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Multilevel Event History Analysis of the Formation and Outcomes of Cohabiting and Marital Partnerships Fiona Steele Centre for Multilevel Modelling University.

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Presentation on theme: "Multilevel Event History Analysis of the Formation and Outcomes of Cohabiting and Marital Partnerships Fiona Steele Centre for Multilevel Modelling University."— Presentation transcript:

1 Multilevel Event History Analysis of the Formation and Outcomes of Cohabiting and Marital Partnerships Fiona Steele Centre for Multilevel Modelling University of Bristol Based on research carried out under the ESRC RMP with Constantinos Kallis, Heather Joshi and Harvey Goldstein

2 2 Outline of talk Research questions Selection effects Scope of study and definitions of partnership transitions Methods: multilevel simultaneous equation modelling Data: British Cohort Study Findings

3 3 Research Questions: Overview Examine womens repartnering behaviour and how it is shaped by past partnership events What is the relationship between previous cohabitation/marriage and the timing of the formation and dissolution of subsequent partnerships?

4 4 Research Questions What are the effects on the timing of partnership formation and dissolution of … previous partnership experience –Are premarital cohabitors at higher risk of marital dissolution? –Does prior experience of marital breakdown deter remarriage? –Are 2 nd + partnerships at higher or lower risk of dissolution? pregnancy and the presence of children

5 5 The Role of Previous Partnership Experience on Subsequent Events: Selection Past partnership outcomes are likely to be endogenous w.r.t. the risk of subsequent events There may be time-invariant characteristics affecting the occurrence of events in the same or a related process throughout the study period –E.g. religious belief may influence the probability of cohabiting and the risk of marital dissolution –Not all of these variables will be observed Important to allow for unobserved heterogeneity when studying repeated events

6 6 Example of Selection Bias: Effect of Divorce on Subsequent Marital Dissolution Suppose there are time-invariant unobservables influencing an individuals dissolution risk in any marriage they form selection of individuals with high dissolution risk into remarriage if uncontrolled, 2 nd + marriages may appear to carry a higher risk of dissolution than 1 st marriages See Aassve et al. (2006) and Lillard et al. (1995)

7 7 Example of Selection Bias: Effect of Cohabitation on Subsequent Marital Dissolution Often observe increased dissolution risk among couples who lived together before marriage In US, Lillard et al. (1995) found that this was due to selection of women with a high risk of dissolution into cohabitation; and this selection was not captured by covariates No British study has allowed for selection on unobservables

8 8 The Effect of Current Fertility Status on Partnership Events: Selection Indicators of current fertility status are past outcomes of the fertility process which may be endogenous w.r.t. partnership events Timing of fertility and partnership events may be correlated due to time-invariant unobservables affecting both childbearing and partnership decisions –E.g. women with a high risk of marital dissolution tend also to have low odds of marital childbearing (Lillard & Waite, 1993) –This is a residual correlation, i.e. not explained by covariates –If uncontrolled, leads to biased estimate of effect of having children on dissolution risk

9 9 Study Overview Partnership transitions between ages 16 and 30 among women born in 1970 Consider all partnerships and distinguish between marriage and cohabitation Jointly model partnership formation and outcomes to allow for endogeneity of previous partnership experience Treat current fertility status as exogenous (based on previous research on 1958 and 1970 cohorts)

10 10 S Stay S M Dissolution Stay M M Formation Partnership Transitions (S=single, M=marriage, C=cohabitation) Outcomes S M FormationOutcomes Dissolution Stay C C M M (same partner) C

11 11 Episodes, States and Competing Risks An episode is a continuous period spent in the same partnership state. Denote by s ij the state (S,M,C) occupied in episode i of woman j, t ij the episode duration, and δ ij a censoring/event indicator. For s ij = M: δ ij = 0 for no event (censored), 1 for dissolution For transitions from states C and S we have competing risks: s ij = C: δ ij = 0 for no event, 1 for dissolution, 2 for marriage s ij = S: δ ij = 0 for no event, 1 for cohabitation, 2 for marriage

12 12 Discrete-time Data Structure From observed data (s ij, t ij, δ ij ) create the following for each time interval t: For s ij = M : a binary response y ij (t) =0 for t < t ij and δ ij for t = t ij. For s ij = C or S: two binary responses { } coded 0 for t < t ij and value at t=t ij determined by s ij and δ ij E.g. if s ij = C = 1 if dissolution and 0 if marry or censored = 1 if marry and 0 if dissolution or censored

13 13 Example of Data Structure

14 14 Hazard Functions

15 15 Multilevel Simultaneous Equation Model

16 16 Estimation Model can be framed as a multilevel binary response model, and estimated in standard software Stack binary responses into a single response vector and, for s ij =S or C, define 2 dummy variables for responses Define another 3 dummy variables for state Allow coefficients of 5 dummies to vary randomly across women to define random effects Interact dummies with covariates

17 17 Example of Data Structure for Estimation

18 18 Data 1970 British birth cohort (BCS70): –Partnership (living together for >1 month) and birth histories collected retrospectively at age 30 –Covariates from childhood and adulthood Analysis sample: n=5495 women; n=15032 partnership episodes (48% single, 32% cohabitation, 20% marriage)

19 19 Explanatory Variables (Exact specification varies by type of transition) Current and previous partnerships: age, previously married/cohabited, current duration in state Current fertility status (TV): pregnant, presence of children by age and relationship to current partner Education (TV): current enrolment, no. post-16 years Family background: region of residence at birth, social class at birth, family disruption

20 20 Summary of Transitions by Age 30 (all % based on total sample, n=5495) 13% still unpartnered 53% had married 72% had cohabited 70% had only 1 partner –46% C+M, 20% M only, 34% C only 17% had >1 partner

21 21 Years to Partnership Transitions

22 22 Selected Random Effect Correlations Women with high (low) hazard of partnership formation tend also to have high (low) hazard of marital dissolution. i.e. fast formation associated with high risk of dissolution.

23 23 Effects of Previous Partnership Experience: Partnership Formation (Estimated coefficients and standard errors)

24 24 Effects of Previous Partnership Experience: Outcomes of Cohabitation ( Estimated coefficients and standard errors)

25 25 Effects of Previous Partnership Experience: Marital Separation ( Estimated coefficients and standard errors)

26 26 Summary of Effects of Previous Partnership Experience Among cohabitors, the never-married are more likely to marry than the previously married No effect of previous partnership breakdown on the stability of later partnerships No effect of premarital cohabitation on the risk of marital dissolution

27 27 Summary of Effects of Current Fertility Status Pregnancy hastens cohabitation and marriage among single women, and transition from cohabitation to marriage Marriage rate lower among cohabitors with a young child (selection?) Presence of an older child fathered by a previous partner inhibits marriage Stabilising effect of pregnancy and children by current partner on cohabitation and marriage

28 28 Conclusions Findings on effects of presence of children on partnership outcomes are similar for 1958 and 1970 cohorts Allowing for selection on time-invariant unobservables is important when assessing the role of previous partnership experience on subsequent transitions Important to distinguish between cohabitation and marriage

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