On the term structure of Interbank interest rates: Jump-diffusion processes and option pricing

In this paper we study the dynamic behavior of the term structureof Interbank interest rates and the pricing of options on interest ratesensitive securities. We posit a generalized single factor model withjumps to take into account external influences in the market. Daily datais used to test for jump effects. Qualitative examination of the linkagebetween Monetary Authorities' interventions and jumps are studied. Pricingresults suggests a systematic underpricing in bonds and call options ifthe jumps component is not included. However, the pricing of put optionson bonds presents indeterminacies.

Phylogeographical structure, postglacial recolonization and barriers to gene flow in the distinctive Valais chromosome race of the common shrew (Sorex araneus).

Using one male-inherited and eight biparentally inherited microsatellite markers, we investigate the population genetic structure of the Valais chromosome race of the common shrew (Sorex araneus) in the Central Alps of Europe. Unexpectedly, the Y-chromosome microsatellite suggests nearly complete absence of male gene flow among populations from the St-Bernard and Simplon regions (Switzerland). Autosomal markers also show significant genetic structuring among these two geographical areas. Isolation by distance is significant and possible barriers to gene flow exist in the study area. Two different approaches are used to better understand the geographical patterns and the causes of this structuring. Using a principal component analysis for which testing procedure exists, and partial Mantel tests, we show that the St-Bernard pass does not represent a significant barrier to gene flow although it culminates at 2469 m, close to the highest altitudinal record for this species. Similar results are found for the Simplon pass, indicating that both passes represented potential postglacial recolonization routes into Switzerland from Italian refugia after the last Pleistocene glaciations. In contrast with the weak effect of these mountain passes, the Rhône valley lowlands significantly reduce gene flow in this species. Natural obstacles (the large Rhône river) and unsuitable habitats (dry slopes) are both present in the valley. Moreover, anthropogenic changes to landscape structures are likely to have strongly reduced available habitats for this shrew in the lowlands, thereby promoting genetic differentiation of populations found on opposite sides of the Rhône valley.

Neutralization of Macrophage Migration Inhibitory Factor (MIF) by Fully Human Antibodies Correlates with Their Specificity for the β-Sheet Structure of MIF.

The macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine that recently emerged as an attractive therapeutic target for a variety of diseases. A diverse panel of fully human anti-MIF antibodies was generated by selection from a phage display library and extensively analyzed in vitro. Epitope mapping studies identified antibodies specific for linear as well as structural epitopes. Experimental animal studies revealed that only those antibodies binding epitopes within amino acids 50-68 or 86-102 of the MIF molecule exerted protective effects in models of sepsis or contact hypersensitivity. Within the MIF protein, these two binding regions form a β-sheet structure that includes the MIF oxidoreductase motif. We therefore conclude that this β-sheet structure is a crucial region for MIF activity and a promising target for anti-MIF antibody therapy.

A Delphi study on National PICU nursing research priorities in Australia and New Zealand.

BACKGROUND: There is a lack of evidence to direct and support nursing practice in the specialty of paediatric intensive care (PIC). The development of national PIC nursing research priorities may facilitate the process of undertaking clinical research and translating evidence into practice. PURPOSE: To (a) identify research priorities for the care of patients and their family as well as for the professional needs of PIC nurses, (b) foster nursing research collaboration, (c) develop a research agenda for PIC nurses. METHODS: Over 13 months in 2007-2008, a three-round questionnaire, using the Delphi technique, was sent to all specialist level registered nurses working in Australian and New Zealand PICUs. This method was used to identify and prioritise nursing research topics. Content analysis was used to analyse Round I data and descriptive statistics for Round II and III data. RESULTS: In Round I, 132 research topics were identified, with 77 research priorities (mdn>6, mean MAD(median) 0.68±0.01) identified in subsequent rounds. The top nine priorities (mean>6 and median>6) included patient issues related to neurological care (n=2), pain/sedation/comfort (n=3), best practice at the end of life (n=1), and ventilation strategies (n=1), as well as two priorities related to professional issues about nurses' stress/burnout and professional development needs. CONCLUSION: The research priorities identified reflect important issues related to critically ill patients and their family as well as to the nurses caring for them. These priorities can be used for the development of a research agenda for PIC nursing in Australia and New Zealand.

