Economic policy uncertainty, Covid-19 and corporate investment: Evidence from the gold mining industry

Mining is a capital-intensive sector that requires substantial upfront investments and continuous capital expenditure to sustain and improve production. This study investigates the impact of Economic Policy Uncertainty (EPU) on the investment decisions of the top 5 gold mining countries, namely Australia, China, Russia, the USA, and Canada, with a focus on the COVID-19 Pandemic. Using a two-step generalized method of moments, we analyze data from 333 gold mining companies from 2006 to 2021. Our results demonstrate that the EPU index has a negative effect on the investment decisions of gold mining companies during the COVID-19 Pandemic. We also utilize quantile regression analysis, which shows that the estimated coefficients for the low and high quantiles are significant. Our study reveals that during periods of uncertainty, gold mining companies tend to be risk-averse, which subsequently dampens investment projects. Furthermore, the capital-intensive nature of the gold mining sector renders companies to be more vulnerable to economic conditions. These findings have significant policy implications for investors, portfolio managers, and policymakers, which will be discussed in the conclusion section.

Economic policy uncertainty, governance institutions and economic performance in Africa: are there regional differences?

In recent years, the global economy has witnessed several uncertainty-inducing events. However, empirical evidence in Africa on the effects of economic policy uncertainty (EPU) on economic activities remains scanty. Besides, the moderating effect of governance institutions on the uncertainty-economic performance relationship in Africa and the likelihood of regional differences in the response of economic activities to EPU on the continent are yet to be investigated. To address these gaps, we applied system GMM and quantile regressions on a panel of forty-seven African countries from 2010 to 2019. We find that while global EPU and EPUs from China, USA and Canada exert considerable influence on economic performance in Africa, the effects of domestic EPU and EPUs from Europe, UK, Japan, and Russia were negligible, suggesting that African economies are resilient to these sources of uncertainty shocks. We also find that governance institutions in Africa are not significantly moderating the uncertainty-economic performance relationship. However, our results highlighted regional differences in the response of economic activities to uncertainty, such that when compared to East and West Africa, economic performance in Central, North and Southern Africa is generally more resilient to global EPU and EPUs from China, USA, Europe and UK. We highlighted the policy implications of these findings.

Has Digitalisation Mitigated the Impact of Covid-19 on the Manufacturing Sector's Performance?

The Covid-19 pandemic brought many businesses to a standstill as international travel restriction was imposed across countries in addition to a national lockdown. Firm performances were depressed due to reduced order and output. This study examines whether digitalization has mitigated the negative impact of the Covid-19 pandemic on Malaysia's manufacturing sector. Using sales as the performance yardstick of 24 industrial sectors from January to December 2020, our result shows that manufacturing sales performance was negatively related to the Covid-19 pandemic. However, the adverse impact of Covid-19 was mitigated with a higher level of digitalization. The mitigating role of digitalization remains robust in further analysis. This study has managed to quantify the mitigating effect of Covid-19 on manufacturing sectors. As a policy implication, the government should expedite the introduction of the 5G network, promote digital adoption across all sectors to ensure business continuity and provide an effective response mechanism in any pandemic or crisis.

UNEMPLOYMENT BEHAVIOUR IN THE COVID-19 PANDEMIC: EVIDENCE FROM DEVELOPING COUNTRIES

This paper explores the impacts of the COVID-19 pandemic, corruption and other determinants on unemployment in developing countries using panel dataset for 89 developing countries from January to December 2020. The proposed unemployment model is estimated utilising a newly formulated conceptual framework to examine whether COVID-19 pandemic, corruption, and human capital, play a moderating role on unemployment determination in our selected developing countries. The model is estimated using the dynamic panel system generalised method of moments (GMM) estimator. Apart from output, inflation and human capital, our results show that the COVID-19 pandemic and corruption are major variables in explaining the unemployment rate for our sampled countries. Furthermore, and more notably, we find evidence that the COVID-19 pandemic and corruption appear to significantly restrain and alter the role of outputs and human capital in impacting unemployment. Therefore, the detrimental effects of the COVID-19 pandemic and corruption on the economies and labour markets of countries examined should not be under-estimated. Additionally, findings show that, while policy initiatives to combat the COVID-19 pandemic are critical, strengthening anti-corruption regulations would further improve the efficiency of any attempt to reduce unemployment rates associated with the COVID-19 period. © 2023, Universiti Malaysia Sarawak. All rights reserved.

