Individual assets, market structure and the drivers of return

Much prior research on the structure and performance of UK real estate portfolios has relied on aggregated measures for sector and region. For these groupings to have validity, the performance of individual properties within each group should be similar. This paper analyses a sample of 1,200 properties using multiple discriminant analysis and cluster analysis techniques. It is shown that conventional property type and spatial classifications do not capture the variation in return behaviour at the individual building level. The major feature is heterogeneity - but there may be distinctions between growth and income properties and between single and multi-let properties that could help refine portfolio structures.

International evidence on the predictability of returns to securitized real estate assets: econometric models versus neural networks

The performance of various statistical models and commonly used financial indicators for forecasting securitised real estate returns are examined for five European countries: the UK, Belgium, the Netherlands, France and Italy. Within a VAR framework, it is demonstrated that the gilt-equity yield ratio is in most cases a better predictor of securitized returns than the term structure or the dividend yield. In particular, investors should consider in their real estate return models the predictability of the gilt-equity yield ratio in Belgium, the Netherlands and France, and the term structure of interest rates in France. Predictions obtained from the VAR and univariate time-series models are compared with the predictions of an artificial neural network model. It is found that, whilst no single model is universally superior across all series, accuracy measures and horizons considered, the neural network model is generally able to offer the most accurate predictions for 1-month horizons. For quarterly and half-yearly forecasts, the random walk with a drift is the most successful for the UK, Belgian and Dutch returns and the neural network for French and Italian returns. Although this study underscores market context and forecast horizon as parameters relevant to the choice of the forecast model, it strongly indicates that analysts should exploit the potential of neural networks and assess more fully their forecast performance against more traditional models.

The impact of livestock assets among indigenous communities: findings from a comparative model in Bolivia

Measuring poverty has occupied a lot of space in the development discourse. Over the years a number of approaches have been offered to capture the experience of what it means to be poor. However, latterly such approaches often ignore core assets. Indeed, the comparative impact of livestock vs. other core assets such as land and education on poverty has not been well explored. Therefore, the authors created an 'asset impact model' to examine changes to both tangible and intangible assets at the household level, with a particular focus on gender and ethnicity among communities residing in the Bolivian Altiplano. The simple model illustrates that for indigenous women, a 20 per cent increase in the livestock herd has the same impact on household income as increasing the education levels by 20 per cent and household land ownership by 5 per cent. The study illustrates the potential role of a productive, tangible asset, i.e. livestock, on poverty reduction in the short term. The policy implications of supporting asset-focused measures of poverty are discussed.

The impact of energy performance certificates on the rental and capital values of commercial property assets: some preliminary evidence from the UK

This paper focuses on the effect of energy performance ratings on the capital values, rental values and equivalent yields of UK commercial property assets. Of which a small number are also BREEAM rated, the study is based upon 708 commercial property assets held in the IPD UK Universe drawn from across all PAS segments. Incorporating a range of controls such as unexpired lease term, vacancy rate and tenant credit risk, hedonic regression procedures are used to estimate the effect of EPC rating. The study finds no evidence of a strong relationship between environmental and/or energy performance and rental and capital value. Bearing in mind the small number of BREEAM rated assets, there was a small but statistically significant effect on equivalent yield only. Similarly, there was no evidence that the EPC rating had any effect on Market Rent or Market Value with only minor effects of EPC ratings on equivalent yields. The preliminary conclusion is that energy labelling is not yet having the effects on Market Values and Market Rents that provide incentives for market participants to improve the energy efficiency of their commercial real estate assets.

Individual assets, market structure and the drivers of return

Much UK research and market practice on portfolio strategy and performance benchmarking relies on a sector‐geography subdivision of properties. Prior tests of the appropriateness of such divisions have generally relied on aggregated or hypothetical return data. However, the results found in aggregate may not hold when individual buildings are considered. This paper makes use of a dataset of individual UK property returns. A series of multivariate exploratory statistical techniques are utilised to test whether the return behaviour of individual properties conforms to their a priori grouping. The results suggest strongly that neither standard sector nor regional classifications provide a clear demarcation of individual building performance. This has important implications for both portfolio strategy and performance measurement and benchmarking. However, there do appear to be size and yield effects that help explain return behaviour at the property level.

The viability of sustained growth by India’s MNEs: India’s dual economy and constraints from location assets

This paper considers the longer-term viability of the internationalization and success of Indian multinational enterprises (MNEs). We apply the ‘dual economy’ concept (Lewis, Manch Sch 22(2):139–191, 1954) to reconcile the contradictions of the typical emerging economy, where a ‘modern’ knowledge-intensive economy exists alongside a ‘traditional’ resource-intensive economy. Each type of economy generates firms with different types of ownership advantages, and hence different types of MNEs and internationalisation patterns. We also highlight the vulnerabilities of a growth-by-acquisitions approach. The potential for Indian MNEs to grow requires an understanding of India’s dual economy and the constraints from the home country’s location advantages, particularly those in its knowledge infrastructure.

Using proxies to calculate the carbon impact of investment into electricity network assets

Replacement and upgrading of assets in the electricity network requires financial investment for the distribution and transmission utilities. The replacement and upgrading of network assets also represents an emissions impact due to the carbon embodied in the materials used to manufacture network assets. This paper uses investment and asset data for the GB system for 2015-2023 to assess the suitability of using a proxy with peak demand data and network investment data to calculate the carbon impacts of network investments. The proxies are calculated on a regional basis and applied to calculate the embodied carbon associated with current network assets by DNO region. The proxies are also applied to peak demand data across the 2015-2023 period to estimate the expected levels of embodied carbon that will be associated with network investment during this period. The suitability of these proxies in different contexts are then discussed, along with initial scenario analysis to calculate the impact of avoiding or deferring network investments through distributed generation projects. The proxies were found to be effective in estimating the total embodied carbon of electricity system investment in order to compare investment strategies in different regions of the GB network.

Assets in Accounting: Reality Lost

The aim of this paper is to trace changes in the definitional concept of assets in an attempt to discover why professional accounting bodies in the major English speaking countries have adopted the problematic abstract 'future benefit' notion, which is so far removed from the simple concept of assets as exchangeable things or rights. It is suggested that in the future financial reporting requirements for business entities include a statement of 'separably exchangeable property' and legal obligations at the reporting date.

Empirical evidence from the corporate collapse literature suggesting re-examination of accounting standards in relation to valuation of assets

This paper examines the recent spectacular corporate collapses of Parmalat in Europe, Enron and WorldCom in the USA and HIH in Australia and argues for a re-examination of corporate governance regulations, particularly in relation to accounting standards regarding the valuation of assets. The recommendation that is put forward in this regard is based upon empirical evidence arising from further examination of the empirical results in (Hossari and Rahman, 2004). Specifically, the recommendation is based upon the realization that, among the 48 financial ratios across the 50-plus refereed studies, five financial ratios, all of which contained assets as one of the variables, were a relatively robust indicator of corporate collapse. The five ratios are: Net Income/Total Assets, Current Assets/Current Liabilities, Total Liabilities/Total Assets, Working Capital/Total Assets, and Earnings Before Interest and Taxes/Total Assets. This paper suggests that it's not the failure of the corporate collapse prediction models, rather it's the erosion of the reliability of some key input data, namely assets and the valuation thereof, that is largely responsible for the apparent failure of these models in capturing impending collapses, such as those that we witnessed in the recent past. Such empirical findings support the argument that assets are soft targets for misrepresentation, because of the leeway granted in accounting standards with regards to their valuation.