The distributional consequences of supply-side reforms in general equilibrium

This paper addresses the issue on whether tax reforms consistent with lower public debt-to-GDP in the long-run can lead to a more efficient and equitable economy. To this end we solve a heterogeneous agent model comprised of a government, a representative capitalist and representative skilled and unskilled workers, under both rational expectations and adaptive learning. Our main findings are that (i) reductions in capital taxation, while beneficial at the aggregate level, lead to increased inequality mainly due to the substitutability of un- skilled labour and capital; (ii) a fall in taxation for skilled labour is Pareto improving, which is largely explained by its complementarity with the other factor inputs; (iii) all agents would prefer increasing the tax rate on capital to increasing the tax rate on skilled and un- skilled labour since it leads to relatively lower welfare losses; and (iv) heterogeneity in initial beliefs under adaptive learning quantitatively matters for welfare.tax reform, structural heterogeneity, inequality, adaptive learning

The Distributional Consequences of Supply-Side Reforms in General Equilibrium

Using a heterogeneous agent model allowing for different degrees of complementarity between capital, skilled and unskilled labour, this paper evaluates supply-side reforms consistent with lower public debt-to-GDP in the long-run. We find that, relative to the other tax reforms, capital tax cuts lead to the highest aggregate welfare but are skill-biased and can thus increase inequality in the long-run. Depending on the elasticity of substitution between capital and unskilled labour, falls in the capital tax can result in welfare losses for unskilled workers, even in the absence of other frictions and increases in other forms of taxation. On the other hand, reductions in labour taxes can hurt the capitalists. We also show that including the transition period in the welfare evaluation lowers the inequality effects of capital tax reduc-tions since the complementarity between capital and all labour inputs is higher in the short- than in the long-run. Finally, our results suggest that a form of "irrational exuberance" can arise after a tax cut under heterogeneous learning in the initial conditions after the reform.tax reform, structural heterogeneity, inequality, adaptive learning

The distributional consequences of supply-side reforms in general equilibrium

Using a heterogeneous agent model allowing for different degrees of complementarity between capital, skilled and unskilled labour, this paper evaluates supply-side reforms consistent with lower public debt-to-GDP in the long-run. We find that, relative to the other tax reforms, capital tax cuts lead to the highest aggregate welfare but are skill-biased and can thus increase inequality in the long-run. Depending on the elasticity of substitution between capital and unskilled labour, falls in the capital tax can result in welfare losses for unskilled workers, even in the absence of other frictions and increases in other forms of taxation. On the other hand, reductions in labour taxes can hurt the capitalists. We also show that including the transition period in the welfare evaluation lowers the inequality effects of capital tax reduc-tions since the complementarity between capital and all labour inputs is higher in the short- than in the long-run. Finally, our results suggest that a form of irrational exuberance can arise after a tax cut under heterogeneous learning in the initial conditions after the reform

A high-density transcript linkage map with 1,845 expressed genes positioned by microarray-based Single Feature Polymorphisms (SFP) in Eucalyptus

<p>Abstract</p> <p>Background</p> <p>Technological advances are progressively increasing the application of genomics to a wider array of economically and ecologically important species. High-density maps enriched for transcribed genes facilitate the discovery of connections between genes and phenotypes. We report the construction of a high-density linkage map of expressed genes for the heterozygous genome of <it>Eucalyptus </it>using Single Feature Polymorphism (SFP) markers.</p> <p>Results</p> <p>SFP discovery and mapping was achieved using pseudo-testcross screening and selective mapping to simultaneously optimize linkage mapping and microarray costs. SFP genotyping was carried out by hybridizing complementary RNA prepared from 4.5 year-old trees xylem to an SFP array containing 103,000 25-mer oligonucleotide probes representing 20,726 unigenes derived from a modest size expressed sequence tags collection. An SFP-mapping microarray with 43,777 selected candidate SFP probes representing 15,698 genes was subsequently designed and used to genotype SFPs in a larger subset of the segregating population drawn by selective mapping. A total of 1,845 genes were mapped, with 884 of them ordered with high likelihood support on a framework map anchored to 180 microsatellites with average density of 1.2 cM. Using more probes per unigene increased by two-fold the likelihood of detecting segregating SFPs eventually resulting in more genes mapped. <it>In silico </it>validation showed that 87% of the SFPs map to the expected location on the 4.5X draft sequence of the <it>Eucalyptus grandis </it>genome.</p> <p>Conclusions</p> <p>The <it>Eucalyptus </it>1,845 gene map is the most highly enriched map for transcriptional information for any forest tree species to date. It represents a major improvement on the number of genes previously positioned on <it>Eucalyptus </it>maps and provides an initial glimpse at the gene space for this global tree genome. A general protocol is proposed to build high-density transcript linkage maps in less characterized plant species by SFP genotyping with a concurrent objective of reducing microarray costs. HIgh-density gene-rich maps represent a powerful resource to assist gene discovery endeavors when used in combination with QTL and association mapping and should be especially valuable to assist the assembly of reference genome sequences soon to come for several plant and animal species.</p

