ONS Economic Forum on the road Bristol
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The document provides an agenda and summaries for an ONS Economic Forum event in Bristol on October 25th. It includes welcome remarks, four presentations on ONS statistics and the UK/regional economies, and a Q&A session. Specifically, it will discuss ONS's role producing statistics, understanding the UK economy at national and regional levels, recent changes to ONS economic statistics from a regional perspective, and the economy of the West of England region.
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ONS Economic Forum on the road Bristol
- 1. ONS Economic Forum - Bristol 25 October Email: ONS.economic.forum@ons.gov.uk Twitter: @ONS #Econstats
- 2. Agenda Time Item Speaker 14:00 – 14:10 Welcome Dr Fiona Tolmie, Associate Dean – Learning, Teaching and the Student Experience 14:10 – 14:30 Office for National Statistics: statistics for the public good Richard Heys, Deputy Chief Economic Adviser 14:30 – 14:50 Understanding the UK economy Fiona Massey, Economic Adviser 14:50 – 15:10 Recent changes to ONS economic statistics – a regional perspective Richard Prothero, Head of Cities and Subregional Analysis, Public Policy Division, ONS 15:10 – 15:30 The Economy of the West of England Damian Whittard, Associate Head of Department, Accounting Economics & Finance 15:30 – 16:00 Question and answer session 16:00 – 17:00 Opportunity for networking
- 3. Welcome Dr Fiona Tolmie, Associate Dean – Learning, Teaching and the Student Experience, University of the West of England
- 4. Office for National Statistics: statistics for the public good Richard Heys – Deputy Chief Economist ONS
- 5. Who are we? • Economic, public policy & population statistics… • … but other Departments provide statistics too (e.g. energy, health) • Our responsibility is for coherence of system as a whole • Census provider in England and Wales • Newport (South Wales) and Titchfield (Southern England), with small London presence UK Statistics Authority Other government stats producers Office for National Statistics Office for Statistics Regulation
- 6. Our status and role • An independent statutory body • Operating at arm’s length from government as a non-ministerial department, reporting directly to the UK’s Parliaments and Assemblies • In law our objective is “promoting and safeguarding the production and publication of official statistics that serve the public good” • Explicit aim of responding promptly to emerging issues
- 7. Explaining the Economics you see in the News Contents 1) GDP 2) Inflation & interest rates 3) Trade 4) Productivity 5) Labour Market
- 8. …And a lot more… GDP growth Inflation (Un)employment Wages Trade Public finances Regional and country economic data Crime Births, deaths and marriages Population Migration Health and social care Personal income and wealth Well-being Environment …and more
- 9. A Halloween Question According to the 2011 Census, how many witches are there in the UK? a) 108 b) 573 c) 1,276 d) None – there are no witches in the UK
- 11. Economic Statistics Transformation Drivers • Users’ needs are changing • Economy evolving quickly • Opportunities from new data sources • ONS needs to be more open Bean Independent Review of UK Economic Statistics 2016 Johnson • UK Consumer Prices Stats – A Review 2015 Barker / Ridgeway • National Statistics Quality Review 2014 Best Practice • European System of Accounts 2010
- 12. Data is central to the decisions which affect our lives Data is now available from previously unimaginable sources We treat personal data confidentially and make sense of numbers for the public good Economic Statistics Transformation
- 13. Economic Statistics and Analysis Strategy Better measurement of the modern economy - the digital revolution Better measurement of services sector activities Better measurement of Gross Domestic Product Better measurement of Trade Better understanding of the productivity puzzle Better measurement of the Labour market Better measurement of prices Exploitation, interrogation and understanding of administrative data and other large datasets Better information below whole economy level
- 14. Relies on up-skilling our workforce • Increasing the number of professional analysts in our workforce by 50% from 2016 to 2021. • Significant increases in the number of economists in this period • Launch of the Data Science Campus in South Wales to develop new cutting edge skills and techniques.
