The effectiveness of emerging markets' legal structure in explaining financial development.

This article examines the role of legal structure in explaining financial development in twenty-three emerging markets, which has not been explored in institutional economics literature before. This study relied on Pedroni, and Kao cointegration tests, which is followed by the renowned panel cointegration technique. The results of the Pedroni and Kao cointegration tests show that the variables understudy is cointegrated in the long-run. These findings are confirmed by the panel cointegration showing that legal structure (LS) has positive impact on financial development (FIND) in long-run that support Law and Finance, and New Institutional Economics theories in emerging markets. This study is the first to directly examine the long-run impact of LS on FIND in emerging markets, and the result remains consistent across alternative measure of FIND. The findings of this study have important policy implications for emerging markets. Policymakers should focus on creating a legal environment that is conducive to financial development. This includes strengthening the legal framework, improving regulatory regimes, and promoting market autonomy. Additionally, policymakers should work to attract foreign investment, which can help spur economic growth and development in emerging markets. The findings of the study are consistent across battery of robustness testing.

Democracy's limited impact on innovation: Panel data evidence from developing countries.

This study investigates the relationship between democracy and innovation across 61 developing countries from 2013 to 2020, utilizing data from Global Innovation Index. Employing the Freedom House Index and Polity2 indicators as proxies for democracy, research employs Ordinary Least Squares (OLS), Fixed Effects and SystemGMM techniques to analyze their impact on innovation. The findings of the study reveal no statistically significant relationships between democracy and innovation in developing nations within specified timeframe. Through empirical analysis, including various econometric approaches, it is observed that the level of democracy as measured by these indicators, does not appear to exert a discernable impact on the innovation landscape of these countries. These results carry important implications for public policy. While the promotion of democracy remains a crucial goal, especially for societal development and political stability, this study suggests that solely focusing on enhancing democratic institutions might not necessarily yield immediate direct improvements in the innovation capacities of developing nations. Policymakers and stakeholders involved in fostering innovation ecosystems in these regions may need to consider a more nuanced approach, encompassing factors beyond the scope of democratic governance to effectively spur innovation. Understanding the nuanced relationship between democracy and innovation in developing countries has significant implications for designing targeted policies aimed at enhancing innovation capacities, economic growth and overall societal development in these regions.

SASAN: ground truth for the effective segmentation and classification of skin cancer using biopsy images.

OBJECTIVES: Early skin cancer diagnosis can save lives; however, traditional methods rely on expert knowledge and can be time-consuming. This calls for automated systems using machine learning and deep learning. However, existing datasets often focus on flat skin surfaces, neglecting more complex cases on organs or with nearby lesions. METHODS: This work addresses this gap by proposing a skin cancer diagnosis methodology using a dataset named ASAN that covers diverse skin cancer cases but suffers from noisy features. To overcome the noisy feature problem, a segmentation dataset named SASAN is introduced, focusing on Region of Interest (ROI) extraction-based classification. This allows models to concentrate on critical areas within the images while ignoring learning the noisy features. RESULTS: Various deep learning segmentation models such as UNet, LinkNet, PSPNet, and FPN were trained on the SASAN dataset to perform segmentation-based ROI extraction. Classification was then performed using the dataset with and without ROI extraction. The results demonstrate that ROI extraction significantly improves the performance of these models in classification. This implies that SASAN is effective in evaluating performance metrics for complex skin cancer cases. CONCLUSIONS: This study highlights the importance of expanding datasets to include challenging scenarios and developing better segmentation methods to enhance automated skin cancer diagnosis. The SASAN dataset serves as a valuable tool for researchers aiming to improve such systems and ultimately contribute to better diagnostic outcomes.

From risk to resilience: Climate change risk, ESG investments engagement and Firm's value.

