scholarly journals Why is pollution embodied in Guangdong exports declining? The roles of trading scale, technology and structural changes

2021 ◽  
Vol 3 (1) ◽  
pp. 229-238
Author(s):  
Long-Ni Liang ◽  
◽  
Ming-Xu Wang ◽  
Weast-Siu Siu ◽  
◽  
...  
Keyword(s):  
Structural Changes ◽  
Average Rate ◽  
Decomposition Analysis ◽  
Structural Effect ◽  
Clothing Industry ◽  
Pollution Reduction ◽  
Structural Decomposition Analysis ◽  
Logarithmic Mean ◽  
Index Model ◽  
Technology Advancement

From 2007 to 2017, Guangdong exports grew at an average rate of 9.6%, while the energy consumption and carbon emission embodied in these trades demonstrated a declining trend. Is total real pollution embodied in exports showing the same trend? If so, what accounts for these changes? Prior studies have provided three explanations, producing greater amount of goods (“the scale effect”), adopting cleaner technologies in production processes (“the technology effect”), and producing proportionally more goods that are environmental-friendly (“the structural effect”). Question then arises as which factor is the driving force of such cleanup in the export business? To answer these questions, an EIO-LMDI (Environmental Input-Output and Logarithmic Mean Divisia Index) model is built to conduct a structural decomposition analysis of pollution embodied in Guangdong exports. We calculate that the pollution embodied in Guangdong export fell by 63 to 85 percent, depending on the pollutants. We further conclude that these pollution reductions are primarily driven by the technology advancement, with some industries, including the clothing industry, communications, computers and other electronic equipment, being more sensitive to the changes in technologies than others. The structural effect is more ambiguous. It only contributes to pollution reduction when the industry itself is pollution intensive.

scholarly journals Analysis of the Structural Decomposition of the Textile-Clothing Industry in Bangladesh

2021 ◽  
pp. 44-55
Author(s):  
Md. Masum ◽  
Md. Mourtuza Ahamed ◽  
Mohammad Sayedur Rahman
Keyword(s):  
Structural Changes ◽  
Low Cost ◽  
Decomposition Analysis ◽  
Domestic Demand ◽  
Final Demand ◽  
Clothing Industry ◽  
Input Output ◽  
Structural Decomposition Analysis ◽  
Structural Decomposition ◽  
Private And Public

Purpose: This paper aims to introduce the technology’s role and the final demand in the textile clothing industry’s growth path (TCI) of Bangladesh. Methodology: This study applies structural decomposition analysis in the input-output framework to measure Bangladesh’s textile–clothing industry structural changes. Structural decomposition analysis is also known as growth accounting in literature. Findings: This paper finds that, from 1975 to 1995, the TCI has grown due to huge domestic demand, from 1995 to 2015, this industry has grown due to export expansion. The technology was never a key factor over low–cost labor for the development of TCI in Bangladesh. Implications: For the sustainable development of the TCI in Bangladesh, domestic demand expansion is significant. Private and public policies should reflect this expansionary (domestic demand expansion) strategy. Originality: Previous studies on the TCI were mainly descriptive; there was no decomposition analysis in the input-output framework. Moreover, this paper decomposes the growth of the TCI into technical effect and final demand effect, which are new in the ready-made garment industry of Bangladesh.

scholarly journals Structural Changes and Growth Factors of China’s Textile Industry: 1997-2012

2018 ◽  
Vol 26 (2(128)) ◽  
pp. 20-25 ◽  
Author(s):  
Jianlei Zhang ◽  
Yunying Liu ◽  
Longdi Cheng
Keyword(s):  
Growth Factors ◽  
Textile Industry ◽  
Structural Changes ◽  
Driving Forces ◽  
Chemical Fibre ◽  
Decomposition Analysis ◽  
Positive Contribution ◽  
Structural Decomposition Analysis ◽  
Contribution Rate ◽  
Industrial Sectors

