The modernization of the different economic sectors has drastically increased energy consumption and CO2 emissions in developing countries, leading to a literature stream on the relationship between ...technological progress and the carbon emissions from the various sectors. However, most related policies do not consider the diversity of technological sources. As such, this study develops a comprehensive model that combines the expanded stochastic impacts by regression on population, affluence, and technology (STIRPAT) and the geographically and temporally weighted (GWTR) models to explore the spatial effects of three technology progress channels (research and development investment, technology spillover related to FDI, and DS) on the CO2 emissions in China from six sectors during 2000–2017. The results show that research and development investment has an inhibitory effect on the CO2 emissions from the agricultural, industrial, and wholesale sectors, and a catalytic effect for those from the construction, transportation, and residential sectors. The DS has a negative impact on the CO2 emissions from the agricultural, construction, and wholesale sectors, but a positive one for those from the industrial, transportation, and residential sectors. Finally, foreign direct investment has a positive effect on the CO2 emissions from all sectors (except for transportation). Therefore, this study shows that all the effects of the three technological progress channels on the carbon emissions from different sectors display spatial correlations and differences. In conclusion, policymakers should tailor policies to the various sectors in the different provinces.
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•We develop a model combining the extended STIRPAT and GWTR models.•We explore the spatial effects of three technology progress channels.•These channels display spatial correlations and differences for the various sectors.
South Africa has a dualistic economic structure that includes the on-farm and off-farm economic sectors. This paper is concerned with whether it is the on-farm or off-farm economic sector that serves ...as the main driver of economic development in South Africa. Agriculture has been previously regarded as the main driver of economic development in South Africa. The Lewis model of economic development is used to gain perspective on the dualistic economic structure of South Africa. This study relied extensively on secondary data, using thematic analysis for qualitative data and Microsoft Excel for quantitative data presentation and analysis. The findings show that the off-farm economic sector holds a major contribution to South African economic development compared to the on-farm economic sector. For example, in 2019, the on-farm economic sector made a significant distribution of employment with about 4.2% but still, the main distribution of employment has been made by the off-farm economic sector through community and social services which recorded about 4.6% of employment. The main issue related to the on-farm economic sector is that it consists of informal economic activities that are struggling to contribute to economic growth. This is because the information generally and statistically on the trade, value and main input of these economic activities is not well recorded in South Africa. There is a need for the government to introduce policies that will guide the operation of the informal economic activities associated with the on-farm economic sector.
In the studies on labour market change and transformation of employment relations, the growth of new forms of self-employment, including platform work, has raised a broad debate about how to define, ...classify, and analyse the wide range of positions within the heterogeneous category of self-employed workers. This article analyses the emergent methodologies used in European comparative labour statistics to identify forms of dependency in self-employment. Using the 6th wave of the 2015 European Working Condition Survey and the 2017 ad hoc module on self-employment from the European Labour Force Survey, this article discusses how the representation of dependent self-employment changes by adopting a different operationalization of economic and operational dependency. Findings show how different indicators of dependency change the representation of self-employment in different economic sectors, affecting our understanding of the transformation of working arrangements within self-employment and the boundaries between employment and self-employment.
This study aims to analyze the effect of 17 economic sectors on economic growth in the Lake Toba Region (KDT). The data used is secondary data in the form of times series from 2010 to 2019 with panel ...data analysis using Fixed Model Effect (FEM). It shows a positive and significant influence between mining, energy, information, finance, and health sectors on KDT economic growth, while the other 12 economic sectors have no significant effect. An increase of 1 percent in the mining sector will incline economic growth by 1.41 percent; the energy sector will promote economic growth by 0.48 percent; the information sector will increase economic growth by 0.81 percent; the financial sector will increase economic growth by 0.78 percent; and the health sector will enhance economic growth by 1.10 percent. The government should make policies related to production and investment enhancement so that the income of each economic sector and economic growth in KDT increases. Keywords: Economic growth, Economic sector, Panel dataJEL Classification: C01, C33, O11
PurposeThis study focuses on the relationship between foreign direct investment (FDI) and economic growth of the formal sector comprising all foreign and domestic registered enterprises engaged in ...production of goods and services.Design/methodology/approachThis study uses a balanced longitudinal data set for the period from 2006 to 2014 from secondary sources in 63 provinces/cities of Vietnam. The generalized method of moments (GMM) estimation for a dynamic panel data model is applied.FindingsThe greater the share of FDI in capital resource, the more favorable the output growth in the whole formal sector. The FDI enterprises are more productive than domestic formal firms, and the output growth of FDI firms creates a positive spillover effect on the output growth of domestic firms.Originality/valueThe effect of FDI on economic growth is investigated at subnational level for the whole formal economic sector as well as the formal domestic firms. The domestic and foreign industrial agglomerations and the business environment are also examined.
