In Search for a Credit Crunch in Germany

The purpose of this paper is to investigate whether a credit crunch occurred in Germany during the recent financial crisis and to analyze the underlying factors. In order to disentangle credit supply and demand we specify a theory-based dynamic disequilibrium model of the German credit market. To estimate this model we use a new approach based on Bayesian Inference suggested by Bauwens and Lubrano (2007). Besides the analysis of the whole banking sector we will apply the model to five groups of banks (big private banks, Landesbanken, savings banks, credit cooperatives, regional institutions of credit cooperatives) that were affected differently by the financial crisis. The results suggest that a credit crunch did not occur in Germany during the recent economic crisis as well as during the following recovery starting in 2010. Furthermore, we find that especially those banks that were more affected by the financial crisis through huge impairments restricted their credit supply more than others. Both supply and demand side factors contributed to the stabilization of credit financing. This suggests that the structure of the German banking sector as well as economic policy measures avoided a credit crunch

Correlated long-range mixed-harmonic fluctuations measured in pp, p+Pb and low-multiplicity Pb+Pb collisions with the ATLAS detector

For abstract see published article

Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC

The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at √s=13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb −1 for the tt ¯ and γ+jet and 36.7 fb −1 −1 for the dijet event topologies

In situ calibration of large-radius jet energy and mass in 13 TeV proton–proton collisions with the ATLAS detector

The response of the ATLAS detector to largeradius jets is measured in situ using 36.2 fb−1 of √s = 13 TeV proton–proton collisions provided by the LHC and recorded by the ATLAS experiment during 2015 and 2016. The jet energy scale is measured in events where the jet recoils against a reference object, which can be either a calibrated photon, a reconstructed Z boson, or a system of well-measured small-radius jets. The jet energy resolution and a calibration of forward jets are derived using dijet balance measurements. The jet mass response is measured with two methods: using mass peaks formed by W bosons and top quarks with large transverse momenta and by comparing the jet mass measured using the energy deposited in the calorimeter with that using the momenta of charged-particle tracks. The transversemomentum and mass responses in simulations are found to be about 2–3% higher than in data. This difference is adjusted for with a correction factor. The results of the different methods are combined to yield a calibration over a large range of transverse momenta (pT). The precision of the relative jet energy scale is 1–2% for 200 GeV < pT < 2 TeV, while that of the mass scale is 2–10%. The ratio of the energy resolutions in data and simulation is measured to a precision of 10–15% over the same pT range

Measurement of the photon identification efficiencies with the ATLAS detector using LHC Run 2 data collected in 2015 and 2016

The efficiency of the photon identification criteria in the ATLAS detector is measured using 36.1 fb1 to 36.7 fb1 of pp collision data at s√=13 TeV collected in 2015 and 2016. The efficiencies are measured separately for converted and unconverted isolated photons, in four different pseudorapidity regions, for transverse momenta between 10 GeV and 1.5 TeV. The results from the combination of three data-driven techniques are compared with the predictions from simulation after correcting the variables describing the shape of electromagnetic showers in simulation for the average differences observed relative to data. Data-to-simulation efficiency ratios are determined to account for the small residual efficiency differences. These factors are measured with uncertainties between 0.5% and 5% depending on the photon transverse momentum and pseudorapidity. The impact of the isolation criteria on the photon identification efficiency, and that of additional soft pp interactions, are also discussed. The probability of reconstructing an electron as a photon candidate is measured in data, and compared with the predictions from simulation. The efficiency of the reconstruction of photon conversions is measured using a sample of photon candidates from Z→μμγ events, exploiting the properties of the ratio of the energies deposited in the first and second longitudinal layers of the ATLAS electromagnetic calorimeter