- 15. The Circular Flow of GDP FirmsHouseholds Expenditure Output (Goods & Services) Labour and other Inputs Income
- 16. Three ways of calculating GDP Expenditure GDP(E) How much is spent Output GDP (O) How much is produced Income GDP (I) How much is earned
- 17. Three ways of calculating GDP Expenditure GDP(E) How much is spent - Use of Credit Card data - Retails Sales Output GDP (O) How much is produced - Use of VAT data - SERVCOM & Purchases Survey - Improving Deflators Income GDP (I) How much is earned - Use of PAYE & Self- Assessment data Improving the Supply-Use system
- 18. VAT – the benefits Current system Turnover is used as a proxy for gross value added Surveys sent to 45,000 firms each month Limited regional and local estimates Refreshing a survey takes time to get new data Future System VAT could give us GVA – in time… 2m returns each quarter Significant increase in granularity of estimates Admin data comes with historical data for rapid use
- 19. PAYE – the benefits Current system Average Weekly Earnings x employment = Salaries LFS sent to 40,000 households MWSS – 9,000 firms monthly Future System PAYE = Salaries + some pensions 65m records within 2 weeks, including 18m pension payments
- 20. The Importance of Services
- 21. Measuring services: SERVCOM • To reconcile Supply and Use across the economy requires not only measures of output/turnover but also products. • 114 x 114 matrix of industry sales by product supply for Supply tables, and industry intermediate consumption by product demand for Use tables • Historically economy dominated by industrial production and goods, reflected in detail of surveys for industrial production for EU e.g. PRODCOM • Economy has changed: services now 80% of GVA of which general government roughly a quarter – with industrial production 10% of GVA • Key recommendation of Bean review to address measurement of the service sector and disproportionate detail e.g. deflators and quality etc. • So propose counterpart to PRODCOM of SERVCOM
- 22. SERVCOM: Industry and Product No product factors available/appl ied Production Industries Services Industries Production Products Historical product factors applied to ABS question “Sales of non- industrial services” ITIS product factors and historical source product factors applied to ABS total industry sales Services Products PRODCOM sales data product factors applied to ABS sales of goods and industrial services Servcom To reconcile Supply and Use across the economy requires not only measures of output/turnover but also products. 114 x 114 matrix of industry sales by product supply for Supply tables, and industry intermediate consumption by product demand for Use tables
- 23. Answer: 1,276 people said they practised witchcraft in 2011
- 24. Understanding the UK economy Fiona Massey Head Economic Review, Economic Advice & Analysis Office for National Statistics economic.advice@ons.gov.uk ONS Regional Forum, 25 October 2017
- 25. Latest data from ONS • GDP • Economic wellbeing • Inflation • Employment • Productivity
- 26. GDP growth – Q3 released today
- 27. Consumer-focused services outpacing growth in other services
- 30. INFLATION
- 31. Inflation by import intensity of products in the CPIH basket Source: Office for National Statistics
- 32. Some international comparisons Source: Eurostat HICP 12-month growth rate, %
- 33. House prices, inflation and wages London SE & East CPIH, AWE Scotland, Wales, NE
- 34. Relative house price growth in Bristol
- 35. EMPLOYMENT
- 36. Employment headline figures • Employment Level (16+): 32.10 million, up 94,000 Rate (16-64): 75.1%, up 0.2 • Unemployment Level (16+): 1.44 million, down 52,000 Rate (16+): 4.3%, down 0.2 • Economic inactivity Level (16-64): 8.81 million, down 17,000 Rate (16-64): 21.4%, down 0.1
- 37. Longitudinal analysis – quarterly flows Source: Labour market economic commentary, October 2017, Labour Force Survey
- 38. Labour market flows since 2003
- 39. Real wages growth has been negative for last 6 months
- 40. PRODUCTIVITY
- 41. Productivity performance is a key weakness… 2015 = 100
- 42. The UK also performs weakly compared to other developed countries Source: Organisation for Economic Co-operation and Development, and Office for National Statistics calculations
- 43. With the vast majority of labour employed in below average productivity industries Financial services Legal and accounting
- 44. Main messages • GDP slow-down driven by services • Economic wellbeing dashboard captures wider measures of welfare • Import intensive goods are putting upward pressure on CPIH • Flows analysis of the labour market shows fall in dislocations from employment • Real wage growth negative for last 6 months • UK productivity weakness continues
- 45. Recent changes to ONS economic statistics – a regional perspective Richard Prothero, Head of Cities and Subregional Analysis, Public Policy Division, ONS
- 46. Devolution Programme A programme to improve ONS regional and local statistics. Regional Balanced GVA Regional & Sub-Regional Household Final Consumption Expenditure Regional Short Term Indicators Country and Regional Public Sector Finances Exports of Services Data Productivity Small Area Data Flexible Geographies. Investigating Uses of Administrative Data Regional Prices. Stakeholder Engagement
- 47. Labour Productivity (GVA per hour worked), 2015
- 48. 'City Regions' Labour Productivity GVA per hour worked, 2015
- 49. Labour Productivity by Industry 60 65 70 75 80 85 90 95 100 105 110 S, T - Other service activities, Activities of households R - Arts, entertainment and recreation. Q - Human health and social work activities. P - Education. O - Public administration and defence N - Administrative and support service activities. M - Professional, scientific and technical activities. L - Real estate activities. K - Financial and insurance activities. J - Information and communication. I - Accommodation and food service activities. H - Transportation and storage. G - Wholesale and retail trade; F - Construction. C – Manufacturing. A, B, D, and E – Non-manufacturing production Output per Hour - South West (UK=100), 2015
- 50. Distribution of firm level productivity (GVA per worker) in the non-financial business economy. • This Figure shows firm-level productivity data for the non- financial business economy for selected regions and countries for 2014. • It shows the proportion of firms at different levels of gross value added (GVA) per worker. • The distributions are skewed to the right, indicating that in all the regions there are fewer firms with high productivity levels than firms with lower productivity levels.
