Empirical Study on the Relationship between Economic Growth and Carbon Emissions in Resource-dependent Cities Based on Vector Autoregression Model

China: ShengdaTech – nanoparticulate calcium carbonate

Scientific analysis of carbon emission characteristics is a key link for precise policy implementation and orderly achievement of Carbon Peak and Carbon Neutrality. Taking 21 prefecture level cities in Guangdong Province as research objects, data including their economic activity, energy consumption, and population distribution from 2013 to 2022 was collected. First, the carbon emission accounting method was used to analyze the time changes and spatial distribution characteristics of carbon emissions in the past decade. Second, the principal component analysis and K-means method was used to reduce the dimensionality and cluster division for Guangdong urban characteristics. Third, the Generalized Schur Decomposition model was applied to analyze the influencing factors. Furthermore, carbon reduction strategies for four typical cities in Guangdong Province were proposed. The results showed that： ① From 2013 to 2022, the total carbon emissions in Guangdong Province continued to increase and showed a significant regional imbalance in its spatial distribution. The carbon emissions contribution in the Pearl River Delta region was as high as 42.50%, whereas that in northern Guangdong was the lowest. ② Each city in Guangdong Province performed differently in green development, economic development, and industrial development. All 21 cities could be broadly divided into four categories, namely, Demonstration City, Resource-dependent City, Traditional Industrial City, and Emission-reducing City, accounting for approximately 14.29%, 28.57%, 19.05%, and 38.09%, respectively. ③ Economic activities were the common driving factors for carbon emissions in all cities, whereas energy consumption and lifestyle were the core driving factors for carbon emissions in resource-dependent cities and traditional industrial cities. After the proposal of Carbon Peak and Carbon Neutrality, energy composition became a key driving force for demonstration cities and emission-reducing cities.

Industrial symbiosis as a countermeasure for resource dependent city: a case study of Guiyang, China

Does the transformation of resource-dependent cities promote the realization of the carbon-peaking goal? An analysis based on typical resource-dependent city clusters in China

Over the past 40years since China's reform and opening up, the industrial structure has undergone tremendous changes. The rapid development of the economy has been accompanied by a surge in carbon emissions. How to achieve a win-win situation for economic growth and carbon emissions reduction has aroused widespread concern from all sectors of society. Here, this paper discusses the dynamic relationship of industrial structure upgrading, economic growth, and carbon emission reduction. Results show that there is a long-term equilibrium relationship among industrial structure upgrading, economic growth, and carbon emissions. In the short term, when the three variables deviate from the long-term equilibrium state, the non-equilibrium state will be pulled back to equilibrium with the adjustment strength of - 0.0633, - 0.0097, and 0.0013. Carbon emission reduction promotes industrial structure upgrading. Industrial structure upgrading has a greater positive impact on economic growth. Industrial structure upgrading and economic growth have a negative impact on carbon emissions, thereby promoting emission reduction. And at the 10% significance level, there is a one-way Granger causality from carbon emissions to industrial structure upgrading, economic growth can cause one-way changes in carbon emissions, and industrial structure upgrading is a one-way Granger cause of economic growth. Finally, several carbon emission reduction policies are proposed promote industrial restructuring and sustainable economic development.

Urban carbon emissions are one of the most important areas contributing to the growth of carbon emissions, and resource-dependent cities with natural resource extraction and processing as their leading industries tend to have higher carbon emissions. Ordos is the city with the highest coal production in China, and its economic development is dominated by coal, oil and gas, and other resource extraction and processing industries, with industrial activities making a large contribution to carbon emissions. At the same time, Ordos has undergone rapid industrialization in recent years, but still faces the problem of environmental pollution, epitomizing a typical resource-dependent city in China. Therefore, this paper takes Ordos as an example and uses the Generalized Divisa Index Method (GDIM) to study the drivers of industrial carbon emissions in Ordos from 2005-2020, a typical resource-dependent city in China, and further analyzes are conducted in relation to the three phases of development. Based on the key drivers, the Monte Carlo method is used to forecast industrial carbon emissions from 2021 to 2030. The results show that the most important factors driving the growth of industrial carbon emissions are the scale of industrial output and industrial energy consumption, while the intensity of industrial energy investment is the most important factor mitigating industrial carbon emissions, and that energy efficiency and carbon intensity of energy consumption can also mitigate carbon emissions after economic transformation. At the same time, investment is the factor with the greatest potential for optimization on the path to emissions reduction.

