDI flows among these economies. Therefore, this study seeks to overcome the limitations of previous studies and tries to find out the impact of BITs on FDI inflows in BRICS economies not only from source developed but also from source developing and other emerging economies.

Board gender diversity and cyber security disclosure in the Indonesian banking industry: a two-tier governance context

PurposeThis study aims to determine the effect of board gender diversity on cyber security disclosure (CSD) in the banking sector of Indonesia as a developing country that adheres to a two-tier system.Design/methodology/approachThis study uses a panel data of 47 banks listed on the Indonesia Stock Exchange from 2014 to 2021. The board gender diversity is measured by three proxies, the proportion of women on the board, BLAU Index value and the critical mass of women. The authors used generalized method of moments estimation to eliminate the simultaneous equation bias.FindingsThe results show that the women board of commissioners increases CSD, and the women of board of directors/top management team were significantly negative for CSD.Research limitations/implicationsFirst, this research was only conducted in the banking sector. The results cannot be generalized to non-financial companies. Second, there is no measurement of the quality of the board from the level of education, experience, expertise and other characteristics of diversity such as age, nationality and religion.Practical implicationsThe study has revealed the need for the government’s role in providing oversight of the presence of women on the board so that banks fully comply with Indonesia Financial Services Authority regulations. Banks should also actively launch policies regarding the presence of women on the board to give a positive effect to stakeholders that women play an important role in decision making. Banks must also adjust the composition of female commissioners with a threshold of two people to maximize their function as supervisors.Originality/valueThis is the first research conducted on the banking sector in Indonesia as a developing country that adheres to a two-tier system. The results of this study provide evidence that patriarchal culture is still dominant in Indonesia.

Corporate social responsibility and firm value: exploring the moderating effects of information technology-enabled knowledge capabilities

PurposeA substantial amount of research has examined the firm value impact of corporate social responsibility (CSR). Nevertheless, the findings have been inconsistent, prompting researchers to identify contingencies under which the impact varies. This study examines how information technology (IT)-enabled knowledge capabilities moderate the relationship between CSR and firm value.Design/methodology/approachWe conducted the ordinary least squares (OLS) regression analysis on a sample of S&P 500 companies spanning from 2010 to 2017. We employed additional methods to test the robustness of the results, including the generalized method of moments (GMM) estimator and the two-stage least squares (2SLS) method.FindingsThe results show that IT-enabled absorptive capability (IT-AC) and IT-enabled social integration capability (IT-SIC) positively moderate the CSR–value relationship. Further, their moderating effects vary in distinct ways when environmental dynamism changes, hinting at the distinct underlying rationales behind the moderating roles of IT-AC and IT-SIC.Research limitations/implicationsThis study improves the understanding of the business value of CSR and IT. It has limitations in generalizability due to the use of secondary data.Practical implicationsThis study provides practical guidelines to managers about how to strategically leverage IT resources for the creation of CSR value.Social implicationsEncouraging businesses to enhance their CSR efforts and uphold sustainability extends beyond our immediate benefit and impacts future generations as well. However, due to an imbalance between costs and returns, companies often refrain from being wholeheartedly devoted to CSR. Our insights on guiding companies to derive more value from CSR can inspire their greater investment in CSR. Meanwhile, companies can obtain additional returns from deployed IT.Originality/valueThis study extends the IT business value literature by revealing how IT generates firm value in the context of CSR. It also adds critical insights into the mixed findings in previous research regarding the CSR–firm value link. The study’s findings offer useful guidance on the strategic deployment and utilization of IT resources to facilitate the creation of CSR value.

EPU and SMEs' financial performance: Industry vs. service sector

The objective of this paper is to analyze the Economic Policy Uncertainty impact on Small and Medium Enterprises’ financial performance, considering the role that sector plays and firm characteristics. Thus, a data sample of 80,620 Spanish SMEs was selected for 2012–2020. Using system Generalized Method of Moments estimators, the results show a negative impact, especially in the service sector. Industrial Spanish SMEs that are larger, younger, more indebted, with more growth opportunities and with higher asset turnover are the most resilient to EPU. The findings can help SMEs design better management strategies to deal with this uncertainty.

