Regional Industrial Structures Research Articles

Research on the impact of regional integration policy on carbon emissions--Taking the Yangtze River Economic Belt as an example.

The Yangtze River Economic Belt serves as a paradigm of ecological integration and high-quality development within China. Under the constraints of the "Dual Carbon" goal, how does the integrative policy of the Yangtze River Economic Belt, aimed at reinforcing inter-regional industrial cooperation, impact carbon emissions across various provinces within the region? Leveraging panel data from 30 Chinese provinces spanning 2009-2019 and treating the 2016 promulgation of the "Yangtze River Economic Belt Development Planning Outline" as a quasi-natural experiment, this study employs a Difference-in-Differences (DID) model for discerning the effects of regional integration policies on carbon emissions, intensity, and efficiency in the 11 provinces of the Yangtze River Economic Belt. The research further delves into the underlying mechanisms through which policy interventions modulate provincial carbon emissions. Key findings include: (1) The policy's enactment has significantly attenuated provincial carbon emissions and intensity, albeit somewhat hampering the enhancement of carbon efficiency-conclusions robust to parallel trend and placebo tests; (2) Heterogeneity analyses reveal disparities in the policy's carbon emission effects, contingent on varying economic development levels and geographical loci; (3) Mechanistically, while the integration bolsters regional environmental governance and strengthens economic ties-thereby curtailing provincial emissions-it is evident that local governments have been somewhat inept in effectively channeling the influx of substantial short-term capital, hence stifling provincial carbon efficiency. In light of these insights, it is posited that local governments within the Yangtze River Economic Belt should ardently endeavor to refine and elevate regional industrial structures, champion the construction of an integrated regional market, intensify capital oversight and coordinated utilization, and enhance the efficiency of regional capital allocation, all in the quest to augment regional carbon emission reduction performance.

Environmental Assessment of Changes in Regional Industrial Structures in Russia at the Beginning of the 21st Century

Environmental Assessment of Changes in Regional Industrial Structures in Russia at the Beginning of the 21st Century

Synergy level of pollution and carbon reduction in the Yangtze River Economic Belt: Spatial-temporal evolution characteristics and driving factors

Achieving synergistic control of air pollution and carbon emissions is crucial for addressing environmental changes. This study aims to assess the synergy level of pollution and carbon reduction, identify driving factors, and provide realization paths to reduce pollution and carbon emissions synergistically. Using a coupling coordination degree model and optimal parameters-based Geographical detector model, this study focuses on 108 cities in the Yangtze River Economic Belt. Results reveal that PM2.5 control is more effective than carbon emission management in the YREB. The synergy level of pollution and carbon reduction shows an upward trend with the mean synergy level increasing 7.2% from 2006 to 2019. Spatially, significant heterogeneity exists, with higher synergy degrees in upstream areas. Social and natural factors including industrial structure, technological innovation, energy structure, human capital, and economic foundation significantly influence pollution and carbon reduction synergy. The interaction between natural constraints and high-quality development factors such as technological innovation and the digital economy further strengthens the driving force, with the strengthening of a single factor reaching up to 75%. Based on regional differences in synergy levels, this study proposes targeted applicable suggestions, including strengthening inter-city interaction, optimizing regional industrial and energy structures, and promoting technological innovation.

High-speed rail network and regional convergence/divergence in industrial structure

Despite the large body of literature on the impact of high-speed rail (HSR) on regional economic development, less is known about how it acts as inter-regional linkages. We seek to enrich the literature by examining if HSR can support inter-regional learning and enable lagging regions to learn from advanced ones. Another feature that distinguishes our study from others is its focus on regional convergence/divergence in industrial structure, while most pay attention to that in GDP/incomes. We investigate the impact of HSR connection on the similarity of regional industrial structures during 2008–2015 in China using the multi-stage difference-in-differences and propensity score matching methods. The results suggest that there is a positive relationship between HSR connection and the similarity of a pair of cities’ industrial structures. The influence of HSR connection varies across time, and is contingent on the features of regions and industries. Econometric results show that it takes time for HSR connections to have some effects. Such effects also fade in the long run. Furthermore, HSR development in China has facilitated knowledge flows from developed, coastal regions to lagging, inland regions and then spread among the latter, especially in the case of high-complexity industries. Our research thus provides a more nuanced perspective to better understand the relationship between transport infrastructure and regional convergence/divergence.

