Briefing on the Regional Economic model (REM) and recent

Briefing on the Regional Economic model (REM)
and recent improvements to its functionality
Summary points

This briefing has been produced to update colleagues about recent
enhancements to the REM functionality that may be useful to be aware of.
It also includes a wider briefing on the model for those who may be less
aware of it.

The REM is an interactive database of economic, demographic and
environmental data available across the region. It has been continually
developed and upgraded over a number of years to help forecast industry
growth and decline over the coming years.

The model includes both historical data and forecasts on 38 industry sectors
between the years 1997 and 2031. It can produce forecasts of output,
productivity, employment, occupations and skills.

As well as forecasting; the other key purpose of the REM is that it allows
impact scenarios to be built into it. It includes a collection of modelling tools
that can be used to create scenarios for local areas based on the “Multiplier
effect”. These can be positive and negative scenarios.

As a result of this unique functionality , it has a number of important uses
including for:
o
o
o
o
o
o
Strategic assessment and review
Policy analysis and options assessment
Spatial planning
Employment Land review work
Local Development Framework activities
Economic appraisal of projects
There have been a number of recent changes made to the REM to further improve
its functionality. The changes can be summarised as:
•
Updated data
•
Revised definitions
•
Sub district coverage
1
o
GVA and employment data is now available for broad sectors at
Middle Layer Super Output Area (MSOA) level for both baselining and
forecasting. The forecasts for small areas are constrained within
those of their constituent local authority but allocate scenario
impacts based on activity as well as local sectoral mix

The small area coverage allows an enhanced view of the locations where
growth is predicted to take place – and to decline – in the coming years. It
also allows this to be analysed by sector. This is further enhanced by the
ability to model scenarios at this level and understand the local impacts of
interventions. As a result, it has become a much more powerful tool.
Examples are included in the full briefing.

The small area methodology has been developed and tested, and the data
and forecasts are now available for REM users. They were included in the
most recent update to the model.

The impact assessment capability for small areas is available in the model
but is currently being tested by REIU. Once the small impact assessment
functionality and capability are fully ready, this will be available to use for
all users.

The REM has been a vital tool for supporting decision making in the region
for a number of years. Recent enhancements have the potential to further
develop this capability going forward and ensure that it remains central for
stakeholders in the region to have access to tools that provide evidence
based decision making.

As ever, the tool is only as good as how it is used and the findings
ultimately interpreted. The REIU will continue to provide advice and support
as needed.

Any queries about the REM generally, recent changes, or the need for more
detailed analysis, feel free to contact us at [email protected]
2
Introduction
Many colleagues in the region will already be aware of the Regional Economic
Model (REM) while there are some who are regular users of the model and fully
aware of its ability. For many, however, the REM and its capabilities are
something of a mystery. This briefing addresses this by setting out a summary
guide to the model and how it can be used.
There have also been a number of recent enhancements made to the REM which
are likely to be of equal interest to experienced users and non-users alike. These
are set out in the second part of this briefing.
What is the REM?
The REM is an interactive database of economic, demographic and environmental
data across Yorkshire and Humberside as well as for a number of surrounding
areas. Developed by Experian, it has been continually developed and upgraded
over a number of years to help forecast industry growth and decline over the
coming years. The model includes both historical data and forecasts on 38
industry sectors between the years 1997 and 2031. It can produce forecasts of
output, productivity, employment, occupations and skills.
As well as forecasting; the other key purpose of the REM is that it allows impact
scenarios to be built into it. It includes a collection of modelling tools that can be
used to create scenarios for local areas. For example, the impact on industry
sectors of a 300 job loss/gain in a particular sector in a particular local authority
area in the region. The model allows the user to view not only the direct impact of
a particular industry’s job losses/gains, but also the indirect impact as well.
3
The REM contains over 40 datasets for the different geographic areas used within
the model. These include:



Economic data, including;
o Output
o Employment
o Commuting
Demographic data, including;
o Population
o Households
Emissions data
This unique functionality means that it has a number of important uses including
for:






