New Horizon Economics is a UK regional economics consultancy specialising in the construction and application of regional input–output models and the analysis of UK and regional economic data (e.g., Gross Value Added, GVA). We publish a monthly regional GVA growth indicator derived from UK ONS GVA indices. We feature a free-to-use GB economic impact model on our site.
WHAT WE DO
- We provide a range of products and services in the field of economics.
- Specialising in tailored data products, economic models and bespoke socio-economic impact analysis projects at national and regional levels in the UK.
HOW WE WORK
- Transparent sources and methods, documented so that clients can scrutinise and reuse.
KNOWLEDGE TRANSFER
- Training, handover and after-sales service are a key part of every project.
- Growing in-house capability for clients is a fundamental objective for us.
FREE PRODUCT EXAMPLES
FREE ECONOMIC IMPACT ANALYSIS
For a limited period you can claim a free economic impact analysis of your company. See details here.
CONTACT US and we’d be happy to discuss this or any other project, product or service you would like our assistance with.
MONTHLY REGIONAL GVA INDICATOR
Official ONS regional Gross Value Added (GVA) estimates are typically published in April each year. The most recent estimates are available for the year 2023, i.e. published with a two year lag.
Our Weighted Industry Mix (WIM) method aims to provide timely regional GVA growth indicators that appear at the same time as the UK monthly GVA release.
LATEST DATA
The June 2025 WIM estimates for ITL1 regions are presented below.
The first chart shows the growth rate for June across ITL1 regions. The chart shows that the East Midlands led the way in June with growth of 0.49% against the GB average of 0.39%. High tech industries in EM such as computer and electronic products, engineering / technical services and scientific R&D all posted strong monthly growth.
The North East and North West saw below average performance, posting implied growth of 0.27%. Pharmaceuticals, telecommunications and educational services dragged the NE growth rate below the GB average, whilst in the NW accounting and educational services dampened growth.
The second chart illustrates the year on year growth as of June 2025. The chart suggests that the South West region performed strongest during this period 1.72% against a GB average of 1.41%. Solid growth in the shipping and aerospace sectors along with the rental and leasing sector helped the SW outperform the GB average. The West Midlands lagged the average with the motor industry dampening growth.
NEXT UPDATE : on or around 14 September 2025
THE WIM GVA INDICATOR IN 2024 AND MONTHLY FOR 2025
The charts below show how regions have performed during 2025 on on a monthly basis. In the first chart you can select either an individual month, or multiple months to show cumulative growth in the months you select.
The second chart tracks the monthly growth rate in 2025 between your selected region and GB.
The chart below shows the implied growth rate in GVA between 2023 (ONS latest estimate) and 2024. The SE (1.42%), NE (1.41%) and Scotland (1.36%) are amongst those estimated to have outperformed the GB average of 1.12%, whilst Yorkshire and Humberside (0.87%), Wales (0.95%) and the East (0.93%) were amongst the lagging regions.
For the SE the growth comes from tech such as computer products and health services; the NE was significantly boosted by the health sector, pharma and construction. In Scotland the health sector led growth. YH, Wales and the East were mostly held back by education services,
HOW RELIABLE IS WIM? NOTES ON METHOD AND 2016-2023 PERFORMANCE
Each month, ONS provide indices of real GVA growth by detailed UK industry (100+ industries). The WIM method weights these indices for their importance at a regional level.
The basic concept is that, if aerospace grew significantly nationally in a given month, the inference is that this would be expected to contribute more significantly to growth in regions specialised in aerospace, such as the South West.
The charts below show how the WIM method has tracked official ONS estimates of GVA growth in each region over time. You can inspect any one region’s WIM projection v ONS over time, or look across the regional WIM projections vs ONS for any given year.
Is the WIM method informative? Yes – the 2023 WIM estimates for example explain around 50% of the variation in ONS regional growth rate (p=0.018) and the joint test across the whole sample, controlling for period fixed effects yields p=0.001, indicating strong statistical evidence that WIM tracks ONS growth rates in a meaningful way. However, the growth rate for any given industry at any point in time can of course vary between regions. WIM is therefore only a partial explanation / indicator of regional growth.
