Benchmarking and valuation issues in measuring depreciation for European office markets

Purpose – The paper addresses the practical problems which emerge when attempting to apply longitudinal approaches to the assessment of property depreciation using valuation-based data. These problems relate to inconsistent valuation regimes and the difficulties in finding appropriate benchmarks. Design/methodology/approach – The paper adopts a case study of seven major office locations around Europe and attempts to determine ten-year rental value depreciation rates based on a longitudinal approach using IPD, CBRE and BNP Paribas datasets. Findings – The depreciation rates range from a 5 per cent PA depreciation rate in Frankfurt to a 2 per cent appreciation rate in Stockholm. The results are discussed in the context of the difficulties in applying this method with inconsistent data. Research limitations/implications – The paper has methodological implications for measuring property investment depreciation and provides an example of the problems in adopting theoretically sound approaches with inconsistent information. Practical implications – Valuations play an important role in performance measurement and cross border investment decision making and, therefore, knowledge of inconsistency of valuation practice aids decision making and informs any application of valuation-based data in the attainment of depreciation rates. Originality/value – The paper provides new insights into the use of property market valuation data in a cross-border context, insights that previously had been anecdotal and unproven in nature.

A question of value: a discussion of property pricing and definitions of value

Valuation is often said to be “an art not a science” but this relates to the techniques employed to calculate value not to the underlying concept itself. Valuation practice has documented different bases of value or definitions of value both internationally and nationally. This paper discusses these definitions and suggests that there is a common thread that ties the definitions together.

Attribution analysis of property portfolios

This paper aims to clarify the potential confusion about the application of attribution analysis to real estate portfolios. Its three primary objectives are: · To review, and as far as possible reconcile, the varying approaches to attribution analysis evident in the literature. · To give a clear statement of the purposes of attribution analysis, and its meaning for real-world property managers. · To show, using real portfolio data from IPD's UK performance measurement service, the practical implications of applying different attribution methods.

Property company performance and real interest rates: a regime-switching approach

Linear models of property market performance may be misspecified if there exist distinct states where the market drivers behave in different ways. This paper examines the applicability of non-linear regime-based models. A Self Exciting Threshold Autoregressive (SETAR) model is applied to property company share data, using the real rate of interest to define regimes. Distinct regimes appear exhibiting markedly different market behaviour. The model both casts doubt on the specification of conventional linear models and offers the possibility of developing effective trading rules for real estate equities.

Dietary intakes and food sources of phytoestrogens in the European Prospective Investigation into Cancer and Nutrition (EPIC) 24-hour dietary recall cohort

BACKGROUND/OBJECTIVES: Phytoestrogens are estradiol-like natural compounds found in plants that have been associated with protective effects against chronic diseases, including some cancers, cardiovascular diseases and osteoporosis. The purpose of this study was to estimate the dietary intake of phytoestrogens, identify their food sources and their association with lifestyle factors in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. SUBJECTS/METHODS: Single 24-hour dietary recalls were collected from 36 037 individuals from 10 European countries, aged 35–74 years using a standardized computerized interview programe (EPIC-Soft). An ad hoc food composition database on phytoestrogens (isoflavones, lignans, coumestans, enterolignans and equol) was compiled using data from available databases, in order to obtain and describe phytoestrogen intakes and their food sources across 27 redefined EPIC centres. RESULTS: Mean total phytoestrogen intake was the highest in the UK health-conscious group (24.9 mg/day in men and 21.1 mg/day in women) whereas lowest in Greece (1.3 mg/day) in men and Spain-Granada (1.0 mg/day) in women. Northern European countries had higher intakes than southern countries. The main phytoestrogen contributors were isoflavones in both UK centres and lignans in the other EPIC cohorts. Age, body mass index, educational level, smoking status and physical activity were related to increased intakes of lignans, enterolignans and equol, but not to total phytoestrogen, isoflavone or coumestan intakes. In the UK cohorts, the major food sources of phytoestrogens were soy products. In the other EPIC cohorts the dietary sources were more distributed, among fruits, vegetables, soy products, cereal products, non-alcoholic and alcoholic beverages. CONCLUSIONS: There was a high variability in the dietary intake of total and phytoestrogen subclasses and their food sources across European regions.

Intakes and sources of isoflavones, lignans, enterolignans, coumestrol and soya-containing foods in the Norfolk arm of the European Prospective Investigation into Cancer and Nutrition (EPIC-Norfolk), from 7-day food diaries, using a newly updated database

Objective: A phytoestrogen-rich diet has been suggested to protect against a variety of common diseases but UK intake data on phytoestrogens or their food sources is sparse. This study aims to estimate the average intake of isoflavones, lignans, enterolignans and coumestrol from 7-day food diaries (7dFD), and to provide data on total isoflavone, lignan and phytoestrogen consumption by food group. Design: Development of a food composition database for twelve phytoestrogens and analysis of soya food and phytoestrogen consumption in a population-based study. Setting: Men and women, aged 40-79 years from the general population participating in EPIC-Norfolk between 1993 and 1997, with nutrient and food data from 7dFD. Subjects: A subset of 20 437 participants. Results: The median daily phytoestrogen intake for men was 1.20mg (interquartile range (IQR) 0.93-1.54 mg; mean 1.50 mg, SD 1.50 mg) and 0.89 mg for women (IQR 0.71-1.14 mg; mean 1.20 mg, SD 1.70 mg). In soya-consumers (SC), median daily intakes were higher: 2.86 mg in men (IQR – 1.30-7.27mg; mean 5.05 mg, SD 5.03 mg) and 3.14 mg in women (IQR – 1.09-7.33mg; mean 5.40 mg, SD 6.09 mg). In both men and women, bread made the greatest contribution to phytoestrogen intake – 40.7% and 35.7% respectively. In SC men and women, vegetable dishes and soya/goat’s/sheep’s milks were the main contributors – 42.6% and 18.9% in men and 38.8% and 29.1% in women, respectively. Conclusions: The ability to estimate phytoestrogen intake in Western populations more accurately will aid investigations into their suggested effects on health.

Sources of multi-decadal variability in Arctic sea ice extent

The observed dramatic decrease in September sea ice extent (SIE) has been widely discussed in the scientific literature. Though there is qualitative agreement between observations and ensemble members of the Third Coupled Model Intercomparison Project (CMIP3), it is concerning that the observed trend (1979–2010) is not captured by any ensemble member. The potential sources of this discrepancy include: observational uncertainty, physical model limitations and vigorous natural climate variability. The latter has received less attention and is difficult to assess using the relatively short observational sea ice records. In this study multi-centennial pre-industrial control simulations with five CMIP3 climate models are used to investigate the role that the Arctic oscillation (AO), the Atlantic multi-decadal oscillation (AMO) and the Atlantic meridional overturning circulation (AMOC) play in decadal sea ice variability. Further, we use the models to determine the impact that these sources of variability have had on SIE over both the era of satellite observation (1979–2010) and an extended observational record (1953–2010). There is little evidence of a relationship between the AO and SIE in the models. However, we find that both the AMO and AMOC indices are significantly correlated with SIE in all the models considered. Using sensitivity statistics derived from the models, assuming a linear relationship, we attribute 0.5–3.1%/decade of the 10.1%/decade decline in September SIE (1979–2010) to AMO driven variability.