What Separates the World’s Strongest City Economies Is Structural Depth

Market size, economic vitality and business environment account for roughly two-thirds of what separates the strongest G7 city economies in a new comparative assessment. New York, London and Tokyo lead not because of one exceptional metric, but because their advantages extend across several of the most heavily weighted dimensions.

Published in Axioms, "Measuring Urban Economic Performance in G7 Countries Through a Novel Grey-Based Multi-Criteria Framework" by Sarfaraz Hashemkhani Zolfani, Ahmet Şengönül, Şerife Merve Koşaroğlu, Berrak Tekgün and Özcan Işık evaluates 16 G7 cities while explicitly accounting for uncertainty in both economic data and expert judgments. Its sharper insight is that the top performers are clearly distinguishable, while much of the middle ranking is too close to treat as a definitive hierarchy.

The strongest cities win across several economic fronts at once

New York's first-place position reflects breadth rather than dependence on one overwhelming advantage. It ranks first in market size, economic vitality and business environment, combining scale, financial-market depth, corporate concentration and a highly developed ecosystem for business activity.

London follows a different route to the top. It leads in human capital and ease of doing business, while maintaining sufficiently strong performance across the other major dimensions to secure second place overall. Tokyo, ranked third, combines high economic vitality and human capital with a strong market-size position, producing a more balanced profile across the most influential criteria.

The contrast at the lower end reinforces the same lesson. Fukuoka, Milan and Osaka do not rank poorly because of one catastrophic weakness; their lower positions reflect shortcomings across several criteria, particularly those carrying heavier weight in the model. Strong performance in a less influential dimension is therefore not always enough to offset weakness in market scale, business depth or economic vitality.

Urban competitiveness, in this framework, looks less like a race to maximize one indicator and more like a problem of building complementary capabilities. A large economy without strong corporate depth can underperform, while good business regulation alone may have limited effect when the surrounding market, labor and financial ecosystem remains comparatively weak. The policy implication is a shift away from narrow score-chasing toward coordinated economic capacity building.

Market size still matters, but business depth increasingly separates the leaders

The researchers assessed six dimensions derived from the Global Power City Index: market size, market attractiveness, economic vitality, human capital, business environment and ease of doing business. Market size received the highest weight, followed closely by economic vitality and business environment, while the remaining dimensions contributed less to the final ordering.

Market size captures both the scale and productivity of the urban economy, while economic vitality reflects financial depth and the presence of major corporations. Business environment incorporates conditions such as wage structures, access to skilled workers and workplace options, making it less about regulation alone and more about whether companies can actually operate and expand effectively.

The weighting pattern suggests that G7 cities are differentiated more strongly by structural economic assets than by institutional conditions that are already relatively mature across advanced economies. Regulatory quality still matters, but differences in market depth, corporate concentration and productive ecosystems may provide greater separation among cities operating within broadly comparable national systems.

Policymakers should not interpret the weights as estimates of what would happen if spending increased in any one area. The authors stress that they represent expert judgments about relative importance, not causal estimates of the economic return from specific interventions. A city cannot assume that improving one criterion by a given amount will automatically produce a predictable movement in its overall economic position.

The ranking becomes more revealing when uncertainty is allowed to remain visible

Many city rankings produce precise-looking league tables even when the underlying data, weighting decisions and yearly performance vary substantially. The study addresses that problem using "grey" numbers, which represent uncertain information as bounded intervals rather than forcing every observation or expert judgment into a single precise value.

For each city and economic dimension, the researchers used the minimum and maximum GPCI scores recorded between 2021 and 2025. Expert judgments were also retained as ranges rather than compressed into an artificial consensus, allowing disagreement and temporal variation to pass through the analytical process.

Robustness testing is where the approach becomes particularly informative. Across 100,000 simulations in which model parameters varied jointly, New York occupied first place in about 74% of runs, while New York and London together accounted for 96.8% of all first-place outcomes. The same three cities occupied the bottom three positions in roughly 86.9% of simulations.

The middle of the ranking is much less certain. Several cities shift across broad ranges when assumptions change, and the authors caution against drawing strong conclusions from adjacent positions. A seventh-place city should not automatically be treated as meaningfully stronger than an eighth-place city when the underlying uncertainty makes their performance statistically difficult to separate.

This turns the ranking from a publicity tool into something closer to a diagnostic instrument. Instead of asking only where a city stands, officials can ask which weaknesses are genuinely structural, which improvements could plausibly shift performance and whether any apparent change is large enough to exceed measurement uncertainty.

Urban strategy needs diagnostics, not another league table

The study's methodological contribution is the development of Grey RANCOM for determining criterion weights and Grey MUNRA for ranking cities. The framework combines expert knowledge with objective secondary data while preserving uncertainty through both stages, an approach the authors present as a new application of the two methods in an interval-grey setting.

For governments, the practical appeal lies in identifying where economic weakness actually sits. A city constrained by limited market size faces a different strategic problem from one with a strong market but weaker human capital or business conditions, and treating both with the same generic competitiveness package would obscure those differences.

The framework also has relevance for investors and development agencies because it distinguishes stable competitive gaps from marginal ranking differences. Large and persistent separations deserve more attention than small shifts among neighboring positions, particularly when location decisions involve infrastructure, labor-market access and long-term capital commitments rather than annual score movements.

It is important to note that the study covers only G7 cities represented in the GPCI, making the sample relatively homogeneous and limiting how confidently the weighting structure can be transferred to emerging or developing economies. All performance data also come from one index, meaning any weaknesses in its scoring and standardization procedures flow into the new model.

The analysis is also restricted to economic performance. Research and development, accessibility, environment, cultural interaction and livability fall outside the framework, so the results should not be read as a ranking of overall urban quality or sustainability.

Future research could test whether the same economic priorities emerge in cities across Asia, Africa, Latin America and other non-G7 settings, where institutional capacity, informality, infrastructure and demographic pressures differ substantially. Larger expert panels, longer time series and independent indicator systems could also strengthen confidence in the weighting structure and reduce dependence on extreme annual observations.

The broader lesson is that urban economic strength is cumulative. Leading cities tend to combine scale, corporate and financial depth, skilled labor and business-supporting institutions rather than relying on a single competitive advantage. For policymakers, the most useful ranking is therefore not the one that produces the neatest league table, but the one that reveals which structural weaknesses are large enough to warrant intervention and which apparent gaps are too uncertain to justify policy conclusions.