Data Revisions in the Estimation of DSGE Models

Revisions of US macroeconomic data are not white-noise. They are persistent, correlated with real-time data, and with high variability (around 80% of volatility observed in US real-time data). Their business cycle effects are examined in an estimated DSGE model extended with both real-time and final data. After implementing a Bayesian estimation approach, the role of both habit formation and price indexation fall significantly in the extended model. The results show how revision shocks of both output and inflation are expansionary because they occur when real-time published data are too low and the Fed reacts by cutting interest rates. Consumption revisions, by contrast, are countercyclical as consumption habits mirror the observed reduction in real-time consumption. In turn, revisions of the three variables explain 9.3% of changes of output in its long-run variance decomposition.

Efficient learning of decomposable models with a bounded clique size

The learning of probability distributions from data is a ubiquitous problem in the fields of Statistics and Artificial Intelligence. During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models due to their advantageous theoretical properties. Some of these algorithms can be used to search for a maximum likelihood decomposable model with a given maximum clique size, k, which controls the complexity of the model. Unfortunately, the problem of learning a maximum likelihood decomposable model given a maximum clique size is NP-hard for k > 2. In this work, we propose a family of algorithms which approximates this problem with a computational complexity of O(k · n^2 log n) in the worst case, where n is the number of implied random variables. The structures of the decomposable models that solve the maximum likelihood problem are called maximal k-order decomposable graphs. Our proposals, called fractal trees, construct a sequence of maximal i-order decomposable graphs, for i = 2, ..., k, in k − 1 steps. At each step, the algorithms follow a divide-and-conquer strategy based on the particular features of this type of structures. Additionally, we propose a prune-and-graft procedure which transforms a maximal k-order decomposable graph into another one, increasing its likelihood. We have implemented two particular fractal tree algorithms called parallel fractal tree and sequential fractal tree. These algorithms can be considered a natural extension of Chow and Liu’s algorithm, from k = 2 to arbitrary values of k. Both algorithms have been compared against other efficient approaches in artificial and real domains, and they have shown a competitive behavior to deal with the maximum likelihood problem. Due to their low computational complexity they are especially recommended to deal with high dimensional domains.

Proposal and validation of methodologies for the categorisation of continuous variables in the development of prediction models

158 p.

Digital Quantum Simulation of Spin Models with Circuit Quantum Electrodynamics

Systems of interacting quantum spins show a rich spectrum of quantum phases and display interesting many-body dynamics. Computing characteristics of even small systems on conventional computers poses significant challenges. A quantum simulator has the potential to outperform standard computers in calculating the evolution of complex quantum systems. Here, we perform a digital quantum simulation of the paradigmatic Heisenberg and Ising interacting spin models using a two transmon-qubit circuit quantum electrodynamics setup. We make use of the exchange interaction naturally present in the simulator to construct a digital decomposition of the model-specific evolution and extract its full dynamics. This approach is universal and efficient, employing only resources that are polynomial in the number of spins, and indicates a path towards the controlled simulation of general spin dynamics in superconducting qubit platforms.

The outset of mental torture. Through the lens of the Ticking Time Bomb Scenario

No doubt shall be placed when qualifying torture as one of the cruellest crime offences against human beings. It is widely known that the first torture practices go back to the Middle Ages, where torture mechanisms and devices were used as a legitimate means of punishment, extraction of confessions or executions. Brutal techniques such as ‘Judas Cradle’, ‘The Rack’ or the ‘Rat Torture’ were indeed, the ones commonly used. Moreover, some centuries onwards, torture warrants were permitted and authorised by Privy Councils in legislations such as the English one. However, examples like that were the only ones which public accountability was given to, whereas off-the-book practices remained in silence in other countries for long lasting years. Nowadays, in the 21st century, there are innumerable enforced laws and provisions that prohibit the act of torture, to be precise, physical and psychological torture. Nonetheless, not only are these legislations necessary for fighting torture, but also ad hoc courts and specialised committees continuously report the existence of this crime offence.

Usage of substances and their dosage regimes in pharmacological animal models of schizophrenia

Background: Contrary to what is generally thought schizophrenia is a very common mental health issue. For this, several animal models are used to assess the illness in order to develop a definitive. The most widely spread paradigm is the use of pharmacological models. Aim: The aim of this review is to display which are the most used insults for the assessment of social behaviour related negative symptoms in animal models as well as to ascertain which is the most adequate regime. Design: Literature review. Methods: PubMed database was used for this article by the search of the indexed “schizophrenia”, “animal models”, “social behaviour” and “negative symptoms” descriptors. With the exception of a single article due to it value this review is based on articles from 10 years onwards. Besides, only clinical trials and reviews written in English or Spanish and that had laboratory rodents as target population were accepted. Results: The studies assessed agree that pharmacological models (specially those regarding the NMDA receptor antagonists) are a valuable means for the experimental investigation of negative symptoms in schizophrenia with the necessity to emphasise that only some negative symptoms (anhedonia and social interaction, mainly) can be experimentally assessed. Conclusions: There is not enough evidence regarding the fours aspects of this review. PCP, Ketamine or MK-801 in sub-acute dosage regimes are currently the most indicated insults to mimic schizophrenic symptoms in rodents, although further research in needed, albeit other substances are valuable as well. (In English language exclusively)