Essentially, the WIM indicator shows whether a region was relatively specialised in industries that grew or declined nationally in the period in question.
In this sense, a simple but interesting interpretation of the WIM estimate is that it represents expected regional growth, given the region’s industry structure. Differences between the WIM and ONS estimates can therefore be interpreted as representing under/over-performance of the region’s industries relative to the nation. This sort of interpretation is essentially the ‘shift-share‘ approach to analysing regional economic growth.
Technical Notes
The historic ‘ONS’ regional growth rates reported here differ slightly to those published for the UK by ONS. This is principally due to WIM estimates being for GB not UK, but also partly due to total GVA being calculated over a different level of industry disaggregation between methods.
The WIM method is described briefly below.
Firstly the ONS chained volume estimates of GVA need to be de-linked because industry volume estimates tend to be progressively non-additive outside of the base year. In order to mitigate against this issue, single link Laspeyres indices are formed as follows.
For ONS estimates, the nominal industry GVA estimate in each industry i in year t is transformed into t-1 prices, e.g. for industry i, t at t-1 prices is the nominal GVA estimate in t-1 multiplied by the volume growth between t and t-1. The ONS volume growth rate is therefore the sum of GVA across all i industries in t at t-1 prices divided by the sum of GVA for all i in t-1 at t-1 prices.
The WIM indicator estimates are then formed by taking nominal GVA in industry i in t-1 and applying the national volume index growth rate in industry i between t and t-1. The estimated total volume growth rate between t and t-1 is therefore the estimated GVA in t aggregated across i industries, divided by the ONS nominal GVA total in t-1.
This method forms an ‘observed’ and estimated volume-based time series that can be aggregated across industries and is suitable for direct comparison between years.
INTERACTIVE ECONOMIC IMPACT TOOL
We offer an illustrative version of the latest ONS national Input-Output model. This is free to use.
Using our web app, you can input changes to the GB economy and see how they impact on 21 different industries in terms of GVA, FTE employment and sector / GB economy growth rates.
HOW TO USE THE NEW HORIZON INPUT-OUTPUT MODEL APP
The interface has two tabs – one for model inputs and one for model outputs. The output tab is dynamically linked to the input tab – adjust the model inputs and the outputs will update automatically. Use in landscape mode if on mobile device for a more effective interface.
INPUT TAB
Firstly specify the type of economic impact you want to simulate.
- Select from GROUP – choose either INDUSTRY or final DEMAND categories (e.g. households, exports).
- Next choose the INPUT TYPE. If you have chosen industry as the group, you can select an impact in £m, a number of Full Time Equivalent (FTE) jobs, or a % shock. If you have chosen a demand category you can only specify this in £m or % terms.
- Next select the CATEGORY – if you chose industries, select one of the 21 industry categories; if you chose demand, select one of the 7 categories of final demand.
- Finally specify the INPUT VALUE. You can enter any positive or negative numeric value, including decimals.
Example input entries
Suppose you select the construction industry and then
- if you select FTEs and enter 1000, this will simulate adding an extra 1000 FTEs to the construction industry;
- £m and enter 100, this will simulate an extra £100m in construction Gross Output (loosely similar to turnover);
- if you select % and enter -5.5, this will simulate a 5.5% fall in construction output;
Suppose you select households from the categories of demand. If you then select
- £m and enter 500, this will simulate an extra £500m of household spending;
- if you select % and enter +1.5, this will simulate a 1.5% rise in household spending;
Click ADD to add your selection to the current list of model inputs, you will see the selection added to the table of CURRENT INPUTS. Once added, the output tab will update your results.
You can add multiple entries to the current input table. These will be treated additively.
The model is calibrated for the year 2022, hence £m input values must first be deflated to 2022 prices. If you enter a value in 2025 prices, GVA effects will be shown in 2025 prices, but FTE effects will tend to be overestimated and will need to be deflated accordingly. Entering any % value gives estimates of GVA valued at 2022 prices.
If you CLEAR the inputs, the current inputs table will be emptied.
