Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean

Time-varying VAR models have become increasingly popular and are now widely used for policy analysis and forecast purposes. They constitute fundamental tools for the anticipation and analysis of economic crises, which represent rapid shifts in dynamic responses and shock volatility. Yet, despite their flexibility, time-varying VARs remain subject to a number of limitations. On the theoretical side, the conventional random walk assumption used for the dynamic parameters appears excessively restrictive. It also conceals the potential heterogeneities existing between the dynamic processes of different variables. On the application side, the standard two-pass procedure building on the Kalman filter proves excessively complicated and suffers from low efficiency. Based on these considerations, this paper contributes to the literature in four directions: i) it introduces a general time-varying VAR model which relaxes the standard random walk assumption and defines the dynamic parameters as general auto-regressive processes with variable- specific mean values and autoregressive coefficients. ii) it develops an estimation procedure for the model which is simple, transparent and efficient. The procedure requires no sophisticated Kalman filtering methods and reduces to a standard Gibbs sampling algorithm. iii) as an extension, it develops efficient procedures to estimate endogenously the mean values and autoregressive coefficients associated with each variable-specific autoregressive process. iv) through a case study of the Great Recession for four major economies (Canada, the Euro Area, Japan and the United States), it establishes that forecast accuracy can be significantly improved by using the proposed general time-varying model and its extensions in place of the traditional random walk specification

Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean

Time-varying VAR models represent fundamental tools for the anticipation and analysis of economic crises. Yet they remain subject to a number of limitations. The conventional random walk assumption used for the dynamic parameters appears excessively restrictive, and the existing estimation procedures are largely inefficient. This paper improves on the existing methodologies in four directions: i) it introduces a general time-varying VAR model which relaxes the standard random walk assumption and defines the dynamic parameters as general autoregressive processes with equation-specific mean values and autoregressive coefficients. ii) it develops an efficient estimation algorithm for the model which proceeds equation by equation and combines the traditional Kalman filter approach with the recent precision sampler methodology. iii) it develops extensions to estimate endogenously the mean values and autoregressive coefficients associated with each dynamic process. iv) through a case study of the Great Recession in four major economies (Canada, the Euro Area, Japan and the United States), it establishes that forecast accuracy can be significantly improved by using the proposed general time-varying model and its extensions in place of the traditional random walk specification

Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean

Time-varying VAR models have become increasingly popular and are now widely used for policy analysis and forecast purposes. They constitute fundamental tools for the anticipation and analysis of economic crises, which represent rapid shifts in dynamic responses and shock volatility. Yet, despite their flexibility, time-varying VARs remain subject to a number of limitations. On the theoretical side, the conventional random walk assumption used for the dynamic parameters appears excessively restrictive. It also conceals the potential heterogeneities existing between the dynamic processes of different variables. On the application side, the standard two-pass procedure building on the Kalman filter proves excessively complicated and suffers from low efficiency. Based on these considerations, this paper contributes to the literature in four directions: i) it introduces a general time-varying VAR model which relaxes the standard random walk assumption and defines the dynamic parameters as general auto-regressive processes with variable- specific mean values and autoregressive coefficients. ii) it develops an estimation procedure for the model which is simple, transparent and efficient. The procedure requires no sophisticated Kalman filtering methods and reduces to a standard Gibbs sampling algorithm. iii) as an extension, it develops efficient procedures to estimate endogenously the mean values and autoregressive coefficients associated with each variable-specific autoregressive process. iv) through a case study of the Great Recession for four major economies (Canada, the Euro Area, Japan and the United States), it establishes that forecast accuracy can be significantly improved by using the proposed general time-varying model and its extensions in place of the traditional random walk specification