Do the macro and global economic factors drive the nonperforming loans in GCC economies?

PurposeThe current study aims to investigate the determinants of nonperforming loans (NPLs) in the GCC economies during the period spanning 2000 to 2018. It also examines whether the worldwide financial crisis of 2007–2008, which brought the issue of non–performing loans to the greater attention of academics and policymakers, had a substantial impact on NPLs in this region.Design/methodology/approachThe sample consists of 53 conventional banks from GCC countries, and the basic data for the study is obtained from various sources such as Bankscope, IMF World Economic Outlook, World Bank and Chicago Board of Options Exchange Market Volatility Index. The estimations were done by dynamic panel data regression modeling using system generalized methods of moments.FindingsThe findings reveal that both, the non-oil real GDP growth rate and inflation have favorable effects on NPLs. On the other hand, domestic credit to the private sector and the volatility index have an adverse effect on NPLs. Furthermore, the period-wise analysis shows that the relevance and significance of the determinants of NPLs vary between the precrisis and postcrisis periods. It is also reflected through the intercept dummy, which is found to be significant, indicating that the financial crisis, as a global economic factor, had a significant impact on NPLs. A number of robustness tests are applied, which indicate that the results are mostly robust and consistent in terms of the significance of the explanatory variables and the direction of their relationship with the dependent variable.Practical implicationsPolicymakers and bank authorities must strive to maintain a healthy economy and implement macroprudential policies to improve the financial stability of banks and reduce credit risk.Originality/valueTo the best of the authors' knowledge, this is likely the first study that empirically investigates the influence of the financial crisis on NPLs in the context of GCC economies. In addition, the research spans 19 years to produce more conclusive results.

Do women on boards enhance firm performance? Evidence from top Indian companies

This paper examines whether gender diversity (GD) on corporate boards influences financial performance (FP) of Indian firms using System Generalized Methods of Moments (GMM) methods by considering panel data of 364 firms during 2017 to 2021, comprising of 1820 firm-year observations. The study reveals that the mere presence of a woman director (WD) on boards makes no difference in financial performance. Presence of WDs as a significant portion of the boards and their active roles in the functioning and governance of companies positively contribute to firms' financial performances and economic value creation. Regarding other governance parameters, the study shows that larger boards do not necessarily improve firm performance. Also, independent directors do not necessarily add value to corporate performance and value creation. While a higher promoter's stake is an important factor for Indian companies to drive corporate performance, firms with separate CEO and chairperson outperform firms with CEO duality. The study also reveals that the covid 19 pandemic has negatively influenced the financial performance and economic profit generation of the Indian firms. This study is important for several reasons. First, this study considers the period (2017–2021) when Indian companies adopted new financial reporting practices (IND-AS) in line with International Financial Reporting System (IFRS), the mandatory quota system of women directors' appointment is implemented and new corporate governance norms are implemented. Hence, our study contributes to the literature by proving meaningful insights on the role of gender diversity and other corporate governance parameters on financial performance of Indian firms in the light of newly adopted accounting and financial reporting practices. Second, few previous India based studies have mostly used pooled OLS or fixed effect models, and did not address the endogeneity problem in different forms like Dynamic Endogeneity, Simultaneity, and Unobserved Heterogeneity. This paper addresses the endogeneity problem appropriately by using the system generalized method of moments (GMM) while modelling the relation between WDs and firms' FP. Therefore, the findings of this study are more reliable and unbiased and can be useful for effective policy making on gender diversity and corporate governance issues. Third, few prior studies which have looked into the role of WDs on FP of Indian firms, have mostly used return on assets (ROA), return on equity (ROE) and Tobin's Q as performance parameters. Here, in addition to ROA, ROE and Tobin's Q, we also use economic value added (EVA) as indicators of corporate performance to understand the role of WDs on economic value creation for companies. The EVA is considered as modern technique to measure the economic profit earned by a firm, and it has gained huge popularity among companies as an improved technique for measuring financial performance for companies. To the best of our knowledge, the role of WDs on economic value creation by firms has not been investigated before particularly in the Indian context. This is another unique contribution of this study. Fourth, the Covid 19 pandemic had impacted global economy severely and India was no exception. Financial performances of most Indian firms were negatively impacted due to the nationwide lockdown and uncertainties about production, revenue and earnings. This study considers both the pre and post Covid 19 pandemic period in examining our central research question using a year dummy. Therefore, our study also captures whether the covid 19 pandemic has actually impacted the financial performance of Indian firms, while modelling this relation. This is another valuable and unique contribution of this study to the literature. The findings of this study provide an understanding of how board gender diversity and other governance parameters influence financial performance of Indian firms in an emerging market context. The outcomes are also explained and aligned with the relevant policy implications in th light of recent Indian corporate governance norms and policies. These findings are useful to the companies and policymakers, as they can use these findings while designing effective boards, which can be useful in improving firm performance. Board of directors, investors, regulators, and policymakers can effectively use these findings to understand how gender diverse boards and other corporate governance parameters influence firms' financial performance under the concentrated ownership pattern.

