Internal rationality, learning and imperfect information

We construct, estimate and explore the monetary policy consequences of a New Keynesian (NK) behavioural model with bounded-rationality and heterogeneous agents. We radically depart from most existing models of this genre in our treatment of bounded rationality and learning. Instead of the usual Euler learning approach, we assume that agents are internally rational (IR) given their beliefs of aggregate states and prices. The model is inhabited by fully rational (RE) and IR agents where the latter use simple heuristic rules to forecast aggregate variables exogenous to their micro-environment. We find that IR results in an NK model with more persistence and a smaller policy space for rule parameters that induce stability and determinacy. In the most general form of the model, agents learn from their forecasting errors by observing and comparing them with those under RE making the composition of the two types endogenous. In a Bayesian estimation with fixed proportions of RE and IR agents and a general heuristic forecasting rule we find that a pure IR model fits the data better than the pure RE case. However, the latter with imperfect rather than the standard perfect information assumption outperforms IR (easily) and RE-IR composites (slightly), but second moment comparisons suggest that the RE-IR composite can match data better. Our findings suggest that Kalman-filtering learning with RE can match bounded-rationality in matching persistence seen in the data

Designing Robust Monetary Policy Using Prediction Pools

How should a forward-looking policy maker conduct monetary policy when she has a finite set of models at her disposal, none of which are believed to be the true data generating process? In our approach, the policy makerfirst assigns weights to models based on relative forecasting performance rather than in-sample fit, consistent with her forward-looking objective. These weights are then used to solve a policy design prob- lem that selects the optimized Taylor-type interest-rate rule that is robust to model uncertainty across a set of well-established DSGE models with and without financial frictions. We find that the choice of weights has a significant impact on the robust optimized rule which is more inertial and aggressive than either the non-robust single model counterparts or the optimal robust rule based on backward-looking weights as in the common alternative Bayesian Model Averaging. Importantly, we show that a price-level rule has excellent welfare and robustness properties, and therefore should be viewed as a key instrument for policy makers facing uncertainty over the nature of financial frictions

The CCFM Monte Carlo generator CASCADE 2.2.0

CASCADE is a full hadron level Monte Carlo event generator for ep, \gamma p and p\bar{p} and pp processes, which uses the CCFM evolution equation for the initial state cascade in a backward evolution approach supplemented with off - shell matrix elements for the hard scattering. A detailed program description is given, with emphasis on parameters the user wants to change and variables which completely specify the generated events

Early Primary Percutaneous Coronary Intervention in Patients with ST-segment Elevation Acute Myocardial Infarction from the Cluj Area

Background: The seriousness of acute myocardial infarction (AMI) and the importance of its early detection and intervention are well known. Rapid reperfusion of the infarct area positively influences the immediate and long-term prognosis of patients with ST-segment elevation AMI. Material and method: Patients with acute myocardial infarction who underwent primary percutaneous transluminal coronary angioplasty (during the first 12 hours after the onset of chest pain) in the cardiac catheterization laboratory of the Cluj-Napoca “Nicolae Stancioiu” Heart Institute between November 2008 and February 2010 were followed prospectively in order to measure time-to-treatment intervals. Results: Our sample of 321 AMI patients included mostly males (73.8% of cases, 95% CI: 68.6-78.5; p<0.001) and patients from the urban area (67.6% of cases, 95% CI: 62.1-72.6; p<0.001) aged between 50 and 79 years. Total ischemia time (from onset of precordial pain to primary angioplasty) was 338.9 minutes on average (between 100 and 720 minutes); ambulance waiting time was 22.1 minutes (3-150 minutes); transport to first hospital took 49.9 minutes (5-276 minutes) while transport to a cardiology hospital averaged 247 minutes from the onset of pain (maximum 660 minutes). The door-to-balloon time was 91.9 minutes while early intervention was possible in 27.4% (95% CI: 22.7-32.7%) of AMI cases. Conclusions: Time-to-treatment intervals allowed early reperfusion in only one third of AMI patients due to lack of access to specialised cardiology hospitals in rural areas and inconsistencies regarding the attitude towards AMI cases across counties

Multi-gluon helicity amplitudes with one off-shell leg within high energy factorization

Basing on the Slavnov-Taylor identities, we derive a new prescription to obtain gauge invariant tree-level scattering amplitudes for the process g*g->Ng within high energy factorization. Using the helicity method, we check the formalism up to several final state gluons, and we present analytical formulas for the the helicity amplitudes for N=2. We also compare the method with Lipatov's effective action approach.Comment: 25 pages, quite a few figures, an appendix added, typos correcte

A Three Dimensional Analysis of Au-Silica Core-Shell Nanoparticles Using Medium Energy Ion Scattering

The medium energy ion scattering (MEIS) facility at the IIAA Huddersfield has been used for the analysis of a monolayer of Au-silica core-shell nanoparticles deposited on Si substrate. Both spherical and rod shape particles were investigated and the spectra produced by 100 keV He+ ions scattered through angles of 90º and 125º were compared with the results of RBS-MAST [1] simulations performed on artificial 3D model cells containing the nanoparticles. The thickness of the silica shell, the diameter of the Au spheres, and the diameter and length of the Au nano-rods were determined from best fits of the measured set of MEIS spectra. In addition, the effect of ion irradiation on the silica shell and gold core was monitored by MEIS measurements in conjunction with RBS-MAST simulations. Ion bombardment was performed under largely different conditions, i.e., by 30 keV Ar+, 150 keV Fe+, or 2.8 MeV N+ ions in the dose range of 2×1015 - 2×1016 cm-2. Significant changes in the particle geometry can be observed due to ion beam-induced sputtering and recoil effects, the significance of which was estimated from full-cascade SRIM simulations. Rutherford backscattering spectrometry (RBS), Field emission scanning electron microscopy (FESEM), and Atomic Force Microscopy (AFM) techniques have been applied as complementary characterization tools to monitor the amount of gold and surface morphology on the un-irradiated and irradiated sample areas. We show that MEIS can yield spatial information on the geometrical changes of particulate systems at the nanometre scale