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Does welfare reform affect fertility? Evidence from the UK


This paper provides evidence on the effect of welfare reform on fertility, focusing on UK reforms in 1999 that increased per-child spending by 50% in real terms. We use a difference-in-differences approach, exploiting the fact that the reforms were targeted at low-income households. The reforms were likely to differentially affect the fertility of women in couples and single women because of the opportunity cost effects of the welfare-to-work element. We find no increase in births among single women, but evidence to support an increase in births (by around 15%) among coupled women.

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  1. The reforms have been extensively documented elsewhere. For further details, see Brewer et al. (2006), Francesconi and van der Klaauw (2007), Gregg and Harkness (2003) and Leigh (2007).

  2. Alternatively, it has been argued that higher income is associated with demand for increased quality of children, implying a possible reduction in quantity demanded.

  3. The scale and pattern of the changes are similar for lone parent families.

  4. This discussion draws on Brewer and Browne (2006) and Brewer et al. (2006). We do not describe the further set of reforms that took place after April 2003: For further details, see Brewer (2003).

  5. The assessment was made on the basis of the couple’s joint earnings even in the case of cohabiting couples.

  6. There was no attempt to present these reforms as revenue neutral: annual expenditure on FC/WFTC almost doubled between 1998–1999 and 2000–2001, from £2.68 billion to £4.81 billion in constant 2002 prices, with a further increase by 2002 to £6.46 billion.

  7. Gregg et al. (2009) show that an important effect of WFTC was to mitigate the negative impact of moving into lone parenthood on employment and income.

  8. Including the increase in support with payments for childcare.

  9. For further discussion of DD methodology, see Blundell and Costa-Dias (2002) and Angrist and Pischke (2009).

  10. The minimum school leaving age was raised from 14 to 15 from 1944 and from 15 to 16 from 1973.

  11. We have replicated the analysis using a split based on household income and an interaction of household income and education. These alternative definitions of treatment and comparison groups produce stronger results, available on request.

  12. See Hills and Waldfogel (2004) for a summary.

  13. We choose end of June rather than end of July to allow for premature births.

  14. Further reforms were made to the system of child-contingent benefits from this time.

  15. It is not possible to do the analysis using official birth statistics because they do not contain information on education or income and, for unmarried or re-married women, on true birth parity.

  16. Where this is missing, we randomly allocate a date of birth given the age of the child and the date of interview. This is the case for all births in the FES sample and 16% of births in the FRS sample.

  17. Another issue that affects information on the number and ages of existing children at the start of the 12-month period (but not information on births during that period) is that older women may have had children who have now left home. We test the sensitivity of our results to restricting our sample to women aged 37 and under for whom this does not appear to be a problem.

  18. This is measured as the total number of children a woman would have over her (reproductive) lifetime if she experienced the age-specific birth rates in a particular year.

  19. The ethnicity information is fairly crude; we include indicators if the woman or her partner is Black, Chinese, Indian, Pakistani or other (non-White). Many of the recent births to women born outside the UK are to recent White immigrants from the eight EU accession countries (including Poland, Czech Republic, Latvia, Lithuania, Estonia, Hungary, Slovakia and Slovenia). However, this wave of immigration occurred after the end of our period of analysis (beginning in May 2004).

  20. The average estimated marginal effects from a probit regression are very similar, and these results are available on request.

  21. A full set of coefficients is given in Table 9 in the “Appendix”.

  22. One implication of this is that the reforms had an effect on the fertility decisions of households who were not (yet) receiving the benefits. However, McKay (2000, 2001) shows that there was a fairly high level of awareness of the new benefits even among those who were not receiving it, which may have come about as a result of the extensive television advertising and/or through word-of-mouth.

  23. This differs to the specification in Table 3, column 4 both because of the longer period (1990–2003 compared to 1995–2003) and because there are no controls for ethnicity. The effect of excluding the ethnicity variables in the 1995–2003 sample is to reduce the coefficient from 0.0130 (0.0066) to 0.0120 (0.0066).

  24. An alternative way of showing that there are no differential trends would be to test for placebo reforms in the pre-reform period. The effects of these placebo reforms—tested for each year of the pre-reform period—are not statistically significant.

  25. Wages, house prices and unemployment are identified by Ermisch (1988) as important determinants of fertility.


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This research was funded by the ESRC under its programme, Understanding Population Trends and Processes (RES-163-25-0018), and through the Centre for Microeconomic Analysis of Public Policy at IFS. Material from the Family Expenditure Survey, the Family Resources Survey and the General Household Survey was made available by the Office for National Statistics (ONS) through the UK Data Archive and has been used by permission of the Controller of HMSO. The authors would like to thank Richard Blundell, Hilary Hoynes, Karl Scholz, Frank Windmeijer and an anonymous referee as well as seminar participants at CMPO, IFS, ONS and the Ministry of Social Development, New Zealand for helpful comments and suggestions.

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Correspondence to Sarah dSmith.

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Table 8 Summary sample statistics
Table 9 Regression results, linear probability model
Fig. 3
figure 3

Estimated period total fertility

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Brewer, M., Ratcliffe, A. & dSmith, S. Does welfare reform affect fertility? Evidence from the UK. J Popul Econ 25, 245–266 (2012).

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  • Welfare reform
  • Fertility

JEL Classification

  • J13
  • J18
  • H53