- 51. Labour Productivity by Size of Urban Area England and Wales = 100 GVA per worker of urban built-up areas classified by population size for the business economy in north and south of England, 2014
- 52. Net Fiscal Balance by Country and Region • In the financial year ending (FYE) 2016, all countries and regions except London, the South East and the East of England had a public sector net fiscal deficit, with the East of England showing a net fiscal surplus for the first time since FYE 2008. • This was the same when North Sea oil and gas revenue was allocated to regions on both geographic and population shares (the chart shows the geographic share). The difference between these two measures was negligible in 2015/16. -30 -20 -10 0 10 20 30 Northern Ireland Scotland Wales South West South East London East of England West Midlands East Midlands Yorkshire and The Humber North West North East Net Fiscal Balance (£bn) 2015/16
- 53. Net Fiscal Balance by Country and Region Chart shown is calculated on geographic basis – population share basis is also available.
- 54. Public Sector Revenue, by Country and Region, Source: ONS - Country and regional public sector finances
- 55. Public Sector Expenditure, by Country and Region Source: ONS - Country and regional public sector finances
- 57. Total value of service exports from NUTS1 areas by continent, Great Britain, 2015
- 58. Total value of service exports from NUTS1 areas by manufacturing industry • The EU was the largest destination for manufacturing services exports, receiving close to £5.0 billion, followed by Asia with £4.3 billion, and the Americas with £3.9 billion. • In the South West, the most important destination for manufacturing services exports was the Americas, generating 46% of the total South West manufacturing service exports.
- 59. House Prices by Area.
- 60. • .
- 61. Combined Authority Economic Indicators
- 62. ‘Balanced’ Regional GVA • In December 2017, a new ‘Balanced’ Regional GVA measure will be published. • UK GDP measured 3 different ways • Income; Output (or Production); Expenditure • Then balanced to provide a single ‘best’ estimate • Regional GVA measured 2 different ways • Income, Output (or Production). No expenditure measure due to inter-regional trade flows • These will be used to derive a single ‘best’ estimate
- 63. ‘Balanced’ Regional GVA • Balanced GVA should be more stable and reliable • Extra industry detail NUTS1: 80 industry breakdown NUTS2: 71 industry breakdown • All of these in both current prices and ‘real’ CVMs (chained volume measures). • The existing income components will be published down to local authority district level. • All regional GVA estimates (inc. small areas and derived productivity estimates) based on a consistent and coherent framework
- 64. Regional Short Term Indicators (RSTI) • Users tell us they need more timely, more granular and more flexible regional economic statistics • Devolution project established 2016 • Includes the development of Regional Short Indicators for England • ie produce quarterly real GVA growth estimates for the regions (NUTS1) of England • Addresses the user need for more timely regional economic statistics
- 66. The detail…. What’s happening when? • Mar 18: Peer review of historic series • Apr 18: User consultation (including the publication of the historic series) • Dec 18: First regular publication of experimental data • Ongoing quarterly publication ~90-110 days after the end of the quarter What’s the approach? • Using a combination of data sources: • Monthly Business Survey (MBS) • Retail Sales Inquiry (RSI) • Remaining industries covered by “other data sources” • Mainly direct volume measures eg Agriculture, Forestry & Fishing, Air Transport, Education • Including the use of VAT data • Using UK deflators Email: RSTI.Enquiries@ons.gov.uk ~60% ind coverage
- 67. The Economy of the West of England Presentation by Damian Whittard Associate Head of Department: AEF 25/10/2017
- 68. Introduction • High level overview of the West of England (WoE) economy: o Set the international and national context o Institutional re-ordering o Main characteristics o Potential challenges ̶ Productivity o UWE econometric study on the WoE productivity gap • UWE hosted event for academics and policy makers to improve understanding of regional economies (25th April, 2018) o Regional Studies Association: joint conference of the South West England and Wales Branches o Call for papers
- 69. International and National Context 1. International comparisons of productivity 2. UK GDP growth slowing i. Productivity growth flat 3. UK Productivity Puzzle i. Mismeasurement ii. Crisis related scarring iii. Forbearance and loose monetary policy iv. Loose labour markets v. Weak business investment 4. Brexit i. Weaker pound squeezing consumers ii. Uncertainty deterring business investment iii. Weaker pound boosts net exports iv. Transition to less trade-intensive economy v. Net inward migration to fall
