This paper explores the relationships between key sub-markets in the Central London office market. The paper models the intra-metropolitan dynamics and examines how sub-markets influence and impact upon one another. Set within a rent adjustment framework, the modeling approach highlights the key linkages and allows a broader examination of the overall dynamics of the London office market. The results highlight the position of the West End as the prime submarket within Central London and also the impact of the development of the Docklands submarket on the Central London office market.

Previous examinations of office market dynamics have tended to concentrate on either national or metropolitan markets. However, many metropolitan markets contain distinct submarkets that may behave in a fragmented manner. Fragmentation can be of two types. The first is spatial fragmentation that refers to locational features. The second is structural fragmentation, whereby differences occur due to property specific issues. While a number of papers have in recent years examined submarket behavior, the majority contain purely descriptive statistics or have analyzed submarket dynamics within a hedonic framework. Fuerst (2005), for example, examines submarket dynamics in the New York market in a hedonic framework. The current paper relies upon a different approach and one that does not require the use of individual property data and a hedonic modeling approach. The model adopted is an extension of the Hendershott, MacGregor, and Tse (2002) errorcorrection specification of a rental adjustment process and is empirically tested using data from the London office market. The model allows the incorporation of disequilibrium in other submarkets into the rent adjustment process for each of the submarkets in term.

The London market is of interest for a number of reasons. First, it is one of the largest office markets globally, both in terms of square footage and also in investment terms. second, the market also contains a number of distinct submarkets. Third, in the development of the docklands office market in the early 1990s, it is an example of a major market that has witnessed substantial structural change with the potential to observe impacts upon submarkets across the city. Existing studies of the London market have, however, examined either the overall metropolitan market (Wheaton, Torto, and Evans, 1997) or the specific City of London market (Hendershott, Lizieri, and Matysiak, 1999 and Stevenson and McGrath, 2003). However, as already noted, London contains a number of quite distinct sub-markets. The two primary submarkets in central London are the City of London and the West End. In addition, there are two smaller submarkets: Midtown and the docklands market. London's submarkets are also key examples of where spatial and structural forms of fragmentation are hard to separate. These differences relate both to tenant mix and to property specific issues relating to office specifications. These can come through in terms of divergences in the dynamics of the different markets as Jackson, Stevenson, and Watkins (2006) illustrate between the City and West End markets. The current paper, however, concentrates on the pure market interaction effects. The remainder of the paper is laid out as follows. First, there is a presentation of the modeling framework used in this paper. Next, the empirical findings are discussed. Finally, the paper closes with concluding comments.

The lagged residual from the long-run log-level model acts as a measure of the divergence of the rent from its long-term equilibrium. While this reduced form model is highly useful in the examination of single markets, it may be problematic to use in the context of markets with multiple distinct office markets that may influence each other. In the context of the current study, it would be dubious to solely examine a single submarket within London without attention being placed on the interactions present. While these interactions will naturally influence variables such as the effective rent and vacancy rate, the proposed model allows an explicit examination of the reaction to disequilibrium in other submarkets. A key example that will be examined concerns the impact of the development of the docklands market and its impact on the City of London market. The innovation in the current paper that allows for the examination of multiple submarkets within a single framework and leads to the incorporation of pricing issues in other markets is based on recent work in a housing context by McQuinn (2004). The long-run model is estimated for each of the four submarkets in Central London: the City, West End, Midtown, and Docklands. However, in the error-correction specification rather than just include the errorcorrection term from the appropriate submarket, the model is extended to include multiple errorcorrection terms. For example, in the specification for the West End, the error-correction terms for the City, Midtown, and Docklands markets are also included in the estimation.

