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This chapter analyzes how the macro-environment determines corporate dividend decisions. First, political factors including political uncertainty, economic policy uncertainty, political corruption, and democracy may have two opposite effects on dividend decisions. For example, firms learn democratic practices to improve their corporate governance, but dividend policy may be the outcome of strong corporate governance or the substitute for poor corporate governance. Second, firms in countries of high national income, low inflation, and highly developed stock markets tend to pay more dividends. A monetary restriction (expansion) reduces (increases) dividend payments, as economic shocks like financial crises and the COVID-19 may negatively affect corporate dividend policy through higher external financial constraint, economic uncertainty, and agency costs. On the other hand, they may positively influence corporate dividend policy through agency costs of debt, shareholders' bird-in-hand motive, substitution of weak corporate governance, and signaling motive. Third, social factors including national culture, religion, and language affect dividend decisions since they govern both managers' and shareholders' views and behaviors. Fourth, firms tend to reduce their dividends when they face stronger pressure to reduce pollution, produce environment-friendly products, or follow a green policy. Finally, firms have high levels of dividends when shareholders are strongly protected by laws. However, firms tend to pay more dividends in countries of weak creditor rights since dividend payments are a substitute for poor legal protection of creditors. Furthermore, corporate dividend policy changes when tax laws change the comparative tax rates on dividends and capital gains.

One of the main sustainable development goals (SDGs) highlights gender equality. Gender inequality is usually measured through the Gender Inequality Index (GII) based on three main dimensions, namely, (1) economy, (2) social empowerment, and (3) reproductive health, as demonstrated by death ratio and fertility rates. The aim is to formulate a model for women’s empowerment towards achieving the SDGs. Specifically, the objectives include (1) comparing gender inequality levels among ASEAN countries and (2) analyzing regulations on gender and development perspectives in Indonesia. This research used the mixed method and panel data, namely analyzing gender inequality.

The results show that, in the common effect model, all variables affected the participation of women in the workforce. The analysis shows that the enactment of laws and regulations on gender mainstreaming has an impact on reducing gender inequality and increasing various indicators of gender mainstreaming, especially in increasing the participation of women in the workforce.

Factor investment is booming in global asset management, especially environmental, social, and governance (ESG), dividend yield, and volatility factors. In this chapter, we use data from the US securities market from 2003 to 2019 to predict dividends and volatility factors through machine learning and historical data–based methods. After that, we utilize particle swarm optimization to construct the Markowitz portfolio with limits on the number of assets and weight restrictions. The empirical results show that that the prediction ability using XGBoost is superior to the historical factor investment method. Moreover, the investment performance of our portfolio with ESG, high-yield, and low-volatility factors outperforms baseline methods, especially the S&P 500 ETF.

The comparison between economic growth and the character of monetary policy is one of the most frequently studied issues in policymaking. However, the number of studies incorporating a dynamic time warping approach to analyse the similarity of macroeconomic variables is relatively small.

The study aims at assessing the mutual similarity among various variables representing the financial sector (including the monetary policy by the central bank) and the real sector (e.g. economic growth, industrial production, household consumption expenditure), as well as cross-similarity between both sectors.

The analysis is based on the dynamic time warping (DTW) method, which allows for capturing various dimensions of changes of considered variables. This method is almost non-existent in the literature to compare financial and economic time series. The application of this method constitutes the main area of value added of the research. The analysis includes five variables representing the financial sector and five from the real sector. The study covers four countries: Czechia, Hungary, Poland and Romania and the 2010–2022 period (quarterly data).

The results show that variables representing the financial sector, including those reflecting monetary policy, are weakly correlated with each other, whereas the variables representing the real economy have a solid mutual similarity. As regards individual variables, for example, GDP fluctuations show relatively substantial similarity to ROE fluctuations – especially in Czechia and Hungary. In the case of Hungary and Romania, CAR fluctuations are consistent with GDP fluctuations. In the case of Poland and Hungary, there is a relatively strong similarity between the economy's monetisation and economic growth. Comparing the individual countries, two clusters of countries can be identified. One cluster includes Poland and Czechia, while another covers Hungary and Romania.

This chapter analyzes the process of surplus generation in Latin America based on the Penn World Tables, also with a comparison with the United States. The reference period is 1950–2019, revealing long-run evolution as well as certain differences between a State-driven industrialization strategy, the turn toward neoliberalism beginning in the 1980s, and a neo-developmentalist period in the twenty-first century. The research shows a steep decline in the rate of profit in Latin America until the early 1990s, with stabilization thereafter but without reversal of the downward trend. However, the turning point in terms of capital accumulation, surplus generation, and productivity indicators occurred in the early 1980s. In addition, divergence vis-à-vis the United States has been growing in the capacity to generate surplus, labor productivity, and GDP per capita.

Reducing and eradicating global poverty features as a primary objective of the sustainable development goals (SDGs) for 2030. Since over half a century, the World Bank has disbursed loans amounting to billions of US dollars to assist countries to alleviate poverty. However, the path to zero poverty is often impaired with conflicts, social unrest and, most commonly, economic crisis. In this chapter, we examine the inter-linkage between various forms of economic crises, poverty and government expenditure for a set of 127 countries from 1985 to 2010. Using a simultaneous equation model, we test the direct effect of a financial crisis on the incidence of poverty and its indirect effect through the immediate decrease in government expenditure. Contrary to previous studies, our findings suggest that crises have no direct impact on poverty. We find a similar effect for currency, inflation and debt crisis. However, there is evidence that poverty increases indirectly due to a fall in government expenditure. Our results are robust for non-advanced and advanced economies and alternate estimation technique using factor analysis.

Although the phenomenon of the corporate social responsibility disclosure (CSRD) has derived the interest of several scholars, in recent years, the comparative studies between Islamic banks (IBs) regarding CSRD quantity versus quality have not been the subject matter of studies till now. In this perspective, this chapter aims to investigate the importance given by IBs to the quality and quantity disclosure of CSR. Moreover, it seeks to explore the impact of CSRD quality and quantity on the IBs' financial performance (FP). To meet these objectives, we used a sample of 59 IBs from 2011 to 2016 in the Arab world and non-Arab world. Then, by adopting the content analysis approach, the authors constructed two CSRD indexes (quality and quantity). The empirical results indicated that IBs give more importance to the qualitative disclosure than the quantitative. Our findings will be very helpful for the policymakers and the managers of IBs because maintaining a good CSRD policy increases the capacity of IBs to deal with possible reputational events, thus protecting their profits and financial results. As far as the comparison between the Arabian and non-Arabian IBs, based on financial reports and Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) governance standard N°7 is concerned, our study is among the first studies that provides two new CSRD indexes (quantity and quality).