The Role of Institutions in Cross-Section Income and Panel Data Growth Models: A Deeper Investigation on the Weakness and Proliferation of Instruments

This paper investigates the role of institutions in determining per capita income levels and growth. It contributes to the empirical literature by using different variables as proxies for institutions and by developing a deeper analysis of the issues arising from the use of weak and too many instruments in per capita income and growth regressions. The cross-section estimation suggests that institutions seem to matter, regardless if they are the only explanatory variable or are combined with geographical and integration variables, although most models suffer from the issue of weak instruments. The results from the growth models provides some interesting results: there is mixed evidence on the role of institutions and such evidence is more likely to be associated with law and order and investment profile; government spending is an important policy variable; collapsing the number of instruments results in fewer significant coefficients for institutions.

Comparing the early research performance of PhD graduates in labor economics in Europe and the USA

This paper analyzes the early research performance of PhD graduates in labor economics, addressing the following questions: Are there major productivity differences between graduates from American and European institutions? If so, how relevant is the quality of the training received (i.e. ranking of institution and supervisor) and the research environment in the subsequent job placement institution? The population under study consists of labor economics PhD graduates who received their degree in the years 2000 to 2005 in Europe or the USA. Research productivity is evaluated alternatively as the number of publications or the quality-adjusted number of publications of an individual. When restricting the analysis to the number of publications, results suggest a higher productivity by graduates from European universities than from USA universities, but this difference vanishes when accounting for the quality of the publication. The results also indicate that graduates placed at American institutions, in particular top ones, are likely to publish more quality-adjusted articles than their European counterparts. This may be because, when hired, they already have several good acceptances or because of more focused research efforts and clearer career incentives.

Assessing Spiritual Distress in Elderly Patients Undergoing Rehabilitation

Spiritual distress has been associated with worse health outcomes. Assessing patient's spirituality seems especially relevant in older patients undergoing post-acute rehabilitation. However, few instruments are designed to assess spiritual distress. The objectives of this research were 1) to conceptualize the spiritual dimension and to develop an instrument to assess spiritual distress in hospitalized older patients; 2) to determine spiritual distress prevalence and to investigate its relationship with rehab outcomes. A qualitative approach was used to develop the Spiritual Distress Assessment Tool (SDAT). The SDAT is a semi-structured interview that assess unmet spiritual needs, and quantifies spiritual distress. In a pilot study among rehab patients (N=69, 82.58.3 years), 61% reported spiritual distress. Compared to the others, these patients had more functional impairment and tended to have longer stay. Further studies are needed to determine whether spiritual intervention would be effective to address spiritual distress and improve health outcomes.

New roles for community pharmacists in modern health care systems: a challenge for pharmacy education and research.

The academic activities led by the Unit of Community Pharmacy can be classified as translational. Our group is interested in person-centered pharmaceutical services aimed at a more responsible use of drugs (effectiveness, safety, efficiency) in collaboration with physicians and other health care professionals in a primary care setting. The following domains of education and research are high priorities for our group: medication therapy management, medication adherence, integrated care, individualization of therapies, care management for the elderly and e-health.

Multilayer perceptron with local constraint as an emerging method in spatial data analysis

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.

The research on radioprotective agents in Chinese materia medica

A series of studies has been carried out in the field of traditional medicine for searching radio-protective agents. According to the theory of traditional Chinese medicine, may prescriptions were tested with experimental animals. Some of them could raise the survival rate of dogs irradiated with lethal dose of Pi-rays by 30-40%. Some symptoms of radiation sickness could be improved. More than one thousand kinds of Chinese herbs were screened. Some of them have pronounced radioprotectice activities. A series of bioactive components wee isolated from these herbs. The mechanism of radiation protection were studied. Having the capability of hemopoietic system and immune system may be the characteristics of these Chinese herbs.

Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.