Gender bias in the spending of child benefits: evidence from a natural policy reform


We examine the causal relationship between child benefits and household spending on child and adult goods. In particular, we examine whether it matters if it is the husband or wife who controls this income transfer. We exploit the introduction of child benefits to families with at least four children. The law assigned the mother as the beneficiary but, when asked who collected the amount, one-third of beneficiary families reported the father as the recipient. We use the propensity score matching approach to assess the issue of possible self-selection of beneficiary families into answering who was the recipient parent and the results favour common support. We apply the difference-in-difference approach and find evidence in favour of a gender bias in the spending of child benefits. On average, after the reform, recipient families’ spending on child clothing, food and tobacco was significantly different from that of non-recipient families. Further analysis suggests that recipient families with the mother (father) in control of the amount spent more on child clothing and food (tobacco) relative to non-recipient families. The evidence has implications on the design of welfare programmes to benefit the children.

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Fig. 1


  1. 1.

    The existence of a labelling effect is consistent with individual psychological and behavioural anomalies, like narrow bracketing or mental accounting (Tversky and Kahnemann 1981).

  2. 2.

    Hines and Thaler (1995) provide a review of the literature on the flypaper hypothesis.

  3. 3.

    These models recognize that members of the household (i.e. husband and wife) may have different preferences due to gender-specific psychological and/or behavioural differences.

  4. 4.

    The data has been used by other empirical studies, including Lyssiotou (2008) to identify flexible equivalence scales that capture the distributional effects of inflation from two cross sections of FES data.

  5. 5.

    The additional instruments are chosen in the following way. First, we exploit the degree of correlation between the additional instruments and the endogenous regressor, conditional on the other covariates, and test for weak instruments. Second, we test the validity of the additional instruments by computing the Hansen’s statistic along with its probability under the null hypothesis that the overidentifying restrictions of the model are valid.

  6. 6.

    The difference in the effects of younger and older children on children’s, women’s and men’s clothing is most probably because the parents may have reported the expenditure on clothing for older children as adult clothing.

  7. 7.

    These effects capture differences in household size, the number and ages of the children, other demographics and the level of household expenditure.

  8. 8.

    Research on financial arrangements within families distinguishes between financial control and management. Control is taken to imply decision making while management is taken to imply implementation of these decisions. In couple households there is a significant association between control over household finances and more general power within the household (Volger and Pahl 1993).

  9. 9.

    These variables are known as distributional factors and affect the household members’ bargaining position but not preferences or the joint budget set. Their significance, in affecting household expenditure patterns, provides support for non-unitary models of household behaviour and the non-pooling of spouses’ incomes.

  10. 10.

    These are kernel density estimates. The choice of the bandwidth parameter does not affect the results regarding common support.


  1. Blow, L., Walker, I., & Zhu, Y. (2012). Who benefits from child benefit? Economic Inquiry, 50(1), 153–170.

    Article  Google Scholar 

  2. Braido, L. H. B., Olinto, P., & Perrone, H. (2012). Gender bias in intrahousehold allocation: Evidence from an unintentional experiment? The Review of Economics and Statistics, 94(2), 552–565.

    Article  Google Scholar 

  3. Browning, M., Bourguignon, F., Chiappori, P. A., & Lechene, V. (1994). Incomes and outcomes: A structural model of intrahousehold allocation. Journal of Political Economy, 102(6), 1067–1096.

    Article  Google Scholar 

  4. Chiappori, P. A., Fortin, B., & Lacroix, G. (2002). Marriage market, divorce legislation, and household labor supply. Journal of Political Economy, 110(1), 37–72.

    Article  Google Scholar 

  5. Edmonds, E. (2002). Reconsidering the labelling effects of child benefits: Evidence from a transitional economy. Economics Letters, 76(3), 303–309.

    Article  Google Scholar 

  6. Fisher, P. (2016). British tax credit simplification, the intra household distribution of income and family consumption. Oxford Economic Papers, 68(2), 444–464.