In line with Sustainable Development Goals, firms are increasingly incorporating Environmental, Social, and Governance (ESG) considerations in their investment strategies. The effect of firms' climate change risk (FCCR) on firms' Value (FV), and how such investment engagements moderate this effect, is a prominent subject of debate among scholars, investors, and policymakers. To examine these dynamics, we analyze a dataset of 1771 United States (US)-listed firms from 2006 to 2021 to quantify the effect of FCCR on FV. We use the generalized method of moments model to achieve our objectives. The major findings are summarized as follows: First, FCCR has a negative and significant effect on FV. Second, ESG investments positively and significantly influence FV. Third, ESG investments significantly moderate the FCCR-FV relationship. We confirm our estimations are robust under different estimations strategies. Finally, this article provides a fresh perspective on risk management with significant policy implications for investors, managers, and regulators in the US. We suggest that ESG investing is an important strategic catalyst for US firms.

From desolation to preservation: Investigating longitudinal trends in forest coverage and implications for future environmental strategies.

Pakistan's forest cover is experiencing significant degradation in the ongoing efforts to combat climate change. The current state of the climate catastrophe is acknowledged. Nevertheless, there is a significant lack of readiness to tackle it effectively, especially regarding safeguarding the welfare of forthcoming generations. Pakistan bears significant relevance for future generations in this global crisis. The primary objective of this study is to examine the environmental difficulties faced by Pakistan and emphasize the critical need to safeguard its natural resources, considering the well-being of present and future generations. By using rigorous correlation and robust least squares regression methods, we investigate the complex interplay of financial aid, environmental legislation, precipitation, population growth, foreign direct investment, and afforestation within the time frame spanning from 1990 to 2022. The findings demonstrate that providing financial aid for afforestation initiatives significantly expands forested areas in Pakistan. Furthermore, the expansion of the population, the implementation of rigorous environmental restrictions, and the yearly amount of precipitation all play a role in the augmentation of forest coverage in Pakistan. Nevertheless, an alarming pattern of diminishing forest coverage over the years presents noteworthy obstacles. The importance of governance in promoting afforestation initiatives and sustainable development is highlighted by the emergence of adequate regulatory quality as a key factor. The average amount of precipitation has a discernible beneficial influence, underscoring the significance of climatic factors. The results above emphasize the need to implement cautious water resource management strategies and regulations responsive to climatic conditions. Based on these observations, the study proposes promoting sustainable agricultural and forest management, adopting a well-balanced strategy towards population expansion, implementing regulatory changes, and prudent use of water resources.

Does sustainable banking facilitate reducing the SDG-10 in weak rule of law setting?

Facilitating economic opportunities is a critical function of the financial sector, and this contributes significantly towards the attainment of Sustainable Development Goals 10 (SDG-10), which aims to reduce income inequality. This research examines the role of sustainable banking practices in reducing income inequality and achieving SDG-10 under weak rule of law settings. We employed a panel cluster regression model to examine the data collected from 890 banks across 49 nations over a nine-year period (2014-2022). Specifically, we opted to cluster the observations based on industry and year to produce unbiased standard error. The findings reveal that sustainable banking practices are more effective in reducing income inequality, especially in settings with weak rule of law. They also contribute to combating money laundering, which is a significant barrier to achieving SDG-10. The study highlights the importance of transparent and responsible financial transactions in promoting investment opportunities that contribute to sustainable development. Moreover, we find that sustainable banking can accelerate the impact of Fintech in reducing income inequality in weak rule of law settings. The use of Fintech in the financial industry can improve transparency, accountability, and fairness, which are essential for progress towards achieving SDG-10. These findings have significant implications for the expansion of sustainable banking practices in regions with weak institutional frameworks.

Dynamic prediction of survival via Landmark method using the asthma prevention trial in young children.

This paper focuses on the applications of Landmark method for obtaining dynamic predictions of survival by using Landmark approach to the data of asthma prevention trial in young children. This work focuses on the different ways to model recurrent events by considering various time scales according to how subjects in the dataset experienced multiple events. Landmark models can be used to dynamically estimate the effect of treatments effects whilst also taken into consideration the history of previous asthma attacks. Our analysis show that the treatment effect should be modelled with a time varying effect and the effect of the previous attack reduces with the passage of time.

Impact of despotic leadership and workplace incivility on innovative work behavior of employees: Application of mediation-moderation model.

