The theory that urban-led growth produces spread effects into proximate rural areas was initially proposed by Francois Perroux (1955), who called it “growth poles” theory.<sup>6</sup> According to this theory, regional development policies focused on urban centers are prone to generate more jobs, leading to rural prosperity from rural–urban commuting and new urban markets for rural products. During massive agricultural restructuring in Europe, however, because backwash forces were initially dominant, the theory grew unpopular. It may be that growth pole policy was simply ahead of its time.

Close relatives to growth-pole policies are those related to regionalization, which attempt to address fragmented local-governance structures. To illustrate, metropolitan areas in the United States can have over 100 local government authorities with distinct objectives that end up competing with each other. Enhanced regionalization of local governments could help address this issue and link the rural hinterlands, which lack the resources to efficiently provide basic public functions (Fox & Krishna Kumar, 1965). Likewise, Olfert et al. (2014) illustrate how urban-centered growth can facilitate rural growth in Chile and Peru by creating commuting opportunities. Stabler & Olfert (2002) also recommend this approach of leveraging agglomeration economies to create more urban jobs for rural commuters, as opposed to dispersing funds for rural communities without considering the importance of rural–urban linkages.

So far, our focus has been on regions centered around one main urban center. However, what about cases with urban–rural regions containing multiple urban areas, all within rough commuting distance? In this case, instead of one dominant urban center, there are multiple centers in a polycentric system— i.e., rural areas are then influenced by multiple cities, rather than only the nearest city (Berdegué & Soloaga, 2018; Ganning, Baylis, & Lee, 2013). In this case, we would move towards a “system of systems” approach. However, there is no clear agreement about how to define polycentric systems and the existing empirical evidence is at best fragmented and disjointed (Hoyler, Kloosterman, & Sokol, 2008), suggesting an area ripe for further investigation. There is an array of methods and indicators to capture polycentric city–regions, including city size, commuter data, retail trade patterns, firm dynamics, and changes in economic profiles and ICT. Such approaches can be augmented by expanding the standard URCA approach to help identify polycentric systems and to provide comparable global data. Capturing the polycentricity of urban systems would require changing the prioritization algorithm in the URCA approach to identify a primary and a secondary urban center of reference. The hierarchy of urban places can be differentiated not only by their size but by the number and order of the functions offered by them, or the price of services and goods.

Designing more realistic polycentric regions at global scale can simulate the evolution of urban systems for government investments such as in infrastructure (e.g., building a road from a city to a rural area may change the “city of reference” for that rural area). In turn, applying the rural–urban continuum can better target which rural areas will benefit the most and promote efficient infrastructure placement.

_Food systems along the rural-urban continuum_ One spin-off of city–regions is city–region food systems (Blay-Palmer et al., 2018; Forster et al., 2015), which generally describe how urbanization affects food systems (Seto & Ramankutty, 2016).

> 6 See Parr (1973) for a review of the growth poles literature.

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