The industrial equilibrium exchange rate in Brazil: an estimation

This paper presents a methodology for calculating the industrial equilibrium exchange rate, which is defined as the one enabling exporters of state-of-the-art manufactured goods to be competitive abroad. The first section highlights the causes and problems of overvalued exchange rates, particularly the Dutch disease issue, which is neutralized when the exchange rate strikes the industrial equilibrium level. This level is defined by the ratio between the unit labor cost in the country under consideration and in competing countries. Finally, the evolution of this exchange rate in the Brazilian economy is estimated.

Overvaluation trend of the Brazilian currency in the 2000s: empirical estimation

The aim of this paper is to discuss the trend of overvaluation of the Brazilian currency in the 2000s, presenting an econometric model to estimate the real exchange rate (RER) and which should be a reference level of the RER to guide long-term economic policy. In the econometric model, we consider long-term structural and short-term components, both of which may be responsible for explaining overvaluation trend of the Brazilian currency. Our econometric exercise confirms that the Brazilian currency had been persistently overvalued throughout almost all of the period under analysis, and we suggest that the long-term reference level of the real exchange rate was reached in 2004. In July 2014, the average nominal exchange rate should have been around 2.90 Brazilian reais per dollar (against an observed nominal rate of 2.22 Brazilian reais per dollar) to achieve the 2004 real reference level (average of the year). That is, according to our estimates, in July 2014 the Brazilian real was overvalued at 30.6 per cent in real terms relative to the reference level. Based on these findings we conclude the paper suggesting a mix of policy instruments that should have been used in order to reverse the overvaluation trend of the Brazilian real exchange rate, including a target for reaching a real exchange rate in the medium and the long-run which would favor resource allocation toward more technological intensive sectors.

Parameter estimation for Chaotic or Stochastic Dynamics

Since its discovery, chaos has been a very interesting and challenging topic of research. Many great minds spent their entire lives trying to give some rules to it. Nowadays, thanks to the research of last century and the advent of computers, it is possible to predict chaotic phenomena of nature for a certain limited amount of time. The aim of this study is to present a recently discovered method for the parameter estimation of the chaotic dynamical system models via the correlation integral likelihood, and give some hints for a more optimized use of it, together with a possible application to the industry. The main part of our study concerned two chaotic attractors whose general behaviour is diff erent, in order to capture eventual di fferences in the results. In the various simulations that we performed, the initial conditions have been changed in a quite exhaustive way. The results obtained show that, under certain conditions, this method works very well in all the case. In particular, it came out that the most important aspect is to be very careful while creating the training set and the empirical likelihood, since a lack of information in this part of the procedure leads to low quality results.

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Original.

Variational Monte Carlo estimation of the dissociation energy of CuH using correlated sampling

A new approach to treating large Z systems by quantum Monte Carlo has been developed. It naturally leads to notion of the 'valence energy'. Possibilities of the new approach has been explored by optimizing the wave function for CuH and Cu and computing dissociation energy and dipole moment of CuH using variational Monte Carlo. The dissociation energy obtained is about 40% smaller than the experimental value; the method is comparable with SCF and simple pseudopotential calculations. The dipole moment differs from the best theoretical estimate by about 50% what is again comparable with other methods (Complete Active Space SCF and pseudopotential methods).

Exact property estimation from diffusion Monte Carlo with minimal stochastic reconfiguration /

Our objective is to develop a diffusion Monte Carlo (DMC) algorithm to estimate the exact expectation values, ($o|^|^o), of multiplicative operators, such as polarizabilities and high-order hyperpolarizabilities, for isolated atoms and molecules. The existing forward-walking pure diffusion Monte Carlo (FW-PDMC) algorithm which attempts this has a serious bias. On the other hand, the DMC algorithm with minimal stochastic reconfiguration provides unbiased estimates of the energies, but the expectation values ($o|^|^) are contaminated by ^, an user specified, approximate wave function, when A does not commute with the Hamiltonian. We modified the latter algorithm to obtain the exact expectation values for these operators, while at the same time eliminating the bias. To compare the efficiency of FW-PDMC and the modified DMC algorithms we calculated simple properties of the H atom, such as various functions of coordinates and polarizabilities. Using three non-exact wave functions, one of moderate quality and the others very crude, in each case the results are within statistical error of the exact values.

"Re-huminization": the role of human-animal similarity in predicting prejudice towards immigrants and non-human animals

Research implies that there ~ay be an association between attitudes toward margil1alized human outgroups and non-human animals. Very few studies, however, have specifically tested this relation empirically. The general purpose of the present research was to determine if such a relation exists and if perceptions of human-animal similarity avail as a common predictor of both types of attitudes. Ideological orientations associated with prejudiced attitudes (Social Dominance Orientation, Right-Wing Authoritarianism, and Universal Orientation) were also examined as individual differences in predicting perceptions of human-animal similarity. As predicted, people who endorsed prejudiced attitudes toward human outgroups (Study 1) and immigrants in particular (Studies 2 and 3), were more likely to endorse prejudiced attitudes toward non-human animals. In Study 2, perceptions that humans are superior (versus similar) to other animals directly predicted higher levels of prejudice toward non-human animals, whereas the effect of human superiority beliefs on immigrant prejudice was mediated by dehumanization. In other words, greater perceptions of humans as superior (versus similar) to other animals "allowed for" greater dehumanization of immigrants, which in turn resulted in heightened immigrant prejudice. Furthermore, people higher in Social Dominance Orientation or Right-Wing Authoritarianism were particularly likely to perceive humans as superior (versus similar) to other animals, whereas people characterized by a greater Universal Orientation were more likely to perceive humans and non-human animals as similar. Study 3 examined whether inducing perceptions of human-animal similarity through experimental manipulation would lead to more favourable attitudes toward non-human animals and immigrants. Participants were randomly assigned to read one of four 11 editorials designed to highlight either the similarities or differences between humans and other animals (i.e., animals are similar to humans; humans are similar to animals;~~nimals are inferior to humans; humans are superior to animals) or to a neutral control condition. Encouragingly, when animals were described as similar to humans, prejudice towards non-human animals and immigrants was significantly lower, and to some extent this finding was also true for people naturally high in prejudice (i.e., high in Social Dominance Orientation or Right-Wing Authoritarianism). Inducing perceptions that nonhuman animals are similar to humans was particularly effective at reducing the tendency to dehumanize immigrants ("re-humanization"), lowering feelings of personal threat regarding one's animal-nature, and at increasing inclusive intergroup representations and empathy, all of which uniquely accounted for the significant decreases in prejudiced attitudes. Implications for research, theory and prejudice interventions are considered.

