Does trade integration alter monetary policy transmission?

This paper explores the role of trade integration—or openness—for monetary policy transmission in a medium-scale New Keynesian model. Allowing for strategic complementarities in price-setting, we highlight a new dimension of the exchange rate channel by which monetary policy directly impacts domestic inflation. Although the strength of this effect increases with economic openness, it also requires that import prices respond to exchange rate changes. In this case domestic producers find it optimal to adjust their prices to exchange rate changes which alter the domestic currency price of their foreign competitors. We pin down key parameters of the model by matching impulse responses obtained from a vector autoregression on U.S. time series relative to an aggregate of industrialized countries. While we find evidence for strong complementarities, exchange rate pass-through is limited. Openness has therefore little bearing on monetary transmission in the estimated model

First second of leptons

A poorly constrained parameter in the Standard Model of Cosmology is the lepton asymmetry l = \sum_f l_f=\sum_f(n_f+n_{\nu_f})/s. Each flavour asymmetry l_f with f=e, \mu, {\tau} is the sum of the net particle density of the charged leptons n_f and their corresponding neutrinos, normalized with the entropy density s. Constraints on l_f \leq O(0.1) from BBN and CMB allow for lepton flavour asymmetries orders of magnitudes larger then the baryon asymmetry b ~ 10^{-10}. In this article we show how such large lepton (flavour) asymmetries influence the early universe, in particular the freeze out of WIMPs and the cosmic QCD transition.Comment: 4 pages, 2 figures; prepared for the 12th international conference on Topics in Astroparticle and Underground Physics, TAUP2011. v2: matches accepted versio

A new comparative approach to macroeconomic modeling and policy analysis

In the aftermath of the global financial crisis, the state of macroeconomic modeling and the use of macroeconomic models in policy analysis has come under heavy criticism. Macroeconomists in academia and policy institutions have been blamed for relying too much on a particular class of macroeconomic models. This paper proposes a comparative approach to macroeconomic policy analysis that is open to competing modeling paradigms. Macroeconomic model comparison projects have helped produce some very influential insights such as the Taylor rule. However, they have been infrequent and costly, because they require the input of many teams of researchers and multiple meetings to obtain a limited set of comparative findings. This paper provides a new approach that enables individual researchers to conduct model comparisons easily, frequently, at low cost and on a large scale. Using this approach a model archive is built that includes many well-known empirically estimated models that may be used for quantitative analysis of monetary and fiscal stabilization policies. A computational platform is created that allows straightforward comparisons of models’ implications. Its application is illustrated by comparing different monetary and fiscal policies across selected models. Researchers can easily include new models in the data base and compare the effects of novel extensions to established benchmarks thereby fostering a comparative instead of insular approach to model development

Modelling the effects of environmental conditions on wind turbine failures

Operation and maintenance is one of the main cost drivers of modern wind farms and has become an emerging field of research over the past years. Understanding the failure behaviour of wind turbines (WTs) can significantly enhance operation and maintenance processes and is essential for developing reliability and strategic maintenance models. Previous research has shown that especially the environmental conditions, to which the turbines are exposed to, affect their reliability drastically. This paper compares several advanced modelling techniques and proposes a novel approach to model WT system and component failures based on the site-specific weather conditions. Furthermore, to avoid common problems in failure modelling, procedures for variable selection and complexity reduction are discussed and incorporated. This is applied to a big failure database comprised of 11 wind farms and 383 turbines. The results show that the model performs very well in several situations such as modelling general WT failures as well as failures of specific components. The latter is exemplified using gearbox failures

Modelling Wind Turbine Failures based on Weather Conditions

A large proportion of the overall costs of a wind farm is directly related to operation and maintenance (O&M) tasks. By applying predictive O&M strategies rather than corrective approaches these costs can be decreased significantly. Here, especially wind turbine (WT) failure models can help to understand the components' degradation processes and enable the operators to anticipate upcoming failures. Usually, these models are based on the age of the systems or components. However, latest research shows that the on-site weather conditions also affect the turbine failure behaviour significantly. This study presents a novel approach to model WT failures based on the environmental conditions to which they are exposed to. The results focus on general WT failures, as well as on four main components: gearbox, generator, pitch and yaw system. A penalised likelihood estimation is used in order to avoid problems due to for example highly correlated input covariates. The relative importance of the model covariates is assessed in order to analyse the effect of each weather parameter on the model output

Does functional soil microbial diversity contribute to explain within-site plant beta-diversity in an alpine grassland and a <i>dehesa</i> meadow in Spain?