- 70. West of England: Institutional Re-ordering • Changing institutional landscape • Metro Mayor, West of England Combined Authority • Bath and North East Somerset, Bristol and South Gloucestershire • Transport, housing and adult education • West of England Local Enterprise Partnership • This also includes North Somerset • Mayor of Bristol, Bristol City Council • Four Local Authorities • Bath and North East Somerset • Bristol • South Gloucestershire • North Somerset
- 71. West of England: Characteristics • Population 1.1 million o Estimated growth of 8.7% by 2025 • Relatively high level of productivity o £33,031 GVA per hour worked • Strong labour market o Employment rate 78% o Unemployment rate 3.8% • Highly educated workforce o 43.8 % of population with NVQ4 or above (GB 38.2%) o Four major universities o Ranked 2nd for first degree education employment • High value/innovative sectors o High value engineering o Creative and digital o Services ̶ Financial and professional services ̶ Higher education and public administration
- 72. • Slowing productivity growth • Inequalities across the region Wage Education Job creation Local deprivation • Sector specific skills shortage e.g. 61% of AE&A firms report a skills gap • Pressure on infrastructure Electrification of railway Housing Traffic congestion Digital connection • Housing affordability (£266,507) Between 8 and 10.5 times average earnings West of England: Challenges
- 73. An econometric study of the West of England LEP priority sectors (2014) By: Damian Whittard (UWE), Don Webber (UWE) and Nigel Jump (Strategic Economics)
- 74. Productivity study of WoE area (2014) • Explain differences in productivity between WoE and national control averages • LEP core cities • LEP southern areas • Focus on WoE LEP priority sectors • Advanced engineering and aerospace (AE&A) • Creative industries (CI) • Professional and legal services (P&LS) • High-tech (H-T) • Low carbon (LC) • Analysis 1998 – 2011 (two year averages) • ONS micro data (Annual Respondents Database, Annual Business Inquiry, Business Register and Employment Survey) • Approximately 25 million observations • Many coding challenges including SIC92 to SIC07, sector classifications & area identifiers
- 75. The productivity gap – LEP core cities
- 76. The productivity gap – Southern LEPs
- 77. Summary • Productivity benefit to business being in WoE compared to: • National control group • LEP core city regions • Southern LEP areas excluding Thames Valley • Strongest growth in productivity of all areas
- 78. 1 2 3 4 N 838,278 838,278 814,881 814,881 Spatial West of England 0.076*** 0.052*** 0.055*** 0.054*** (0.007) (0.007) (0.008) (0.008) City of London 0.410*** 0.333*** 0.298*** 0.295*** (0.013) (0.012) (0.014) (0.014) London (excluding 0.116*** 0.114*** 0.108*** 0.108*** city of) (0.003) (0.003) (0.004) (0.004) Industry Advanced engineering 0.629*** 0.661*** 0.649*** & aerospace (0.007) (0.009) (0.009) Creative industries 0.311*** 0.347*** 0.345*** (0.010) (0.013) (0.013) Professional and 0.573*** 0.661*** 0.662*** legal services (0.009) (0.011) (0.011) High-tech 1.302*** 0.957*** 0.950*** (0.005) (0.006) (0.006) Low Carbon 1.223*** 0.790*** 0.791*** (0.013) (0.012) (0.012) Firm Log (unit) -0.060*** -0.044*** -0.056*** -0.074*** (0.000) (0.000) (0.001) (0.001) Log (capital) 0.266*** 0.263*** (0.001) (0.002) Log (employment) 0.019*** (0.001) R2 0.025 0.098 0.233 0.233 F statistic 4861.30*** 10485.38*** 12625.69*** 12170.02*** Determinants of labour productivity (2010-11)
- 79. Summary • WoE LEP Priority sectors explain about a third of the productivity premium • Evidence of diseconomies of scale for multiple plant operations • Capital stock positive contribution to productivity nationally • Influence in West of England is less pronounced • Size of employers explain some of the benefit (influences varies over time)
- 80. 1 2 3 4 N 1,024,279 1,024,279 509,121 509,121 Spatial BANES -0.049*** -0.063*** -0.034* -0.032 (0.017) (0.016) (0.020) (0.020) Bristol 0.111*** 0.087*** 0.092*** 0.090*** (0.010) (0.010) (0.012) (0.012) North Somerset 0.039** 0.032** 0.039** 0.038* (0.016) (0.015) (0.020) (0.020) South Gloucestershire 0.118*** 0.077*** 0.058*** 0.055*** (0.014) (0.013) (0.018) (0.018) City of London 0.410*** 0.333*** 0.298*** 0.295*** (0.013) (0.012) (0.014) (0.014) London (excluding 0.116*** 0.114*** 0.108*** 0.108*** City of) (0.003) (0.003) (0.004) (0.004) Industry Advanced engineering 0.629*** 0.661*** 0.649*** & aerospace (0.007) (0.009) (0.009) Creative industries 0.311*** 0.347*** 0.344*** (0.010) (0.013) (0.013) Professional and 0.573*** 0.660*** 0.662*** legal services (0.009) (0.011) (0.011) High-tech 1.302*** 0.957*** 0.950*** (0.005) (0.006) (0.006) Low Carbon 1.223*** 0.790*** 0.791*** (0.013) (0.012) (0.012) Firm Log (unit) -0.075*** -0.057*** -0.056*** -0.074*** (0.000) (0.000) (0.001) (0.001) Log (capital) 0.266*** 0.263*** (0.001) (0.002) Log (employment) 0.019*** (0.001) R2 0.034 0.098 0.233 0.233 F statistic 3673.62*** 7871.56*** 9715.53*** 9565.63*** Sub-regional determinants of labour productivity (2010 -11)