COVID-19 and culture

The USA has been particularly hard hit by the COVID-19 pandemic and a wide spatial variation can be seen in its spread and mortality. This raises the question of why some regions are more resilient to the pandemic than others? We hypothesize that the individualism-collectivism cleavage explains the disparity in COVID-19 cases observed across sub-national units in the USA. Cultural disparity among different groups of people leads to differences in how they perceive health crises and thereby shapes the way they respond to pandemics. A heightened sense of obligation and responsibility increases in-group sociability and interdependence and raises the perceived vulnerability towards disease transmission among collectivistic individuals, and this leads to greater adherence to containment measures and social distancing rules. Our results provide evidence that more individualistic states tend to have more COVID-19 cases across the USA.

COVID-19 Dataset Clustering based on K-Means and EM Algorithms

In this paper, a COVID-19 dataset is analyzed using a combination of K-Means and Expectation-Maximization (EM) algorithms to cluster the data. The purpose of this method is to gain insight into and interpret the various components of the data. The study focuses on tracking the evolution of confirmed, death, and recovered cases from March to October 2020, using a two-dimensional dataset approach. K-Means is used to group the data into three categories: "Confirmed-Recovered”, "Confirmed-Death”, and "Recovered-Death”, and each category is modeled using a bivariate Gaussian density. The optimal value for k, which represents the number of groups, is determined using the Elbow method. The results indicate that the clusters generated by K-Means provide limited information, whereas the EM algorithm reveals the correlation between "Confirmed-Recovered”, "Confirmed-Death”, and "Recovered-Death”. The advantages of using the EM algorithm include stability in computation and improved clustering through the Gaussian Mixture Model (GMM). © 2023,International Journal of Advanced Computer Science and Applications. All Rights Reserved.

The Effect of Economic Policy Uncertainty on Foreign Direct Investment in the Era of Global Value Chain: Evidence from the Asian Countries

The global value chain has promoted foreign direct investments in emerging markets. Not only resources but also public policies can affect the inflows or outflows of foreign direct investments (FDI). This study investigates the effect of economic policy uncertainty on net foreign direct investment inflows in 48 Asian countries. We use the panel dataset from different sources from 1995 to 2020. Our core dependent variable is net foreign direct investment inflows, and the explanatory variable is economic policy uncertainty. The study's control variables include trade, GDP per capita, GDP growth, population, financial development, inflation, and employment. We use the generalized system method of moment (SYS_GMM). Furthermore, the robustness of our empirical results is checked by using the different proxy variables of policy uncertainty. Our results confirm the negative effect of policy uncertainty on foreign direct investment inflows in 48 Asian countries. Our results show that foreign investment inflows are more sensitive than domestic investment. The influence of domestic and global uncertainty on inward FDI is greater than domestic investment. Furthermore, the interaction effect of financial development (FD) shows that FD does not affect mitigation of the negative impact of global economic policy uncertainty on foreign investment inflow. In contrast, FD mitigates the adverse effects of domestic policy uncertainty on foreign and domestic investment. The findings imply that policies need to be attractive, effective, and transparent to woo FDI to the emerging markets.

