The concentration of this economic activity in one area (usually a city center) allows for the growth and expansion of activity into other and surrounding areas because of
the cost-minimizing location decisions of firms within these agglomeration economies to sustain high productivity and advantages which therefore allow them to grow outside of the city (core) and into the periphery.
At the foundational level, proximity – especially to other facilities and suppliers – is a driving force behind economic growth and is one explanation for why agglomeration
effects are so evident in major urban centres.
If localization economies were the main factor contributing to why cities exist with the exclusion of urbanization economies, then it would make sense for each firm in the
same industry to form its city.
The second benefit is the development of industries due to the increasing returns to scale in intermediate inputs for a product, and the third source is the relative ease
of communication and exchange of supplies, laborers, and innovative ideas due to the proximity among firms.
 Another source of agglomeration diseconomies—higher crowding and increased waiting time—can be observed in disciplines or industries that are characterized by constrained
access to relevant production facilities or resources.
 Advantages of agglomeration When firms form clusters of economic activity, particular development strategies flow in and throughout this area of economic activity.
 Furthermore, agglomerated centres of production, like cities, also facilitate learning – that is, knowledge generation, diffusion, and accumulation – on a larger scale
than smaller economic regions.
This technological impact, specifically in the communications field, will provide and dismiss the barrier between firms in the same industry located further away and nearby,
leading to a greater concentration of information flow and economic production and activity.
These increasing returns to scale “give rise to [urban systems]”, capturing “the trade-off between transportation costs and economies of scale”.
 Moreover, massive urban areas like cities, which contain a multitude of industries in a localised area, can help firms offset their reaction to shocks more efficiently
by ‘pooling’ labour resources together.
Large cities experience these problems, and this tension between agglomeration economies and agglomeration dis-economies may contribute to the area’s growth, control the growth
of the area, or cause the area to experience a lack of growth.
In that case, there are no networking linkages and therefore makes it difficult for all firms in the area to obtain resources and increase production.
The decreased transportation costs associated with the clustering of firms lead to an increase in the likelihood of a core-periphery pattern; the result will be that more
intermediate inputs will be focused at the core and, therefore, will attract more firms in related industries.
A small decrease in the fixed cost of production can increase the range of locations for further establishment of firms leading to loss of concentration in the city and possibly
the development of a new city outside the original city where agglomeration and increasing returns to scale existed.
 While the concentration of economic activity in cities has a positive effect on their development and growth, cities, in turn, help foster economic activity by accommodating
population growth, driving wage increases, and facilitating technological change.
Increasing returns to scale are internal economies of scale to a firm, and may allow for establishing more of the same firm outside the area or region.
Furthermore, technological spillovers may be more beneficial to smaller cities in their growth than larger cities because of the existing informational networks that already
helped them form and grow.
 As stated above, these factors are what decrease the pricing power of firms because of the many competitors in the area as well as a shortage of labor and lack of flexibility
among firms to the laborers abound.
 • Labour pooling and matching: agglomerating effects, such as an increase in population and therefore human capital, arguably help improve matching within the economy,
 However, over-competition would hinder companies’ development and innovation, and also generate some social problems.
It provides increasing returns to scale for each of the firms located within that area because of the proximity to available sources needed for production.
Benefits arise from the spatial agglomeration of physical capital, companies, consumers and workers: • Low transport costs: physical proximity to other firms and centres
of production can minimise costs associated with transportation.
The capital flow and technology industry is concentrated within specific areas, and therefore, it is to the advantage of the firm to locate near these areas.
As more firms in related fields of business cluster together, their costs of production tend to decline significantly (firms have competing multiple suppliers; greater specialization
and division of labor result).
 Ellison and Glaeser argue that while this may be true for firms whose location decisions are highly sensitive to cost differences or geographic locations, such as the
wine industry, they find that only 20% of geographic agglomeration effects in the United States can be explained by “natural” cost advantages.
