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Proximity of Couples to Parents: Influences of Gender, Labor Market, and Family

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Demography

Abstract

We use household survey data from the UK to study how close middle-aged men and women in partnerships live to their parents and their partner’s parents. We find a slight tendency for couples to live closer to the woman’s parents than the man’s. This tendency is more pronounced among couples in which neither partner has a college degree and in which there is a child. In other respects, proximity to parents is gender-neutral, with the two partners having equal influence on intergenerational proximity. Better-educated couples live farther from their parents. And although certain family characteristics matter, intergenerational proximity is primarily driven by factors affecting mobility over long distances, which are mainly associated with the labor market, as opposed to gender or family circumstances.

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Notes

  1. If either set of parents is divorced, the situation becomes even more complex.

  2. Evidence for this is the negative impact of local friendship networks on longer-distance movement (Belot and Ermisch 2009).

  3. To study the dynamics of intergenerational proximity, we would need residence mobility data for both partners for up to 36 years (from ages 18 to 54).

  4. The associations between distance from parents and an individual’s education are consistently positive (see, e.g., Blaauboer et al. 2011; Chan and Ermisch forthcoming; Compton and Pollak 2013; Hank 2007; Løken et al. 2013; Shelton and Grundy 2000).

  5. See Ermisch and Pronzato (2008) for such effects on men’s child support payments in Britain; on bargaining power effects, see Basu (2006), Chiappori et al. (2002), Couprie (2007), Lundberg and Pollak (1996), Lundberg et al. (1997), and Rangel (2006).

  6. Further details of the survey are available online (http://www.understandingsociety.ac.uk).

  7. Coresidence with parents is not uncommon among younger respondents in Understanding Society. For example, Chan and Ermisch (forthcoming) showed that about 18 % of people aged 25–29 coreside with their parents, compared with 7 % for people aged 30–34.

  8. Ethnic minorities are oversampled in Understanding Society. All results presented are weighted to reflect the sampling design and nonresponse, using the weight variable a_indinus_xw.

  9. For the white, UK-born sample, the corresponding figures are 35 % and 28 %, respectively.

  10. Comparisons with the American data are inexact because of different age ranges (25 and older in the U.S. sample versus 31–54 for the UK sample) and different distant measures (miles in the U.S. sample versus traveling time in the UK sample). In the U.S. data, the median distance to the woman’s mother is 20 miles, compared with 25 miles for distance to the man’s mother (Compton and Pollak 2013: table 3).

  11. Chan and Ermisch (forthcoming: figure 1) showed that adult children aged 31–54 are much more likely to see their parent daily if they live within 15 minutes of each other (25 % versus 8 % for the 15–30 minute distance category). There is a sharp decline in daily and weekly contact as proximity decreases beyond 30 minutes traveling distance. The third (2011–2012) wave of Understanding Society indicates that adult children aged 31–54 are much more likely to give some form of regular or frequent in-kind help to their parents if they live within 15 minutes of each other than if they live 15–30 minutes apart: 63 % versus 50 %. They are also more likely to receive in-kind help from parents if they live within 15 minutes: 54 % versus 44 %.

  12. We acknowledge that coresidence is qualitatively different from living near but in a separate household (Compton and Pollak 2013); indeed, we demonstrated this to be the case in a previous study using individual data from the same source as used here (Chan and Ermisch forthcoming). But coresidence is too rare (less than 1 % of the couples) to be treated as a separate category in our analyses. Compton and Pollak (2013) also found small numbers coresiding in their couples’ sample.

  13. Not all choices are available to all couples. For example, if the two sets of parents live very close to each other, then X 3 and X 4 would not be possible.

  14. A woman’s higher share could also be interpreted as an indicator of higher labor market aspirations, which would encourage geographic mobility and thus locations farther from her parents. We recognize that woman’s share of household income may be an endogenous variable because it partly depends on location. The results are not affected by its exclusion from the models reported in this article.

  15. Using data from the 18 annual waves of the British Household Panel Survey, we find that among movers under the age of 30, the mean distance moved is 65 km for persons with a university degree, 44 km for persons with an intermediate level of education, and 21 km for those with lower-level qualifications. If these young movers are also single, the distances for the three education groups are 70 km, 52 km, and 22 km, respectively. Details are available from the authors on request. See Ermisch (2009), who showed that young people from richer homes move farther from their parents when they leave, particularly when they are single.

