Search results

The dynamic effect of globalization on socio-economic disparity measured by the income inequality is always a noteworthy issue of research interests. Globalization is mostly appreciated from the aspect of economic growth, but it has been blamed for influencing the imperfect competition, environmental degradation, economic inequality, etc. Under this backdrop, this chapter seeks to examine the impacts of international trade and informational globalization on income inequality in both developing and developed groups of nations of the world using dynamic panel Generalized Method of Moments (GMM) estimates. The results of first difference dynamic panel GMM estimates imply the analogous impacts of trade and informational globalization on income inequality in both developing and developed groups of nations. However, the financial and political measures of globalization have dissimilar effects on income inequality across developing and developed economies.

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

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

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

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

Despite the importance of tax policy in reducing energy consumption and carbon emissions, there is a dearth of research on the environmental impact of indirect taxes. This paper examines the impact of indirect taxes on carbon dioxide (CO₂) emissions, with an emphasis on institutional quality.

The study uses the Government Revenue Dataset (2021), comprising 143 countries, dividing into 114 developing and 29 developed countries, during the period between 1996 and 2019. The author adopts panel data techniques, with Driscoll–Kraay standard errors to account for the issue of cross-sectional dependence (CSD).

The results indicate that indirect tax revenues have a negative and significant impact on CO₂ emissions for the total sample. The subsample analysis revealed that while indirect taxes reduce carbon emissions in developing countries, opposed results are reported for developed countries. This finding implies that most of the advanced countries have already reached a high level of taxes, at which carbon emissions increase as indirect tax increases further. Interestingly, the results revealed that institutional quality enhances the role of indirect taxes in mitigating carbon emissions for both developing and developed countries.

To the best of the authors' knowledge, this is the sole study using the newly developed tax data by the United Nations University, World Institute for Development Research (UNU-WIDER) to investigate the impact of indirect taxes on carbon emissions, with an emphasis on institutional quality. The existing literature focuses on specific taxes, like carbon taxes, with no comprehensive research on the link between indirect taxes and carbon emissions.

The paper aims to empirically examine the impact of foreign direct investment (FDI) inflows and digitalization on employment opportunities in selected 70 developing economies across the world over the period of 2001–2019. The same empirical investigations are also carried out on two groups of these developing countries created on the basis of the levels of FDI inflows and digitalization.

The study uses various panel unit root tests followed by the estimations of the generalized method of moments in the dynamic panel framework, using secondary data collected from the World Bank (2020), International Labour Organization (2020) and International Telecommunication Union (2020).

Empirical findings reveal that both FDI inflows and digitalization have positive effects on employment; however, the extent of the impact of digitalization is greater than that of FDI inflows in developing economies, mostly in countries with relatively low FDI inflows and low digitalization.

Conventionally, FDI inflows accelerate economic growth and thus improve the labour market in host countries. However, FDI inflows into developing countries with low-skilled labours may limit job creation, particularly during the process of digitalization. This study shows that despite a much moderate impact of FDI inflows, digital transformation supports a higher employment in developing economies with low level of FDI inflows and digitalization.

The purpose of this study is to examine the impact of board attributes and managerial ownership on cash holdings.

The present study examines a sample of 70 listed firms in Saudi Arabia observed during the period stretching from 2006 to 2016. To test the hypotheses, the authors used generalized method of moments and quantile regressions.

The empirical results reveal that corporate governance (CG) mechanisms are inefficient in the Saudi context. In fact, the authors found that board size, board independence, duality and managerial ownership impact positively and significantly cash holdings. Additionally, quantile regressions confirm the results that at certain thresholds, CG mechanisms are not efficient in protecting shareholders’ interests. Shariah compliance is found to moderate negatively and significantly the studied relationship.

This study helps to not only clarify and help decision-makers to see the importance of corporate cash management but also to identify the limits of the CG mechanisms put in place.

Expansion of the consumption of renewable energy is a significant issue for reducing global warming, to cope with climate change and achieve sustainable development. This study aims to examine how research and development expenditure (R&D) affects renewable energy development in developed G-7 countries over the period from 2000 to 2019. Variables of trade liberalization and CO₂ emissions are considered control variables.

This study has adopted a panel quantile regression. The impact of the variables on renewable development has been examined in quantiles of 0.1, 0.25, 0.5, 0.75 and 0.9. Also, a robust examination is accomplished by applying generalized quantile regression (GQR).

