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Cited by 508

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Networking off Madison Avenue

ARZAGHI, MOHAMMAD, HENDERSON, J. VERNON·2008·Review of Economic Studies

Abstract

This paper studies the advertising agency industry in Manhattan to infer networking benefits among agencies in close spatial proximity. We use economic census data that allow us to distinguish locations at a fine level of geographic detail, so as to infer the strong effect on productivity of having more near advertising agency neighbours. Paying close attention to identification issues, we show, however, that there is extremely rapid spatial decay in the benefits of more near neighbours, even in the close quarters of southern Manhattan, a finding that is new to the literature. This suggests that high density of similar commercial establishments is important in enhancing local productivity for those industries found in large cities, where information sharing plays a critical role. Our results indicate that the benefits of more near neighbours are largely capitalized into rents rather than wages, challenging an existing literature, which estimates wage equations alone to infer agglomeration benefits. Copyright 2008, Wiley-Blackwell.

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Metadata

Authors
ARZAGHI, M., & HENDERSON, J. V.
Venue
Review of Economic Studies
Published
2008-10
Volume
75
Issue
4
Pages
1011-1038
ISSN
  • 0034-6527 (ISSN-L)
  • 1467-937X
OpenAlex
W2061794449
Cited by
508
References
26
FWCI
42.47
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Networking off Madison Avenue. https://app.cochat.ai/papers/10.1111/j.1467-937x.2008.00499.x
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ARZAGHI, M., & HENDERSON, J. V. (2008). Networking off Madison Avenue. Review of Economic Studies. https://doi.org/10.1111/j.1467-937x.2008.00499.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.