Estimating agglomeration economies with history, geology and worker effects

By Pierre-Philippe Combes, Gilles Duranton, L. Gobillon, Sébastien Roux. 2008

421 citations recorded by the source corpus.

Does productivity increase with density? We revisit the issue usingFrench wage and TFP data. To deal with the ‘endogenous quantity of labour' bias (i.e., urban agglomeration is consequence of high local productivity rather than a cause), we take an instrumental variable approach and introduce a new set of geological instruments in addition to standard historical instruments. To dealwith the ‘endogenous quality of labour' bias (i.e., cities attract skilled workers so that the effects of skills and urban agglomeration are confounded), we take a worker fixed-effect approach with wage data. We find modest evidence about theendogenous quantity of labour bias and both sets of instruments give a similar answer. We find that the endogenous quality of labour bias is quantitatively more important.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/6ce757bd7d3992f2ff3c9d90915b9ec47b19f0bb

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In Economics and Econometrics

Citations in the corpus

A meta-analysis of estimates of urban agglomeration economies (2009, background): “Combes et al. (2008a) find that there is positive aggregation bias from using regional instead of worker level data.”
Productivity and the Density of Human Capital (2012, positive): “Combes et al. (2008, 2010) argue that existing estimates of agglomeration economies derived from aggregate production functions are upward biased by as much as 50 percent because they fail to account for individual attributes. In contrast, using U.S. data, Glaeser and Mare (2001) find little evidenc”
Agglomeration Effects in Colombia (2016, positive): “Using a similar specification, Glaeser and Resseger (2010) report an elasticity of 3.4 percent for U.S. cities while, Combes et al. (2010) report 7This coefficient of 0.05 may seem small but only small differences are needed here given the large effects of individual education on wages.”
Urban Growth and Transportation (2012, neutral): “Davis et al. (2009) find a value of 0.”
Growing through Cities in Developing Countries (2014, positive): “Deep historical lags, such as the population from 200 years ago or soil characteristics, can do the job (at least under some circumstances—see Combes et al. 2010, for a discussion).”
Urban revival in America (2020, neutral): “Finally, we use the smartphone visit data, described further in Couture et al. (2019), to calculate an amenity quality index that captures the presence of restaurant chains preferred by a given age and education group.”
Female Entrepreneurship, Agglomeration, and a New Spatial Mismatch (2012, result): “This is analogous to previous literature that has considered the impact of agglomeration on individual worker wage rates (Glaeser & Mare, 2001; Rosenthal & Strange, 2008; Combes et al., 2010).”
Entrepreneurship and Market Size - The Case of Young College Graduates in Italy (2010, methodology): “In this section we deal with the potential endogeneity problem by instrumenting urbanization with pre-World War II population density (in 1921), similarly to Ciccone and Hall (1996), Rice et al. (2006), Combes et al. (2008) and Guiso and Schivardi (forthcoming).”
Why Has Urban Inequality Increased? (2018, neutral): “See Combes et al. (2010) for a review.”
Cities in Bad Shape: Urban Geometry in India (2020, background): “Indeed, the literature documents many channels through which physical geography affects local development: amongst others, see Combes et al. (2010), Rosenthal and Strange (2004), and Barr, Tassier, and Trendafilov (2011) on geology, density, and agglomeration; Burchfield et al. (2006) on local…”