The empirical findings reveal a positive and significant relationship between R&D and the consumption of renewable energy in 0.1, 0.25, 0.5 and 0.75 quantiles. Also, the findings describe that the expansion of trade liberalization and CO₂ emissions can significantly increase the development of renewable energy in G-7 countries. Furthermore, GQR verifies the main outcomes.

These results have very momentous policy consequences for the governments of G-7 countries. Therefore, investment and support for the R&D section to promote the development of renewable energy are recommended.

This paper, in comparison to other research, used panel quantile regression to investigate the impact of factors affecting renewable energy consumption. Also, to the best of the authors’ knowledge, no study has perused the effect of R&D along with trade liberalization and carbon emissions on renewable energy consumption in G-7 countries. Also, in this paper, as a robustness check for panel quantile regression, the GQR has been used.

The paper aims to investigate the relationship between institutions and economic growth in developing countries, considering the role of financial inclusion, education spending and military spending.

The study employs dynamic panel analysis, specifically two-step system generalized method of moments (GMM), on a sample of 61 developing countries over the period 2009–2020.

The results confirm that weak institutional quality, weak financial inclusion and increased military spending are barriers to economic growth, conversely, increased spending on education and gross capital formation contribute to economic growth in developing countries. Regarding the specific institutional factor, we find that corruption, ineffective government, voice and accountability and weak rule of law contribute negatively to growth.

The study calls for strengthening institutions so that the financial system supports economic growth and suggests increasing spending on education to improve access to and the quality of human capital, which is an important determinant of economic growth.

The study contributes to scarce literature by empirically analyzing the relationship between institutions and economic growth by considering the role of financial inclusion, public spending on education and military spending, factors that have been ignored in previous studies. In addition, the study identifies the institutional dimension that contributes to reduced economic growth in developing countries.

We test the pertinence of the unemployment invariance hypothesis (UIH) for a set of Organisation for Economic Co-operation and Development countries.

We empirically investigate the nexus between unemployment and labour force participation employing structural vector autoregressive methods for panel data.

We find that shocks in unemployment produce long-lasting, negative effects on participation, testifying to a discouraged worker effect.

Our results do not support the validity of the UIH in high-income economies. This has relevant implications for policy making and macroeconomic models.

This study aims to explore the relationship between tourism and women’s employment in 32 South American and Caribbean countries from 1996 to 2020.

In this paper, both static (fixed effects and random effects) and dynamic panel data models (system and differenced generalized method of moments) are used. In addition to gross domestic product, trade, education and urban population are also considered in this study.

According to the findings, a boost in tourism led to an increase in women’s engagement in the economy and service sectors. This paper also explores the efficiency of alternate methods to deal with various models of women labor force (WLF) involvement in various sectors. Women’s employment opportunities in the service sector expand as a result of tourism, but in the agricultural and industrial sectors, that employment opportunity is reduced.

This study investigated the impact of tourism on WLF participation and found that it had a significant impact. This study, on the other hand, specifically contributed to the tourism sector in some specific study areas, such as tourism and agriculture, service and industry sectors. This study also displays that female participation in South America and the Caribbean countries is increasing and women are shifting away from traditional economic sectors.

This is the pioneering study to discover tourism and female participation in employment in South American and Caribbean countries. The findings of this study have important implications for future studies and policy debates examining the consequence of the tourism industry on WLF.

The digital economy has become a new engine for economic development, promoting the upgrading and transformation of traditional industries as well as fostering emerging industries and forms of business. Nonetheless, how does the digital economy affect innovation? The research objective is to explore the specific impact of the digital economy on innovation output.

This paper innovatively adopts the dynamic panel data model (DPDM) to carry out an empirical study on the impact of the digital economy on innovation output, through the observation of 30 provincial-level administrative regions in China. Furthermore, the paper innovatively analyzes the impact of different dimensions of the digital economy on innovation output and the impact of the digital economy on different dimensions of innovation output.

It is found that the digital economy is conducive to boosting innovation output considering innovation continuity. Specifically, the driving impact of core industries and enterprise application of digital economy on innovation output is more prominent, but the driving impact of infrastructure and personal application on innovation output is not fully played. Meanwhile, the driving impact of the digital economy on the innovation output quality is more significant than that digital economy on the innovation output quantity.

This study employs a DPDM for the first time to investigate the specific impact of the digital economy on innovation output, and contributes to the existing literature on the digital economy and digital economy-driven innovation. The findings offer a comprehensive explanation for the impact of the digital economy on innovation output, which has reference value for the formulation of innovation policies driven by digital economy, thereby providing impetus for the sustained and stable development of China's economy.