Electrophysiological constituents of the P100 and N170 ERP complex: De-constructing of face processing using independent component analysis and robust estimation.

The initial timing of face-specific effects in event-related potentials (ERPs) is a point of contention in face processing research. Although effects during the time of the N170 are robust in the literature, inconsistent effects during the time of the P100 challenge the interpretation of the N170 as being the initial face-specific ERP effect. The interpretation of the early P100 effects are often attributed to low-level differences between face stimuli and a host of other image categories. Research using sophisticated controls for low-level stimulus characteristics (Rousselet, Husk, Bennett, & Sekuler, 2008) report robust face effects starting at around 130 ms following stimulus onset. The present study examines the independent components (ICs) of the P100 and N170 complex in the context of a minimally controlled low-level stimulus set and a clear P100 effect for faces versus houses at the scalp. Results indicate that four ICs account for the ERPs to faces and houses in the first 200ms following stimulus onset. The IC that accounts for the majority of the scalp N170 (icNla) begins dissociating stimulus conditions at approximately 130 ms, closely replicating the scalp results of Rousselet et al. (2008). The scalp effects at the time of the P100 are accounted for by two constituent ICs (icP1a and icP1b). The IC that projects the greatest voltage at the scalp during the P100 (icP1a) shows a face-minus-house effect over the period of the P100 that is less robust than the N 170 effect of icN 1 a when measured as the average of single subject differential activation robustness. The second constituent process of the P100 (icP1b), although projecting a smaller voltage to the scalp than icP1a, shows a more robust effect for the face-minus-house contrast starting prior to 100 ms following stimulus onset. Further, the effect expressed by icP1 b takes the form of a larger negative projection to medial occipital sites for houses over faces partially canceling the larger projection of icP1a, thereby enhancing the face positivity at this time. These findings have three main implications for ERP research on face processing: First, the ICs that constitute the face-minus-house P100 effect are independent from the ICs that constitute the N170 effect. This suggests that the P100 effect and the N170 effect are anatomically independent. Second, the timing of the N170 effect can be recovered from scalp ERPs that have spatio-temporally overlapping effects possibly associated with low-level stimulus characteristics. This unmixing of the EEG signals may reduce the need for highly constrained stimulus sets, a characteristic that is not always desirable for a topic that is highly coupled to ecological validity. Third, by unmixing the constituent processes of the EEG signals new analysis strategies are made available. In particular the exploration of the relationship between cortical processes over the period of the P100 and N170 ERP complex (and beyond) may provide previously unaccessible answers to questions such as: Is the face effect a special relationship between low-level and high-level processes along the visual stream?

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

A domain-general perspective on medial frontal brain activity during performance monitoring

Activity of the medial frontal cortex (MFC) has been implicated in attention regulation and performance monitoring. The MFC is thought to generate several event-related potential (ERPs) components, known as medial frontal negativities (MFNs), that are elicited when a behavioural response becomes difficult to control (e.g., following an error or shifting from a frequently executed response). The functional significance of MFNs has traditionally been interpreted in the context of the paradigm used to elicit a specific response, such as errors. In a series of studies, we consider the functional similarity of multiple MFC brain responses by designing novel performance monitoring tasks and exploiting advanced methods for electroencephalography (EEG) signal processing and robust estimation statistics for hypothesis testing. In study 1, we designed a response cueing task and used Independent Component Analysis (ICA) to show that the latent factors describing a MFN to stimuli that cued the potential need to inhibit a response on upcoming trials also accounted for medial frontal brain responses that occurred when individuals made a mistake or inhibited an incorrect response. It was also found that increases in theta occurred to each of these task events, and that the effects were evident at the group level and in single cases. In study 2, we replicated our method of classifying MFC activity to cues in our response task and showed again, using additional tasks, that error commission, response inhibition, and, to a lesser extent, the processing of performance feedback all elicited similar changes across MFNs and theta power. In the final study, we converted our response cueing paradigm into a saccade cueing task in order to examine the oscillatory dynamics of response preparation. We found that, compared to easy pro-saccades, successfully preparing a difficult anti-saccadic response was characterized by an increase in MFC theta and the suppression of posterior alpha power prior to executing the eye movement. These findings align with a large body of literature on performance monitoring and ERPs, and indicate that MFNs, along with their signature in theta power, reflects the general process of controlling attention and adapting behaviour without the need to induce error commission, the inhibition of responses, or the presentation of negative feedback.

Comparaison des performances relatives de différents modèles d'estimation de la valeur à risque.

Rapport de recherche

Educational Attainment of Second-Generation Immigrants in Belgium: an Estimation of the Assimilation Degree of Immigrants Based on Cross Section Analysis.

Rapport de recherche

Genre, santé et développement: les inégalités entre les hommes et les femmes dans la santé constituent-elles un frein au développement? Estimation empirique en coupe transversale dans un modèle Mankiw – Romer – Weil.

Rapport de recherche