 • Knowledge spillovers: the accumulation of knowledge and human capital in concentrated areas like major urban centres can contribute to the sharing of production technologies
 Moreover, other studies have shown that when negative externalities like pollution are taken into account, agglomerated city centres are more likely to be dispersed over
a larger geographical area rather than be confined to a single, metropolis-like urban region.
This helps accumulate information and the flow of new and innovative ideas among firms to achieve what economists call increasing returns to scale.
New forms of technology can create problems and involve risk; the clustering of firms creates an advantage to reduce the uncertainty and complications involved with using
new technology through information flow.
The over-agglomeration in the city would affect agricultural production and cause unemployment problems.
[‘• Brueckner, Jan. “Lectures in Urban Economics.” 2011. The MIT Press
• O’Flaherty, Brendan. City Economics. Cambridge, Massachusetts. London, England. 2005. Harvard University Press
• Coe, Neil M., Kelly, Philip F., Yeung, Henry W.C. Economic
Geography: A Contemporary Introduction.’ Malden, Massachusetts. Oxford, United Kingdom. Victoria, Australia. 2007. Blackwell Publishing
• Bogart, William Thomas. The Economics of Cities and Suburbs. Upper Saddle River, New Jersey. 1998. Prentice
• Strange, William C., 2008, “urban agglomeration,” The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
• Venables, Anthony, 2008. “new economic geography,” The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
Ellison, Glenn; Glaeser, Edward L. (May 1999). “The Geographic Concentration of Industry: Does Natural Advantage Explain Agglomeration?”. The American Economic Review. 89 (2): 311–316. doi:10.1257/aer.89.2.311. JSTOR 117127 – via JSTOR.
o ^ Jump
up to:a b c d Puga, Diego (3 February 2010). “The magnitude and causes of agglomeration economies”. Journal of Regional Science. 50 (1): 203–219. doi:10.1111/j.1467-9787.2009.00657.x. S2CID 17848032 – via Wiley Online Library.
o ^ Combes, Pierre-Philippe;
Duranton, Gilles; Gobillon, Laurent (March 2011). “The identification of agglomeration economies”. Journal of Economic Geography. 11 (2): 253–266. doi:10.1093/jeg/lbq038 – via Oxford Academic.
o ^ Jump up to:a b Duranton, Gilles; Puga, Diego (August
2003). “Micro-foundations of urban agglomeration economies” (PDF). NBER Working Paper Series (9931): 1–61 – via National Bureau of Economic Research.
o ^ Glaeser, Edward (29 July 2011). “Cities, productivity, and quality of life”. Science. 333 (6042):
592–594. doi:10.1126/science.1209264. PMID 21798941. S2CID 998870 – via JSTOR.
o ^ Jump up to:a b Beckmann, Martin J (1995). Giersch, Herbet (ed.). “Economic Growth in a Central Place System”. Urban Agglomeration and Economic Growth. Publications
of the Egon-Sohmen-Foundation: 107–115. doi:10.1007/978-3-642-79397-4_4. ISBN 978-3-642-79399-8 – via SpringerLink.
o ^ Jump up to:a b “Economies of agglomeration”. SetThings. 3 November 2014. Retrieved July 22, 2017.
o ^ Glaeser, Edward L; Gottlieb,
Joshua D (December 2009). “The Wealth of Cities: Agglomeration Economies and Spatial Equilibrium in the United States”. Journal of Economic Literature. 47 (4): 983–1028. doi:10.1257/jel.47.4.983. S2CID 59054155 – via ProQuest.
o ^ Kyriakopoulou,
Efthymia; Xepappadeas, Anastasios (May 2017). “Atmospheric pollution in rapidly growing industrial cities: spatial policies and land use patterns”. Journal of Economic Geography. 17 (3): 607–634. doi:10.1093/jeg/lbw018. hdl:11585/580210 – via Oxford
o ^ Liang, Jiaochen; Goetz, Stephan J. (December 2018). “Technology intensity and agglomeration economies”. Research Policy. 47 (10): 1990–1995. doi:10.1016/j.respol.2018.07.006. S2CID 158504616.