The spillover effects among sectors are of concern for distinct market participants, who are in distinct investment horizons and concerned with the information in different time scales. In order to ...uncover the hidden spillover information in multi-time scales in the rapidly changing stock market and thereby offer guidance to different investors concerning distinct time scales from a system perspective, this paper constructed directional spillover effect networks for the economic sectors in distinct time scales. The results are as follows: (1) The “2–4 days” scale is the most risky scale, and the “8–16 days” scale is the least risky one. (2) The most influential and sensitive sectors are distinct in different time scales. (3) Although two sectors in the same community may not have direct spillover relations, the volatility of one sector will have a relatively strong influence on the other through indirect relations.
•Spillover networks of sectors in distinct time scales are constructed.•“2–4 days” scale is the most risky one.•“8–16 days” scale is the less risky one.•The most influential and sensitive sectors in each time scale are different.•Indirectly related sectors in the same community interact closely.
Cluster analysis of the Russian labour market sectors Nikolenko, Sofia O.; Moiseev, Nikita A.; Smirnova, Elena I.
Vestnik Voronezhskogo gosudarstvennogo universiteta. Serii͡a︡ Ėkonomika i upravlenie,
06/2023
2
Journal Article
Recenzirano
Odprti dostop
Subject. In the face of significant change, with companies suspending or completely terminating their operations in the Russian Federation, there are supply and logistical challenges, and planning ...issues arise. It is still necessary to plan financial support for industries that are most likely to be affected by these changes. The changes affect not only the output, but also the employment and wages in the sectors. A comprehensive analysis of the developments is required to make the most effective decisions. In this study, we considered the relationship between sectors of the economy in terms of average wages, which is an important factor reflecting the development vector in the sector.Objectives. The purpose of the study was to analyse the specific features of the Russian labour market, based on average wages by sector and to identify similar sectors.Methodology. In the study, we used the classification of economic sectors based on the methodology developed by the Federal State Statistics Service. Throughout the study, the terms “economic sector” and “industry” are used as synonyms. The following scientific methods were used: measurement, description, and modelling. The research is based on reviewing topical scientific literature, both Russian and foreign.Results. We grouped economic sectors based on characteristics such as chained rate of increase, average rate of increase, minimum and maximum value, standard deviation, and the range of the studied time series. The resulting clusters reflect the specific features of the industries included, which supports the results of the analysis.Conclusions. The analysis revealed three clusters with industries sharing a common development dynamic. The first cluster includes industries that are part of the primary sector of the economy. The second cluster includes state-supported industries, while the third cluster represents industries that are part of the manufacturing sector.
Load-side re-electrification—the substitution of prevalent fossil fuel-dominated structures with a wider range of electric end-use technologies—has been recognized as a crucial strategy for systemic ...decarbonization. This strategy focuses on expanding the proportion of clean energy consumption to support the attainment of carbon neutrality goals. While prior research has explored the ramifications of re-electrification strategies within specific sectors, such as transportation, comprehensive assessments evaluating the impacts of an entire portfolio of load-side options remain scarce. This analysis bridges this gap by scrutinizing the effects of multiple load-side re-electrification options on decarbonization pathways and transition costs within energy systems. We leverage a detailed, bottom-up dispatch model with an hourly resolution for this research. A case study of Northwestern China serves to illuminate the implications of our research, demonstrating that without the deployment of carbon dioxide removal technologies, an extensive load-side re-electrification can yield a maximum carbon dioxide emission reduction of up to 37.15% by 2060. Furthermore, this study offers an in-depth comparison of the transition costs across multiple future scenarios employing foreseeable technologies.
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•Load-side re-electrification in energy systems greatly influences the pathways of regional decarbonization•The implementation of re-electrification strategies can lessen the dependence on uncertain technologies and the impact of individual sector emission reductions•Comprehensive load-side re-electrification strategies will inevitably entail higher overall system transition costs
The increasing competition in the electric sector is challenging retail companies as they must assign its commercial efforts to attract the most profitable customers. Those are whose energy demand ...best fit certain target profiles, which usually depend on generation or cost policies. But, even when the demand profile is available, it is in an anonymous way, preventing its association to a particular client. In this paper, we explore a large dataset containing several millions of monthly demand profiles in Spain and use the available information about the associated economic sector and location for an indirect identification of the customers. The distance of the demand profile from the target is used to define a key performance indicator (KPI) which is used as the main driver of the proposed marketing strategy. The combined use of activity and location has been revealed as a powerful tool for indirect identification of customers, as 100,000 customers are uniquely identified, while about 300,000 clients are identifiable in small sets containing 10 or less consumers. To assess the proposed marketing strategy, it has been compared to the random attraction of new clients, showing a reduction of distance from the target of 40% for 10,000 new customers.
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