Realizing the coordinated progress of carbon reduction and economic growth is an inevitable choice for China to promote low-carbon transformation and development. This article is based on panel data from 282 prefecture level and above cities from 2006 to 2022. Using the PVAR model to clarify the interaction between carbon emissions and economic growth， the modified Gruber Lloyd index is used to measure the degree of synergy between the two. ArcGIS and other tools are used to visualize the temporal characteristics and spatial distribution of the coordinated development of urban carbon emission reduction and economic growth. Kernel density estimation method is used to reveal its distribution dynamics and evolution rules， and the Dagum Gini coefficient and its subgroup decomposition method are used to explore the overall differences and their sources. The results indicated that： ① From the perspective of interactive relationships， both carbon emissions and economic growth had self-reinforcing mechanisms， but their cumulative effects gradually weakened. The impact of economic growth on carbon emissions conformed to the inverted "U" shape of the Environmental Kuznets Curve， while carbon emissions exhibited long-term negative effects on economic growth. In terms of spatiotemporal characteristics， the synergy level between urban carbon reduction and economic growth showed a significant upward trend， with an increase of 24.17% during the investigation period. The spatial distribution characteristics gradually evolved into a gradient distribution of "low in the west and high in the east." In terms of dynamic evolution， the core density curve of the synergy level between carbon emission reduction and economic growth in cities across the country and the four major regions generally shifted to the right， with the main peak height first increasing and then decreasing and the width widening. The phenomenon of a right tail was obvious， mainly in the form of a single peak， indicating that the synergy level in various regions improved. However， the overall differences within the regions widened， and the degree of dispersion intensified. There has not yet been a significant multipolar differentiation phenomenon. From the perspective of regional differences， the overall Gini coefficient of the country showed a slight fluctuation and upward trend， indicating that the differences in carbon reduction and economic growth synergy among Chinese cities expanded， but at the same time， they also maintained a relative balance. The overall differences within and between the four major regions also increased， but the dynamic characteristics of various regions were significantly different， and inter-regional differences constituted the main source of overall differences. The research conclusion is beneficial for each region to clarify its own advantages and shortcomings and to achieve low-carbon transformation and development according to local conditions.

For a specific small-scale region with abundant resources, its copious resources tend to dictate the basic direction of its development, and may subsequently give rise to an industrial structure centered on the advantageous resources. This can give rise to an economic structure that lacks diversity, causing the economic development in the entire local region to fall into the dilemma of the resource curse. The present study conducts a case study from the perspective of small-scale regions, incorporating various types of resource-dependent cities in China, including Qingyang, Jinchang, and Baiyin, to interpret and analyze the resource curse effect by calculating a resource curse coefficient. Moreover, based on the regression model, the present study further discusses the empirical relations associated with the resource curse phenomenon. The results show that, regardless of whether a resource-dependent city is in the early, intermediate or late stage of its resource development, economic development is always plagued by the resource curse effect to a certain degree. Resource development cannot promote economic development, rather, it inhibits economic growth to some extent, resulting in an array of effects that are unfavorable to economic development, rendering the development unsustainable. For different types of resource-dependent cities, resource curse effect exhibits distinct characteristics. The resource curse effect is strongest for a resource-dependent city during an economic recession, is less severe during a development period, and is weakest during maturation. Resource development not only has a direct adverse impact on economic growth, but also often affects economic growth in multiple ways and on various levels through the Dutch disease effect, the crowding out effect, and the institution weakening effect. Until now, most results show that there is no obvious resource curse effect at the national and provincial level. The verification results of small-scale regions show that the resource curse effect at the city level still exists. In addition, the resource curse effect differs across different types of resource-dependent cities.

