Abstract
How large are the economies of scale of living together? And how do partners share their resources? The first question is usually answered by equivalence scales which assume equal sharing of resources within the household. Recent evidence based on collective household models rejects this equal sharing assumption. This paper uses data on financial satisfaction to simultaneously estimate the sharing rule and the economies of scale in a collective household model. The estimates indicate substantial scale economies of living together. Furthermore, wives receive on average almost 50 % of household resources, but the estimated shares vary between 30 and 60 %. Female resource shares increase with the ratio of female to male wages. Consumption inequality is underestimated by 16 % if unequal sharing is ignored.
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Notes
Alternatively, there can also be an altruistic dictator who controls a larger share of the family income.
Alternative models include cooperative household models as proposed by McElroy and Horney (1981) or Manser and Brown (1980), who describe household behavior as result of a Nash-bargaining game, where the bargaining power depends on the emerging expenditure patterns on the options outside marriage. Non-cooperative household models describe household behavior as a non-cooperative game with no binding and enforceable contracts between the household members and resulting inefficiencies.
We test and cannot reject the linearity assumption in the empirical section.
BCL specify \(z_j={\mathbf A} (q^f_j+q^m_j)+a\), where \(z_j\) is an observable vector of household j’s consumption of n goods, \(q^f_j\) and \(q^m_j\) are unobservable vectors of private consumption of both spouses. A is an \(n\times n\) nonsingular matrix and a is a n-vector. This linear consumption technology nests familiar cases, e.g. the well-known Barten scales if A is diagonal and \(a = 0\). By contrast to BCL we can only identify an aggregate consumption technology, i.e. A is diagonal with identical elements A. Assuming the budget constraint holds with equality we have \(y_j=p'z_j=(p'{\mathbf A} q^f_j+p'{\mathbf A} q^m_j)\). Given the restriction on A this simplifies to \(A(x^f_j+x^m_j)=y_j\), and \(\tau =A^{-1}\).
We are also able to distinguish between single living individuals with and without a partner. As we show in Sect. 4, single living individuals with partner are equally satisfied with their financial situation as single living individuals without partner. There is, however, a difference in the life satisfaction between these two group. This finding indicates that financial satisfaction is not necessarily altered by having a partner and therefore a better measure for indirect utility.
See also www.swisspanel.ch.
Since not all necessary variables are available for the first wave in 1999, this wave is excluded from this study.
The data generation process was designed to mimic the theoretical model of Sect. 2. We generated a continuous latent utility which was split into 11 categories such that the empirical distribution of the ordinal responses was replicated.
For this reason, also using the original reported satisfaction level as dependent variable hardly affects the estimates of \(\gamma\) and \(\tau\).
We also tested a more flexible specification where the coefficient \(\beta\) is allowed to vary by gender. The coefficient of the interaction term of \(\beta\) and the gender dummy is not significant on a 5 % level. Furthermore, allowing \(\beta\) tol vary by gender has no effect on the parameters of the sharing rule.
As shown by Fernández et al. (2004), the growing presence of a new type of man-one raised by a working mother-contributes significantly to the increasing female labor supply over time. Hence, family attitudes and their intergenerational transmission played a quantitatively significant role in transforming women’s role in the economy.
Their overall measure \(R\) is defined as (equivalent expenditures/actual expenditures) \(-\)1; hence R is in the range 0.27–0.41 in their Table 4.
The structural parameters can be obtained from the reduced form parameters by a straightforward minimum distance step (c.f. their paper).
ACH denote the consumption technology \(A=1/\tau\) in their model
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Acknowledgments
This study has been realized using the data collected in the “Living in Switzerland” project, conducted by the Swiss Household Panel (SHP), which is based at the Swiss Foundation for Research in the Social Sciences FORS, University of Lausanne. The project is financed by the Swiss National Science Foundation. We thank Gabi Wanzenried, two anonymous referees, and participants at the EEA congress in Barcelona, the EALE meeting in Tallinn and the ESPE meeting in Essen for helpful comments. Since the previous version of the paper (IZA Discussion Papers 4327) was written a new release of the SHP data was published. All estimations are redone with this latest release.
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Bütikofer, A., Gerfin, M. The economies of scale of living together and how they are shared: estimates based on a collective household model. Rev Econ Household 15, 433–453 (2017). https://doi.org/10.1007/s11150-014-9255-8
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DOI: https://doi.org/10.1007/s11150-014-9255-8