THE INFLUENCE OF BASEL III ON ISLAMIC BANK RISK

This paper investigates the impact of bank regulatory capital on Islamic bank risk using bank-level data from 29 countries covering the period from 2004 to 2020. Applying the generalized method of moments technique on dynamic panels, we discover that on average Islamic bank regulatory capital ratios exceed the level required by Basel III. The findings provide evidence in support of the moral hazard hypothesis;that is, there is a negative relationship between capital and risk. They indicate that Islamic banks are better protected against risk when they fulfill Basel III and IFSB regulatory capital requirements. According to our findings, authorities that aim to improve the financial stability of the banking industry should reinforce their policies and oblige banks to adhere to regulatory capital requirements during crises such as Covid-19. Finally, we observe that different risk indicators have diverse correlations with regulatory capital, and that the findings are robust across a variety of estimation methodologies. © 2023 University of Ljubljana - Veterinary Faculty. All rights reserved.

Analysis Pre and Post COVID-19 Pandemic Rorschach Test Data of Using EM Algorithms and GMM Models

The global spread of the COVID-19 virus has become one of the greatest challenges that humanity has faced in recent years. The unprecedented circumstances of forced isolation and uncertainty that it has imposed on us continue to impact our mental well-being, whether or not we have been directly affected by the virus. Over a period of nearly three years (2017-2020), data was collected from multiple administrations of the Rorschach test, one of the most renowned and extensively studied psychological tests. This study involved the clustering of data, collected through the RAP3 software, to analyze the distinctive trends in data recorded before and after the pandemic. This was achieved through the implementation of the well-established machine learning algorithm, Expectation-Maximization. The proposed solution effectively identifies the key variables that significantly influence the subject's score and provides a reliable solution. Additionally, the solution offers an intuitive visualization that can assist psychologists in accurately interpreting shifts in trends and response distributions within a large amount of data in the two periods. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

The social role of supply chain firms during the pandemic period

Purpose: Social risk management is vital for growth and business continuity. This study investigates the social risk shift in supply chain management during the Coronavirus Disease 2019 (COVID-19) pandemic. Design/methodology/approach: Data were retrieved from Bloomberg between 2010 and 2021 regarding all supply chain enterprises from nine countries. The authors undertake a confirmatory examination of formulated hypotheses. Social supply chain risk (SSCR) refers to "firms that took the necessary steps to decrease social risks in their supply chain. Social risks involve the child or forced labor, poor working conditions, lack of a living and fair or minimum wage”. The authors complement the analysis and address the endogeneity issue using the dynamic generalized moments method (GMM). Findings: A significant positive relationship between COVID-19 and SSCR was discovered in this study. Due to the COVID-19 pandemic, supply chain firms faced supply chain social risk. Notably, SSCR policies differ from one country to another during this period. Research limitations/implications: The research has some limitations. The sample data are limited to 9 countries. Furthermore, it was somewhat difficult to determine the country-wise difference using COVID-19 as a dummy variable. Future research may adopt qualitative approaches, such as structural or semi-structural interviews. Practical implications: The results have important implications for supply chain practitioners to consider the critical role of social risk in their operations. COVID-19 has exposed the new political economy and re-centered governments as the key actors in tackling grand challenges to safeguard workers, produce socially useful products and protect their stakeholders. Also, the study highlights the importance of governments and policymakers having a well-structured regulatory framework and environment for firms to comply with the social norms in their supply chain management. Finally, the study's findings should encourage supply chain managers to adopt a proactive mechanism that reduces the social risk impacts of pandemics. Originality/value: Considering the historical backdrop of the COVID-19 pandemic, this study is unique in measuring the SSCR of enterprises from a worldwide viewpoint. © 2023, Emerald Publishing Limited.

Does political risk matter for infrastructure investments? Empirical evidence

Infrastructure assets are vital for economic development and integration, but they also encompass political risks. In Africa, infrastructure assets have remained a paradox where there is great potential for opportunities but very few projects get to the final phases. Adequate infrastructure can propagate the attainment of the Sustainable Development Goals whilst supporting recovery from the Covid-19 pandemic. Drawing from a longitudinal data set from 2000 to 2021 for 35 African countries, the paper empirically examined the nexus between infrastructure and political risk. Several techniques were employed to determine the dynamic effect, cointegration and causality between infrastructure and political risk. Controlling for the potential endogeneity in infrastructure the system Generalized Method of Moments, the relationship between political risk and infrastructure was ascertained. Furthermore, the ARDL-PMG was employed to determine the cointegration and causal relationship between infrastructure and political risk. The results suggest a cointegration between infrastructure assets and political risk. Infrastructure adjusts to changes in political risk to its long-run equilibrium at a speed of adjustment of 16.9 per cent. Bridging infrastructure gaps in Africa requires an extensive set of actions. Thus, the policy derivatives of our findings, suggest controlling the proliferation of political risk to support infrastructure investment. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Impact of Anti-Pandemic Policy Stringency on Firms' Profitability during COVID-19

The coronavirus (COVID-19) pandemic devastated all economies across the world and triggered a deterioration in firms' financial performance. However, some sectors turned out to be more vulnerable while others continued to perform well during the crisis period. Given this fact, we conducted a comprehensive study to estimate the impact of the COVID-19 pandemic on firms' profitability in Europe. We used a dynamic panel data approach and a system generalized method of moment (System-GMM) model to investigate (i) which sectors were affected and what was the magnitude of the impact on firms' profitability, and (ii) whether the stringency of anti-pandemic policies such as workplace closures and travel bans impacted firms unevenly. We find that COVID-19 caused about a 25% decline in the profitability of firms. The most impacted sectors were Consumer Discretionary, Consumer Staples, and Industrials, where profitability declined from 20 to 48%. We also find that firms in countries with high anti-pandemic policy stringency lost about 19% more in profitability than in the rest of the countries in Europe during 2020. © 2023 by the authors.

The impacts of financial and macroeconomic factors on financial stability in emerging countries: evidence from Turkey's nonperforming loans

This study examines the impacts of financial and macroeconomic factors on financial stability in emerging countries by focusing on Turkey's banking sector. In this con-text, financial stability is represented by nonperforming loans (NPLs). Four financial and three macroeconomic indicators as well as the Covid-19 pandemic are included as explanatory variables. Quarterly data from 2005 Q1 to 2020 Q3 are analyzed by using the residual augmented least squares unit root test and generalized method-of-moments. The empirical results show the following: credit volume, which is a financial indicator, has the greatest effect on NPLs;risk-weighted assets, unemployment rate, foreign exchange rate and economic growth all have a statistically significant impact on NPLs;the Covid-19 pandemic has had an increasing impact on NPLs;inflation and interest rates have a positive coefficient, as expected, although they are not statistically significant. These results highlight the importance of financial factors (ie, credit volume and risk-weighted assets) over macroeconomic factors in terms of NPLs. Based on the empirical results of the study, we suggest Turkish policy makers focus primarily on financial variables (ie, credit growth and risk-weighted assets) as well as considering the effects of other factors. © Infopro Digital Limited 2023.

Application of Artificial Intelligence on Post Pandemic Situation and Lesson Learn for Future Prospects

Coronavirus disease (COVID-19) pandemic has intensively damaged human socio-economic lives and the growth of countries around the world. Many efforts have been made in the direction of artificial intelligence (AI) techniques to detect the corona at an early stage and take necessary precautions to stop it from spreading or recovery from the infection. However, the situation and solutions are still challenging. In this paper, we proposed various technological aspects, solutions using a supervised/unsupervised manner and continuous health monitoring with physiological parameters. Finally, the performance of COVID-19 detection with Gaussian mixture model-universal background model (GMM-UBM) technique using the voice signal has been demonstrated. The developed system achieves the COVID-19 detection performance in terms of areas under receiver operating characteristic (ROC) curves in the range 60–67%. Moreover, the various lessons learned from the current COVID-19 crisis are presented for future directions.

What Will Be the Impact of the COVID-19 Pandemic on the Human Capital and Economic Growth? Evidence from Eurozone

This study provides new empirical evidence concerning the relationship between human capital and economic growth for 17 European countries over the periods 2015–2019 and 2019–2022. The results show that both education and health have a positive and significant impact on economic growth, and thus support higher growth. Also, our empirical results before COVID-19 show that there is bidirectional causality between economic growth and health, as well as education and economic growth, and there is unidirectional causal relationship running from education to health. After COVID-19, there is no significant causality between economic growth education and health. The results of this study may be of great importance for policy and decision makers in developing policies to foster human capital for European countries. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Automatic illness prediction system through speech.