Aim: This study aimed to model and analyze the impact of the COVID-19 pandemic on economic growth and stability in Nigeria using the Vector Autoregressive (VAR) model. The study specifically focused on understanding the short-term interactions among confirmed COVID-19 cases, the Nigerian Stock Exchange All Shares Index (ASI), Nigerian crude oil prices (OP), and the Nigerian Naira to US Dollar exchange rate (NGNUSD). Study Design: A comparative analysis approach was employed using VAR and ARDL models to examine the interconnectedness and dynamic relationships between COVID-19 health indicators and key economic variables. The study covered a post-pandemic period in Nigeria, assessing the short-term and potential long-term impacts. Methodology: Daily time series data for the four variables were collected from May 26, 2020, to May 25, 2022, comprising 501 observations. A VAR(8) model was developed to capture the short-run dynamics,. Diagnostic tests including stability tests, Granger Causality/Block Exogeneity Wald Tests, and variance decomposition were conducted to validate the model and interpret the results. Results: The VAR(8) model results indicated the presence of only short-run relationships among the four variables, as confirmed by the absence of cointegration. Stability test results confirmed the reliability of the model, and Granger causality tests revealed significant causal effects between confirmed COVID-19 cases and key economic indicators such as ASI, OP, and NGNUSD. Furthermore, variance decomposition highlighted robust forecasting capabilities of the VAR model, demonstrating the immediate impacts of the pandemic on economic dynamics in Nigeria. Conclusion: The study concluded that the COVID-19 pandemic had significant short-run effects on economic growth and stability in Nigeria. The VAR model proved effective in capturing these short-term dynamics, highlighting the importance of understanding the interplay between health crises and economic variables for informed policymaking. The findings emphasized the need for strategic interventions to stabilize the economy during health-related external shocks.

Uncovering the benefits of integrating industrial symbiosis and urban symbiosis targeting a resource-dependent city: A case study of Yongcheng, China

<sec><title>Objective</title> The world is still in a phase of rapid industrialization and urbanization. Excessive carbon emissions has become the primary root cause of various urban or even global environmental problems, further impacting human physiological and psychological health. Cities are the largest sources of carbon emissions and are crucial regions for achieving carbon neutrality goals. Urban blue-green infrastructure (UBGI), comprising natural, semi-natural, or artificial green and blue spaces within cities, is considered as the most important carbon sink space in urban areas and has increasingly attracted widespread attention from researchers. However, there are still many unresolved issues regarding the effectiveness of UBGI in carbon sink enhancement and emission reduction: 1) How is the energy efficiency of carbon sink enhancement and emission reduction measured, and what factors influence it? 2) What are the mechanisms and pathways through which UBGI enhances carbon sink and reduces carbon emission? 3) How can UBGI be regulated to better enhance its effectiveness in carbon sink enhancement and emission reduction? 4) What are the limitations and potential directions for future research? This research aims to address these issues and propose scientifically sound planning strategies for UBGI construction to achieve urban carbon neutrality goals. </sec><sec><title>Methods</title> Through literature synthesis and deduction, this research organizes and analyzes the multi-scale measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction, identifies corresponding influencing factors at each scale, and constructs multi-scale planning strategies for UBGI based on the logical framework of “measurement methods–influencing factors – planning strategies”. </sec><sec><title>Results</title> The research proposes UBGI planning strategies across three spatial scales (site, community and urban area), covering three key aspects: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. Based on current research gaps and planning needs, five major research topics are further identified. This research provides a detailed analysis of the measurement methods and influencing factors of UBGI’s efficiency in carbon sink enhancement and emission reduction from three perspectives: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. The research finds significant differences in the measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction efficiency across different scales. Contradictory results may occur at different scales, and large-scale research often lacks characterization of internal features, leading to unclear mechanisms of influencing factors and obstructing practical planning. Based on the interpretation of UBGI’s mechanisms for carbon sink enhancement and emission reduction at different scales, this research formulates UBGI planning strategies across three spatial scales (site, community, and urban area). These strategies include: 1) At the site scale, for carbon sequestration and sink enhancement – carbon sink at the source, land balance, and ecological design; for emission reduction – symbiosis with buildings and integration into daily life. 2) At the community scale, for carbon sequestration – overall balance of revenue and expenditure, precise positioning, and proper interconnection of the carbon chain; for emission reduction – incorporation of cool islands and co-construction. 3) At the urban area scale, for carbon sequestration – enhancement of ecological space management and establishment of a carbon-safe pattern; for emission reduction – demand-based layout and organic dispersion. Finally, the research proposes five major research topics for the planning of UBGI’s carbon sink enhancement and emission reduction: How to construct unified measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction across scales? How to measure UBGI’s efficiency in carbon reduction based on temperature reduction (or preservation) at the site scale? How to integrate the pathways of carbon sink enhancement and emission reduction for a life cycle assessment of UBGI? How to balance UBGI’s carbon sink enhancement and emission reduction with other functions to achieve the optimal layout for comprehensive benefits? How to achieve urban “carbon justice” through UBGI? </sec><sec><title>Conclusion</title> The carbon sink pathway of the strategy framework requires “carbon sink at the source – precise positioning – safe pattern”, and the emission reduction pathway requires “symbiotic integration – co-construction and sharing – organic dispersion”. The key trade-offs between these two pathways at three spatial scales may provide theoretical support and practical guidance for UBGI construction and management. The five major research topics mentioned above may offer valuable assistance for UBGI construction and future research. </sec>

