Search Results (16)

This study probes the complex interplay between tourism development (TDI), economic growth (GDP), and environmental sustainability, focusing on the ten most influential tourism nations: China, France, Italy, the United Kingdom, Mexico, Germany, Turkey, Spain, the United States, and Russia, covering the time from 1994 to 2023. This study uses feasible generalized least squares (FGLS) and Two-Stage Least Squares (2SLS) together with Driscoll–Kraay (DK) and panel quantile regression (PaQR) to examine the environmental as well as economic effects of TDI combined with trade openness (TOPE), foreign direct investment (FDI), energy prices (EPS), and population density (POPD). All models show that tourism development, indicated by TDI, and economic growth increase carbon emissions, demonstrating these variables’ adverse environmental impact. Energy prices, trade openness, and foreign direct investment lead to decreased emissions because these factors help promote energy-efficient clean technology. Furthermore, GDP growth positively influences TDI, while excessive carbon emissions negatively impact the appeal of tourism. The results indicate the need for sustainable tourism policies and investment in clean energy and green infrastructure, aligned with SDG 9, to foster innovation in energy-efficient practices and infrastructure. The research also supports SDG 13 by advocating climate-resilient tourism models and policies that decouple economic growth from environmental degradation. By adopting various advanced econometric approaches, this study provides strong evidence on the relationship between tourism, the macroeconomy, and environmental results. It offers fresh insights on how to achieve the growth of tourism and climate protection at the world’s top tourist destinations. Full article

This study innovatively develops a multi-objective Markal-Macro model, which simultaneously considers three objectives: minimizing carbon emissions from energy consumption, minimizing carbon emissions from production processes, and maximizing societal welfare. Based on the Cobb–Douglas production function, we construct a production function of carbon emission and use it as a coupling equation of the Markal-Macro model (Markal is the abbreviation of market allocation, and Macro is the abbreviation of macroeconomy). This enables the coupling of the endogenous variables of carbon emissions and those related to maximizing societal welfare. By collecting relevant data on energy consumption, production outputs, and key economic indicators, five different scenarios are established. To enhance the computational efficiency of the simulation, we introduce a Firefly Algorithm into the penalty function method. The objective of our simulation is to explore the optimal carbon peak pathway for China. The results indicate that under the baseline scenario, China can achieve its carbon peak by 2029, with the peak value reaching approximately 12.5 billion tons of carbon dioxide. Finally, based on the simulation results, this study provides specific policy recommendations for China’s carbon peak pathway, addressing aspects such as industrial structure, energy consumption structure, the share of clean energy, economic growth targets, and the growth of emission reduction expenditures, while considering regional five-year plans and regional carbon peak strategies. From the aspect of the practical contributions, this article not only provides a set of methods for policymakers to make the Carbon Peak Implementation Plan but also offers an optimal path to improve the sustainable development for China. Full article

Nowadays, the call for sustainable development is becoming stronger in all countries of the world, and environmental, social, and governance (ESG) performance, as a vivid practice of this concept, has gradually received extensive attention from enterprises and investors. Financial institutions have an important position in the national economy as an important tool for the state to regulate the macroeconomy. Whether ESG performance can improve financial institutions’ efficiency is of key significance for boosting sustainable development. Based on data from China’s listed financial institutions from 2015 to 2021, this study aims to investigate the impact of ESG performance on financial institutions. The robust nonparametric boundary model and fixed-effects model are employed for analysis. The empirical results demonstrate that ESG performance and its sub-indicators of environmental performance and social responsibility performance can significantly enhance financial institutions’ efficiency. In particular, this effect is more pronounced in the securities industry and diversified financial industry, as well as in non-state and small-scale financial institutions. The results remain unchanged after a series of robustness tests. Furthermore, the mechanism tests indicate that ESG performance can enhance financial institutions’ efficiency by reducing downside risk and agency costs. Full article

