US Infl ation and infl ation uncertainty in a historical perspective: The impact of recessions

We use over two hundred years of US inflation data to examine the impact of inflation uncertainty on inflation. An analysis of the full period without allowing for various regimes shows no impact of uncertainty on inflation. However, once we distinguish between recessions and non recessions, we find that inflation uncertainty has a negative effect on inflation only in recession times, thus providing support to the Holland hypothesis.asymmetric GARCH, recession, inflation uncertainty

Inflation, inflation uncertainty, and Markov regime switching heteroskedasticity: Evidence from European countries

We use a Markov regime-switching heteroskedasticity model in order to examine the association between inflation and inflation uncertainty in four European countries over the last forty years. This approach allows for regime shifts in both the mean and variance of inflation in order to assess the association between inflation and its uncertainty in short and long horizons. We find that this association differs (i) between transitory and permanent shocks to inflation and (ii) across countries. In particular, the association is positive or zero for transitory shocks and negative or zero for permanent shocks. Hence, Friedman's belief that inflation is positively associated with inflation uncertainty is only partially supported in this study, i.e., by short-run inflation uncertaintyInflation, Inflation uncertainty, Markov process, regime-switching heteroskedasticity

A GARCH Model of Inflation and Inflation Uncertainty with Simultaneous Feedback

We examine the relationship between inflation and inflation uncertainty using a GARCH model that allows for simultaneous feedback between the conditional mean and variance of inflation. We also derive a number of theoretical econometric results and illustrate the relevance of these results with an empirical example of the US monthly inflation process. Our results show that there is strong evidence in favour of a positive bi-directional relationship between inflation and inflation uncertainty in agreement with the predictions of economic theory.Inflation, Inflation uncertainty, GARCH-M

Oil Volatility and the Option Value of Waiting: An analysis of the G-7

There has recently been considerable interest in the potential adverse effects associated with excessive uncertainty in energy futures markets. Theoretical models of investment under uncertainty predict that increased uncertainty will tend to induce firms to delay investment. These models are widely utilized in capital budgeting decisions, particularly in the energy sector. There is relatively little empirical evidence, however, on whether such channels have industry-wide effects. Using a sample of G7 countries we examine whether uncertainty about a prominent commodity — oil — affects the time series variation in manufacturing activity. Our primary result is consistent with the predictions of real options theory — uncertainty about oil prices has had a negative and significant effect on manufacturing activity in Canada, France, UK and US.Oil, Volatility, Vector autoregression, Multivariate GARCH-in-Mean VAR

Macroeconomic Uncertainty and Performance in Asian Countries

We use a very general bivariate GARCH-M model and quarterly data for five Asian countries to test for the impact of real and nominal macroeconomic uncertainty on in°ation and output growth. We conclude the following. First, in the majority of countries uncertainty regarding the output growth rate is related negatively to the average growth rate. Second, contrary to expectations, infation uncertainty in most cases does not harm the output growth perfor- mance of an economy. Third, in°ation and output uncertainty have a mixed effect on inflation. Consistent results are found using the VAR-GARCH-M approach to investigate the dynamic relationship between in°ation and output growth using impulse response functions. This evidence implies that macroeconomic uncertainty may even improve macroeconomic performance, i.e., raise output growth and reduce inflation. Our empirical results highlight important differences with those for industrialized countries.Inflation, Output growth, Uncertainty, GARCH models

Theoretical study and experimental implementation of an ion-nanowire hybrid system

Numerous efforts are currently aiming at the implementation of hybrid quantum systems in the quest for developing new devices for quantum technologies. The motivation for a solid state-atomic interface emerges from the possibility to couple otherwise incompatible platforms in order to combine the advantages of both in a complementary fashion. Under this scope, we report in this thesis the implementation of a new quantum device for the interface of an ultracold trapped ion and a conductive nanowire. The experimental measurements obtained here seem promising for the realization of the hybrid dynamics of the ion-nanowire hybrid system. Additionally, we performed numerical calculations in order to characterize the perturbation of the trapping potential for the ion by the nanowire. From our classical and quantum dynamics calculations we explored possibilities of generating Gaussian and non-Gaussian quantum states of the ion from the nanowire drive. Our modelling indicated, also, that sympathetic cooling and quantum entanglement can be realized when both subsystems operate in the quantum regime. The present ion-nanowire hybrid system might prove promising as a new quantum device for quantum information and quantum sensing experiments, for spectroscopy and for mass spectrometry

Action selection in the rhythmic brain: The role of the basal ganglia and tremor.

