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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.

Population growth has remained a key issue facing developing economies in the world. While developed countries are experiencing diminished or negative population growth, many countries in sub-Saharan Africa including Nigeria are having population growth above the economic growth rate. With the deadline for the sustainable development goals approaching, attention is increasingly being focused on population growth and human capital development. Extant literature focused on population growth, human resource utilization and economic growth but this study aims to examine the effect of population growth on human resource utilization.

Using secondary data for the period 1990-2018, the study conducted unit root test and co-integration analyses to determine the stationarity and correlation in the long-run in the variables. The study used the error correction model to ascertain the speed at which shocks can be corrected in the long-run. Granger causality test was also carried out to ascertain the direction of causality among the variables.

The empirical results revealed that population growth has a negative and significant effect on human resource utilization. The study also revealed that unidirectional causality runs from employment rate to population growth rate and a unidirectional causality runs from employment growth rate to expected years of schooling. The Nigerian Government needs to not only control population growth but also focus on the quality of education.

The paper provides insights into the relationship between population growth and human capital utilization in Nigeria focusing on the 1986-2018 period.

The study explores the relationship among economic growth, population growth, gross savings and energy consumption over the period 1987– 2017.

The autoregressive distributed lag (ARDL) bounds test approach by Pesaran et al. (2001) was employed to investigate variables for the study.

In the key findings, both gross savings and population growth negatively affect economic growth. However, energy consumption has positive impact on economic growth.

These findings call for policy portfolios to address the impacts of gross savings and population growth on economic development. In particular, the financial sector needs to be revamped to be more efficient in channeling funds from the surplus units to the deficit units. It is recommended that investment be made in financial and technological innovation to provide efficient access to credits and other financial products even though individual savings may not move with economic growth.

Many studies have explored the nexus between savings and economic growth without considering population growth and energy consumption. In this study, the relationship among savings, economic growth, population growth and energy consumption provide additional knowledge in policy formulation.

This paper aims to test three hypotheses in city growth literature documenting the poverty reduction observed in Brazil and exploring a rich spatial dataset for 5,564 Brazilian cities observed between 1991 and 2010. The large sample and the author's improved econometric methods allows one to better understand and measure how important income growth is for poverty reduction, the patterns of agglomeration and population growth in all Brazilian cities.

The author identifies literature gaps and use a sizeable spatial dataset for 5,564 Brazilian cities observed in 1991, 2000 and 2010 applying instrumental variables methods. The bias-corrected accelerated bootstrap percentile interval supports the author's point estimates.

This manuscript finds that Brazilian data for cities does not support Gibrat's law, raising the scope for urban planning and associated policies. Second, economic growth on a sustainable basis is still a vital source of poverty reduction (The author estimates the poverty elasticity at four percentage points). Lastly, agglomeration effects positively affect the city's productivity, while negative externalities underlie the city's development patterns.

Data for cities in Brazil possess unique characteristics such as spatial autocorrelation and endogeneity. Applying proper methods to find more reliable answers to the above three questions is a desirable procedure that must be encouraged. As the author points out in the manuscript, dealing with endogenous regressors in regional economics is still a developing matter that regional scientists could more generally apply to many regional issues.

Poverty alleviation has been a major theme of China's modernization process since the founding of New China. This paper points out that China's poverty alleviation process presents three stylized facts: “Miraculous” achievements of poverty alleviation have been made on a global scale; the poverty alleviation achievements mainly occurred in the high growth stage after reform and opening up; the poverty alleviation process is accompanied by the structural transformation of the urban–rural dual economy.

Therefore, a logically consistent analytical framework should form among the structural transformation of the dual economy, economic growth and the achievements in poverty alleviation. In logical deduction, the structural transformation of the dual economy affects rural poverty alleviation through the effects of labor reallocation, agricultural productivity improvement, demographic change and fiscal resource allocation.

The first two refer to economic growth, and the latter two are alleviation policies. The combination of economic growth and poverty alleviation policies is the main cause for poverty alleviation performance. China's empirical evidence can support the four effects by which the structural transformation of the dual economy affects poverty alleviation.

China's socialist system and its economic system transformation after reform and opening up provide an institutional basis for the effects to come into play. After 2020, China's poverty alleviation strategies will enter the “second-half” phase, namely, the phase of solving the problems of relative poverty in urban and rural areas by adopting conventional methods and establishing long-term mechanisms. This requires the facilitation of the reconnection between poverty alleviation strategies and the structural transformation of the dual economy in terms of development ideas and policy directions.

The relationship between man and nature varies with different stages of the development of human society. The destructive consequences brought about in the early stage of industrialization sparked serious concerns about ecological and environmental issues.

The worldwide controversy aroused by The Limits to Growth published in 1972 made people realize that the carrying capacity of the ecosystem was limited, as were the resources. In the long run, scientific and technological progress can constantly discover new energy and resources.

However, in every specific stage of human society, the energy and resources crises are always a severe challenge that human beings should face. It is the core contents of sustainable development to change the old economic growth model and explore a new economic growth model.

The relationship between man and nature is one of the most fundamental relationships in human society and economic development. How to deal with it is also one of the most fundamental issues in human society and economic development. From the perspective of the historical process of human society, the relationship has roughly gone through the following stages.

The economic shock posed by the current COVID-19 outbreak brought out a worldwide public health emergency with a close relationship between the industrial marketing practices, the health level of society and its economic development. The purpose of this study is to analyse the industrial dynamics in health care and their impact on economic growth and health status.

To empirically investigate the relationship between growth and health, the authors use a data set drawn from 29 selected Organisation for Economic Co-operation and Development (OECD) countries over the period 2000 and 2019. Using panel regressions, the authors investigate the impact of the health-care industry measured in terms of health status, health expenditure, sales on pharmaceutical products, the number of persons working in health care and the coverage by private health insurances. Fixed effect and random effect regressions are used to estimate this model.

Overall, the results are suggestive of a nexus between the industrial marketing dynamics of health-care context and economic growth – both interacting and improving each other. As the quality of the health-care market enhances, the economy grows richer and the health status of the population improves considerably.

To support health-care markets in OECD countries, health policymakers need to formulate a long-term industrial health policy that addresses all the social and individual determinants of health.

To the best of the knowledge, this is the first study to provide a better understanding of the relationship between health-care industrial dynamics and economic growth in OECD countries along different dimensions.

The intended nationally determined contributions (INDCs) is a major outcome of the Paris Agreement on international cooperation to reduce emissions, and is likely to be the future scenario for carbon emissions. This paper aims to obtain the fine spatial pattern of carbon emissions in 2030, identify hot spots and analyze changes of carbon emissions with a spatial grid method.

Based on the integrated quantified INDCs of each economy in 2030, the authors predict the population density pattern in 2030 by using the statistics of current population density, natural growth rates and differences in population growth resulting from urbanization within countries. Then the authors regard population density as a comprehensive socioeconomic indicator for the top-bottom allocation of the INDC data to a 0.1° × 0.1° grid. Then, the grid spatial pattern of carbon emissions in 2030 is compared with that in 2016.

Under the unconditional and conditional scenarios, the global carbon emission grid values in 2030 will be within [0, 59,200.911] ktCO₂ and [0, 51,800.942] ktCO_2, respectively; eastern China, northern India, Western Europe and North America will continue to be the major emitters; grid carbon emissions will increase in most parts of the world compared to 2016, especially in densely populated areas.

While many studies have explored the overall global carbon emissions or warming under the INDC scenario, attention to spatial details is also required to help us make better emissions attributions and policy decisions from the perspective of the grid unit rather than the administrative unit.