A dwelling-level investigation into the physical and socio-economic drivers of domestic energy consumption in England

The UK Government's Department for Energy and Climate Change has been investigating the feasibility of developing a national energy efficiency data framework covering both domestic and non-domestic buildings. Working closely with the Energy Saving Trust and energy suppliers, the aim is to develop a data framework to monitor changes in energy efficiency, develop and evaluate programmes and improve information available to consumers. Key applications of the framework are to understand trends in built stock energy use, identify drivers and evaluate the success of different policies. For energy suppliers, it could identify what energy uses are growing, in which sectors and why. This would help with market segmentation and the design of products. For building professionals, it could supplement energy audits and modelling of end-use consumption with real data and support the generation of accurate and comprehensive benchmarks. This paper critically examines the results of the first phase of work to construct a national energy efficiency data-framework for the domestic sector focusing on two specific issues: (a) drivers of domestic energy consumption in terms of the physical nature of the dwellings and socio-economic characteristics of occupants and (b) the impact of energy efficiency measures on energy consumption.

Real estate markets and the macroeconomy: a dynamic coherence framework

This paper analyzes the dynamic interactions between real estate markets, in the US and the UK and their macroeconomic environments. We apply a new approach based on a dynamic coherence function (DCF) to study these interactions bringing together different real estate markets (the securitized market, the commercial market and the residential market). The results suggest that there is a common trend that drives the different real estate markets in the UK and the US, particularly in the long run, since they have a similar shape of the DCF. We also find that, in the US, wealth and housing expenditure channels are very conductive during real estate crises. However, in the UK, only the wealth effect is significant as a transmission channel during real estate market downturns. In addition, real estate markets in the UK and the US react differently to institutional shocks. This brings some insights on the conduct of monetary policy in order to avoid disturbances in real estate markets.

A new scenario framework for climate change research: background, process, and future directions

The scientific community is developing new global, regional, and sectoral scenarios to facilitate interdisciplinary research and assessment to explore the range of possible future climates and related physical changes that could pose risks to human and natural systems; how these changes could interact with social, economic, and environmental development pathways; the degree to which mitigation and adaptation policies can avoid and reduce risks; the costs and benefits of various policy mixes; residual impacts under alternative pathways; and the relationship of future climate change and adaptation and mitigation policy responses with sustainable development. This paper provides the background to and process of developing the conceptual framework for these scenarios, as described in the three subsequent papers in this Special Issue (Van Vuuren et al.; O’Neill et al.; Kriegler et al.). The paper also discusses research needs to further develop and apply this framework. A key goal of the current framework design and its future development is to facilitate the collaboration of climate change researchers from a broad range of perspectives and disciplines to develop policy- and decision-relevant scenarios and explore the challenges and opportunities human and natural systems could face with additional climate change.

Economic forecasting: some lessons from recent research

This paper describes some recent advances and contributions to our understanding of economic forecasting. The framework we develop helps explain the findings of forecasting competitions and the prevalence of forecast failure. It constitutes a general theoretical background against which recent results can be judged. We compare this framework to a previous formulation, which was silent on the very issues of most concern to the forecaster. We describe a number of aspects which it illuminates, and draw out the implications for model selection. Finally, we discuss the areas where research remains needed to clarify empirical findings which lack theoretical explanations.

CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

Treatment of child anxiety in the context of maternal anxiety disorder: a randomised controlled trial and economic analysis

