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Public transfers and marital dissolution

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Abstract

In this paper, we analyze determinants of marital dissolution, focusing on the alleged influences from public transfers, child allowance, and child support awards. We use a Norwegian panel of 2,806 couples with information on public and private transfers in cases of divorce. The sample was observed over a 5-year period, with the purpose of registering marital dissolution. We find that the level of transfers has a significantly positive effect on divorce probability and that the distribution of transfers in favor of the wife increases this probability. Our findings are consistent with noncooperative family models allowing for inefficient outcomes.

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Notes

  1. There is a substantial literature on how divorce, in turn, affects the (female) labour supply (e.g., Johnson and Skinner (1986, 1988), Haurin (1989), and Tanda (1994)).

  2. By efficiency we mean efficiency in the family. From a social point of view, following Lommerud (1997), specialization in home production due to gender discrimination in the labour market is not efficient, but for each family it may be efficient.

  3. For example, in unitary family models, decisions are modeled as though spouses are maximizing a common utility function subject to a single budget constraint. Among unitary models, we find Samuelson’s (1956) consensus model, Becker’s (1974, 1991) altruistic model, and Becker et al.’s (1977) common utility model for marriage and divorce. In Apps and Rees (1988) and Chiappori (1988, 1992), the spouses by assumption reach a Pareto-efficient allocation. Clearly, relative endowments between spouses do not influence divorce decisions in these models.

  4. There might be a counter-effect, however. If the welfare state reduces the number of marriages, the stability of the couples who still marry, in spite of reduced financial incentives, is probably increased.

  5. These are all based on US data. European contributions are remarkably scarce. There is a related literature on the drop in (female) income caused by marital splits (e.g., Jarvis and Jenkins 1999), but this research tends to treat the divorce as an exogenous event, instead of modelling its determinants.

  6. These are all based on US data. European contributions are remarkably scarce. There is a related literature on the drop in (female) income caused by marital splits (e.g., Jarvis and Jenkins 1999), but this research tends to treat the divorce as an exogenous event, instead of modelling its determinants.

  7. Jensen and Smith (1990), analysing the effects of unemployment on marital dissolution, also use data on married couples.

  8. The Ministry of Child and Family (1996, page 11).

  9. See Smith and Løderup (1991) for a detailed description of the relationship between parents and children in cases of divorce.

  10. Unfortunately, we do not observe actual custody arrangements in our data. However, we can identify custody status as persons without custody are recorded as having no children after divorce. By comparing pre- and postdivorce child status, we infer custody status as either custodian or noncustodian, but we cannot infer joint custody. Parents with joint custody usually change custody status every year to ensure that the governmental transfers are shared. This adds noise but not bias to our custody variable.

  11. According to national surveys, 4% of the divorced parents had shared custody in 1996 (Jensen and Clausen 1997; Sætre 2004).

  12. Our own calculations based on Table 5.3 in NOU (1998).

  13. In a representative survey of divorced parents in Norway in 2002, 11% of the custodial parents were fathers (Sætre 2004). In the cases that were brought to court in 1995, the custody decision was in favor of the father in 27% of the cases (NOU 1998).

  14. See Bratberg and Tjøtta (forthcoming 2006) for coinciding findings based on a larger sample.

  15. Note, however, the model in Lam (1988), where household public goods create incentives for positive assortative mating in wages which may offset the negative assortative mating from specialization. Also Narkosteen et al. (2004) find evidence for positive mating using premarriage earnings in Sweden.

  16. The common outcome is that the mother gets custody. However, in a substantial number of cases (13% in our data), the father is awarded custody. This may suggest that, prior to divorce, the parents are faced with genuine uncertainty regarding the custody decision. Alternatively, the couples may have more or less certain information on the decision, the variation being due to idiosyncratic factors that are known to the couple but unobserved by the researcher. For now, we assume uncertainty, but will return to the alternative assumption in Section 4.

  17. The hypothesis that relative endowments matter for family decisions is further supported by empirical evidence that consumption patterns in intact families depend on spouses’ relative incomes and total family income. See Phipps and Burton (1998), Hoddinott and Haddad (1995), and Lundberg et al. (1997).

  18. See Fella et al. (2004) and Wickelgren (2005) who allow for inefficient divorce decisions.

  19. Divorce law in general may also affect other parts of the divorce settlement, such as child support payments, parents’ time with the children and the well-being of a couple who remain married. In Flinn (2000), child support awards are focal points in the divorce negotiating process, and in his model, strengthened child support enforcement policy will weaken the custodian’s incentive to spend resources on the children. Del Boca and Ribero (2001), using a noncooperative model where child support and parents’ time with the child are outcomes of a negotiation process, demonstrate that a mandatory child support payment improves the welfare of the custodian, reduces the welfare of the noncustodian, and decreases the proportion of the noncustodian’s time spent with the children. Farmer and Tiefenthaler (2003) also model child support and time within a noncooperative model and argue that the parent might achieve Pareto improvements but that the children’s welfare may decline. Finally, Stevenson and Wolfers (2003), using the across state variation in timing of the introduction of unilateral divorce law, find a significant reduction in both domestic violence and women’s suicide rates after the introduction of the new law. This change to unilateral divorce law redistributes the dissolution rights from the spouse who wants to stay to the spouse who wants to leave.

