Bayesian Inference in the Time Varying Cointegration Model

There are both theoretical and empirical reasons for believing that the parameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved Vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper we develop time varying parameter models which permit cointegration. Time-varying parameter VARs (TVP-VARs) typically use state space representations to model the evolution of parameters. In this paper, we show that it is not sensible to use straightforward extensions of TVP-VARs when allowing for cointegration. Instead we develop a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP-VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving a permanent/transitory variance decomposition for inflation.

Sistema d'autenticació one-time password (OTP) per a mòbils

Aquest projecte consisteix en fer l’anàlisi, disseny i implementació d'un sistema d'autenticació a través de contrasenyes d’un sol ús (One Time Password ‐OTP‐) per a dispositius mòbils. Per evitar l’ús de contrasenyes estàtiques farem una aplicació per a telèfons mòbils capaç de generar contrasenyes aleatòries gràcies a uns paràmetres previs, així com de poder tenir un registre dels serveis on poden ser utilitzades. Partirem d’un protocol repte/resposta on l’usuari interactuarà amb el seu telèfon mòbil i un ordinador personal amb una connexió a Internet. Podrà registrar‐se i, introduint certes dades al mòbil que li proporciona el servidor, podrà fer el procés d’autenticar‐se per poder accedir a zones restringides del servei.

Does Semantic Context Benefit Speech Understanding through "Top-Down" Processes? Evidence from Time-resolved Sparse fMRI.

When speech is degraded, word report is higher for semantically coherent sentences (e.g., her new skirt was made of denim) than for anomalous sentences (e.g., her good slope was done in carrot). Such increased intelligibility is often described as resulting from "top-down" processes, reflecting an assumption that higher-level (semantic) neural processes support lower-level (perceptual) mechanisms. We used time-resolved sparse fMRI to test for top-down neural mechanisms, measuring activity while participants heard coherent and anomalous sentences presented in speech envelope/spectrum noise at varying signal-to-noise ratios (SNR). The timing of BOLD responses to more intelligible speech provides evidence of hierarchical organization, with earlier responses in peri-auditory regions of the posterior superior temporal gyrus than in more distant temporal and frontal regions. Despite Sentence content × SNR interactions in the superior temporal gyrus, prefrontal regions respond after auditory/perceptual regions. Although we cannot rule out top-down effects, this pattern is more compatible with a purely feedforward or bottom-up account, in which the results of lower-level perceptual processing are passed to inferior frontal regions. Behavioral and neural evidence that sentence content influences perception of degraded speech does not necessarily imply "top-down" neural processes.

Changes in Running Mechanics and Spring-Mass Behaviour during a 5-km Time Trial

Research into the biomechanical manifestation of fatigue during exhaustive runs is increasingly popular but additional understanding of the adaptation of the spring-mass behaviour during the course of strenuous, self-paced exercises continues to be a challenge in order to develop optimized training and injury prevention programs. This study investigated continuous changes in running mechanics and spring-mass behaviour during a 5-km run. 12 competitive triathletes performed a 5-km running time trial (mean performance: 17 min 30 s) on a 200 m indoor track. Vertical and anterior-posterior ground reaction forces were measured every 200 m by a 5-m long force platform system, and used to determine spring-mass model characteristics. After a fast start, running velocity progressively decreased (- 11.6%; P<0.001) in the middle part of the race before an end spurt in the final 400-600 m. Stride length (- 7.4%; P<0.001) and frequency (- 4.1%; P=0.001) decreased over the 25 laps, while contact time (+ 8.9%; P<0.001) and total stride duration (+ 4.1%; P<0.001) progressively lengthened. Peak vertical forces (- 2.0%; P<0.01) and leg compression (- 4.3%; P<0.05), but not centre of mass vertical displacement (+ 3.2%; P>0.05), decreased with time. As a result, vertical stiffness decreased (- 6.0%; P<0.001) during the run, whereas leg stiffness changes were not significant (+ 1.3%; P>0.05). Spring-mass behaviour progressively changes during a 5-km time trial towards deteriorated vertical stiffness, which alters impact and force production characteristics.

Time-consistent fiscal policy under heterogeneity: Conflicting or common interests?

This paper studies the aggregate and distributional implications of Markov-perfect tax-spending policy in a neoclassical growth model with capitalists and workers. Focusing on the long run, our main fi ndings are: (i) it is optimal for a benevolent government, which cares equally about its citizens, to tax capital heavily and to subsidise labour; (ii) a Pareto improving means to reduce ine¢ ciently high capital taxation under discretion is for the government to place greater weight on the welfare of capitalists; (iii) capitalists and workers preferences, regarding the optimal amount of "capitalist bias", are not aligned implying a conflict of interests.

