Reduction of carbon dioxide (CO₂) emissions is one of the biggest challenges for global sustainable development, in which economic growth characterized by industrialization plays a formidable role. We innovatively adopted the input and output (I-O) table of 41 countries released by World I-O Database to determine the industrial structure change and analyze its impact on CO₂ emission evolution by developing a cross-country panel model. The empirical results show that industrial structure change has a significantly negative effect on CO₂ emissions; to be specific, 0.1 unit increase in the linkage of manufacturing sector and service sector will lead to a decrease of 0.94 metric tons per capita CO₂ emissions, indicating that upgrading industrial structure contributes to carbon mitigation and sustainable development. Further, urbanization, technology and trade openness have significantly negative impact on CO₂ emissions, while economy growth and energy use take positive impacts. In particular, a 1% increase in per capita income will contribute to an increase of 8.6 metric tons per capita CO₂ emissions. However, the effect of industrial structure on environment degradation is moderated by technology level. These findings fill the gaps of previous literature and provide valuable references for effective policies to mitigate CO₂ emissions and achieve sustainable development.

In recent years, the population growth rate has been gradually declining in China. As the population problem becomes increasingly significant, the accurate prediction of population development trends has become a top priority, used to facilitate national scientific planning and effective decision making. Based on historical data spanning a period of 20 years (1999–2018), this article presents predictions of the populations of 210 prefecture-level cities using the Malthusian model, Unary linear regression model, Logistic model, and Gray prediction model. Furthermore, because the gray prediction model exhibited the highest degree of accuracy in formulating predictions, this study uses the model to predict and analyze future population development trends. The results reveal that the population gap between cities is gradually widening, and the total urban population shows a pattern of rising in middle-tier cities (second-tier cities and third-tier cities) and declining in high-tier cities (first-tier cities and new first-tier cities) and low-tier cities (fourth-tier cities and fifth-tier cities). From the viewpoint of geographical distribution, the population growth rate is basically balanced between the northern part and the southern part of China. In addition, the population growth of the high-tier cities is gradually slowing while the low-tier cities are experiencing a negative growth of population, but middle-tier cities are experiencing skyrocketing population growth. From the viewpoint of regional development, although the development of regional integration has been strengthened over the years, the radiative driving effect of large urban agglomerations and metropolitan areas is relatively limited.

Since the 2008 global financial crisis, the study of real estate risks, bubbles and exuberance has attracted a lot of attention, which is of great significance to the government, enterprises and individuals. This paper carries out a statistical and bibliometric analysis of 739 studies over the past 20 years in this field, and identifies the theoretical basis, research topics and latest research hotspots in this field. Through the construction of a co-citation network and co-word network, we find that the current studies have commonly employed basic economic theories or econometric methods to detect and quantify real estate bubbles. Explosive bubbles and financialization of real estate are frontier hotspots that have gained much popularity. Based on the comparative study, we further discover that American scholars have paid more attention to topics related to the financial crisis, while Chinese scholars have studied topics more related to real estate market policies. Finally, this paper proposes several important research directions in this field for the future.

Environmental regulation affects the financial performance of firms, while the findings are mixed. This paper quantitatively analyzes the current and lagged effect of environmental regulation (ER) on financial performance (FP), based on the data of 361 highly polluting A-shares firms and 936 mildly polluting A-shares firms in China. It is proved that ER exerts a negative effect on the FP of polluting firms in the short term and a positive effect in the long term, which unifies the ‘Porter Hypothesis’ (PH) and the ‘Costly Regulation Hypothesis’ (CRH) on the temporal dimension. Mechanism analysis reveals that ER negatively affects current FP of highly polluting firms by improving their green innovation investment. In addition, ER has a significant positive lagged effect on the FP of polluting firms by improving their operating efficiency, rather than reducing production costs. Furthermore, we find that ER significantly improves the FP of highly polluting firms, especially state-owned firms, as opposed to mildly polluting firms and privately-owned firms. The conclusions imply that government should make subsidies for green firms or firms going green, and firms should pay more attention to green innovation investment and green development.