Background Cognitive–behavioural therapy (CBT) for childhood anxiety disorders is associated with modest outcomes in the context of parental anxiety disorder. Objectives This study evaluated whether or not the outcome of CBT for children with anxiety disorders in the context of maternal anxiety disorders is improved by the addition of (i) treatment of maternal anxiety disorders, or (ii) treatment focused on maternal responses. The incremental cost-effectiveness of the additional treatments was also evaluated. Design Participants were randomised to receive (i) child cognitive–behavioural therapy (CCBT); (ii) CCBT with CBT to target maternal anxiety disorders [CCBT + maternal cognitive–behavioural therapy (MCBT)]; or (iii) CCBT with an intervention to target mother–child interactions (MCIs) (CCBT + MCI). Setting A NHS university clinic in Berkshire, UK. Participants Two hundred and eleven children with a primary anxiety disorder, whose mothers also had an anxiety disorder. Interventions All families received eight sessions of individual CCBT. Mothers in the CCBT + MCBT arm also received eight sessions of CBT targeting their own anxiety disorders. Mothers in the MCI arm received 10 sessions targeting maternal parenting cognitions and behaviours. Non-specific interventions were delivered to balance groups for therapist contact. Main outcome measures Primary clinical outcomes were the child’s primary anxiety disorder status and degree of improvement at the end of treatment. Follow-up assessments were conducted at 6 and 12 months. Outcomes in the economic analyses were identified and measured using estimated quality-adjusted life-years (QALYs). QALYS were combined with treatment, health and social care costs and presented within an incremental cost–utility analysis framework with associated uncertainty. Results MCBT was associated with significant short-term improvement in maternal anxiety; however, after children had received CCBT, group differences were no longer apparent. CCBT + MCI was associated with a reduction in maternal overinvolvement and more confident expectations of the child. However, neither CCBT + MCBT nor CCBT + MCI conferred a significant post-treatment benefit over CCBT in terms of child anxiety disorder diagnoses [adjusted risk ratio (RR) 1.18, 95% confidence interval (CI) 0.87 to 1.62, p = 0.29; adjusted RR CCBT + MCI vs. control: adjusted RR 1.22, 95% CI 0.90 to 1.67, p = 0.20, respectively] or global improvement ratings (adjusted RR 1.25, 95% CI 1.00 to 1.59, p = 0.05; adjusted RR 1.20, 95% CI 0.95 to 1.53, p = 0.13). CCBT + MCI outperformed CCBT on some secondary outcome measures. Furthermore, primary economic analyses suggested that, at commonly accepted thresholds of cost-effectiveness, the probability that CCBT + MCI will be cost-effective in comparison with CCBT (plus non-specific interventions) is about 75%. Conclusions Good outcomes were achieved for children and their mothers across treatment conditions. There was no evidence of a benefit to child outcome of supplementing CCBT with either intervention focusing on maternal anxiety disorder or maternal cognitions and behaviours. However, supplementing CCBT with treatment that targeted maternal cognitions and behaviours represented a cost-effective use of resources, although the high percentage of missing data on some economic variables is a shortcoming. Future work should consider whether or not effects of the adjunct interventions are enhanced in particular contexts. The economic findings highlight the utility of considering the use of a broad range of services when evaluating interventions with this client group. Trial registration Current Controlled Trials ISRCTN19762288. Funding This trial was funded by the Medical Research Council (MRC) and Berkshire Healthcare Foundation Trust and managed by the National Institute for Health Research (NIHR) on behalf of the MRC–NIHR partnership (09/800/17) and will be published in full in Health Technology Assessment; Vol. 19, No. 38.

Towards a meta-analysis and toolkit for port-related socio-economic impacts: a review of socio-economic impact studies conducted for seaports

Port authorities increasingly need to communicate with a variety of external stakeholders in order to maintain and strengthen the societal acceptance of seaport activities. The availability of socio-economic impact studies on port authority and regional development agency websites has often made this information accessible to the public at large. However, the differences in methodologies adopted, in terms of selecting, defining and measuring various types of socio-economic impacts, sometimes lead to misconceptions as well as misleading comparisons across ports within and between regions. In this paper, we suggest guidelines for the design and application of a potential best practice from an interregional perspective (UK, France and Belgium), based on research in the framework of a European Commission co-funded project, ‘IMPACTE’. The paper also aims to develop guidelines for comparing the socio-economic impacts of ports across regional and national borders and discusses the development of a European port economic impact measurement toolkit. We analyse a sample of 33 recent socio-economic impact assessment reports in terms of methodologies adopted and types of impacts measured. The review shows a great diversity among these studies, leading to important differences between the impacts of port activity communicated to stakeholders.

Marine protected areas in artisanal fisheries: a spatial bio-economic model based on observations in Costa Rica and Tanzania

In many lower-income countries, the establishment of marine protected areas (MPAs) involves significant opportunity costs for artisanal fishers, reflected in changes in how they allocate their labor in response to the MPA. The resource economics literature rarely addresses such labor allocation decisions of artisanal fishers and how, in turn, these contribute to the impact of MPAs on fish stocks, yield, and income. This paper develops a spatial bio-economic model of a fishery adjacent to a village of people who allocate their labor between fishing and on-shore wage opportunities to establish a spatial Nash equilibrium at a steady state fish stock in response to various locations for no-take zone MPAs and managed access MPAs. Villagers’ fishing location decisions are based on distance costs, fishing returns, and wages. Here, the MPA location determines its impact on fish stocks, fish yield, and villager income due to distance costs, congestion, and fish dispersal. Incorporating wage labor opportunities into the framework allows examination of the MPA’s impact on rural incomes, with results determining that win-wins between yield and stocks occur in very different MPA locations than do win-wins between income and stocks. Similarly, villagers in a high-wage setting face a lower burden from MPAs than do those in low-wage settings. Motivated by issues of central importance in Tanzania and Costa Rica, we impose various policies on this fishery – location specific no-take zones, increasing on-shore wages, and restricting MPA access to a subset of villagers – to analyze the impact of an MPA on fish stocks and rural incomes in such settings.

