Another look at the relative importance of sectors and regions in determining property returns

This paper re-examines the relative importance of sector and regional effects in determining property returns. Using the largest property database currently available in the world, we decompose the returns on individual properties into a national effect, common to all properties, and a number of sector and regional factors. However, unlike previous studies, we categorise the individual property data into an ever-increasing number of property-types and regions, from a simple 3-by-3 classification, up to a 10 by 63 sector/region classification. In this way we can test the impact that a finer classification has on the sector and regional effects. We confirm the earlier findings of previous studies that sector-specific effects have a greater influence on property returns than regional effects. We also find that the impact of the sector effect is robust across different classifications of sectors and regions. Nonetheless, the more refined sector and regional partitions uncover some interesting sector and regional differences, which were obscured in previous studies. All of which has important implications for property portfolio construction and analysis.

Changes in the relative importance of sector and regional factors: 1987-2002

A stylised fact in the real estate portfolio diversification literature is that sector (property-type) effects are relatively more important than regional (geographical) factors in determining property returns. Thus, for those portfolio managers who follow a top-down approach to portfolio management, they should first choose in which sectors to invest and then select the best properties in each market. However, the question arises as to whether the dominance of the sector effects relative to regional effects is constant. If not property fund managers will need to take account of regional effects in developing their portfolio strategy. Using monthly data over the period 1987:1 to 2002:12 for a sample of over 1000 properties the results show that the sector-specific factors dominate the regional-specific factors for the vast majority of the time. Nonetheless, there are periods when the regional factors are of equal or greater importance than the sector effects. In particular, the sector effects tend to dominate during volatile periods of the real estate cycle; however, during calmer periods the sector and regional effects are of equal importance. These findings suggest that the sector effects are still the most important aspect in the development of an active portfolio strategy.

Relative order defines a topology for recurrent networks

This paper uses techniques from control theory in the analysis of trained recurrent neural networks. Differential geometry is used as a framework, which allows the concept of relative order to be applied to neural networks. Any system possessing finite relative order has a left-inverse. Any recurrent network with finite relative order also has an inverse, which is shown to be a recurrent network.

Quantitative plant proteomics

Quantitation is an inherent requirement in comparative proteomics and there is no exception to this for plant proteomics. Quantitative proteomics has high demands on the experimental workflow, requiring a thorough design and often a complex multi-step structure. It has to include sufficient numbers of biological and technical replicates and methods that are able to facilitate a quantitative signal read-out. Quantitative plant proteomics in particular poses many additional challenges but because of the nature of plants it also offers some potential advantages. In general, analysis of plants has been less prominent in proteomics. Low protein concentration, difficulties in protein extraction, genome multiploidy, high Rubisco abundance in green tissue, and an absence of well-annotated and completed genome sequences are some of the main challenges in plant proteomics. However, the latter is now changing with several genomes emerging for model plants and crops such as potato, tomato, soybean, rice, maize and barley. This review discusses the current status in quantitative plant proteomics (MS-based and non-MS-based) and its challenges and potentials. Both relative and absolute quantitation methods in plant proteomics from DIGE to MS-based analysis after isotope labeling and label-free quantitation are described and illustrated by published studies. In particular, we describe plant-specific quantitative methods such as metabolic labeling methods that can take full advantage of plant metabolism and culture practices, and discuss other potential advantages and challenges that may arise from the unique properties of plants.

A comparison of the relative toxicity of bone meal and other P sources used as remedial treatments to the earthworm Eisenia fetida

