A look into the factor model black box: publication lags and the role of hard and soft data in forecasting GDP

We derive forecast weights and uncertainty measures for assessing the role of individual series in a dynamic factor model (DFM) to forecast euro area GDP from monthly indicators. The use of the Kalman filter allows us to deal with publication lags when calculating the above measures. We find that surveys and financial data contain important information beyond the monthly real activity measures for the GDP forecasts. However, this is discovered only, if their more timely publication is properly taken into account. Differences in publication lags play a very important role and should be considered in forecast evaluation. JEL Classification: E37, C53Dynamic Factor Models, filter weights, forecasting

Hierarchical shrinkage in time-varying parameter models

In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time-varying parameter models. Our approach allows for the coefficient on each predictor to be: i) time varying, ii) constant over time or iii) shrunk to zero. The econometric methodology decides automatically which category each coefficient belongs in. Our empirical results indicate the benefits of such an approach

Large Time-Varying Parameter VARs

In this paper, we develop methods for estimation and forecasting in large time-varying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints, we draw on ideas from the dynamic model averaging literature which achieve reductions in the computational burden through the use forgetting factors. We then extend the TVP-VAR so that its dimension can change over time. For instance, we can have a large TVP-VAR as the forecasting model at some points in time, but a smaller TVP-VAR at others. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output and interest rates demonstrates the feasibility and usefulness of our approach

Egg-size variation in algerian populations of the Blue Tit (Parus caeruleus ultramarinus) : effects of altitude and habitat

Egg-size, as a component of life history, is expected to be traded-off with other components and, consequently, to display a pattern of variation between different habitats and altitudes. Relevant data being very scarcely available for just a few bird species caused us to study interhabitat and interaltitude variation in egg dimensions and mass in the Blue Tit Parus caeruleus ultramarinus, taking the advantage of the occurrence of this species in a variety of habitats and at different altitudes in North Africa (north-eastern Algeria). In 1991-1993 we selected 6 study sites representing two types of habitat (rich deciduous forests dominated by A lnus glutinosa and Quercus faginea vs poor evergreen forests of Quercus suber) at three elevations (30m asl, 500m als and 900-1000m asl). We analysed both multiple response variables characterizing egg dimensions and individual egg traits. Eggs tumed out to differ between altitudes (the lowest elevation against the two higher ones) but did not differ between habitats. They also display relatively high within-clutch repeatabilities, 0.6 on average for ali traits. Egg traits were not significantly correlated with clutch-size within study stations, but the analysis of a bivariate response variable composed of egg volume and clutch-size suggested that these components of life history were negatively linked. Moreover, this bivariate response variable differed both between habitats and altitudesLa taille de l'oeuf est un caractère que l'on s'attend à être lié à d'autres traits d'histoire de la vie de sorte qu'il devrait montrer des variations en fonction de l'habitat et de l'altitude. Fort peu de données probantes étant disponibles et pour un nombre limité d'espèces, nous avons conduit en 1991-93 une étude de la variation interhabitat et altitudinale des dimensions et du poids des œufs de la Mésange bleue Parus caeruleus ultramarinus, profitant de ce que cette espèce se montre dans toute une gamme d'habitats et d'altitudes en Afrique du Nord, notamment dans le nord-est de l'Algérie. Six stations d'étude ont été sélectionnées, représentant deux types d'habitat (les riches forêts caducifoliées dominées par Alnus glutinosa et Quercus faginea opposées aux forêts sempervirentes pauvres de Quercus suber) et trois altitudes (30 m, 500 m et 900-1 000 m). Nous avons analysé à la fois les variables à réponse multiple qui caractérisent les dimensions des œufs et les traits individuels de ces oeufs. Les œufs sont apparus différer selon l'altitude (opposition entre le plus bas niveau et les suivants) mais pas selon l'habitat, Ils montrent aussi un relativement fort degré de répétabilité intraponte, de 0,6 en moyenne pour tous les caractères. Ceux-ci n'étaient pas significativement liés à la taille de la ponte dans un même site mais l'analyse d'une variable bivariée intégrant le volume de l'oeuf et la taille de la ponte a suggéré que ces deux traits seraient négativement corrélés. De plus, cette variable bivariée différait à la fois d'un habitat et d'une altitude à l'autre

