When looking at research on office rents in the United Kingdom provided by real estate agents, such as Colliers, it becomes obvious that headline rents vary significantly from location to location. According to Colliers International (2012a), prime rents in the Mayfair are at £100.00/Sf p.a. whereas places such as Londenderry (North Ireland) are estimated to yield £10.50/Sf p.a for Grade A units (Colliers International, 2012b). However, it is not necessary to look far as to Northern Ireland since the deviations in rents in London are themselves significant. For example prime rents in the Eastern City (£22.50/sf p.a.) are a fraction of prime rents in Mayfair (Colliers International, 2012a). This paper draws on main stream theories of rent and urban economics to single out factors which determine office rents in England and Wales. Section two is a brief overview of theories of rent as well as systems of cities. A comprehensive set of data was analysed with regards to the factors influencing rental levels in accordance with these theories. The results are presented in the third section. The paper closes with a conclusion on the findings. [...]
Contents
1. Using theories of rent and urban economics to explain patterns in office rents
2. Factors determining office rents: The basic theories
2.1 Office location and the bid-rent curve
2.2 Office location and urban hierarchy
3. The data for England and Wales
3.1 Data gathering and preparation
3.2 Spatial patterns of office locations in England and Wales
3.2.1 Distances between locations
3.2.2 Office space and rents
3.2.3 An office hierarchy for England and Wales
4. Conclusion
References
Appendix A
Cities included in samples ordered from smallest to largest
Appendix B
Rent and distance
1. Using theories of rent and urban economics to explain patterns in office rents
When looking at research on office rents in the United Kingdom provided by real estate agents, such as Colliers, it becomes obvious that headline rents vary significantly from location to location. According to Colliers International (2012a), prime rents in the Mayfair are at £100.00/Sf p.a. whereas places such as Londenderry (North Ireland) are estimated to yield £10.50/Sf p.a for Grade A units (Colliers International, 2012b). However, it is not necessary to look far as to Northern Ireland since the deviations in rents in London are themselves significant. For example prime rents in the Eastern City (£22.50/sf p.a.) are a fraction of prime rents in Mayfair (Colliers International, 2012a).
This paper draws on main stream theories of rent and urban economics to single out factors which determine office rents in England and Wales. Section two is a brief overview of theories of rent as well as systems of cities. A comprehensive set of data was analysed with regards to the factors influencing rental levels in accordance with these theories. The results are presented in the third section. The paper closes with a conclusion on the findings.
2. Factors determining office rents: The basic theories
2.1 Office location and the bid-rent curve
The basic assumption of the standard theory of office location is that businesses chose locations which maximize their profits and that property is sold to the highest bidder. In accordance with the residual theory of land value, the maximum amount a business or type of business can pay for a specific location is the difference between the respective revenue earning capacity of that site for that business and the costs of the mobile factors of production i.e. raw materials, capital and labour for that business (Geltner et al., 2007, p. 62f.).
Bollinger, Ihlanfeldt and Bowes (1998, p. 1,099) describe the office production function as follows:
Abbildung in dieser Leseprobe nicht enthalten
The output of an office services (Q) is a function of office space (OS), service of depreciable capital assets (K), labour input in efficiency units (N), face-to-face meetings with suppliers (MS) and face-to-face meetings with customers (MC). The measurement of labour input in efficiency units is based on the assumption that physical proximity among workers increases productivity by exchange of ideas, knowledge and technology. With regards to face-to-face meetings it is argued that office services depend on customized outside support such as legal services, accountants, etc. Furthermore, office services frequently provide highly tailored services which require face-to-face contact in the production process (Bollinger, Ihlanfeldt and Bowes, 1998, p. 1,099f.).
The costs of these face-to-face interactions will depend on several factors including travelled distance or time spend traveling, frequency of meetings for a unit of output and attendees per meeting. Likewise, the revenue earning capacity of a specific location will be influenced by these factors. For example, the number of clients a sales representative will be able to meet in a given amount of time depends on the distance between the office and the clients. Hence, the rent payable by a specific business is influenced by general accessibility. According to Harvey and Jowsey (2004, p. 239) general accessibility is ‘the advantage of a particular location in terms of the movement costs (including time) it avoids and the revenue-earning capacity (including convenience) it affords’. The relation between general accessibility and rent is conceptualised in the bid-rent curve. This curve is a specification of the residual rent theory and displays the maximum amount an occupant would be able to pay depending on the distance between location and one specific point of highest accessibility, e.g. the central business district of a town were (Geltner et al. 2007, p. 64f.).