- 81. Summary • Bristol and South Gloucestershire consistently contribute to WoE net benefit • The productivity premium is explained by: o South Gloucestershire - plants operating in priority sectors, capital stocks and size of workforce. o Bristol – priority sectors, other variables shed vary little insight • Over the period North Somerset increased their productivity faster than national average o Model provides little insight as to the drivers • BANES performed consistently below the national average o Much attributed to capital stock and scale economies in the workforce – possibly due to relative intensity of other industries
- 82. Priority sectors, capital stocks & employment: Different effects across the WoE (2010-11) 2010-11 WoE N 509,121 effect Spatial West of England 0.159*** (0.043) City of London 0.295*** (0.014) London (excluding City of) 0.108*** (0.004) Industry Advanced engineering & aerospace 0.646*** 0.079* (0.009) (0.044) Creative industries 0.344*** 0.028 (0.013) (0.065) Professional and legal services 0.663*** -0.013 (0.011) (0.076) High-tech 0.951*** -0.024 (0.006) (0.032) Low Carbon 0.790*** 0.053 (0.012) (0.062) Firm Log (unit) -0.074*** 0.026*** (0.001) (0.009) Log (capital) 0.263*** -0.015 (0.002) (0.010) Log (employment) 0.019*** -0.023*** (0.001) (0.008) R2 0.233 0.214 F statistic 7072.74*** 9492.58***
- 83. Summary (Time Series Analysis) • Industrial sectors are driving productivity growth o AE&A in the WoE consistently outperformed the national sector as a whole – on average by 10% o CI in the WoE started 17% below the national average but caught up to the national average o P&LS initially outperformed the national average but performance is now comparable • H-T and LC perform generally in line with the national average for the sector, but lower in some years • Multisite firms were less productive in WoE, but improved over time • Beneficial effects of larger capital stocks are potentially smaller in the WoE • Larger employers were generally more productive in WoE, but declining over time
- 84. Overall summary and recommendations • Evidence of diseconomies of scale for firms with multiplants o Provide support and guidance for managers of multi-plant facilities • Priority sectors are more productive nationally, however the performance regionally has been variable o Tailored support for individual sectors • Capital stock in the WoE has not been as productive as elsewhere o Further research needed (e.g. establish whether capital stock used less efficiently or just due to sector composition effects) • Large employers contribute to productivity differential in WoE o Support current and potential ‘anchor’ companies • Differences in productivity performance between constituent parts of WoE o Tailored support focussed on local needs that build on strengths and address weaknesses • Research has identified a number of important issues but only a limited part of the productivity differential is explained o Further research is required to make sure policy is focussed on the right levers
- 86. Help us improve the ONS website • In the first year we made 1500 changes to the ONS website • “Customise my data” is our biggest change and will enable users to customise datasets and browse by location • Signup to be involved in our user testing at www.surveymonkey.com/r/helptheons or email us userinsight@ons.gsi.gov.uk
Editor's Notes
- Intend to use growth rates first in selected industries, and develop levels in due course to inform balancing against other sources
- Intend to use growth rates first in selected industries, and develop levels in due course to inform balancing against other sources
- Servcom will cover the whole service sector (excluding banks and government) with a sample of 40,000 covering 274 industries Will ask for a breakdown of turnover into the service products from which it is generated, irrespective of classified industry Will complement new data from the purchases survey and measures of turnover and intermediate consumption from VAT returns. In particular Servcom will enable improved deflation and hence volume measures of output In the round new data sources will provide a profound improvement to Supply-Use and hence measurement of GDP more broadly. In the future extend coverage to ALLCOM.
