Forecasting GDP Growth using Disaggregated GDP Revisions

This paper investigates the informational content of regular revisions to real GDP growth and its components. We perform a real-time forecasting exercise for the advance estimate of real GDP growth using dynamic regression models that include revisions to GDP and its components. Echoing other work in the literature, we find little evidence that including aggregate GDP growth revisions improves forecast accuracy relative to an AR(1) baseline model; however, models that include revisions to components of GDP improve forecast accuracy. The first revision to consumption is particularly relevant in that every model that includes the revision outperforms the baseline model. Measured by root mean squared forecasting error (RMSFE), improvements are quite sizable, with many models increasing forecasting performance by 5% or more, and with top-performing models forecasting 0.24 percentage points closer to the advance estimate of growth. We use Bayesian model averaging to underscore that our results are driven by the informational content of revisions. The posterior probability of models with the first revision to consumption is significantly higher than our baseline model, despite strong priors that the latter should be the preferred forecasting model

The impact of analyst sentiment on UK stock recommendations and target prices

© 2015 Taylor & Francis. The aim of this paper is to investigate the relationship between narrative sentiment in analysts' company reports and their recommendation and target price outputs. We study an industry-balanced sample of 275 UK quoted company sell-side analyst reports over the period 2006-2010 using a content analysis methodology to measure net sentiment for a range of themes. We then model analysts' outputs against themed sentiment scores to analyse the impact of the Global Financial Crisis. We find that themed sentiments impact upon analysts' outputs, but their magnitude and direction vary over the pre-crisis, crisis and post-crisis periods. In particular, before the crisis we find a strong negative relationship between the macroeconomic and regulatory environment and report outputs, though this effect diminishes somewhat with the onset of the crisis, to be restored thereafter. Growth sentiment exerts a weak positive impact before the crisis which disappears thereafter. Financial performance sentiment becomes a significant positive driver of outputs following the crisis. There is evidently a "back to basics" approach following the crisis which restores financial fundamentals to the heart of stock analysis. Our findings provide some insight into the thought processes of analysts by identifying the dynamic relation between analysts' outputs and themed sentiments

Broken Symmetry in Density-Functional Theory: Analysis and Cure

We present a detailed analysis of the broken-symmetry mean-field solutions using a four-electron rectangular quantum dot as a model system. Comparisons of the density-functional theory predictions with the exact ones show that the symmetry breaking results from the single-configuration wave function used in the mean-field approach. As a general cure we present a scheme that systematically incorporates several configurations into the density-functional theory and restores the symmetry. This cure is easily applicable to any density-functional approach.Comment: 4 pages, 4 figures, submitted to PR

How do scientists perceive the current publication culture? A qualitative focus group interview study among Dutch biomedical researchers.

OBJECTIVE: To investigate the biomedical scientist's perception of the prevailing publication culture. DESIGN: Qualitative focus group interview study. SETTING: Four university medical centres in the Netherlands. PARTICIPANTS: Three randomly selected groups of biomedical scientists (PhD, postdoctoral staff members and full professors). MAIN OUTCOME MEASURES: Main themes for discussion were selected by participants. RESULTS: Frequently perceived detrimental effects of contemporary publication culture were the strong focus on citation measures (like the Journal Impact Factor and the H-index), gift and ghost authorships and the order of authors, the peer review process, competition, the funding system and publication bias. These themes were generally associated with detrimental and undesirable effects on publication practices and on the validity of reported results. Furthermore, senior scientists tended to display a more cynical perception of the publication culture than their junior colleagues. However, even among the PhD students and the postdoctoral fellows, the sentiment was quite negative. Positive perceptions of specific features of contemporary scientific and publication culture were rare. CONCLUSIONS: Our findings suggest that the current publication culture leads to negative sentiments, counterproductive stress levels and, most importantly, to questionable research practices among junior and senior biomedical scientists

The Role of the Gut Microbiota in the Effects of Early-Life Stress and Dietary Fatty Acids on Later-Life Central and Metabolic Outcomes in Mice

Early-life stress (ELS) leads to increased vulnerability for mental and metabolic disorders. We have previously shown that a low dietary ω-6/ω-3 polyunsaturated fatty acid (PUFA) ratio protects against ELS-induced cognitive impairments. Due to the importance of the gut microbiota as a determinant of long-term health, we here study the impact of ELS and dietary PUFAs on the gut microbiota and how this relates to the previously described cognitive, metabolic, and fatty acid profiles. Male mice were exposed to ELS via the limited bedding and nesting paradigm (postnatal day (P)2 to P9 and to an early diet (P2 to P42) with an either high (15) or low (1) ω-6 linoleic acid to ω-3 alpha-linolenic acid ratio. 16S rRNA was sequenced and analyzed from fecal samples at P21, P42, and P180. Age impacted α- and β-diversity. ELS and diet together predicted variance in microbiota composition and affected the relative abundance of bacterial groups at several taxonomic levels in the short and long term. For example, age increased the abundance of the phyla Bacteroidetes, while it decreased Actinobacteria and Verrucomicrobia; ELS reduced the genera RC9 gut group and Rikenella, and the low ω-6/ω-3 diet reduced the abundance of the Firmicutes Erysipelotrichia. At P42, species abundance correlated with body fat mass and circulating leptin (e.g., Bacteroidetes and Proteobacteria taxa) and fatty acid profiles (e.g., Firmicutes taxa). This study gives novel insights into the impact of age, ELS, and dietary PUFAs on microbiota composition, providing potential targets for noninvasive (nutritional) modulation of ELS-induced deficits. IMPORTANCE Early-life stress (ELS) leads to increased vulnerability to develop mental and metabolic disorders; however, the biological mechanisms leading to such programming are not fully clear. Increased attention has been given to the importance of the gut microbiota as a determinant of long-term health and as a potential target for noninvasive nutritional strategies to protect against the negative impact of ELS. Here, we give novel insights into the complex interaction between ELS, early dietary ω-3 availability, and the gut microbiota across ages and provide new potential targets for (nutritional) modulation of the long-term effects of the early-life environment via the microbiota

