Real Estate Returns and Inflation: An Added Variable Approach

This study analyses the inflation hedging effectiveness of residential real estate over the 1969-94 period. The results indicate that residential real estate is a significant hedge against both expected and unexpected inflation. These results indicate that since financial assets are not good inflation hedges in periods of high unexpected inflation, including real estate in a portfolio should decrease the variance of the portfolio returns. These results were made possible by the use of the Added Variable Regression Method (AVRM), a measure which has yet to be employed in this context. There are nine variables included in the AVRM framework which are also found to have significant explanatory power relative to residential real estate returns.

An odyssey into local refinement and multilevel preconditioning III: Implementation and numerical experiments

In this paper, we examine a number of additive and multiplicative multilevel iterative methods and preconditioners in the setting of two-dimensional local mesh refinement. While standard multilevel methods are effective for uniform refinement-based discretizations of elliptic equations, they tend to be less effective for algebraic systems, which arise from discretizations on locally refined meshes, losing their optimal behavior in both storage and computational complexity. Our primary focus here is on Bramble, Pasciak, and Xu (BPX)-style additive and multiplicative multilevel preconditioners, and on various stabilizations of the additive and multiplicative hierarchical basis (HB) method, and their use in the local mesh refinement setting. In parts I and II of this trilogy, it was shown that both BPX and wavelet stabilizations of HB have uniformly bounded condition numbers on several classes of locally refined two- and three-dimensional meshes based on fairly standard (and easily implementable) red and red-green mesh refinement algorithms. In this third part of the trilogy, we describe in detail the implementation of these types of algorithms, including detailed discussions of the data structures and traversal algorithms we employ for obtaining optimal storage and computational complexity in our implementations. We show how each of the algorithms can be implemented using standard data types, available in languages such as C and FORTRAN, so that the resulting algorithms have optimal (linear) storage requirements, and so that the resulting multilevel method or preconditioner can be applied with optimal (linear) computational costs. We have successfully used these data structure ideas for both MATLAB and C implementations using the FEtk, an open source finite element software package. We finish the paper with a sequence of numerical experiments illustrating the effectiveness of a number of BPX and stabilized HB variants for several examples requiring local refinement

Company dividends and taxes in the UK

The tax treatment of company dividend payments is an area where corporate taxation interacts with the personal income tax. This interaction raises some awkward issues, such as whether shareholders who are exempt from personal income tax should also be exempt from corporation tax, and if so, then how this can be achieved. The solutions adopted are often complex and certainly diverse, as witnessed by the range of different approaches used in the OECD countries, described in OECD (1991).

An approach for finding long period elliptical orbits for precursor SEI missions

Precursors for Solar System Exploration Initiative (SEI) missions may require long period elliptical orbits about a planet. These orbits will typically have periods on the order of tens to hundreds of days. Some potential uses for these orbits may include the following: studying the effects of galactic cosmic radiation, parking orbits for engineering and operational test of systems, and ferrying orbits between libration points and low altitude orbits. This report presents an approach that can be used to find these orbits. The approach consists of three major steps. First, it uses a restricted three-body targeting algorithm to determine the initial conditions which satisfy certain desired final conditions in a system of two massive primaries. Then the initial conditions are transformed to an inertial coordinate system for use by a special perturbation method. Finally, using the special perturbation method, other perturbations (e.g., sun third body and solar radiation pressure) can be easily incorporated to determine their effects on the nominal trajectory. An algorithm potentially suitable for on-board guidance will also be discussed. This algorithm uses an analytic method relying on Chebyshev polynomials to compute the desired position and velocity of the satellite as a function of time. Together with navigation updates, this algorithm can be implemented to predict the size and timing for AV corrections

Residential Real Estate Prices: A Room with a View

This article is the winner of the Real Estate Broker / Agency manuscript prize (sponsored by the Center for the Study of Real Estate Brokerage/ Agency at Cleveland State University) presented at the 2001 American Real Estate Society Annual Meeting. This study examines the effect that a view of Lake Erie has on the value of a home. Unlike previous studies, the current investigation is able to successfully control for view. That is, because of the unique building codes of lakefront homes in this sample, homes analyzed either do or do not have a view. Moreover, transaction-based home prices are used which is an improvement over previous studies that rely on appraisal-based data. The results indicate that square footage and lot size also significantly affect a home’s value. More importantly, having this very desirable view adds $256,544.72 (an 89.9% premium) to the value of the home.

Pain education issues in developing countries and responses to them by the international association for the study of pain

Unrelieved pain remains a global health problem. There is a major difference between what could be done to relieve pain and what is being done in developing countries – this is known as the ‘treatment gap’. Poor education of health professionals, limited facilities for pain treatment and poor access to drugs for pain relief are contributing factors. While enthusiasm for pain education and clinical training in developing countries has grown, restrictions by governments and health administrations have represented a significant barrier to practice changes. Since 2002, the International Association for the Study of Pain, through its Developing Countries Working Group, has established a series of programs that have resulted in significant improvements in pain education and the clinical management of pain, together with the beginnings of a system of pain centres. These pain centres will act as regional hubs for the future expansion of education and training in pain management in developing countries. Further success will be increased with the demolition of barriers to the treatment of people in pain worldwide

Demand for Money: A Study in Testing Time Series for Long Memory and Nonlinearity

This paper draws attention to the limitations of the standard unit root/cointegration approach to economic and financial modelling, and to some of the alternatives based on the idea of fractional integration, long memory models, and the random field regression approach to nonlinearity. Following brief explanations of fractional integration and random field regression, and the methods of applying them, selected techniques are applied to a demand for money dataset. Comparisons of the results from this illustrative case study are presented, and conclusions are drawn that should aid practitioners in applied time-series econometrics.