- Good morning, I’m going to start by presentation on the UK economy - with an interesting fact about the audience reach of the ONS. Independent research has found that in August this year, the ONS was reaching an average audience of 5.6m people per day. This means that articles covering the statistical outputs of the ONS are being read in print and on-line media by a potentially very large audience – and a large part of that audience reach is driven by coverage of our economic statistics. The research tells us for example, that there is particularly high coverage for our inflation and GDP estimates, as might be expected given their significance for the economy. So, this gave me a good idea of what to cover in my presentation today. So I decided to focus on…
- These 5 areas: GDP Economic wellbeing Inflation Employment and Productivity Most of the charts I’m going to show you contain the latest data, apart from those on GDP which use Q2 data, as Q3 data was only available this morning. I can of course explain the changes to the data we see in the first estimate of GDP for Q3 as we go along. I hope you are happy with this choice, but please feel free to ask questions about other areas of the economy at the end of the presentation.
- So, my first chart is one which we use every month in our Monthly Economic Commentary. This is the lead chart in each commentary and the easiest way to find this material is by using the release calendar on the ONS website and look at the publications on the same day as the GDP estimates are published. I will use the format of this chart again later, so I will explain the bars and line: Bars = quarter on previous quarter growth, % (LHS) Line = quarter on previous year’s quarter, % (rolling annual average) (RHS) The main message from this chart is that we can see Q1 and Q2 are showing 0.3% quarterly growth; slowing from previous growth rates of around 0.5-0.6%. With the implication that the annual growth rate (line) has slowed from over 2% in 2014-2015 to 1.5% now. The figures for Q3 are : In terms of why the UK has seen a slow-down in its rate of economic growth – again we talk about this in our Monthly Economic Commentary released this morning: The statistician’s quote explains that…. So this complex mixture of data, gives us the current picture of GDP growth.
- A similar chart to this one, appears in today’s Monthly Economic Commentary, but this chart shows the different growth rates for consumer-focussed industries and the total index of services from Q2 2009 to Q2 2017. The message here is that consumer-focussed industries have grown slightly faster than the overall index, but that the rate of growth in recent quarters has been flattening. “Consumer-focused services” defined here include retail trade (Standard Industrial Classification (SIC) codes 45 and 47), food and beverage (SIC 56), publishing, audiovisual and broadcasting activities (SIC 58 to 60; including motion pictures), and arts, entertainment and recreation (SIC 90 to 93). Q3 figures show…
- In the next part of my presentation, I’m going to move a little Beyond GDP – which is a phrase which is used to describe a broader set of measures to aggregate GDP which particularly include more social and environmental data.
- Firstly, I’d like to introduce the economic Well-being dashboard – which has recently been introduced into the Economic Well-being release which is published a few working days after the Quarterly National Accounts. I think these data provide a useful info-graphic style dashboard which shows the trends in each variable, and most also have a green or red arrow showing whether they are moving in a positive or negative direction. The variables on the dashboard generally take a household or per capita perspective – e.g. on the top row we have GDP per head, net national disposable income per head, Real household disposable income per head, median equivalised disposable income and real household expenditure per head. There are also wealth characteristics in the dashboard on the 2nd row, and I’d like to draw your attention to the middle chart on the 2nd row - which is a behavioural question. This uses data from the Eurobarometer Consumer Survey, conducted by GFK on behalf of the European Commission and asks about people’s perceptions of their financial situation. As you can see both this measure and the one directly above it – RHDI per head are showing a fall over the latest quarter or year. So, again I recommend you have a look at the economic wellbeing release each quarter if you are interested in monitoring these wider measures of economic performance.
- Moving onto my last 2 topics: Inflation: As I’m sure you are aware, there has been relatively steady increase in the 12-month rate of CPI and CPIH from its very low base during 2015. Growth in CPIH is shown as the line on this chart. And the bars decompose the change in CPIH inflation into the different import-intensity brackets of the goods and services within the CPIH basket. To explain a bit further – the import intensity of goods and services in the basket have been calculated by using the ONS Input-Output analytical tables on a product by product basis. The import spending share by households of each product is then converted into the proportions of these products that are in the CPIH basket. The movement in the CPIH can then be broken down into the different import intensity groups of these products and services. So, on the chart – the main contribution to the CPIH comes actually from the 0-10% bracket of goods and services (dark blue) – which actually is mostly services as these are provided and consumed domestically. E.g. restaurants, hotels, insurance, education. But as I hope you can see, the orange sections (energy) and the light blue and green sections (30-40% and 40%) either put more upward or downward pressure on the overall inflation rate. Goods in these categories include food, household goods, and clothing. In recent months, there has been an increase in the contribution to overall CPIH from these sections compared to late 2016 when these sectors didn’t contribute much to CPIH at all. In future months I am hoping to extend this analysis of import intensity by including import spending on products in the supply chain and to use the more recent input output analytical tables relating to 2013 which were published a few months ago.
