Modelling global trade flows: results from a GVAR model

This paper uses a Global Vector Auto-Regression (GVAR)model in a panel of 21 emerging market and advanced economies to investigate the factors behind the dynamics of global trade flows, with a particular view on the issue of global trade imbalances and on the conditions of their unwinding. The GVAR approach enables us to make two key contributions: first, to model international linkages among a large number of countries, which is a key asset given the diversity of countries and regions involved in global imbalances, and second, to model exports and imports jointly. The latter proves to be very important due to the inter-nationalisation of production and the high import content of exports. The model can be used to gauge the effect on trade flows of various scenarios, such as an output shock in the United States, a shock to the US real effective exchange rate and shocks to foreign (German and Chinese) variables. Results indicate in particular that world exports respond much more to a (normalised) shock to US output than to a real effective depreciation of the dollar. In addition, the model can be used to monitor trade developments, such as the sharp contraction in world trade that took place in the wake of the financial crisis. While the fall in imports seems well accounted for by the model, the fall in exports of several countries remains partly unexplained, suggesting perhaps that specific factors might have been at play during the crisis. JEL Classification: F10, F17, F32, C33Exchange Rates, global imbalances, Global VAR, international trade, trade elasticities

The Predictive Information Content of External Imbalances for Exchange Rate Returns: How Much Is It Worth?

This paper examines the exchange rate predictability stemming from the equilibrium model of international financial adjustment developed by Gourinchas and Rey (2007). Using predictive variables that measure cyclical external imbalances for country pairs, we assess the ability of this model to forecast out-of-sample four major US dollar exchange rates using various economic criteria of model evaluation. The analysis shows that the model provides economic value to a risk-averse investor, delivering substantial utility gains when switching from a portfolio strategy based on the random walk benchmark to one that conditions on cyclical external imbalances.foreign exchange; predictability; global imbalances; fundamentals.

Episodic memory retrieval, parietal cortex, and the default mode network: Functional and topographic analyses

The default mode network (DMN) is often considered a functionally homogeneous system that is broadly associated with internally directed cognition (e.g., episodic memory, theory of mind, self-evaluation). However, few studies have examined how this network interacts with other networks during putative default processes such as episodic memory retrieval. Using functional magnetic resonance imaging, we investigated the topography and response profile of human parietal regions inside and outside the DMN, independently defined using task-evoked deactivations and resting-state functional connectivity, during episodic memory retrieval. Memory retrieval activated posterior nodes of the DMN, particularly the angular gyrus, but also more anterior and dorsal parietal regions that were anatomically separate from the DMN. The two sets of parietal regions showed different resting-state functional connectivity and response profiles. During memory retrieval, responses in DMN regions peaked sooner than non-DMN regions, which in turn showed responses that were sustained until a final memory judgment was reached. Moreover, a parahippocampal region that showed strong resting-state connectivity with parietal DMN regions also exhibited a pattern of task-evoked activity similar to that exhibited by DMN regions. These results suggest that DMN parietal regions directly supported memory retrieval, whereas non-DMN parietal regions were more involved in postretrieval processes such as memory-based decision making. Finally, a robust functional dissociation within the DMN was observed. Whereas angular gyrus and posterior cingulate/precuneus were significantly activated during memory retrieval, an anterior DMN node in medial prefrontal cortex was strongly deactivated. This latter finding demonstrates functional heterogeneity rather than homogeneity within the DMN during episodic memory retrieval

Energy density equations and power flow in structures

A potential alternative to Statistical Energy Analysis that is gaining increasing interest in recent years is the “thermal” energy flow approach. Its advantage is represented by the possibility of modelling the spatial distribution of energy density at high frequencies, thus yielding a more effective estimate of the system behaviour than the average constant value given by SEA. However, the thermal analogy proposed by the energy flow approach is questionable for any type of wave in any type of structure. To make the analysis more clear, exact equations for power balance in continuous structures are derived. The investigation confirms the questionability of the thermal approach and shows whether and when it is possible to determine exact equations for the energy density. Physical considerations are developed to explain some critical points. For one-dimensional systems a transmission potential is defined in analogy to the temperature in heat conduction problems