In this study, the Input-Output Structural Decomposition Analysis (I-O SDA) method is adopted to analyze the structural change in China’s textile industry during 1997-2012 and to measure the contribution rate of the growth factors (consumption, investment, inventory, exports and imports) affecting change in its gross output. Then the key factors and main driving forces promoting textile industry development are figured out. The results show that China’s textile industry has experienced great change both in scale and structure. Among the growth factors, the contribution rate of exports is the largest, followed by investment, consumption, imports and inventory. The textile industry still relies heavily on exports, investment and consumption, while the contribution rate of imports is relatively small. In addition, technological change makes a positive contribution with technological innovation. Among the industrial sectors, the cotton & chemical fibre textile industry holds dominance, with the textile manufactured goods industry exhibiting tremendous development, the growth of the knitted textile industry fluctuating, and the wool textile industry and hemp & silk textile industry progressing slowly. Finally relevant policy suggestions are proposed to promote the balanced and coordinated development of China’s textile industry.

scholarly journals Decomposition analysis of water footprint changes in a water-limited river basin: a case study of the Haihe River basin, China

2014 ◽  
Vol 18 (5) ◽  
pp. 1549-1559 ◽  
Author(s):  
Y. Zhi ◽  
Z. F. Yang ◽  
X. A. Yin
Keyword(s):  
River Basin ◽  
Water Resource Management ◽  
Water Footprint ◽  
Decomposition Analysis ◽  
Structural Effect ◽  
Haihe River Basin ◽  
Structural Decomposition Analysis ◽  
Haihe River ◽  
Agriculture Sector ◽  
The Haihe River Basin

Abstract. Decomposition analysis of water footprint (WF) changes, or assessing the changes in WF and identifying the contributions of factors leading to the changes, is important to water resource management. Instead of focusing on WF from the perspective of administrative regions, we built a framework in which the input-output (IO) model, the structural decomposition analysis (SDA) model and the generating regional IO tables (GRIT) method are combined to implement decomposition analysis for WF in a river basin. This framework is illustrated in the WF in Haihe River basin (HRB) from 2002 to 2007, which is a typical water-limited river basin. It shows that the total WF in the HRB increased from 4.3 × 1010 m3 in 2002 to 5.6 × 1010 m3 in 2007, and the agriculture sector makes the dominant contribution to the increase. Both the WF of domestic products (internal) and the WF of imported products (external) increased, and the proportion of external WF rose from 29.1 to 34.4%. The technological effect was the dominant contributor to offsetting the increase of WF. However, the growth of WF caused by the economic structural effect and the scale effect was greater, so the total WF increased. This study provides insights about water challenges in the HRB and proposes possible strategies for the future, and serves as a reference for WF management and policy-making in other water-limited river basins.

scholarly journals Decomposition analysis of water footprint changes in a water-limited river basin: a case study of the Haihe River Basin, China

2013 ◽  
Vol 10 (12) ◽  
pp. 14591-14615 ◽  
Author(s):  
Y. Zhi ◽  
Z. F. Yang ◽  
X. A. Yin
Keyword(s):  
River Basin ◽  
Water Resource Management ◽  
Water Footprint ◽  
Decomposition Analysis ◽  
Structural Effect ◽  
Haihe River Basin ◽  
Structural Decomposition Analysis ◽  
Haihe River ◽  
Agriculture Sector ◽  
The Haihe River Basin

Abstract. Decomposition analysis of water footprint (WF) changes, or assessing the changes in WF and identifying the contributions of factors leading to the changes, is important to water resource management. However, conventional studies focus on WF from the perspective of administrative region rather than river basin. Decomposition analysis of WF changes from the perspective of the river basin is more scientific. To address this perspective, we built a framework in which the input–output (IO) model and the Structural Decomposition Analysis (SDA) model for WF could be implemented in a river basin by computing IO data for the river basin with the Generating Regional IO Tables (GRIT) method. This framework is illustrated in the Haihe River Basin (HRB), which is a typical water-limited river basin. It shows that the total WF in the HRB increased from 4.3 × 1010 m3 in 2002 to 5.6 × 1010 m3 in 2007, and the agriculture sector makes the dominant contribution to the increase. Both the WF of domestic products (internal) and the WF of imported products (external) increased, and the proportion of external WF rose from 29.1% to 34.4%. The technological effect was the dominant contributor to offsetting the increase of WF; however, the growth of WF caused by the economic structural effect and the scale effect was greater, so the total WF increased. This study provides insights about water challenges in the HRB and proposes possible strategies for the future, and serves as a reference for WF management and policy making in other water-limited river basins.

scholarly journals Study on the Impact of the Export of China’s Final Use Products on Domestic SO2 Emissions

