A meta-analysis of estimates of urban agglomeration economies

By P. Melo, Daniel J. Graham, Robert B. Noland. 2009

868 citations recorded by the source corpus.

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.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/6ebaeb185e2c7e08b37857bff1de44de47be7584

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Citations in the corpus

What is Different About Urbanization in Rich and Poor Countries? Cities in Brazil, China, India and the United States (2017, neutral): “A metaanalysis by Melo et al. (2009) has shown sizable differences”
Tourism and Economic Development: Evidence from Mexico’s Coastline (2019, background): “Topalova (2010), Donaldson (in press), Atkin et al.”
Travel and the Built Environment (2010, neutral): “This is the standard approach in meta-analysis (see, eg, Melo, Graham, & Noland, 2009 ).”
The impact of energy labels and accessibility on office rents (2012, background): “Clustering of services in a confined area is often found to increase the efficiency of labor and, ceteris paribus, increases the rents that companies can afford to pay (see Melo et al., 2009, for an extensive review on urban agglomeration economies).”
Productivity and the Density of Human Capital (2012, neutral): “These findings are consistent with those set forth in the existing literature, where accounting for the potential endogeneity of density typically does not yield noticeable changes in the size of urban agglomeration estimates (Melo et al., 2009).17”
Growing through Cities in Developing Countries (2014, neutral): “Most of the studies reviewed by Rosenthal and Strange (2004), Melo, Graham, and Noland (2009), and Puga (2010) measure an elasticity of wages or firm productivity with respect to city employment or urban density of between 0.02 and 0.10.”
Agglomeration, clusters, and industrial policy (2013, background): “…economies, confirms these basic intuitions (see Duranton and Puga (2004) for an overview of theoretical approaches, and empirical work by Melo et al. (2009) and Combes et al. (2008) for the UK, Rosenthal and Strange (2004) for the US, Mion and Naticchioni (2009) for Italy, and De La…”