o ^ “Model cities”. 2008. Retrieved April
o ^ Borowiecki, Karol J. (2015) Agglomeration Economies in Classical Music, Papers in Regional Science, 94(3): 443-68.
o ^ Romero, Jessie and Schwartzman. Inequality in and across Cities. Economic Brief. October 2018, No. 18-10. Federal
Reserve Bank of Richmond.
o ^ Collier, Paul (2018). The Future of Capitalism: Facing the New Anxieties. pps. 136-40. Penguin. ISBN 9780241333891
o ^ Hashmi, Shujahat Haider; Fan, Hongzhong; Fareed, Zeeshan; Shahzad, Farrukh (2021-03-01). “Asymmetric
nexus between urban agglomerations and environmental pollution in top ten urban agglomerated countries using quantile methods”. Environmental Science and Pollution Research. 28 (11): 13404–13424. doi:10.1007/s11356-020-10669-4. ISSN 1614-7499.
Byrne, Christopher D.; Targher, Giovanni (February 2022). “Non‐alcoholic fatty liver disease‐related risk of cardiovascular disease and other cardiac complications”. Diabetes, Obesity and Metabolism. 24 (S2): 28–43. doi:10.1111/dom.14484. ISSN 1462-8902.
Tao, Jing; Wang, Ying; Zameer, Hashim (2023-03-24). “Can urban spatial structure adjustment mitigate air pollution effect of economic agglomeration? New evidence from the Yangtze River Delta region, China”. Environmental Science and Pollution Research.
doi:10.1007/s11356-023-26561-w. ISSN 1614-7499.
o ^ Shiu, Alice; Lam, Pun-Lee (2004-01-01). “Electricity consumption and economic growth in China”. Energy Policy. 32 (1): 47–54. doi:10.1016/S0301-4215(02)00250-1. ISSN 0301-4215.
o ^ Fuerst, Franz;
Warren-Myers, Georgia (2018-08-01). “Does voluntary disclosure create a green lemon problem? Energy-efficiency ratings and house prices”. Energy Economics. 74: 1–12. doi:10.1016/j.eneco.2018.04.041. ISSN 0140-9883.
o ^ Williamson, Jeffrey G. (July
1965). “Regional Inequality and the Process of National Development: A Description of the Patterns”. Economic Development and Cultural Change. 13 (4, Part 2): 1–84. doi:10.1086/450136. ISSN 0013-0079.
o ^ Deiwiks, Christa; Cederman, Lars-Erik; Gleditsch,
Kristian Skrede (March 2012). “Inequality and conflict in federations”. Journal of Peace Research. 49 (2): 289–304. doi:10.1177/0022343311431754. ISSN 0022-3433.
o ^ Lessmann, Christian (2014-01-01). “Spatial inequality and development — Is there
an inverted-U relationship?”. Journal of Development Economics. 106: 35–51. doi:10.1016/j.jdeveco.2013.08.011. ISSN 0304-3878.
o ^ Wu, JunJie (2019-10-05). “Agglomeration: Economic and Environmental Impacts”. Annual Review of Resource Economics.
11 (1): 419–438. doi:10.1146/annurev-resource-100518-094151. ISSN 1941-1340.
o ^ Takeuchi, Ai; Seki, Erika (2023-02-01). “Coordination and free-riding problems in the provision of multiple public goods”. Journal of Economic Behavior & Organization.
206: 95–121. doi:10.1016/j.jebo.2022.11.022. hdl:11094/73432. ISSN 0167-2681.
o ^ Aghion, Philippe; Cai, Jing; Dewatripont, Mathias; Du, Luosha; Harrison, Ann; Legros, Patrick (2015-10-01). “Industrial Policy and Competition”. American Economic
Journal: Macroeconomics. 7 (4): 1–32. doi:10.1257/mac.20120103. ISSN 1945-7707.
Photo credit: https://www.flickr.com/photos/rocketjim54/4932735566/’]