Hicks meets Hotelling: the direction of technical change in capital-resource economies

We analyze a two-sector growth model with directed technical change where man-made capital and exhaustible resources are essential for production. The relative profitability of factor-specific innovations endogenously determines whether technical progress will be capital- or resource-augmenting. We show that any balanced growth equilibrium features purely resource-augmenting technical change. This result is compatible with alternative specifications of preferences and innovation technologies, as it hinges on the interplay between productive efficiency in the final sector, and the Hotelling rule characterizing the efficient depletion path for the exhaustible resource. Our result provides sound micro-foundations for the broad class of models of exogenous/endogenous growth where resource-augmenting progress is required to sustain consumption in the long run, contradicting the view that these models are conceptually biased in favor of sustainability.

Resource access needs and capabilities as mediators of the relationship between VC firm size and syndication

Drawing from the resource-based view and transaction costs economics, we develop a theoretical framework to explain why small and large firms face different levels of resource access needs and resource access capabilities, which mediate the relationship between firm size and hybrid governance. Employing a sample of 317 venture capital firms, drawn across six European countries, we empirically assess our framework in the context of venture capital syndication. We estimate a path model using structural equation modeling and find, consistent with our theoretical framework, mediating effects of different types of resource access needs and resource access capabilities between VC firm size and syndication frequency. These findings advance the small business literature by highlighting the trade-offs that size imposes on firms that seek to manage their access to external resources through hybrid governance strategies.

Reforming central government: An evaluation of an accounting innovation

This paper examines a significant accounting innovation in central government accounting – the introduction of Resource Accounting and Budgeting (RAB) in the UK. This innovation is studied through the lens of Rogers diffusion theory. The study setting is the Scotland Parliament. This research shows that, in the terms of diffusion theory, RAB can be classified as an accounting innovation. However, the implementation of RAB is problematic. While the reform of the UK central government system was initially sought as a mechanism to enhance democratic accountability, this paper shows that RAB does not connect with parliamentarians. The introduction of RAB flows as much from a managerial agenda as it does from the aim of democratic accountability.

Evidence and Spatial Planning for Sustainable Development: A Model for Spatially Allocating Material Flows

The aspiration the spatial planning should act as the main coordinating function for the transition to a sustainable society is grounded on the assumption that it is capable of incorporating both a strong evidence base of environmental accounting for policy, coupled with opportunities for open, deliberative decision-making. While there are a number of increasingly sophisticated methods (such as material flow analysis and ecological footprinting) that can be used to longitudinally determine the impact of policy, there are fewer that can provide a robust spatial assessment of sustainability policy. In this paper, we introduce the Spatial Allocation of Material Flow Analysis (SAMFA) model, which uses the concept of socio-economic metabolism to extrapolate the impact of local consumption patterns that may occur as a result of the local spatial planning process at multiple spatial levels. The initial application the SAMFA model is based on County Kildare in the Republic of Ireland, through spatial temporal simulation and visualisation of construction material flows and associated energy use in the housing sector. Thus, while we focus on an Ireland case study, the model is applicable to spatial planning and sustainability research more generally. Through the development and evaluation of alternative scenarios, the model appears to be successful in its prediction of the cumulative resource and energy impacts arising from consumption and development patterns. This leads to some important insights in relation to the differential spatial distribution of disaggregated allocation of material balance and energy use, for example that rural areas have greater resource accumulation (and are therefore in a sense “less sustainable”) than urban areas, confirming that rural housing in Ireland is both more material and energy intensive. This therefore has the potential to identify hotspots of higher material and energy use, which can be addressed through targeted planning initiatives or focussed community engagement. Furthermore, due to the ability of the model to allow manipulation of different policy criteria (increased density, urban conservation etc), it can also act as an effective basis for multi-stakeholder engagement.

The DietCompLyf study: A prospective cohort study of breast cancer survival and phytoestrogen consumption

DietCompLyf is a multi-centre prospective study designed to investigate associations between phytoestrogens - naturally occurring plant compounds with oestrogenic properties - and other diet and lifestyle factors with breast cancer recurrence and survival. 3159 women with grades I-III breast cancer were recruited 9-15 months post-diagnosis from 56 UK hospitals. Detailed information on clinico-pathological, diet, lifestyle and quality of life is collected annually up to 5 years. Biological samples have also been collected as a resource for subsequent evaluation. The characteristics of the patients and associations between pre-diagnosis intake of phytoestrogens (isoflavones and lignans; assessed using the EPIC-Norfolk UK 130 question food frequency questionnaire) and breast cancer (i) risk factors and (ii) prognostic factors are described for 1797 women who had complete data for all covariates and phytoestrogens of interest. Isoflavone intakes were higher in the patients who were younger at diagnosis, in the non-smokers, those who had breast-fed and those who took supplements. Lignan intakes were higher in patients with a higher age at diagnosis, in ex-smokers, those who had breast-fed, who took supplements, had a lower BMI at diagnosis, lower age at menarche and were nulliparous. No significant associations between pre-diagnosis phytoestrogen intake and factors associated with improved breast cancer prognosis were observed. The potential for further exploration of the relationship between phytoestrogens and breast cancer recurrence and survival, and for the establishment of evidence to improve dietary and lifestyle advice offered to patients following breast cancer diagnosis using DietCompLyf data is discussed.