Adaptive Continuous time Markov Chain Approximation Model to General Jump-Diusions

We propose a non-equidistant Q rate matrix formula and an adaptive numerical algorithm for a continuous time Markov chain to approximate jump-diffusions with affine or non-affine functional specifications. Our approach also accommodates state-dependent jump intensity and jump distribution, a flexibility that is very hard to achieve with other numerical methods. The Kolmogorov-Smirnov test shows that the proposed Markov chain transition density converges to the one given by the likelihood expansion formula as in Ait-Sahalia (2008). We provide numerical examples for European stock option pricing in Black and Scholes (1973), Merton (1976) and Kou (2002).

Large Time-Varying Parameter VARs

In this paper we develop methods for estimation and forecasting in large timevarying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman filter estimation with forgetting factors. We also draw on ideas from the dynamic model averaging literature and extend the TVP-VAR so that its dimension can change over time. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output, and interest rates demonstrates the feasibility and usefulness of our approach.

Matrix-assisted laser desorption ionization-time of flight mass spectrometry for direct bacterial identification from positive blood culture pellets.

An ammonium chloride erythrocyte-lysing procedure was used to prepare a bacterial pellet from positive blood cultures for direct matrix-assisted laser desorption-ionization time of flight (MALDI-TOF) mass spectrometry analysis. Identification was obtained for 78.7% of the pellets tested. Moreover, 99% of the MALDI-TOF identifications were congruent at the species level when considering valid scores. This fast and accurate method is promising.

Time is Running Out: The 2°C Target and Optimal Climate Policies

The quintessence of recent natural science studies is that the 2 degrees C target can only be achieved with massive emission reductions in the next few years. The central twist of this paper is the addition of this limited time to act into a non-perpetual real options framework analysing optimal climate policy under uncertainty. The window-of-opportunity modelling setup shows that the limited time to act may spark a trend reversal in the direction of low-carbon alternatives. However, the implementation of a climate policy is evaded by high uncertainty about possible climate pathways.

Time Horizons And Smoothing In The Bank Of England’s Reaction Function: The Contrast Between The Standard GMM And Ex Ante Forecast Approaches

The monetary policy reaction function of the Bank of England is estimated by the standard GMM approach and the ex-ante forecast method developed by Goodhart (2005), with particular attention to the horizons for inflation and output at which each approach gives the best fit. The horizons for the ex-ante approach are much closer to what is implied by the Bank’s view of the transmission mechanism, while the GMM approach produces an implausibly slow adjustment of the interest rate, and suffers from a weak instruments problem. These findings suggest a strong preference for the ex-ante approach.

Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada

VAR methods have been used to model the inter-relationships between inflows and outfl ows into unemployment and vacancies using tools such as impulse response analysis. In order to investigate whether such impulse responses change over the course of the business cycle or or over time, this paper uses TVP-VARs for US and Canadian data. For the US, we find interesting differences between the most recent recession and earlier recessions and expansions. In particular, we find the immediate effect of a negative shock on both in ow and out flow hazards to be larger in 2008 than in earlier times. Furthermore, the effect of this shock takes longer to decay. For Canada, we fi nd less evidence of time-variation in impulse responses.

Time Horizons And Smoothing In The Bank Of England’s Reaction Function: The Contrast Between The Standard GMM And Ex Ante Forecast Approaches

The monetary policy reaction function of the Bank of England is estimated by the standard GMM approach and the ex-ante forecast method developed by Goodhart (2005), with particular attention to the horizons for inflation and output at which each approach gives the best fit. The horizons for the ex-ante approach are much closer to what is implied by the Bank’s view of the transmission mechanism, while the GMM approach produces an implausibly slow adjustment of the interest rate, and suffers from a weak instruments problem. These findings suggest a strong preference for the ex-ante approach.

Relationship between trade openness and economic growth of India: A time series analysis

The paper aims to examine the empirical relationship between trade openness and economic growth of India for the time period 1970-2010. Trade openness is a multi-dimensional concept and hence measures of both trade barriers and trade volumes have been used as proxies for openness. The estimation results from Vector Autoregressive method suggest that growth in trade volumes accelerate economic growth in case of India. We do not find any evidence from our analysis that trade barriers lower growth.

Model Switching and Model Averaging in Time- Varying Parameter Regression Models

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.

On the time-varying relationship between EMU sovereign spreads and their determinants

We use a dynamic multipath general-to-specific algorithm to capture structural instability in the link between euro area sovereign bond yield spreads against Germany and their underlying determinants over the period January 1999 – August 2011. We offer new evidence suggesting a significant heterogeneity across countries, both in terms of the risk factors determining spreads over time as well as in terms of the magnitude of their impact on spreads. Our findings suggest that the relationship between euro area sovereign risk and the underlying fundamentals is strongly timevarying, turning from inactive to active since the onset of the global financial crisis and further intensifying during the sovereign debt crisis. As a general rule, the set of financial and macro spreads’ determinants in the euro area is rather unstable but generally becomes richer and stronger in significance as the crisis evolves.