Economic growth measures growth in economic activities. Economic growth is important for countries, because it often brings better economic and social standards. Stock exchange performance is often a good indicator of the economy since it shows the performance of some of the important companies in the economy. The empirical analysis in this article aims to investigate the relationship between economic growth and stock exchange performance. Percentage change in GDP of Turkey and BIST100 are used as variables for this purpose. Two different data sets; 2003-2022 and 2013-2022 are available in the research. The analysis include error correction model, vector auto regression, Granger causality, impulse response, and variance decomposition. For the period 2013-2022, cointegration long run relationship is determined but there is no short run relationship as explained by error correction model. 30% of changes in economic growth can be explained by stock exchange performance and only 5% of changes in stock exchange performance can be explained by economic growth. BIST100 Granger causes economic growth. For the period 2003-2022, both short run and long run relationships are detected. Shocks in the long run disappear by 24%. The results indicate that the stock exchange performance can be used as an indicator of economic growth. Works in the literature also show significant relationship between stock markets and GDP both in local and international studies. The findings have important academic, policy and practical implications.

The Hu-Bao-O-Yu urban area is a major source of carbon emissions in China. It is also a major source of energy exports and high-end chemicals in China. Reaching peak carbon emissions early is especially important for meeting the national peak goal. For urban areas that rely on natural resources, we need to make it clearer how carbon emissions and economic growth affect each other and slowly break the strong link between the two. Therefore, in this paper, based on the data on carbon emissions, the decoupling state and the driving mechanism of carbon emissions in the Hu-Bao-O-Yu City group are researched by using the Tapio decoupling model and GDIM method. A new decoupling index model is constructed by combining GDIM and the traditional decoupling model. The main findings are as follows: (1) The Hu-Bao-O-Yu urban agglomeration, Ordos City, Baotou City and Yulin City have significant growth trends in annual carbon emissions, with Yulin City being the most important carbon source for the Hu-Bao-O-Yu urban agglomeration and its economic contribution to carbon emissions of the whole urban agglomeration is the most efficient. (2) The decoupling of Hu-Bao-O-Yu, Huhhot City, Baotou City, and Ordos City is dominated by expansionary negative decoupling, whereas Yulin City has strong negative decoupling. (3) The Hu-Bao-O-Yu urban cluster mainly affects the carbon intensity of fixed asset investments and output carbon intensity, which is a key part of the carbon separation process. The energy scale and structure also play a part in this process over time. (4) Changes in GDP per capita are a bigger part of changes in carbon emissions in the Hu-Bao-O-Yu urban agglomeration. These changes also determine the direction for changes in carbon emissions in the Hu-Bao-O-Yu urban agglomeration. In the future, the Hu-Bao-O-Yu urban agglomeration needs to coordinate its economic growth. Ordos and Yulin need to speed up the optimisation and transformation of their energy structures. Baotou needs to push for the low-carbon transformation of its industries. Huhhot needs to do more research on carbon sequestration technology and spend more on environmental protection. This will make the Hu-Bao-O-Yu urban agglomeration a resource-saving urban agglomeration and improve its ability to reduce emissions.