Wind energy resource modelling in Portugal and its future large-scale alteration due to anthropogenic induced climate changes

The high dependence of Portugal from foreign energy sources (mainly fossil fuels), together with the international commitments assumed by Portugal and the national strategy in terms of energy policy, as well as resources sustainability and climate change issues, inevitably force Portugal to invest in its energetic self-sufficiency. The 20/20/20 Strategy defined by the European Union defines that in 2020 60% of the total electricity consumption must come from renewable energy sources. Wind energy is currently a major source of electricity generation in Portugal, producing about 23% of the national total electricity consumption in 2013. The National Energy Strategy 2020 (ENE2020), which aims to ensure the national compliance of the European Strategy 20/20/20, states that about half of this 60% target will be provided by wind energy. This work aims to implement and optimise a numerical weather prediction model in the simulation and modelling of the wind energy resource in Portugal, both in offshore and onshore areas. The numerical model optimisation consisted in the determination of which initial and boundary conditions and planetary boundary layer physical parameterizations options provide wind power flux (or energy density), wind speed and direction simulations closest to in situ measured wind data. Specifically for offshore areas, it is also intended to evaluate if the numerical model, once optimised, is able to produce power flux, wind speed and direction simulations more consistent with in situ measured data than wind measurements collected by satellites. This work also aims to study and analyse possible impacts that anthropogenic climate changes may have on the future wind energetic resource in Europe. The results show that the ECMWF reanalysis ERA-Interim are those that, among all the forcing databases currently available to drive numerical weather prediction models, allow wind power flux, wind speed and direction simulations more consistent with in situ wind measurements. It was also found that the Pleim-Xiu and ACM2 planetary boundary layer parameterizations are the ones that showed the best performance in terms of wind power flux, wind speed and direction simulations. This model optimisation allowed a significant reduction of the wind power flux, wind speed and direction simulations errors and, specifically for offshore areas, wind power flux, wind speed and direction simulations more consistent with in situ wind measurements than data obtained from satellites, which is a very valuable and interesting achievement. This work also revealed that future anthropogenic climate changes can negatively impact future European wind energy resource, due to tendencies towards a reduction in future wind speeds especially by the end of the current century and under stronger radiative forcing conditions.

A framework for programming sensor networks with scheduling and resource-sharing optimizations

Several projects in the recent past have aimed at promoting Wireless Sensor Networks as an infrastructure technology, where several independent users can submit applications that execute concurrently across the network. Concurrent multiple applications cause significant energy-usage overhead on sensor nodes, that cannot be eliminated by traditional schemes optimized for single-application scenarios. In this paper, we outline two main optimization techniques for reducing power consumption across applications. First, we describe a compiler based approach that identifies redundant sensing requests across applications and eliminates those. Second, we cluster the radio transmissions together by concatenating packets from independent applications based on Rate-Harmonized Scheduling.

Constrained Consumption Shifting Management in the Distributed Energy Resources Scheduling Considering Demand Response

Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.

Missing value imputation in longitudinal measures of alcohol consumption

Attrition in longitudinal studies can lead to biased results. The study is motivated by the unexpected observation that alcohol consumption decreased despite increased availability, which may be due to sample attrition of heavy drinkers. Several imputation methods have been proposed, but rarely compared in longitudinal studies of alcohol consumption. The imputation of consumption level measurements is computationally particularly challenging due to alcohol consumption being a semi-continuous variable (dichotomous drinking status and continuous volume among drinkers), and the non-normality of data in the continuous part. Data come from a longitudinal study in Denmark with four waves (2003-2006) and 1771 individuals at baseline. Five techniques for missing data are compared: Last value carried forward (LVCF) was used as a single, and Hotdeck, Heckman modelling, multivariate imputation by chained equations (MICE), and a Bayesian approach as multiple imputation methods. Predictive mean matching was used to account for non-normality, where instead of imputing regression estimates, "real" observed values from similar cases are imputed. Methods were also compared by means of a simulated dataset. The simulation showed that the Bayesian approach yielded the most unbiased estimates for imputation. The finding of no increase in consumption levels despite a higher availability remained unaltered. Copyright (C) 2011 John Wiley & Sons, Ltd.

Excessive alcohol consumption in young men: is there an association with their earlier family situation? A baseline-analysis of the C-SURF-study (Cohort Study on Substance Use Risk Factors).

