Examination of the Effects of COVID-19 on Happiness in Different Geographical Regions with Piecewise Linear Panel Data Models

The COVID-19 pandemic has recently caused the loss of millions of lives, and billions of others have been deeply affected. This crisis has changed the way people live, think about life, and perceive happiness. The aim of this study is to reveal differences between geographical regions by investigating the effect of the happiness variable on different countries during the international COVID-19 pandemic. The primary purpose is to demonstrate how such a pandemic may affect different countries in terms of happiness at the individual level and to identify possible strategies for the future. With this aim, both static and dynamic panel data models were used while applying fixed effects, random effects, and the generalized method of moments (GMM). A basic assumption in panel data models is that the coefficients do not change over time. This assumption is unlikely to hold, however, especially during major devastating events like COVID-19. Therefore, the piecewise linear panel data model was applied in this study. As a result of empirical analysis, pre- and post-COVID differences were seen between different geographical regions. Based on analysis conducted for three distinct geographical regions with piecewise linear models, it was determined that the piecewise random effects model was appropriate for European and Central Asian countries, the piecewise FGLS model for Latin American and Caribbean countries, and the piecewise linear GMM model for South Asian countries. According to the results, there are many variables that affect happiness, which vary according to different geographical conditions and societies with different cultural values.

Gambling-Motivated Market Attention and Stock Market Volatility

Retail investors show gambling preferences and pay greater attention to the market than individual stocks. Previous studies report a positive and significant relationship between market attention and volatility. This relationship results from the joint effects of attention to investment-motivated and gambling-motivated components. However, the separate roles of these two components have not yet been examined. Hence, this study applied principal component analysis to identify the gambling-motivated component from market attention and gambling-related variables. The investment-motivated component is the regression residual of the market's attention paid to the gambling-motivated component. This study linearly relates these two components to volatility. The generalized method of moments regression was used to resolve endogeneity problems and biased estimates. The Google search volume index is a proxy for unobserved retail investors' market attention. Using a daily sample of the Thai market from August 6, 2008, to September 30, 2022 (a total of 3,450 observations), this study found a positive relationship between market attention and stock market volatility. This relationship results from the positive effects of both investment-motivated and gambling-motivated components. Attention to gambling is more influential than attention to investment. The explanatory powers of gambling-attention and investment-attention for volatility were 81.33% and 18.67%, respectively. These effects were less pronounced during the COVID-19 pandemic.

Comparison of the Performances for CAPM and Fama-French models During COVID-19

Since the outbreak of COVID-19, it has caused a startling stun to both society and economy in numerous nations, where different industries suffered unequally. This paper reviews the various performance of the Capital Asset Pricing Model (CAPM), and the Fama-French three-factor model and the five-factor model in different regions and industries. To metric the performance, various statistics models and scaling are applied including Pearson correlation, linear regression, R2 scores, t-test, etc. Specifically, this paper demonstrates the different performances of the CAPM model on the US and Egyptian stock markets, whereas using generalized method of moments in a panel data analysis to evaluate the performance in the U.S. market and the paired sample t-test and Wilcoxon signed-rank to evaluate the performance in the Egyptian market. The Fama-French three-factor model and five-factor model are both based on the U.S. market and analyze the model's performance (measured by significant level) in the U.S. market in general and in individual sectors, respectively. Whereas, in terms of three-factors model, the OLS estimation and relapse expected excess return are used onto the variables and multiple linear regression method was used to study the significance of factors in three sub-industries. Regarding to five-factors model, a multivariate regression with covariates and OLS estimation are the method for evaluation. These results shed light for deeply understanding the model and recognizing the impact on the security market of the COVID-19. © 2023 SPIE.

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.

Unemployment - Corruption Relationship in OECD Countries: System GMM Approach

Corruption, abuse of public office for private gain, is mainly found to impact macroeconomic indicators adversely in the long run. In this vein, this paper investigates the impact of corruption on unemployment in Organization of Economic Cooperation and Development (OECD) countries between 1996-2020. Utilizing World Governance Indicators (WGI) corruption data and implementing the system generalized method of moments (GMM) methodology to overcome endogeneity and reverse causality issues, the results indicate that corruption increases unemployment in all models when various variables are controlled for. The robustness checks with alternative econometric estimations (i.e., difference GMM, fixed effect, and ordinary least squares (OLS) regressions) and corruption index (i.e., Corruption Perception Index (CPI)) verify the conclusion of system GMM that higher corruption leads to higher unemployment. However, the magnitude depends on the model and specification. The results reveal that specific policies should be implemented to eliminate corruption in political and bureaucratic spheres so that the unemployment rate can be maintained around the natural rate of each country.

