1 Combining migration data from multiple sources: Applications to internal movements in England, James Raymer with Peter W.F. Smith and Corrado Giulietti Southampton Statistical Sciences Research Insitute (S3RI) Centre for Spatial Analysis and Policy, University of Leeds, 19 February 2009

ESRC project on Combining Migration Data in England and Wales Develop a methodology for combining migration data and for producing ‘more detailed’ flows over time Applications include flows by ethnicity, economic activity and education at regional, county and area group levels

Background Internal migration data in England are limited due to differences in sources, availability, quality and measurement, e.g., –National Health Service Central Register –Census –Labour Force Survey

Significance The combination of multiple data sources increases the capacity to study migration and population change for specific groups by producing –harmonised data sets –time series Estimates can be used for subnational projections, planning or policies

Outline A general log-linear model for combining data Ethnic migration at regional level, –Combining census and health registration data –Results Economic activity migration at county level, –Combining census, survey and health registration data –Results Conclusions and future work

A general log-linear model for combining migration data We are interested in estimating five-way migration flow tables over time The five dimensions are origin, destination, age, sex and some other ‘more detailed’ variable Migration flow tables are composed of various hierarchical structures, not all of which are necessary for accurate prediction If certain (important) structures are unavailable, they can be ‘borrowed’ from auxiliary data sources

Log-linear models for origin, destination and age migration flow tables Saturated model Unsaturated model Unsaturated-with-offset model

Ethnic migration Categorical variables –9 origins (O) and destinations (D) –16 age groups (A) –2 sexes (S) –4 ethnic groups (E) National Health Service (NHS) register* –OD, OAS and DAS tables each year 1991 and 2001 censuses –ODAS and ODSE * Males undercounted

Reported proportions of NHS interregional migration in England by sex, and 2001 Census = 50.8 M and 49.2 F

Age patterns of NHS interregional migration in England by sex, 1991 and 2007

Adjustment ratios for NHS migration data

Basic framework Data preparation Identification of key structures and theoretical model Estimate the flows Analyse the results

Identifying the ethnic migration model: Analysis of Census 2001 data structures ODAS table –Key structures are OD, OA, DA and AS ODSE table –Key structures are ODE, S Theoretical model (ODASE) –ODE, OA, DA, AS

Model specification Steps Construct time series of ODE tables using geometric interpolation of counts from 1992 to 2000 and extrapolation to 2007 Use iterative proportional fitting to estimate flows, where the ODE tables are adjusted to match simultaneously all of the counts imposed by the NHSCR tables Adjust counts of males for three age groups NHSCRCensus

Results: Estimated levels of South Asian, Black and Chinese & Other interregional migration in England, % White 1991 = = = 85

Results: Estimated interregional migration from London by ethnicity, WhiteSouth Asian BlackChinese & Other SE EA SW SE EA WM SE EA SE WM

Results: Estimated interregional migration from South East by ethnicity, WhiteSouth Asian BlackChinese & Other LO SW EA LO

Results: Estimated age-specific migration of female South Asians: 1991, 1999 and 2007 West Midlands to London London to South East South East to London London to West Midlands

Categorical variables –47 origins (O) and destinations (D) –12 age groups, (A) –2 sexes (S) –6 economic activity groups (G): Self employed, employee, unemployed, retired, other inactive and students NHS Patient Registry Data System* –OD, OAS and DAS tables each year 2001 census –ODAS and ODSG Labour Force Survey –AG and SG Economic activity migration * Males undercounted

Age patterns of PRDS inter-county migration in England by sex, 1999 and 2007

Identifying the economic activity migration model Theoretical model (ODASG) –ODG, OA, DA, AS, AG, SG 1 st step: Combine LFS and Census data 2 nd step: Combine estimates from 1 st step with PRDS data

Results: Overall levels of migration by economic activity groups,

Results: Spatial patterns of employee and inactive migration from Greater Manchester (top 10 flows), 1999 EmployeeInactive

Results: Spatial patterns of student migration from Greater Manchester and Hampshire (top 10 flows), 1999

Results: Spatial patterns of retired migration from Greater Manchester and Hampshire (top 10 flows), 1999

Results: Spatial patterns of retired migration from Greater Manchester (top 5 flows),

Results: Age- and sex-specific migration of selected economic activity groups from Greater Manchester (top flow), 1999 Employee to Cheshire Retired to Lancashire Students to West Yorkshire Inactive to Lancashire

Conclusions Flexible model and framework for combining migration data –Level of detail –Geography –Sources of information Result is a synthetic data base that takes advantage of several available data sources Estimates can be used for analysis, projections or planning

Future work In the next six months –Model ethnic migration flows at county level –Extend approach to estimate flows by education –Test model to predict flows between local authorities, say, within a county or region In the next few years… –Link this framework and resulting estimates with subnational population modelling –Extend this framework to analyse other transition data, such as health, labour force and household change

30 Contact information James Raymer Southampton Statistical Sciences Research Institute (S3RI) University of Southampton Southampton SO17 1BJ See also Raymer J, Smith PWF and Giulietti C (2008) Combining census and registration data to analyse ethnic migration patterns in England from 1991 to University of Southampton Statistical Sciences Institute Methodological Working Paper, M08/09. Available at: