Metropolis-Hastings prefetching algorithms

Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based on the idea of evaluating the posterior in parallel and ahead of time. In this paper improved Metropolis-Hastings prefetching algorithms are presented and evaluated. It is shown how to use available information to make better predictions of the future states of the chain and increase the efficiency of prefetching considerably. The optimal acceptance rate for the prefetching random walk Metropolis-Hastings algorithm is obtained for a special case and it is shown to decrease in the number of processors employed. The performance of the algorithms is illustrated using a well-known macroeconomic model. Bayesian estimation of DSGE models, linearly or nonlinearly approximated, is identified as a potential area of application for prefetching methods. The generality of the proposed method, however, suggests that it could be applied in many other contexts as well.Prefetching; Metropolis-Hastings; Parallel Computing; DSGE models; Optimal acceptance rate

Deaf-perspective in the Gospel of Mark 7:31-37

This essay examines the theme of the deaf -perspective in the Gospel of Mark 7:31-37 . Two main questions asked are: 1 ) ” How does the Gospel of Marks view on deafness in the periscope of Mark 7:31-37? 2 ) ” How can one interpret the text from a deaf perspective parallel l to the contemporary scientific discourse disability studies today”? The view of deafness is nuanced and the essay then discusses the complexity of Mark´s texts in view of deaf perspective in dialogue with disability studies. It become more complex when the view of deafness in Marks gospel both constructs and deconstructs deafness as a disability

Debt dynamics and monetary policy: A note

"Leaning against the wind" - a tighter monetary policy than necessary for stabilizing inflation around the inflation target and unemployment around a long-run sustainable rate - has been justified as a way of reducing household indebtedness. In a recent paper Lars Svensson claims that this policy is counterproductive, since a higher policy rate actually leads to an increase (and not a decrease) in real debt and the debt-to-GDP ratio. In this note we offer some comments and extensions to Svensson's analysis. In particular, we take Svensson's debt model to the data and show that it provides an incomplete account of short term debt dynamics. Further, the overall analysis of the effects of monetary policy on debt rests on the rather strong assumption that debt is independent of the policy rate, conditional on housing prices. The policy responses advocated by Svensson can therefore be questioned. More importantly, our exercises with a modified model of debt dynamics enables further understanding of how different assumptions affect the assessment of the effects of monetary policy on debt

Adaptive hybrid Metropolis-Hastings samplers for DSGE models

Bayesian inference for DSGE models is typically carried out by single block random walk Metropolis, involving very high computing costs. This paper combines two features, adaptive independent Metropolis-Hastings and parallelisation, to achieve large computational gains in DSGE model estimation. The history of the draws is used to continuously improve a t-copula proposal distribution, and an adaptive random walk step is inserted at predetermined intervals to escape difficult points. In linear estimation applications to a medium scale (23 parameters) and a large scale (51 parameters) DSGE model, the computing time per independent draw is reduced by 85% and 65-75% respectively. In a stylised nonlinear estimation example (13 parameters) the reduction is 80%. The sampler is also better suited to parallelisation than random walk Metropolis or blocking strategies, so that the effective computational gains, i.e. the reduction in wall-clock time per independent equivalent draw, can potentially be much larger.Markov Chain Monte Carlo (MCMC); Adaptive Metropolis-Hastings; Parallel algorithm; DSGE model; Copula

Metropolis-Hastings prefetching algorithms

Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based on the idea of evaluating the posterior in parallel and ahead of time. Improved Metropolis-Hastings prefetching algorithms are presented and evaluated. It is shown how to use available information to make better predictions of the future states of the chain and increase the efficiency of prefetching considerably. The optimal acceptance rate for the prefetching random walk Metropolis-Hastings algorithm is obtained for a special case and it is shown to decrease in the number of processors employed. The performance of the algorithms is illustrated using a well-known macroeconomic model. Bayesian estimation of DSGE models, linearly or nonlinearly approximated, is identi…ed as a potential area of application for prefetching methods. The generality of the proposed method, however, suggests that it could be applied in other contexts as well

Optimal Opportunistic Monetary Policy in A New-Keynesian Model

The present paper compares the performance in terms of second order accurate welfare of opportunistic non-linear Taylor rules and with respect to traditional linear Taylor rules. The macroeconomic model representing the benchmark for the analysis includes capital accumulation (with quadratic costs of adjustment), price rigidities (quadratic approach), along the standard New-Keynesian approach. The model is solved up to second order approximation and welfare is evaluated according to several criteria (conditional to the non-stochastic steady state, unconditional, and according to a linear ad hoc function). The results show that: (i) the opportunistic rule is a Pareto improvement with respect to other monetary policy rules traditionally considered in the literature; (ii) the computation of welfare costs reveals that the burden of adjustment is almost entirely on labor supply fluctuations;(iii) increasing the degree of price rigidities and the degree of competition in the final goods markets, makes the opportunistic rule even more preferable with respect to the alternatives. Business Cycle statistics for the model with opportunistic rule show a large volatility in labor supply, with a limited volatility for the nominal interest rate

Adaptive hybrid Metropolis-Hastings samplers for DSGE models

Bayesian inference for DSGE models is typically carried out by single block random walk Metropolis, involving very high computing costs. This paper combines two features, adaptive independent Metropolis-Hastings and parallelisation, to achieve large computational gains in DSGE model estimation. The history of the draws is used to continuously improve a t-copula proposal distribution, and an adaptive random walk step is inserted at predetermined intervals to escape difficult points. In linear estimation applications to a medium scale (23 parameters) and a large scale (51 parameters) DSGE model, the computing time per independent draw is reduced by 85% and 65-75% respectively. In a stylised nonlinear estimation example (13 parameters) the reduction is 80%. The sampler is also better suited to parallelisation than random walk Metropolis or blocking strategies, so that the effective computational gains, i.e. the reduction in wall-clock time per independent equivalent draw, can potentially be much larger

Multiple roles for UV RESISTANCE LOCUS8 in regulating gene expression and metabolite accumulation in arabidopsis under solar ultraviolet radiation

Photomorphogenic responses triggered by low fluence rates of ultraviolet B radiation (UV-B; 280–315 nm) are mediated by the UV-B photoreceptor UV RESISTANCE LOCUS8 (UVR8). Beyond our understanding of the molecular mechanisms of UV-B perception by UVR8, there is still limited information on how the UVR8 pathway functions under natural sunlight. Here, wild-type Arabidopsis (Arabidopsis thaliana) and the uvr8-2 mutant were used in an experiment outdoors where UV-A (315–400 nm) and UV-B irradiances were attenuated using plastic films. Gene expression, PYRIDOXINE BIOSYNTHESIS1 (PDX1) accumulation, and leaf metabolite signatures were analyzed. The results show that UVR8 is required for transcript accumulation of genes involved in UV protection, oxidative stress, hormone signal transduction, and defense against herbivores under solar UV. Under natural UV-A irradiance, UVR8 is likely to interact with UV-A/blue light signaling pathways to moderate UV-B-driven transcript and PDX1 accumulation. UVR8 both positively and negatively affects UV-A-regulated gene expression and metabolite accumulation but is required for the UV-B induction of phenolics. Moreover, UVR8-dependent UV-B acclimation during the early stages of plant development may enhance normal growth under long-term exposure to solar UV