The final type of intervention operates at the scale of a city. The success of cities in attracting investment and creating jobs—the hoped-for indirect effects of most policies—is closely tied to the way the city has been built: its infrastructure and connectivity, its housing stock, and its consequent amenity value to urban workers. However, as discussed in chapter 2, despite the rising concentration of workers and firms in developing country cities, the productivity-enhancing agglomeration economies experienced in the advanced economies appear to be largely absent. Meta-analysis by Grover, Lall, and Timmis (2021) and a careful estimation of agglomeration elasticity with respect to physical productivity by Grover and Maloney (2021) suggest that higher wages are reflecting higher prices and urban disamenities—not productivity. While this is partly due to a delinking of urbanization and structural transformation, thereby diminishing or eliminating the economic activity that might benefit from greater agglomeration, it is also due to high urban costs that arise from the way that poorly functioning cities limit scale and specialization, especially in internationally tradable manufacturing and services (Venables 2016). Congestion in land, housing, and transport exerts a serious drag on urban economies, raising the costs of doing b usiness and limiting access to labor markets, while also curtailing the entry of new firms. Thus, this chapter investigates the interventions to lessen urban congestion.
Corridors and Long-Distance Transport Improvements Cost-benefit analysis is widely used to evaluate policy interventions. Early cost-benefit analysis for appraising investments in the road infrastructure sector was developed for roads in more urbanized, high-traffic, high-density areas, drawing on methods from a developed country literature. Traditionally, road investments in projects financed by the World Bank were based on ad hoc analysis of direct benefits derived from consumer surplus calculations of road user savings, in terms of both costs and time. However, this approach tends to bias investments toward higher-income areas because the demand for vehicle traffic—and hence, willingness-to-pay measures—are higher for the relatively better off (Van de Walle 2000). To correct for this bias, rural infrastructure projects were dealt with using “costeffectiveness” analysis: certain projects were exempt from a conventional cost-benefit analysis. The success of these measures was based on socioeconomic indicators. An alternative cost-benefit analysis methodology was popularized by Shenngen Fan and colleagues (Fan, Zhang, and Zhang 2002; Fan and Chan-Kang 2005) to justify road investment in lagging regions. Fan’s methodology attempts to capture both direct and indirect effects through the estimation of a set of equations with multiple variables (also known as simultaneous equations). The approach, however, does not account for the reverse causality of the public investment itself (that is, the growth potential of a region may have stimulated investment in the first place) and hence invariably and unknowingly overestimates the benefits of rural road projects.
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Place, Productivity, and Prosperity
