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.
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