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Modelling short-distance residential moves using the Northern Ireland Longitudinal Study (NILS)

Modelling short-distance residential moves using the Northern Ireland Longitudinal Study (NILS). Ian Shuttleworth (QUB), Myles Gould ( UoL ) & Paul Barr (QUB). Outline. The project Scope and rationale Research questions The data Northern Ireland Longitudinal Study (NILS)

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Modelling short-distance residential moves using the Northern Ireland Longitudinal Study (NILS)

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  1. Modelling short-distanceresidential moves using theNorthern Ireland LongitudinalStudy (NILS) Ian Shuttleworth (QUB), Myles Gould (UoL) & Paul Barr (QUB)

  2. Outline • The project • Scope and rationale • Research questions • The data • Northern Ireland Longitudinal Study (NILS) • Analytical strategy (ML models) • Model Results • answers to 3 questions about residential moves through sectarian space • Conclusion

  3. The Project & Research Questions

  4. Analysis of address changes within NI (2001-2007) 76,741 people (with 2001 NI Census record) who moved between 890 SOAs, within NI, between 2001 & 2007 Residential segregation moving apart or moving together? understanding migration patterns – which areas are gaining and losing population through migration after the 2001 Census? All part of wider project who moves, how far, from/to where, and what influences moves exploring how far internal migration in NI sifts the population with regard to residential segregation (community background & socio-economic deprivation) Today’s focus: residential moves through sectarian space (with particular focus community background) The Project

  5. Research Questions With respect to residential moves across sectarian space... • Are individuals more likely to move in areas where they are in the minority? • Is there evidence of longer distance moves in areas where individuals are in the minority? • Do Catholics and Protestants move to different areas? • Does it matter? [i.e. Our Conclusion] • How far does migration redistribute the population and does it lead to greater residential segregation?

  6. The Data & Analytical Strategy

  7. A 28% sample of the NI population (based on 104/365 birthdates) data on individuals and households collected by the 2001 Census; information on post-census moves from health card registrations (2001-2007); information on residents of 890 SOAs in NI – built from OAs – c1,800-2,500 residents; in total, c500,000 NILS members Project selection criteria: were in NI in 2001 and had a census record were still in NI in 2007 (e.g. not dead or left NI) were aged 25-74; exclude student age group (who bias results) & very old c.274,000 in the analytical database The Data: Northern Ireland Longitudinal Study

  8. Analytical Strategy (ML Models) • Approach: Complex modelling, simple graphing/presentation • Relatively simple hierarchical data structure • individuals (level-1) nested within 890 SOAs (level-2) • Properly handle spatial clustered data • Get purchase on within-area and between-area variability • Precision weighted estimation • Individual variables: sex, religion, marital status, SES, age, limiting long-term illness, housing tenure • can include as overall main effects (as here) • allow different, differentials between SOAs - complex between-area random variation (done but not presented here today) • Ecological level-2 variables: %Catholic, deprivation score • Can also model cross-level interaction between individual & ecological variables (presenting today)

  9. Different Modelling Strategies Macro-level effect on micro-level response Macro model Micro model Multilevel models Cross-level interaction Main effects only Source: Tacq (1986) cited in Snijders & Bosker (1999)

  10. Results

  11. 1. Are individuals more likely to move in areas where they are in the minority? Average 42.9% Average 42.9% • Catholics are less mobile (less likely to make one or more moves) than Protestants everywhere • Catholics, ceteris paribus, are less likely to move in areas where they are in the majority • Protestants are slightly more likely to move in highly-Catholic areas • Overall, cross-level interactions between individual community background and ecological religion are small but highly statistically significant Logit Propensity to move Predicted Probability to move Predicted Ratio %Cath Origin/Destination ≈0% 14.4% 42.9% 71.4% 99.9% ≈0% 14.4% 42.9% 71.4% 99.9% %Catholic %Catholic