Big data analysis of water quality monitoring results from the Xiang River and an impact analysis of pollution management policies.

Water pollution prevention and control of the Xiang River has become an issue of great concern to China's central and local governments. To further analyze the effects of central and local governmental policies on water pollution prevention and control for the Xiang River, this study performs a big data analysis of 16 water quality parameters from 42 sections of the mainstream and major tributaries of the Xiang River, Hunan Province, China from 2005 to 2016. This study uses an evidential reasoning-based integrated assessment of water quality and principal component analysis, identifying the spatiotemporal changes in the primary pollutants of the Xiang River and exploring the correlations between potentially relevant factors. The analysis showed that a series of environmental protection policies implemented by Hunan Province since 2008 have had a significant and targeted impact on annual water quality pollutants in the mainstream and tributaries. In addition, regional industrial structures and management policies also have had a significant impact on regional water quality. The results showed that, when examining the changes in water quality and the effects of pollution control policies, a big data analysis of water quality monitoring results can accurately reveal the detailed relationships between management policies and water quality changes in the Xiang River. Compared with policy impact evaluation methods primarily based on econometric models, such a big data analysis has its own advantages and disadvantages, effectively complementing the traditional methods of policy impact evaluations. Policy impact evaluations based on big data analysis can further improve the level of refined management by governments and provide a more specific and targeted reference for improving water pollution management policies for the Xiang River.

Ecological Assessment of Changes in Regional Industrial Structures in Russia at the Beginning of the 21st Century

Ecological Assessment of Changes in Regional Industrial Structures in Russia at the Beginning of the 21st Century

The effect of green finance on industrial pollution emissions: Evidence from China

At present, China is undergoing a transformation from high-speed growth to high-quality development, and environmental protection is placed in a very important position. To explore the relationship between the pollution and green finance, this research uses the data of 30 provinces from 2001 to 2020 to calculate the provincial level green finance index and further examines the non-linear influence of green finance on industrial pollution emissions based on Kuznets Curve. Three types of pollutants are selected to generate the green Kuznets curves, and the "inverted N" curves were obtained to express the relationship between green finance and industrial pollution emission. For regional heterogeneity, the results show that relationship between green finance and industrial pulltion emission has regional heterogeneity for three types of pollutants, which can be attributed to different regional industrial structures to some extent. Hence, upgrading industrial structure is a win-win solution for green finance development and industrial pulltion emission reduction.

Study of the Effect of China’s Emissions Trading Scheme on Promoting Regional Industrial Carbon Emission Reduction

The creation of carbon emissions trading markets is a core policy for realizing China’s twin objectives of reaching a peak in CO2 emissions before 2030 and achieving carbon neutrality by 2060. Given that industry is the most significant energy consumer and CO2 emitter, it is imperative to implement carbon reducing initiatives to attain these goals. Following the implementation of carbon emissions trading pilots in China, this article theoretically analyzes the mechanisms of action and paths of influence of China’s carbon trading policies on regional industrial carbon emissions. Then, regarding the trading rights policies launched in 2013 as a quasi-natural experiment, this study uses provincial panel data and industry data from 2003 to 2016 to empirically test the effect of carbon trading on industrial emissions by employing the difference-in-difference and difference-in-difference-in-difference methods. It was found that carbon emissions trading can promote a reduction in regional industrial carbon emissions, achieving the dual aims of reducing total emissions and reducing emission intensity. The reduction effect occurs after the implementation of the carbon trading market policies. The carbon trading policies reduced regional industrial emissions by optimizing regional industrial structures and increasing regional technological innovation. It was also found that reductions in carbon emissions were heterogeneous among industries. These research conclusions will help to improve the top-level design of China’s industrial energy saving and carbon reduction policies and to achieve low-carbon and green industrial development.