You can download your input profile as a .csv file.
OUTPUT TAB
At the top of the tab the economy wide effects for GVA, FTEs and Growth are shown.
These are broken down for each industry in the INDUSTRY EFFECTS table.
Select the METRIC , either GVA (default), FTE or GROWTH.
The effects are split as follows:
- Initial Effect – these are the industries directly affected by the changes you specified.
- Direct Suppliers – these are the suppliers of the industries affected in the initial phase
- Indirect Suppliers – these are suppliers further down the supply chain
- Induced Effects – these are effects generated by workers receiving additional incomes and spending them within the economy
Growth effects show % changes in each industry and the economy wide growth effect. The effects apply equally to GVA and FTE as the standard Leontief IO model assumes labour productivity is fixed.
The table can be downloaded as a .csv file by clicking the download button.
NHE GB INPUT-OUTPUT MODEL WEB APP
TECHNICAL DETAILS
INPUT-OUTPUT MODELS – A BRIEF OVERVIEW
An Input-Output (IO) model is a snapshot of buying and selling that takes place in an economy over the course of a year. It maps how different industries supply goods and services to each other, and how they meet the final demands of households, government, exports, and investment.
Examples of these transactions might include:
- intermediate production – buying and selling between industries, e.g. car manufacturers buying steel;
- final demand – the purchase of finished goods and services by households or government, or that are sold for export;
- distribution to primary inputs – payments to labour and capital — such as wages and salaries, and profits, which reflect how industries draw on the economy’s resources
Under certain assumptions, this map can be used to trace the effects of a change in demand — for example, a 2% rise in household spending or an extra £100 million in manufacturing exports. The model shows how this shock ripples and flows through the economy, affecting:
- the sector(s) directly impacted,
- their direct suppliers,
- other industries indirectly linked in the supply chain, and
- sectors influenced by changes in household income and spending.
These effects are typically measured in terms of:
- Gross Value Added (GVA) – a measure of the value created by each industry
- Employment – typically estimated through full-time equivalent (FTE) jobs
However, other types of impact can also be modelled — such as environmental emissions, energy use, or demand for particular occupations.
For further reference on input-output modelling, see
Miller, R and Blair, P (2009) Input-Output Analysis: Foundations and Extensions, Cambridge University Press
DATA SOURCES & NOTES ON METHOD
The NHE table for Great Britain is estimated using the following sources:
- ONS UK Industry-by industry input output table for 2022
- ONS balanced method GVA data for 2022
- ONS regional accounts data on taxation, social contribution etc.
- ONS BRES employment data for 2022
- Self employment data from the LFS
- Hours worked by industry from LFS
- Data regarding Northern Ireland’s share of UK employment and GVA (LFS, ONS GVA accounts), and regional trade (NI Department for Economy)
Please note the following regarding estimation methodology:
- Whilst trade between GB and Northern Ireland is accounted for in the GB model specification, ‘Exports to Northern Ireland’ is not explicitly shown as a selectable demand vector. Regional analyses are available as part of a subscription service. However, the underlying modelling assumption for trade between NI/GB is centred around Northern Ireland’s output share of the UK market in each industry (formed and applied at the 105 industry level), adjusted for the tradability of each industry’s output (e.g. manufactures traded more than services). For broad context, imports of goods and services by GB from NI within the model are estimated in 2022 at around £11.8bn, £10.1bm of which was goods, £1.7bn services. These values are consistent with the figures estimated by the NI Department for Economy.
- FTE employment includes employees in employment, self-employment and MoD military staff.
- Headcount values are converted to FTE by applying estimates of FT / PT / SE working hours in each industry derived from the Labour Force Survey.
- The income row of the national input-output table is augmented to include an estimate of self employment income, hence the induced model closure includes compensation of both employees in employment and the self employed.
- The household spending vector of the national input-output model is augmented to incorporate income taxation, and social contributions in the income-expenditure model closure. These are treated as leakages – closure of the model only extends to the household sector.
PRODUCTS & SERVICES
You can see a more comprehensive list of our products and services here