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This chapter provides a comprehensive exploration of global demographic trends and challenges, specifically focusing on Asian countries and the demographic landscape of Bangladesh. This chapter highlights the implications of rapid population growth, aging populations, and urbanization, analyzing their socioeconomic impacts on education, healthcare, and employment. By contextualizing these trends within the broader framework of sustainable development, this chapter sets the stage for understanding the intricate relationship between population dynamics and the empowerment of marginalized communities through family planning strategies.

Our paper studies a central issue with a long history in economics: the relationship between population and economic growth. We analyze the joint dynamics of economic and demographic growth in 111 countries during the period 1960–2019.

Using the concept of economic regime, the paper introduces the notion of distance between the dynamical paths of different countries. Then, a minimal spanning tree (MST) and a hierarchical tree (HT) are constructed to detect groups of countries sharing similar dynamic performance.

The methodology confirms the existence of three country clubs, each of which exhibits a different dynamic behavior pattern. The analysis also shows that the clusters clearly differ with respect to the evolution of other fundamental variables not previously considered [gross domestic product (GDP) per capita, human capital and life expectancy, among others].

Our results indirectly suggest the existence of dynamic interdependence in the trajectories of economic growth and population change between countries. It also provides evidence against single-model approaches to explain the interdependence between demographic change and economic growth.

We introduce a methodology that allows for a model-free topological and hierarchical description of the interplay between economic growth and population.

The purpose of this study is to analyze the horizontal expansion of Burayu Town between 1990 and 2020. The study typically acts as a baseline for integrated spatial planning in small- and medium-sized towns, which will help to plan sustainable utilization of land.

Landsat5-TM, Landsat7 ETM+, Landsat5 TM and Landsat8 OLI were used in the study, along with other auxiliary data. The LULC map classifications were generated using the Random Forest Package from the Comprehensive R Archive Network. Post-classification, spatial metrics, and per capita land consumption rate were used to understand the manner and rate of expansion of Burayu Town. Focus group discussions and key informant interviews were also used to validate land use classes through triangulation.

The study found that the built-up area was the most dynamic LULC category (85.1%) as it increased by over 4,000 ha between 1990 and 2020. Furthermore, population increase did not result in density increase as per capita land consumption increased from 0.024 to 0.040 during the same period.

As a result of financial limitations, there were no high-resolution satellite images available, making it challenging to pinpoint the truth as it is on the ground. Including senior citizens in the study region allowed this study to overcome these restrictions and detect every type of land use and cover.

Data on urban growth are useful for planning land uses, estimating growth rates and advising the government on how best to use land. This can be achieved by monitoring and reviewing development plans using satellite imaging data and GIS tools.

The use of Random Forest for image classification and the employment of local knowledge to validate the accuracy of land cover classification is a novel approach to properly customize remote sensing applications.

This study aims to investigate the relationship between digital financial inclusion and economic growth in specific Asian countries, emphasizing the exploration of how digital financial inclusion dynamics impact gross domestic per capita income.

The study creates a digital financial inclusion composite index (DFII) by incorporating essential metrics from the Global Findex report. Economic growth is measured using Gross Domestic Product per capita income in its natural logarithmic form (LnPCI), with three control variables– employment-to-population ratio; population growth and inflation. The analysis utilizes a fixed-effect dummy variable model to examine the relationship, considering unobserved country-specific heterogeneity. 30 Asian countries have been selected for the study for the periods 2014, 2017 and 2021 based on their availability, as outlined in Table 4.

The research revealed a robust positive correlation between the Digital Financial Inclusion Index (DFII) and logarithmic GDP per capita income (LnPCI), indicating higher per capita income with enhanced digital financial inclusion. Employment and population exhibited minimal influence, whereas inflation had a notable negative effect on per capita income. Population growth showed a limited impact. The model demonstrated a high explanatory power for the dependent variable (high R-squared), and the residuals displayed low autocorrelation (Durbin–Watson of 1.96).

This study adds to the existing literature by examining the intricate connection between digital financial inclusion (DFI) and economic growth in 30 Asian countries, employing a comprehensive composite index for analysis.

The article aims to identify the determinants of the urbanization process given the magnitude of this phenomenon and also its economic, social and environmental implications and pressure on public authorities to find viable solutions in the context of sustainable development.

The research is based on regression analysis with urbanization growth being the dependent variable and enrollment in higher education, GDP, value added by industry and female labor force as independent variables.

The main factors that favor urbanization are the increase in population, industry value-added and the female labor force. Urbanization is an objective that must be pursued differently by public authorities in developed and developing countries, given the different realities they face-population growth in developing countries, and population aging and international migration in developed countries.

The present research has limitations generated by the selection of independent variables, which is why in future directions, the research will consider the use of other indicators such as the number of graduates, exports as percent of GDP or migrations as a percentage of the total population. Given the complexity of the phenomenon of urbanization, future research will focus on groups of countries as they resulted from the clustering made by this article.

The impact of higher education on urbanization is low, which is why the intensification of partnerships between municipal authorities and universities could be a solution that ensures not only the transfer of knowledge from academia to the public sector but also from entrepreneurs increasingly aware of the importance of promoting SDGs for urban development in the context of the challenges posed by global warming. The involvement of women in the labor market is essential for the intensification of the urbanization process. The increasing presence of women in the labor market generates an increase in the income of families, an increase in the level of education and an intensification of national and international migration. The research findings can be used by policy and decision-makers to develop appropriate urbanization and education policies and strategies.

The existence of inhomogeneous clusters is noticeable, which demonstrates the complexity of the urbanization phenomenon that is present in all countries around the world, but under the influence of different factors such as the export of natural resources (mainly oil) or the intensification of industrial activity. Taking into account the variables used, this study stands out in the multitude of articles published in the international mainstream.

Few empirical studies examined the relationship between life expectancy and income in India. This study aims to examine the impact of life expectancy on economic growth in India by incorporating all the major states of India.

This study is based on secondary data and includes 16 major states of India covering the periods 2000–2014. The author used panel fixed effect model (FEM) to examine the impact of life expectancy on economic growth.

Empirical analysis revealed a positive trend in life expectancy in India. In association with life expectancy, the author found continuous growth in the elderly population. The result of the FEM shows that gains in life expectancy positively affect economic growth in India. The empirical findings do not support any negative impact of life expectancy gains on economic growth.

This study is the outcome of the independent and original research work of the authors and contributes significantly to the literature on the demography–economic relationship. The findings of this study help the author to understand that life expectancy gain is in no way a constraint, rather the skill and experience of the workforce are crucial to determining economic growth.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2022-0422.

The purpose of this paper is to investigate sustainable green economy in sub-Saharan African (SSA) countries over the period 1990–2019 using a quantile regression approach, considering the nexus between urbanization, economic growth, renewable energy, trade and carbon dioxide (CO₂) emissions.

The study used a dynamic panel quantile regression to investigate the conditional distribution of CO₂ emissions along the turn-points of urbanization, economic growth, renewable energy, trade and the regressors via quadratic modeling specifications.

The main findings are established as follows. There is strong evidence of the Kuznets curve in the nexus between urbanization, economic growth, renewable energy, trade and CO₂ emissions, respectively. Second, urbanization thresholds that should not be exceeded for sustainability to reduce CO₂ emissions are 0.21%, and 2.70% for the 20th and 75th quantiles of the CO₂ emissions distribution. Third, growth thresholds of 3.64%, 3.84%, 4.01%, 4.36% and 5.87% across the quantiles of the CO₂ emissions distribution. Fourth, energy thresholds of 3.64%, 3.61%, 3.70%, 4.02% and 4.34% across the quantiles of the CO₂ emissions distribution. Fifth, trade thresholds of 3.37% and 4.47% for the 20th and median quantiles of the CO₂ emissions distribution, respectively.

The empirical shreds of evidence offer policy implications in such that building sustainable development and environment requires maintaining the critical mass, not beyond those insightful thresholds to achieving sustainable development and environmentally friendly SSA countries.

Sustainable cities and communities in an era of economic recovery path COVID-19 mitigate greenhouse gas. The policy relevance is of particular concern to the sustainable development goals.

The study is novel considering the extant literature by providing policymakers with avoidable thresholds for policy formulations and implementations in the nexus between urbanization, economic growth, renewable energy and trade openness.

Under the circumstances of the accelerated technological advance and the overlapping of various global crises in the recent years, one of the main strategic priorities of the European Union in medium and long terms consists of building resilient regional and local communities which implies the aim to protect citizens against the impact of climate changes. Considering the essential role of the human capital in this endeavor, this chapter aims to investigate the relationship between human resources and economic development focusing a SWOT analysis in the case of Romania taking into account recent developments and trends of the European and global labor market related to various aspects induced by the green transition. The analysis of the structural demo-economic characteristics of Romania’s population revealed a decline of the total population, against the background of negative demographic and net migration, the increase in the average and median age of the total population, the rise in demographic and economic dependency ratios representing serious challenges for the development strategy on short, medium and long terms. To these, increasing quantitative and qualitative shortages in the labor market are added, which complicate the advancement of the green transition in Romania. In the conclusions of this chapter, strategic milestones on policies and measures in the short, medium and long terms at macroeconomic and labor market levels are proposed.

The current chapter proposes a theoretical framework to assess the sustainability of economic growth in the Gulf Cooperation Council (GCC) States. The authors integrate insights from endogenous growth models and consider the unique socioeconomic characteristics of the GCC region to provide a comprehensive and tailored approach to understanding the determinants of economic growth and formulating effective policy measures to foster sustainable development and growth. This chapter highlights the environmental challenges faced by GCC; based on this, the authors suggested indicators to construct a theoretical framework (Economic Growth, Climatic Indicators, Energy Indicators, Social Indicators, and Economic Resources Indicators). The authors propose that policymakers and researchers in GCC States should take these factors into account when devising policies or conducting research aimed at fostering sustainable economic growth. Overall, this chapter presents significant insights for policymakers, researchers, and stakeholders involved in promoting the sustainable economic advancement of the GCC States.