Manifestations of loan growth – profitability and non-performing loans – a study of the Indian banking sector

PurposeAfter half a decade of balance sheet clean-up prompted by the Reserve Bank of India’s (RBI) asset quality review (AQR), Indian banks are back on track for increased loan growth. Being a financial vehicle for the economy, loan growth cannot be put on hold for a long period of time. But it is also important to understand that loan growth carries an inherent risk of default. A trade-off exists between loan growth, non-performing loans (NPLs) and bank profitability. Our study highlights the importance of understanding this relationship.Design/methodology/approachFor our study, we have taken a sample of India’s private and public sector banks. The dataset consists of the financials of our sample for the period 2006–2021. Two-step differenced generalized method of moments (SYS-GMM) estimation has been used to establish the relationship. The mediating role of NPLs in the relationship between loan growth and profitability is examined by the mediation analysis using structural equation modeling (SEM) and the Sobel test. We have used Stata 16.1 for the analysis of our dataset.FindingsThe findings of our study suggest that bank lending is a major contributor to the bank’s earnings. Loan growth after a certain point has a negative impact on profitability, and it also adds to the NPLs of the bank. The study result indicates that moderate loan growth is key to steady and stable growth in the Indian banking industry.Practical implicationsOur study is directed toward understanding the positive and negative manifestations of loan growth. We develop a framework to understand this relationship and then empirically prove it. The study is beneficial for employees and policymakers alike to minimize the negative impact of loan growth.Originality/valueThe issue of the simultaneous impact of loan growth on NPLs and profitability has not been studied in the Indian banking sector. Also, this study adds to the present literature by studying the mediation effect of the NPLs on the loan growth and profitability relationship.

Does crude oil price volatility affect risk-taking capability in business group firms: evidence from India?

PurposeThe study tests risk-taking and risk-aversion capabilities while distinguishing between business group firms and stand-alone firms and considering oil price volatility. Second, this attempt to study the linkage between risk-taking during market down movements and when the firms have established themselves as product market leaders. Third, this study analyses the “sentiment” state, where it explores the reaction of corporations when the market is in the negative direction, and lastly, it explores the linkage between product market competition and risk-aversion.Design/methodology/approachThis study uses financial information for 1,273 non-financial companies and other required data from various sources. The study employs panel data and utilizes different empirical methodologies, including the generalized method of moments (GMM) estimator, to test the stated hypotheses.FindingsWe find that the business group firms have more risk-taking proficiencies compared with the stand-alone firms. Moreover, this study discovers that the corporates avoid taking risks when the market is not performing well. Also, when the market is down and crude prices are high, the management expects high earnings in the future, willingly takes risks and shows that product market leaders do not follow the risk-aversion strategy.Practical implicationsThe empirical results indicate that oil price movement can restrict management’s behaviour when choosing a risky investment project. Management should develop a robust policy that follows the group of firms. In the policy, the management should describe the level of risk that may be taken by the firm and implement it when required.Originality/valueSince we do not find any studies in this context, then there is a major and essential gap in the literature that this study should fill.

Do institutional environment and corporate governance structures determine Islamic Banks’ sustainability performance? Evidence across key jurisdictions in Islamic finance industry

This study examines the impact of the institutional environment and corporate governance structures on Islamic banks' sustainability performance (SP). It applies a two-step System Generalized Method of Moments (GMM) estimator to analyze data gathered on a panel of 32 Islamic banks drawn from nine key Islamic finance jurisdictions from 2016 to 2021. To consistently code and quantify the Islamic banks' SP, we use the Specific Standard Disclosures for the Financial Services Sector introduced by the GRI as a framework of reference. Then, we employ the weighted content analysis method on the sustainability and annual reports of the subjected sample. Our findings indicate that the institutional factors specifically, regulatory guidelines (regulatory isomorphism) and the adherence of Islamic banks to the sustainable finance networks' specifications (normative isomorphism) are not currently determinants of their SP. Contrarily, we observe that the establishment of a sustainability committee and a better experience of sustainability disclosure improve Islamic banks' SP. In contrast to agency theory, board activity is identified to have a significantly negative relationship with SP. An important policy implication of our results is that policymakers should closely monitor Islamic banks' regulatory dependency and enhance their SF ecosystem to positively influence their SP. Finally, future research may leverage on more conducive regulatory frameworks to sustainability transition in these key jurisdictions, more effective normative structures, further disclosure of sustainability committee characteristics, the development of appropriate measures of Islamic banks' digitalization levels, and the availability of more material sustainability data to provide further insights and better understand the determinants of Islamic banks’ SP.

A comparative study on ensemble soft-computing methods for geothermal power production potential forecasting

Many developed countries are increasingly interested in renewable energy sources (RESs) as a result of environmental changes and the depletion of fossil fuels in recent years. Since geothermal energy can be used as both a source of electricity and heat, it occupies an important spot among renewable energy sources. In this study, soft-computing ensemble models (SCEMs) based on supervised deep neural network (SDNN) models supported by the forward stepwise regression (FSR) method are used in estimating the power generation from geothermal resources. Outputs of the FSR process led SDNN phase. Adaptive Moment Estimation (ADAM) and Nesterov-accelerated Adaptive Moment Estimation (NADAM) methods were used to optimize SDNN models. For the daily power generation, the best performance has been shown by the model of SDNN optimized using ADAM optimizer with a coefficient of determination (R2) of 0.9807 and root mean square error (RMSE) of 0.0466, respectively.