Although the productivity gains of urban agglomeration economies are generally found to be positive, there is a great deal of variability in the magnitude of reported estimates. This paper undertakes a quantitative review of the empirical literature on agglomeration through a meta-analysis of 729 elasticities taken from 34 different studies. The objective is to make sense of the range of values for agglomeration economies found in the literature by identifying some key characteristics that affect the magnitude of the results obtained. Our analysis confirms that study characteristics do matter. In particular, we find that country specific effects, the industrial coverage, the specification of agglomeration economies, and the presence of controls for both unobserved cross-sectional heterogeneity and differences in time-variant labor quality can give rise to large differences in the results reported in the literature. In contrast, correcting for reverse causality of agglomeration does not seem to produce noticeable changes in the size of urban agglomeration estimates. We also test for publication bias and find some evidence supporting the presence of positive reporting bias. The findings support the intuition that agglomeration estimates for any particular empirical context may have little relevance elsewhere.

Investments in transport infrastructure have been widely used by decision makers to encourage economic growth, particularly during periods of economic downturn. There has been extensive research on the linkage between transport infrastructure and economic performance since the late 1980s, characterised by widely varying evidence. We conduct a meta-analysis of the empirical evidence on the output elasticity of transport infrastructure, based on a sample of 563 estimates obtained from 33 studies. Previous meta-analyses have focused on total public capital and hence cannot appropriately explain the wide variation in the productivity effect of transport infrastructure nor provide guidance to policymakers on the returns to investment in different types of transport infrastructure. Our results indicate that the existing estimates of the productivity effect of transport infrastructure can vary across main industry groups, tend to be higher for the US economy than for European countries, and are higher for roads compared to other modes of transport. The variation in the estimates of the output elasticity of transport is also explained by differences in the methods and data used in previous studies. Failing to control for unobserved heterogeneity and spurious associations tends to result in higher values, while failing to control for urbanisation and congestion levels leads to omitted variable bias. These findings can be used to inform future research on the choice of model specification and estimation and transport-related policy making

This paper estimates the productivity gains from agglomeration economies for a sample of the largest metropolitan areas in the United States using measures of urban agglomeration based on employment density and employment accessibility. The latter is a more accurate measure of economic proximity and allows testing for the spatial decay of agglomeration effects with increasing travel time. We find that the productivity gains from urban agglomeration are consistent between measures, with elasticity values between 0.07 and 0.10. The large majority of the productivity gains occur within the first 20 minutes, and do not appear to exhibit significant nonlinearities.