Why Urban Quality of Life, Not Just Wages, Drives City Growth
Ahlfeld, Bald, Roth & Seidel: "Measuring the Urban Quality of Life Premium" CRC Discussion Paper No. 544
More than half of the world’s population now resides in cities. In developed countries, the urban share is substantially higher, while in developing nations it is rapidly increasing. Productivity advantages and the corresponding wage premia have long been identified as fundamental drivers of urbanization, dating back to Marshall’s seminal work in 1890. Extensive empirical evidence confirms that productivity is higher in cities, making them attractive places to work. Cities also offer a range of urban amenities—such as ethnic restaurants, music venues, and art galleries—that make them appealing places to live. In contrast, rural areas tend to attract residents through their environmental or natural amenities, including clean air, forests, and lakes. Economists refer to the overall effect of these amenities on the perceived desirability of a location as quality of life (QoL). While there exists a rich literature on the measurement of QoL, relatively little is known about whether cities tend to exhibit higher QoL than rural areas—that is, whether there exists a positive urban QoL premium. In a recent paper, Gabriel Ahlfeldt (HU Berlin, Project B10), Fabian Bald (Viadrina University), Duncan Roth (Institute for Employment Research), and Tobias Seidel (University of Duisburg-Essen) argue that the lack of evidence for such a premium may be due to measurement error.
Measuring QoL empirically is challenging because many of its determinants are unobservable or difficult to quantify. Economists therefore rely on spatial equilibrium models to infer unobserved QoL from observed wages and living costs. In the canonical framework, all non-housing goods are assumed to be freely tradable, and workers are considered homogeneous and perfectly mobile. Under these assumptions, migration equilibrates wage and housing price differences across locations, such that any remaining variation reflects differences in QoL.
However, this canonical approach neglects spatial frictions. Trade frictions, for instance, can generate local differences in non-housing prices that are unrelated to QoL. Similarly, mobility frictions—such as idiosyncratic preferences, family ties, or social connections—may prevent workers from relocating even when wage differentials exist.
By explicitly incorporating these spatial frictions, the authors show that quantitative spatial models can reduce measurement error in QoL estimates. Their theoretical analysis confirms that the canonical model systematically underestimates differences in QoL between locations, with the measurement error being particularly pronounced in large cities. A decomposition analysis reveals that this bias arises more from mobility frictions than from trade frictions. The findings are robust to parameter variation, suggesting that the results are likely to generalize across countries.
To construct the first theory-based QoL ranking that accounts for spatial frictions, the authors apply their model to detailed German data from Immoscout24, the Federal Employment Agency, and the Federal Statistical Office. The application produces greater variation in QoL across regions and substantial changes in rankings relative to the canonical model. For 2015, Hamburg surpasses Munich as the city with the highest QoL. Frankfurt rises to fourth place, Düsseldorf climbs seven ranks to fifth, while Chemnitz advances by 62 places to 39th, and Lörrach drops by 49 places to 86th. Berlin (3rd) and Höxter (131st) remain unchanged. On average, the absolute rank change is 17. Over time, Munich and Hamburg have alternated between first and second place—Munich leading in 2007, Hamburg in 2011, again Hamburg in 2015, and Munich in 2019—while Berlin has steadily closed the gap, moving from fourth in 2011 to third in 2015. An interactive web tool allows users to explore these QoL rankings over time for any pair of German cities.
The authors’ model also uncovers a pronounced urban QoL premium in Germany: doubling a region’s population is associated with a 20% increase in QoL, whereas the corresponding wage increase is no more than 5%.
The findings suggest that QoL is a far more important determinant of regional economic success than previously assumed. This has strong implications for regional policy. While efforts to enhance productivity in lagging regions remain crucial, improving QoL is equally vital. Policy strategies might include investments in cultural and recreational infrastructure, reductions in pollution and crime, and improvements to the urban built environment.
As a practical contribution, the authors provide an open-access GitHub toolkit that computes the new QoL measure using parsimonious data inputs. While the fully theory-consistent version requires richer data, a simplified population-based variant still substantially reduces measurement error relative to the canonical approach. The toolkit can help policymakers identify areas with objectively low QoL and better understand the factors driving spatial differences in well-being and economic prosperity.
Link (pdf): Measuring the Urban Quality of Life Premium
