Core-Periphery Models and Agglomeration Economies

Core-periphery models describe an uneven geography of economic development in which a wealthy, innovative core region has strong growth and a poorer periphery depends on it, and agglomeration economies are the cost savings and productivity gains that firms and workers enjoy when they locate close to each other. In brief: activity clusters because proximity makes it cheaper to share suppliers, workers and ideas. Gunnar Myrdal’s cumulative causation (1957) explains why advantages grow: the core attracts capital and skilled labor (“backwash effects”), which may leave the periphery behind, although growth can also spread outward (“spread effects”). Paul Krugman’s new economic geography (1991) shows how increasing returns and transport costs create a core and periphery even in a uniform space.

These ideas explain why some regions are rich and others are poor within the same country and across the world, and why policies to spread growth are difficult. This guide explains the core-periphery concept and its theories, the sources and limits of agglomeration, compares the types of economies in a table, works through calculations, outlines the history and corrects common mistakes.

What are core-periphery models?

The core-periphery idea appears at several scales. John Friedmann’s model (1966) proposed that regions develop through the growth of a dominant core with capital, innovation and political power, surrounded by regions that supply resources and labor and are controlled from the core. The Swedish economist Gunnar Myrdal described cumulative causation: an initial advantage (a port, a resource, a university) attracts firms and skilled workers, which creates a larger market, better services and more investment, which attracts still more, a positive feedback loop. The core draws investment and talent from the periphery (backwash effects), such as when rural youth move to cities. At the same time, growth in the core may create demand for goods and technology from other areas (spread effects). Albert Hirschman called these polarization and “trickle-down” effects. Myrdal expected that in poor, weakly governed countries the backwash would dominate, so market forces alone would increase inequality.

The model is applied to many scales: within a country (the London and southeast of England against the north; the Paris region; northern against southern Italy; the coast against the interior of China), within a continent (the “Blue Banana,” a corridor of dense urban and industrial development from northwest England through the Benelux countries and the Rhine valley to northern Italy) and globally (the high-income North as the core and the low-income South as the periphery). Immanuel Wallerstein’s world-systems theory adds a “semi-periphery.” Cores are characterized by high incomes, diverse economies, advanced services and innovation, and peripheries by lower incomes, dependence on primary products or low-wage manufacturing, and outflows of people.

What are agglomeration economies?

Alfred Marshall explained in 1890 why firms in the same industry cluster, and identified three sources, which are still the basis of the theory.

• Labor market pooling: a large pool of workers with specialized skills makes it easier for firms to hire and for workers to find jobs, and reduces the risk for both.
• Sharing of inputs: clusters support specialist suppliers, services and infrastructure that none of the firms could support alone.
• Knowledge spillovers: ideas spread when workers meet, move between firms and observe competitors, which supports innovation, as in Silicon Valley.

Economists distinguish localization economies (benefits from being near firms in the same industry, such as the finance district of London or the film industry in Hollywood) and urbanization economies (benefits from the size and diversity of a city, such as access to a large market, universities, airports and varied services). Studies find that, on average, doubling the size of a city raises its productivity by about 3 to 8%. Agglomeration also explains the “winner-takes-most” geography of knowledge industries, where a few cities capture a large share of high-wage jobs. In Krugman’s model, even small differences at the beginning can be amplified by economies of scale, and the economy “tips” toward a concentrated pattern when transport costs are in an intermediate range.

What limits agglomeration?

Concentration also creates agglomeration diseconomies: higher land prices and rents, congestion, longer commutes, pollution, higher wages, crime and strain on infrastructure. These costs eventually offset the benefits of size and push firms and people to move outward, leading to suburban growth, secondary centers and relocation to cheaper regions. Improvements in transport and communication change the balance: when travel is cheap, activities can spread out, and when face-to-face contact is important, they cluster. The rise of remote work and digital technology has not eliminated clustering, though it has altered patterns inside cities and regions.

What policies address regional imbalance?

Governments use regional policy to spread development: investment in infrastructure (transport, broadband), grants and tax incentives for firms in lagging regions, relocation of public institutions and universities, enterprise zones and “growth poles” (such as Brasília, planned in the 1950s), support for secondary cities, and education and training in the periphery. The European Union’s cohesion funds aim to reduce gaps between regions. Experience shows that such policies work better when they build on local strengths (clusters, institutions and skills) and not only on subsidies, and that improving transport links can sometimes help the core more than the periphery, by making it easier to serve the periphery from the core.

Types of agglomeration economies compared

Worked example: productivity and location quotients

The values are hypothetical and illustrate typical calculations.

1. Productivity and city size: suppose productivity rises with city population P according to productivity ∝ P^0.05. A city that is twice as large is 2^0.05 = 1.035 times as productive, a gain of 3.5%. A city ten times as large is 10^0.05 = 1.122 times as productive, a gain of 12.2%.

2. Wage effect: if the average wage in a city of 500,000 is 30,000 a year, a city of 5,000,000 with the same elasticity would have 30,000 × 1.122 = 33,660, which is 3,660 more.
3. Location quotient: the LQ = (regional employment in an industry ÷ total regional employment) ÷ (national employment in the industry ÷ total national employment). A region has 24,000 of 200,000 jobs in an industry (12%), and nationally the share is 4%. LQ = 12 ÷ 4 = 3.0, which suggests a strong cluster.

4. Core-periphery gap: the GDP per person is 48,000 in the core region and 19,200 in the periphery. The ratio is 48,000 ÷ 19,200 = 2.5, and the periphery has 19,200 ÷ 48,000 = 40% of the core’s level.

5. Catching up: if the periphery grows by 3.5% a year and the core by 1.5%, the gap closes when 19,200 × 1.035ⁿ = 48,000 × 1.015ⁿ, so (1.035 ÷ 1.015)ⁿ = 2.5, and n = ln 2.5 ÷ ln 1.0197 = 0.916 ÷ 0.01951 = about 47 years.
6. Multiplier of a high-tech job: the economist Enrico Moretti estimated that each job in the high-tech sector creates about five additional local jobs in other sectors. A new plant with 2,000 high-tech jobs would then support about 2,000 × 5 = 10,000 other jobs, and a total of 12,000.

How did the theories develop?

Johann Heinrich von Thünen (1826), Alfred Weber (1909) and August Lösch (1940) established the classic location theories, and Alfred Marshall wrote about industrial districts in 1890. François Perroux proposed growth poles in 1955, Myrdal and Hirschman wrote on cumulative causation and polarization in 1957–58, and Friedmann presented his core-periphery model in 1966. Paul Krugman’s 1991 paper “Increasing Returns and Economic Geography” led to the new economic geography and earned him the Nobel Prize in Economics in 2008. Since the 1990s, Michael Porter’s cluster theory and empirical studies of agglomeration have influenced policy. Current debates concern the spatial effects of globalization, the geography of knowledge and platform companies, and “left-behind” regions.

Which mistakes are common?

Mistake 1: Thinking that markets automatically spread growth from the core

Spread effects can occur, but backwash and cumulative advantage often widen gaps, particularly without good institutions and infrastructure.

Mistake 2: Equating agglomeration with large cities only

Clusters can be small, such as a specialized industrial district. Localization economies depend on the concentration of one industry, not on city size.

Mistake 3: Believing that agglomeration always grows

Congestion and high costs create limits and push firms to relocate, and new technologies can change where firms need to be.

Mistake 4: Treating the periphery as a single type

Peripheral regions differ widely: some are resource-rich, some are remote, some are former industrial areas. Policies need to fit local conditions.