52 research outputs found

    Presentation of the Three-ME model: Multi-sector Macroeconomic Model for the Evaluation of Environmental and Energy policy

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    This paper presents the structure and the main properties of Three-ME. This new model of the French economy has been especially designed to evaluate the medium and long term impact of environmental and energy policies at the macroeconomic and sector levels. To do so Three-ME combines two important features. Firstly, it has the main characteristics of neo-Keynesian models by assuming a slow adjustment of effective quantities and prices to their notional level. Compared to standard multi-sectors CGEM, this has the advantage to allow for the existence of under-optimum equilibriums such as the presence of involuntary unemployment. Secondly, production and consumption structures are represented with a generalized CES function which allows for the elasticity of substitution to differ between each couple of inputs or goods. This is an improvement compared to the standard approach that uses nested CES functions which has the disadvantage to impose a common elasticity of substitution between the goods located in two different nested structures.neo-Keynesian model, macroeconomic modeling, energy and environmental policy modeling

    Real time estimation of potential output and output gap for theeuro-area: comparing production function with unobserved componentsand SVAR approaches

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    We develop a new version of the production function (PF) approach usually used for estimating the output gap of the euro area. Our version does not call for any (often imprecise) measure of the capital stock and improves the estimation of the trend total factor productivity. We asses this approach by comparing it with two other multivariate methods mostly used for output gap estimates, a multivariate unobserved components (MUC) model and a Structural Vector Auto-Regressive (SVAR) model. The comparison is conducted by relying on assessment criteria such as the concordance of the turning points chronology with a reference one, the inflation forecasting power and the real-time consistency of the estimates. Two contributions are achieved. Firstly, we take into account data revisions and their impact on the output gap estimates by using vintage datasets coming from the Euro Area Business Cycle (EABCN) Real-Time Data-Base (RTDB). Secondly, the PF approach, generally employed by policy-makers despite of its difficult implementation, is assessed. We thus improve on previous papers which limited their assessment on other multivariate methods, e.g. MUC or SVAR models. The different methods show different ranks in relation to the three criteria. This new PF estimate appears highly concordant with the reference chronology. Its forecasting power appears favourable only for the shortest horizon (1 month). Finally, the SVAR model appears more consistent in real-time.potential output, production function, state-space models, structural VARs

    Real time estimation of potential output and output gap for theeuro-area: comparing production function with unobserved componentsand SVAR approaches

    Get PDF
    We develop a new version of the production function (PF) approach usually used for estimating the output gap of the euro area. Our version does not call for any (often imprecise) measure of the capital stock and improves the estimation of the trend total factor productivity. We asses this approach by comparing it with two other multivariate methods mostly used for output gap estimates, a multivariate unobserved components (MUC) model and a Structural Vector Auto-Regressive (SVAR) model. The comparison is conducted by relying on assessment criteria such as the concordance of the turning points chronology with a reference one, the inflation forecasting power and the real-time consistency of the estimates. Two contributions are achieved. Firstly, we take into account data revisions and their impact on the output gap estimates by using vintage datasets coming from the Euro Area Business Cycle (EABCN) Real-Time Data-Base (RTDB). Secondly, the PF approach, generally employed by policy-makers despite of its difficult implementation, is assessed. We thus improve on previous papers which limited their assessment on other multivariate methods, e.g. MUC or SVAR models. The different methods show different ranks in relation to the three criteria. This new PF estimate appears highly concordant with the reference chronology. Its forecasting power appears favourable only for the shortest horizon (1 month). Finally, the SVAR model appears more consistent in real-time

    Plasmodium falciparum parasite population structure and gene flow associated to anti-malarial drugs resistance in Cambodia

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    Background: Western Cambodia is recognized as the epicentre of emergence of Plasmodium falciparum multi-drug resistance. The emergence of artemisinin resistance has been observed in this area since 2008–2009 and molecular signatures associated to artemisinin resistance have been characterized in k13 gene. At present, one of the major threats faced, is the possible spread of Asian artemisinin resistant parasites over the world threatening millions of people and jeopardizing malaria elimination programme efforts. To anticipate the diffusion of artemisinin resistance, the identification of the P. falciparum population structure and the gene flow among the parasite population in Cambodia are essential. Methods: To this end, a mid-throughput PCR-LDR-FMA approach based on LUMINEX technology was developed to screen for genetic barcode in 533 blood samples collected in 2010–2011 from 16 health centres in malaria endemics areas in Cambodia. Results: Based on successful typing of 282 samples, subpopulations were characterized along the borders of the country. Each 11-loci barcode provides evidence supporting allele distribution gradient related to subpopulations and gene flow. The 11-loci barcode successfully identifies recently emerging parasite subpopulations in western Cambodia that are associated with the C580Y dominant allele for artemisinin resistance in k13 gene. A subpopulation was identified in northern Cambodia that was associated to artemisinin (R539T resistant allele of k13 gene) and mefloquine resistance. Conclusions: The gene flow between these subpopulations might have driven the spread of artemisinin resistance over Cambodia

    Staphylococcus aureus infective endocarditis versus bacteremia strains: Subtle genetic differences at stake

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    AbstractInfective endocarditis (IE)(1) is a severe condition complicating 10–25% of Staphylococcus aureus bacteremia. Although host-related IE risk factors have been identified, the involvement of bacterial features in IE complication is still unclear. We characterized strictly defined IE and bacteremia isolates and searched for discriminant features. S. aureus isolates causing community-acquired, definite native-valve IE (n=72) and bacteremia (n=54) were collected prospectively as part of a French multicenter cohort. Phenotypic traits previously reported or hypothesized to be involved in staphylococcal IE pathogenesis were tested. In parallel, the genotypic profiles of all isolates, obtained by microarray, were analyzed by discriminant analysis of principal components (DAPC)(2). No significant difference was observed between IE and bacteremia strains, regarding either phenotypic or genotypic univariate analyses. However, the multivariate statistical tool DAPC, applied on microarray data, segregated IE and bacteremia isolates: IE isolates were correctly reassigned as such in 80.6% of the cases (C-statistic 0.83, P<0.001). The performance of this model was confirmed with an independent French collection IE and bacteremia isolates (78.8% reassignment, C-statistic 0.65, P<0.01). Finally, a simple linear discriminant function based on a subset of 8 genetic markers retained valuable performance both in study collection (86.1%, P<0.001) and in the independent validation collection (81.8%, P<0.01). We here show that community-acquired IE and bacteremia S. aureus isolates are genetically distinct based on subtle combinations of genetic markers. This finding provides the proof of concept that bacterial characteristics may contribute to the occurrence of IE in patients with S. aureus bacteremia
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