Nowcasting inflation using high frequency data

This paper proposes a methodology to nowcast and forecast inflation using data with sampling frequency higher than monthly. The nowcasting literature has been focused on GDP, typically using monthly indicators in order to produce an accurate estimate for the current and next quarter. This paper exploits data with weekly and daily frequency in order to produce more accurate estimates of inflation for the current and followings months. In particular, this paper uses the Weekly Oil Bulletin Price Statistics for the euro area, the Weekly Retail Gasoline and Diesel Prices for the US and daily World Market Prices of Raw Materials. The data are modeled as a trading day frequency factor model with missing observations in a state space representation. For the estimation we adopt the methodology exposed in Banbura and Modugno (2010). In contrast to other existing approaches, the methodology used in this paper has the advantage of modeling all data within a unified single framework that, nevertheless, allows one to produce forecasts of all variables involved. This offers the advantage of disentangling a model-based measure of ”news” from each data release and subsequently to assess its impact on the forecast revision. The paper provides an illustrative example of this procedure. Overall, the results show that these data improve forecast accuracy over models that exploit data available only at monthly frequency for both countries. JEL Classification: C53, E31, E37Factor models, forecasting, inflation, Mixed Frequencies

The wild bootstrap for multilevel models

In this paper we study the performance of the most popular bootstrap schemes for multilevel data. Also, we propose a modified version of the wild bootstrap procedure for hierarchical data structures. The wild bootstrap does not require homoscedasticity or assumptions on the distribution of the error processes. Hence, it is a valuable tool for robust inference in a multilevel framework. We assess the finite size performances of the schemes through a Monte Carlo study. The results show that for big sample sizes it always pays off to adopt an agnostic approach as the wild bootstrap outperforms other techniques

Expansion of a Fermi gas interacting with a Bose-Einstein condensate

We study the expansion of an atomic Fermi gas interacting attractively with a Bose-Einstein condensate. We find that the interspecies interaction affects dramatically both the expansion of the Fermi gas and the spatial distribution of the cloud in trap. We observe indeed a slower evolution of the radial-to-axial aspect ratio which reveals the importance of the mutual attraction between the two samples during the first phase of the expansion. For large atom numbers, we also observe a bimodal momentum distribution of the Fermi gas, which reflects directly the distribution of the mixture in trap. This effect allows us to extract information on the dynamics of the system at the collapse.Comment: 4 pages, 4 figure

Dynamical instability and dispersion management of an attractive condensate in an optical lattice

We investigate the stability of an attractive Bose-Einstein condensate in a moving 1D optical lattice in the presence of transverse confinement. By means of a Bogoliubov linear stability analysis we find that the system is dynamically unstable for low quasimomenta and becomes stable near the band edge, in a specular fashion with respect to the repulsive case. For low interactions the instability occurs via long wavelength excitations that are not sufficient for spoiling the condensate coherence, producing instead an oscillating density pattern both in real and momentum space. This behaviour is illustrated by simulations for the expansion of the condensate in a moving lattice.Comment: 5 pages, 4 figure

39-K Bose-Einstein condensate with tunable interactions

We produce a Bose-Einstein condensate of 39-K atoms. Condensation of this species with naturally small and negative scattering length is achieved by a combination of sympathetic cooling with 87-Rb and direct evaporation, exploiting the magnetic tuning of both inter- and intra-species interactions at Feshbach resonances. We explore tunability of the self-interactions by studying the expansion and the stability of the condensate. We find that a 39-K condensate is interesting for future experiments requiring a weakly interacting Bose gas.Comment: 5 page

Multilevel Models with Stochastic Volatility for Repeated Cross-Sections: an Application to tribal Art Prices

In this paper we introduce a multilevel specification with stochastic volatility for repeated cross-sectional data. Modelling the time dynamics in repeated cross sections requires a suitable adaptation of the multilevel framework where the individuals/items are modelled at the first level whereas the time component appears at the second level. We perform maximum likelihood estimation by means of a nonlinear state space approach combined with Gauss-Legendre quadrature methods to approximate the likelihood function. We apply the model to the first database of tribal art items sold in the most important auction houses worldwide. The model allows to account properly for the heteroscedastic and autocorrelated volatility observed and has superior forecasting performance. Also, it provides valuable information on market trends and on predictability of prices that can be used by art markets stakeholders