- The measure of inflation which is internationally comparable to other European countries, is the CPI index for the UK, as this fits the definition of the Harmonised Index of Consumer Prices (HICP). This chart uses Eurostat data to compare inflation rates across a selection of countries. The dotted line shows the UK rate of inflation, which as you can see was very similar to other EU countries during 2015 and 2016, as all countries experienced a pick-up in inflation from historically low bases. This is potentially related to the growth in oil prices and other commodities during this time. However, the UK has seen continued upward movement in the rate of CPI into 2017, whereas inflation in Germany, France and Italy has fallen back. As we saw in the previous slide, some of this upward pressure is coming from the higher import intensity product groups.
- This a chart that we included in our Prices Economic Commentary in August, looking at the relative house price growth since the economic downturn across various regions, compared with AWE regular pay growth and CPIH. As you can see the regions all experienced a dip in average house prices between end of 2007 and 2009, when some regions and London in particular began to recover fairly strongly. So by the middle of 2017, London, SE and SW had outpaced growth in wages and inflation since the downturn, and the other regions shown here had mostly regained their levels from 2007, but had grown less quickly than inflation and wages.
- And this is the equivalent chart, focussing on the SW and Bristol average house prices, and the same line for AWE regular pay and CPIH. Here, you can see the house price recovery has been stronger in the City of Bristol than the SW as a whole, although average prices for Bristol have outstripped wages and prices by around 20% - by August 2017 bristol house prices were 40% higher than the pre-downturn peak, while national average wages and prices are around 20% higher.
- 3 months to August 2017
- This chart is an interactive graphic from the latest October Labour market economic commentary, looking at the flow of workers between quarter 1 and quarter 2 2017. This chart shows estimated gross flows, that is, the total inflow or outflow for working-age employment, unemployment and inactivity from one calendar quarter to the next. The period covers January to March 2017 (Quarter 1) and April to June 2017 (Quarter 2). Approximately 3.22 million people move across the labour market either by moving from one pool to another or changing employment every quarter. More people left inactivity (937,000) than any other stock. The number of people who moved from inactivity to employment was 540,000. This was higher than those who moved from unemployment to employment, which was 439,000. Comparing these gross flows with the published quarterly changes in the headline Labour Force Survey aggregates reveals how substantial the underlying movements hidden behind these values are. Note: Stocks for January to March 2017 and April to June 2017 may not equal the published figures due to attrition and changes in working age population.
- This chart compares four-quarter moving average flows as a percentage of working-age population since April to June 2003 with the latest available period (April to June 2017). In the three months to June 2017, on average 459,000 people (1.12% of the working age population) moved from unemployment to employment every three months, whereas 290,000 people (0.70% of working age population) moved from employment to unemployment, the lowest since the earliest comparable period in 2001. Flows from employment to unemployment as a four-quarter moving average have been falling since July to September 2016. This means that not only are there more people in work (higher employment levels) as per published Labour Force Survey indicators, but on average a record low level of employed people are transiting into the unemployed category. In the three months to June 2017, on average 544,000 people (1.32% of the working population) moved from inactivity to employment every quarter, whereas on average 567,000 people (1.38% of the working population) every quarter moved in the other direction – from employment to inactivity (Figure 4). The gross outflow from employment was 797,000 in the three months to June 2017; this is lower when compared with the same period in 2015, which was 901,000. In fact, this gross outflow from employment is at its lowest since the three months to March 2006. Recently, the flows from employment to unemployment and vice versa have fallen by a larger proportion compared with the other flows (Figure 4). In contrast, Figure 4 shows that there was a notable rise in the flow from employment to unemployment during the most recent economic downturn. This is because in economic downturns, as the labour market gets looser, there are more movements between the statuses. The unemployment pool is most affected as more of the unemployed find a job or stop searching for one. Also, more of the inactive population may start looking for a job and more workers lose theirs. In other words, gross flows in and out of the three pools appear countercyclical1. In expansions, as the labour market becomes tighter, there are fewer movements between these three statuses, whereas in economic downturns, there are more movements between the statuses.
- Nominal average weekly earnings for employees in Great Britain increased by 2.2% including bonuses in August 2017, and by 2.1% excluding bonuses compared with a year earlier. In real terms, average weekly earnings fell by 0.4% on the previous year (excluding bonuses) and by 0.3% (including bonuses). The recent fall (since the three months to March 2017) in real wages is due to higher rates of inflation, which has outpaced nominal wage growth.
