The document discusses the development of economic forecasting models for the East of England and West Midlands, emphasizing the need for consistent and policy-neutral data to inform local authorities and organizations. It highlights the importance of involving these entities in the design of the forecasting model and ensuring the data used is reliable. The models aim to provide insights into economic trends, job forecasts, and demographic changes while assessing the impact of various policy scenarios.

1. ‘ The Environmental Limits on Returning to Economic Growth’ Break-Out Session Two: Examples of Modelling and Forecasting With Andrew Jamieson, Andrew Hermann and Oliver Nicholls

2. East of England Economic Forecasting Andrew Jamieson (EEDA Insight East) at ARO, 27 th Jan 2010

3. Background East of England has 47 local authorities and many other local and regional organisations. Each has its own priorities, policies, responsibilities, strategies – and they don’t always agree! We need a view of future trends which (1) everyone can agree on, and (2) separate local and regional decisions and strategies can be based on, to ensure they are consistent with each other.

4. Why is it necessary? A forecasting model is a shared base of understanding, and a starting point for discussion. It recognises the connections between jobs, output (wages, profits, etc), economic sectors, labour supply, housing, etc, across local boundaries. It produces results which are consistent and comparable across local boundaries.

5. What people need to know! Forecasting is not a statement of what we want to happen, nor what will happen. It is based on past trends, existing knowledge, available data, etc. Outcomes are sensitive to input data, and some of this is fallible and fluctuating (eg, migration and household size interaction). For consistency, forecasting needs to be ‘policy neutral’ (that means it doesn’t take into account policy proposals which haven’t been implemented yet, or aren’t reflected in the available data). Forecasts can be seen as a challenge – what might happen if we do nothing! For statistical reasons, forecasts for local areas or individual industries, etc, need to be interpreted very carefully.

6. Developing the East of England Forecasting Model Very important that local authorities, regional organisations, etc, have confidence in the Model, so . . . Involve them in its design and content, and Use data they can trust – good quality national data, or local data collected to a high and consistent standard. Get suppliers to compete for the contract and provide evidence of their work elsewhere. Keep local authorities involved in managing the Model and its supplier. Make sure the supplier writes a Technical Report which explains the structure, assumptions and data of the Model, and make sure this is easy for users to find and easy to read.

7. Content of the East of England Forecasting Model Output and jobs in 28 economic sectors Employment rate Labour productivity Unemployment Population and migration Housing and households Data for all local authorities and selected groups of local authorities Content and capability of Model needs to evolve over time as needs change. Model needs to be easy to find and easy to use – we use the Insight East website . . .

8. Insight East Front Page Click on ‘Forecast Model’

9. EEFM first page Technical Report

10. Spring 2009 Results page Scenarios

11. Scenarios ‘ Baseline’ – the “least unlikely outcome” – ie, the average expectation based on past trends, existing knowledge, available data, etc. ‘ Scenario’ – variation on baseline with one or more factors shifted from the average expected value to a less likely (but still possible) value. Scenarios can be used to test possible effects of policy decisions. In Spring 2009 two scenarios were linked to output (GVA), and five others were linked to housebuilding (that is, policy decisions). In Autumn 2009, two scenarios were linked to housebuilding, and one to Local Authorities’ “economic aspirations.”

12. Spring 2009 Economic Forecasts Baseline and scenarios, and two different spreadsheet formats for each

13. Economic Forecasts – local area (1) Here is the document to click on

14. Economic Forecasts – local area (2) Geographic area tabs Use top line to check location

15. Economic Forecasts – variables (1) 28 industry sectors

16. Economic Forecasts – variables (2)

17. Spring 2009 RSS Scenarios

18. Integrated Policy Model Andrew Hermann West Midlands Regional Observatory West Midlands Regional Observatory 2009

19. Overview Background Key Features Environmental Limits and Impact Modelling West Midlands Regional Observatory 2009

20. Background to IPM Past Methods Partial models forecast jobs and population separately Incompatible assumptions Integrated policy making requires integrated models Limitations identified during preparation of RES evidence base Modelling across local areas within the Region Initially the 34 local authority districts Includes interactions between neighbouring areas Modelling more than just a single theme Economic and environmental (like REEIO) Population demographics and housing Co-determination – each influences the other

21. How the IPM works What does it cover? Focus is on long-term trends Integrating economic and demographic outcomes Co-determines jobs and housing Importance of spatial linkages Feedback and interaction Results cover economic, demographic and environment indicators Policy levers planning consents, transport improvements West Midlands Regional Observatory 2009

22. How the IPM works What are the key drivers? Location of jobs depends on structural change (sectors) local demand from population and business access to markets further away agglomeration/cluster benefits space constraints access to workers Location of population depends on access to jobs (for working-age population) space constraints West Midlands Regional Observatory 2009

23. How the IPM works What are the key relationships in the model? West Midlands Regional Observatory 2009 Jobs (by LAD and sector) Resident workers (by LAD and occupation) Occupied floorspace (by LAD and property type) Occupied dwellings(by LAD) Population (by LAD) Retired population (by LAD Dwellings(by LAD) Floorspace (by LAD and property type) Transport costs between each pair of LADs Utility of Environment indicator (by LAD) Availability of land for housing (by LAD) Availability of land for offices, retail, industry

24. Uses of the IPM Who could it be used by and for what? Regional policy makers and strategists Development of regional strategies Assessing the impact of different scenarios Evaluating policy options Understanding the interaction of economic and spatial policy Local authorities Local Economic Assessments Evaluating policy options Understanding economic impact of planning policies Testing the impact of major developments Investors and Developers Making business case for investments Identify priorities for future developments Understand the wider impact of their plans

25. Environmental Limitations Environmental impact not the driving force behind development CO 2 and energy consumption modelled by industry Outputs generated through a multiplier and industrial performance West Midlands Regional Observatory 2009

26. Modelling Environmental Impact West Midlands Regional Observatory 2009

27. Modelling Environmental Impact West Midlands Regional Observatory 2009 2015

28. Modelling Environmental Impact West Midlands Regional Observatory 2009 2020

29. Any questions? More details on our website www.wmro.org Email [email_address] Telephone Anderew Hermann on 0121 202 3247 West Midlands Regional Observatory 2009