The results from the initial short-term errorcorrection model are reported in Exhibit 3. A number of issues are worth noting. The first is in respects similar to those noted concerning the implied elasticities obtained from the long-run model in that there are notable differences between the West End and Midtown markets on the one hand and the City and Docklands markets on the other. For the West End and Midtown markets, the majority of the coefficients are both of the anticipated sign and significant, the exceptions being the employment variable for Midtown and the error-correction term for the West End. Legal firms occupy a large proportion of the Midtown market and it is therefore perhaps not surprising that it is less sensitive to general movements in service employment. The lack of significance with regard to the West End's error-correction term is again perhaps indicative of its position as the prime office market in London and the spatial constraints within that submarket. In contrast to these findings, the results for the City and Docklands markets are to some extent disappointing in terms of the significance of the variables. In the City market, only the error-correction term is significant, while for the Docklands market the employment variable is significant together with its disequilibrium term. These findings may be due to both markets effectively chasing the same potential tenants and the impact of the supply shock that occurred as the Docklands market developed. The fact that both submarkets have significant error-correction terms highlights the divergences from long-run equilibrium during the period under examination. This is understandable as the time period studied covers the rise of the Docklands.

The results for the augmented error-correction models with the inclusion of the additional ECM terms are reported in Exhibit 4. The only difference in the reported coefficients for employment, vacancy, and stock is that the employment variable for the Docklands market is no longer significant at conventional levels. The main interest is with the results obtained for the different errorcorrection terms. In each case at least one of the terms from another submarket is significant, highlighting the potential usefulness of such an approach. The results also reveal possibly interesting patterns in the dynamics. The City market's term has a significant impact in each case. This implies that the disequilibrium observed within the City market had a significant impact on each of the other submarkets. This in all likelihood highlights its importance and also its relative size within the overall central London market. Given these factors, the City is often seen as a barometer of how London itself is doing. In contrast to the initial model, the West End's term is significant when the West End itself is modeled. However, the lack of significance of the West End's ECM term in relation to the Midtown market is perhaps surprising, given that the two are spatially contiguous. However, differences in tenant mix may explain this finding. The results with regard to the Midtown market are in line with expectations given its relative size.

Mending deteriorated asphalt pavements with portland cement concrete is a familiar technology Highway engineers used whitetopping--concrete overlays placed on top of asphalt--as early as 1918. Offering benefits that include long life and superior bonding to underlying material, whitetopping overlays grew in popularity through the mid-1970s, and ultra-thin whitetopping burst onto the scene in the early 1990s. Until recently, however, pavement engineers had no one clear resource or set of guidelines that they could refer to when determining where, when, or how to use whitetopping as a pavement option.

In 2001, to fill this knowledge void and help validate whitetopping as a viable alternative, the Austin, TX-based transportation engineering firm, The Transtec Group, developed design, construction, and rehabilitation guidelines for whitetopping. Capitalizing on state-of-the-art computer modeling technologies, the firm is developing a Windows [R]-based software that pavement practitioners can use to analyze and compare different whitetopping strategies. Balancing cutting-edge research, field-tested best practices, and construction and traffic restraints with economics, the project team's goal is to help make whitetopping a more competitive alternative for roadway construction and rehabilitation projects. By June 2002, the white- topping software was nearing the beta testing stage.

"Conventional and ultra-thin whitetopping overlays are based on two different technologies and bonding interactions," Mack says. "The computer program will bridge the gap between ultra-thin and conventional whitetopping, enabling pavement engineers to design whitetopping overlays effectively for any road application from residential streets to high-volume interstates."

With the whitetopping software, pavement practitioners will be able to analyze all three whitetopping applications-ultra-thin, thin, and conventional. The software will help construction and materials engineers, construction supervisors, and contractors produce more effective concrete mixtures, pavements, specifications, and repairs using whitetopping overlays. The product will help engineers choose the proper overlay thickness, joint spacing, and the optimum surface preparation.

A virtual bible for all things whitetopping, the software demonstrates the inherent value of approaching the world of whitetopping through a systems approach. Rather than view the processes of white-topping design, construction, and rehabilitation as independent sets of procedures--which easily could have led to authoring three different sets of guidelines--the software developers elected to employ a systems approach to the project.

