The Effect of Clustering on Office Rents: Evidence from the Amsterdam Market

Abstract

This article examines the rent effects of office clustering in the Amsterdam office market for the period 2000-2005. We isolate the rent effects of location density based on geographic information system (GIS) methodology, while controlling for variations in object characteristics in a cross-sectional hedonic model. While controlling for the age, location and quality of the object, we find a strong positive effect of being located in dense office areas. We find that the vicinity of other office objects is priced into rent levels, regardless of market conditions. This article extends existing literature by examining the influence of clustering outside the United States, during changing economic tides and by application of novel methodology, based on objective clustering schemes, which can be replicated for other geographic areas. Copyright (c) 2009 American Real Estate and Urban Economics Association.

Urban planning in office markets: A methodological approach

“…12 See Shilton and Webb (1995), Westhead and Wright (1999), Coughlin and Segev (2000), Feser and Bergman (2000), and Maurer and Walz (2000). 13 Several authors use time lengths to assess building's age (Nappi-Choulet et al, 2007;Jennen and Brounen, 2009), despite in the former case results are distorted by recovery works in buildings holding patrimonial value. 14 Despite other less rational variables may also intervene in location or relocation decisions.…”

“…These activities are (Polèse, 1994;Bellini, 2000): (i) the social headquarters and offices of production, transports, telecommunications and energy firms, (ii) the financial services lend by banks, financial institutions, insurance and real estate firms; and (iii) the specialized offices in technical-scientific consultancy, namely engineering, informatics, management, architecture, accounting, law, and so on (Liang and Kim, 1998;Polèse, 1994;Rabianski, 2004;Rabianski and Gibler, 2007). The filtering processes shape a hierarchical pattern in the spatial distribution of the economic-financial characteristics of services (Jennings, 1965;Nappi, 1995) that results from skips among alternative discontinuous poles (Jennen and Brounen, 2009). But location and relocation choices of services depend not only on spatial variation (Ihlanfeldt and Raper, 1990) but also on temporal variation 13 (Rebelo, 2009a;Rebelo and Pinho, 2010) of variables that impact profits.…”

“…This implies, thus, a reassessment of the outline and relative importance of these variables, and of their impact on upper tertiary sector's rents. The traditional variable of distance to the CBD -based on a monocentric layout -does not fit the majority of actual European cities, that mainly exhibit polycentric layouts in services location (Archer and Smith, 2003;Greenhalgh, 2008;Jennen and Brounen, 2009;Ozus, 2009). Besides, due to advancements in information and communication technologies -able to surmount the need for centrality -rent gradients slow down, thus rents keep high throughout larger territorial extensions (Sivitanidou, 1995).…”

“…Despite the effects of zoning restrictions on supply and demand may be doubtful (Ihlanfeldt and Raper, 1990), they have been tackled in several studies, through the use of dummy variables (Bourassa et al, 1999;Nitsch, 2006), densities and kinds of land uses (Wasylenko, 1980), and zoning maps (Long, 1984). The main advantages upper tertiary activities can extract from external or agglomeration economies result from favoured access to workmanship and services they cannot provide internally (Jennen and Brounen, 2009), what is particularly relevant for firms in the incubation stage (Leone and Struyk, 1976;Fagg, 1980). Besides, wage levels are one of the most determinant variables in offices' demand.…”

“…According to different theoretical and empirical studies, the main reasons that traditionally explain offices' locations and, consequently, their prices and rents are: (i) centrality/proximity to the CBD (Archer and Smith, 2003;Nitsch, 2006;Greenhalgh, 2008;Jennen and Brounen, 2009;Ozus, 2009), (ii) nearness to other businesses, namely banks, insurance companies, and financial institutions (Kutay, 1986;Shilton and Webb, 1995;Jennen and Brounen, 2009), (iii) amenities, facilities and local services (Bollinger et al, 1998;Din et al, 2001), (iv) accessibility and proximity to transports' infrastructures and services (Nitsch, 2006;Nappi-Choulet et al, 2007), (v) status, prestige and symbolic meaning of offices' location (Archer et al, 1990;Krätke, 1992), (v) positive externalities, including agglomeration economies (Leone and Struyk, 1976;Fagg, 1980;Mun and Hutchinson, 1995;Jennen and Brounen, 2009), (vi) increased value that results from the use of productive factors (Fogarty and Garofalo, 1988;Ihlanfeldt and 7 Few agents intervene in property transactions (what implies lack of liquidity), information is bounded (what shrinks transparency), and transactions are costly. 8 Geographic, economic and social characteristics of land are spatially changeable and planning and market interventions reinforce these divergences even more.…”