Promoting resilience and protective factors in the Children's Fund: supporting children and young people's pathways towards social inclusion?

As part of the broader prevention and social inclusion agenda, concepts of risk, resilience, and protective factors inform a range of U.K. Government initiatives targeted towards children and young people in England, including Sure Start, the Children's Fund, On Track, and Connexions. This paper is based on findings from a large qualitative dataset of interviews conducted with children and their parents or caregiver who accessed Children's Fund services as part of National Evaluation of the Children's Fund research.1 Drawing on the notion of young people's trajectories, the paper discusses how Children's Fund services support children's and young people's pathways towards greater social inclusion. While many services help to build resilience and protective factors for individual children, the paper considers the extent to which services also promote resilience within the domains of the family, school, and wider community and, hence, attempt to tackle the complex, multi-dimensional aspects of social exclusion affecting children, young people, and their families.

Developing responsive preventative practices: key messages from children's and families' experiences of the Children's Fund

As part of the prevention and social inclusion agenda, the Children's Fund, set up in 2000, has developed preventative services for children at risk of social exclusion. Drawing on a large qualitative dataset of interviews conducted in 2004/05 with children, young people and their parents/carers who accessed Children Fund services, this article analyses key practices and approaches valued by children and parents. These included: specialist support tailored to individual support needs, family-oriented approaches, trusting relationships with service providers, multi-agency approaches and sustainability of services. Finally, the article draws out key lessons for the future development of preventative services.

On the question of proportionality of the count of observed Scrapie cases and the size of holding

Background: The present paper investigates the question of a suitable basic model for the number of scrapie cases in a holding and applications of this knowledge to the estimation of scrapie-ffected holding population sizes and adequacy of control measures within holding. Is the number of scrapie cases proportional to the size of the holding in which case it should be incorporated into the parameter of the error distribution for the scrapie counts? Or, is there a different - potentially more complex - relationship between case count and holding size in which case the information about the size of the holding should be better incorporated as a covariate in the modeling? Methods: We show that this question can be appropriately addressed via a simple zero-truncated Poisson model in which the hypothesis of proportionality enters as a special offset-model. Model comparisons can be achieved by means of likelihood ratio testing. The procedure is illustrated by means of surveillance data on classical scrapie in Great Britain. Furthermore, the model with the best fit is used to estimate the size of the scrapie-affected holding population in Great Britain by means of two capture-recapture estimators: the Poisson estimator and the generalized Zelterman estimator. Results: No evidence could be found for the hypothesis of proportionality. In fact, there is some evidence that this relationship follows a curved line which increases for small holdings up to a maximum after which it declines again. Furthermore, it is pointed out how crucial the correct model choice is when applied to capture-recapture estimation on the basis of zero-truncated Poisson models as well as on the basis of the generalized Zelterman estimator. Estimators based on the proportionality model return very different and unreasonable estimates for the population sizes. Conclusion: Our results stress the importance of an adequate modelling approach to the association between holding size and the number of cases of classical scrapie within holding. Reporting artefacts and speculative biological effects are hypothesized as the underlying causes of the observed curved relationship. The lack of adjustment for these artefacts might well render ineffective the current strategies for the control of the disease.

Timing and the holding periods of institutional real estate

Literature on investors' holding periods for securities suggests that high transaction costs are associated with longer holding periods. Return volatility, by contrast, is associated with shorter holding periods. In real estate, high transaction costs and illiquidity imply longer holding periods. Research on depreciation and obsolescence suggests that there might be an optimal holding period. Sales rates and holding periods for U.K. institutional real estate are analyzed, using a proportional hazards model, over an 18-year period. The results show longer holding periods than those claimed by investors, with marked differences by type of property and over time. The results shed light on investor behavior.

Drivers of fund performance: a panel data analysis

The principle aim of this research is to elucidate the factors driving the total rate of return of non-listed funds using a panel data analytical framework. In line with previous results, we find that core funds exhibit lower yet more stable returns than value-added and, in particular, opportunistic funds, both cross-sectionally and over time. After taking into account overall market exposure, as measured by weighted market returns, the excess returns of value-added and opportunity funds are likely to stem from: high leverage, high exposure to development, active asset management and investment in specialized property sectors. A random effects estimation of the panel data model largely confirms the findings obtained from the fixed effects model. Again, the country and sector property effect shows the strongest significance in explaining total returns. The stock market variable is negative which hints at switching effects between competing asset classes. For opportunity funds, on average, the returns attributable to gearing are three times higher than those for value added funds and over five times higher than for core funds. Overall, there is relatively strong evidence indicating that country and sector allocation, style, gearing and fund size combinations impact on the performance of unlisted real estate funds.

Property funds: how much diversification is enough?

t is well known that when assets are randomly-selected and combined in equal proportions in a portfolio, the risk of the portfolio declines as the number of different assets increases without affecting returns. In other words, increasing portfolio size should improve the risk/return trade-off compared with a portfolio of asset size one. Therefore, diversifying among several property funds may be a better alternative for investors compared to holding only one property fund. Nonetheless, it also well known that with naïve diversification although risk always decreases with portfolio size, it does so at a decreasing rate so that at some point the reduction in portfolio risk, from adding another fund, becomes negligible. Based on this fact, a reasonable question to ask is how much diversification is enough, or in other words, how many property funds should be included in a portfolio to minimise return volatility.

Judgments, forecasts and decisions: an analysis of fund managers over time

Decision theory is the study of models of judgement involved in, and leading to, deliberate and (usually) rational choice. In real estate investment there are normative models for the allocation of assets. These asset allocation models suggest an optimum allocation between the respective asset classes based on the investors’ judgements of performance and risk. Real estate is selected, as other assets, on the basis of some criteria, e.g. commonly its marginal contribution to the production of a mean variance efficient multi asset portfolio, subject to the investor’s objectives and capital rationing constraints. However, decisions are made relative to current expectations and current business constraints. Whilst a decision maker may believe in the required optimum exposure levels as dictated by an asset allocation model, the final decision may/will be influenced by factors outside the parameters of the mathematical model. This paper discusses investors' perceptions and attitudes toward real estate and highlights the important difference between theoretical exposure levels and pragmatic business considerations. It develops a model to identify “soft” parameters in decision making which will influence the optimal allocation for that asset class. This “soft” information may relate to behavioural issues such as the tendency to mirror competitors; a desire to meet weight of money objectives; a desire to retain the status quo and many other non-financial considerations. The paper aims to establish the place of property in multi asset portfolios in the UK and examine the asset allocation process in practice, with a view to understanding the decision making process and to look at investors’ perceptions based on an historic analysis of market expectation; a comparison with historic data and an analysis of actual performance.