A unified approach to substructuring and structural modification problems

Substructures coupling is still an important tool in several applications of modal analysis, especially structural modification and structures assembling. The subject is particularly relevant in virtual prototyping of complex systems and responds to actual industrial needs. This paper analyzes the possibility of assembling together different substructures' models. The important role of rotational DoFs is highlighted, underlying the difficulty of assembling theoretical and experimental models, for which, usually, the rotational DoFs are not available. Expansion techniques can be used to provide this information as well as appropriate modelling of joints. With this information FRF models, modal models and FE models can be appropriately combined together and solutions for several cases of practical interest are presented. The analyzed procedures are tested on purpose-built benchmarks, showing limits and capabilities of each of them

An envelope energy model for high frequency dynamic structures

High frequency structural and acoustic problems require prohibitive computational efforts. The tendency, nowadays, is to find a solution in statistical terms (SEA) through an average of the field variables on the space domain. A limitation of SEA is the loss of any local information. In contrast with SEA, a power flow method [1] can describe a trend of the energy density along the structure, thus improving the quality of the solution. However, in dealing with flexural waves, the power flow neglects the near field contribution: the related solution can sometimes differ considerably from the expected trend. In this paper a held trend is obtained in a totally different manner. An envelope energy is used that describes well the exact solution: specifically, only the decaying fields, obtained from the projection on the real axis of the damped bending wavenumbers are accounted for, while the propagating components are omitted. Simulated results are presented and compared with exact and approximate solution

Estimating Trade Elasticities: Demand Composition and the Trade Collapse of 2008-09

This paper introduces a new methodology for the estimation of demand trade elasticities based on an import intensity-adjusted measure of aggregate demand, with the foundation of a stylized theoretical model. We compute the import intensity of demand components by using the OECD Input-Output tables. We argue that the composition of demand plays a key role in trade dynamics because of the large movements in the most import-intensive categories of expenditure (especially investment, but also exports). We provide evidence in favor of these mechanisms for a panel of 18 OECD countries, paying particular attention to the 2008-09 Great Trade Collapse.

The relationship between perseverative thinking, proactive control, and inhibition in psychological distress: a study in a women's cohort.

Cognitive control is a core feature of several mental disorders. A recent account poses that health problems may derive from proactive forms of cognitive control that maintain stress representation over time. The working hypothesis of the present study is that psychological distress is caused by the tendency to select a particular maladaptive self-regulation strategy over time, namely perseverative thinking, rather than by transient stimulus-response patterns. To test this hypothesis, we asked 84 women to carry out a battery of standardized questionnaires regarding their tendency to undertake perseverative thinking and their level of psychological distress, followed by cognitive tasks measuring the tendency to use proactive versus reactive control modality and disinhibition. Through a series of mediation analyses, we demonstrate that the tendency to use proactive control correlates with psychological distress and that this relation is mediated by perseverative thinking. Moreover, we show that the relation between low inhibitory control and psychological stress is more strongly mediated by perseverative thinking than impulsiveness, a classical construct that focuses on more transient reactions to stimuli. The present results underline the importance of considering psychological distress as the consequence of a maladaptive way of applying control over time, rather than the result of a general deficit in cognitive control abilities. [Abstract copyright: © 2023. The Author(s).

Energy flow uncertainties in vibrating systems: definition of a statistical confidence factor

A method for evaluating the energy flow confidence level in vibrating systems with randomly perturbed parameters is presented. The energy flow is predicted in terms of the mobilities of resonant subsystems or by the solution of the velocity wave field for non-resonant subsystems. The statistical moments of the energy flow are calculated by a perturbation technique and a confidence factor is defined as the ratio between mean and standard deviation. The properties of the confidence factor are investigated by a theoretical analysis as a function of frequency. Three cases are studied to compare the confidence factor obtained theoretically with a prediction provided by a Monte-Carlo simulation

Attention to memory and the environment: functional specialization and dynamic competition in human posterior parietal cortex

none3siPosterior parietal cortex has been traditionally associated with perceptual attention and sensory-motor processing, but recent studies also indicate a potential role in episodic memory retrieval. Here, we developed a new paradigm to isolate top-down attention-related activity directed to either memory or perceptual information. We demonstrated a robust topographic separation in human posterior parietal cortex associated with searching for task-relevant information in episodic memory or in the environment. Control analyses confirmed that this difference was not dependent on differences in sensory stimulation or eye movements across tasks. Notably, we observed in memory-and perception-related regions a mechanism of reciprocal dynamic competition that was related to behavioral performance. These results provide the first evidence for a double dissociation between parietal networks involved in top-down attention to memory and the environment and support the idea of neural competition between perception and memory.openSestieri, Carlo; Shulman, Gordon L.; Corbetta, MaurizioSestieri, Carlo; Shulman, Gordon L.; Corbetta, Maurizi