Abbildung in dieser Leseprobe nicht enthalten
Modelled after Harvey & Jowsey (2004 p. 237)
The above chart shows an exemplary bid rent curves for different usages of office space. A steep slope indicates a high sensitivity for accessibility. As the land is assumed to be occupied by the highest bidder, headquarters will settle between O and A and back office functions between A and B whereas call centres will be found between B and C.
In addition to general accessibility the dependence of office service output on efficient labour and face-to-face meetings reveals that agglomeration economics have an impact on revenue and costs of an office business. Agglomeration economics are advantages in cost or productivity resulting from firm locating near each other. They result either from linkages in the production process as can be exemplified by law firms locating near investment banks, or from synergies such as sharing of a pool of skilled labour or infrastructure (Geltner, 2007, p.43 f.). For example, rapid changing industries with high level of uncertainty in products and processes can neither codify the necessary knowledge nor smooth output levels during downturns. They can therefore not hoard labour during recession and need rapid access to specialized workers during recovery. This matching-without-hoarding problem can be mitigated by a large pool of specialized labour (Storper, 2010, p. 319).
2.2 Office location and urban hierarchy
General accessibility and economies of agglomeration together with economies of scale not only influence the rental level at a particular location but, according to central place theory and theory of urban hierarchy, also shape the characteristics of a system of cities. This system consists of few high order cities which are far apart from each other and a larger number of less widely spread lower order cities. Within their respective levels of hierarchy, cities would be evenly spread. Higher order cities supply lower order cities with higher order goods and services. Higher order services or goods are either highly specialized or require significant economies of scale. Given the even distribution of demand, these goods or services must be distributed to a large area in order to be profitable. Lower order cities provide goods or services with less specialization, lower economies of scale or higher transport costs to their smaller service areas. Hence, the service area of a high order city includes several service areas of lower order cities (Geltner et al., 2007, p.45 f.). In the general hierarchical model every centre of level m+1 or higher is surrounded by Abbildung in dieser Leseprobe nicht enthalten lower order cities. While in the general hierarchical model Abbildung in dieser Leseprobe nicht enthalten is variable, it is kept constant in the Christaller model with the most frequent number used being s=2 (Parr & Budd, 2000, p. 595).
Parr and Budd (2000) clustered UK cities using population as the main representation of centrality and link these classes with a hierarchy of UK financial service activities. The hierarchy of the financial services was established by counting how many cities offer a particular service. The fewer cities provide the service the higher its level. The findings for the two highest levels of urban centres are depicted below. A ‘0’ means that non of the activities of that level of functions are found in either of the cities in a given level of urban function. A ‘1’ implies that a given function is not supplied by all centres of the given level and ‘2’ means that all functions of that level are provided by all cities of a given urban level.
Abbildung in dieser Leseprobe nicht enthalten
3. The data for England and Wales
3.1 Data gathering and preparation
The basis of the following analysis is a set of data comprising floor space in thousand square meters as well as rateable values for office premises in administrative areas in England and Wales for 2012 (Valuation Office Agency, 2012). The rateable value represents an open market annual rental value and is based on the actual rent paid, thus including rent free periods (Valuation Office Agency, 2010). In the following the rental value per square meter will be used as an approximation of the average market rent. No comparable data could be found for Scotland. A major drawback is administrative areas often include multiple cities and spread over a large area. To eliminate these issues the data was mapped with UK postcodes where, apart from the London area, the first two letters of each code represent a clearly defined city (Ordance Survey, 2012). In case of London it was decided to treat ‘Inner London’ as one city (London). Every administrative area for which no postcode could be mapped was excluded from the analysis. Hence the sample size was reduced from 382 administrative areas to 136 cities. A list of the cities can be found in appendix A.
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