Transport and macroeconomic development are closely linked. Under the comprehensive management system for China’s rail, road, water, and air transport, there is an urgent need for a comprehensive, timely, and accurate index that reflects the relationship between transport and the macroeconomy, to help the government analyze the current situation of transport, judge the macroeconomic and sustainable transport trends, and make scientific decisions, so as to achieve the carbon emission peak and carbon neutrality goals. This paper innovatively proposed the Transport Development Index (TDI), a new evaluation system with 38 indicators, covering the infrastructure, development scale, efficiency, sustainability, and safety and profitability of the four modes of transport: road, rail, water, and air. The analytic hierarchy process and the entropy weight method were used to determine the weights for the indicators. Yunnan was selected as a case study to calculate the TDI values for 2016 to 2021 and analyze the transport service performance for each year. The study results show that the TDI can be used for analyzing the regional transport services and economic operation status, proving the positive effect of transport development on the macroeconomy or warning of possible risks, and facilitating scientific decision making for sustainable transport development. Full article

Energy prices (EPs) play an imperative role in South Asian Country (SAC) Gross Domestic Product (GDP). This research empirically examines the influence of sustainable energy price shocks (EPSs) on macroeconomic indicators. The study is to forecast the impact of EPS on macroeconomic indicators from 1980 to 2020. The analysis is carried out by employing the Vector Auto-Regression (VAR) approach. Impulse Response Functions (IRFs) results indicate that EPS decreases Gross Domestic Product (GDP). They exist in the short run and the long run. This research study’s overall findings suggest that high EPSs have a negative impact on GDP. The study implies that policymakers should develop, adopt, and initiate some imperatives to control the unanticipated volatility and movements in EP. The study highlights that policy should be designed to prevent fluctuations in sustainable EP and plan conservative energy policies that motivate discovering alternative energy sources to meet increasing energy demand and improve economic growth. Full article

Tax revenue is one of the essential means through which the government controls the macro-economy and plays a vital role in promoting environmental protection and sustainable development. This study takes Chinese panel data from 2004 to 2020 as sample observations, uses the SBM-GML index method to measure industrial green total factor productivity, and then uses econometric methods such as the two-way fixed effects model and instrumental variable method to analyze the impact of an environmental tax on industrial green transformation. It is found that the generalized environmental tax represented by vehicle and vessel tax, resource tax, and urban land use tax has a significant positive effect on industrial green transformation. After a series of robustness tests and the exclusion of endogeneity, this conclusion remains valid. The research shows that credit governance, the agglomeration of producer service, and their co-agglomeration with manufacturing are important adjustment mechanisms. Among them, credit management is special and compulsory, greatly restricting the environmental pollution behavior of industrial enterprises, and encourages enterprises to make green investments and to actively improve production processes. Full article

To improve financial sustainability and promote economic stability, it is important to understand the intricate relationship between finance and macroeconomy. Thus, focusing on financial stress and macroeconomic sectors, this paper investigates macro-financial spillovers in China. First, we develop a high-frequency financial stress index based on eight daily financial indicators to measure the stability of China’s financial markets. Through event identification, we find that China’s Financial Stress Index can effectively reflect the stress situation of China’s financial market. Then, given that the traditional co-frequency method fails to deal with financial stress index and macroeconomic data with different frequencies, we employ the mixed-frequency spillover method to evaluate macro-financial spillovers to examine the connectedness between China’s financial market and the real side of the economy. We find that financial stress is the leading net risk output and primarily affects the loan sector; deterioration of economic conditions can lead to more apparent fluctuations in spillover effects, with spillovers from financial stress to others being the most susceptible; within the sample, the 2015 stock crash, U.S.–China trade friction, and COVID-19 have the most impact on macro-financial spillover effects. In addition, we track the results of different risk events on spillover effects across sectors. Full article

As the supply of commodities forms essential lifelines for modern society, commodity price fluctuations can significantly impact the operation and sustainable development of macroeconomics, production activities, and people’s security and well-being. The commodity trading market also plays a pivotal role in the competition of the international industrial chain and the sustainable development of the industry. The method of bibliometrics was used in this study to trace the development of research on commodity prices, and statistical and co-citation analyses were conducted on selected literature samples. It was found that the research hotspots in this field are concentrated on four aspects: factors influencing commodity prices, the impact of price fluctuations on the macroeconomy, forecasts of commodity prices, and the financialization of commodities. A current commodity price research network centered on oil prices has formed. Future directions in this field, which developed out of oil shock research 40 years ago, can further investigate the impact of factors and the responses that can be made to emergencies on commodity prices, as well as continuing to develop better methods of commodity price forecasting. Full article