Environmental tax and global income inequality: A method of moments quantile regression analysis

Even though Environmental tax policy impacts inequality theoretically, empirical studies remain scanty not only in the context of volumes and the estimation approaches but are also focused on selected advanced countries, communities, households, and emerging countries, the neglect of the global or big picture effect, which is essential for measuring the overall effect of the collective and individual country-concerted efforts in addressing this global cancer. We provide empirical evidence in the global context using the novel method of moments quantile regression. We found that Income Inequality across the globe is sharply reduced by restrictive environmental tax policy, a finding that has ramifications for global sustainable development, particularly in dealing with the ravaging effects of Covid-19. © 2023 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

The Arab Spring and Its Implications for FDI Inflows to the MENA Region

The Arab Spring (AS) marked an unprecedented event in the Middle East and North Africa (MENA) region, and it generated political and economic uncertainties and triggered violent conflicts and political rifts. This paper empirically examines the short-run and long-run effects of the AS on foreign direct investment (FDI) inflows to the MENA region and to individual MENA countries. The empirical analysis is implemented through the generalized method of moments (GMM) estimator for dynamic panel models, using different empirical specifications. The benchmark results show that the AS has led to important reductions in FDI inflows to the MENA region. A more detailed empirical analysis reveals significant variations in the AS effects on FDI inflows across MENA countries and it underscores distinct patterns over different time periods. These findings imply that governments in the MENA region are required to maintain political stability, and to adopt distinctive policies that lessen the adverse implications of the AS and that set favorable conditions for FDI inflows in the post-COVID-19 pandemic era.

Determinants of nonperforming financing in Indonesian Islamic banks: A regional and sectoral analysis

This study examines the determinants of Islamic banks' non-performing financing from the perspective of regional and sectoral aspects during the periods before and during the pandemic. The study adopts a dynamic panel data analysis, namely the Generalized Method of Moments, and assesses panel data from the Indonesian banking industry in 32 provinces from October 2018 to July 2021 on a monthly basis. The study uses non-performing financing as the dependent variable and regional inflation, total financing, financing to deposit ratio, and Islamic bank size as the dependent variables. The findings indicate that the COVID-19 pandemic generally influenced the performance of non-performing financing in Islamic banks. This was evident in the significant relationship between regional inflation, total financing, financing to deposit ratio, and the non-performing financing value. Moreover, in the sectoral analysis, a different level of impact was observed in each sector. The most severe impact was seen in the construction sector, while other sectors were less affected during the pandemic. The regional analysis shows that all provinces on Java Island, as the epicenter of the pandemic in Indonesia, did not perform better than the provinces outside Java. Concerning policy implications, the Indonesian Financial Services Authority must be more aware of the determinants of Islamic banks' non-performing financing by considering sectoral and regional aspects. Furthermore, sectoral and regional-based policies should be developed to achieve and maintain the performance of Islamic banks' non-performing financing. © Faaza Fakhrunnas, Riska Dwi Astuti, Mohammad Bekti Hendrie Anto, 2022.

Information and volatility linkages between real estate, equity, bond and money markets in Australia

