GLA Economics estimates of London's exports by sector over time based on the UK level service exports from the Pink Book 2014, HM Revenue and Customs (HMRC) goods exports and GLA Economics modelling. Additional data sources to inform GLA Economics modelling include 'GVA per Workforce Job in London and the UK' and the 'London Business Survey 2014'.

GLA Economics produces long-term employment projections for London by sector and by borough. The methodology in the accompanying report explains the approach adopted. Links to the 2022 employment projections (latest, interim update) Borough projections Sector projections London labour market projections report Links to previous employment projections Provided below are links to the previous versions of GLA Economics’ employment projections, with breakdowns of the numbers (historic and projected) available by sector and by local authority. 2017 Borough projections, 1971-2050 Sector projections, 1971-2050 London projections of scenarios London labour market projections report 2016 Borough Projections, 1971-2041 Sector Projections, 1971-2041 London labour market projections report 2015 Borough [trend-based only], 1981-2036 Sector, 1984-2036 Working paper 67 2013 Borough, 1984-2036 Sector, 1984-2036 London labour market projections report 2011 Borough [trend-based only, data excludes self-employed], 1981-2036 Sector, 1984-2036 Working paper 51 2009 Borough, 2011-2036 Sector [based on SIC 1992], 1971-2031 Working paper 38

•GLA Economics has produced long-run projections of London’s employment since 2002. These projections are trend based and set out the long run path of employment considered most likely based on the historic data available at the time of construction. These are used within the GLA for planning to provide capacity to accommodate the longer-terms needs of the London economy. Given their importance to GLA policy planning, this note looks at how the GLA Economics’ employment projections have performed since 2002 and how this compares to projections from some other respected organisations. •Although GLA Economics’ employment projections are consistently below outturn, much of this is the result of upward revisions to historic employment data (which underpin the projections model). Further, the projections perform relatively well when looking at the projected annual growth rate and average annual error in relation to outturn, with the accuracy of the projections generally improving the longer the time period over which the estimates are analysed. •The revisions to historic employment data also drive much of the variability in the GLA Economics’ employment projections numbers over time. However, and by design, the revised projections are relatively consistent over time and average revisions between iterations in GLA Economics employment projections are relatively small.

GLA Demography has published 2016-based employment-led projections for London which provide population projections which are consistent with the employment projection scenarios published by GLA Economics. However, this should be viewed as an experimental output which may not be updated in the future. In addition to the raw data for this set of population projections, we have also produced a methodology document which explains how these projections were produced. GLA Demography produces a variety of different types of population projections in order to meet the needs of a wide range of users. To see our full range of population projections, please visit our Population and household projections homepage.

Origin and destination of London public transport journeys by time of day and day of week. This dataset is included in the Greater London Authority's Night Time Observatory. Click here to find out more.

These slides begin to explore the potential impacts of the transition to a net-zero carbon and circular economy on different industry groups and workers in London. It should be noted that this analysis has not been based on London’s emissions as reported through the London Energy and Greenhouse Gas Inventory (LEGGI). Instead we use UK level data on emissions and energy consumption by industry group and apportion to a London level using regional employment estimates. This is an imperfect approach, intended to provide a first approximation of trends by industry group based on available data. The findings provide an initial insight but should be treated with caution. Main findings from the analysis Among the main findings, the analysis shows that by industry group: London apportioned GHG emissions are highest in Transport & Storage, followed by Electricity & Gas and Manufacturing High-emitting industry groups tend to account for a relatively small share of employment among London residents Some (but not all) high-emitting industry groups have seen a recent increase in GHG emissions at the UK level and employment at the London level Jobs in high-emitting industry groups tend to be spatially concentrated in different parts of London What are the main assumptions behind these findings? In the absence of sub-national estimates being available by industry group, we have apportioned UK GHG emissions and energy consumption to London using (resident based) ONS Annual Population Survey data. This allows us to look at trends using Standard Industrial Classification (SIC 2007) groups. This approach assumes that GHG emissions per worker and energy consumption per worker are the same within industries across the country. In reality, the occupational structure and carbon intensity of an industry is likely to vary across regions. It also reflects resident, not workplace, employment patterns. Our London apportion estimates also exclude GHG emissions from consumer expenditure and only covers direct emissions by industry. Further analysis of indirect emissions across supply chains could be of value when considering the longer-term challenges faced by the economy as part of this transition.

The main aim of this work is to develop a set of high level macro economic scenarios for the medium-term (to the end of 2022) and for the long-term (to 2030) in order to inform the development of recovery strategies in London, reflecting unprecedented uncertainty on the economic outlook. The primary scenario dimensions include Effectiveness/nature of public health response and Effectiveness/impact of economic support measures. Other scenario dimensions include: Brexit and migration; International economic context; Technology and innovation; Financial climate; Political economy; Economic Geography and GHG emissions. This is an agile project - GLA Economics will continue to track actual data in order to review the assessment of the likelihood of alternative scenario outcomes. Successive updates will be released when they become available for the benefit of external stakeholders in tackling the COVID-19 crisis.

GLA Economics calculations of GVA per workforce job, by Section and Division of the UK Standard Industrial Classification 2007 (SIC07), for London and UK, attributable to the activities of the workforce. Regional data on GVA per Workforce Job by sector is also provided.

The ethnic group projections are produced for London borough and provide detailed projection by 17 ethnic groups of London’s future population. Two variants are produced: one consistent with the 2016-based central trend projection, and one consistent with the 2016-based housing-led projection. The 2016-based projections remain the most recent set of GLA ethnic group projections.