Equid herpesvirus type 1 (EHV-1) disrupt actin cytoskeleton during productive infection in equine leukocytes

Equid herpesvirus type 1 (EHV-1) is a prevalent causative agent of equine diseases worldwide. After primary replication in the respiratory epithelium the virus disseminates systemically through a peripheral blood mononuclear cell (PBMC)-associated viraemia. EHV-1 is the only alphaherpes-virus known so far which is capable of establishing latent infection not only in neurons but also in immune system cells (mainly in lymphocytes and macrophages). Since leukocytes are not the target cells for viral replication but are used to transport EHV-1 to the internal organs, the question remains how the virus avoids the immune response and whether it could potentially be associated with virus-induced cytoskeletal rearrangements. Therefore, the aim of this study was to investigate the progress of EHV-1 replication in leukocytes stimulated by phytohemagglutinin and the impact of EHV-1 infection on the actin cytoskeleton. Using the real-time PCR method we evaluated the quantity of viral DNA from samples collected at indicated time points post infection. In order to examine possible changes in actin cytoskeleton organization due to EHV-1 infection, we performed immunofluorescent staining using TRITC-phalloidin conjugate. The results showed that EHV-1 replicates in leukocytes at a restricted level but with the accompaniment of chromatin degradation. Simultaneously, infection with EHV-1 caused disruption of the actin cytoskeleton; this was particularly apparent in further stages of infection. Disruption of the actin cytoskeleton may lead to the limited release of the virus from the cells, but may be also beneficial for the virus, since at the same time it potentially impairs the immune function of leukocytes

Prior selection for panel vector autoregressions

Bayesian shrinkage priors have been very popular in estimating vector autoregressions (VARs) of possibly large dimensions. Many of these priors are not appropriate for multi-country settings, as they cannot account for the type of restrictions typically met in panel vector autoregressions (PVARs). With this in mind, new parametric and semi-parametric priors for PVARs are proposed, which perform valuable shrinkage in large dimensions and also allow for soft clustering of variables or countries which are homogeneous. The implication of these new priors for modelling interdependencies and heterogeneities among different countries in a panel VAR setting, is discussed. Monte Carlo evidence and an empirical forecasting exercise show clear and important gains from the new priors compared to existing popular priors for VARs and PVARs

Model uncertainty in panel vector autoregressive models

We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsimonious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group

Have Standard VARs Remained Stable Since the Crisis?

Small vector autoregressions are commonly used in macroeconomics for forecasting and evaluating shock trans-mission. This requires VAR parameters to be stable over the evaluation and forecast sample or modeled as time-varying. Prior work has considered whether there were sizable parameter changes in the early 1980s and in the subsequent period until the beginning of the new century. This paper conducts a similar analysis focused on the period since the recent crisis. Using a range of techniques, we provide substantial evidence against parame-ter stability. The evolution of the unemployment rate seems particularly different relative to its past behavior. We also evaluate alternative methods to handle parameter instability in a forecasting contex

Signals from the government : policy disagreement and the transmission of fiscal shocks

We investigate the effects of fiscal policy communication on the propagation of government spending shocks. To this aim, we propose a new index measuring the coordination effects of policy communication on private agents׳ expectations. This index is based on the disagreement amongst US professional forecasters about future government spending. The underlying intuition is that a clear fiscal policy communication can coalesce expectations, reducing disagreement. Results indicate that, in times of low disagreement, the output response to fiscal spending innovations is positive and large, mainly due to private investment response. Conversely, periods of elevated disagreement are characterised by muted output response