PurposeThe purpose of this paper is to examine information and volatility linkages among real estate, equity, bond and money markets in Australia.Design/methodology/approachA novel rational expectations framework of financial contagion (Kodres and Pritsker, 2002), along with a combination of robust statistical methods including simple and dynamic correlations and generalized impulse response (Fereidouni et al., 2014) have been employed using data covering three dynamic pre-pandemic economic cycles, namely, global financial crisis (GFC) period, pre-pandemic housing boom and pre-pandemic housing downturn from 2008 (February) to 2019 (December).FindingsResults reveal information linkages across real estate, equity, bond and money markets through correlations in return and volatilities of these series. Finding indicates that the three financial markets (equity, bond and money markets) are interdependent and integrated through information and volatility linkages during the GFC period and pre-pandemic housing downturn period. Financial markets have stronger associations with real estate market during pre-pandemic housing boom. The findings contribute to the general notion that the performances of three financial markets are closely related to the "boom” phase of the real estate cycle.Originality/valueThis research provides an extension of existing literature regarding the information and volatility contagion of the expanded set of core investment markets in Australia. The findings could assist household buyers and investors in designing strategic investment portfolios/hedging strategies and minimizing asset specific risks through diversification over short-term and long-term. In addition, results could support the maintenance, growth and development of a combination of competitive balanced investment markets including real estate, equity, bond and money markets in post-pandemic economy.

Sustainable economic development across globe: The dynamics between technology, digital trade and economic performance

Technology makes a significant contribution to economic performance globally. Information and communication technologies and the economic growth nexus are widely debated;however, this study examined the economic performance of 93 countries categorized as developed and developing countries between 2005 and 2019. The study employs Breitung et al.'s (2021) novel bias-corrected method of moments estimators for dynamic panel data models For serve the purpose, the study utilizes the novel Bias-corrected method of moments estimators for dynamic panel data models by Breitung et al. (2021) [1]. The results were threefold: first, technology has both direct and indirect impacts on economic performance. Education plays a moderating role in further escalating economic performance through technology across the globe. Second, digital trade does contribute to economic growth as well. Third, there is a heterogeneous effect of COVID-19 on economic performance across various income groups of countries. The innovative results of the study suggest important policy recommendations.

Latin America and the Caribbean SARS-CoV-2 Surveillance: Longitudinal Trend Analysis.

BACKGROUND: The COVID-19 pandemic has placed unprecedented stress on economies, food systems, and health care resources in Latin America and the Caribbean (LAC). Existing surveillance provides a proxy of the COVID-19 caseload and mortalities; however, these measures make it difficult to identify the dynamics of the pandemic and places where outbreaks are likely to occur. Moreover, existing surveillance techniques have failed to measure the dynamics of the pandemic. OBJECTIVE: This study aimed to provide additional surveillance metrics for COVID-19 transmission to track changes in the speed, acceleration, jerk, and persistence in the transmission of the pandemic more accurately than existing metrics. METHODS: Through a longitudinal trend analysis, we extracted COVID-19 data over 45 days from public health registries. We used an empirical difference equation to monitor the daily number of cases in the LAC as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. COVID-19 transmission rates were tracked for the LAC between September 30 and October 6, 2020, and between October 7 and 13, 2020. RESULTS: The LAC saw a reduction in the speed, acceleration, and jerk for the week of October 13, 2020, compared to the week of October 6, 2020, accompanied by reductions in new cases and the 7-day moving average. For the week of October 6, 2020, Belize reported the highest acceleration and jerk, at 1.7 and 1.8, respectively, which is particularly concerning, given its high mortality rate. The Bahamas also had a high acceleration at 1.5. In total, 11 countries had a positive acceleration during the week of October 6, 2020, whereas only 6 countries had a positive acceleration for the week of October 13, 2020. The TAC displayed an overall positive trend, with a speed of 10.40, acceleration of 0.27, and jerk of -0.31, all of which decreased in the subsequent week to 9.04, -0.81, and -0.03, respectively. CONCLUSIONS: Metrics such as new cases, cumulative cases, deaths, and 7-day moving averages provide a static view of the pandemic but fail to identify where and the speed at which SARS-CoV-2 infects new individuals, the rate of acceleration or deceleration of the pandemic, and weekly comparison of the rate of acceleration of the pandemic indicate impending explosive growth or control of the pandemic. Enhanced surveillance will inform policymakers and leaders in the LAC about COVID-19 outbreaks.

