A new look at the housing consequences of

A new look at the housing consequences of

A new look at the housing consequences of partnership dissolution Rory Coulter, University College London ([email protected]) Michael Thomas, University of Groningen Clara H Mulder, University of Groningen Understanding Society Conference, Colchester, 13th July 2017 Separation and housing Separation often a turning point in the housing career Alters trajectory and identities (Gotlib and Wheaton, 1997) Homeowner Renting Renting with partner Shared housing Parental home Intensely gendered patterns and processes Known housing impacts Short-term Triggers moves constrained by time, finances and spatially linked lives (Cooke et al., 2016) Longer-term Suboptimal initial moves, reduced resources and new preferences elevate risk of moving

(Feijten and van Ham, 2010) Exits from homeownership, returns to Lower odds of homeownership later the parental home and reduced in life course (Herbers et al. 2014) housing quality (Dewilde, 2008; Feijten and van Ham 2010) Theoretical framework INDIVIDUAL LEVEL Gender, children, income, tenure, housing history (contract status) Resources & restrictions HOUSING OUTCOMES Institutions LOCAL CONTEXT Urbanization, tenure structures, housing costs Opportunities & constraints Motivations for the study 1. Place: rarely consider geography Emphasis on cross-national not local geographies

2. Time: focused on homeownership in 1990s-2000s Reduced homeownership and rapid growth in private renting Also new housing benefit regime (SAR to age 35; LHA at 30% BRMA; benefit caps), constrained access to social sector, housing affordability pressures (vary spatially) Research question: How do the housing outcomes of partnership dissolution vary by tenure and across space in England and Wales? Research design Household relationship grid to identify separations in W1-W6, defined as: a transition from a legal marriage or cohabiting union observed at the wave t interview to living apart from the wave t spouse or partner at the wave t+1 interview (Jenkins, 2009) Discard TSMs, same-sex couples, widowed and a small number of cases where partners split but stay in same HH Short panel so look at t to t+1 transitions (n=1480) Four outcomes (own, social rent, private rent, parents/sharing) Housing Market Areas (HMAs) CURDS project for short-lived NHPAU Use commute and migration

patterns to create functional geography using 2001 census Blackburn We use silver standard and single tier version London Source: Coombes and Wymer (2010) In practice, choice of HMA definition seems to have very little impact on results Changes in housing position with separation 100 Men (n=557) Women (n=923) 7.7 12.4 11.8 Percent 40 60 80

21.2 21.8 21.4 26.3 29.8 22.3 16.7 23.9 11.1 20 49.6 48.2 37.9 0 37.9 Pre separation Homeownership Post separation Social tenancy Pre separation Private tenancy

Post separation Parents/sharing 0 20 Percent 40 60 80 Destinations of homeowners Homeownership Social tenancy Men (n=276) Private tenancy Women (n=445) Parents/sharing 0 20 Percent

40 60 80 Destinations of social tenants Homeownership Social tenancy Men (n=93) Private tenancy Women (n=206) Parents/sharing 0 20 Percent 40 60 80 Destinations of private tenants Homeownership

Social tenancy Men (n=119) Private tenancy Women (n=201) Parents/sharing Multinomial model Outcome (ref=ownership) Variable (measured at t) Social tenant Private tenant Parents/sharing Female social tenant # female private tenant # female parent/sharing # female Lives with children lives with children # female Age Cohabiting Repartnered at t+1 Degree level qualifications Income (1000) Ln population density of HMA % homeowners in HMA Ln terraced house prices in HMA N Social tenancy

5.319 3.131 2.073 -0.375 2.249 2.246 1.815 0.573 -0.265 0.017 -0.176 0.721 -0.414 -0.428 -0.129 -0.065 -0.260 Private tenancy 2.632 3.690 0.741 0.066 0.535 1.440 0.890 0.983 -1.070 -0.025 -0.344 0.473 -0.012

-0.174 -0.128 -0.018 0.459 1480 Parents/sharing 2.985 2.814 2.593 -0.025 0.759 1.444 1.457 0.495 -1.786 -0.068 -0.347 -0.872 -0.457 -0.105 0.075 -0.006 0.262 Notes: Extra controls for wave, housing contract status and survey origin. Bold indicates significant at 5% level. Predicted probability of owning at t+1 London 0

0.2 0.4 0.6 0.8 1 Blackburn M, no child M, child F, no child F, child M, no child M, child F, no child Previous housing position Homeowner Social tenant Private tenant

F, child Predicted probability of social tenancy at t+1 London 0 0.2 0.4 0.6 0.8 1 Blackburn M, no child M, child F, no child F, child M, no child M, child

F, no child Previous housing position Homeowner Social tenant Private tenant F, child Predicted probability of private tenancy London 0 0.2 0.4 0.6 0.8 1 Blackburn M, no child M, child

F, no child F, child M, no child M, child F, no child Previous housing position Homeowner Social tenant Private tenant F, child Initial conclusions 1. Separation a demographic risk with housing consequences Reduced homeownership, increased renting/parents/sharing 2.Gendered impacts, especially if children present 3.Relatively minor role of local housing geography Slightly reduced post-split homeownership in costly HMAs 4.Next step: Two-stage models