It has been suggested that sources of P could be used to remediate metal-contaminated soil. The toxicity of four potential P sources, potassium hydrogen phosphate (PHP), triple superphosphate (TSP), rock phosphate (RP) and raw bone meal (RBM) to Eisenia fetida was determined. The concentration of P that is statistically likely to kill 50% of the population (LC50) for PHP, TSP and RBM was determined in OECD acute toxicity tests. 14 day LC50s expressed as bulk P concentration lay in the range 3319–4272 mg kg−1 for PHP, 3107–3590 mg kg−1 for TSP and 1782–2196 mg kg−1 for RBM (ranges present the 95% confidence intervals). For PHP and TSP mortality was significantly impacted by the electrical conductivity of the treated soils. No consistent relationship existed between mortality and electrical conductivity, soil pH and available (Olsen) P across the PHP, TSP and RBM amendment types. In RP toxicity tests mortality was low and it was not possible to determine a LC50 value. Incineration of bone meal at temperatures between 200 and 300 ◦C, pre-washing the bone meal, co-amendment with 5% green waste compost and delaying introduction of earthworms after bone meal amendments by 21 days or more led to significant reductions in the bone meal toxicity. These results are consistent with the toxicity being associated with the release and/or degradation of a soluble organic component present in raw bone meal. Bone meal can be used as an earthworm-friendly remedial amendment in metal-contaminated soils but initial additions may have a negative effect on any earthworms surviving in the contaminated soil before the organic component in the bone meal degrades in the soil.

Unsaturated σ-hydrocarbyl transition-metal complexes. Part 4. Crystal and molecular structure of trans-chlorobis(diethylphenylphosphine)-(phenylethynyl)platinum(II) and comments on the relative trans influence of various carbon ligands

The molecular structure of trans-[PtCl(CCPh)(PEt2Ph)2] has been determined by X-ray diffraction methods. The crystals are monoclinic, space group P21, with a= 12.359(3), b= 13.015(3), c= 9.031(2)Å, β= 101.65(2)°, and Z= 2. The structure has been solved by the heavy-atom method and refined by full-matrix least squares to R 0.046 for 1 877 diffractometric intensity data. The crystals contain discrete molecules in which the platinum coordination is square planar. The phenylethynyl group is non-linear, with a Pt–CC angle of 163(2)°. Selected bond lengths are Pt–Cl 2.407(5) and Pt–C 1.98(2)Å. The structural trans influences of CCPh, CHCH2, and CH2SiMe3 ligands in platinum(II) complexes are compared; there is only a small dependence on hybridization at the ligating carbon atom.

Suitability of pesticide risk indicators for less developed countries: a comparison

Pesticide risk indicators provide simple support in the assessment of environmental and health risks from pesticide use, and can therefore inform policies to foster a sustainable interaction of agriculture with the environment. For their relative simplicity, indicators may be particularly useful under conditions of limited data availability and resources, such as in Less Developed Countries (LDCs). However, indicator complexity can vary significantly, in particular between those that rely on an exposure–toxicity ratio (ETR) and those that do not. In addition, pesticide risk indicators are usually developed for Western contexts, which might cause incorrect estimation in LDCs. This study investigated the appropriateness of seven pesticide risk indicators for use in LDCs, with reference to smallholding agriculture in Colombia. Seven farm-level indicators, among which 3 relied on an ETR (POCER, EPRIP, PIRI) and 4 on a non-ETR approach (EIQ, PestScreen, OHRI, Dosemeci et al., 2002), were calculated and then compared by means of the Spearman rank correlation test. Indicators were also compared with respect to key indicator characteristics, i.e. user friendliness and ability to represent the system under study. The comparison of the indicators in terms of the total environmental risk suggests that the indicators not relying on an ETR approach cannot be used as a reliable proxy for more complex, i.e. ETR, indicators. ETR indicators, when user-friendly, show a comparative advantage over non-ETR in best combining the need for a relatively simple tool to be used in contexts of limited data availability and resources, and for a reliable estimation of environmental risk. Non-ETR indicators remain useful and accessible tools to discriminate between different pesticides prior to application. Concerning the human health risk, simple algorithms seem more appropriate for assessing human health risk in LDCs. However, further research on health risk indicators and their validation under LDC conditions is needed.

Farm income, population and farmland prices: a relative information approach

This paper uses an entropy-based information approach to determine if farmland values are more closely associated with urban pressure or farm income. The basic question is: how much information on changes in farm real estate values is contained in changes in population versus changes in returns to production agriculture? Results suggest population is informative, but changes in farmland values are more strongly associated with changes in the distribution of returns. However, this relationship is not true for every region nor does it hold over time, as for some regions and time periods changes in population are more informative. Results have policy implications for both equity and efficiency.