By integrating all three sets of procedures into one unified software program, the project team created a practical and reliable one-stop-shop That will enable State highway agencies, contractors and pavement designers to design and build-white topping overlays efficiently, based on the best data on materials, cost, and safety available in the industry.

Highway engineers used a similar approach when developing the original philosophy behind the asphalt industry's Superpave[TM], which combines, three distinct components--binder specification mix design, and performance prediction testing--into one comprehensive system.

"The whitetopping software will be for the concrete industry what Superpave[TM] is' for the asphalt industry," Bob Risser, executive director of the Michigan Concrete Paving Association, says. "But more than just a set of design principles, the white-topping software will provide a usable tool that highway agencies can use on a daily basis to explore pavement overlay alternatives."

Highway engineers traditionally perceive portland cement concrete pavements as an option for new construction only, primarily for heavy-duty pavements. But for pavement rehabilitation, agencies generally view hot-mix asphalt (HMA) overlays as the first option, regardless of the existing pavement structure. HMA overlay designs, however, are not usually as robust as concrete. Economics and construction restraints often drive the design of HMA overlays, resulting in typical thicknesses of 10 to 15 centimeters (4 to 6 inches), independent of the design procedure. Many agencies regard an HMA overlay as an intermediate fix before major rehabilitation or reconstruction is required. In many cases, the length of service is expressed as a minimum requirement but not geared to any type of service-related distress.

The team established an additional expert advisory group, the Whitetopping Internal Technical Advisory Panel. Composed of representatives from the Colorado, Michigan, and Texas highway departments and the concrete paving industry, the panel provided invaluable consultation in shaping the beta version of the software into a user-friendly format that could be implemented readily in their home States and beyond.

Bob Risser, with the Michigan Concrete Paving Association, was a member of this panel. "The goal that [the software developers] had all along was that the tool would be usable by engineers on an everyday basis;' Risser says. "We were the reality check for the Ph.D.s."

Anticipating value in using both synthetic and steel fibers in whitetopping concrete, the project team's second objective involved partnering with Synthetic Industries, Inc., and Master Builders, Inc., to investigate the effects of using fiber reinforcement in whitetopping concrete.

Developing the Design Procedure

Using the best available technologies, Dr. George Chang led the team of software developers in creating a product that integrates environmental, material, traffic, pavement response, pavement distress, and economic (life-cycle cost) modeling. Carefully coded and thoroughly tested, the end result is an accurate and practical software application that makes performance predictions possible.

Environmental modeling in the whitetopping software uses pavement profile temperature models based on technology similar to that used in FHWA's HIPERPAV system. (See "Paving the Way" on page 20.) By employing finite-difference methods--mathematical procedures that determine the stress deformation in a system such as whitetopping--the team could correct some of the mistakes common to pavement temperature methods used in the past. The developers tested and validated the environmental model extensively, using field data.

The material models include ones for concrete, HMA, subbase, and subgrade materials. The team developed a number of concrete property conversion modules to maximize the practical side of the software, allowing the user to correlate various types of concrete strengths and moduli. The HMA model selected for the software includes an innovative damage-adjusted modulus model in addition to a sophisticated model to consider traffic speed, asphalt binder type, and aging. The soils model includes a modulus estimation tool that enables users to enter a value back-calculated from falling weight deflectometer data--which provides data on a pavement's response to dynamic wheel loads--or even just the soil classification.

The traffic model includes a convenient tool to convert equivalent single-axle loads to axle load spectra, which corresponds with the upcoming American Association of State Highway and Transportation Officials' 2002 Design Guide. The response and distress models also include state-of-the-art methods such as finite element modeling.

To meet the varying demands of the users, the whitetopping software provides a range of analysis levels that enable users to run the program at one of three different speeds. As a result, the software can serve as a planning tool, a day-to-day analysis tool, and as a final design tool.