Due to the COVID-19 epidemic and the curfew caused by it, many people have sought to find an ADPS on the internet in the last few years. This hints to a new age of medical treatment, all the more so if the number of internet users continues to expand. As a result, automatic illness prediction online applications have attracted the interest of a large number of researchers worldwide. This work aims to develop and implement an automated illness prediction system based on speech. The system will be designed to forecast the sort of ailment a patient is suffering from based on his voice, but this was not feasible during the trial, therefore the diseases were divided into three categories (painful, light pain and psychological pain), and then the diagnose process were implemented accordingly. The medical dataset named "speech, transcription, and intent" served as the baseline for this study. The smoothness, MFCC, and SCV properties were used in this work, which demonstrated their high representation to human being medical situations. The noise reduction forward-backward filter was used to eliminate noise from wave files captured online in order to account for the high level of noise seen in the deployed dataset. For this study, a hybrid feature selection method was created and built that combined the output of a genetic algorithm (GA) with the inputs of a NN algorithm. Classification was performed using SVM, neural network, and GMM. The greatest results obtained were 94.55% illness classification accuracy in terms of SVM. The results showed that diagnosing illness through speech is a difficult process, especially when diagnosing each type of illness separately, but when grouping the different illness types into groups, depending on the amount of pain and the psychological situation of the patient, the results were much higher.

Colonial legacies on employment: comparisons between some former Anglophone and French colonies

Purpose: In this paper, the author assesses if the effect of structural policies, macroeconomic indicators and demographic factors on employment elasticities over the period 2000–2017 can distinguish the former French colonies from the Anglophone ones. Design/methodology/approach: Using a panel of 44 countries taken from Africa and Middle East Area, elasticities are estimated in the first stage by rolling regression. Then, both static and dynamic panel models are investigated. Findings: Results suggest big difference between the former French colonies and Anglophone ones. For the French colonies, product and labor market flexibility are found to have significant and positive impact on elasticities, while for Anglophone ones, only foreign direct investment and government size are found to have significant and positive impact. Besides, all reforms and/or economic measures need to be complemented by macroeconomic policies aimed to increase economic stability. Originality/value: The results presented in this study highlight some of the factors that appear to drive the relationship between employment and some structural policies, macroeconomic indicators and demographic factors for two groups of former colonies. The paper provides policy conclusions based on these results for the two groups. This analysis may indeed help to inform future policy discussions, yet much additional work is needed to identify macroeconomic "best practices” for encouraging employment in the post-2019 covid crisis period. © 2022, Malika Neifar.

Path to sustainable development: Does digital economy matter in manufacturing green total factor productivity?

In the context of the outbreak of the COVID-19 pandemic and China's "digital power” strategy, the realization of a green shift of manufacturing has become a necessary condition to promote the economy, and the digital factor has increasingly become a new driving force. The DEA-Malmquist index and entropy method were used to measure the manufacturing green total factor productivity (GTFP) and the level of digital economy level from 2011 to 2018, respectively. This study then explored the impact of digital economy on manufacturing GTFP based on the system generalized method of moments (GMM) model, as well as the adjustment effects of talent aggregation and financial scale according to the moderating model. This research came to four conclusions. (1) The digital economy can significantly improve the manufacturing GTFP of China, and the influence shows the characteristic of a "marginal increase”;(2) notably, the perspective of manufacturing GTFP decomposition indicates that the digital economy exerts a significant positive effect on manufacturing technical efficiency during the current period but obviously hinders technical progress;(3) interestingly, a mechanistic test showed that the two dimensions of innovation environment—talent aggregation (0.385) and financial scale (0.359)—play critical moderating roles in the influencing process;and (4) the influence has evident regional heterogeneity—it is significantly positive in the east and negative in the central region and west. Finally, corresponding policy suggestions are suggested. © 2022 ERP Environment and John Wiley & Sons Ltd.