We propose a programme of research leading to the establishment of a new methodology for surveying household energy use nationally, to complement existing methods (e.g., the English Housing Survey and regional equivalents), which leverages the rollout of Smart Meters to achieve cost-effective, detailed understanding of energy use behaviours. The key enablers of this new methodology are: 1) the Smart Meters themselves, 2) advances in semi-supervised disaggregation methods which can infer the behaviours that result in energy use, and 3) other wireless sensors placed in some households to bootstrap the disaggregation methods. The output will be twofold: a validated scalable novel survey method suitable for national rollout, providing significant additional data on energy consumption in UK homes; and 2) an assessment of which variables can be effectively surveyed with this method.

The aim of this project is to visualise information from climate change models so that it can be displayed on an internet "game" called the the 2050 Global Calculator. The aim of the Global Calculator is to energise and inform discussion about energy and climate choices in the lead-up to the UNFCCC climate negotiations in Paris in 2015. The Global Calculator lets you make decisions about the energy system in 2050: should we use lots of nuclear power, or insulate our houses, or become vegetarian? The impact of these choices is then shown in terms of carbon emissions and the effect on the global climate. In the early stages of constructing the Global Calculator, we have already learnt a lot about the different expectations of climate scientists and of policy-makers from the Department for Energy and Climate Change. The target audience for the web tool is businesspeople, who will probably have different expectations again. So what we want to do is to use the Global Calculator to demonstrate those differences, and work towards finding a system that will help all of us to communicate better. That means helping climate scientists design experiments that give answers that are directly relevant for real-world decisions, and helping decision-makers to understand the limits of climate information, so they don't ask for the impossible. Providing a forum for feedback and constructive discussion, by starting this conversation around the Global Calculator, will improve the use of climate information in business and policy.

In this proposal we aim to work with our partner the UK Intellectual Property Office (IPO) to gather evidence on the extent of recourse to patent protection in the UK economy, the use of patents by firms and on the strategies being used by firms to manage their IP and circumvent the problems caused by overlapping patent rights or 'patent thickets'. We bring new academic thinking on these issues (in the US and UK) to bear on a small scale survey where the user community is involved in generating and gathering the data needed by them. By doing this we will be able to plug important evidentiary gaps about the recourse to patenting for innovative firms and also the use of patents though licensing and cross-licensing in the UK-wide economy. In addition a detailed survey of UK IP management practices based on similar surveys conducted in the US will enable a deeper understanding of the patent thicket question as well the measures UK firms are taking to gain 'freedom to operate'. We expect that this understanding of IP management practices will be a valuable input in IPOs training programs to raise awareness in small and medium firms and can also inform IP policy in the UK.

This Knowledge Exchange fellowship has two strands i. The Engagement focus aims to increase government use of academic work, by increased engagement between BIS and NIESR through a) a series of seminars for policy people, b) review of processes for government research and data management, and c) improved communication of the policy perspective. ii. The Research focus aims to undertake analysis of firm level data and explore the potential to extend the findings in the literature in order a) to gain greater impact on policy development from academic knowledge, and b) identify and develop potential for further policy relevant research from these areas of NIESR expertise. The Engagement focus of the project contains different elements: a. Seminars. NIESR has agreed to arrange a series of 4 seminars on BIS policy topics over the 12 months of the fellowship. These will involve experts from the academic community, including ESRC centres such as SKOPE, and will be open to government officials from BIS and other departments. The topics are likely to include areas such as macro-economic projections, migration and the labour market, and sources of productivity gain. b. Research and data processes. The opportunity of the Fellowship will be used to improve academic links with government processes for research and data where possible. The aim is to develop and provide greater feedback to academic bidders on the features of weaker bids, and how to strengthen them. c. Policy context. As well as policy relevant seminars, other steps will be taken to ensure that BIS priorities are conveyed to the academic community. The approach will be to arrange a workshop for academics, hosted by NIESR, and invite policy leads from government to provide feedback on what has worked for them. The Research focus will use firm-level micro-data to explore the relation between the dynamic economy (firms closing and opening, growing and contracting, improving and declining) and productivity, the labour market, and one or more of skills, innovation, high growth firms, sectors and clusters. The approach is to explore the potential of these data for greater insight and impact, rather than direct data analysis - in recognition of the challenges presented by the patchy documentation, and inconsistent data records. The starting point is the finding that the great majority of productivity gain arises from 'external restructuring' of firms or plants (80-90% of Total Factor Productivity according to Disney et al (2003), and greater according to Harris and Moffat (2012). At first sight this seems surprising - it suggests that little productivity gain occurs within existing firms or plants. The implication is sometimes drawn that economic churn amongst firms is the route for growth rather than improvement within firms. The picture could in fact be different. The empirical literature appears to focus mainly on churn among plants rather than firms and there is little detail on how much of the gain occurs between plants but within firms, and how much between firms. This is the first question that will be explored. The second stage will consider how this decomposition varies over time, under different macro-economic circumstances. The literature suggests there is some but not much variation. One would expect the components of change to differ at times of growth from times of contraction or recession. The third stage will assess the feasibility of separating the decomposition by firm size, as churn is likely to operate rather differently for small firms than for middle or larger ones. Policy on investment in areas such as skills or innovation will be informed and influenced by the findings. The fourth stage will explore the potential for future work in one or more policy areas - skills and training (building on work by Haskel et al 2003, Dearden et al 2005, and Galindo-Rueda et al 2005), in innovation, or employment.

Efforts to reduce the emissions from car travel have been hampered by a lack of specific information on car ownership and use. In 2010, the Department for Transport released a dataset containing annual MOT test records for cars from 2005 onwards, with regular updates promised. By providing relatively comprehensive information about British car ownership and use, this dataset provides a key opportunity to address a number of issues in transport and energy debates. For the first time precise links can be made between car use and car type, and changes in use over space and time can be examined on a relatively complete basis. When combined with a wealth of other existing data sets (not least the new information from the 2011 Census), a range of new and important insights should emerge. Having already worked together as a project team to scope the use of this data in a small EPSRC-funded study in 2011, we now propose to use it as a platform upon which to develop a set of interlinked modelling and analysis tasks using multiple sources of vehicle-specific and area-based data. A set of interdependent workpackages will span three years to investigate spatial and temporal differences in car ownership and use, the determinants of those differences, and how levels may change over time and in response to various policy measures. The relationships between car ownership, car use, fuel use and vehicle emissions, and the demographic, economic, infrastructural and socio-cultural factors influencing these will be tested mathematically using spatial statistics, regression modelling and scenario analyses. Linkages will also be made with spatial patterns of domestic gas and electricity usage in order to understand relationships within and between these end-user energy demands. The new analysis capability will be tested through case study evaluation of local transport policies. By enabling car ownership and use to be examined at relatively fine spatial and temporal scales, and via techniques to identify areas sharing important 'background' characteristics, it should be possible to answer key questions for sustainable transport policies such as, what difference to car ownership and use have particular policies achieved (compared with areas where these policies were not in place)? It will also be able to calculate figures for fuel use and emissions to contribute to the development of policies specifically targeted at the most energy intensive or polluting drivers or localities. We will also be able to link energy use from cars, with domestic energy usage through household electricity and gas. This will allow us to build up a much better picture of energy and carbon footprints across the country. When linked to patterns of income, multiple deprivation and other socio-economic factors, there will be insights for the design of much more effective climate and energy policies, and to ensure that the burden of these is borne equitably. The project will be supported by an Applied Statistics Expert Panel, and includes provision for workshops with key stakeholders to help shape the work. The project will also help develop a specification for a possible web-based tool to enable a wide community of users to undertake their own analysis on these sorts of issues, using the data and tools that we develop. In order to achieve our goals, we will develop methods to overcome the challenges of merging a range of important but disparate datasets, based on varying spatial, temporal and other characteristics, and subject to varying issues of data protection and sensitivity. Our scoping study demonstrated that there are very significant technical challenges to be overcome in working with datasets of this size and nature, and a wide range of disciplines may be able to learn from this work. The analysis frameworks and the new scientific understanding delivered will be the important legacies of this project.