Innovative Work Behavior (IWB) of employees is one of the essential requirements for organizations to excel in competition in today's dynamic world. Nowadays, organizations can keep the current pace through competitive advantage. But to acquire competitive advantage, employees must be creative and innovative in their work-related behaviors. Small and Medium Enterprises (SMEs) in Pakistan are suffering several challenges in this regard. Therefore, current study is designed to examine the role of negative events and negative leadership on the IWB of the employees with mediating role of Psychological Well-being (PsyWB). Further, the moderating role of Perceived Organizational Support (POS) has also been tested. The negative event used in current research is Workplace Incivility (WPI) and Despotic Leadership (DL) from the negative leadership styles examined. Results of the current study showed that the presence of WPI and DL in organizations damage the IWB of employees as they harm the PsyWB of employees. We find that PsyWB mediated the relationship among DL, WPI, and IWB. POS is helpful for employees to overcome the negative issues prevailing in the organizations. The SMEs need to construct policies to eradicate WPI and must discourage despotic personalities to make the environment favorable for employees to protect their IWB. There must be some events that can increase the positive PsyWB of employees to make them more creative and motivated. Likewise, POS must be at sufficient level so that employees feel safe and healthy in all respects.

Does investors' site visits improve the capital market pricing efficiency?

This article empirically tested the impact of investors' site visits on capital market pricing efficiency. Leveraging the data from 2009 to 2022 of Shenzhen Stock Exchange's listed companies, we found that: (1) Investors' site visits could reduce stock price synchronicity, indicating improved pricing efficiency of the capital market. (2) The mechanisms tests showed that: investors could obtain private incremental information through site visits. (3) The conclusions remained intact after robust tests, including alternative key variables, samples and specifications, and various endogenous treatments. (4) Investors added arbitrage trading behavior after the site visit without significantly impounding industry-level information into the stock price. This paper enriched the knowledge of how site visits of different investment entities affect capital market pricing efficiency.

Dynamic association of stock market volatility, foreign portfolio investment and macroeconomic indicators by taking the impact of structural breaks.

In an asymmetric information environment, investors diversify their investments to minimize risk and maximize their wealth. Such diversification ranges from one market to another market and from one country to another country. Investors prefer foreign portfolio investment over foreign direct investment because of the economy's turmoil, changes in macroeconomic indicators, and market liberation. This study analyzes the dynamic relationship among stock market volatility, foreign portfolio investment, and macroeconomic indicators (foreign exchange rate, interest rate, and Gross Domestic Product) using the dynamic long-run Auto-regressive Distributed Lag (ARDL) model concerning the Pakistan environment. This study also considers the impact of multiple structural breaks, representing variables' endogenous and exogenous shocks. The secondary data is used from Oct. 01, 2009, to Sept. 30, 2019, with monthly frequency. The results indicate a co-integration between SMV, FPI, FXR, IR, and GDP. In short-run analyses, the error correction term is statistically significant, while in the long run, the SMV, FPI, and FXR are not impacted. As no evidence of volatility has been found between SMV and FPI, unidirectional or bi-directional policies can be devised to further attract the new FPI for strengthening the foreign reserves, the balance of payments, and other macroeconomic variables. Additionally, investors should update their knowledge based on considering the endogenous and exogenous shocks on the SMV.

Country-level institutional quality and financial system efficiency: An international evidence.

The optimum economic outcome of financial system development depends on its level of efficiency. The purpose of this study is to investigate the effect of institutional quality on financial system efficiency. For empirical analysis, we have used a panel dataset of 108 countries from 1996-2020 and employed fixed effect regression and two stages least squares (2SLS) regression methods. The empirical results show that institutional quality has a significant positive effect on financial system efficiency. Particularly all the constituting elements-voice and accountability, political stability and absence of violence, regulatory quality, government effectiveness, rule of law, and control of corruption-of institutional quality are found to have a significant positive impact on financial system efficiency. Moreover, we found that the effect of institutional quality is more pronounced in countries with low-income levels and strong institutional quality. These findings are robust across several robustness tests conducted using additional controls, alternative methodologies, an alternative measure of institutional quality, and financial system efficiency. The results of the study suggest that policy makers should prioritize both enhancing and sustaining institutional quality to promote the efficiency of the financial system, which is crucial for sustainable growth and development.

