scholarly journals Systematisation of factors behind the agglomeration effect

2022 ◽  
Vol 22 (4) ◽  
Author(s):  
Yuriy Pavlov
Keyword(s):  
Agglomeration Effect

scholarly journals The Impact of Environmental Regulation on the Location of Pollution-Intensive Industries in China under Agglomeration Effect

2021 ◽  
Vol 18 (8) ◽  
pp. 4045
Author(s):  
Yinhao Wu ◽  
Shumin Yu ◽  
Xiangdong Duan
Keyword(s):  
Environmental Regulation ◽  
Local Economic Development ◽  
Negative Impact ◽  
Empirical Test ◽  
Mediating Effect ◽  
Production Costs ◽  
Agglomeration Effect ◽  
The Government ◽  
Pollutant Discharge ◽  
The Impact

Pollution-intensive industries (PIIs) have both scale effect and environmental sensitivity. Therefore, this paper studies how environmental regulation (ER) affects the location dynamics of PIIs under the agglomeration effect. Our results show that, ER can increase the production costs of pollution-intensive firms (PIFs) by internalizing the negative impact of pollutant discharge in a region, and thus, directly reduces the region’s attractiveness to PIFs. Meanwhile, ER can indirectly reduce the attractiveness of a region to PIFs by reducing the externality of the regional agglomeration effect. Moreover, these influences are regulated by the level of local economic development. Based on the moderated mediating effect model, we find evidence from the site selection activities of newly built chemical firms in cities across China. The empirical test shows that compared with 2014, the proportion of the direct effect of ER to the total effects significantly decreased in 2018, while the proportion of indirect effects under the agglomeration effect increased significantly. Our findings provide reference for the government to design effective environmental policies to guide the location choice of new PIFs.

scholarly journals Agglomeration and Urban Manufacture Labor Productivity in Indonesia

2019 ◽  
Vol 8 (2) ◽  
Author(s):  
Yohanes Nurcahyo Agung Wibowo ◽  
Toshihiro Kudo
Keyword(s):  
Labor Productivity ◽  
Industrial Development ◽  
Manufacturing Industry ◽  
Negative Impact ◽  
Industrial Clusters ◽  
Economic Conditions ◽  
Agglomeration Effect ◽  
Positive Externalities ◽  
The Government ◽  
Input Sharing

Agglomeration, the spatial concentration of industries in a specific location, has been argued to improve productivity since it could provide positive externalities such as knowledge spillover, input sharing, and labor pooling. This paper examines the effect of large and medium manufacturing industry (LMI) agglomeration on labor productivity. Measuring the output and labor density as agglomeration effect by using 2009-2014 panel data from 44 cities and regions across the metropolitan areas of Indonesia, this study shows that in terms of output share, agglomeration positively contributes to labor productivity. On the other hand, in terms of labor density, agglomeration results in a negative impact on productivity. These findings suggest the government should expand industrial clusters in less densely populated areas, especially outside the island of Java, by providing necessary infrastructures such as electricity, ports, and roads, so that this development creates favorable economic conditions for investment and industrial development in such areas.

scholarly journals Study on Agglomeration Level and Effect of Equipment Manufacturing Industry in the Yangtze Delta Urban Agglomeration

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Min Zhou ◽  
Sheng Li ◽  
Yu Wu
Keyword(s):  
Yangtze River ◽  
Manufacturing Industry ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
The Yangtze River ◽  
Agglomeration Effect ◽  
Equipment Manufacturing ◽  
Equipment Manufacturing Industry ◽  
The Yangtze River Delta

This paper analyzes the agglomeration level and agglomeration effect of 8 subindustries of equipment manufacturing industry and 26 prefecture-level cities in the Yangtze River Delta (YRD). From the perspective of industry, the agglomeration change trend of 8 subsectors of equipment manufacturing industry from 2006 to 2016 in the Yangtze River Delta Urban Agglomeration (YRDUA) is analyzed. From the perspective of cities, the spatial differences of equipment manufacturing agglomeration degree in 26 prefecture-level cities in the YRDUA are discussed. By using CES production function, the agglomeration effect of equipment manufacturing agglomeration is studied. The results show that the YRDUA has formed an agglomeration pattern of equipment manufacturing industry, with Shanghai as the core, and Hefei, Hangzhou, Suzhou, and Nanjing as the auxiliary cities, and the overall agglomeration effect in the region is relatively obvious.

