From the Lucasian revolution to DSGE models: An account of recent developments in macroeconomic modelling

PHD THESIS SUMMARY.From the Lucasian revolution to DSGE models: an accountof recent developments in macroeconomic modellin

DSGE models and the Lucas Critique. A historical appraisal

This contribution to the history of the economic thought aims at describing how “Econometric Policy Evaluation: A Critique” (Lucas, 1976) has been interpreted through four decades of debates. This historical appraisal clarifies how Lucas’s argument is currently understood and discussed within the dynamic stochastic general equilibrium (DSGE) approach. The article illustrates how two opposite interpretations of the Lucas Critique arose in the early 1980s. On the one hand, a theoretical interpretation” has been championed by the real business cycle (RBC) approach; on the other hand, an “empirical interpretation” has been advocated by Keynesians. Both interpretations can be understood as addressing a common question: Do microfoundations imply parameters’ stability? Following the RBC theoretical interpretation, microfoundations do imply stability; conversely, for Keynesians, parameters’ stability (or instability) should be supported by econometric evidence rather than theoretical considerations. Furthermore, the article argues that the DSGE approach represent a fragile compromise between these two opposite interpretations of Lucas (1976). This is especially true for the recent literature criticizing the DSGE models for being vulnerable to the Lucas Critique

Random graph model with power-law distributed triangle subgraphs

Clustering is well-known to play a prominent role in the description and understanding of complex networks, and a large spectrum of tools and ideas have been introduced to this end. In particular, it has been recognized that the abundance of small subgraphs is important. Here, we study the arrangement of triangles in a model for scale-free random graphs and determine the asymptotic behavior of the clustering coefficient, the average number of triangles, as well as the number of triangles attached to the vertex of maximum degree. We prove that triangles are power-law distributed among vertices and characterized by both vertex and edge coagulation when the degree exponent satisfies $2<\beta<2.5$; furthermore, a finite density of triangles appears as $\beta=2+1/3$.Comment: 4 pages, 2 figure; v2: major conceptual change

Investigation on edge joints of Inconel 625 sheets processed with laser welding

Abstract Laser welding of Inconel 625 edge joint beads in square groove configuration was investigated. The use of different weld geometries in new aerospace solutions explains research on edge joints. A structured plan was carried out in order to characterize the process defining the influence of laser power and welding speed and to study possible interactions among the governing factors. As weld pool protection is crucial in order to obtain sound joints when processing superalloys, a special glove box for gas supply was designed to upgrade the welding head. Welded joints were characterized referring to bead profile, microstructure and X-rays. It was found that heat input plays an important role as it affects welding stability, porosity content and bead shape. Results suggest operating with low values of heat input to reduce porosity and guarantee stable bead conformation. Furthermore, a decrease in the grain size has been observed as a consequence of decreasing heat input

Harmful effects of mechanical ventilation on neurocognitive functions

Whether mechanical ventilation (MV) induces neurotoxicity that can trigger or accelerate chronic cognitive disorders is controversial [1, 2]. The relationship between MV and neurocognitive impairment—that persisted at hospital discharge and at 1-year follow up—was first reported in 1999 in MV-treated ARDS patients [3]. Since then, several preclinical and clinical studies have investigated the mechanisms, localization, and timing of brain damage induced by MVand possible preventive/therapeutic strategies

Statistical Mechanics of Quantum-Classical Systems with Holonomic Constraints

The statistical mechanics of quantum-classical systems with holonomic constraints is formulated rigorously by unifying the classical Dirac bracket and the quantum-classical bracket in matrix form. The resulting Dirac quantum-classical theory, which conserves the holonomic constraints exactly, is then used to formulate time evolution and statistical mechanics. The correct momentum-jump approximation for constrained system arises naturally from this formalism. Finally, in analogy with what was found in the classical case, it is shown that the rigorous linear response function of constrained quantum-classical systems contains non-trivial additional terms which are absent in the response of unconstrained systems.Comment: Submitted to Journal of Chemical Physic

Exploring EEG for Object Detection and Retrieval

This paper explores the potential for using Brain Computer Interfaces (BCI) as a relevance feedback mechanism in content-based image retrieval. We investigate if it is possible to capture useful EEG signals to detect if relevant objects are present in a dataset of realistic and complex images. We perform several experiments using a rapid serial visual presentation (RSVP) of images at different rates (5Hz and 10Hz) on 8 users with different degrees of familiarization with BCI and the dataset. We then use the feedback from the BCI and mouse-based interfaces to retrieve localized objects in a subset of TRECVid images. We show that it is indeed possible to detect such objects in complex images and, also, that users with previous knowledge on the dataset or experience with the RSVP outperform others. When the users have limited time to annotate the images (100 seconds in our experiments) both interfaces are comparable in performance. Comparing our best users in a retrieval task, we found that EEG-based relevance feedback outperforms mouse-based feedback. The realistic and complex image dataset differentiates our work from previous studies on EEG for image retrieval.Comment: This preprint is the full version of a short paper accepted in the ACM International Conference on Multimedia Retrieval (ICMR) 2015 (Shanghai, China

3D Printing of Low-Filled Basalt PA12 and PP Filaments for Automotive Components

Fused Deposition Modeling (FDM) enables many advantages compared to traditional manufacturing techniques, but the lower mechanical performance due to the higher porosity still hinders its industrial spread in key sectors like the automotive industry. PP and PA12 filaments filled with low amounts of basalt fibers were produced in the present work to improve the poor mechanical properties inherited from the additive manufacturing technique. For both matrices, the introduction of 5 wt.% of basalt fibers allows us to achieve stiffness values comparable to injection molding ones without modifying the final weight of the manufactured components. The increased filament density compared with the neat polymers, upon the introduction of basalt fibers, is counterbalanced by the intrinsic porosity of the manufacturing technique. In particular, the final components are characterized by a 0.88 g/cm3 density for PP and 1.01 g/cm3 for PA12 basalt-filled composites, which are comparable to the 0.91 g/cm3 and 1.01 g/cm3, respectively, of the related neat matrix used in injection molding. Some efforts are still needed to fill the gap of 15–28% for PP and of 26.5% for PA12 in tensile strength compared to injection-molded counterparts, but the improvement of the fiber/matrix interface by fiber surface modification or coupling agent employment could be a feasible solution

Do stock markets love misery? Evidence from the COVID-19

This study examines the impact of the change in the Barro Misery Index (BMI) and the novel coronavirus (COVID-19) cases and deaths on the stock markets’ returns and volatility. Based on a sample of 76 different countries, we find that an increase in BMI adversely affects the stock returns and increases stock volatility. We also find that an increase in BMI coupled with an in crease in percentage cases of COVID-19 adversely affect stock returns and increases volatility. We find that the impacts of BMI on stock returns and volatility are driven by real GDP changes, unemployment rate, and long-term interest rate instead of inflation rates, especially for the developed countries. Our findings are consistent with Barro (1999), which indicates that the BMI represents a better measure relative to the original misery index in predicting the economic outcome, especially during the COVID-19 pandemic. We also find that the impacts of BMI components on stock returns and volatility for the developed countries are different from the emerging markets