The comparative responsiveness of Hospital Universitario Princesa Index and other composite indices for assessing rheumatoid arthritis activity

Objective To evaluate the responsiveness in terms of correlation of the Hospital Universitario La Princesa Index (HUPI) comparatively to the traditional composite indices used to assess disease activity in rheumatoid arthritis (RA), and to compare the performance of HUPI-based response criteria with that of the EULAR response criteria. Methods Secondary data analysis from the following studies: ACT-RAY (clinical trial), PROAR (early RA cohort) and EMECAR (pre-biologic era long term RA cohort). Responsiveness was evaluated by: 1) comparing change from baseline (Delta) of HUPI with Delta in other scores by calculating correlation coefficients; 2) calculating standardised effect sizes. The accuracy of response by HUPI and by EULAR criteria was analyzed using linear regressions in which the dependent variable was change in global assessment by physician (Delta GDA-Phy). Results Delta HUPI correlation with change in all other indices ranged from 0.387 to 0.791); HUPI's standardized effect size was larger than those from the other indices in each database used. In ACT-RAY, depending on visit, between 65 and 80% of patients were equally classified by HUPI and EULAR response criteria. However, HUPI criteria were slightly more stringent, with higher percentage of patients classified as non-responder, especially at early visits. HUPI response criteria showed a slightly higher accuracy than EULAR response criteria when using Delta GDA-Phy as gold standard. Conclusion HUPI shows good responsiveness in terms of correlation in each studied scenario (clinical trial, early RA cohort, and established RA cohort). Response criteria by HUPI seem more stringent than EULAR''s

Genetic diversity, linkage disequilibrium and power of a large grapevine (Vitis vinifera L) diversity panel newly designed for association studies

UMR-AGAP Equipe DAVV (Diversité, adaptation et amélioration de la vigne) ; équipe ID (Intégration de Données)International audienceAbstractBackgroundAs for many crops, new high-quality grapevine varieties requiring less pesticide and adapted to climate change are needed. In perennial species, breeding is a long process which can be speeded up by gaining knowledge about quantitative trait loci linked to agronomic traits variation. However, due to the long juvenile period of these species, establishing numerous highly recombinant populations for high resolution mapping is both costly and time-consuming. Genome wide association studies in germplasm panels is an alternative method of choice, since it allows identifying the main quantitative trait loci with high resolution by exploiting past recombination events between cultivars. Such studies require adequate panel design to represent most of the available genetic and phenotypic diversity. Assessing linkage disequilibrium extent and panel power is also needed to determine the marker density required for association studies.ResultsStarting from the largest grapevine collection worldwide maintained in Vassal (France), we designed a diversity panel of 279 cultivars with limited relatedness, reflecting the low structuration in three genetic pools resulting from different uses (table vs wine) and geographical origin (East vs West), and including the major founders of modern cultivars. With 20 simple sequence repeat markers and five quantitative traits, we showed that our panel adequately captured most of the genetic and phenotypic diversity existing within the entire Vassal collection. To assess linkage disequilibrium extent and panel power, we genotyped single nucleotide polymorphisms: 372 over four genomic regions and 129 distributed over the whole genome. Linkage disequilibrium, measured by correlation corrected for kinship, reached 0.2 for a physical distance between 9 and 458 Kb depending on genetic pool and genomic region, with varying size of linkage disequilibrium blocks. This panel achieved reasonable power to detect associations between traits with high broad-sense heritability (> 0.7) and causal loci with intermediate allelic frequency and strong effect (explaining > 10 % of total variance).ConclusionsOur association panel constitutes a new, highly valuable resource for genetic association studies in grapevine, and deserves dissemination to diverse field and greenhouse trials to gain more insight into the genetic control of many agronomic traits and their interaction with the environment

Micromechanical Properties of Injection-Molded Starch–Wood Particle Composites

The micromechanical properties of injection molded starch–wood particle composites were investigated as a function of particle content and humidity conditions. The composite materials were characterized by scanning electron microscopy and X-ray diffraction methods. The microhardness of the composites was shown to increase notably with the concentration of the wood particles. In addition,creep behavior under the indenter and temperature dependence were evaluated in terms of the independent contribution of the starch matrix and the wood microparticles to the hardness value. The influence of drying time on the density and weight uptake of the injection-molded composites was highlighted. The results revealed the role of the mechanism of water evaporation, showing that the dependence of water uptake and temperature was greater for the starch–wood composites than for the pure starch sample. Experiments performed during the drying process at 70°C indicated that the wood in the starch composites did not prevent water loss from the samples.Peer reviewe

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types