Is industrial related variety an enabling condition for regional entrepreneurship? A comparison between mining and non-mining regions in Chile

A central question in Evolutionary Economic Geography is why regions differ in their ability to diversify and thus retain or expand their competitive position. Economic geography has generally tackled this question linking initial regional industrial structures with the emergence of new economic specializations. In this article, we argue that entrepreneurship is a key and largely overlooked mechanism of regional diversification, which has been shown to be eased by industrial related variety, but at the same time dampened by the weak linkages between the mining industry and the local economy. We analyze whether related variety is an enabling condition for entrepreneurship in mining regions. Using an unbalanced panel of around 187,000 new firms created between 2005 and 2011 in Chile, we show that related variety favors new firms’ creation, sales, and employment in non-mining regions, but not in mining regions. The results indicate that, due to the absence of pro-entrepreneurship effects of a relatedly-varied structure, mining regions face particularly challenging conditions for an entrepreneurship-based diversification process. Place-based policies attracting external knowledge, reinforcing territorial embeddedness of mining assets, and strengthening local absorptive capacity can help creating new development paths in mining regions driven by local entrepreneurs.

The Path of Housing Prices in Promoting the Upgrading of Industrial Structure: Bank Credit Funds, Land Finance, and Consumer Demand

The impact path of housing prices on the upgrading of the industrial structure is an important part of realizing the high-quality operation of the national economy in China. In order to discuss the mechanism of different influencing paths to upgrading industrial structure, this paper introduces three different intermediary variables from the levels of supply, demand, and government, and further subdivides and compares them to empirically test the specific impact path of housing prices on industrial structure upgrading by constructing multi-dimensional industrial structure upgrading indicators. It obtains some meaningful results. Firstly, there is a significant U-shaped relationship between housing prices and industrial structure upgrading; secondly, rising house prices will exacerbate the real estate industry’s occupation of bank credit funds, hindering the upgrading of the whole industrial structure; thirdly, the negative impact of the land’s financial dependence on the upgrading of the industrial structure was underestimated; and, finally, the rise in housing prices can improve the consumption level and promote the upgrading of regional industrial structures. By studying the impact path of house prices on the upgrading of different industrial structures, it will help local governments regulate house prices and give full play to the role of house prices in promoting the upgrading of industrial structure through multiple channels.

How regional economic structure matters in the era of COVID-19: resilience capacity of U.S. states.

The COVID-19 pandemic is an unexpected-extreme event and has considerably impacted the national and regional economies. This paper emphasizes the importance of industrial structure for a region’s resistance to the recessionary shock. Two significant factors that may determine the regional industrial structures in this ongoing recession include the relative composition of essential/non-essential sectors and the intensity of face-to-face interactions. Considering these factors, we focus on two groups of industries: essential industry with low interpersonal interactions and non-essential industry with high interpersonal interactions. The specialization in these industries is associated with the regional economic resistance to the COVID-19 induced recession. Estimation results from the ordinal logistic regression models show that essential industries with low interpersonal interactions, especially the retail and service sectors––for instance, non-store retailers and financial and professional service––are significantly related to regional economic resistance, and their relationship intensifies compared to other sectors during the COVID-19 pandemic. However, states specialized in the non-essential industries with high interpersonal interactions are less likely to resist economically during the lockdown-COVID and until the stabilizing-COVID period. In addition, a state that quickly recovered from the 2001 recession is more likely to resist the pandemic shock during early- and lockdown-COVID periods. Findings in this paper indicate the importance of regional industrial structure to determine the level of vulnerability to unexpected recessionary shocks. Additionally, identifying the vital factors to determine the industrial structure based on the type of shock is found to be crucial.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00168-022-01134-w.

Impact of spatial misallocation of electric power resources on economic efficiency and carbon emissions in China.