Features of Agglomeration Effect of Regional Spatial System

2021 ◽  
pp. 1415-1427
Author(s):  
Yuriy A. Salikov ◽  
Natalia I. Kuzmenko ◽  
Irina S. Zinovyeva ◽  
Elena V. Korolyuk
Keyword(s):  
Agglomeration Effect ◽  
Spatial System

scholarly journals Does Population Mobility Contribute to Urbanization Convergence? Empirical Evidence from Three Major Urban Agglomerations in China

2020 ◽  
Vol 12 (2) ◽  
pp. 458 ◽  
Author(s):  
Feng Wang ◽  
Wenna Fan ◽  
Xiangyan Lin ◽  
Juan Liu ◽  
Xin Ye
Keyword(s):  
Pearl River Delta ◽  
High Growth ◽  
Yangtze River Delta ◽  
High Growth Rate ◽  
River Delta ◽  
Population Mobility ◽  
Urban Agglomerations ◽  
Agglomeration Effect ◽  
The Pearl River ◽  
The Yangtze River Delta

Population mobility accelerates urbanization convergence and mitigates the negative impact of the spatial agglomeration effect on urbanization convergence, which is the most important conclusion in this paper. Taking 38 cities in China’s three urban agglomerations (the Yangtze River Delta, the Pearl River Delta, and the Beijing–Tianjin–Hebei region) from 2005 to 2016 as research subjects, the study first shows that there is a large gap in the level of urbanization between the three major urban agglomerations, but the gap has been constantly narrowed and presents a trend of absolute convergence and conditional convergence. Furthermore, without adding a population mobility variable, the combination of the diffusion effect of high-urbanization cities and the high growth rate of low-urbanization cities causes the inter-regional urbanization level to be continuously convergent in the Yangtze River Delta region; however, the combination of the agglomeration effect of high-urbanization cities and the high growth rate of low-urbanization cities causes the inter-regional urbanization to be divergent in the Pearl River Delta and the Beijing–Tianjin–Hebei region. Under the influence of population mobility, the “catch-up” effect in low-urbanization regions is greater than the agglomeration effect in high-urbanization regions, which promotes the continuous convergence of inter-regional urbanization.

Agglomeration and innovation: Selection or true effect?

2019 ◽  
Vol 52 (2) ◽  
pp. 423-448
Author(s):  
Li Fang
Keyword(s):  
Cost Effectiveness ◽  
Quantile Regression ◽  
Selection Effect ◽  
Cost Benefit ◽  
Ordinary Least Squares ◽  
Least Squares Regression ◽  
Firm Innovation ◽  
Industrial Policies ◽  
Agglomeration Effect ◽  
Patent Applications

This paper separates two mechanisms through which agglomeration increases average firm innovation: selection (less innovative firms being forced out of agglomerations) and true agglomeration (firms become more innovative). I apply a quantile regression to estimate the distribution of firm innovation and separate these two mechanisms. Linking a unique establishment-level dataset with the patent dataset in the state of Maryland for the period 2004–2013, I find that a 1-mile radius area with above-median employment concentration significantly encourages firm innovation. An average establishment that files for at least one patent during the study period increases citation-weighted patent applications by 31.2% to 31.5% in such employment centers. I also find evidence of selection: non-innovators are 1.3% less likely to survive in agglomerations. The coexistence of agglomeration and selection causes the result of an ordinary least squares regression to be upwardly biased. By eliminating the selection effect, this study more precisely estimates the agglomeration effect, which can be applied to cost–benefit and cost-effectiveness analyses of urban and industrial policies.

scholarly journals The Influences of Acoustic and Pulsed Corona Discharge Coupling Field on Agglomeration of Monodisperse Fine Particles

2020 ◽  
Vol 10 (3) ◽  
pp. 1045
Author(s):  
Mingchun He ◽  
Zhongyang Luo ◽  
Haolin Wang ◽  
Mengxiang Fang
Keyword(s):  
Corona Discharge ◽  
Fine Particles ◽  
Reduction Ratio ◽  
Pulsed Corona Discharge ◽  
Coupling Field ◽  
Pulse Input ◽  
Agglomeration Effect ◽  
Pulsed Corona ◽  
Low Efficiency ◽  
Discharge Field

In view of the low efficiency of traditional electrostatic precipitators in removing fine particles, acoustic and pulsed corona discharge coupling fields were proposed to increase particle size. In this paper, monodisperse particles with three different sizes (0.5 μm, 2 μm, and 4 μm) were generated to investigate the agglomeration effect under different parameters in external fields. A larger reduction ratio of particle number concentration resulted in a higher agglomeration efficiency. Results indicated that, in the range from 800 to 2400 Hz, the acoustic agglomeration effect on 4-μm particles was better than that on 0.5-μm and 2-μm particles. In the pulsed corona discharge field, agglomeration efficiencies of the three particle sizes were lower than those in the acoustic field. However, application of the coupling field highly improved agglomeration efficiency compared with the single field. When a pulse input voltage of 50 kV with acoustic sound pressure level (SPL) of 143 dB and frequency of 1600 Hz was selected, the corresponding number reduction ratio of 0.5-μm, 2-μm, and 4-μm particles increased to 0.464, 0.526, and 0.918 from 0.254, 0.438, and 0.814 in the acoustic wave field and 0.226, 0.385, and 0.794 in the pulsed corona discharge field.

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