Human capital, the structure of production and growth

Do high levels of human capital foster economic growth by facilitating technology adoption? If so, countries with more human capital should have adopted more rapidly the skilled-labor augmenting technologies becoming available since the 1970 s. High human capital levels should therefore have translated into fast growth in more compared to less human-capital-intensive industries in the 1980 s. Theories of international specialization point to human capital accumulation as another important determinant of growth in human-capital-intensive industries. Using data for a large sample of countries, we find significant positive effects of human capital levels and human capital accumulation on output and employment growth in human-capital-intensive industries.

Aggregate fluctuations and the network structure of intersectoral trade

This paper analyzes the flow of intermediate inputs across sectors by adopting a network perspective on sectoral interactions. I apply these tools to show how fluctuationsin aggregate economic activity can be obtained from independent shocks to individualsectors. First, I characterize the network structure of input trade in the U.S. On thedemand side, a typical sector relies on a small number of key inputs and sectors arehomogeneous in this respect. However, in their role as input-suppliers sectors do differ:many specialized input suppliers coexist alongside general purpose sectors functioningas hubs to the economy. I then develop a model of intersectoral linkages that can reproduce these connectivity features. In a standard multisector setup, I use this modelto provide analytical expressions linking aggregate volatility to the network structureof input trade. I show that the presence of sectoral hubs - by coupling productiondecisions across sectors - leads to fluctuations in aggregates.

Structure of bee-flower system in the coastal sand dune of Abaeté, northeastern Brazil

For twelve months (from January to December of 1996) we investigated bee-flower interactions in a sea coastal ecosystem in Bahia, Brazil. Samples were taken three times each month. 3983 individuals belonging to 49 bee species, grouped in 13 morph-functional categories, visited 66 plant species belonging to 39 botanic families. It was observed 310 interactions between bees and plants at species level. The use of floral resources by bees was not homogeneous; most of the plant species received a low number of visitors. No restricted plant-bee species relationship in resource use concerning the subset of analyzed interactions was detected. In Abaeté the generalist relationships predominated.

Protecting Your Spouse When You Go to a Nursing Home, July 2007

The Spousal Impoverishment Protection Law Have you ever wondered… What will happen if your spouse is not able to live at home because of poor health or confusion? Will you have to spend all of your resources to pay for your spouse’s nursing home care before Medicaid will help? The answer is, “NO”! You have protection from losing all income and assets to pay for your spouse’s care in the nursing home when your spouse qualifies for Medicaid.

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Heritability of left ventricular structure and function in Caucasian families.

AIMS: The aim of this study was to investigate the heritability as well as genetic and environmental correlations of left ventricular (LV) structural and functional traits in complex pedigrees of a Caucasian population. METHODS AND RESULTS: We randomly recruited 459 white European subjects from 52 families (50% women; mean age 45 years). LV structure was measured by M-mode and 2D echocardiography and LV function was measured by conventional Doppler and tissue Doppler imaging (TDI). Other measurements included blood pressure, anthropometric, and biochemical measurements. We estimated the heritability of LV traits while adjusting for covariables, including sex, age, body height and weight, systolic and diastolic blood pressures, and heart rate. With full adjustment, heritability of LV mass was 0.23 (P= 0.025). The TDI-derived mitral annular velocities Ea and Aa showed moderate heritability (h(2)= 0.36 and 0.53, respectively), whereas the mitral inflow A peak had weak heritability (h(2) = 0.25) and the E peak was not heritable (h(2) = 0.11). We partitioned the total phenotypic correlation when it reached significance, into a genetic and an environmental component. The genetic correlations were 0.61 between the E and Ea peaks and 0.90 between the A and Aa peaks. CONCLUSION: Our study demonstrated moderate heritability for LV mass as well as the mitral annular Ea and Aa peaks. We also found significant genetic correlations between the E and Ea peaks and between the A and Aa peaks. Our current findings support the ongoing research to map and detect genetic variants that contribute to the variation in LV mass and other LV structural and functional phenotypes.

How much structure in empirical models?

This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature of DSGE models. The problems can be patched up in a number of ways but solved only if DSGEs are completely reparametrized or respecified. The potential misspecification of the structural relationships give Bayesian methods an hedge over classical ones in structural estimation. SVAR approaches may face invertibility problems but simple diagnostics can help to detect and remedy these problems. A pragmatic empirical approach ought to use the flexibility of SVARs against potential misspecificationof the structural relationships but must firmly tie SVARs to the class of DSGE models which could have have generated the data.