The relationship between resource misallocation and productivity has become a hot topic in recent years, but few studies examined the impact of spatial misallocation of electric power resources (SMEPRs) on economic efficiency and carbon emissions. Here, we constructed a calculation model of SMEPRs that can measure both the misallocation degree and direction and uncovered the spatiotemporal evolvement mechanism of SMEPRs. On this basis, we explored the impact of SMEPRs on regional economic efficiency and carbon emissions using panel data from 29 provinces in China from 1988 to 2017. The results demonstrate that the high level of SMEPRs in China shows complex spatiotemporal characteristics and significantly affects the regional economic efficiency and carbon emissions. Specifically speaking, first, SMEPRs present the characteristics of the coexistence of excessive and insufficient allocation among provinces and regions, the increasing extent of misallocation in the eastern and western regions, and the gradual decline in the central region; second, SMEPRs have a strong negative effect on the regional economic efficiency and carbon emissions by affecting regional industrial structures, which indicates that SMEPRs are an important factor restricting the high-quality development of regional economies. The research is conducive to the development of resource misallocation theory. Moreover, the research observations offer fresh insights to upgrading the high-quality and green development of China's power sector and promoting regional economic transformation and ecological sustainability.

A Regional Economy\u2019s Resistance to the COVID-19 Shock: Sales Revenues of Micro-, Small-, and Medium-Sized Enterprises in South Korea

The coronavirus disease 2019 (COVID-19) is a global pandemic that has heavily impacted not only the health sector, but also the economic sector in general. Many countries have projected a negative economic impact, and the effect on micro-, small-, and medium-sized enterprises (MSMEs) is predicted to be significantly large. This study estimated the regional resistance of MSME sales revenues and identified the regional economic factors that affect resistance by analyzing South Korea, a country with one of the lowest economic impact projections from COVID-19. Resistance was estimated by comparing sales revenues and changes in resistance observed during the early COVID-19 period to those recorded in the same weeks (weeks 6 to 9) of 2019. The factors that affect regional resistance were determined by conducting robust regression and spatial regression analyses. The results show that the number of confirmed COVID-19 cases, a direct risk factor, is negatively related to regional resilience, while diversity is positively related to regional resistance. To improve the regional resistance against uncertain events, this study recommends increased diversity among regional industrial structures to reduce the duration of the early shock of an unexpected adverse event.

Global Competition in the Lithium-Ion Battery Supply Chain: A Novel Perspective for Criticality Analysis

With the accelerated pace of energy transition, competition in the lithium-ion battery (LIB) supply chain is intensifying across a wide scope of countries. In order to understand the potential risk derived from the competitors, this study quantifies the global competition intensities of 15 categories of LIB-related commodities, which has not been well characterized by previous criticality analysis studies. On the basis of the collected data and designed treatment techniques, the "competition index" is developed for this purpose. Here, we show that lithium hydroxides, LIBs, and lithium carbonates were the focal points of global competition in the LIB supply chain in 2019, and there will be more competition for lithium hydroxide in the future. The competition for commodities related to LIBs among Korea, Japan, and the USA are the most notable. Such insights into the global conflict potential of LIB-related commodities provide a reference for underlying competitors and corresponding transition strategies of regional industrial structures. The index developed by us complements the criticality analysis framework, which could be expanded to assess the criticality of materials relevant with other industries.

Universities, students and regional economies: a symbiotic relationship?

ABSTRACT This paper examines the heterogeneous effect of student spending in UK NUTS-2 regions. Impact analyses of the more than £45 billion students spend each year have so far been agnostic of the regional absorptive capacity to benefit from this expenditure. Building a multi-regional input–output model for the UK and combining it with data on student expenditure, domicile and level of study, the paper finds significant regional heterogeneity in gross value added and employment multipliers as well as in interregional spillovers. The analysis shows how important student expenditure is for regional economies and the symbiotic relationship between student spending and regional industrial structures that produce varying impact outcomes.