  20. Given a 10% random sample of the working age population, it is possible to identify approximately 1% of the married couples in 1989 where the wives are less than 40 years of age. Unfortunately, KIRUT provides no information on cohabitation.

  21. Separated couples are counted as divorced.

  22. To represent such a heterogeneous group simply with a dummy indicator is not very sophisticated but it follows from our rather crude data on this matter. It turns out that inclusion or omission of this indicator does not alter the remaining coefficients in any significant way.

  23. All three variables refer to children living in the households (identified by family number). Hence, they may be biological and/or stepchildren, but there is no way to separate these in our data.

  24. While we have access to more recent income information (1989–1994), a major concern is that the income variables are as predetermined as possible. In the trade-off between precision and predeterminedness, we give priority to the latter. All incomes and transfers are deflated by the Norwegian Consumer Price Index, with 1995 as the base year.

  25. It may be the case, however, that custody is more of an open, undetermined question at the outset of the divorce process for couples in Norway relative to couples in most other countries. The female labour market participation is high. In the mid-1990s, more than two-thirds of the female population had joined the labour market (Statistics Norway 2005) and more than 50% of these were in full-time jobs (Statistics Norway 2000). Hence, the traditional specialization—with the husband working in the labour market and the wife at home taking care of the children—is less frequent in Norway. Our observable characteristics of the custodial vs noncustodial mothers point in the same direction: the noncustodial mothers have stronger labour market attachment than the custodial ones.

  26. See the last paragraph of Section 5 for further discussion.

  27. Note that we use the actual rules in force, and that the calculated amounts do not necessarily equal the realizations. Details are available from the authors upon request.

  28. Spouse index is omitted for ease of exposition.

  29. This is a common finding in the sociological literature; we will return to this point in Section 5.

  30. The fact that the correlation between the two possibilities can be positive and negative does not remove the endogeneity problem. It simply implies that the direction of the bias is unknown, a priori.

  31. The parameterization, and hence, the functional form, is different in the two equations and constitutes our identifying restrictions.

  32. Assuming the same labour market attachment before and after divorce, lone breadwinners in our sample receive on average NOK 43,700 in public divorce transfers, while couples where both work receive on average NOK 27,000. As families with one breadwinner also have lower family incomes, the ratio of transfers to income for this group (mean: 25%, median: 19%) is much higher than for couples where both are fully employed (mean and median: 10%).

  33. We have experimented with variables that account for fertility after the baseline (1989), but we decided, based on obvious endogeneity problems, not to include it in the final model.

  34. As we control for variation in the income differences between couples, variation in the family income can only come about by changing both spouses’ income in the same direction and by the same amount. Hence, the estimated coefficient represents level variation conditional on income differences being unaltered.

  35. This result gives partial support to Hoffman and Duncan (1995), who find a small and significantly positive effect on the probability of divorce, and to Moffitt (1990), who reports a positive effect, albeit insignificant at the 5% level.

  36. It should be added that there are few cases and small amounts involved when husbands are net receivers of transfers, making our attempts to quantify the effect more difficult.

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Acknowledgements

We would like to thank Arild Aakvik, Espen Bratberg, Gary Fournier, Shelly Lundberg, Jarle Møen, Alf Erling Risa, Steinar Vagstad, the editor Deborah Cobb-Clark, two anonymous referees, and seminar participants at the University of Bergen and the Humboldt University, Berlin, for helpful discussions and comments. Financial support from the Norwegian Ministry of Finance, the Norwegian Research Council programs “Family, Work and Welfare“ and “The Programme on Welfare Research” and the Central Bank of Norway is gratefully recognized. Data were provided by the Norwegian Social Science Data Service (NSD). Neither the financial sponsors nor NSD are responsible for the results and opinions presented in the paper.

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Authors and Affiliations

  1. Department of Economics, University of Bergen, Herman Fossg 6, N-5007, Bergen, Norway

    Sigve Tjøtta & Kjell Vaage

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  1. Sigve Tjøtta
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  2. Kjell Vaage
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Correspondence to Kjell Vaage.

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Responsible editor: Deborah Cobb–Clark

Appendix

Appendix

Table A1. Determinants for child custody. Probit estimates, marginal effect (%)

Dependent variable: The mother’s probability of receiving child custody.

 

Coeff

Std err

#Children

0.07

2.87

AgeYounges

−1.40**

0.55

Age Husb

0.27

0.56

Age Wife

−0.23

0.70

Breadw Husb

11.14**

4.07

Breadw Wife

0.45

5.23

Income Husb

−0.06**

0.03

Income Wife

0.02

0.04

  1. All variables are observed at the year of divorce
  2. N=206; pseudo R 2=0.155; observed probability=0.88; predicted probability=0.92; #Children and AgeYoungest measure number of children and age of youngest child, respectively. Age S is age of spouse S, S=(Husb(and), Wife). Breadw S is a dummy variable indicating which of the spouses is the main breadwinner (1 if he/she works more than the other; 0 if otherwise). Income S is earnings for spouse, S
  3. **Indicates significance at least at the 5% level

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Tjøtta, S., Vaage, K. Public transfers and marital dissolution. J Popul Econ 21, 419–437 (2008). https://doi.org/10.1007/s00148-006-0071-1

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