Achieving the ambitious climate targets required to limit global warming to 1.5 °C requires a deep transformation of the supply-and-demand side of energy–environmental–economic systems. Recent articles have shown that environmentally sustainable consumer behaviors driven by lifestyle changes can significantly contribute to climate-change mitigation and sustainable development goals. However, lifestyle changes are not adequately captured by scenarios developed with integrated assessment and energy-system models (IAMs/ESMs), which provide limited policy insights. This article conducts a systematic review of the IAM and ESM literature to identify the most important lifestyle changes in current mitigation pathways for the residential and transport sectors, review the employed state-of-the-art modeling approaches and scenario assumptions, and propose improvements to existing methodological frameworks. The review finds that mode shifts towards public transport and active transport modes, shared mobility, and eco-driving have the greatest impact in the transport sector, while actions that reduce space and water-heating requirements and the circular economy are the most effective practices in households. Common modeling approaches lack sophistication as they omit (1) the dynamics and costs of demand-side transitions, (2) the heterogenous responses of different consumer groups, and (3) the structural effects of lifestyles on the macro-economy. New approaches employing innovative methodologies combined with big data collected from users offer new avenues to overcome these challenges and improve the modeling of lifestyle changes in large-scale models. Full article

This paper studies the impact of the COVID-19 pandemic on the sustainability of Chinese economic growth, government debt, and income inequality by constructing a new Keynesian dynamic stochastic general equilibrium (NK-DSGE) model. The choice of monetary policy targets is then analyzed to hedge the impact of the pandemic. We find that: (1) the aggregate demand and labor demand shocks caused by the COVID-19 pandemic posed serious challenges to the sustainable development of the economy and debt, and increased social inequality; (2) when the impact of the pandemic is mainly reflected in the recession in aggregate demand, monetary policy should pay more attention to the target of price stability; (3) when the impact of the pandemic is mainly reflected in a decline in labor demand, monetary policy should focus more on the target of economic growth; (4) when the pandemic has a significant impact on both aggregate demand and labor demand, a monetary policy which focuses more on the target of economic growth is conducive to minimizing welfare losses. Targeted policy implications, such as selecting monetary policy targets according to different manifestations of the impact of the COVID-19 pandemic and placing emphasis on monetary policy tools to stimulate consumption, alleviate unemployment, and alleviate social inequality, are suggested to improve the sustainability of the Chinese economy. Full article

With the help of the time-varying parameter vector autoregression with stochastic volatility (TVP-SV-VAR) model and the Bayesian dynamic conditional correlational autoregressive conditional heteroscedasticity (Bayesian DCC-GARCH) model, this study analyzes the interaction mechanism and dynamic correlation among financial leverage, house price, and consumer expenditure (the survey data are collected from China’s National Bureau of Statistics from January 2000 to December 2019; the data on financial leverage and consumer expenditure are from the Wind economic database, and the price of commercial housing was calculated based on the sales volume and area of commercial housing on the official website of China’s National Bureau of Statistics). Empirical results show that an increase in financial leverage significantly increases house prices and reduces consumer expenditure, that a rise in house prices inhibits financial leverage and weakens consumer expenditure, and that an increase in consumer expenditure raises financial leverage and stimulates a rise in house prices. In addition, house price and consumer expenditure are most relevant, followed by financial leverage and consumer expenditure, and then by financial leverage and house price. Therefore, systematic analysis of dynamic correlation among the three variables has important practical significance for formulating appropriate financial policies to stabilize house prices and promote the growth of consumer expenditures. Specially, financial leverage is an important factor to hold back soaring house prices and shrinking consumer expenditure. Therefore, monetary and macroprudential policies should be used to deal with financial leverage variables in order to achieve a balanced and sustainable development of the macroeconomy in China. Full article