Measuring the economic value of pollination services: principles, evidence and knowledge gaps

An increasing degree of attention is being given to the ecosystem services which insect pollinators supply, and the economic value of these services. Recent research suggests that a range of factors are contributing to a global decline in pollination services, which are often used as a “headline” ecosystem service in terms of communicating the concept of ecosystem services, and how this ties peoples׳ well-being to the condition of ecosystems and the biodiversity found therein. Our paper offers a conceptual framework for measuring the economic value of changes in insect pollinator populations, and then reviews what evidence exists on the empirical magnitude of these values (both market and non-market). This allows us to highlight where the largest gaps in knowledge are, where the greatest conceptual and empirical challenges remain, and where research is most needed.

A three-fold framework for understanding HRM practices in South-Eastern European SMEs

Purpose We study particular structural and organisational factors affecting the formality of human resource management (HRM) practices in small and medium-sized enterprises (SMEs) in South-Eastern European (SEE) post-communist countries, in particular Serbia, Romania, Bulgaria and the Former Yugoslav Republic of Macedonia (FYROM) in order to understand the antecedents of formalization in such settings. Design/methodology/approach Adopting a quantitative approach, this study analyses data gathered through a survey of 168 managers of SMEs from throughout the region. Findings The results show that HRM in SMEs in the SEE region can be understood through a three-fold framework which includes: degree of internationalisation of SMEs, sector of SMEs and organisational size of SMEs. These three factors positively affect the level of HRM formalisation in SEE SMEs. These findings are further attributed to the particular political and economic context of the post-communist SEE region. Research limitations/implications Although specific criteria were set for SME selection, we do not suggest that the study reflects a representative picture of the SEE region because we used a purposive sampling methodology. Practical implications This article provides useful insights into the factors which influence HRM in SMEs in a particular context. The findings can help business owners and managers understand how HRM can be applied in smaller organisations, particularly in post-communist SEE business contexts. Originality/value HRM in SMEs in this region has hardly been studied at all despite their importance. Therefore, this exploratory research seeks to expand knowledge relating to the application of HRM in SMEs in SEE countries which have their business environments dominated by different dynamics in comparison to western European ones.

Kazakhstan: long-term economic growth and the role of the oil sector

This study combines a narrative and modelling framework to analyse the development of Kazakhstan’s oil sector since its takeoff following separation from the USSR. As in the case of other emerging or transitional countries with large natural resource endowments, a key question is whether the exploitation of the natural resource is a benefit to longer term economic development: is it a curse, a blessing – or neither? Narrative evidence suggests that the establishment of good governance, in terms of institutions and policies, provides a background to sound long-term development, especially if combined with the development of sectors outside the natural resource sector, for example diversification into manufacturing and services, often through attracting FDI. The narrative is supported by econometric modelling of the relationship between domestic output, overseas output and exports of oil, which finds in favour of a sustained positive effect of oil exports on GDP. The model then provides a basis for projection of the growth in GDP given a consensus view of likely developments in the oil price.

A decision framework for considering climate change adaptation in biodiversity conservation planning

General principles of climate change adaptation for biodiversity have been formulated, but do not help prioritize actions. This is inhibiting their integration into conservation planning. We address this need with a decision framework that identifies and prioritizes actions to increase the adaptive capacity of species. The framework classifies species according to their current distribution and projected future climate space, as a basis for selecting appropriate decision trees. Decisions rely primarily on expert opinion, with additional information from quantitative models, where data are available. The framework considers in-situ management, followed by interventions at the landscape scale and finally translocation or ex-situ conservation. Synthesis and applications: From eight case studies, the key interventions identified for integrating climate change adaptation into conservation planning were local management and expansion of sites. We anticipate that, in combination with consideration of socio-economic and local factors, the decision framework will be a useful tool for conservation and natural resource managers to integrate adaptation measures into conservation plans.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise based upon data from a well known survey is also presented. Overall, theoretical and empirical results show promise for the feasible bias-corrected average forecast.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular it delivers a zero-limiting mean-squared error if the number of forecasts and the number of post-sample time periods is sufficiently large. We also develop a zero-mean test for the average bias. Monte-Carlo simulations are conducted to evaluate the performance of this new technique in finite samples. An empirical exercise, based upon data from well known surveys is also presented. Overall, these results show promise for the bias-corrected average forecast.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise, based upon data from a well known survey is also presented. Overall, these results show promise for the feasible bias-corrected average forecast.