Identification of mutations at the origin of various phenotypes in donkeys

Publiées depuis le début des années 1990, de nombreuses observations décrivent l'effet de mutations ponctuelles affectant les gènes responsables des différentes couleurs de la robe du cheval. Par contre, à ce jour, aucune étude n’a encore été consacrée à l’espèce asine, bien que celle-ci, en dépit de sa grande proximité phylogénique, présente des phénotypes très différents de ceux du cheval. Notre étude permet d’établir les bases génétiques de deux particularités : la robe à poils longs, caractéristique des Baudets du Poitou, et la décoloration observée autour du museau, des yeux et au niveau des membres et appelée Pangaré. Pour accomplir cette analyse, nous utilisons une approche par gènes candidats basée sur les données de la littérature concernant le cheval et d’autres espèces de mammifères. Par cette approche, nous mettons en évidence deux mutations dans le gène FGF5, toutes les deux responsables du phénotype poils longs, et une mutation dans le gène ASIP, associée au phénotype bouchard ou non pangaré.From 1990s, many results have described punctual mutations in the genes responsible for different colors of dresses of horses, but to day no study had been achieved for the asinine species, which display very different phenotypes although a close phylogenetic neighboring. Our study was designed to try to establish the genetic basis of two features: the long hair dress found in Baudets du Poitou, and the discoloration observed around the muzzle, eyes and limbs and which is called Light Point. We have so adopted an approach by candidate genes from the existing literature in horses and other mammals. By this approach two mutations have been identified in the gene FGF5 responsible for the phenotype long hair and one mutation in the gene ASIP was associated with the phenotype No Light Point

The EGIM, modular though generic addresses the requirements of the EMSO platforms

The EGIM (EMSO Generic Instrument Module ) is designed to consistently and continuously measure parameters of interest for most major science areas covered by EMSO. This research infrastructure provides accurate records on marine environmental changes from distributed regional nodes around Europe. The system can deliver data that can support the Global Ocean Observing System –Essential Ocean Variables concept, as well as the Marine Strategy Framework Directive towards evaluating environmentalstatus. The EGIM is flexible for adaptation according to site and disciplinespecific requirements. Inter - operability and capacity of future evolution of the system are key aspects of the modularity. The EGIM is able to operate on any EMSO node type: mooring line, sea bed station, cabled or non - cabled and surface buoy to monitor environmental parameters over a wide depth range. Operating modes, power requirements, mechanical design can adapt to the various EMSO node configurations. In addition to sensors already included in the EGIM prototype (temperature, conductivity, pressure, dissolved Oxygen, Turbidity, currents and passive acoustics) the EGIMcan host up to five additional sensors such as chl -a, pCO 2, pH, seismic and photographic/video images ornew sensors. The EGIM provides all the sensor hosting services required ,for instance power distribution, positioning , and protection against bio -fouling . Within EMSO , the EGIM aimsto have a number of ocean locations where the same set of core variables are measured homogeneously: using the same hardware, same sensor references, same qualification methods, same calibration methods, same data format and access and the same maintenance procedures. It’s compact and modular nature allows for flexible deploymentscenarios that include being able to accommodate new instruments such for Essential Ocean Variables and other needs as theirtechnology readiness levels improve.Peer ReviewedPostprint (published version

Differential effects of lobe A and lobe B of the conserved oligomeric golgi complex on the stability of β1,4-galactosyltransferase 1 and α2,6-sialyltransferase 1

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)Initially described by Jaeken et al. in 1980, congenital disorders of glycosylation (CDG) is a rapidly expanding group of human multisystemic disorders. To date, many CDG patients have been identified with deficiencies in the conserved oligomeric Golgi (COG) complex which is a complex involved in the vesicular intra-Golgi retrograde trafficking. Composed of eight subunits that are organized in two lobes, COG subunit deficiencies have been associated with Golgi glycosylation abnormalities. Analysis of the total serum N-glycans of COG-deficient CDG patients demonstrated an overall decrease in terminal sialylation and galactosylation. According to the mutated COG subunits, differences in late Golgi glycosylation were observed and led us to address the question of an independent role and requirement for each of the two lobes of the COG complex in the stability and localization of late terminal Golgi glycosylation enzymes. For this, we used a small-interfering RNAs strategy in HeLa cells stably expressing green fluorescent protein (GFP)-tagged β1,4-galactosyltransferase 1 (B4GALT1) and α2,6-sialyltransferase 1 (ST6GAL1), two major Golgi glycosyltransferases involved in late Golgi N-glycosylation. Using fluorescent lectins and flow cytometry analysis, we clearly demonstrated that depletion of both lobes was associated with deficiencies in terminal Golgi N-glycosylation. Lobe A depletion resulted in dramatic changes in the Golgi structure, whereas lobe B depletion severely altered the stability of B4GALT1 and ST6GAL1. Only MG132 was able to rescue their steady-state levels, suggesting that B4GALT1- and ST6GAL1-induced degradation are likely the consequence of an accumulation in the endoplasmic reticulum (ER), followed by a retrotranslocation into the cytosol and proteasomal degradation. All together, our results suggest differential effects of lobe A and lobe B for the localization/stability of B4GALT1 and ST6GAL1. Lobe B would be crucial in preventing these two Golgi glycosyltransferases from inappropriate retrograde trafficking to the ER, whereas lobe A appears to be essential for maintaining the overall Golgi structure

