Seasonality in revisions of macroeconomic data

We analyze five vintages of eighteen quarterly macroeconomic variables for the Netherlands and we focus on the degree of deterministic seasonality in these series. We document that the data show most such deterministic seasonality for their first release vintage and for the last available vintage. In between vintages show a variety of seasonal patterns. We show that seasonal patterns in later vintages can hardly be predicted by those in earlier vintages. The consequences of these findings for the interpretation and modeling of macroeconomic data are discussed.seasonality;real-time data

Inference on the tail process with application to financial time series modelling

To draw inference on serial extremal dependence within heavy-tailed Markov chains, Drees, Segers and Warcho{\l} [Extremes (2015) 18, 369--402] proposed nonparametric estimators of the spectral tail process. The methodology can be extended to the more general setting of a stationary, regularly varying time series. The large-sample distribution of the estimators is derived via empirical process theory for cluster functionals. The finite-sample performance of these estimators is evaluated via Monte Carlo simulations. Moreover, two different bootstrap schemes are employed which yield confidence intervals for the pre-asymptotic spectral tail process: the stationary bootstrap and the multiplier block bootstrap. The estimators are applied to stock price data to study the persistence of positive and negative shocks.Comment: 22 page

Improving Upon the Marginal Empirical Distribution Functions when the Copula is Known

At the heart of the copula methodology in statistics is the idea of separating marginal distributions from the dependence structure. However, as shown in this paper, this separation is not to be taken for granted: in the model where the copula is known and the marginal distributions are completely unknown, the empirical distribution functions are semiparametrically efficient if and only if the copula is the independence copula. Incorporating the knowledge of the copula into a nonparametric likelihood yields an estimation procedure which by simulations is shown to outperform the empirical distribution functions, the amount of improvement depending on the copula. Although the known-copula model is arguably artificial, it provides an instructive stepping stone to the more general model of a parametrically specified copula and arbitrary margins.independence copula;nonparametric maximum likelihood estimator;score function;semiparametric efficiency;tangent space

Bayesian near-boundary analysis in basic macroeconomic time series models

Several lessons learnt from a Bayesian analysis of basic macroeconomic time series models are presented for the situation where some model parameters have substantial posterior probability near the boundary of the parameter region. This feature refers to near-instability within dynamic models, to forecasting with near-random walk models and to clustering of several economic series in a small number of groups within a data panel. Two canonical models are used: a linear regression model with autocorrelation and a simple variance components model. Several well-known time series models likeunit root and error correction models and further state space and panel data models are shown to be simple generalizations of these two canonical models for the purpose of posterior inference. A Bayesian model averaging procedure is presented in order to deal with models with substantial probability both near and at the boundary of the parameter region. Analytical, graphical and empirical results using U.S. macroeconomic data, in particular on GDP growth, are presented.MCMC;Bayesian model averaging;Gibbs sampler;autocorrelation;error correction models;nonstationarity;random effects panel data models;reduced rank models;state space models

Observation of a parity oscillation in the conductance of atomic wires

Using a scanning tunnel microscope or mechanically controlled break junctions, atomic contacts of Au, Pt and Ir are pulled to form chains of atoms. We have recorded traces of conductance during the pulling process and averaged these for a large amount of contacts. An oscillatory evolution of conductance is observed during the formation of the monoatomic chain suggesting a dependence on even or odd numbers of atoms forming the chain. This behaviour is not only present in the monovalent metal Au, as it has been previously predicted, but is also found in the other metals which form chains suggesting it to be a universal feature of atomic wires

Formation of a Metallic Contact: Jump to Contact Revisited

The transition from tunneling to metallic contact between two surfaces does not always involve a jump, but can be smooth. We have observed that the configuration and material composition of the electrodes before contact largely determines the presence or absence of a jump. Moreover, when jumps are found preferential values of conductance have been identified. Through combination of experiments, molecular dynamics, and first-principles transport calculations these conductance values are identified with atomic contacts of either monomers, dimers or double-bond contacts.Comment: 4 pages, 5 figure

A Narratology-Based Framework for Storyline Extraction

Stories are a pervasive phenomenon of human life. They also represent a cognitive tool to understand and make sense of the world and of its happenings. In this contribution we describe a narratology-based framework for modeling stories as a combination of different data structures and to automatically extract them from news articles. We introduce a distinction among three data structures (timelines, causelines, and storylines) that capture different narratological dimensions, respectively chronological ordering, causal connections, and plot structure. We developed the Circumstantial Event Ontology (CEO) for modeling (implicit) circumstantial relations as well as explicit causal relations and create two benchmark corpora: ECB+/CEO, for causelines, and the Event Storyline Corpus (ESC), for storylines. To test our framework and the difficulty in automatically extract causelines and storylines, we develop a series of reasonable baseline system

Seasonality in revisions of macroeconomic data

We analyze five vintages of eighteen quarterly macroeconomic variables for the Netherlands and we focus on the degree of deterministic seasonality in these series. We document that the data show most such deterministic seasonality for their first release vintage and for the last available vintage. In between vintages show a variety of seasonal patterns. We show that seasonal patterns in later vintages can hardly be predicted by those in earlier vintages. The conseque