Modeling COVID-19 Infected Cases and Deaths Based on Generalized Method of Moments

This paper investigates the dynamic relationships between the number of COVID-19 infected cases and deaths in all the districts of Karnataka state, India, from July 2020 to December 2021 based on the panel Generalized Method of Moments (GMM). The panel GMM model with the first difference transformation was found suitable for studying the dynamics of the number of deaths due to COVID-19 infections over time. The one-period lag (DEATHS (-1)) has a positive and significant effect on the number of deaths (DEATH). The Wald test confirms the validity of the coefficients' significance and adds explanatory power to the model. The correlation between number of fatalities at time t positively correlated with the number of deaths in the previous period. Also, the number of infected cases positively and significantly influences the number of deaths over time. Granger pairwise causality test reveals the existence of bi-directional causality relationships between the COVID-19 infected cases and deaths.

A Wiener process with jumps to model the logarithm of new epidemic cases

The number of daily new cases of an epidemic is assumed to evolve as the exponential of a Wiener process with Poissonian jumps that are exponentially distributed. The model parameters can be estimated by using the method of moments. In an application to the COVID-19 pandemic in the province of Quebec, Canada, the proposed model is shown to be acceptable. General formulas for the probability that a given increase in the number of daily new cases is due to the normal variations of the continuous part of the process or rather to a jump of this process are given. Based on these formulas, the probability of observing the likely start of a new wave of infections is calculated for the application to the COVID-19 pandemic.

Bank-specific performance indicators, macroeconomic variables and capital adequacy of Nigerian banking industry

[...]we canvass those Nigerian banks should reduce dividend payouts and increase retained profits as a buffer against exposed risks. To ensure the healthiness of banks in the banking industry as well as facilitate international transaction, the central bank of ten countries (Belgium, Canada, France, Germany, Italy, Japan, the Netherlands, Sweden, the UK and the US) formed the committee of banking supervision in 1988 (the Basel Committee on Banking Supervision). Since the formation of this committee, it has undergone at least three stages called the Basel I, Basel II and Basel III. Premised on shock to the economy brought on by the coronavirus pandemic, with economic growth in 2020 expected to contract by as much as 4.4 percent to 8.94 percent, a drop in oil receipt and a devalued Naira in the range of 380-450 to US dollar, the capital adequacy of banks could be severely threatened, (Egba, 2020). [...]scholars have extensively shown that bank specific performance indicators and macroeconomic factors affected capital adequacy ratio. [...]this paper examined the effect of banks specific-performance indicators and macroeconomic factors on bank financing which is the minimum funds required for their short-term obligation or capital adequacy ratio.

To Study the Effect of Corporate Governance on the Performance of Indian Listed Firms: A Comparative Panel Data Analysis

Purpose –This study aims to provide empirical evidence on the relationship between corporate governance and firm performance during pre and post-pandemic. The pandemic's effect on businesses, especially those of developing nations, served as a motivating factor for the author. Methodology – The balanced panel data were used for firms listed in BSE S&P 500 from the financial year 2018 to 2021. To account for possible endogeneity and unobserved heterogeneity, we employed the Generalised Method of Moments to analyse the relationship between corporate governance and business performance. After excluding financial firms and firms with unavailable data, the sample size was reduced to 285 listed firms. Findings – The study's findings showed that the average board size for Indian firms is over nine and has a significant positive relationship with ROA. ROE and dividend payout in both sampling periods. A significant number of directors bring intellectual diversity and a variety of ideas. However, before the pandemic, board independence had a significant positive relationship with ROA, ROE and TobinQ but a significant negative association with the firm's market value (TobinQ). Further findings revealed that CEO-Duality had a significant negative relationship with firm performance in both sampling periods. Implications-The study's findings provide helpful empirical evidence to policymakers and listed companies in India. Originality-Few studies have examined the relationship between corporate governance and firm performance in pre and post-pandemic periods in emerging markets. Limitation-Although the time frame for this study was restricted, further research might be conducted over a longer time. Future studies could add other factors, such as ownership structure and cost of capital.

Non-Renewable and Renewable Energies, and COVID-19 Pandemic: Do They Matter for China’s Environmental Sustainability?