The impact of constructive operating lease capitalisation on key accounting ratios

Current UK lease accounting regulation does not require operating leases to be capitalised in the accounts of lessees, although this is likely to change with the publication of FRS 5. This study conducts a prospective analysis of the effects of such a change. The potential magnitude of the impact of lease capitalisation upon individual users' decisions, market valuations, company cash flows, and managers' behaviour can be indicated by the effect on key accounting ratios, which are employed in decision-making and in financial contracts. The capitalised value of operating leases is estimated using a method similar to that suggested by Imhoff, Lipe and Wright (1991), adapted for the UK accounting and tax environment, and developed to incorporate company-specific assumptions. Results for 1994 for a random sample of 300 listed UK companies show that, on average, the unrecorded long-term liability represented 39% of reported long-term debt, while the unrecorded asset represented 6% of total assets. Capitalisation had a significant impact (at the 1% level) on six of the nine selected ratios (profit margin, return on assets, asset turnover, and three measures of gearing). Moreover, the Spearman rank correlation between each ratio before and after capitalisation revealed that the ranking of companies changed markedly for gearing measures in particular. There were significant inter-industry variations, with the services sector experiencing the greatest impact. An analysis of the impact of capitalisation over the five-year period from 1990 to 1994 showed that capitalisation had the greatest impact during the trough of the recession. Results were shown to be robust with respect to key assumptions of the capitalisation method. These findings contribute to the assessment of the economic consequences of a policy change requiring operating lease capitalisation. Significant changes in the magnitude of key accounting ratios and a major shift in company performance rankings suggest that interested parties' decisions and company cash flows are likely to be affected

Prediction of Therapy Tumor-Absorbed Dose Estimates in I-131 Radioimmunotherapy Using Tracer Data Via a Mixed-Model Fit to Time Activity

Abstract Background: For individualized treatment planning in radioimmunotherapy (RIT), correlations must be established between tracer-predicted and therapy-delivered absorbed doses. The focus of this work was to investigate this correlation for tumors. Methods: The study analyzed 57 tumors in 19 follicular lymphoma patients treated with I-131 tositumomab and imaged with SPECT/CT multiple times after tracer and therapy administrations. Instead of the typical least-squares fit to a single tumor's measured time-activity data, estimation was accomplished via a biexponential mixed model in which the curves from multiple subjects were jointly estimated. The tumor-absorbed dose estimates were determined by patient-specific Monte Carlo calculation. Results: The mixed model gave realistic tumor time-activity fits that showed the expected uptake and clearance phases even with noisy data or missing time points. Correlation between tracer and therapy tumor-residence times (r=0.98; p<0.0001) and correlation between tracer-predicted and therapy-delivered mean tumor-absorbed doses (r=0.86; p<0.0001) were very high. The predicted and delivered absorbed doses were within±25% (or within±75 cGy) for 80% of tumors. Conclusions: The mixed-model approach is feasible for fitting tumor time-activity data in RIT treatment planning when individual least-squares fitting is not possible due to inadequate sampling points. The good correlation between predicted and delivered tumor doses demonstrates the potential of using a pretherapy tracer study for tumor dosimetry-based treatment planning in RIT.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98438/1/cbr%2E2011%2E1053.pd

Modelling the Hosting Capacity of Orion's Low Voltage Network for EV Charging

Forecasting future electricity demand on low voltage (LV) distribution networks is particularly challenging in the face of new technologies such as Electric Vehicles (EVs) where the uptake and charging behaviours are highly uncertain. To support their planning processes, Orion has undertaken a staged assessment of LV network performance in the face of increasing levels of EV charging. The first stage of EV modelling involved a high-level deterministic simulation of all Orion’s LV networks to identify areas that may be more vulnerable to constraints. From the results of the first stage, a smaller subset of vulnerable LV networks was selected for further modelling. This paper focuses on the second stage of the assessment process where 236 selected distribution transformers and their downstream LV networks were modelled using a probabilistic methodology developed by the EPECentre. This model captures a wide range of scenarios and encompasses data from New Zealand-centric inputs, including national travel surveys, household smart meter demand profiles and the current NZ EV fleet composition. In order to meet the large simulation burden required of a probabilistic methodology, a fast power flow solver was developed. This paper reports the forecast congestion levels and probabilities that these selected circuits may face as EV charging increases on Orion’s network. The learnings and challenges of working with imperfect distribution asset data sets to develop these models are also shared, such as approximating LV phase imbalance and electricity demand profiles with only the LV distribution transformer’s Maximum Demand Indicator (MDIs) measurements

Health expenditure of employees versus self-employed individuals; a 5-year study.

It is unclear to what extent self‐employed choose to become self‐employed. This study aimed to compare the health care expenditures—as a proxy for health—of self‐employed individuals in the year before they started their business, to that of employees. Differences by sex, age, and industry were studied. In total, 5,741,457 individuals aged 25–65 years who were listed in the tax data between 2010 and 2015 with data on their health insurance claims were included. Self‐employed and employees were stratified according to sex, age, household position, personal income, region, and industry for each of the years covered. Weighted linear regression was used to compare health care expenditures in the preceding (year x–1) between self‐employed and employees (in year x). Compare