by Gabriel Ahlfeldt (London School of Economics, LSE), Stephen Redding (Princeton University), Daniel Sturm (LSE) and Nikolaus Wolf (Humboldt University Berlin)
The full post and online access to the full article is available on the Microeconomic Insights website
Economic activity is highly unevenly distributed across geographical space. This is reflected in the existence of cities as well as the concentration of economic functions in specific locations within cities, such as Manhattan in New York and the Square Mile in London. Understanding the strength of the forces of agglomeration that underlie these concentrations of economic activity is central to a range of policy questions.
What makes cities thrive? Is it proximity to natural resources – such as rivers, oceans, and energy sources – that make places attractive for firms to locate production? Is it shared amenities – such as leafy streets and scenic views – that make them attractive places for people to live? Or does the cumulative effect of growing population density itself make cities more productive, thereby attracting more firms and workers, boosting productivity further and raising demand for services, such as shops, cafés, and theatres?
Because of the complex history of many cities, identifying the sources of urban development is difficult. This study, for which its authors have recently been awarded the prestigious Frisch Medal, develops a model that shows a positive relationship between urban density and productivity growth in a virtuous circle of ‘cumulative causation’. The researchers then apply their model to the unique natural experiment of the construction and demolition of the Berlin Wall – and the impact on economic activity in neighbouring locations.
When Berlin was divided at the end of the Second World War, the western part lost access to the heart of the city; when the wall came down in 1989, the city was reunified. The researchers track the fortunes of West Berlin, which remained a market economy during the 41-year period of division, collecting data on employment, population, and rents between the 1930s and the 2000s.
They find that property prices and economic activity in the eastern side of West Berlin, close to the historic central business district in East Berlin, began to fall when the city was divided. Then, after reunification, the same area began to redevelop: West Berlin suddenly had access to all the knowledge and public resources in the resurgent central business district it had been denied. That spurred development in these areas, raising land prices close to the central business district and demonstrating the positive effect of exposure to density in neighbouring areas.
The model is successful in explaining the observed reorganisation of economic activity within West Berlin not only qualitatively but also quantitatively. What’s more, it has practical applications for urban planners making decisions on infrastructure and housing. For example, if a city is considering a subway, the model can be used to show how property prices are likely to increase.
The model also makes it possible to simulate what will happen to places that are close to proposed new infrastructure, and the potential economic spillovers to other locations. And it can show when improving one area is likely to hurt another area, when firms and workers might move away to better connected and more desirable locations.