The preceding brief constructed and tested an indicator of whether a young person stays at home or has left it. This brief considers the reasons for leaving home and their impact. Some of the argument in this brief is quite technical. Readers uninterested in technique are advised to read only the introduction and the summary and conclusions.


There are four main reasons why a young person may leave home:

  1. He or she may find a job.  The ideal indicator would be whether the person has ever been employed, but that information is not available in the 2015 General Household Survey, so the indicator used is whether the person was employed at the time of the survey.
  2. He or she may enter into a union (either marriage or cohabitation).  One may distinguish between young people who have never been in a union from the others, based on information in the 2015 GHS.
  3. He or she may lose both parents.  By ‘lost’ is meant that the parents are either known to be dead or it is not known whether the parents or dead or alive.  This is the case of the household leaving the young person, rather than the other way round, as discussed in the first brief.  An indicator of lostness can be constructed from the 2015 GHS.
  4. He or she may move without the household having moved at the same time.  GHS 2015 has no information on migration, but the 2016 Community Survey does.  An indicator can be constructed using the methods set out in migration briefs already published [1].  A move means a move across local authority boundaries.


Because information about reasons 1 to 3 are all found in the 2015 GHS, one may determine (a) if all reasons exist and (b) if any reason exists.  It would have been desirable to integrate reason 4 in the same way, but this is not possible since information on it is drawn from a different data set.

None of the first three reasons are decisive in determining whether a young person leaves home.  A young person may be employed and remain at home.  A young person who has ever married or cohabited may become single again and live at home or, more rarely, married and cohabiting people may remain at home.  Some of these young people may have been absent from home for a spell, but these departures are treated here as excursions.  A young person may have lost both parents, but may be living with grandparents or great grandparents. 

The analysis here is what demographers call a ‘period’ analysis.  It does not represent the experience of any actual cohort, but of a hypothetical cohort experiencing at successive ages the conditions in 2015 (or 2016 in the case of migration).


The analysis will be conducted using survival curves against age.  The survival curves are as follows:

  1. Proportion of young people not employed.
  2. Proportion of young people never in a union.
  3. Proportion of young people who have not lost both parents.
  4. Proportion of young people who have not moved.
  5. One minus the proportion of young people who are employed, in a union, and have lost both parents.  This is the “all” curve
  6. One minus the proportion of young people satisfying at least one of the following conditions: employed, in a union, have lost both parents.  This is the “any” curve.
  7. Proportion of young people staying at home.


Survival curves 1 to 4 for either gender are plotted in Figure 1, and survival curves 5 to 7 are plotted in Figure 2. 

Figure 1 displays the survival curve until each individual event occurs: employment, entry into union, loss of both parents and migration since the age of 15.   Figure 2 displays survival to the first event (excluding migration) as the “Any” curve, survival until all three events have occurred (the “All” curve), and survival at home until leaving (the “Stay” curve).  Figure 2 confirms the statement in the introduction that none of the three events are decisive in causing young people to leave home, since the “Any” curve lies below the “Stay” curve.

A further investigation involves the use of two conditional probabilities.  Given two states A and B, the conditional probability is defined as the probability that A occurs given that B occurs.  Essentially, the conditional probability ignores what happens if B does not occur.

The table in the Appendix, which sets out the relationship between events and whether young people have stayed at home or left, indicate that the state (excluding migration) most closely correlated with departure is whether the young person has ever been in a union.  It is clearly superior for women and as good as employment for men.  So the first conditional probability to be considered is the probability of having left, given that the person has ever been in a union.  This conditional probability is graphed along with the unconditional probability of having left in Figure 3.

The gaps between the conditional and unconditional probabilities indicate the influence of ever having been in a union on leaving.  The effect starts at a younger age for women and is stronger than the effect for men up to the late 20s. 

Finally, one may ask what the effect of employment is on being, or ever having been, in a union.  The relevant conditional probability is the probability of ever having been in a union given that the person is in employment.  Figure 4 sets out conditional and unconditional probabilities.

Figure 4 shows that employment improves the probability for men, but not for women. 

A couple of final points:

  1. The table in the Appendix shows that while one or two of the reasons for leaving are not decisive, satisfying all three conditions is decisive.
  2. The upward slope of the curves in Figure 3 show that age by itself increases the probability of leaving, over and above the reasons for leaving.


Summary and conclusions

The analytical findings can be summarized as follows:

  1. The conditions encouraging young people to leave households can be divided into two groups:
    1. Entry into employment, being or ever have been married or cohabiting, and loss of both parents.  These three variables are all derived from data in the 2015 General Household Survey and interactions between them can be observed.
    2. Migration, where the information has to be taken from a different source: the 2016 Community Survey.  Migration interacts with the other conditions, but we have no information on how.
  1. Employment has a positive influence on whether men are, or have been, in union, but no similar effect on women.  To put the point another way:  employment increases the marriageability of young men, but not of young women.
  2. Whether a young person is, or has been, in a union has a positive effect on the probability of leaving home.  This positive effect starts at younger ages among women and is stronger among women than among men up to their late 20s.
  3. Satisfaction of one or two elements of group (a) in Section 1 increase the probability of leaving home.  All young people satisfying all three of the conditions have left home.
  4. There is a pure age component of the probability of leaving home, over and above the influence of encouraging conditions.  Put simply, the older a young person gets, all other things being equal, the greater the probability that he or she has left home.

Charles Simkins
Head of Research





The relationship between events and staying or leaving








Not employed












Not employed












Never in union




Ever in union







Never in union




Ever in union





Parent(s) not lost




Both parents lost





All conditions not met




All conditions met





No condition met




Any condition met





[1] See Charles Simkins, What does the 2016 Community Survey tell us about internal migration? and What does the 2016 Community Survey tell us about immigration and emigration of the foreign born? both published on 12 April 2017