- Productivity well below it’s pre-crisis trend level, and has remained fairly stagnant since 2009. UK facing a “productivity puzzle”. productivity would have been 20.8% higher had it followed this pre-downturn trend And my final topic is Productivity. The latest data show that as measured by output per hour worked – whole economy productivity fell by 0.5% in Q1 compared with Q4 2016, and a further 0.1% in Q2 2017. As a result, on an annual basis - output per hour is 0.3% lower in Q2 2017 compared with Q2 a year ago. The quarterly path of productivity as you can see is quite volatile, with growth and contractions largely offsetting each other during the period since 2015. Lots more analysis of productivity was published on 6 October, including comparisons to other EU and G7 countries, and some new work on the relationship between firms making and receiving FDI and their productivity levels. The FDI research is also summarised in today’s Economic Review. Again I would recommend you look at that material to find more investigation of this important subject.
- These first estimates of labour productivity indicate that the gap between the UK and the rest of the G7 remained relatively stable in 2016, narrowing slightly from 16.1% to 15.4% in output per worker terms. Figure 3 shows the ratio of UK GDP per worker to that in the other G7 economies and to the G7 excluding the UK. It indicates that the UK’s productivity performance improved relative to all of the G7 countries in 2016, with the largest improvements relative to Canada, Germany and France. On this basis, the UK is fifth out of seven in the G7 on both a GDP per hour worked and GDP per worker basis. On a per hour basis, the gap between the UK and the rest of the G7 is broadly similar, at around 15.1%. More details on these results can be found in the main International comparisons of productivity release.
- Industry data exclude real estate, but whole economy average includes real estate. the labour productivity of each industry (the height of the bar) as well as the share of hours worked in that industry (the width of the bar). Industries are ordered from the most productive on the left-hand side, to the least productive on the right-hand side, and the UK average for the period is also shown for reference. the UK produced £33.49 per hour in the year to Quarter 2 2017 (in current prices), labour productivity varied substantially across industries. The most productive UK industries are located in production – mining and quarrying, water transport, and pharmaceutical manufacturing – and in industries that account for a relatively small share of total hours. Services account for a large share of the hours worked at below average productivity. However, there are some high-productivity services industries that – compared with other high-productivity industries – have a relatively large share of hours. Industry 64 (financial services excluding insurance) and industry 69 (legal and accounting activities) each have above average productivity and a share of hours greater than 1.5%. These data should enable more detailed analysis – in particular of the contribution of the “reallocation” effect, which is thought in general to shift resources away from less productive industries towards more productive industries over time.
- So, in summary on my 4 topics, I leave you with these the main messages: GDP has slowed in the first half of 2017 compared to previous years, and most other EU and G7 countries. There are a number of reasons for this and there is a complex picture of some areas of positive growth (for example, services) being offset by areas of negative growth (such as production and construction). The Economic wellbeing dashboard highlights a range of wider measures of welfare. Import intensive goods have been putting upward pressure on CPIH during 2017. and we have experienced 2 consecutive quarters of falling productivity in 2017. I hope you have found these data interesting and given you some ideas of where to find more material and economic analysis of our data. I will be shortly joining the panel to help answer any questions you may have. Thank you very much.
- Replace + add London.
- Replace with SE, SW, Wal, Lon, GB
- Development of Regional Short Term Statistics (also called ‘RUSTY’) Users tell us they want more timely, more granular and more flexible regional economic statistics. These requirements were also captured in the Bean Review. As a result (as part of the devolution project) a work stream was established to develop Regional Short Term Indicators for England ie produce quarterly real GVA growth estimates for the regions of England
- Related statistics already exist for Scotland, NI and Wales Scotland has GDP (not strictly GDP but they call it GDP) NI has the Northern Ireland Composite (the media refer to it as GDP) Wales doesn’t cover the whole Economy so they have 2 x releases – one for the index of production and index of construction, one for the index of market services. The underlying data are processed by ONS staff on behalf of WG (but WG publish the bulletins).
- VAT data are potentially hugely beneficial for the project. MBS and RSI are national surveys with no regional stratification. Therefore at a regional level the data can be ‘lumpy’ due to sample rotation (ie sampled businesses moving between regions). VAT has the potential to resolve this ‘lumpiness’. We have recently received VAT data and are in the early stages of assessing it. Using UK deflators as we don’t have regional deflators Currently have a historic series back to 2013 but hope to take this back further to include the recession (ideally back to 2005 if possible) The Dec 18 publication will/should be for Q3 2018