Economic policy uncertainty and stock market in G7 Countries: A panel threshold effect perspective.

Based on the literature, it is commonly understood that stock prices (SP) are influenced by economic policy uncertainty (PU), with a rise in PU typically having a negative impact on SP. However, the relationship between PU and SP may not always be linear due to the varying risk preferences of individuals. Risk preference theory posits that individuals respond differently to different levels of risk. Therefore, this study aims to investigate whether PU determines SP asymmetrically (i.e., in a non-linear manner) by considering risk preferences and addressing a gap in the literature. To answer this question, the study employs a panel threshold approach to examine the effect of PU on SP in the Group of Seven (G7) countries, namely Canada, France, Germany, Italy, Japan, UK, and the US. In contrast to previous research, this study finds evidence of an asymmetric effect of PU on SP in the G7 countries. Specifically, the panel threshold results reveal that the impact of increased PU on SP is positive up to a certain level (Threshold1), beyond which it becomes negative (Threshold2). These findings are in line with information asymmetry hypothesis, prospect theory, behavioural finance hypothesis, and market liquidity hypothesis and shed light on the asymmetric behaviour of SP in response to varying levels of PU. The implications of these findings are significant for understanding how to manage risks effectively in the financial markets.

Corporate vulnerability in the US and China during COVID-19: A machine learning approach.

The impact of COVID-19 on stock market dynamics and other macroeconomic indicators has been extensively researched. However, the question of how it affects corporate vulnerability has received less attention. This article aims to fill this gap by examining the implications of COVID-19 on corporate vulnerability in the United States (US) and China, using daily data from January 2020 to December 2021. The empirical results of cointegration analysis demonstrate that COVID-19 considerably worsen corporate vulnerabilities in the long-term in the US and in the short-term in China. Additionally, non-linear results demonstrate long-run asymmetries in the US and short-run asymmetries in China, confirming the accuracy of error prediction and suggesting that US corporations are more exposed to COVID-19-induced risks. The channels through which COVID-19 may affect corporate vulnerability include changes in consumer behavior and demand, disruptions in supply chains, financial stress, government policies and regulations, and changes in the competitive landscape. This study sheds light on the effects of the COVID-19 pandemic on corporate vulnerability in the US and China, revealing regulatory implications that may necessitate greater government involvement, managerial implications that emphasize risk management and contingency planning, and social implications that highlight the importance of prioritizing stakeholder welfare and embracing digital transformation.

Role of institutions in promoting finance in emerging markets: A panel data analysis.

Differences in institutions have garnered much attention in recent years as one of the primary reasons for long-term economic performance, and a vast corpus of theoretical and empirical research demonstrates that financial development can have a substantial impact on economic and financial performance. In fast-growing emerging markets, the demand for financial services has considerably increased, which amplified the need for an efficient regulatory framework to deal with the sensitive nature of financial activities. Surprisingly, the existing literature on the impact of institutions and finance is focused on developed economies, while emerging markets are rarely focused on. Since emerging markets are becoming increasingly important as a result of the swift evolution of institutional and financial transformation, it is crucial to examine how the growth of financial markets reacts to institutional quality. This study investigates the role of institutions in promoting finance in emerging economies using the balanced panel dataset of 21 emerging market. Given the endogenous relationship between institutions and finance, the paper applies a two-stage least squares estimator to test the settler mortality hypothesis in this context. Aligned with theoretical intuition, the empirical result shows that settler mortality is a relevant instrument to institutions. Furthermore, the study performs robustness, using framework that deals with heterogeneity, and cross-section dependence. This empirical effort validates La Porta's Law and Finance Hypothesis in the context of emerging markets. The results of the study are found robust across the variety of alternative measures of institutions and finance, and standard error correction specifications. Therefore, the study offers useful insight into policy implications.

