Global Versus Local Shocks in Micro Price Dynamics

A number of recent papers point to the importance of distinguishing between the price reaction to micro and macro shocks in order to reconcile the volatility of individual prices with the observed persistence of aggregate inflation. We emphasize instead the importance of distinguishing between global and local shocks. We exploit a panel of 276 micro price levels collected on a semi-annual frequency from 1990 to 2010 across 88 cities in 59 countries around the world, that enables us to distinguish between different types (local and global) of micro and macro shocks. The persistence associated with each of these components and its relation with volatility of the different components, provides a number of new facts. Prices respond more slowly to global shocks as compared to local ones .in particular, prices respond faster to local macro shocks than to global micro ones .implying that the relatively slow response of prices to macro shocks documented in recent studies comes from global rather than local sources. In addition, more volatility in local conditions leads to more persistent relative price distortions due to slower response of prices to global shocks, with this local -global link more than twice as large as the corresponding micro-macro link. Finally, global shocks account for half of the volatility in prices. Overall, our results imply that global shocks are important when analyzing price dynamics or assessing price-setting models.global shocks, local shocks, micro shocks, macro shocks, price adjustment, micro-macro gap, price-setting models, micro prices

Trends in International Prices

We exploit the panel dimension of a price levels dataset for more than one hundred product items across 140 cities in 90 countries for the period from 1990 to 2009 in order to improve our understanding of international price dispersion and the evolution of prices over time. We consider a panel data model with exchangeable units that allows for the possibility of common components for different dimensions of the panel. This allows one to gauge the contribution of each dimension of the data to total variation and to disentangle the sources of potential non-stationarity. It also allows us to identify differences in the speed of convergence for different time-varying components in response to location-specific, product-specific, and idiosyncratic shocks. Finally, we proceed to identify the economic determinants of different components to show that particular dimensions of the data are more suited for examining particular theories.Price levels, Variance decomposition, Convergence, Non-stationarity, International price dispersion

Secular Dynamics of S-type Planetary Orbits in Binary Star Systems: Applicability Domains of First- and Second-Order Theories

We analyse the secular dynamics of planets on S-type coplanar orbits in tight binary systems, based on first- and second-order analytical models, and compare their predictions with full N-body simulations. The perturbation parameter adopted for the development of these models depends on the masses of the stars and on the semimajor axis ratio between the planet and the binary. We show that each model has both advantages and limitations. While the first-order analytical model is algebraically simple and easy to implement, it is only applicable in regions of the parameter space where the perturbations are sufficiently small. The second-order model, although more complex, has a larger range of validity and must be taken into account for dynamical studies of some real exoplanetary systems such as $\gamma$-Cephei and HD 41004A. However, in some extreme cases, neither of these analytical models yields quantitatively correct results, requiring either higher-order theories or direct numerical simulations. Finally, we determine the limits of applicability of each analytical model in the parameter space of the system, giving an important visual aid to decode which secular theory should be adopted for any given planetary system in a close binary.Comment: 32 pages, 8 figures, accepted for publication in Celestial Mechanics and Dynamical Astrophysic

Radiolysis of Amino Acids by Heavy and Energetic Cosmic Ray Analogs in Simulated Space Environments: α\alpha-Glycine Zwitterion Form

In this work, we studied the stability of the glycine molecule in the crystalline zwitterion form, known as {\alpha}-glycine ($^{+}$NH$_{3}$CH$_{2}$COO$^{-}$) under action of heavy cosmic ray analogs. The experiments were conducted in a high vacuum chamber at heavy ions accelerator GANIL, in Caen, France. The samples were bombarded at two temperatures (14 K and 300 K) by $^{58}$Ni$^{11+}$ ions of 46 MeV until the final fluence of $10^{13}$ ions cm$^{-2}$. The chemical evolution of the sample was evaluated in-situ using Fourrier Transformed Infrared (FTIR) spectrometer. The bombardment at 14 K produced several daughter species such as OCN$^-$, CO, CO$_2$, and CN$^-$. The results also suggest the appearing of peptide bonds during irradiation but this must be confirmed by further experiments. The halflives of glycine in Interstellar Medium were estimated to be 7.8 $\times 10^3$ years (300 K) and 2.8 $\times 10^3$ years (14 K). In the Solar System the values were 8.4 $\times 10^2$ years (300 K) and 3.6 $\times 10^3$ years (14 K). It is believed that glycine could be present in space environments that suffered aqueous changes such as the interior of comets, meteorites and planetesimals. This molecule is present in proteins of all alive beings. So, studying its stability in these environments provides further understanding about the role of this specie in the prebiotic chemistry on Earth.Comment: 28 pages, 12 figures, 9 tables. Accepted to be published at Monthly Notices of the Royal Astronomical Society (MNRAS

First results from SAM-FP: Fabry-Perot observations with ground-layer adaptive optics - the structure and kinematics of the core of 30 Doradus