2019 ◽  
Vol 11 (20) ◽  
pp. 5809 ◽  
Author(s):  
Zhenjie Zang ◽  
Hua Zhang ◽  
Huifang Liu ◽  
Jun Wang ◽  
Kealeboga Fredah Goetswang
Keyword(s):  
Scale Effect ◽  
Decomposition Analysis ◽  
Structural Effect ◽  
Structural Decomposition Analysis ◽  
So2 Emissions ◽  
Factors Affecting ◽  
Technical Effect ◽  
Export Volume ◽  
The Impact ◽  
The Relationship

Since China’s accession to the World Trade Organization (WTO), its export volume has achieved rapid growth. Meanwhile, the manufacturing of export products has also resulted in a large amount of SO2 emissions in China. To explore the relationship between the export of China’s final use products (ECFuP) and SO2 emissions, this paper first used the Multi-Regional Input–output (MRIO) model to study the SO2 emissions caused by ECFuP during 2003–2011. Then, this paper uses Structural Decomposition Analysis (SDA) to decompose the factors affecting SO2 emission into technical effect, structural effect and scale effect. The results showed that (1) the amounts of China’s SO2 emissions caused by the ECFuP have increased (2003–2007), declined (2007–2009), and increased again (2009–2011). (2) Scale effect is the main factor that causes the increase of SO2 emissions in China; technical effect mainly resulted in a decrease of emissions, whereas structural effect has less impact. Specifically, from 2003 to 2011, scale effect increased domestic SO2 emissions by 2.2 million tons; technical effect and structural effect reduced by 2.4 million tons and 0.5 million tons of emissions, respectively. (3) For different regions, there is a positive correlation between the consumption of the ECFuP and China’s SO2 emissions. Among them, NAFTA (accounting for 33.77%) leads to the largest SO2 emissions, and OTHER EU (5.79%) is the least. (4) From the industrial aspect, some industries with relatively small ECFuP have caused high SO2 emissions. The specific performance is as follows, among the 17 industries, Electricity, Gas and Water Supply (EGW) only occupied 0.6% of the total ECFuP, but it has the largest SO2 emissions (55%); in contrast, while Electrical and Optical Equipment (EOE) occupied 42% of the total ECFuP, its SO2 emissions only accounted for 0.2% of the total. In 2003–2011, the export trade volumes of all the industries increased, but the growth rates of less polluted industries are higher than that of heavy polluted industries. Based on the above findings, the paper also proposed some policy recommendations.

Socioeconomic effects of pension spending: evidence from Spain

2020 ◽  
Vol 47 (5) ◽  
pp. 599-617
Author(s):  
Fernando Bermejo ◽  
Eladio Febrero ◽  
Andre Fernandes Tomon Avelino
Keyword(s):  
Peer Review ◽  
Social Protection ◽  
Pension System ◽  
Decomposition Analysis ◽  
Value Added ◽  
Total Output ◽  
Alternative View ◽  
Input Output ◽  
Structural Decomposition Analysis ◽  
Content Type

PurposeThe purpose of this study is to provide broader understanding of the significant role that the pension system has in the Spanish economy by estimating the sectoral production, employment and income sustained by pensioners' consumption.Design/methodology/approachBased on input–output tables by the World Input–Output Database and consumption data from the Household Budget Survey by the Spanish Statistical Office, a demoeconomic model is applied to quantify the direct impacts, indirect impacts from interindustry links and induced impacts from income–consumption connections over a nine-year period (2006–2014). Then, the factors driving the evolution of total output, employment and value added during such period have been examined by using structural decomposition analysis.FindingsThe growing participation of consumption by pensioner households in final demand had proven crucial during the 2008 crisis to alleviate the negative trend in production and employment derived from the collapse in consumption suffered by the rest of households.Practical implicationsDetermining the underlying factors driving changes in both employment and income during the 2008 crisis can be of interest in political decision-making on the sustainability of the Spanish pension system.Social implicationsThe results of estimating both the employment and income supported by pensioners' consumption reveal the significant stabilizing effect of the public spending on pensions, particularly during the 2008 crisis.Originality/valueThe current Spanish approach of attaining the pension system sustainability by merely reducing social protection costs ignores the adverse consequences of a lower pensioners' demand. This paper addresses an alternative view in which pension spending is not considered a burden on economic growth but rather a means of improving the level of production and employment.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2019-0047

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