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Distributing Immigrants to Local Authorities

This symposium overview provides insights into the current and proposed methods for distributing migration estimates to local authorities (LAs). The Migration Statistics Improvement Programme (MSIP) aims to enhance the accuracy of population estimates critical for funding allocations in local government, including schools and hospitals. The importance of revising the International Passenger Survey (IPS) methodology is highlighted, addressing issues such as robustness, transparency, and centralising tendencies. Detailed descriptions of streams for measuring student migration are included, supporting better allocation of resources.

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Distributing Immigrants to Local Authorities

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  1. Distributing Immigrants to Local Authorities Helena Howarth and Ben Winkley GSS Methodology Symposium: 6 July 2011

  2. Overview Section 1: • Background • Overview of current method • Overview of proposed method Section 2: • Detailed description of the student stream

  3. Background • The Migration Statistics Improvement Programme is a cross government initiative. • MSIP has already led to changes in the migration estimates. • Currently developing a distributional approach to LA level migration estimates using administrative data.

  4. Why are the estimates important? • Population estimates are used for calculating funding allocations for local government: schools, hospitals etc. • In 2009 natural change became the largest component of population change

  5. ONS ONS IPS IPS Overview of the current method Welcome to Stansted ONS • The International Passenger Survey samples 250k people at ports – a small percentage of whom are migrants. • Produces a robust national level migration estimate. • Produces Intermediate Geography estimates (between Region and LA). • LA level estimates modelled using information from admin sources, the Census and other indicators. ONS IPS

  6. Why change? • Some of the issues with the current method are: • The IPS sample is not robust enough for distribution to LA level • The method is not transparent for users • It includes “centralising tendency” • The IPS is intentions based • The new method is designed to solve these issues.

  7. Overview of the distribution method IPS long-term in-migration is split into different “streams” by “reason for visit” • Workers • Students • Returning migrants • Others

  8. Students • Students can be HE or FE • Data for split provided by IPS 2004/2005 • HE can be at government or private institutions. • There is no private/government split for FE 20% HE data from HESA and FE data from BIS and WAG. 11% 69%

  9. Higher Education – Government Source: Students in Higher Education Institutions 2008/09 – Table 9

  10. Higher Education – Government (2) Linking to other administrative sources (3) Imputation of missing term-time addresses (1) Sub-setting HESA data

  11. Higher Education - Private • HESA conducted a census of Private Providers of HE education in 2010. • This asked for aggregate data by: 1) mode of study • 2) level of study • 3) domicile • 4) Subject • Institution address used to allocate students: • Outside London – Term-time address distribution of HESA government institutions in the LA where available and LA of institution where not. • London – Term-time address distribution of all HESA government institutions in the London GOR

  12. Further Education • Datasets: • Individualised Learner Record (BIS) • Lifelong Learning Wales Record (Welsh Government) • Key Points: • Domicile known • Term-time address not known • No length of stay data • Coverage based on funding

  13. Any Questions?

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