AIMS: To determine whether parental factors earlier in life (parenting, single parent family, parental substance use problem) are associated with patterns of alcohol consumption among young men in Switzerland. METHODS: This analysis of a population based sample from the Cohort Study on Substance Use Risk Factors (C-SURF) included 5,990 young men (mean age 19.51 years), all attending a mandatory recruitment process for the army. These conscripts reported on parental monitoring and rule-setting, parental behaviour and family structure. The alcohol use pattern was assessed through abstention, risky single occasion drinking (RSOD), volume drinking and dependence. Furthermore, the impact of age, family socio-economic status, educational level of the parents, language region and civil status was analysed. RESULTS: A parental substance use problem was positively associated with volume drinking and alcohol dependence in young Swiss men. Active parenting corresponded negatively with RSOD, volume drinking and alcohol dependence. Single parent family was not associated with a different alcohol consumption pattern compared to standard family. CONCLUSION: Parental influences earlier in life such as active parenting (monitoring, rule-setting and knowing the whereabouts) and perceived parental substance use problem are associated with alcohol drinking behaviour in young male adults. Therefore, health professionals should stress the importance of active parenting and parental substance use prevention in alcohol prevention strategies.

A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance.

Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and β-cell dysfunction but have contributed little to the understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways might be uncovered by accounting for differences in body mass index (BMI) and potential interactions between BMI and genetic variants. We applied a joint meta-analysis approach to test associations with fasting insulin and glucose on a genome-wide scale. We present six previously unknown loci associated with fasting insulin at P < 5 × 10(-8) in combined discovery and follow-up analyses of 52 studies comprising up to 96,496 non-diabetic individuals. Risk variants were associated with higher triglyceride and lower high-density lipoprotein (HDL) cholesterol levels, suggesting a role for these loci in insulin resistance pathways. The discovery of these loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.

Alcohol consumption in late adolescence and early adulthood - where is the problem?

Risky single-occasion drinking (RSOD) is more common in late adolescence and early adulthood (approximately between the ages of 16 and 30) than in any other period in life. This is also the age when young people in Switzerland and many other European countries are legally allowed to buy and drink alcohol, but they usually do not yet have adult responsibilities. This paper reviews evidence from the international literature and provides examples of studies conducted in Switzerland demonstrating that (a) RSOD is by far most prevalent on Saturday evenings followed by Friday evenings, usually because young people go out and do not have any work or study responsibilities the next day; (b) RSOD results from drinking in private before going out ("predrinking") and accelerating the pace of drinking (i.e. increasing the number of drinks consumed per hour); (c) RSOD is often not accidental but purposeful,. to seek excitement, to have fun and to feel the effects of alcohol; (d) RSOD occurs predominantly outside the home, mostly in bars, pubs, discos or at special events and festivals; (e) RSOD often results in intended and unintended injuries and other acute consequences, which are leading risk factors for mortality and morbidity in this age group. Effective prevention strategies should include attempts to reduce opportunities to engage in heavy drinking as well as strategies to reduce its harmful consequences.

Alcohol drinking, the metabolic syndrome and diabetes in a population with high mean alcohol consumption.

AIMS: To investigate the relationship of alcohol consumption with the metabolic syndrome and diabetes in a population-based study with high mean alcohol consumption. Few data exist on these conditions in high-risk drinkers. METHODS: In 6172 adults aged 35-75 years, alcohol consumption was categorized as 0, 1-6, 7-13, 14-20, 21-27, 28-34 and ≥ 35 drinks/week or as non-drinkers (0), low-risk (1-13), medium-to-high-risk (14-34) and very-high-risk (≥ 35) drinkers. Alcohol consumption was objectively confirmed by biochemical tests. In multivariate analysis, we assessed the relationship of alcohol consumption with adjusted prevalence of the metabolic syndrome, diabetes and insulin resistance, determined with the homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS: Seventy-three per cent of participants consumed alcohol, 16% were medium-to-high-risk drinkers and 2% very-high-risk drinkers. In multivariate analysis, the prevalence of the metabolic syndrome, diabetes and mean HOMA-IR decreased with low-risk drinking and increased with high-risk drinking. Adjusted prevalence of the metabolic syndrome was 24% in non-drinkers, 19% in low-risk (P<0.001 vs. non-drinkers), 20% in medium-to-high-risk and 29% in very-high-risk drinkers (P=0.005 vs. low-risk). Adjusted prevalence of diabetes was 6.0% in non-drinkers, 3.6% in low-risk (P<0.001 vs. non-drinkers), 3.8% in medium-to-high-risk and 6.7% in very-high-risk drinkers (P=0.046 vs. low-risk). Adjusted HOMA-IR was 2.47 in non-drinkers, 2.14 in low-risk (P<0.001 vs. non-drinkers), 2.27 in medium-to-high-risk and 2.53 in very-high-risk drinkers (P=0.04 vs. low-risk). These relationships did not differ according to beverage types. CONCLUSIONS: Alcohol has a U-shaped relationship with the metabolic syndrome, diabetes and HOMA-IR, without differences between beverage types.