Currently, scientifically and reasonably specifying carbon emission reduction measures in the context of "double carbon" has become a common concern worldwide. China's administrative divisions have a notable impact on the formulation and implementation of relevant policies. Therefore the carbon emissions must be calculated accurately under China's administrative divisions at different scales. The spatiotemporal change characteristics of absorption and carbon emissions can provide scientific basis for the formulation of reasonable and differentiated carbon emission reduction policies in different administrative regions in China. To this end, this study used multi-source data such as remote sensing and statistics and integrated ecological models, statistics, and GIS space analysis and other methods to analyze the spatiotemporal dynamic change characteristics of carbon emissions and carbon absorption at different administrative scales （provinces, cities, and counties） in China. The results showed that： ① The total carbon absorption of vegetation in China continued to increase from 2000 to 2021 and the average value gradually increased. Differences were observed in spatiotemporal changes in carbon emissions at different administrative scales. The spatiotemporal changes at smaller scales were more evident. Carbon emissions showed obvious spatial differences of "high in the north and low in the south, high in the east and low in the west." ② The spatiotemporal distribution of CPI at the administrative scale was similar to that of carbon emissions and the overall trend was increasing annually. The pressure of carbon emissions on carbon absorption gradually weakened from the east to the central and western regions. ③ Spatiotemporal hotspot analysis showed that the overall spatial distribution of cold and hot spots in China's carbon absorption was as follows： In the spatial pattern of "hot in the east and cold in the west," the spatial distribution of cold and hot spots of carbon emissions showed agglomeration characteristics. The provincial scale was primarily oscillating hotspot whereas municipal and county scales were majorly continuous hot spots. Further results revealed that： ① Carbon absorption in different regions and periods in China showed significant variability, especially in the central and eastern regions. The possibility of offsetting carbon emissions by increasing carbon absorption remains. ② At the same scale, administrative regions （such as different provinces） and lower-level administrative regions at another scale （such as different cities in the same province） showed varying degrees of variability in carbon absorption and carbon emissions. Therefore, taking provincial administrative regions as an example for subsequent formulation considering carbon trading, emission reduction, and other policies, we should first consider the coordination of emissions between different cities in the province and then consider the coordination between provinces, which is expected to better promote the implementation of relevant policies.

This study examines the effect of tourism activity on the economic growth in Indonesia for the period of 1984 - 2014. This study applies the vector autoregressive model, along with the Granger causality test and the persistence profile to analyze the dynamic relationship between tourism activity, economic growth, and real exchange rate in Indonesia. To examine the shock response of the variables, this study uses variance decomposition and impulse response function approach. Throughout analysis is performed based on the empirical literature of the tourism-led growth (TLG) hypothesis. The results show that, based on the co-integration test, there is no long-term relationship between tourism activity and economic growth, while the Granger causality test results no evidence of causality between observed variables, except for economic growth and real exchange rate. In addition, by using variance decomposition and impulse response function to analyze the response of each variable. In explaining the shock of tourism activity in Indonesia, economic growth is more important than the real exchange rate. Meanwhile, tourism activity and real exchange rates are equally important in explaining the shock of economic growth. The impulse response function states that the shock of economic growth and real exchange rate has a positive effect on the tourism activity in the short- and long-term. In addition, the shock of tourism activity has a positive effect on economic growth, while the real exchange rate shock has a negative effect on economic growth in Indonesia.