Since the international financial crisis in 2008, to achieve the political goal of financial stability, academic circles, financial industry, and regulatory authorities worldwide have deeply reflected on the current economic regulatory theories and policy adjustment tools through introducing the macroprudential policy. The dynamic provisioning system is a counter-cyclical policy tool in the macro-prudential adjustment framework widely used in the world. This paper uses the binary Gaussian Copula function to combine the measurement method of the default distance in the contingent claims analysis method with the risk warning idea based on the Probit model and proposes the contingent claims analysis (CCA)–Probit–Copula dynamic provisioning model based on nine forward-looking indicators. Based on China’s actual conditions, this model solves present problems faced by the current dynamic provisioning system in China, such as insufficient historical credit data reserves of commercial banks, excessive reliance on subjective judgments, and conflicts with the current accounting system. Moreover, this model can put forward corresponding counter-cyclical provisioning requirements according to the influence degree of macro-cyclical factors to different commercial banks’ own default risk, which not only takes into account the security and liquidity of commercial banks, but also ensures their profitability and competitiveness. Based on the empirical test of historical data from listed commercial banks in China, it proves that the dynamic provisioning requirements proposed in this model can effectively adjust the overall credit scale of the banking industry in counter-cyclical ways, thereby achieving the policy goals of counter-cyclical adjustment under the macro-prudential framework and maintaining the security of China’s financial system and the sustainable development of the macroeconomy. Full article

Air transport provides important transportation services for economic development; meanwhile, its operation requires massive resource inputs into the air transport sector (ATS). In order to ensure sustainable development of air transport industry, improve the utilization efficiency of resources, and coordinate the development of the ATS and the macroeconomy, the operational efficiency of the industry should be evaluated accurately. However, few studies have analyzed the operational performance of ATSs across different regions. This study therefore constructs an index system and applied a three-stage data envelopment analysis (DEA) approach, which considers various regional environmental factors and statistical noise, to evaluate regional ATS operational performance. China’s 30 provincial ATS operational efficiencies in year 2017 are empirically evaluated using the proposed model. The empirical results show that different levels of environmental factors, such as regional GDP, openness, technical markets, technological development, and consumption, pose various influences on provincial ATS operational efficiency in China. Operational performance evaluation results eliminating these environmental effects in the third stage show considerable differences with that stage 1 results. In addition, corresponding development strategy implications in different provinces and regions are put forward according to the evaluation results. Full article

To address climate change, the carbon emission trading scheme has become one of the main measures to achieve emission reduction goals. One of the core problems in constructing the carbon emissions trading market is determining carbon emissions trading prices. The scientific nature of carbon emissions pricing determines the effectiveness of market regulation. Research on the influencing factors and heterogeneous tail distribution of carbon prices can increase the accuracy of carbon pricing, which is particularly important for the development of the carbon emissions trading market. The current studies have some limitations and lack heterogeneous tail description. We employ the arbitrage pricing theory-standardized standard asymmetric exponential power distribution model to analyze China’s regional carbon emissions trading price and use a genetic algorithm to solve linear programming. The results confirm the theoretical results and efficiency of the proposed algorithm. First, the new model can capture the skewness, fat-tailed distribution, and asymmetric effects of China’s regional carbon emissions trading price. Second, the macroeconomy, similar products, energy price, and exchange rate influence the carbon price fluctuation; investors’ behavior plays an important role in the heterogeneous tail distribution of carbon price. The findings provide references for the government to take appropriate measures to promote carbon emission reduction and improve the effectiveness of China’s carbon market. Therefore, our findings can help enhance emission reduction and achieve sustainable development of a low-carbon environment. Full article

In countries that have developed under the current market economy, inequalities in income distribution tend to increase with three different trends, i.e., high (United States, United Kingdom, Japan), low (North Europe countries), and medium Gini coefficient levels. On the other hand, the relationship between income distribution and social welfare is generally a difficult problem to solve in economics. So, this paper discusses the impact of income distribution on the macroeconomy, limiting the scope to consistency with long-term economic growth. We attempt to answer these economic policy issues by simulation using an agent-based model based on replicator dynamics. As a result of the simulation in this paper, in general, in countries with the high marginal propensity to consume, long-term growth can be maintained by inducing equality in income distribution. On the other hand, a mature country with a low marginal propensity to consume can sustain not so high but stable growth despite increasing inequality in income distribution. According to simulation results based on OECD (Organisation for Economic Co-operation and Development) data, in the former UK, US, and Japan, the lower the Gini coefficient is, the higher the growth potential is, while in the latter Norway and Luxembourg, relatively stable growth is maintained even if the Gini coefficient increases. Full article