Do Laboratory Biomarkers Predict Survival In Severe Covid-19? A Cross-Sectional Study.

Background: This study aims to compare lymphocyte count, C-reactive protein (CRP), ferritin, Lactate Dehydrogenase (LDH) and D-dimer among survivors and non-survivors of severe COVID-19. Methods: This retrospective cross-sectional analytical study included 69 patients for whom a record of the biomarkers and survival status was available. Baseline and peak values were selected for serum CRP, ferritin, LDH and D-Dimer. Baseline and trough lymphocyte counts were selected. Data were analyzed using SPSS version 21. Mean and standard deviation were used to compare the biomarkers with paired t-test. p-value <0.05 was taken as significant. Results: The mean age of the study population was 55.5±9.1 years and 50 (72.5%) were male. Among survivors, the increase in CRP level was not significant (from 15.80±9.8 mg/dl to 17.87±8.4 mg/dl, p=0.45) while it was significant in non-survivors (from 16.68±10.90 mg/dl to 20.77±12.69 mg/dl, p=0.04). There was no significant rise in LDH levels in survivors (from 829.59±499 U/L to 1018.6±468 U/L, p=0.20) while it increased significantly in non-survivors (from 816.2±443.08 U/L to 1056.61±480.54 U/L, p=0.003). The decrease in lymphocyte count and increase in D-Dimers in both the groups was significant (p=0.001). There was no significant elevation in ferritin in both the groups (p>0.05). Conclusion: In severe COVID-19 patients, serum CRP and LDH can be used for risk stratification and predicting survival. Lymphopenia, increase in serum ferritin and D-dimers may not predict survival.

Work-life balance practices and organizational cynicism: The mediating role of person-job fit.

This study aims to elaborate on how work-life balance (WLB) practices influence organizational cynicism (OC) through the mediation effects of person-job fit (PJF). We collected data from 331 nurses through a self-administered survey, and we tested our hypothesized model through partial least square structural equation modeling techniques using SmartPLS software. The findings revealed that WLB practices influenced OC negatively and PJF positively. We further found that PJF negatively influenced OC and mediated WLB practices' effect on OC. These findings imply that nurses should be provided WLB practices to meet their job and home responsibilities and thus have a less cynical attitude toward the organization.

A Dynamically Consistent Nonstandard Difference Scheme for a Discrete-Time Immunogenic Tumors Model.

This manuscript deals with the qualitative study of certain properties of an immunogenic tumors model. Mainly, we obtain a dynamically consistent discrete-time immunogenic tumors model using a nonstandard difference scheme. The existence of fixed points and their stability are discussed. It is shown that a continuous system experiences Hopf bifurcation at one and only one positive fixed point, whereas its discrete-time counterpart experiences Neimark-Sacker bifurcation at one and only one positive fixed point. It is shown that there is no chance of period-doubling bifurcation in our discrete-time system. Additionally, numerical simulations are carried out in support of our theoretical discussion.

Can retail investors induce corporate green innovation? -Evidence from Baidu Search Index.

China's rapid economic development has caused some environmental damage in recent years. The popularity of the Internet has enriched the ways for investors to obtain information, which would exert an impact on corporate environmental behavior. Focusing on micro-enterprise green innovation from the perspective of informal regulation, this paper investigates the impact of investor attention on corporate green innovation. This study takes Chinese A-share listed companies from 2011 to 2018 as samples, constructs panel fixed-effects models and adopts multiple linear, Logistic and Tobit regressions. This article finds that investor attention, measured by the web search index, can significantly improve corporate green innovation. The conclusion is still valid after a series of robust tests. Besides, mechanism tests reveal that investor attention can promote corporate green innovation by improving the implementation efficiency of punitive environmental regulation, the use efficiency of environmental subsidies, and by increasing the reputation cost of enterprises. In additional tests, this paper further clarifies that investors' attention to negative public opinion can play a better role in environmental governance, and reveals the reason why investors are motivated to improve corporate green innovation. This research puts forward a unique perspective, which extends the understanding of informal environmental regulation and enriches research on green innovation at the micro-enterprise level, promoting the cross research of finance and environmental protection.

