# **1. Introduction**

Economic activity is highly concentrated. Coastal areas have always been favored for regional and international commerce, and the centripetal forces of agglomeration economies drive a virtuous cycle of economic concentration and higher productivity (Duranton and Puga 2020). Economic activity increases with population density. Even in the poorest countries, industry and services tend to be concentrated in dense metropolitan areas and productivity rises with the density of economic activity. Grover, Lall, and Maloney (2021) show that night light intensity, a measure of economic activity, is on average 2.5 times higher in cities of more than 5 million people compared to cities with populations between 500,000 and 1 million.

Along with high spatial inequalities in living standards and slugging domestic labor mobility, the spatial concentration of economic activity has raised increasing concern among policy makers about “places left behind” (Grover, Lall and Maloney 2021; Rodriguez-Pose 2018; World Bank 2008). In this context, policy makers may find global value chain (GVC) integration appealing as production disintegration through “unbundling” of tasks and products makes industrial development less lumpy (Baldwin 2011a), providing opportunities for smaller cities to plug and play in niche spaces while not having to fight agglomeration economies offered by large metropolitan areas.

Some studies suggest that cross-country cooperation in GVCs could provide opportunities for secondary cities and help mitigate spatial inequalities. For example, cooperation between Singapore and secondary cities in Malaysia (Johor Baru) and Indonesia (Bintan Batam) have shown that collaboration on integrated supply chains in manufacturing, where each city is assigned a specialized role in production, could boost the global competitive advantage of secondary cities (Toh Mun 2006).<sup>1</sup> In this paper, we examine the impact of a country’s participation in GVCs on spatial inequality, measured by the domestic size distribution of cities. For example, the assembly of parts through the maquiladora program boosted Mexico’s participation in global production networks that accounted for half of Mexico's exports in 2006; yet most exporting firms remain clustered around the US-Mexico border (Mia and Austin, 2008; Hanson, 1996). Vietnam’s participation in GVCs is driven by firms located around Ho Chi Minh City that account for nearly 83 percent of apparel and textile exports. Even after several decades following its establishment, these activities of global production networks are confined to the city and its contiguous agglomerations (Pham et al., 2013). Further, clustering is more likely when production on integrated networks is intensive in technology, knowledge and skills -- if a country plugs into the higher end of the value chain, agglomeration forces are likely stronger.<sup>2</sup> We organize our analysis in two stages. We first estimate a measure of city size distribution for each country and year using demographic data on urban agglomerations. By regressing the log rank of each urban agglomeration in a given country on the log of the agglomeration’s population size, we estimate the country’s _Zipf_ coefficient, a parameter generally used as a summary statistic of city size distribution. Next, we examine the determinants of city size distributions, with participation in GVCs being the focus of our analysis.

> 1 The three city triangle is known for GVCs related to production of chemicals and the manufacture of technology-based equipment. 2 Duranton and Puga (2001) and Desmet and Rossi-Hansberg (2009) argue that knowledge spillovers in new industries (such as business services) motivates clustering  in city centers, while more mature industries such as standardized or low-tech manufacturing tends to relocate to less expensive places (e.g. urban periphery or secondary cities).

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