The aim of this paper is to present the first data set obtained with SOAR Adaptive Module-Fabry-Parot (SAM-FP), a Fabry-Perot instrument mounted inside the SOAR telescope Adaptive-Optics Module. This is the only existing imaging Fabry-Perot interferometer using laser-assisted ground-layer adaptive optics. SAM-FP was used to observe the ionized gas, traced by Halpha, in the centre of the 30 Doradus starburst (the Tarantula Nebula) in the Large Magellanic Cloud, with high spatial (~0.6" or 0.15 pc) and spectral (R=11200) resolution. Radial velocity, velocity dispersion and monochromatic maps were derived. The region displays a mix of narrow, sigma ~ 20 km/s profiles and multiple broader profiles with sigma ~ 70-80 km/s, indicating the complex nature of the nebula kinematics. A comparison with previously obtained VLT/FLAMES spectroscopy demonstrates that the data agree well in the regions of overlap, but the Fabry-Perot data are superior in spatial coverage. A preliminary analysis of the observations finds a new expanding bubble south of R136, with a projected radius of r=5.6 pc and an expansion velocity of 29 +/- 4 km/s. In addition, the first-time detailed kinematic maps derived here for several complexes and filaments of 30 Doradus allow identification of kinematically independent structures. These data exemplify the power of the combination of a high-order Fabry-Perot with a wide-field imager (3' x 3' GLAO-corrected field of view) for high-resolution spatial and spectral studies. In particular, SAM-FP data cubes are highly advantageous over multifibre or long-slit data sets for nebula structure studies and to search for small-scale bubbles, given their greatly improved spatial coverage. For reference, this paper also presents two appendices with detailed descriptions of the usage of Fabry-Perot devices, including formulae and explanations for understanding Fabry-Perot observations.Comment: 22 pages, 9 figures, 1 tabl

Priorização de variáveis explicativas na modelagem de acidentes de trânsito utilizando técnicas de aprendizado de máquina

A priorização de variáveis no processo de modelagem de acidentes pode contribuir para otimização de recursos e indicação de quais dados são prioritários para coleta. Assim, este estudo objetivou investigar a influência da priorização de variáveis no ajuste de modelos de previsão de acidentes de resposta multivariada (número de acidentes sem vítimas, número de acidentes com vítimas e número de acidentes com mortes). Duas abordagens foram empregadas: técnicas de agrupamento de árvores de decisão (Random Forest e Boosted Trees) para a priorização inicial e posterior modelagem com uso de redes neurais artificiais (RNA); e, utilização direta de RNA para priorização e modelagem. Os resultados gerais, entretanto, indicaram piora no ajuste dos modelos quando da redução do número de variáveis explicativas. Apesar disso, acredita-se que a evolução de técnicas de aprendizado de máquina de dados que lidem melhor com resposta multivariada, conduzam à identificação adequada das variáveis mais importantes para modelagem.The prioritization of variables in the process of accident modeling can contribute to the optimization of resource and indication of which data are priority to collect. This study aimed to investigate the influence of the prioritization of variables in the adjustment of accident predictive models of multivariate response (number of accidents without victims, number of accidents with victims and number of accidents with deaths). Two approaches were used: decision tree grouping techniques (Random Forest and Boosted Trees) for initial prioritization and later modeling using artificial neural networks (ANN); and, direct use of ANN for both, prioritization and modeling. Overall results, however, indicated a worse fitness of the models when the number of explanatory variables was reduced. Despite this, it is believed that the evolution of machine learning techniques that best deal with multivariate response, lead to the adequate identification of the most important variables for modeling

Noisy information and fundamental disagreement

We study the term structure of disagreement of professional forecasters for key macroeconomic variables. We document a novel set of facts: 1) forecasters disagree at all horizons, including the very long run; 2) the shape of the term structure of disagreement differs markedly across variables: the term structure is downward-sloping for real output growth, relatively flat for CPI inflation, and upward-sloping for the federal funds rate; 3) disagreement is time varying at all horizons, including the very long run. We suggest a model with noisy information and shifting long-run beliefs that is consistent with these stylized facts. Notably, our model does not rely on the heterogeneity of prior beliefs, bounded rationality, or differences in the precision of signals across agents

The optimal inflation target and the natural rate of interest

We study how changes in the steady-state real interest rate affect the optimal inflation target in a New Keynesian DSGE model with trend inflation and a lower bound on the nominal interest rate. In this setup, a lower steady-state real interest rate increases the probability of hitting the lower bound. That effect can be counteracted by an increase in the inflation target, but the resulting higher steadystate inflation has a welfare cost in and of itself. We use an estimated DSGE model to quantify that trade-off and determine the implied optimal inflation target, conditional on the monetary policy rule in place before the financial crisis. The relation between the steady-state real interest rate and the optimal inflation target is downward sloping. While the increase in the optimal inflation rate is in general smaller than the decline in the steady-state real interest rate, in the currently empirically relevant region the slope of the relation is found to be close to −1. That slope is robust to allowing for parameter uncertainty. Under “make-up” strategies such as price level targeting, the required increase in the optimal inflation target under lower steady-state real interest rate is, however, much smaller