Since the emergence of the COVID-19 pandemic, people all around the globe have seen its effects, including city closures, travel restrictions, and stringent security measures. However, the effects of the COVID-19 pandemic extend beyond people’s everyday lives. It impacts the air, water, soil, and carbon emissions as well. This article examines the effect of energy and the COVID-19 pandemic on China’s carbon dioxide emissions in light of the aforementioned context, using the daily data from 20 January 2020 and ending on 20 April 2022. Using the nonlinear autoregressive distributed lag model for empirical analysis, the findings indicate that COVID-19 pandemic confirmed cases and renewable energy advance environmental sustainability due to their negative effects on carbon dioxide emissions, whereas fossil fuel energy hinders environmental sustainability due to its positive effect on carbon dioxide emissions. Moreover, these results are also supported by the results of the frequency domain causality test and the Markow switching regression. In light of these results, there are several policy implications, such as vaccination, renewable energy utilization, and non-renewable energy alternative policies, which have been proposed in this paper.

A new face of food security: A global perspective of the COVID-19 pandemic.

COVID-19 has impacted the world economy and food system in many aspects. We conducted a comprehensive examination of global food security during the COVID-19 pandemic by considering the food security index and its four key pillars (affordability, availability, quality and safety, and natural resources and resilience) for 102 countries. In addition to the fixed effect panel data estimator, the Method of Moments Quantile regression is useful for disaggregating the impact of the COVID-19 pandemic in relation to inflation, economic growth, urbanization, and agricultural land on global food security among countries with different levels of food security. We found that COVID-19 has negatively affected food security globally, especially in countries with a low food security level. The effect of income per capita and urbanization rate on the food security index is positive and statistically significant across all quantiles. Inflation rate and agricultural land, however, adversely affect food security, and this effect is stronger for countries with lower levels of food security. The results of affordability, availability, quality, and safety, and natural resources and resilience models provide meaningful implications for governments and policymakers to build resilience in food systems and to be better prepared for future crises and disruptions in the food supply.

The Influence of Taxation on Income Inequality: Analysis of the Practice in the EU Countries

The growing economic inequality around the world is recognized as a global problem of mankind. At the same time, the key tool for reducing inequality and ensuring the achievement of sustainable development goals is the taxation system given its distributive function. That is why this paper puts forward and proves a scientific hypothesis according to which direct taxation has a significant impact on economic inequality, with its scale and sphere depending on the level of economic development and the specific architecture of the tax system adopted in a particular country. The study relies on data from 28 European Union countries, including the United Kingdom, whose tax systems are not identical but harmonized in accordance with European Union directives, the same as the legislation in other economic sectors. Accordingly, it can be concluded that similar institutional characteristics are present. We have used the method of two-stage cluster analysis, which is meant for identifying the natural splitting of the mass of data into groups, then carried out regression analysis and built some models. The contribution of the study is revealing a number of important regularities that are significant for characterizing the dependence of income inequality on direct taxation as well as formulation recommendations for improving the tax policies of European Union countries, with the potential of policy implications. The results obtained can play a significant role in the development and further harmonization of tax systems and resolving the global problem of increased inequality within and between countries.

Exploring the Relationship between Energy and Food Security in Africa with Instrumental Variables Analysis

The well-being of human populations and their sustainable development are strongly predicated on energy and food security. This is even more true of Africa due to often suboptimal food production, undernourishment, and extreme poverty. This article researches the relationship between energy and food security using Cobb–Douglas production functions based on the World Development Indicators data for 28 African countries. The methodological approach includes cross-sectional dependence and unit root tests, instrumental variables two-stage least-squares and generalized method of moments, and panel Driscoll–Kraay standard errors. Results suggest that the promotion of energy security promotes food security. This is possible because food production and distribution are energy-intensive. Therefore, energy is fundamental to achieving food security and zero hunger. The availability, affordability, accessibility, and acceptability of energy can thus help to fix the growing agricultural production shortage in Africa. An important policy focus should be on achieving energy security.

Is Ethereum's Price Return Determined by COVID-19, Macro-financial, and Crypto Market Factors?

We investigated COVID-19 cases per country, macro-financial, and crypto market factors that might have affected Ethereum's price return in the top three countries of users, which were also affected by COVID-19 (United States, China, and Germany). Feasible Generalized Least Square (FGLS) was used as the methodology and the generalized method of moments (GMM) was tested for a robustness check. The findings revealed that Ethereum price returns were greatly affected by COVID-19 factors. Meanwhile, macro-financial factors (stock indices and gold) had stronger effects on the return of Ethereum price rather than the crypto market. © 2022 ACM.