London office performance: determinants and measurement of capital returns
||London office performance: determinants and measurement of capital returns
||PhD-Thesis at London School of Economics and Political Science
||This thesis develops three chapters which extend our understanding of asset performance within the London office market by analysing the determinants and measurement of capital returns. The first chapter examines whether enlisting the services of a star-architect allows developers to persuade city planners to build bigger within the tightly regulated London property market, and therefore to engage in rent-seeking behaviour. We find that outside protected conservation areas famous architects can not only build taller, but that their designs have no effect on building sale prices holding the amount of space constant. For a given land plot however, the ability to build taller increases total floorspace and developer profits even when accounting for the increased costs of hiring a famous architect and building to their higher standards. The second chapter investigates potential sources of bias in commercial repeat-sales price indices by constructing such an index for the central London office market and examining the sources of index change relative to the underlying market. We find evidence that employment density changes and the restrictiveness of new development in the relevant local authority are key external drivers of bias on estimated price levels. This discrepancy arises because repeat-sales occur disproportionately in areas where changes in these attributes differ relative to the stock as a whole. The third chapter presents a comparison of seven competing real estate price index construction methodologies in the London office market. This exercise sheds light on the history of London office market returns from 1998-2010, and the relative pros and cons of the major index construction methods utilized by research and industry. This comparison also reveals substantial differences between indices in the timing of market turning points and various descriptive statistics, and demonstrates that the hedonic model outperforms the repeat-sales index due to the greater inclusivity of sale observations.
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