Labor productivity management in the competence system at the regional level

Importance. Economic recovery after the pandemic is associated with the transition of production to more efficient technological solutions aimed at increasing labor productivity. Optimization of existing production processes, increasing the efficiency of proven technologies should be accompanied by the organization of a parallel advanced process of developing new promising systems and technologies. The implementation of these tasks is associated with a number of difficulties associated with the low qual- ity of management systems. One of the significant problems was the lack of a training and retraining system built into the full technological and marketing cycle of production. Objectives. The purpose of the study is to develop a concept of a management system based on a com- petency-based approach and aimed at increasing labor productivity at the regional level. The article developed a management model that allows to combine various departmental and corporate interests. For the study, the regional level was chosen as the base one, since the main set of issues necessary for the dynamic development of production processes are in the competence of regional state, industrial and educational structures. Methods. The work used such methods of economic research as: modeling, the method of scientific abstractions, analysis and synthesis, systemic and functional approaches; special research methods: analytical and comparative methods. Conclusions and Relevance. The proposed model allows the use of scientific developments to increase production efficiency and includes a system of scientific and educational competencies in the regional management circuit. The management model was focused on the implementation of methodologies to achieve the lowest cost results in the short term, which should be part of the strategic management framework. The article highlighted the operational level of increasing labor productivity as the most amenable to formalization and identification of indicators, and developed principles for the formation of indicators of labor productivity. The practice of applying new approaches to management by organi- zations had shown the need to coordinate the management of labour productivity at the macroeconom- ic level, since, in many respects, key management decisions should be made at the regional and federal levels due to the separation of departments and corporations, which could not agree on a single tech- nological policy. The theoretical rationale for the economic model of digital peri-ode is gaining a new socio-economic content, which we have begun and continue to develop in this publication.

Regional Resilience in Times of a Pandemic Crisis: The Case of COVID-19 in China.

The notion of resilience to analyse how fast systems recover from shocks has been increasingly taken up in economic geography, in which there is a burgeoning literature on regional resilience. Regional resilience is a place‐sensitive, multi‐layered and multi‐scalar, conflict‐ridden and highly contingent process. The nature of shocks is one important impact factor on regional resilience. Arguably, so far, most literature on regional resilience has dealt with the financial crisis in 2008/2009. In this research note, we will analyse both the particular characteristics of the current COVID‐19 crisis, as well as its effects on regional recovery and potential resilience in China, where it started. We conclude that a complex combination of the characteristics of the current COVID‐19 crisis, the institutional experience of dealing with previous pandemic and epidemic crises, government support schemes, as well as regional industrial structures, might potentially affect the recovery and resilience rates of Chinese regions.

Changes in Russia's sectoral and regional industrial structures

Subject. This article considers the industry structure of the economy as a system susceptible to rapid quantitative and qualitative changes. Objectives. The article aims to comprehensively study shifts and changes in the sectoral and regional structures of the Russian industry. Methods. For the study, we used the methods of theoretical differentiation and insight of the object, sequential clustering, analytical population, grouping of data on an adjacent basis, and conceptual algorithmization. Results. The article highlights structural changes in the Russian industry, significant disparities in the types of economic activity under study in terms of regions, positive shifts, growth zones, and prospective regions for investment. Positive trends need to be promoted. Conclusions. The Russian industrial policy traditionally gravitates towards a vertical model and the preferential use of budgetary and quasi-budget financing tools. The consequence of this situation is the excessive fragmentation of the policy. Taking into account the variety of cases of the industrial policy implementation in Russia, the success achieved can be considered relatively local.

Mapping of industrial innovations of the fifth technological mode within the framework of industrial park structures of the Sverdlovsk region

The main objective of the research presented in this article is to determine the priorities for the technological development of production based in industrial park structures of the Sverdlovsk region. The method of mapping technological innovations is used as the main research methodology, the information base is the plans and programs for the technological development of industrial enterprises in the Sverdlovsk region. The study develops a comprehensive methodology for assessing the technological and innovative development of industrial park structures based on the experience of Russia, Belarus and Moldova. Based on the results of the analysis, proposals are developed for adjusting the innovative development programs of regional industrial park structures.

Interprovincial differences in labour force distribution and utilization based on educational attainment in Indonesia, 2002–2015

AbstractIntroducing an employment variable with five levels of educational attainment per capita and employing inequality decomposition, this study addresses three questions. How does labour force vary by education and provinces? How does labour force utilization vary by education and provinces? What are the potential causes of differences? We find that the no‐primary‐education group is more endowed in less‐developed provinces and allocated most unequally among education groups across provinces, despite past universal primary education policies. The senior‐secondary‐education group with the largest labour share is a growing concern due to the lower employment rate and largest interprovincial inequality.