Two step models Relational variables Housing contract status Exit decision Move out Stay Destination selection Owning Social Private rent rent Opportunity structure (HMAs) Parental home/share Acknowledgements Rory Coulters contribution to this research is supported by an Economic and Social Research Council Future Research Leaders award [ES/L009498/1]. Financial support from the Isaac Newton Trust is also gratefully acknowledged. Michael Thomas and Clara Mulders work on this paper is part of the project Partner relationships, residential relocations and housing in the life course (PartnerLife). Principal investigators: Clara H. Mulder (University of

Groningen), Michael Wagner (University of Cologne) and Hill Kulu (University of St Andrews). PartnerLife is supported by a grant from the Netherlands Organisation for Scientific Research [NOW, grant number 464-13148], the Deutsche ForschungsGemeinschat [DFG, grant number WA1502/6-1] and the Economic and Social Research Council [ESRC, grant number ES/L0166X/1] in the Open Research Area Plus scheme. Understanding Society (UKHLS) is an initiative funded by the Economic and Social Research Council and various Government Departments, with scientific leadership by the Institute for Social and Economic Research, University of Essex, and survey delivery by NatCen Social Research and Kantar Public. The research data are distributed by the UK Data Service. The authors are solely responsible for all analyses and interpretations of the data. Census statistics are adapted from data from the Office for National Statistics licensed under the Open Government Licence v.3.0. We are grateful to Mike Coombes for supplying the HMA shapefiles used in this project. References Cooke, T. J., Mulder, C. H., & Thomas, M. (2016). Union dissolution and migration. Demographic Research, 34(26), pp. 741760. Coombes M., & Wymer, C. (2010) Geography of Housing Market Areas (HMAs) in England: Stage 2 Report from CURDS. Dewilde, C. (2008). Divorce and the housing movements of owner-occupiers: A European comparison. Housing Studies, 23(6), pp. 809832. Feijten, P., & van Ham, M. (2010). The Impact of Splitting Up and Divorce on Housing Careers in the UK. Housing Studies, 25(4), pp. 483507. Gotlib, I. H. & Wheaton, B. (1997). Trajectories and turning points over the life course: Concepts and themes, in I.H. Gotlib & B. Wheaton (Eds.) Stress and adversity over the life course: Trajectories and turning points. Cambridge: CUP. Herbers, D. J., Mulder, C. H., & Mdenes, J. A. (2014). Moving out of home ownership in later life: The influence of the family and housing careers. Housing Studies, 29(7), pp. 910936. Jenkins, S. P. (2009). Marital splits and income changes over the longer term, in: M. Brynin & J. Ermisch (Eds.), Changing Relationships, pp. 217236. Abingdon: Routledge. Appendix: Problem A: Family attrition Attribute at t 14%

enumerated (col % orof mean) Men couples Tracked at t Women lost completely t+1 Attrition Tracked Attrition 12% of interviewed cases (8% in BHPS, Brewer and Nandi 2014: 8) Age 51.0 sample Cannot know if split up71.6 UKHLS BHPS sample 18.8 EMB sample 9.6 Wave 1 19.6 Cohabiting

18.0 Lives with own child 53.8 Homeowner 78.7 London 11.2 Fully interviewed 81.0 White British 82.8 Low education (<=GCSE) 41.3 Personal income () 2420 48.6 71.9 12.7 15.4 32.0 21.1 55.9 69.0 16.3 66.2 73.8 46.1 2283 48.5 71.8

18.7 9.5 19.6 17.9 54.6 78.7 11.1 91.4 82.0 45.0 1436 46.0 72.0 12.7 15.3 31.9 21.0 57.0 68.9 16.2 80.8 75.0 50.4 1357 Problem B: Break up attrition Attrition also correlates with separation (2.3% couples separate/wave) By using both partners records we can identify cases where separation occurs but one partner is lost 641 of 977 separating men tracked (66%)

1070 of 1214 separating women tracked (88%) Equivalents 78% and 94% in BHPS (Brewer and Nandi, 2014: 9) Potential problem if loss is selective Modelling break up attrition (probit) Variable (measured at t) Age Survey origin (ref=UKHLS) BHPS EMB Wave (ref=1) 2 3 4 5 Cohabiting (ref=married) Lives with child (ref=no) Housing tenure (ref=ownership) Social rent Private rent In housing contract (ref=no) Constant McFadden's pseudo-r2 Men (coeff.) Women (coeff.) -0.001 -0.014+

-0.256 0.234 -0.346 -0.945* -0.692** -0.402+ -0.994*** -0.526* -0.475** 0.797*** 0.101 -0.350 -0.404 -0.358 -0.793*** -1.023*** 0.342+ 0.379+ -0.712*** 0.231 0.085 -0.083 -0.081 -0.950*** 0.914+ 0.097

Notes: ***=p<0.001 **=p<0.01 *=p<0.05 +=p<0.1 Insignificant controls not shown (London, education, employment, income) Implication Need to adjust models for selective dropout (Heckman?) Challenge= identifying movers! Work ongoing

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