Can Sectoral Shifts Generate Persistent Unemployment in Real Business Cycle Models?

This paper extends the standard Real Business Cycle model to incorporate sectoral shifts in unemployment. Using relative sectoral technology and sectoral tastes shocks, combined with labor adjustment costs across sectors, we assess the possibility of generating persistent aggregate unemployment. Calibrated to Canadian data, the models suggest that the introduction of sectoral labor mobility with adjustment costs improves the ability of the standard real business cycle model to match the observed persistence in unemployment. Empirically, we estimated a Vector Auto-Regressive model and successfully matched the models' overshooting of labor. The results suggest that government policies aimed to alleviate the unemployment burden should pay closer attention to sectoral phenomena, specifically to sectoral labor mobility.Real Business Cycle (RBC), Sectoral Shocks, Unemployment Persistence, Vector Auto-Regressive (VAR), Blanchard-Quah (B-Q) Identification

Testing and Estimating Persistence in Canadian Unemployment.

A vital implication of unemployment persistence applies to the Bank of Canada's disinflation policies since it adversely influences unemployment and considerably lengthens recessions. This paper tests for persistence in Canadian sectoral unemployment, using the modified rescaled-range test. Our results show evidence of persistence in sectoral unemployment that translates to persistence in aggregate unemployment. To quantify this aggregate-level persistence, we estimate it within the framework of Bayesian ARFIMA class of models. The results conclude that Canadian unemployment exhibits persistence in the short and intermediate run.ARFIMA, Fractional Integrated, Bayesian, Unemployment Persistence, Canada, Rescaled-Range Statistic

On the Evidence of Non-Linear Structure in Canadian Unemployment.

In this paper, we focus on and examine the empirical evidence of non- linearity in aggregate Canadian unemployment. Contrary to the conclusion reached in Murray et al. (1993), and using a corrected for bias simple non-parametric test (SNT), we reject the null hypothesis of a linear structure for Canadian unemployment.Canada, Unemployment, Brock Dechert and Scheinkman (BDS) test, Simple Non-Paramteric Test (SNT), U-Statistics, Correlation Integral, Non-Linear Specification.

Bethe-Salpeter Equation Calculations of Core Excitation Spectra

We present a hybrid approach for GW/Bethe-Salpeter Equation (BSE) calculations of core excitation spectra, including x-ray absorption (XAS), electron energy loss spectra (EELS), and non-resonant inelastic x-ray scattering (NRIXS). The method is based on {\it ab initio} wavefunctions from the plane-wave pseudopotential code ABINIT; atomic core-level states and projector augmented wave (PAW) transition matrix elements; the NIST core-level BSE solver; and a many-pole GW self-energy model to account for final-state broadening and self-energy shifts. Multiplet effects are also accounted for. The approach is implemented using an interface dubbed OCEAN (Obtaining Core Excitations using ABINIT and NBSE). To demonstrate the utility of the code we present results for the K-edges in LiF as probed by XAS and NRIXS, the K-edges of KCl as probed by XAS, the Ti L_2,3-edge in SrTiO_3 as probed by XAS, and the Mg L_2,3-edge in MgO as probed by XAS. We compare the results to experiments and results obtained using other theoretical approaches

SemanticFusion: Dense 3D Semantic Mapping with Convolutional Neural Networks

Ever more robust, accurate and detailed mapping using visual sensing has proven to be an enabling factor for mobile robots across a wide variety of applications. For the next level of robot intelligence and intuitive user interaction, maps need extend beyond geometry and appearence - they need to contain semantics. We address this challenge by combining Convolutional Neural Networks (CNNs) and a state of the art dense Simultaneous Localisation and Mapping (SLAM) system, ElasticFusion, which provides long-term dense correspondence between frames of indoor RGB-D video even during loopy scanning trajectories. These correspondences allow the CNN's semantic predictions from multiple view points to be probabilistically fused into a map. This not only produces a useful semantic 3D map, but we also show on the NYUv2 dataset that fusing multiple predictions leads to an improvement even in the 2D semantic labelling over baseline single frame predictions. We also show that for a smaller reconstruction dataset with larger variation in prediction viewpoint, the improvement over single frame segmentation increases. Our system is efficient enough to allow real-time interactive use at frame-rates of approximately 25Hz

Discovery of High-Latitude CO in a HI Supershell in NGC 5775

We report the discovery of very high latitude molecular gas in the edge-on spiral galaxy, NGC 5775. Emission from both the J=1-0 and 2-1 lines of 12CO is detected up to 4.8 kpc away from the mid-plane of the galaxy. NGC 5775 is known to host a number of HI supershells. The association of the molecular gas M(H2,F2) = 3.1x10^7 solar masses reported here with one of the HI supershells (labeled F2) is clear, which suggests that molecular gas may have survived the process which originally formed the supershell. Alternatively, part of the gas could have been formed in situ at high latitude from shock-compression of pre-existing HI gas. The CO J=2-1/J=1-0 line ratio of 0.34+-40% is significantly lower than unity, which suggests that the gas is excited subthermally, with gas density a few times 100 cubic cm. The molecular gas is likely in the form of cloudlets which are confined by magnetic and cosmic rays pressure. The potential energy of the gas at high latitude is found to be 2x10^56 ergs and the total (HI + H2) kinetic energy is 9x10^53 ergs. Based on the energetics of the supershell, we suggest that most of the energy in the supershell is in the form of potential energy and that the supershell is on the verge of falling and returning the gas to the disk of the galaxy.Comment: Accept by ApJL, 4 pages, 3 ps figure