Questions: Once that the effects of hydrological and chemical soil properties have been accounted for, does soil microbial diversity contribute to explain change in plant community structure (i.e. within-site beta-diversity)? If so, at which spatial scale does microbial diversity operate? Location: La Mina in Moscosa Farm, Salamanca, western Spain (dehesa community) and Laguna Larga in the Urbión Peaks, Soria, central-northern Spain (alpine grassland). Methods: The abundance of vascular plant species, soil gram-negative microbial functional types and soil chemical properties (pH, available phosphorus, and extractable cations) were sampled at both sites, for which hydrological models were available. Redundancy analysis (RDA) was used to partition variation in plant community structure into hydrological, chemical and microbial components. Spatial filters, arranged in scalograms, were used to test for the spatial scales at which plant community structure change. Results: In the case of the dehesa the diversity of soil gram-negative microbes, weakly driven by soil pH, contributed to a small extent (adj-R2 = 2%) and at a relative medium spatial scale to explain change in plant community structure. The abundance of a few dehesa species, both annual (Trifolium dubium, Vulpia bromoides) and perennial (Poa bulbosa, Festuca ampla), was associated with either increasing or decreasing soil microbial diversity. In the alpine meadow the contribution was negligible. Conclusions: Microbial diversity can drive community structure, though in the hierarchy of environmental factors structuring communities it appears to rank lower than other soil factors. Still, microbial diversity appears to promote or restrain individual plant species. This paper aims to encourage future studies to use more comprehensive and insightful techniques to assess microbial diversity and to combine this with statistical approaches such as the one used here

Trimethyl­sulfonium 1-amino-6-fluoro-2,3,4,5,7,8,9,10,11,12-decaiodo-1-carba-closo-dodeca­borate

In the asymmetric unit of the title salt, C3H9S+·CH2B11FI10N− or (CH3)3S[1-H2N-6-F-closo-1-CB11I10], both ions lie in general positions. The anion is perfectly ordered and so the positions of the C—NH2 vertex and the fluorine substituent are clearly assigned. The relatively short C—N bond length may be inter­preted in terms of a very electron deficient {closo-1-CB11} cluster

Tetra­ethyl­ammonium 12-phenyl­ethynylcarba-closo-dodeca­borate, [Et4N][12-PhCC-closo-CB11H11]

The asymmetric unit of the title compound, C8H20N+·C9H16B11 − or [Et4N][12-PhCC-closo-CB11H11], consists of one cation and one anion. The [12-PhCC-closo-CB11H11]− anion is close to possessing a non-crystallographic plane of mirror symmetry with a nearly linear B—C C—C group, with B—C C and C C—C angles of 177.15 (16) and 176.64 (17)°, respectively

Data-driven learning framework for associating weather conditions and wind turbine failures

The need for cost effective operation and maintenance (O&M) strategies in wind farms has risen significantly with the growing wind energy sector. In order to decrease costs, current practice in wind farm O&M is switching from corrective and preventive strategies to rather predictive ones. Anticipating wind turbine (WT) failures requires sophisticated models to understand the complex WT component degradation processes and to facilitate maintenance decision making. Environmental conditions and their impact on WT reliability play a significant role in these processes and need to be investigated profoundly. This paper is presenting a framework to assess and correlate weather conditions and their effects on WT component failures. Two approaches, using (a) supervised and (b) unsupervised data mining techniques are applied to pre-process the weather and failure data. An apriori rule mining algorithm is employed subsequently, in order to obtain logical interconnections between the failure occurrences and the environmental data, for both approaches. The framework is tested using a large historical failure database of modern wind turbines. The results show the relation between environmental parameters such as relative humidity, ambient temperature, wind speed and the failures of five major WT components: gearbox, generator, frequency converter, pitch and yaw system. Additionally, the performance of each technique, associating weather conditions and WT component failures, is assessed