    Article  Google Scholar 

  7. Gregg, P., Waldfogel, J., & Washbrook, E. (2006). Family expenditures post-welfare reform in the UK: Are low-income families starting to catch up? Labour Economics, 13(6), 721–746.

    Article  Google Scholar 

  8. Heckman, J., LaLonde, R., & Smith, J. (1999). The economics and econometrics of active labor market programs. In O. Ashenfelter & D. Card (Eds.), Handbook of Labor Economics (Vol. 3, pp. 1865–2097). Amsterdam: North Holland.

    Google Scholar 

  9. Hines, J., & Thaler, R. H. (1995). The flypaper effect. Journal of Economic Perspectives, 9(4), 217–226.

    Article  Google Scholar 

  10. Hotchkiss, J. L. (2005). Do husbands and wives pool their resources? Further evidence. Journal of Human Resources, 40(2), 519–531.

    Article  Google Scholar 

  11. Jacoby, H. (2002). Is there an intrahousehold ‘flypaper effect’? Evidence from a school feeding programme. The Economic Journal, 112(476), 196–221.

    Article  Google Scholar 

  12. Keen, M. (1986). Zero expenditures and the estimation of engel curves. Journal of Applied Econometrics, 1(3), 277–286.

    Article  Google Scholar 

  13. Kooreman, P. (2000). The labeling effect of a child benefit system. American Economic Review, 90(3), 571–583.

    Article  Google Scholar 

  14. Lundberg, S., Pollak, R. A., & Wales, T. J. (1997). Do husbands and wives pool their resources? Evidence from the United Kingdom child benefit. Journal of Human Resources, 32(3), 463–80.

    Article  Google Scholar 

  15. Lyssiotou, P. (2008). Comparisons of poverty across periods: Significance of distributional effects of prices. Economics Letters, 99(1), 14–17.

    Article  Google Scholar 

  16. Lyssiotou, P. (2016). The impact of targeting policy on spouses’ demand for public goods, labor supplies and sharing rule. Empirical Economics,. doi:10.1007/s00181-016-1134-0.

    Google Scholar 

  17. Milligan, K., & Stabile, M. (2011). Do child tax benefits affect the well-being of children? Evidence from Canadian child benefit expansions. American Economic Journal: Economic Policy, 3(3), 175–205.

    Google Scholar 

  18. Phipps, S., & Burton, P. (1998). What’s mine is yours? The influence of male and female incomes on patterns of household expenditure. Economica, 65(260), 599–613.

    Article  Google Scholar 

  19. Thaler, R. H., & Sunstein, C. R. (2003). Libertarian paternalism. American Economic Review, 93(2), 175–179.

    Article  Google Scholar 

  20. Tversky, A., & Kahnemann, K. (1981). The framing of decisions and the psychology of choice. Science, 211(30), 453–458.

    Article  Google Scholar 

  21. Volger, C., & Pahl, T. (1993). Social and economic change and the organisation of money within marriage. Work, Employment and Society, 7(1), 71–95.

    Article  Google Scholar 

  22. Ward-Batts, J. (2008). Out of the wallet and into the purse: Using micro data to test income pooling. Journal of Human Resources, 43(2), 325–335.

    Article  Google Scholar 

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I am very grateful to the Editors-in-Chief, Prof. Ronald B. Davies and Prof. Kimberley Scharf, for their very valuable comments and suggestions. I would like to thank the University of Cyprus for financial support and the Department of Statistics and Research of Cyprus for making available the Family Expenditure Survey data. I am solely responsible for the interpretation of the data and all errors.

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Correspondence to Panayiota Lyssiotou.

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Lyssiotou, P. Gender bias in the spending of child benefits: evidence from a natural policy reform. Int Tax Public Finance 25, 1029–1070 (2018).

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  • Child benefits
  • Public policy
  • Household expenditure behaviour
  • Intrafamily allocation
  • Welfare
  • Recipient and labelling hypotheses

JEL Classification

  • I38
  • H31
  • J18
  • D1