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 The Review of Economic Studies Limited.

We thank Enrico Spolaore for early advice and Rajiv Vohra for helpful discussions on the topic. We are also grateful to James C. Davis for his help throughout the project, Christine Kearney for preparation of the federalism index, and Fumiko Tamura for her help as a research assistant. Finally we thank two anonymous referees and an editor for helpful detailed comments.

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This paper extends the utility maximization model of migration by introducing income and unemployment-related uncertainties as determinants of utility, and analyzes the effects of the informational advantages of migrants. The paper maintains that migration would expand an individual's economic choices and opportunities and allow diversification. Consequently, diversification advantages influence the location decisions of migrants, an effect captured by the correlation of incomes at the origin and potential destinations. We use the discrete choice model based on random utility maximization as the framework for our empirical investigation of migration from the United States rural to urban counties. This paper takes advantage of an equivalent relation between the conditional logit model and Poisson regression to study the migration decisions using aggregate data among a large set of spatial alternatives. The results show that the diversification concerns have significant effects on location decisions of the rural-urban migrants in the United States.

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In this article, we study the influence of the room properties, hotel amenities, hotel location, and, more importantly, the characteristics of hotels in the surrounding area on the prices of hotel rooms. The effects of different determinants are estimated using the hedonic price model for a cross-section of 250 hotels in Dubai. In addition to the typical characteristics of hotels and hotel rooms such as hotel amenities, star rating, and room size, we include location-specific characteristics such as accessibility to public transportation, airport, and, more importantly, clustering variables to capture the effects of local competition and spillovers from surrounding hotels. Our results indicate significant and strong effects of accessibility to attractions, transportation, hotel’s star rating, and room size, as expected. Our estimations also indicate that local competition reduces the room price, and local quality spillover increases the room price, and both effects are predominantly limited to the hotel’s immediate surroundings. Our estimations indicate that having one more hotel in the immediate surroundings decreases the room price by about one percent, and an increase in the average quality of the hotels in the immediate surroundings by one star rating increases the room price by more than 20%.

We address a puzzle surrounding the shift from bundling to unbundling of U.S. advertising agency services and the slow pace of change over several decades. We model an agency’s decision as a tradeoff between the fixed cost to the advertiser of establishing a relationship with an agency and pecuniary economies of scale from media services provision. Using micro-data from the U.S. Census of Services for 1982-2007, we find agencies are more likely to unbundle with increasing size, diversification and higher media prices, and less likely with increasing age, larger media volume, and an interaction between media prices and volume.

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