Differential effects of lobe A and lobe B of the Conserved Oligomeric Golgi complex on the stability of β1,4-galactosyltransferase 1 and α2,6-sialyltransferase 1

Initially described by Jaeken et al. in 1980, congenital disorders of glycosylation (CDG) is a rapidly expanding group of human multisystemic disorders. To date, many CDG patients have been identified with deficiencies in the conserved oligomeric Golgi (COG) complex which is a complex involved in the vesicular intra-Golgi retrograde trafficking. Composed of eight subunits that are organized in two lobes, COG subunit deficiencies have been associated with Golgi glycosylation abnormalities. Analysis of the total serum N-glycans of COG-deficient CDG patients demonstrated an overall decrease in terminal sialylation and galactosylation. According to the mutated COG subunits, differences in late Golgi glycosylation were observed and led us to address the question of an independent role and requirement for each of the two lobes of the COG complex in the stability and localization of late terminal Golgi glycosylation enzymes. For this, we used a small-interfering RNAs strategy in HeLa cells stably expressing green fluorescent protein (GFP)-tagged β1,4-galactosyltransferase 1 (B4GALT1) and α2,6-sialyltransferase 1 (ST6GAL1), two major Golgi glycosyltransferases involved in late Golgi N-glycosylation. Using fluorescent lectins and flow cytometry analysis, we clearly demonstrated that depletion of both lobes was associated with deficiencies in terminal Golgi N-glycosylation. Lobe A depletion resulted in dramatic changes in the Golgi structure, whereas lobe B depletion severely altered the stability of B4GALT1 and ST6GAL1. Only MG132 was able to rescue their steady-state levels, suggesting that B4GALT1- and ST6GAL1-induced degradation are likely the consequence of an accumulation in the endoplasmic reticulum (ER), followed by a retrotranslocation into the cytosol and proteasomal degradation. All together, our results suggest differential effects of lobe A and lobe B for the localization/stability of B4GALT1 and ST6GAL1. Lobe B would be crucial in preventing these two Golgi glycosyltransferases from inappropriate retrograde trafficking to the ER, whereas lobe A appears to be essential for maintaining the overall Golgi structur

Genetic evolution of equine influenza virus strains (H3N8) isolated in France from 1967 to 2015 and the implications of several potential pathogenic factors

International audienceEquine influenza virus (EIV) is a major respiratory pathogen of horses despite the availability of equine influenza vaccines. This study aimed to determine genetic evolution of EIV strains in France between 1967 to present. A whole genome comparative analysis was also conducted on recent French strains in order to identify potential factors of pathogenicity. Comparison of French EIV sequences with vaccine and worldwide epidemic strains revealed amino acid substitutions in both haemagglutinin (HA) and neuraminidase, especially within the antigenic sites and/or close to receptor binding sites (HA). Amino acid substitutions were also identified in other genes, mainly the polymerase complex proteins and PB1-F2. Viruses belonging to Eurasian and American lineages have circulated until 2003 and Florida sub-lineage Clade 2 strains predominates since 2005. The last French strain (2015) displayed several specificities in HA suggesting the occurrence of antigenic drift with presence of pathogenic markers in the PA and PB1-F2 genes