Urbanization and Economic Complexity

Low urbanization
Mid-low urbanization
Mid-high urbanization
High urbanization

It is an established fact that urbanization in developed countries accompanies economic growth and industrialization in a mutually self-reinforcing cycle. This historic pattern generates expectations of a virtuous circle between economic growth and urbanization regardless of local conditions. Yet this expectation poses a dilemma: why, given similar urbanization rates, does Asia contain explosive economies while sub-Saharan Africa has seen very little growth?

We tackle this puzzle by coupling the World Trade Web (WTW) with urbanization levels for 144 countries from 1995-2010, using the Economic Complexity framework to capture how urbanization fingerprints countries' productive systems through the lens of their exports. The "Fitness" metric quantifies a country's competitiveness based on the diversity and sophistication of its export basket, while "Complexity" measures the capabilities required to produce each product.

Our analysis reveals a striking asymmetry. In rural economies (urban population below 60%), increases in urban population foster structural changes in industrial exports—boosting diversification, improving fitness, and enabling the export of more complex products. But in already-urbanized countries, this reciprocal relation between economic growth and urbanization fades away, becoming negligible for resource-dependent economies where urbanization is decoupled from any structural economic transformation.

The Virtuous Circle—And Its Limits

Representing the WTW as a bipartite network—countries connected to products via Revealed Comparative Advantage (RCA)—we find that highly urbanized countries export a wide range of complex products (textiles, heavy manufacturing, IT), while rural countries concentrate on low-sophistication goods (raw materials, agricultural products). Crucially, starting from 2005, we observe rural countries shifting their export baskets toward higher complexity products.

Using network motif analysis to track the evolution of trade topology, we can identify which rural countries are successfully transforming their productive systems versus those experiencing "urbanization without industrialization." Sub-Saharan Africa presents both patterns: some countries show the virtuous circle fostering structural change, while others—particularly oil-dependent economies like Qatar, Kuwait, Gabon, and Libya—have achieved high urbanization through policy decisions without any corresponding transformation in their export baskets.

Economic complexity and urbanization correlation

The fitness ranking provides a stable metric for tracking these transformations. Countries that successfully couple urbanization with economic development show correlated growth in both urban population and fitness ranking (R² = 0.53), while GDP-based metrics fail to capture this structural relationship. This finding has profound implications for development policy: urbanization alone is not sufficient for economic development—it must be accompanied by structural transformation in the productive system.

Research Metrics

Altmetric Attention

Citations

References

Di Clemente, R., Strano, E. & Batty, M.

Urbanization and Economic Complexity

Scientific Reports, 11, 3952 (2021)

Python implementation of the Bipartite Configuration Model (BiCM)

BiCM - Statistical null model for undirected and binary bipartite networks

Python, R and Matlab implementation of the bmotifs package

bmotifs - Motif analysis for bipartite networks