University of Pennsylvania ScholarlyCommons Real Estate Papers Wharton Faculty Research 3-2007 Urban Evolutions: The Fast, the Slow, and the Still Gilles Duranton University of Pennsylvania Follow this and additional works at: https://repository.upenn.edu/real-estate_papers Part of the Real Estate Commons Recommended Citation Duranton, G. (2007). Urban Evolutions: The Fast, the Slow, and the Still. American Economic Review, 97 (1), 197-221. http://dx.doi.org/10.1257/aer.97.1.197 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/real-estate_papers/73 For more information, please contact [email protected]. Urban Evolutions: The Fast, the Slow, and the Still Abstract With the use of French and US data, new and systematic evidence is provided about the rapid location changes of industries across cities (the fast). Cities are also slowly moving up and down the urban hierarchy (the slow), while the size distribution of cities is skewed to the right and very stable (the still). The model proposed here reproduces these three features. Small, innovation-driven shocks lead to the churning of industries across cities. Then, cities slowly grow or decline following net gains or losses of industries. These changes occur within a stable distribution. The quantitative implications of the model are also explored. Disciplines Real Estate This journal article is available at ScholarlyCommons: https://repository.upenn.edu/real-estate_papers/73 Urban Evolutions: The Fast, the Slow, and the Still By GILLES DURANTON* With the use of French and US data, new and systematic evidence is provided about the rapid location changes of industries across cities (the fast). Cities are also slowly moving up and down the urban hierarchy (the slow), while the size distri- bution of cities is skewed to the right and very stable (the still). The model proposed here reproduces these three features. Small, innovation-driven shocks lead to the churning of industries across cities. Then, cities slowly grow or decline following net gains or losses of industries. These changes occur within a stable distribution. The quantitative implications of the model are also explored. (JEL R12, R32) A fundamental but much neglected issue in in the shadow of Eastman Kodak, came up with urban development is the role played by the a new process for making copies without the churning of industries across locations. Jane need for developing. The process, called xerog- Jacobs (1970) provides early anecdotal evi- raphy, made Rochester the new capital of the dence about what the key mechanisms at stake duplication industry in place of New York might be. In the late nineteenth century, New (again), where the previous dominant technol- York City was the capital of the photographic ogy, the varityper, was produced. These two industry, whereas Rochester, New York, was industries came to represent an important part of the leading city for precision instruments. Rochester’s employment. George Eastman, while working at improving Section I presents novel and systematic evi- optical instruments in Rochester, invented an dence that there is indeed considerable indus- emulsion-coating machine that enabled him to trial churning across cities. Industries move and mass-produce photographic dry plates. His cities experience rapid changes in the composi- company soon took over the market for photo- tion of their economic activity. This stylized graphic film. As a consequence, Rochester re- fact, the fast, is closely related to two better- placed New York as the main center for the known features of urban evolutions: the slow, industry. Rochester, 50 years later, was still the where cities move slowly up and down the capital of the US film industry, whereas New distribution of city sizes as they grow or decline York was that of the duplication industry. Then, relative to other cities; and the still, where the Haloid Company, a firm specialized in the man- size distributions of cities tend to be stable over ufacturing of photographic papers and operating time and skewed to the right. The model in Section II provides microeco- nomic foundations for the churning of indus- * Department of Economics, University of Toronto, 150 Saint George Street, Toronto, Ontario M5S 3G7, Canada tries across cities. Formally, it embeds an (e-mail: [email protected]; Web site: http:// extension of Gene M. Grossman and Elhanan individual.utoronto.ca/gilles/default.html). This is a much Helpman’s (1991) quality ladder model in an revised version of a paper previously circulated as “City urban framework. In each industry, research Size Distributions as a Consequence of the Growth Pro- firms try to invent the next step up the quality cess.” I am grateful to Vernon Henderson, Yannis Ioan- nides, Janet Kohlhase, Tomoya Mori, Henry Overman, John ladder in order to reap monopoly profits. Re- Parr, Diego Puga, Kwok Tong Soo, Dan Trefler, Hyoung search firms may be successful in their own Gun Wang, Fabrizio Zilibotti, conference and seminar par- industry or may develop a new leading quality ticipants, and four referees for helpful comments, sugges- in another industry. Local spillovers induce re- tions, and encouragement. I am also grateful to Pierre- Philippe Combes for sharing his data and helping me with search firms in an industry to co-locate with them. Funding from the Leverhulme Trust is gratefully production in the same industry and in most acknowledged. industries, successful innovators need to start 197 198 THE AMERICAN ECONOMIC REVIEW MARCH 2007 producing where they did their research. This economies and crowding (Stuart S. Rosenthal implies that own-industry innovations lead to a and William C. Strange 2004), it is possible to change of monopoly but to no change of loca- replicate the US and French urban systems very tion for an industry. By contrast, cross-industry closely. innovations imply not only a change of monop- There is a large urban growth literature that oly but also, typically, a change of location, builds on the trade-off between agglomeration since the old and new monopolies are not gener- economies and crowding (see Marcus Berliant ally located in the same city. Hence, innovation- and Ping Wang 2004, or J. Vernon Henderson driven shocks provide the basis for the growth and 2006, for surveys). Like this paper, this litera- decline of cities so that urban evolutions result ture often views purposeful innovative activity from the aggregation of small industry-level as a key engine of urban growth. Its main em- shocks. phasis, however, is on how the growth process The results derived in Section III show that, depends on urban agglomeration, and vice over a specific time period, a city typically versa, an issue that is intentionally left aside experiences employment gains in some sectors here. On the other hand, the spatial churning of and losses in others. Since gains and losses industries, the slow mobility of cities in the partially offset each other, net employment urban hierarchy, and their heterogeneity in pop- changes in cities are smaller than gross employ- ulation size are usually neglected in this ment flows, and cities move slowly up and literature.2 down the size distribution. Furthermore, these A second important strand of literature, changes occur within an approximately stable which dates back to Herbert Simon (1955), has right-skewed distribution of city sizes. Hence sought to generate distributions of city sizes that the model can replicate the three stylized facts would obey Zipf’s law. This literature, recently above. revived by the work of Xavier Gabaix (1999), is The quantitative predictions of the model are successful at generating realistic and stable dis- explored in Section IV using simulations. The tributions of city sizes with some mobility model is calibrated to replicate French and US within them. It has two main limitations. First, it city-size distributions. The simulations approx- ignores the churning of industries across cities, imate the US distribution well. The model does the main focus of this paper. Second, and more better than Zipf’s law according to a natural subtly, urban evolutions in this literature are efficiency criterion.1 For France, the perfor- driven by ad hoc exogenous shocks: amenity mance is also good. Interestingly, the model can shocks in Gabaix (1999), preference shocks in replicate the nonregular features of the French Juan-Carlos Co´rdoba (2003), and productivity and US Zipf’s curves like their concavity, al- shocks in Jan Eeckhout (2004) and Esteban though it exaggerates them. Rossi-Hansberg and Mark L. J. Wright (forth- These systematic deviations can be reduced coming). By contrast, the model presented here or eliminated altogether by considering a natu- offers detailed microeconomic foundations for ral extension of the model. In Section V, the technology shocks.3 Such microeconomic foun- returns to innovative activities in cities are af- dations are important because these shocks are fected by their size: positively, through (reduced- form) dynamic agglomeration economies, and 2 A possible exception is Duranton and Diego Puga negatively, through crowding. When agglomer- (2001), who examine the movements of firms from diver- ation economies dominate crowding, the prob- sified to specialized cities in steady state. Their focus is ability of innovating in a city increases more nonetheless different, since churning occurs across cities than proportionately to its size. This reduces the that keep the same population and sectoral structure. 3 Zipf’s coefficient in the upper tail and increases In a companion paper (Duranton 2006), a Zipf’s law model with detailed microeconomic foundations is pro- it in the lower tail. Under empirically plausible posed. This companion paper builds on the product prolif- values for the trade-off between agglomeration eration model of endogenous growth (Paul M. Romer 1990) instead of its quality ladder version. This companion model is unable to deal with the churning of industries—a crucial focus of the present paper—since existing industries never 1 Zipf’s law refers to the well-known empirical claim move.