Development and economic growth: the effectiveness of traditional policies

The empirical evidence of low effectiveness for growth of investment in physical and human capital policies based on international aid is analyzed and discussed (§ 1 and 2). Reasons are linked both to limits of analytical and econometric methods (§ 4) and the existence of strong complementarities between different dimensions of macroeconomic, social and institutional context (§ 3). We critically discuss the new strategies proposed to gain effectiveness in development projects and policies.Aid Effectiveness, Growth Policies, Institutions, Development

Optimizing Associative Information Transfer within Content-addressable Memory

Original article can be found at: http://www.oldcitypublishing.com/IJUC/IJUC.htmlPeer reviewe

Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks

The pattern of sleep stages across a night (sleep architecture) is influenced by biological, behavioral, and clinical variables. However, traditional measures of sleep architecture such as stage proportions, fail to capture sleep dynamics. Here we quantify the impact of individual differences on the dynamics of sleep architecture and determine which factors or set of factors best predict the next sleep stage from current stage information. We investigated the influence of age, sex, body mass index, time of day, and sleep time on static (e.g. minutes in stage, sleep efficiency) and dynamic measures of sleep architecture (e.g. transition probabilities and stage duration distributions) using a large dataset of 3202 nights from a non-clinical population. Multi-level regressions show that sex effects duration of all Non-Rapid Eye Movement (NREM) stages, and age has a curvilinear relationship for Wake After Sleep Onset (WASO) and slow wave sleep (SWS) minutes. Bayesian network modeling reveals sleep architecture depends on time of day, total sleep time, age and sex, but not BMI. Older adults, and particularly males, have shorter bouts (more fragmentation) of Stage 2, SWS, and they transition less frequently to these stages. Additionally, we showed that the next sleep stage and its duration can be optimally predicted by the prior 2 stages and age. Our results demonstrate the potential benefit of big data and Bayesian network approaches in quantifying static and dynamic architecture of normal sleep

MetAssign: probabilistic annotation of metabolites from LC–MS data using a Bayesian clustering approach

Motivation: The use of liquid chromatography coupled to mass spectrometry (LC–MS) has enabled the high-throughput profiling of the metabolite composition of biological samples. However, the large amount of data obtained can be difficult to analyse and often requires computational processing to understand which metabolites are present in a sample. This paper looks at the dual problem of annotating peaks in a sample with a metabolite, together with putatively annotating whether a metabolite is present in the sample. The starting point of the approach is a Bayesian clustering of peaks into groups, each corresponding to putative adducts and isotopes of a single metabolite.<p></p> Results: The Bayesian modelling introduced here combines information from the mass-to-charge ratio, retention time and intensity of each peak, together with a model of the inter-peak dependency structure, to increase the accuracy of peak annotation. The results inherently contain a quantitative estimate of confidence in the peak annotations and allow an accurate trade off between precision and recall. Extensive validation experiments using authentic chemical standards show that this system is able to produce more accurate putative identifications than other state-of-the-art systems, while at the same time giving a probabilistic measure of confidence in the annotations.<p></p> Availability: The software has been implemented as part of the mzMatch metabolomics analysis pipeline, which is available for download at http://mzmatch.sourceforge.net/

Impact of Sleep and Circadian Disruption on Energy Balance and Diabetes: A Summary of Workshop Discussions

A workshop was held at the National Institute for Diabetes and Digestive and Kidney Diseases with a focus on the impact of sleep and circadian disruption on energy balance and diabetes. The workshop identified a number of key principles for research in this area and a number of specific opportunities. Studies in this area would be facilitated by active collaboration between investigators in sleep/circadian research and investigators in metabolism/diabetes. There is a need to translate the elegant findings from basic research into improving the metabolic health of the American public. There is also a need for investigators studying the impact of sleep/circadian disruption in humans to move beyond measurements of insulin and glucose and conduct more in-depth phenotyping. There is also a need for the assessments of sleep and circadian rhythms as well as assessments for sleep-disordered breathing to be incorporated into all ongoing cohort studies related to diabetes risk. Studies in humans need to complement the elegant short-term laboratory-based human studies of simulated short sleep and shift work etc. with studies in subjects in the general population with these disorders. It is conceivable that chronic adaptations occur, and if so, the mechanisms by which they occur needs to be identified and understood. Particular areas of opportunity that are ready for translation are studies to address whether CPAP treatment of patients with pre-diabetes and obstructive sleep apnea (OSA) prevents or delays the onset of diabetes and whether temporal restricted feeding has the same impact on obesity rates in humans as it does in mice

Economic and Political Determinants of Budget Deficits in the European Union: A Dynamic Random Coefficient Approach

This paper formulates a dynamic Random Coefficient Model (RCM) to consider a set of popular determinants of public deficits in the EU-15 over the period 1971-2006, both at a country-specific level and from a population-wide perspective. Although the extent of government deficits and debt has been one of the most debated macroeconomic issues in recent times, the models trying to capture the explanatory powers driving these deficits typically estimate models that pose the strict assumption of homogeneity on the coefficients over all countries in the model. The sensibility of this assumption will be investigated, with results showing that an increase in the degree of heterogeneity leads to an improvement in the model fit and provides additional information to nuance the effects of the explanatory variables. In this way, the paper exposes a limited degree of partisanship over all countries under consideration, but on the other hand provides evidence for opportunistic behaviour of policymakers in the major part of the sample. The effect of institutional changes following the enforcement of the Maastricht Treaty varies over the countries and is related to the necessity of budgetary consolidation.fiscal policy, European Monetary Union, Random Coefficient Model, Bayesian Analysis

The Gravity of R&D FDIs.

The negative effect of distance is justified by the existence of transport costs which hamper the international exchange of final and intermediate goods, and by higher uncertainty about local markets. We submit that distance plays a remarkably different role in the case of R&D FDIs since they mainly involve the international transfer, absorption and use of knowledge. Using data on bilateral investment projects in R&D, manufacturing and other business activities between 58 countries, we find that geographic distance does not hinder R&D FDIs as much as in the case of production and other investment activities. Furthermore, once we control for institutional and psychic distance, in particular language and religious differences, the negative effect of geographic distance vanishes.Multinational Firms, International Business, Technological Change, Choices and Consequences, Diffusion Processes.

FLOODING RISK AND HOUSING VALUES: AN ECONOMIC ASSESSMENT OF ENVIRONMENTAL HAZARD

Climate change, the ‘boom and bust’ cycles of rivers, and altered water resource management practice have caused significant changes in the spatial distribution of the risk of flooding. Hedonic pricing studies, predominantly for the US, have assessed the spatial incidence of risk and the associated implicit price of flooding risk. Using these implicit price estimates and their associated standard errors, we perform a meta-analysis and find that houses located in the 100-year floodplain have a –0.3 to –0.8% lower price. The actual occurrence of a flooding event or increased stringency in disclosure rules causes ex ante prices to differ from ex post prices, but these effects are small. The marginal willingness to pay for reduced risk exposure has increased over time, and it is slightly lower for areas with a higher per capita income. We show that obfuscating amenity effects and risk exposure associated with proximity to water causes systematic bias in the implicit price of flooding risk.Manufactured Housing; valuation, environmental risk, meta-analysis, hedonic pricing