A novel systematic byte substitution method to design strong bijective substitution box (S-box) using piece-wise-linear chaotic map.

Cryptography deals with designing practical mathematical algorithms having the two primitive elements of confusion and diffusion. The security of encrypted data is highly dependent on these two primitive elements and a key. S-box is the nonlinear component present in a symmetric encryption algorithm that provides confusion. A cryptographically strong bijective S-box structure in cryptosystem ensures near-optimal resistance against cryptanalytic attacks. It provides uncertainty and nonlinearity that ensures high confidentiality and security against cryptanalysis attacks. The nonlinearity of an S-box is highly dependent on the dispersal of input data using an S-box. Cryptographic performance criteria of chaos-based S-boxes are worse than algebraic S-box design methods, especially differential probability. This article reports a novel approach to design an 8 × 8 S-box using chaos and randomization using dispersion property to S-box cryptographic properties, especially differential probability. The randomization using dispersion property is introduced within the design loop to achieve low differential uniformity possibly. Two steps are involved in generating the proposed S-box. In the first step, a piecewise linear chaotic map (PWLCM) is utilized to generate initial S-box positions. Generally, the dispersion property is a post-processing technique that measures maximum nonlinearity in a given random sequence. However, in the second step, the concept is carefully reverse engineered, and the dispersion property is used within the design loop for systematic dispersal of input substituting sequence. The proposed controlled randomization changes the probability distribution statistics of S-box's differentials. The proposed methodology systematically substitutes the S-box positions that cause output differences to recur for a given input difference. The proposed S-box is analyzed using well-established and well-known statistical cryptographic criteria of nonlinearity, strict avalanche criteria (SAC), bit independence criteria (BIC), differential probability, and linear probability. Further, the S-box's boomerang connectivity table (BCT) is generated to analyze its strength against boomerang attack. Boomerang is a relatively new attacking framework for cryptosystem. The proposed S-box is compared with the state-of-the-art latest related publications. Results show that the proposed S-box achieves an upper bound of cryptographic properties, especially differential probability. This work hypothesizes that highly dispersive hamming distances at output difference, generated a systematic S-box. The mixing property of chaos generated trajectories utilized for decimal mapping. To test the randomness of generated chaotic trajectories, a cryptographically secure pseudo-random sequence was generated using a chaotic map that was tested using the National Institute of Standards and Technology (NIST) NIST-800-22 test suit.

Determinants of anxiety and depression among Bangladeshi adults during COVID-19 lockdown: An online survey.

Background: Human health and well-being are adversely affected by the effects of COVID-19. This study examined the prevalence of anxiety and depression during COVID-19 lockdown in Bangladesh, and their association with some less explored factors like perceived and relative health status, having elderly members in the family, fear for own and family future, and others from the Asian context. Methods: Using an online survey, data were collected from the population aged 18 years and above, on socio-demographic and economic attributes, and two separate standardized twelve-item scales were used to assess the level of anxiety and depression. Both descriptive and multivariate linear regression were used to analyze the factors associated with anxiety and depression scores. Results: The respondents had an average anxiety score of 21.74 (SD = 8.20) on a scale ranging from 12 to 60 and an average depression score of 24.39 (SD = 10.30) on the same scale. The study findings revealed that respondents' concern for future well-being, perceived physical health status compared to others in the same cohort, and perceived physical health status during the survey compared to prior COVID-19 were significantly associated with anxiety and depression scores during COVID-19 lockdown. In addition, the anxiety score was significantly higher (p = 0.046) for women respondents than men. Moreover, respondents aged 18-24 years had significantly higher (p < 0.001) depression than others. Conclusions: The increased level of anxiety and depression during COVID-19 of adult people in Bangladesh are associated with several factors of which their greater concern about the future of their own and family members and health-related attributes are important. These findings may lead to developing interventions to reduce the psychological crisis during the pandemic in Bangladesh.