  16. In England, Wales, and Northern Ireland, GCSE refers to the “school-leaving” qualifications, typically gained by pupils at age 16; achieving A-levels, typically at age 18, is the qualification for university matriculation. Scotland has its own qualifications system, which has been converted to its equivalents for the rest of the UK in this analysis.

  17. In contrast to what we find here, Compton and Pollak (2013: table 5), using data from the National Survey of Families and Households, found that when the woman has a degree and the man does not, the percentage of couples who live near her mother is 5.8 percentage points higher compared with couples in which the educational difference is reversed (in their data, we define near as the mother living within 30 miles). In the UK data, the corresponding difference is –5.6 percentage points for the 15-minute near–far threshold and 0.3 percentage points for a 30-minute near–far threshold.

  18. Chan and Ermisch (forthcoming) showed very large differences between ethnic groups in intergenerational proximity, even after controlling for education and other covariates.

  19. If UK-born nonwhites are included in the analysis, N increases from 2,506 to 2,803. The main results of this article are not affected by whether nonwhites are included in the sample. Details are available from the authors on request.

  20. Generically, the model can be expressed in terms of a latent continuous variable. Let y jrc represent the latent travelling distance to parents for a partner in couple j. We assume that y jrc = wδ rr + (1 − w cc + e j . An assumption about the distribution of e j is needed, such as a logistic or standard normal distribution. With the logistic assumption and the near–far dichotomy, π rc is the probability that y jrc > 0, π rc = exp(wδ rr + (1 − w cc ) / [1 + exp(wδ rr + (1 − w cc )], which implies that log(π rc / (1 − π rc )) = wδ rr + (1 − w cc . Thus, the parameters δ kk  = log(π kk / (1 − π kk )), k = 1, 2, 3; that is, they are the logit coefficients along the diagonal. The latent variable formulation extends easily to ordered logit or probit models when there are more distance categories.

  21. We fit diagonal reference models with the R package gnm (Turner and Firth 2011). We have also used Stata to fit the same set of models using probit rather than the logit link function. The results we obtained are very similar to those reported here.

  22. The unconstrained model contains nine parameters, one for each log(π rc / (1 − π rc )), compared with four parameters in the diagonal reference model.

  23. We use the woman’s report of their parental status.

  24. This variable refers to whether either of the partners moved in the past five years.

  25. We cannot reject the parameter restrictions in Model 4 relative to Model 1 plus covariates, or Model 3 plus covariates. Details are available from the authors on request. In a bivariate probit model that allows the residual error terms in the two partners’ distance-to-parent equation to be correlated, the results are similar. The correlation between the errors is estimated to be .25. The conclusions are also similar when we estimate ordered probit and logit models using all seven categories of Table 1.

  26. Regarding distance to woman’s parents, the parameter of “move in the past five years” is marginally not significant with p = .06.

  27. For the X 3 versus X 2 contrast, the following parameters are significant at the 10 % level: woman experienced parental divorce by age 16 (p = .10), woman’s age (p = .07), and having moved in the past five years (p = .05). The same applies to the following parameters for the X 4 versus X 2 contrast: having a child (p = .06), man experienced parental divorce by age 16 (p = .06), and man’s age difference with his parents (p = .09).

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Acknowledgments

We are grateful to Heather Turner for helpful advice on the R gnm package. Early versions of this article were presented at seminars at Oxford and Barcelona, and at the 2014 annual conferences of the Population Association of America and the British Society for Population Studies. We thank the participants of these meetings and anonymous referees for helpful comments. Our research is supported by the Economic and Social Research Council’s Secondary Data Analysis Initiative, Phase 1, Award Number ES/K002902/1.

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Correspondence to Tak Wing Chan.

Appendix

Appendix

Table 9 Descriptive statistics (white, UK-born couples)

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Chan, T.W., Ermisch, J. Proximity of Couples to Parents: Influences of Gender, Labor Market, and Family. Demography 52, 379–399 (2015). https://doi.org/10.1007/s13524-015-0379-0

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