Strategic assessment and review
Policy analysis and options assessment
Spatial planning
Employment Land review work
Local Development Framework activities
Economic appraisal of projects
How it works:
The REM uses a number of complex modelling techniques to produce its forecasts
and scenarios. It is not the purpose of this briefing to set these out in detail,
rather it summarises the broad approach. More detail can be provided to those
who may be interested.
The baseline forecasts in the model are calculated using a combination of national
and local factors. UK forecasts drive regional forecasts which in turn drive local
area forecasts. In broad terms, the historical performance of local economies is
interpreted in terms of their share of the regional economy of which they are a
part. Regional and industry sectors forecasts vary on the basis of their differing
economic structures and historic performance, as well as on UK wide
relationships.
The impact model allows users to understand the overall effect of changes in
employment (relative to the baseline level) on the wider economy. At the heart of
this is the assumption that the overall effect on the whole economy of an initial
increase of, say, 1000 job in Industry A will be greater than 1000. This is to model
the “multiplier effect”.
In order to calculate this, it is necessary to have information about how the
different sectors of the economy purchase from each other. The model uses an
4
input-output model to calculate these wider effects, showing how outputs from
one sector of the economy are used as inputs by another.
Fortunately, the model is user friendly and takes care of much of this so users can
have confidence in the functionality to be able to concentrate on their headline
figures.
Recent changes to the REM
There have been a number of recent changes made to the REM to further improve
its functionality and make it a more powerful model. Many of these are worth of
note. These include updates to the data, revised employment definitions and the
exciting development of sub district functionality for the first time. The changes
can be summarised as:

Updated data being available including:
o Employment data
o revised ONS GVA data
o stronger annual growth assumptions

Revised definitions
o Full-time and part-time employees have been replaced by total
employees

Sub district coverage
o GVA and employment data is now available for broad sectors at
Middle Layer Super Output Area (MSOA) level for both baselining and
forecasting. The forecasts for small areas are constrained within
those of their constituent local authority but allocate scenario
impacts based on activity as well as local sectoral mix.
The rationale for these changes includes the need to take advantage of the recent
availability of new and updated data and the need to better define employment in
terms of full time equivalent workers. Among the reasons for the desire for sub
district trends and forecasting were to use it within the Single Appraisal
Framework and better fit with the Urban Dynamic models in the Leeds City
Region. It adds an extra layer of detail to what was previously available in the
REM.
5
Examples of findings
Figure 1 below shows historic and forecast employment by LEP area, compared to
the UK. In terms of past trends, the slowing impact of the 2008/09 recession on
employment can be clearly seen. Positively, all areas are forecast to see
employment growth, although all below national levels of growth.
Figure 1: Historical and forecast total employment by Yorkshire LEP area
1997-2031 (indexed to 1997)
1.30
1.20
1.10
Humber Ports
Leeds City Region
1.00
North Yorkshire & East Riding
Sheffield City Region
0.90
United Kingdom
0.80
0.70
Source: REM
The enhanced sub district functionality is demonstrated in the following three
example maps. The first shows current total concentrations of employment in
parts of West Yorkshire. As expected, the main employment concentrations are in
urban centres and locations near motorways and other transport links.
6
Figure 2: Total employment 2012
Figure 3 below shows baseline projected employment up to 2030 at the small area
level. It demonstrates that the existing spatial pattern of employment is likely to
see the principle employment increases in future – in the absence of other forms
of policy intervention. This is crucial evidence to inform planners about, in
particular in estimating future amounts of land that may need to be made
available to support this future growth. There are some areas that are projected
to increase that are currently less of employment centres which would be worthy
of note.
When analysed by a particular sector – finance and business in this case – the
forecast can be seen to suggest a broadly similar pattern of employment growth
in future (Figure 4 below). The advantage of analysing by small area is that there
are a number of areas forecast to see particular or less growth in this sector than
overall growth and these can be identified using a mapping approach similar to
that below.
The final point to make is that if a particular policy intervention is modelled, the
spatial impact of these can be seen including the difference it makes to the
existing and forecast patterns of employment.
7
Figure 3: Projected total employment to 2030
Figure 4: Projected employment in finance and business to 2030
8
Recent progress and areas for further development
The small area methodology has been developed and tested, and the data and
forecasts are now available for REM users. They were included in the most recent
update to the model.
The small area impact assessment capability is available (although not included in
version released to subscribers) but is currently being tested by REIU. Once the
small impact assessment functionality and capability are fully ready, this will be
available to use for all users. This is also linked to the development of the Leeds
City Region Single Appraisal Framework.
Further data is also due to be added on population and household forecasts.
Conclusions
The REM has been a vital tool for supporting decision making in the region for a
number of years. Recent enhancements have the potential to further develop this
capability going forward and ensure that it remains central for stakeholders in the
region to have access to tools that provide evidence based decision making.
As ever, the tool is only as good as how it is used and the findings ultimately
interpreted. The REIU will continue to provide advice and support as needed.
Any queries about the REM generally, recent changes, or the need for more
detailed analysis, feel free to contact us at [email protected]eeds.gov.uk
9