Low-frequency oscillatory activity has been the target of extensive research both in cortical structures and in the basal ganglia (BG), due to numerous reports of associations with brain disorders and the normal functioning of the brain. Additionally, a plethora of evidence and theoretical work indicates that the BG might be the locus where conflicts between prospective actions are being resolved. Whereas a number of computational models of the BG investigate these phenomena, these models tend to focus on intrinsic oscillatory mechanisms, neglecting evidence that points to the cortex as the origin of this oscillatory behaviour. In this thesis, we construct a detailed neural model of the complete BG circuit based on fine-tuned spiking neurons, with both electrical and chemical synapses as well as short-term plasticity between structures. To do so, we build a complete suite of computational tools for the design, optimization and simulation of spiking neural networks. Our model successfully reproduces firing and oscillatory behaviour found in both the healthy and Parkinsonian BG, and it was used to make a number of biologically-plausible predictions. First, we investigate the influence of various cortical frequency bands on the intrinsic effective connectivity of the BG, as well as the role of the latter in regulating cortical behaviour. We found that, indeed, effective connectivity changes dramatically for different cortical frequency bands and phase offsets, which are able to modulate (or even block) information flow in the three major BG pathways. Our results indicate the existence of a multimodal gating mechanism at the level of the BG that can be entirely controlled by cortical oscillations, and provide evidence for the hypothesis of cortically-entrained but locally-generated subthalamic beta activity. Next, we explore the relationship of wave properties of entrained cortical inputs, dopamine and the transient effectiveness of the BG, when viewed as an action selection device. We found that cortical frequency, phase, dopamine and the examined time scale, all have a very important impact on the ability of our model to select. Our simulations resulted in a canonical profile of selectivity, which we termed selectivity portraits. Taking together, our results suggest that the cortex is the structure that determines whether action selection will be performed and what strategy will be utilized while the role of the BG is to perform this selection. Some frequency ranges promote the exploitation of actions of whom the outcome is known, others promote the exploration of new actions with high uncertainty while the remaining frequencies simply deactivate selection. Based on this behaviour, we propose a metaphor according to which, the basal ganglia can be viewed as the ''gearbox" of the cortex. Coalitions of rhythmic cortical areas are able to switch between a repertoire of available BG modes which, in turn, change the course of information flow back to and within the cortex. In the same context, dopamine can be likened to the ''control pedals" of action selection that either stop or initiate a decision. Finally, the frequency of active cortical areas that project to the BG acts as a gear lever, that instead of controlling the type and direction of thrust that the throttle provides to an automobile, it dictates the extent to which dopamine can trigger a decision, as well as what type of decision this will be. Finally, we identify a selection cycle with a period of around 200 ms, which was used to assess the biological plausibility of the most popular architectures in cognitive science. Using extensions of the BG model, we further propose novel mechanisms that provide explanations for (1) the two distinctive dynamical behaviours of neurons in globus pallidus external, and (2) the generation of resting tremor in Parkinson's disease. Our findings agree well with experimental observations, suggest new insights into the pathophysiology of specific BG disorders, provide new justifications for oscillatory phenomena related to decision making and reaffirm the role of the BG as the selection centre of the brain.Open Acces

The role of cortical oscillations in a spiking neural network model of the basal ganglia.

Although brain oscillations involving the basal ganglia (BG) have been the target of extensive research, the main focus lies disproportionally on oscillations generated within the BG circuit rather than other sources, such as cortical areas. We remedy this here by investigating the influence of various cortical frequency bands on the intrinsic effective connectivity of the BG, as well as the role of the latter in regulating cortical behaviour. To do this, we construct a detailed neural model of the complete BG circuit based on fine-tuned spiking neurons, with both electrical and chemical synapses as well as short-term plasticity between structures. As a measure of effective connectivity, we estimate information transfer between nuclei by means of transfer entropy. Our model successfully reproduces firing and oscillatory behaviour found in both the healthy and Parkinsonian BG. We found that, indeed, effective connectivity changes dramatically for different cortical frequency bands and phase offsets, which are able to modulate (or even block) information flow in the three major BG pathways. In particular, alpha (8-12Hz) and beta (13-30Hz) oscillations activate the direct BG pathway, and favour the modulation of the indirect and hyper-direct pathways via the subthalamic nucleus-globus pallidus loop. In contrast, gamma (30-90Hz) frequencies block the information flow from the cortex completely through activation of the indirect pathway. Finally, below alpha, all pathways decay gradually and the system gives rise to spontaneous activity generated in the globus pallidus. Our results indicate the existence of a multimodal gating mechanism at the level of the BG that can be entirely controlled by cortical oscillations, and provide evidence for the hypothesis of cortically-entrained but locally-generated subthalamic beta activity. These two findings suggest new insights into the pathophysiology of specific BG disorders