Selectivity of Bargaining and the Effect of Retirement on Labour Division in Italian Couples


Using Italian data on the Use of Time, in this study we analysed the influence of the bargaining process between partners on the allocation of intra-household labour after the retirement of the male partner. Adopting an appropriate procedure to identify the effect of women's bargaining power, we found that men’s propensity to retire increased if women had strong bargaining power in labour division. This implies an overstatement of the effect of a man’s retirement on the housework of a woman with higher bargaining power and, conversely, an understatement of the effect of the man’s retirement on the housework time of a woman with lower bargaining power. To correct this selectivity effect, we estimated the effect of a man's retirement on the paid and domestic work of both partners by comparing couples in which the woman had high bargaining power and couples in which the woman had low bargaining power.

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Dataset Used for This Research

Time Use Survey 2008–2009 provided by Istat (Italian National Institute of Statistics)) is available in the public domain by accessing to the link:


  1. 1.

    However, gender construction theories still take precedence in explaining the division of housework time after retirement also in other European countries, such as Germany (cf. Leopold and Skopek 2018).

  2. 2.

    The Time Use Survey 2008–2009 provided by Istat (Italian National Institute of Statistics)) is available in the public domain at:

  3. 3.

    Note that, over the last decade, Italian government progressively imposed stringent constraints on early retirement, making it difficult to derive an empirical support for the analysis here proposed from recent data.

  4. 4.

    These are the so-called Big Five traits, the most commonly used measures of personality to study the interface between Psychology and Economics (Borghans et al. 2008).

  5. 5.

    The nature of this contract, however, departs substantially from that of paid labour in the labour market, in which remuneration varies in proportion to the effort expended. In addition, unlike the labour-market rule, the dependent cannot easily change the employer (breadwinner).

  6. 6.

    The values of the standard normal distribution can be taken as a reference for the evaluation of the level of heterogeneity measured computing the HI statistics. If the HI statistic provides (positive or negative) values close to zero, this indicates a low level of heterogeneity. The opposite occurs with higher values (positive or negative) of the index.

  7. 7.

    The subjects in our sample were interviewed between Monday and Saturday.

  8. 8.

    Several studies suggest that a strong and positive association exists between religion and marital quality (Myers 2006) and between religion and life satisfaction (Snoep 2008; Swinyard et al. 2001). Moreover, through attendance of religious services the subject can build friendships and social networks (Lim and Putnam 2010). Also Mencarini and Sironi (2012) argue the positive effect of religion in building social networks. Lehrer (2004) and Snoep (2008) underline the positive effects of religion on physical and mental health.

  9. 9.

    In the period of the survey, the minimum of 58 years of retirement age was introduced.

  10. 10.

    Variables explaining eligibility have been introduced as exogenous regressors in the “Regression Discontinuity” approach to the estimation of the effect of retirement (cf. Battistin et al. 2009;; Ciani 2016; Jurado Guerrero and Naldini 1996; Stancanelli and Van Soest 2012). Using the Regression Discontinuity model, these variables serve to identify the separation point between the decision to remain in the workforce and the decision to retire.

  11. 11.

    Brines (1994) and Gupta (2007), inter alia, applied the Sørensen–McLanahan index to evaluate the relative contribution of the woman to housework tasks.

  12. 12.

    Lundberg et al. (2003), for instance, found that the retirement of the primary earner (usually the husband) reduces household consumption expenditures for couples and increases the bargaining weight of the wife (usually, more engaged in household domestic work).


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The authors are grateful for the comments received from the participants to the meeting of the Population Association of America (Chicago) and the Time Use Across the Life Course conference (University of Maryland). The authors thank two anonymous referees for their useful suggestions.

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Correspondence to Antonino Di Pino.

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Checking Robustness of Model Estimation

In this section we report the results of a robustness check on the estimates of our model. In particular, we evaluate how the estimated relationship between bargaining process and a man's retirement decision changes if we restrict the analysis to a subsample of couples with non-working women. The comparison with non-working women allows us to verify the robustness of our estimates with respect to the endogeneity of women’s retirement decisions. In Tables 11 and 12 we show the estimation results of the bargaining equation, estimated by applying the LPM regression alone (the GSEM-MIMIC procedure involves relevant convergence problems, unless several factors of the latent construct are drastically eliminated). In order to test the effect of the possible endogenous influence of the woman's decision to retire, we verified the extent to which the estimated parameters of the Retirement Equation changed as a consequence of reducing the sample to households with non-working women (the non-working condition excludes the possibility of choosing early retirement a priori) (Table 12).

Table 11 Estimation results of Woman’s satisfaction with housework division (LPM)
Table 12 Estimation results of retirement equation

The estimation results reported in Table 12 confirm that the sample restriction to couples with non-working women does not lead to relevant modifications in the sign and level of coefficients of covariates explaining the male partner's retirement decision. Note, however, that the bargaining correction coefficient is not significant if we impose the sample restriction. Applying matching procedure and computing ATT parameters, we found that the domestic work of non-working women decreased by 38.5 (SE = 11.42) minutes a day (− 38.51), while men’s domestic work increased by 77.2 (SE = 9.80) minutes a day. Compared to the results reported above in Table 8 for the full sample, the reduction of the woman’s domestic work, consequent to the man’s retirement, was found to be higher for non-working women. May this difference imply that the woman’s decision on whether or not to retire ended up mitigating or exacerbating the effect of the man’s retirement? A convincing answer to this question requires a more detailed investigation which, for reasons of space, cannot be carried out here.

Finally, proper balancing statistics are provided to test the extent to which the matching procedure reduces differences in covariate distribution among families which experienced the retirement of the male partner and those which did not. (Tables 13, 14, 15).

Table 13 Balancing score statistics difference between treated and controls, before and after matching
Table 14 Category of low women’s bargaining power: balancing score statistics—difference between treated and controls, before and after matching
Table 15 Category of high women’s bargaining power: Balancing score statistics—difference between treated and controls, before and after matching

Balancing Test Statistics on Matching

After performing the simple matching procedure, we checked the covariates conditioning the propensity score by testing the balance between treated and untreated cases before and after matching. In order to quantify the bias between the two sample units, we used the Absolute Standardized Difference in Covariate Means (Haviland et al. 2007), as a standardized mean difference between treatment and control units. The bias (as a percentage) was computed by dividing the absolute difference in means of the covariate between the treated group and the control group by the overall standard deviation, as shown by the following formula:

$$BIAS= \frac{\left|{\stackrel{-}{x}}_{T-} {\stackrel{-}{x}}_{C}\right|*100}{{S}_{x}}$$

where the denominator is the overall standard deviation \(S_{X} = \sqrt {\frac{{S_{T }^{2} + S_{C}^{2} }}{2}}.\)

The statistics (7) of BIAS in balancing, computed before and after matching, are presented in Tables 13, 14 and 15. In particular, we show the statistics regarding the matching procedures applied to the full sample, and separately, to the subsamples of women, respectively, with lower and higher bargaining power.

The second and the third columns of Tables 13, 14 and 15 contain the standardized bias of propensity scores and covariates, before and after matching, computed following formula (7). The fourth and the fifth columns show, for each covariate, the Student-t statistics computed on the difference of means between treated and untreated, before and after matching. In general, we found that balancing score statistics perform better when we consider the subsample of women with high bargaining power.

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Campolo, M.G., Di Pino, A. Selectivity of Bargaining and the Effect of Retirement on Labour Division in Italian Couples. J Fam Econ Iss 41, 639–657 (2020).

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  • Effects of retirement
  • Housework division between partners
  • Bargaining process
  • Matching