all else being equal, a 10% increase in the initial stock of highways in a city leads to higher employment of 1.5% between 1983 and 2003. A similar analysis for the USA concludes that the construction of interstate highways raises economic growth in counties through which the highway passes, but reduces economic activity in nearby regions, thus leading to an unclear effect on overall economic activity (Chandra and Thompson, 2000).

Road networks also impact regional productivity through changes in transport costs and increased economy‐wide allocative efficiency. Faber (2014) investigates the displacement of economic activity caused by increased ease of transport through a 15‐year construction program as part of the National Trunk Highway System in China. The study overcomes endogeneity in road placement by considering a hypothetical road network as a benchmark and finds that reduced transport costs lower economic activity in peripheral regions when connected to large centers of production. Baum‐Snow et al. (2017) provide somewhat contrasting evidence by showing strong negative relationships between GDP in peripheral regions and the construction of new transport infrastructure in Chinese cities between 1990 and 2010. The results suggest that development of a new radial railroad or ring road displace industrial GDP in the city center by about 20% or 50%, respectively.

It is important to note that these positive or negative changes at the sub‐national level do not contradict the national‐level gains from better transportation networks found in other studies. Rather, they illustrate the important role of infrastructure systems in distributing and reallocating economic centers across space. This is evident, for example, in studies looking at early infrastructure projects such as the railroad network in colonial India. This transport systems has been shown to have reduced transportation costs, facilitated the harmonization of price levels, and thus increased agricultural income by 16% in the average district (Donaldson, 2018). In current times, Asturias et al. (2015) estimate that the Golden Quadrilateral, a large infrastructure project in India connecting Delhi, Mumbai, Chennai, and Kolkata with highways established from 2001 onwards, lead to real income gains in the manufacturing sector of 2.7%, about 7% of which was caused by gains in allocative efficiency.

In addition to reductions in transport cost, better road infrastructure can also reduce transaction costs for firms. In the US, a marginal dollar invested in highway capital has been estimated to decrease firm‐level raw material inventory by seven cents in the 1970s, although the return shrunk to two and 0.3 cents in the 80s and 90s, respectively (Shirley and Winston, 2004). Using the World Bank Enterprise Survey (ES) data for India, Datta (2012) shows that businesses in cities affected by the Golden Quadrilateral project could reduce their average inventory by production inputs worth 6‐12 days between 2002 and 2005 and are more likely to have switched their supplier, again hinting at improvements in allocative efficiency. Using firm‐level data for Chinese manufacturers, Li and Li (2013) confirm the existence of this effect channel. They find that for every dollar invested in roads, affected firms can reduce their inventory costs by about two cents.

Empirical evidence exists for several other ways in which transport networks can boost productivity. The quality of physical infrastructure has been found to substantially impact the entrance of new firms into the market (Ghani, Kerr and O’Connell, 2014; Ghani, Goswami and Kerr, 2016). Martincus et al. (2017) use the Inca road network to assess changes in road infrastructure in Peru and estimate that 26% of growth in firm exports between 2003 and 2010 can be attributed to upgrades of domestic transport infrastructure. In addition to these direct effects on productivity, Wan and Zhang (2018) identify an indirect effect of infrastructure on firm productivity through agglomeration economies in the Chinese manufacturing sector, 5