  12. 2. Is there evidence of longer distance moves in areas where individuals are in the minority? Average 42.9% Average 42.9% • Protestants in most places tend to move greater distances than Catholics • Protestants who lived in highly Catholic areas tended to travel further than those who were in highly Protestant places • Catholics in highly Catholic areas tend to move shorter distances than Catholics in Protestant areas • Cross-level interactions are large and statistically significant ≈0% 14.4% 42.9% 71.4% 99.9% ≈0% 14.4% 42.9% 71.4% 99.9%

  13. 3. Do Catholics and Protestants move to different areas? Null model, for Ratio %Catholics receiving over sending response, before including any predictors • Considerable place variation (0.034 units, 34% of tot. variation) • Biggest ratio: SOAs 419, 439 & 118 • Smallest ratio SOAs: 201, 822, & 782

  14. Ratio %Catholic Receive : Sending – Main Effects * = statistically significant

  15. 3. Do Catholics and Protestants move to different areas? • Catholics are always more likely to go to more Catholic areas than Protestants • Others/nones lie somewhere between Catholics and Protestants • Everybody in highly-Protestant areas are more likely to move to more Catholic areas – a function of the balance of opportunities for moves • At the other end of the scale, in highly-Catholic areas, everyone moves to more Protestant (e.g. less Catholic) areas but Protestants are more likely to move to less Catholic areas than Protestants Difference %Catholics receiving compared to sending Predicted Ratio %Catholics receiving over sending Logten Ratio %Catholics receiving over sending Logten Ratio %Catholics receiving over sending Predicted Ratio %Catholics receiving over sending %Catholic %Catholic %Catholic %Catholic Average 42.9% Average 42.9%

  16. 3. Do Catholics and Protestants move to different areas? • Response: Ratio %Catholics receiving over sending response • PLUS: individual & ecological effects; and also cross-level interaction: individual community background/ %Catholic • Large reduction in place variation (reduced to 0.011 units, now 10% of tot.) • Biggest ratio: SOAs 419, 439 & 634 • Smallest ratio SOAs: 235, 110, & 61

  17. Conclusion (1): Does it matter? • Clear evidence for communal differentials in: • migration propensity • distance moved and • the types of SOA to which Catholics and Protestants move • Even 12 years after the Belfast/Good Friday Agreement of 1998 communal/national identity remains an important factor shaping short-distance migratory moves in NI

  18. Conclusion (2): Does it matter? • But this is very different from saying that the segregation is increasing as the two communities ‘move apart’. • This is because: • Although Catholics are more likely than Protestants to move to more Catholic SOAs some Protestants still move to more Catholic areas • Catholics move to areas that are typically only ‘slightly more Catholic’ – most moves are short-distance to very similar areas [& vice versa?] • Moves to less Catholic areas tend to cancel out moves to ‘more Catholic areas’ • Differences in migration propensities and distances moved (eg long distance moves for Protestants who live in SOAs more than 80% Catholic) tend to be numerically less noteworthy in changing the demographic composition of SOAs because of the relatively small numbers living at the ends of the distribution (eg Catholics living in Protestant areas and vice versa)

  19. Conclusion (3): Does it matter? • Most moves tend to be short distance and most to and from very similar SOAs in terms of religious composition • Given the already existing social geography/sectarian geography of NI, migration of the type and level seen since 2001 is unlikely to redistribute the population to lead to either more segregation or integration • More moves, particularly over a long distance, are needed to lead to either of these two outcomes

  20. Conclusion • With regard to community background, migration 2001-2007 did not redistribute the population fundamentally • This suggests that ‘normal’ migration will on its not desegregate the NI population • The other implication is that to increase/decrease segregation more individuals need to move and to move further • Was the population system much more dynamic 1971-1991 when biggest increases in residential segregation seen?

  21. Acknowledgements The help provided by the staff of the Northern Ireland Longitudinal Study (NILS) and NILS Research Support Unit is acknowledged. NILS is funded by the HSC R&D function of the Public Health Agency. The NILS-RSU is funded by the ESRC and the Northern Ireland Government. The authors alone are responsiblefor the interpretation of the data.

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