Although theoretical models provide the foundations for examining the equilibrium spatial configuration of polycentric cities, they are not immediately applicable to producing empirically testable comparative static predictions. Recent empirical works at smaller spatial scales show that it is very important to understand a firm’s location choice at a given zip code within the same metro city. A general conclusion of these studies is that firms may agglomerate at zip code or county level for usual reasons such as input sharing and labor pooling in a given location. Evidence on the US counties suggests that agglomeration due to input sharing is only present at the state level and not at county or zip code level while the idea of labor pooling makes firms agglomerate at all levels. By contrast, knowledge spillovers significantly affect agglomeration at the zip‐code level but not so much at county or state level. Theory suggests that the benefits of agglomeration diminish rapidly with distance and empirical research seems to hint that this decay function varies by the source of agglomeration economies. Particularly, evidence on the US counties reveals that the decay of knowledge spillovers with distance occurs much more rapidly vis‐à‐vis that of input sharing.<sup>19</sup> One paper that elegantly ties theory with empirics is that by Daniel McMillen and Stefani Smith.<sup>20</sup> Their study derives tractable predictions from the Fujita and Ogawa (1982) model regarding the relationship between an urban area’s population, commuting costs, and its number of sub‐centers. Using 1990 data on large US urban areas, the authors test the predictions of Fujita and Ogawa, whose simulations suggest that the equilibrium number of sub‐centers is likely to increase with population and the unit cost of commuting. Controlling for other variables affecting urban form, such as the median income in the urban area and the age of the central city, McMillen and Smith find very strong support for theory, with population and commuting costs accounting for nearly 80% of the variation in the number of sub‐centers across the urban areas.<sup>21</sup> 19 Studies at higher spatial level include Glaeser et al. (1992), Henderson et al. (1995), Rosenthal and Strange (2004) while a recent study by Agarwal et al. (2012) makes a descriptive attempt to understand agglomeration at sub‐city level in Los Angeles. There are few examples of studies at zip code level by Rosenthal and Strange (2001, 2003); Kolko (2010); De Silva and McComb (2011). Besides, spatial decay in externalities and spillovers, Redfearn (2007b) notes that the stability in subcenter employment in Los Angeles may be associated with historical path dependence. However, path dependence cannot entirely explain the rise of subcenters in the last few decades.

20 McMillen and Smith (2003) is an empirical application of Fujita and Ogawa (1982). The analysis also brings to light the fact that several theoretical papers have highlighted the role of commute costs (such as Lucas and Rossi‐Hansberg, 2002) and population size (e.g. Fujita and Mori, 1997) in determining the urban form.

21 Much of the recent literature actually suggests there is a lot of persistence in urban patterns. Bleakley and Lin (2012) document the consistent and persistent development of cities in the US along a fall line. Similarly, Redfearn (2009) finds that the most important predictor of clusters of de‐centralized jobs in Los Angeles in 2000 in a location is the presence of decentralized jobs in the same location in 1980. Thus, history has much to determine the current state of land use in a given city. For instance, the existence of a number of subcenters for a port city may well be explained by its evolution. Starting from the initial port site, expansion of the port results from technological innovations in maritime engineering and improvements in cargo handling. This marks the beginning of changing spatial relationships between the port and the urban core, as docks are built further away from the CBD due to congestion and space limitation. In the later stages of port development, increased specialization of cargo handling, growing sizes of ships, and ever increasing demands for space for cargo‐handling and storage results in port activity being concentrated at sites far removed from the oldest facilities. Such models of de‐concentration in port cities have been exemplified by metropolises in the developed countries such those in Europe and the US. In developing countries, on the other hand, studies suggest an increasing level of port concentration as certain hinterland routes develop to a greater extent vis‐à‐vis others. The urban system evolves from an initial pattern of scattered, poorly connected ports along the coastline to a main network consisting of corridors between gateway ports and major hinterland centres. See Taaffe et al. (1963), Bird (1980), Barke 7